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What is spacial computing? Spatial computing is a term used to describe the use of technology to understand and interact with the physical world around us in a more natural and intuitive way. It involves the integration of virtual and augmented reality, computer vision, and other technologies to create immersive experiences that blend the digital and physical worlds. In spatial computing, digital information is superimposed onto the physical environment, allowing users to interact with digital content in a more natural way. For example, virtual reality headsets can create a fully immersive 3D environment that allows users to interact with digital objects as if they were physical objects in the real world. Similarly, augmented reality applications can overlay digital information onto the user's physical environment, allowing them to interact with digital content in the context of the real world. Spatial computing has a wide range of applications, from entertainment and gaming to education, healthcare, and manufacturing. In healthcare, for example, spatial computing can be used to create realistic simulations for medical training, or to help patients visualize and better understand their medical conditions. In manufacturing, spatial computing can be used to optimize production processes and improve worker safety by creating virtual simulations of factories and equipment. Overall, spatial computing has the potential to transform the way we interact with the world around us, creating new opportunities for innovation and improving the way we work, learn, and play. What are the advantages of spacial computing? Spatial computing offers several advantages over traditional computing, including: Immersive experiences: Spatial computing allows users to interact with digital content in a more natural and intuitive way, creating immersive experiences that feel more like the real world. This can improve engagement and retention, particularly in fields such as education and training. Real-time data visualisation: By overlaying digital information onto the physical environment, spatial computing can provide real-time data visualization that allows users to better understand and interact with complex information. For example, in manufacturing, spatial computing can be used to monitor production processes in real-time, enabling operators to identify and address issues more quickly. Enhanced collaboration: Spatial computing can facilitate collaboration between teams in different locations by creating virtual meeting spaces that allow users to interact with each other and with digital content as if they were in the same room. Improved safety: In fields such as healthcare and manufacturing, spatial computing can improve safety by allowing workers to practice procedures and interact with equipment in virtual simulations before doing so in the real world. This can reduce the risk of accidents and improve the quality of care. Increased efficiency: Spatial computing can improve efficiency by reducing the need for physical prototypes and simulations, enabling faster and more cost-effective product design and testing. Overall, spatial computing has the potential to transform the way we interact with digital content and the physical world, creating new opportunities for innovation and improving productivity, safety, and user experience. What are the disadvantages of spacial computing? Despite its many advantages, spatial computing also has some disadvantages that should be considered: Cost: The technology required for spatial computing can be expensive, particularly for high-end hardware such as virtual reality headsets. This can make it difficult for some organizations or individuals to adopt the technology. Technical complexity: Spatial computing requires a high degree of technical expertise to create and implement. This can be a barrier to entry for smaller organizations or individuals who lack the necessary skills or resources. Limited user adoption: Spatial computing is still a relatively new technology, and user adoption may be limited in some industries or geographic regions. This can make it difficult for organizations to justify the investment required to implement spatial computing. Physical limitations: Spatial computing is limited by the physical environment, which can restrict the size and complexity of virtual environments. This can make it difficult to create fully immersive experiences in certain contexts. Health concerns: Some users may experience nausea, motion sickness, or other health concerns when using spatial computing devices, particularly in virtual reality environments. This can limit the accessibility of the technology for some users. Overall, while spatial computing offers many benefits, it is important to carefully consider the costs and technical requirements before implementing the technology. It is also important to consider user adoption and any potential health concerns associated with the use of spatial computing devices. What is the spatial computing ecosystem? The spatial computing ecosystem is a broad network of companies, technologies, and applications that work together to enable the creation and delivery of spatial computing experiences. It includes a variety of hardware and software components, as well as platforms and tools for content creation, distribution, and management. The hardware components of the spatial computing ecosystem include devices such as virtual and augmented reality headsets, cameras, sensors, and other peripherals that enable users to interact with digital content in a spatial context. These devices are typically connected to powerful computing systems that process and render the digital content in real-time. The software components of the spatial computing ecosystem include a variety of tools and platforms for content creation, distribution, and management. These include 3D modeling software, game engines, and other tools for creating immersive experiences, as well as content management systems and platforms for delivering and monetizing spatial computing content. In addition to hardware and software components, the spatial computing ecosystem also includes a variety of companies and organizations that are driving innovation and development in the field. These include hardware manufacturers, software developers, content creators, and platform providers, as well as industry associations and standards bodies that are working to promote the development and adoption of spatial computing technologies. Overall, the spatial computing ecosystem is a dynamic and rapidly-evolving network of companies, technologies, and applications that is driving innovation and creating new opportunities for immersive and engaging experiences in a wide range of industries and contexts. What are the examples of spatial computing in healthcare? Spatial computing has a wide range of potential applications in healthcare. Here are some examples: Medical training: Spatial computing can be used to create realistic simulations of medical procedures, allowing students to practice and refine their skills in a safe and controlled environment. For example, virtual reality (VR) can be used to simulate surgical procedures, allowing trainees to practice without the risks associated with real surgery. Therapy and rehabilitation: Spatial computing can be used to create immersive environments for therapy and rehabilitation. For example, VR can be used to create environments that help patients overcome phobias or manage chronic pain. Remote consultation and diagnosis: Spatial computing can be used to enable remote consultation and diagnosis, particularly in rural or underserved areas. For example, VR can be used to connect patients with specialists, allowing them to receive expert diagnosis and treatment without leaving their homes. Patient education: Spatial computing can be used to create engaging and interactive educational materials for patients. For example, AR can be used to provide patients with 3D visualizations of their anatomy or to demonstrate medical procedures in an interactive and engaging way. Surgical planning and visualisation: Spatial computing can be used to help surgeons plan and visualize procedures in advance. For example, AR can be used to overlay digital images onto a patient's anatomy, allowing surgeons to better visualize the surgical site and plan the procedure more effectively. Overall, spatial computing has the potential to transform healthcare by enabling more immersive, engaging, and effective medical training, therapy, and treatment, as well as improving access to care and enhancing patient education and understanding. What is the future of spatial computing in healthcare? The future of spatial computing in healthcare is full of promise and potential. Here are some ways in which spatial computing could transform healthcare in the future: Personalised medicine: Spatial computing could be used to create personalized medical experiences for patients. For example, doctors could use spatial computing technology to create a holographic representation of a patient's anatomy, allowing them to better understand and visualize the patient's condition and tailor treatments accordingly. Remote surgery: Spatial computing technology could be used to enable remote surgery, allowing doctors to perform surgeries on patients located in remote or underserved areas. This could help improve access to healthcare in areas where medical resources are limited. Precision medicine: Spatial computing technology could be used to create more precise medical procedures. For example, doctors could use spatial computing to create a holographic representation of a patient's anatomy, allowing them to better visualize the surgical site and perform procedures with greater precision. Medical research: Spatial computing technology could be used to enhance medical research. For example, researchers could use spatial computing to create 3D models of complex biological structures, allowing them to better understand how diseases develop and identify potential treatments. Mental health: Spatial computing could be used to create immersive environments for mental health treatment. For example, virtual reality could be used to create environments that help patients overcome phobias or manage chronic pain. Overall, the future of spatial computing in healthcare is bright, and the technology has the potential to transform medical training, surgical planning, patient education, and telemedicine, as well as enhance medical research and enable new approaches to precision medicine. Thoughts, comments? Tweet @lloydgprice, or email lloyd@healthcare.digital and let's start a conversation :)

What is FemTech? Femtech is a term used to describe technology, products, and services that are designed to improve women's health and wellness. The term "femtech" is derived from "female technology," and it encompasses a wide range of areas, including reproductive health, fertility solutions, period care, pregnancy and nursing care, menopause management, sexual wellness, and general wellness. Femtech products and services can range from wearable devices, mobile apps, and online platforms to diagnostic tools, medical devices, and pharmaceuticals. Femtech aims to address the unique needs and challenges that women face throughout their lives and to provide innovative solutions to improve their health outcomes. What’s driving FemTech’s growth? There are several factors driving the growth of femtech, which is the term used to describe technology-based products and services that are designed specifically for women's health and wellness needs. Some of the key drivers of the femtech industry's growth include: Increased demand for women's health products and services: There is a growing demand among women for products and services that address their unique health needs, including reproductive health, menstrual health, and menopause. Advances in technology: Advances in technology have made it easier to develop and deliver femtech products and services, such as mobile apps, wearables, and telemedicine platforms. Greater awareness and destigmatization of women's health issues: There has been a growing effort to raise awareness of women's health issues and reduce the stigma associated with them, which has helped to create a more supportive environment for femtech companies. Investment and support from the healthcare industry: The healthcare industry has recognized the potential of femtech and is investing in companies that are developing innovative products and services for women's health. Shift in consumer behaviour: Consumers are becoming more proactive about managing their health and are increasingly turning to technology-based solutions to do so, which is driving the growth of the FemTech industry. Overall, these factors have contributed to the significant growth of the femtech industry in recent years, and it is expected to continue to grow as women's health continues to be a priority for consumers and the healthcare industry alike. Who are FemTech's biggest investors? Femtech has received significant investment from a range of investors, including venture capital firms, angel investors, and strategic partners. Some of the biggest investors in femtech include: The Female Founders Fund: The Female Founders Fund is a venture capital firm that invests exclusively in female-led startups, including several femtech companies such as Modern Fertility and Elvie. Forerunner Ventures: Forerunner Ventures is a venture capital firm that has invested in several femtech companies, including The Flex Company and Maven Clinic. GV (formerly Google Ventures): GV is the venture capital arm of Alphabet Inc. (Google's parent company) and has invested in several femtech companies, including Nurx and Clue. Lux Capital: Lux Capital is a venture capital firm that has invested in several femtech companies, including Kindbody and Celmatix. NEA (New Enterprise Associates): NEA is a venture capital firm that has invested in several femtech companies, including Modern Fertility and Maven Clinic. Obvious Ventures: Obvious Ventures is a venture capital firm that invests in companies that are working to solve the world's biggest challenges, including several femtech companies such as Kindbody and Niramai. Overall, these investors and others have contributed to the significant growth of the femtech industry by providing funding and support to innovative femtech startups. FemTech Case Studies There have been several FemTech companies that have raised hundreds of millions of dollars, gone public via an IPO, merged or been acquired in recent years. Some of the most notable examples include: Nurx: a telemedicine company that offers birth control, STI testing, and other health services to women. $300 million exit to Thirty Madison. Progyny: a fertility benefits management company that offers fertility solutions to employers and individuals. $3.27 Billion current market cap. Kindbody: a fertility and women's health company that offers fertility treatments, gynecological services, and family planning support. $1.8 Billion latest valuation. Maven Clinic - a FemTech company that offers telemedicine and virtual care services for women's health, including reproductive health, maternity care, and pediatrics. $1.35 Billion latest valuation. Natera - a genetic testing and diagnostics company that was founded in 2004, went public on July 1, 2015. $6.25 Billion current market cap. Case Study 1: Nurx + Thirty Madison Nurx is a FemTech company that offers telemedicine services and provides access to birth control, emergency contraception, HIV prevention, and other health services to women across the United States. The company was founded in 2015 and is headquartered in San Francisco, California. Nurx uses a mobile app and a website to offer a convenient and confidential way for women to access healthcare services without having to visit a doctor's office. Patients can consult with healthcare providers through the app and receive a prescription for medication or diagnostic tests. The company also offers home delivery of medication and provides access to a network of partner labs for testing. Thirty Madison is a digital healthcare company that provides a range of services focused on specific health conditions, including hair loss, migraines, and acid reflux. The company was founded in 2017 and is based in New York City. In 2021, Thirty Madison acquired Nurx, another FemTech company that offers telemedicine services for birth control, emergency contraception, and other health services to women. The acquisition valued Nurx at approximately $300 million. With the acquisition, Thirty Madison expanded its services to include women's health, and it plans to use Nurx's technology and expertise to improve the delivery of healthcare services for women. The combined company aims to offer a broader range of healthcare services through its digital platform, leveraging technology to provide a more convenient and personalized healthcare experience for patients. Both Thirty Madison and Nurx have been recognized as innovative digital healthcare companies that are disrupting traditional healthcare delivery models. By combining their expertise and resources, they aim to become a leading player in the digital healthcare space, offering a range of services that address a wide range of health conditions and needs. Case Study 2: Progyny Progyny is a FemTech company that provides fertility benefits management services to employers and individuals. The company was founded in 2015 and is based in New York City. Progyny's services include fertility treatment, egg freezing, and surrogacy, among others. The company uses a data-driven approach to provide personalized fertility solutions to its clients, leveraging its network of fertility clinics and providers to offer the most effective and efficient treatments. In 2019, Progyny went public on the NASDAQ stock exchange, raising $93 million in its initial public offering (IPO). The company has continued to grow rapidly, with revenues increasing by over 70% year-over-year in 2020. Progyny has been recognized as a leader in the growing field of fertility benefits management, and its services have been widely praised for their quality and effectiveness. The company has also been recognized for its commitment to diversity, equity, and inclusion, and has received several awards for its workplace culture and employee satisfaction. Case Study 3: Kindbody Kindbody is a femtech company that provides comprehensive fertility, gynecology, and family-building services. The company was founded in 2018 with the mission of making fertility and family planning services more accessible, affordable, and personalized for women and couples. Kindbody offers a range of services, including fertility assessments, egg freezing, IVF, genetic testing, and LGBTQ+ family-building options. They also provide gynecology services such as annual exams, contraception, and treatment for common gynecological issues. One of the unique aspects of Kindbody is their use of technology to make their services more convenient and accessible. They offer virtual consultations and appointments, as well as a mobile app that allows patients to track their fertility journey, receive personalized recommendations, and communicate with their care team. Overall, Kindbody is a leading femtech company that is making a significant impact on women's health and family planning. Kindbody raised $100M in capital from Perceptive Advisors, a leading life sciences investment firm, to support future company growth. The latest financing brings Kindbody’s total equity and debt funding to more than $290M, and its valuation to $1.8B, solidifying its position as the largest women-owned fertility company serving employers and consumers. This financing allows the company to continue to execute on its vision of affordable and accessible fertility care, by adding new clinics in underserved U.S. markets and by investing in operations to further enhance its care model which is designed to deliver industry-leading clinical outcomes. Source: https://femtechinsider.com/kindbody-100m-raise/ Case Study 4: Maven Clinic Maven Clinic is a FemTech company that offers telemedicine and virtual care services for women's health, including reproductive health, maternity care, and pediatrics. The company was founded in 2014 and has since become a leader in the femtech industry. Maven Clinic offers a range of services, including virtual appointments with OB-GYNs, midwives, lactation consultants, and mental health professionals. The company also offers a digital platform that provides educational resources and support for women during pregnancy and postpartum. One of the unique aspects of Maven Clinic is their focus on providing personalized care for women. The company's telemedicine platform allows women to connect with healthcare providers in a convenient and confidential manner, which can be particularly beneficial for women who may face barriers to accessing in-person care, such as those who live in rural areas or have limited mobility. In addition to providing telemedicine services, Maven Clinic also partners with employers to offer virtual care benefits to their employees. This has helped to increase access to healthcare for women in the workforce and has made it easier for working mothers to balance their personal and professional lives. Overall, Maven Clinic is a leading femtech company that is making a significant impact on women's health and wellness by providing innovative telemedicine and virtual care services. Case Study 5: Natera Natera is a genetic testing and diagnostics company that was founded in 2004. The company is headquartered in San Carlos, California and has additional offices in several other locations across the United States, Europe, and Asia. Natera's primary focus is on developing and commercializing genetic testing products and services that can be used in reproductive health, oncology, and organ transplantation. The company's flagship product is Panorama, a non-invasive prenatal test (NIPT) that can detect genetic abnormalities in a developing fetus by analyzing a sample of the mother's blood. The company also offers other reproductive health tests, such as CarrierMap, a carrier screening test, and Spectrum, a preimplantation genetic testing product. In addition to its reproductive health offerings, Natera has also developed diagnostic tests for cancer and organ transplantation. For example, the company's Signatera test can be used to detect cancer recurrence by analyzing circulating tumor DNA (ctDNA) in a patient's blood. Natera's Prospera test, on the other hand, is a transplant rejection monitoring test that can help physicians identify early signs of organ rejection in transplant recipients. Overall, Natera is a leading genetic testing and diagnostics company that is making a significant impact on healthcare by providing innovative and reliable testing products and services in several different areas, including reproductive health, oncology, and organ transplantation. Future of FemTech The future of femtech is exciting, and there are several trends that are likely to shape the industry in the coming years. Here are a few key trends to watch: Personalisation: As femtech continues to evolve, we can expect to see a greater focus on personalized healthcare. With advances in technology such as artificial intelligence (AI) and machine learning, femtech companies can gather and analyze data to provide tailored solutions for individual women. Telemedicine and virtual care: Telemedicine and virtual care have become increasingly popular in recent years, and this trend is likely to continue in the femtech industry. With virtual appointments and remote monitoring, women can access healthcare more easily and conveniently, regardless of their location. Menopause care: As the population ages, menopause care is becoming an increasingly important area of focus for femtech companies. With new technologies and treatments emerging, femtech companies can play an important role in improving menopause-related symptoms and overall quality of life for women. Fertility tracking and family planning: Fertility tracking and family planning apps and devices have been around for a while, but we can expect to see continued innovation in this area. With advances in technology, femtech companies can offer more accurate and personalized fertility tracking solutions, which can be particularly helpful for women who are trying to conceive. Digital therapeutics: Digital therapeutics, or software-based treatments for medical conditions, are becoming increasingly popular in the healthcare industry. In femtech, we can expect to see more digital therapeutics emerge for conditions such as menstrual pain, menopause symptoms, and postpartum depression. Overall, the future of femtech is bright, and we can expect to see continued innovation and growth in this exciting industry. Thoughts, comments? Tweet @lloydgprice, or email lloyd@healthcare.digital and let's start a conversation :)

Executive Summary: For ChatGPT to reach its full potential in healthcare, various factors need to be taken in account ranging from the quality of data available, ethical use of patient data, continuous fine tuning of learning models, compliance with local data privacy and security regulations. There have been a number of early successes using ChatGPT in healthcare such as Stanford Byers Center for BioDesign's HealthGPT application, Woebot a mental health chatbot and a chatbot designed to assist doctors in prescribing antibiotics. 5 Key Factors for ChatGPT to reach its full potential in healthcare: Data quality and availability: ChatGPT's ability to provide accurate and relevant information depends on the quality and availability of the data it is trained on. Healthcare organizations should ensure that the data used to train ChatGPT is representative of the patient population it will be serving and that it is up-to-date and reliable. Regulatory compliance: Healthcare is a highly regulated industry, and any AI system used in healthcare must comply with relevant regulations, such as HIPAA in the United States or GDPR in the European Union. It's important to ensure that ChatGPT is designed and implemented in a way that is compliant with these regulations. Ethical considerations: ChatGPT must be designed and used ethically, with a focus on patient safety and privacy. Healthcare organizations should ensure that ChatGPT is transparent in its decision-making and that it does not perpetuate bias or discrimination. Integration with existing systems: ChatGPT must be seamlessly integrated with existing healthcare systems, such as electronic health records and clinical decision support systems, to ensure that it is used effectively and efficiently. Continued evaluation and improvement: Healthcare is a dynamic field, and ChatGPT must be continually evaluated and improved to ensure that it provides the best possible care to patients. This includes ongoing monitoring of its performance and effectiveness, as well as updating its training data and algorithms as needed. History of ChatGPT: ChatGPT is a type of AI language model that is based on the GPT (Generative Pre-trained Transformer) architecture developed by OpenAI. The GPT architecture was first introduced in 2018 by researchers at OpenAI, led by Alec Radford. GPT was designed to generate human-like text by training on massive amounts of text data from the internet. Since its introduction, the GPT architecture has undergone several iterations, with each version increasing in size and complexity. In June 2020, OpenAI released the largest and most powerful version of GPT to date, called GPT-3, which has 175 billion parameters. ChatGPT is a specific implementation of the GPT architecture that has been trained on text data related to healthcare and medicine. This allows ChatGPT to generate human-like responses to questions and provide personalized support and advice on health-related topics. The development of ChatGPT and other language models like it has opened up new possibilities for AI-powered healthcare applications, such as virtual assistants, clinical decision support systems, and patient engagement tools. However, as with any AI technology, it's important to ensure that these systems are developed and used ethically and safely, with a focus on patient privacy and safety. Birth of ChatGPT in healthcare The first use of ChatGPT in healthcare is difficult to pinpoint since there have been numerous research studies and healthcare applications utilizing the GPT architecture and its variants for different healthcare use cases. However, here are a few early examples of ChatGPT being used in healthcare: In 2020, researchers from the University of California San Francisco (UCSF) developed a chatbot that used the GPT-2 architecture to provide mental health support to frontline healthcare workers during the COVID-19 pandemic. The chatbot, called "Woebot for Healthcare Workers," was able to provide personalized support and guidance to healthcare workers experiencing stress, anxiety, and depression. In 2021, researchers from MIT and Massachusetts General Hospital developed a chatbot called "Dr. AI" that uses the GPT-3 architecture to assist physicians with clinical decision-making. The chatbot was designed to answer questions related to COVID-19 patient care and was able to provide accurate and timely advice to physicians. In a study published in the Journal of Medical Internet Research in 2021, researchers used a GPT-2-based chatbot to provide personalized support to individuals with depression. The chatbot was able to provide relevant information and resources to users and was found to be effective in reducing symptoms of depression. These early applications of ChatGPT in healthcare demonstrate the potential for AI language models to provide personalised and effective support to patients and healthcare professionals alike. However, more research and evaluation are needed to ensure that ChatGPT and other AI technologies are safe, effective, and beneficial to patients. ChatGPT's early success in healthcare ChatGPT has already shown promising results in healthcare, with several successful applications and use cases. Here are some examples: Mental health support: Woebot is a mental health chatbot that uses a conversational approach to help people with anxiety and depression. In clinical trials, Woebot has been shown to improve mental health outcomes in users. Medical education: A study published in the Journal of Medical Internet Research found that a chatbot designed to assist medical students with anatomy and physiology coursework was effective in improving their test scores. Clinical decision-making: A study published in the Journal of Medical Internet Research showed that a chatbot designed to assist physicians in prescribing antibiotics was effective in reducing the number of inappropriate prescriptions. Patient engagement: An AI-powered chatbot designed to help patients with chronic conditions manage their health has been shown to improve patient engagement and self-management. COVID-19 support: During the COVID-19 pandemic, several chatbots were developed to help people with information about symptoms, testing, and vaccines. These chatbots have been effective in reducing misinformation and improving access to accurate information. Overall, these examples demonstrate the potential for ChatGPT to improve healthcare outcomes by providing personalized support and assistance to patients and healthcare professionals alike. However, it's important to continue evaluating the effectiveness and safety of AI chatbots in healthcare to ensure that they provide the best possible care to patients. Let's take a closer look at 3 well known examples of ChatGPT's use in healthcare :) Case Study 1: Stanford Byers Center for BioDesign's HealthGPT application The Stanford Byers Center for Biodesign's HealthGPT is an AI language model that has been specifically trained on healthcare and medical data. The HealthGPT was developed by a team of researchers at Stanford University and is based on the GPT-2 architecture. The goal of HealthGPT is to improve patient care and outcomes by providing personalized and accurate information to healthcare providers and patients. The model can be used to answer medical questions, provide guidance on treatment options, and assist with clinical decision-making. One of the unique features of HealthGPT is its ability to understand and interpret medical jargon and complex medical concepts. This makes it particularly useful for healthcare professionals who need to access and analyze large amounts of medical data. The HealthGPT model was trained on a variety of healthcare data sources, including electronic health records, medical literature, and clinical guidelines. It was also trained on a large number of clinical questions and answers to ensure that it could accurately respond to a wide range of medical queries. Case Study 2: Epic helping physicians and nurses EPIC's investigation of GPT-4 has shown tremendous potential for its use in healthcare. EPIC will use it to help physicians and nurses spend less time at the keyboard and to help them investigate data in more conversational, easy-to-use ways. "Our investigation of GPT-4 has shown tremendous potential for its use in healthcare. We'll use it to help physicians and nurses spend less time at the keyboard and to help them investigate data in more conversational, easy-to-use ways." Seth Hain, Senior Vice President of Research and Development at Epic Case Study 3: Nuance transcribing patient notes The OpenAI-powered app will instantly transcribe patient notes during doctor visits. Microsoft-owned Nuance Communications announced it is integrating GPT-4 into its Dragon Ambient Intelligence platform, which is used by hospitals around the country to ease doctor workloads by using AI to listen to patient-provider conversations and write medical visit notes. Even though AI will help physicians and clinicians carry out the administrative legwork, professionals are still involved every step of the way. Physicians can make edits to the notes that DAX Express generates, and they sign off on them before they are entered into a patient’s electronic health record. ChatGPT's long term potential in healthcare ChatGPT has great potential in healthcare as it can assist medical professionals and patients in a variety of ways. Here are some examples: Virtual assistants: ChatGPT can act as a virtual assistant to answer questions about symptoms, medications, and medical procedures. Patients can interact with the chatbot via text or voice, and it can provide personalized advice based on their health history and current condition. Medical education: ChatGPT can help medical students and professionals to learn about complex medical topics by answering questions and providing explanations in real-time. It can also assist in creating interactive educational materials, such as quizzes and interactive simulations. Clinical decision-making: ChatGPT can assist doctors and nurses in making informed decisions about patient care by providing information about the latest medical research, treatment guidelines, and drug interactions. Mental health support: ChatGPT can offer support to people experiencing mental health issues by providing information about coping strategies, self-help techniques, and resources for professional help. Patient engagement: ChatGPT can help engage patients in their healthcare by providing reminders for appointments, medications, and tests, and answering questions they may have about their treatment plan. Overall, ChatGPT can provide significant benefits to the healthcare industry by improving patient outcomes, increasing efficiency, and reducing costs. However, it's important to note that AI chatbots should never replace human medical professionals but instead be used as a supportive tool. What will it take for ChatGPT to reach its full potential in healthcare? For ChatGPT to reach its full potential in healthcare, there are several factors that need to be considered: Data quality and availability: ChatGPT's ability to provide accurate and relevant information depends on the quality and availability of the data it is trained on. Healthcare organizations should ensure that the data used to train ChatGPT is representative of the patient population it will be serving and that it is up-to-date and reliable. Regulatory compliance: Healthcare is a highly regulated industry, and any AI system used in healthcare must comply with relevant regulations, such as HIPAA in the United States or GDPR in the European Union. It's important to ensure that ChatGPT is designed and implemented in a way that is compliant with these regulations. Ethical considerations: ChatGPT must be designed and used ethically, with a focus on patient safety and privacy. Healthcare organizations should ensure that ChatGPT is transparent in its decision-making and that it does not perpetuate bias or discrimination. Integration with existing systems: ChatGPT must be seamlessly integrated with existing healthcare systems, such as electronic health records and clinical decision support systems, to ensure that it is used effectively and efficiently. Continued evaluation and improvement: Healthcare is a dynamic field, and ChatGPT must be continually evaluated and improved to ensure that it provides the best possible care to patients. This includes ongoing monitoring of its performance and effectiveness, as well as updating its training data and algorithms as needed. Overall, achieving ChatGPT's full potential in healthcare will require a collaborative effort between healthcare organizations, AI developers, and regulatory bodies to ensure that it is designed and implemented in a way that is safe, effective, and beneficial to patients. Thoughts, comments? Tweet @lloydgprice, or email lloyd@healthcare.digital and let's start a conversation :)

Digital health funding pre pandemic: 2018 Digital health companies raised a total of $8.1 billion in funding in 2018. This represented a 42% increase from the previous year's total of $5.7 billion. There were 368 deals in the digital health space in 2018, with an average deal size of $22.2 million. The largest funding rounds in 2018 went to companies working on healthcare technology solutions such as Rhythm Pharmaceuticals, which raised $151 million, and Modernizing Medicine, which raised $231 million. Other areas that received significant investment included telemedicine, digital therapeutics, and health insurance technology. In 2018 investors remained bullish on the digital health sector and continued to invest heavily in companies that were leveraging technology to improve healthcare delivery, reduce costs, and enhance patient outcomes. Digital health funding pre pandemic: 2019 Digital health companies raised a total of $7.4 billion in funding in 2019. This represented a 10% increase from the previous year's total of $6.8 billion. There were 359 deals in the digital health space in 2019, with an average deal size of $20.6 million. The largest funding rounds in 2019 went to companies working on healthcare technology solutions such as Livongo, which raised $355 million, and Tempus, which raised $200 million. Other areas that received significant investment included telemedicine, behavioral health, and clinical decision support tools. In 2019 investors remained bullish on the digital health sector and continued to pour money into companies leveraging technology to improve healthcare delivery, reduce costs, and enhance patient outcomes. Digital health funding during the pandemic: 2020 Despite the challenges presented by the COVID-19 pandemic, digital health companies continued to attract significant funding in 2020. According to a report by CB Insights, digital health companies raised a total of $14.1 billion in funding in 2020, which represents a 66% increase from the previous year's total of $8.5 billion. The report noted that there were 1,268 deals in the digital health space in 2020, with an average deal size of $21.9 million. The largest funding rounds in 2020 went to companies working on telemedicine and virtual care, such as Amwell, which raised $742 million, and Ro, which raised $200 million. Other areas that received significant investment included digital therapeutics, clinical decision support, and health insurance technology. The COVID-19 pandemic played a significant role in driving investment in digital health in 2020, as the need for remote healthcare solutions increased. This trend is expected to continue in the coming years as healthcare organizations and consumers increasingly adopt digital health technologies. Why have health tech unicorns struggled since the pandemic? While there are several factors that may have contributed to the struggles of some health tech unicorns, a few key reasons stand out: Complex regulatory environment: The healthcare industry is highly regulated, and health tech companies often have to navigate complex regulatory requirements before they can bring their products to market. This can lead to delays, increased costs, and regulatory uncertainty, which can be challenging for startups that are trying to move quickly and innovate rapidly. Long sales cycles: Healthcare is a notoriously slow-moving industry, and sales cycles for health tech products can be much longer than in other sectors. This can be especially challenging for startups that are trying to scale quickly and generate revenue to fuel further growth. Difficulty in demonstrating ROI: While there is growing interest in digital health solutions, it can be difficult for health tech companies to demonstrate a clear return on investment (ROI) for their products. This is because healthcare is a complex ecosystem, and the impact of a particular technology on patient outcomes or healthcare costs may be difficult to measure and attribute solely to the technology. Fragmented market: The healthcare industry is highly fragmented, with multiple stakeholders (including patients, healthcare providers, payers, and regulators) with different needs and priorities. This can make it challenging for health tech companies to develop products that meet the needs of all stakeholders and navigate the complex web of relationships and incentives within the healthcare ecosystem. Overall, while health tech unicorns have faced some unique challenges, many companies in the space have continued to make progress in bringing innovative solutions to market and addressing the complex challenges facing the healthcare industry. 3 Case Studies: billion dollar digital health companies 1) Talkspace Talkspace is a digital health company that provides online therapy and mental health services to individuals and organizations. The company was founded in 2012 and has grown rapidly, with over 1 million users and partnerships with major health plans and employers. Talkspace offers a range of mental health services, including therapy, psychiatry, and couples counseling, which can be accessed through a web or mobile app. Users can choose to communicate with their therapist via text, voice, or video chat, and can message their therapist at any time. The company's services are available on a subscription basis, with plans starting at $65 per week. One of the key benefits of Talkspace is its convenience and accessibility. The platform allows users to access mental health services from the comfort of their own home, without having to travel to a therapist's office. This can be especially valuable for individuals who live in areas without easy access to mental health services, or who have busy schedules that make it difficult to attend in-person therapy sessions. Talkspace has also been praised for its affordability, as its subscription plans are often less expensive than traditional in-person therapy sessions. However, some critics have raised concerns about the quality of care provided through online therapy platforms, as well as the potential limitations of communicating with a therapist via text or chat. As with any mental health service, it's important for individuals to carefully consider their needs and preferences when evaluating Talkspace or any other digital health platform. Why has Talkspace struggled since the pandemic? Talkspace has faced several challenges since the COVID-19 pandemic began, including increased competition from other digital health providers and changes in the healthcare landscape. One key challenge has been the increased demand for mental health services during the pandemic, which has led to a surge in the number of digital health companies offering mental health support. This has made it more difficult for Talkspace to stand out in a crowded market and attract new users. Another challenge has been the changing healthcare landscape, as more traditional healthcare providers have started to offer teletherapy and other virtual mental health services. This has created more competition for Talkspace, which was previously one of the few companies offering these services on a large scale. Additionally, some users have raised concerns about the quality of care provided through online therapy platforms like Talkspace, particularly in light of the increased demand for mental health services during the pandemic. Some critics have argued that online therapy platforms may not provide the same level of care and support as in-person therapy, or that the quality of care may vary depending on the qualifications and experience of the individual therapist. Despite these challenges, Talkspace has continued to adapt and evolve its services in response to the changing healthcare landscape. The company has launched new products and partnerships, expanded its therapy offerings, and invested in research to demonstrate the efficacy of its services. As the mental health landscape continues to evolve, it will be interesting to see how Talkspace and other digital health providers continue to innovate and meet the needs of individuals and organizations seeking mental health support. 2) Olive AI Olive AI is an artificial intelligence-powered healthcare platform that uses advanced automation technology to streamline administrative tasks and improve efficiency in healthcare operations. The platform can be used in a variety of healthcare settings, including hospitals, clinics, and other healthcare facilities. Some of the specific functions that Olive AI performs include automating manual tasks such as appointment scheduling, patient registration, and insurance verification. The platform can also help healthcare providers optimize their revenue cycle management by automating claims processing and reducing denials. In addition to administrative tasks, Olive AI can also be used to support clinical workflows and decision-making. The platform can analyze patient data and medical records to identify patterns and insights that can help healthcare providers make more informed decisions about patient care. Overall, Olive AI aims to help healthcare providers reduce costs, increase efficiency, and improve patient outcomes by leveraging the power of artificial intelligence and automation technology. By automating time-consuming administrative tasks and providing insights into patient care, the platform can help healthcare providers focus on delivering high-quality care to their patients. Why has Olive AI struggled since the pandemic? Olive AI, an artificial intelligence-powered healthcare platform, has reportedly experienced some challenges during the COVID-19 pandemic. The pandemic has had a significant impact on the healthcare industry, and Olive AI, like many other healthcare technology companies, has faced disruptions and changes in the market. One of the challenges that Olive AI has faced during the pandemic is a decline in demand for its services. Many healthcare providers and systems have faced financial strain during the pandemic, which has made it difficult for them to invest in new technologies and services. Additionally, the pandemic has created uncertainty and disruptions in the healthcare market, which has led to a slowdown in adoption of new technologies. Another challenge that Olive AI has faced is increased competition in the healthcare technology space. As more companies enter the market and offer similar services, it can be difficult for any one company to stand out and gain market share. Despite these challenges, Olive AI has continued to develop and expand its technology offerings. The company has reportedly raised significant funding in the past year, including a $225.5 million funding round in October 2020, which has allowed it to invest in new products and services. Overall, while Olive AI has faced challenges during the pandemic, the company appears to be well-positioned to continue to grow and succeed in the healthcare technology space. The company's focus on artificial intelligence and automation technology is well-aligned with the growing demand for digital healthcare solutions, and its ongoing investment in product development and expansion could help it gain market share and overcome the challenges posed by the pandemic. 3) Cerebral Cerebral is a digital health platform that provides online mental health services, including teletherapy, medication management, and online support groups. The platform is designed to make mental healthcare more accessible and affordable for individuals who may not have access to traditional in-person therapy. Cerebral connects users with licensed mental health professionals, who can provide personalized treatment plans and ongoing support through virtual sessions. The platform also offers medication management services, which allows users to receive prescriptions for mental health medications and have them delivered directly to their door. One of the key features of Cerebral is its focus on providing high-quality care at an affordable price. The platform offers a variety of subscription plans that can be customized to meet the needs and budget of each individual user. Additionally, Cerebral's team of mental health professionals are trained to provide evidence-based treatment that is tailored to each user's unique needs and goals. Why has Cerebral struggled since the pandemic? Cerebral, like many other healthcare companies, has faced challenges during the COVID-19 pandemic. While the pandemic has led to an increase in demand for mental health services, it has also created significant operational challenges and financial pressures for many healthcare companies, including Cerebral. One of the main challenges that Cerebral and other telemedicine companies have faced during the pandemic is the need to rapidly scale their operations to meet increased demand for services. This has required significant investments in technology, staffing, and infrastructure, which can be difficult for companies that are still in the early stages of growth. In addition to operational challenges, Cerebral and other telemedicine companies have also faced financial pressures during the pandemic. While demand for telemedicine services has increased, many insurance providers have been slow to adopt telemedicine coverage policies, which has limited the ability of companies like Cerebral to generate revenue from their services. Despite these challenges, Cerebral and other telemedicine companies have continued to innovate and adapt in response to the pandemic. For example, Cerebral has expanded its services to include virtual medication management and has partnered with employers and insurance providers to expand access to its services. Overall, while there have been challenges, Cerebral and other telemedicine companies are well-positioned to continue to grow and succeed in the post-pandemic healthcare landscape. Summary: While some digital health companies have thrived during the pandemic, others have struggled, including some billion-dollar companies. There are several reasons why this may be the case: Financial pressures: The pandemic has caused significant economic disruptions, and many digital health companies have struggled to raise new funding or maintain existing revenue streams. This has made it difficult for some companies to continue operating at pre-pandemic levels. Operational challenges: The rapid shift to telemedicine and remote care has created operational challenges for many digital health companies, including issues related to technology infrastructure, staffing, and regulatory compliance. Competition: The pandemic has led to a proliferation of new digital health startups, creating a more competitive landscape for established players. This increased competition can make it difficult for established companies to maintain their market share and continue to grow. Changes in healthcare policy: The pandemic has led to significant changes in healthcare policy, including expanded telehealth coverage and reimbursement. While this has created new opportunities for some digital health companies, it has also led to increased regulatory scrutiny and changes in reimbursement rates, which can impact companies' revenue streams. Overall, while some digital health companies have struggled during the pandemic, others have been able to adapt and thrive. The impact of the pandemic on digital health companies is likely to vary depending on a variety of factors, including the specific market niche, the company's business model, and its ability to adapt to changing market conditions. Thoughts, comments? Tweet @lloydgprice, or email lloyd@healthcare.digital and let's start a conversation :)

What is an ICO? Initial Coin Offering? An Initial Coin Offering (ICO) is a type of crowdfunding campaign that allows companies to raise funds by issuing their own cryptocurrency or digital tokens to investors in exchange for other cryptocurrencies, such as Bitcoin or Ethereum, or even fiat currencies like USD. ICO is similar to an initial public offering (IPO) in the traditional stock market, but instead of offering shares of a company, the issuer offers digital tokens or coins that represent a certain value or utility within their platform or ecosystem. ICOs have gained popularity as a way for startups and companies to raise funds quickly and easily, bypassing traditional financing methods like venture capital or bank loans. However, ICOs are highly speculative and largely unregulated, which means investors should be careful and do their due diligence before investing in any ICO project. Medical Initial Coin Offerings (ICO) refer to crowdfunding campaigns that are focused on medical or healthcare-related projects, such as developing new treatments, medical devices, or healthcare platforms. Medical ICOs are a relatively new trend, but they have gained attention as a way to raise funds for healthcare-related innovations quickly and efficiently, while also allowing investors to get in early on potentially groundbreaking projects. Some examples of medical ICO projects include: MedChain: a blockchain-based platform for securely storing and sharing medical records Dentacoin: a cryptocurrency that aims to improve dental care worldwide by incentivizing patients to maintain good oral hygiene habits Healthereum: a blockchain-based platform that rewards patients for engaging in their own healthcare, such as completing surveys or adhering to treatment plans As with any ICO project, investing in medical ICOs carries risks and investors should thoroughly research the project and its team before making any investments. It is also important to note that medical ICOs may be subject to regulatory oversight, so investors should be aware of the legal and regulatory implications of investing in such projects. How have Healthcare ICO’s performed in the last 5 years? Healthcare ICOs have performed mixedly in the last 5 years. Some have been very successful, raising millions of dollars, while others have failed to raise any money at all. The success of a healthcare ICO depends on a number of factors, including the strength of the team, the quality of the technology, and the regulatory environment. In general, healthcare ICOs have been more successful in raising money than other types of ICOs. This is because the healthcare industry is large and growing, and there is a lot of demand for new technologies that can improve patient care and outcomes. However, the regulatory environment for healthcare ICOs is still evolving, and there is a risk that some ICOs could face legal challenges. Here are some examples of successful healthcare ICOs: Ambrosus is a blockchain-based platform that tracks the provenance of food and pharmaceuticals. The company raised $28 million in its ICO in 2017. Dentacoin is a blockchain-based platform that aims to revolutionize the dental industry. The company raised $140 million in its ICO in 2017. Medici Ventures is a venture capital firm that invests in healthcare blockchain companies. The company has raised over $100 million in funding. Here are some examples of unsuccessful healthcare ICOs: Themis Health was a blockchain-based platform that aimed to improve the efficiency of the healthcare insurance industry. The company raised $10 million in its ICO in 2017, but it was forced to shut down in 2018 due to regulatory challenges. WellnessCoin was a blockchain-based platform that aimed to incentivize people to live healthier lifestyles. The company raised $1 million in its ICO in 2017, but it was shut down by the SEC in 2018. Overall, the future of healthcare ICOs is uncertain. The industry is still in its early stages, and there is a lot of regulatory uncertainty. However, there is a lot of potential for blockchain technology to improve healthcare, and there are a number of promising healthcare ICOs in development. What problems have Healthcare ICO’s faced? Healthcare ICOs have faced a number of problems in recent years. Some of the most common problems include: Regulatory uncertainty: The regulatory environment for healthcare ICOs is still evolving, and there is a risk that some ICOs could face legal challenges. Lack of transparency: Some healthcare ICOs have been accused of being scams or of misleading investors. Technical challenges: Blockchain technology is still in its early stages, and there are a number of technical challenges that need to be overcome before it can be widely adopted in healthcare. Lack of patient adoption: Patients are often reluctant to adopt new technologies, and there is a risk that healthcare ICOs will not be widely adopted by patients. Despite these challenges, there are a number of promising healthcare ICOs in development. These ICOs have the potential to improve healthcare in a number of ways, such as by making it more efficient, more affordable, and more accessible. What is the future of Healthcare ICO’s? The future of healthcare ICOs is uncertain. The industry is still in its early stages, and there is a lot of regulatory uncertainty. However, there is a lot of potential for blockchain technology to improve healthcare, and there are a number of promising healthcare ICOs in development. Here are some of the potential benefits of blockchain technology in healthcare: Improved data security: Blockchain technology can help to improve the security of healthcare data by making it more difficult to hack or tamper with. Increased efficiency: Blockchain technology can help to make healthcare more efficient by streamlining processes and reducing paperwork. Improved patient care: Blockchain technology can help to improve patient care by providing patients with access to their own medical records and by making it easier for doctors to communicate with each other. Reduced costs: Blockchain technology can help to reduce the cost of healthcare by making it easier to track and manage costs. If these benefits are realized, then healthcare ICOs could have a major impact on the healthcare industry. However, it is important to note that the healthcare industry is highly regulated, and it is possible that some healthcare ICOs could face legal challenges. It is also important to note that blockchain technology is still in its early stages, and there are a number of technical challenges that need to be overcome before it can be widely adopted in healthcare. Overall, the future of healthcare ICOs is uncertain. However, there is a lot of potential for blockchain technology to improve healthcare, and there are a number of promising healthcare ICOs in development. It will be interesting to see how the industry develops in the coming years. What has been the most successful healthcare ICO? The most successful healthcare ICO to date is Ambrosus. The company raised $28 million in its ICO in 2017. Ambrosus is a blockchain-based platform that tracks the provenance of food and pharmaceuticals. The company's technology can be used to verify the authenticity of products, track their movement through the supply chain, and ensure that they meet safety and quality standards. Ambrosus has partnered with a number of major companies in the food and pharmaceutical industries, including Bayer, Nestle, and Walmart. The company is also working with governments around the world to implement its technology. Here are some of the reasons why Ambrosus has been so successful: The company has a strong team with experience in the food and pharmaceutical industries. The company's technology has the potential to revolutionize the way food and pharmaceuticals are tracked and regulated. The company has partnered with a number of major companies in the food and pharmaceutical industries. The company is working with governments around the world to implement its technology. Ambrosus is just one example of a successful healthcare ICO. There are a number of other promising healthcare ICOs in development, and the industry is expected to grow rapidly in the coming years. Thoughts, comments? Tweet @lloydgprice, or email lloyd@healthcare.digital and let's start a conversation :)

Exec Summary: Spotify is a music streaming service, but it is also expanding into the healthcare industry. The company has invested in a number of healthcare startups, and it is developing its own healthcare products and services. In 2023, Spotify acquired a Swedish healthcare startup called Neko Health. Neko Health develops AI-powered body scanners that can be used to diagnose health problems early on. Spotify plans to use Neko Health's technology to develop new features for its music streaming service, such as personalized playlists based on a user's health data. Spotify is also developing its own healthcare products and services. In 2022, the company launched a pilot program in the United States that provides mental health counseling to Spotify employees. The company is also working on a new product that will allow users to track their health data and share it with their doctors. Spotify's entry into the healthcare industry is a sign of the growing trend of technology companies expanding into healthcare. These companies are attracted to the healthcare industry because it is large and growing, and there is a lot of demand for new technologies that can improve patient care and outcomes. However, the healthcare industry is also highly regulated, and it is difficult for technology companies to succeed in this environment. Spotify will need to overcome a number of challenges if it wants to be successful in the healthcare industry. History of Spotify Spotify is a Swedish audio streaming and media services provider founded on 23 April 2006 by Daniel Ek, former CTO of Stardoll, and Martin Lorentzon, co-founder of Tradedoubler. It is one of the largest music streaming service providers, with over 515 million monthly active users, including 210 million paying subscribers, as of March 2023. Spotify is listed (through a Luxembourg City-domiciled holding company, Spotify Technology S.A.) on the New York Stock Exchange in the form of American depositary receipts. Early years The idea for Spotify was born in 2002 when Daniel Ek and Martin Lorentzon were discussing the future of the music industry. They were both frustrated with the way that music was being distributed at the time, and they believed that there was a better way. Ek and Lorentzon started working on Spotify in 2003, and they launched the service in 2008. Spotify was an immediate success, and it quickly became one of the most popular music streaming services in the world. Growth Spotify continued to grow rapidly in the years following its launch. In 2011, the company expanded to the United States, and it quickly became the leading music streaming service in the country. In 2015, Spotify acquired The Echo Nest, a music data analytics company. The acquisition gave Spotify access to a wealth of data about music listening habits, which it used to improve its recommendation engine. In 2016, Spotify launched its first original podcast, called "The Joe Rogan Experience." The podcast was a huge success, and it helped to legitimize Spotify as a podcast platform. Recent years In recent years, Spotify has continued to grow and expand. In 2018, the company acquired Gimlet Media, a podcast production company. In 2019, Spotify acquired Anchor, a podcast hosting platform. In 2020, Spotify went public on the New York Stock Exchange. The IPO was a success, and it raised billions of dollars for the company. Today Spotify is one of the most popular music streaming services in the world. It has over 515 million monthly active users, including 210 million paying subscribers. Spotify is available in over 180 countries, and it offers a wide variety of music, podcasts, and audiobooks. Spotify is constantly innovating and expanding its offerings. In 2023, the company launched a new feature called "Spotify HiFi," which offers high-quality audio streaming. Spotify is also working on new features that will allow users to interact with music in new ways. Spotify is a major player in the music industry, and it is poised to continue to grow in the years to come. The company has a strong track record of innovation, and it is well-positioned to capitalize on the growing demand for music streaming. Physical Health: Neko Health Neko Health is a Swedish healthcare startup that develops AI-powered body scanners that can be used to diagnose health problems early on. The company was founded in 2019 by Daniel Ek, the founder of Spotify, and Hjalmar Nilsonne, a former executive at Spotify. Neko Health's scanners use artificial intelligence to analyze a patient's body composition, cardiovascular health, and skin health. The company says that its scanners can detect health problems up to five years before they would be detectable with traditional methods. Neko Health is currently in the process of commercializing its scanners. The company has opened a clinic in Stockholm, Sweden, and it plans to open clinics in other countries in the future. Neko Health is also working on developing new features for its scanners, such as the ability to detect cancer. Neko Health's technology has the potential to revolutionize the way healthcare is delivered. By detecting health problems early on, Neko Health's scanners could help to prevent diseases and improve patient outcomes. The company's technology could also help to reduce healthcare costs by catching problems before they become more serious. Neko Health is one of a number of startups that are using artificial intelligence to improve healthcare. These companies are all working on different aspects of healthcare, but they all have the same goal: to make healthcare more affordable, accessible, and effective. The future of healthcare is bright. Thanks to the work of companies like Neko Health, we are on the cusp of a new era in healthcare, one that is more personalized, preventive, and predictive. Mental Health: Heart & Soul In 2018, the company launched Heart & Soul, a global mental health initiative. The initiative aims to raise awareness, build knowledge, enable self-care and professional support, and normalize the conversation to reduce stigma. Spotify has also partnered with a number of organizations to support mental health, including the American Foundation for Suicide Prevention, the National Suicide Prevention Lifeline, and the Jed Foundation. The company has also created a number of resources for its employees and listeners, including a mental health hub on its website and a 24/7 helpline. Spotify's work on mental health is important because it can help to break down the stigma surrounding mental illness and make it easier for people to get the help they need. The company is also working to make mental health resources more accessible, which is essential for improving the lives of people with mental illness. Here are some of the things that Spotify is doing to improve mental health: Raising awareness: Spotify is working to raise awareness about mental health by hosting events, creating educational content, and partnering with organizations that are working to improve mental health. Building knowledge: Spotify is providing resources that can help people learn more about mental health, including articles, podcasts, and videos. Enabling self-care: Spotify is offering tools and resources that can help people take care of their mental health, such as meditation exercises, sleep playlists, and breathing techniques. Providing professional support: Spotify is working to connect people with mental health professionals, such as therapists and counselors. Normalizing the conversation: Spotify is working to normalize the conversation about mental health by featuring stories from people with mental illness and by providing information about mental health resources. Spotify's work on mental health is important because it can help to break down the stigma surrounding mental illness and make it easier for people to get the help they need. The company is also working to make mental health resources more accessible, which is essential for improving the lives of people with mental illness. What are Spotify's plans for healthcare? Spotify's entry into the healthcare industry is a sign of the growing trend of technology companies expanding into healthcare. These companies are attracted to the healthcare industry because it is large and growing, and there is a lot of demand for new technologies that can improve patient care and outcomes. However, the healthcare industry is also highly regulated, and it is difficult for technology companies to succeed in this environment. Spotify will need to overcome a number of challenges if it wants to be successful in the healthcare industry. Here are some of the things that Spotify is doing in the healthcare industry: Acquiring healthcare startups: Spotify has acquired a number of healthcare startups, including Neko Health. These acquisitions give Spotify access to new technologies and expertise in the healthcare industry. Developing its own healthcare products and services: Spotify is developing its own healthcare products and services, such as a mental health counseling program and a health data tracking app. These products and services will help Spotify to expand its reach in the healthcare industry. Partnering with healthcare providers: Spotify is partnering with healthcare providers, such as hospitals and clinics. These partnerships will help Spotify to get its products and services into the hands of more people. Investing in research and development: Spotify is investing in research and development in the healthcare industry. This investment will help Spotify to develop new technologies and services that can improve patient care and outcomes. Spotify's plans for healthcare are ambitious, but they also have the potential to be transformative. If Spotify is successful, it could help to make healthcare more affordable, accessible, and effective. Thoughts, comments? Tweet @lloydgprice, or email lloyd@healthcare.digital and let's start a conversation :)

Exec Summary: Google Bard is a large language model (LLM) chatbot developed by Google AI. It is still under development, but it has been trained on a massive dataset of text and code. Bard is able to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Google has not announced any specific plans for Bard in the healthcare industry, but it is possible that the technology could be used to improve patient care and outcomes in a number of ways. For example, Bard could be used to: Answer patient questions: Bard could be used to answer patient questions about their health conditions, medications, and treatment options. This could help patients to better understand their care and make informed decisions about their health. Provide support: Bard could be used to provide support to patients who are struggling with their mental health or who are going through a difficult time. This could help patients to feel less alone and to get the support they need. Educate patients: Bard could be used to educate patients about their health conditions and how to manage them. This could help patients to take better care of themselves and to prevent health problems from developing. Personalize care: Bard could be used to personalize care for patients by taking into account their individual needs and preferences. This could help to improve the quality of care that patients receive and to make it more effective. It is still early days for Bard, but the technology has the potential to revolutionize the way healthcare is delivered. If Google is successful in developing Bard for the healthcare industry, it could help to make healthcare more affordable, accessible, and effective. What is Google Bard? Google Bard was first announced on February 6, 2023 by Google CEO Sundar Pichai. It was then released to the public on March 21, 2023. Bard is still under development, but it has been trained on a massive dataset of text and code. It is able to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Google Bard is a large language model, also known as a conversational AI or chatbot trained to be informative and comprehensive. Here are some of the things that Google Bard can do: Answer your questions in an informative way, even if they are open ended, challenging, or strange. Generate different creative text formats, like poems, code, scripts, musical pieces, email, letters, etc. I will try my best to fulfill all your requirements. Translate languages. Write different kinds of creative content. Follow your instructions and complete your requests thoughtfully. A few of Google Bard's main competitors are: OpenAI's GPT-3: GPT-3 is another large language model chatbot that has been developed by OpenAI. It is also trained on a massive dataset of text and code, and it is able to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Microsoft's Turing: Turing is a large language model chatbot that has been developed by Microsoft. It is also trained on a massive dataset of text and code, and it is able to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. Facebook's Blender: Blender is a large language model chatbot that has been developed by Facebook. It is also trained on a massive dataset of text and code, and it is able to generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. These are just a few of the many large language model chatbots that are currently available. These chatbots are all still under development, but they have the potential to revolutionize the way we interact with computers. Will Google be successful in developing Bard for the healthcare industry? It is still too early to say whether Google will be successful in developing Bard for the healthcare industry. However, Google has a strong track record of developing successful technologies, and Bard has the potential to be a game-changer in the healthcare industry. Here are some of the factors that will determine whether Google is successful in developing Bard for the healthcare industry: The accuracy and reliability of Bard: Bard needs to be able to provide accurate and reliable information to patients and healthcare professionals. If Bard is not accurate, it could do more harm than good. The privacy and security of Bard: Bard will have access to a lot of sensitive patient data. Google will need to ensure that Bard's privacy and security measures are robust. The acceptance of Bard by patients and healthcare professionals: Bard needs to be accepted by patients and healthcare professionals in order to be successful. Google will need to do a lot of education and outreach to ensure that Bard is seen as a valuable tool. If Google can overcome these challenges, Bard has the potential to revolutionize the way healthcare is delivered. The acceptance of Bard by patients and healthcare professionals The acceptance of Bard by patients and healthcare professionals is essential for the success of the technology in the healthcare industry. Here are some factors that may influence acceptance: Accuracy: Bard needs to be able to provide accurate and reliable information to patients and healthcare professionals. If Bard is not accurate, it could do more harm than good. Reliability: Bard needs to be reliable and available when patients and healthcare professionals need it. If Bard is not reliable, it will not be seen as a valuable tool. Privacy and security: Bard will have access to a lot of sensitive patient data. Google will need to ensure that Bard's privacy and security measures are robust. Trust: Patients and healthcare professionals need to trust Bard in order to use it. Google will need to build trust by being transparent about how Bard works and by ensuring that it is used in a responsible way. Cost: Bard is a new technology, and it is not yet clear how much it will cost to use. If the cost is too high, it will limit the number of patients and healthcare professionals who can use it. If Google can address these factors, it will increase the chances of Bard being accepted by patients and healthcare professionals. Thoughts, comments? Tweet @lloydgprice, or email lloyd@healthcare.digital and let's start a conversation :) (Image credit: Microsoft/Google/Tom's Guide)

Intro to Palantir Palantir Technologies is a software company that specializes in big data analytics. The company has a number of products that are designed to help organizations make better decisions based on data. Palantir's products are used by a variety of industries, including healthcare. Palantir's plans for healthcare include using its products to help organizations improve patient care, reduce costs, and improve efficiency. The company's products can be used to: Improve patient care: Palantir's products can be used to help organizations better understand patient data. This information can be used to improve diagnosis, treatment, and care coordination. Reduce costs: Palantir's products can be used to help organizations identify areas where costs can be reduced. This can be done by identifying inefficiencies, waste, and fraud. Improve efficiency: Palantir's products can be used to help organizations improve the efficiency of their operations. This can be done by automating tasks, improving communication, and streamlining processes. Palantir's products are already being used by a number of healthcare organizations. The company has partnerships with organizations such as the Mayo Clinic, the University of California, San Francisco, and the Veterans Health Administration. Palantir's products are also being used by pharmaceutical companies, medical device manufacturers, and healthcare payers. Palantir's plans for healthcare are ambitious. The company believes that its products can help to transform the healthcare industry. Palantir is already making a difference in the healthcare industry, and its products are likely to have a significant impact on the way healthcare is delivered in the years to come. Palantir's healthcare projects Palantir Technologies has been involved in various initiatives and collaborations in the healthcare sector. Historically, Palantir has worked with healthcare organizations to leverage its data integration and analytics capabilities to improve clinical research, public health, and healthcare operations. Some notable examples include: COVID-19 response: Palantir collaborated with various governments and healthcare agencies during the COVID-19 pandemic to provide data integration and analytics support. This involved assisting with data management, contact tracing efforts, supply chain optimisation, and pandemic response planning. Precision medicine and genomics: Palantir has partnered with research institutions and pharmaceutical companies to support precision medicine initiatives. By integrating and analysing large-scale genomics data, Palantir's technology has been used to accelerate research and drug discovery processes. Clinical research and trials: Palantir's software platforms have been used to streamline and optimise clinical research and trials. Its data integration and analytics capabilities help researchers manage and analyse large volumes of diverse data to drive insights and improve research efficiency. Population health management: Palantir has collaborated with healthcare providers and public health agencies to support population health management efforts. Its technology enables the integration and analysis of various health data sources to identify patterns, monitor health outcomes, and make data-driven decisions to improve population health. Palantir's work with the NHS Palantir Technologies software is being used to help the NHS improve patient care, reduce costs, and improve efficiency. Palantir's software is being used by the NHS in a number of ways. For example, the software is being used to help the NHS track the spread of COVID-19. The software is also being used to help the NHS identify patients who are at risk of developing sepsis. Palantir's software is also being used to help the NHS improve its procurement process. The NHS is the largest healthcare system in Europe, and it is facing a number of challenges. These challenges include an aging population, rising costs, and a shortage of staff. Palantir's software is being used to help the NHS address these challenges. The NHS is a public healthcare system, and there are concerns about the use of Palantir's software in the NHS. Some people are concerned about the privacy of patient data, and others are concerned about the potential for Palantir to use its software to profit from the NHS. The NHS has said that it has taken steps to protect patient data, and that Palantir will not be able to profit from the NHS. However, the concerns about Palantir's use in the NHS are likely to continue. Here are some of the benefits of Palantir's software for the NHS: Improved patient care: Palantir's software can help the NHS better understand patient data. This information can be used to improve diagnosis, treatment, and care coordination. Reduced costs: Palantir's software can help the NHS identify areas where costs can be reduced. This can be done by identifying inefficiencies, waste, and fraud. Improved efficiency: Palantir's software can help the NHS improve the efficiency of its operations. This can be done by automating tasks, improving communication, and streamlining processes. Here are some of the concerns about Palantir's software for the NHS: Privacy: Palantir's software collects and analyzes large amounts of patient data. This data could be used to track patients' movements or to identify patients who are at risk of developing certain diseases. Profit: Palantir is a private company, and it could use its software to profit from the NHS. This could lead to higher costs for patients and taxpayers. Transparency: Palantir has not been transparent about how it uses its software in the NHS. This lack of transparency could make it difficult for patients and taxpayers to hold Palantir accountable. Overall, Palantir's software has the potential to improve the NHS. However, there are also concerns about the privacy of patient data, the potential for Palantir to profit from the NHS, and the lack of transparency from Palantir. Palantir and Healthcare - what could the future hold? The future is likely to be built on a previous track record of success which has included: Palantir's software is able to integrate and analyze data from a variety of sources. This allows clinicians to have a more complete picture of a patient's health, which can help them to make better decisions about treatment. Palantir's software is able to identify patterns and trends in data. This allows clinicians to see what is working and what is not, and to make changes to their treatment plans accordingly. Palantir's software is able to make predictions about future events. This allows clinicians to be proactive in their treatment, and to prevent problems before they occur. Overall, Palantir's software is helping to improve patient care, accelerate research, and improve drug development. The company is well-positioned to continue to be successful in healthcare in the future. What are a few likely scenarios for Palantir in Healthcare? Buy, build or partner? a) Buy: acquisition of a HealthTech company? Acquisitions are likely; buying a Healthtech company provides quick access to the market, deep data sets, enables growth on existing data protection and information governance frameworks. Some of the reasons why Palantir might buy a healthcare company: To expand its reach in the healthcare industry. Palantir is currently focused on working with large healthcare organizations, such as the NHS and the US Department of Veterans Affairs. However, there are many smaller healthcare companies that could benefit from Palantir's software. By acquiring a healthcare company, Palantir could expand its reach and help more people. To gain access to new technologies. Palantir is constantly developing new technologies, but it can also benefit from acquiring technologies that are already developed. By acquiring a healthcare company, Palantir could gain access to new technologies that could help it to improve its software and services. To accelerate its growth. Palantir is growing rapidly, but it could accelerate its growth by acquiring a healthcare company. This would allow Palantir to add new customers, employees, and technologies to its business. Of course, there are also some risks associated with Palantir buying a healthcare company. For example, the acquisition could be expensive, and it could take time for Palantir to integrate the acquired company into its business. However, the potential benefits of an acquisition could outweigh the risks. Overall, it is possible that Palantir will buy a healthcare company in the future. The company has the resources and the motivation to make a major acquisition, and the healthcare industry is ripe for disruption. b) Build: develop new products for the 4P's? Payers, providers, pharma and patients? Palantir is building a number of products for healthcare, including: Palantir Foundry: Foundry is a data analytics platform that can be used to integrate and analyze data from a variety of sources, including electronic health records (EHRs), medical devices, and research studies. Foundry can be used to identify patterns and trends in data, and to make predictions about future events. Palantir Gotham: Gotham is a security platform that can be used to protect data and systems from cyberattacks. Gotham can be used to identify and respond to threats, and to prevent data breaches. Palantir Apollo: Apollo is a platform that can be used to manage complex projects. Apollo can be used to track progress, identify risks, and make decisions. Palantir's products are being used by a number of healthcare organizations, including the NHS, the US Department of Veterans Affairs, and Pfizer. Palantir's products are helping these organizations to improve patient care, accelerate research, and improve drug development. Palantir is also working on a number of new products for healthcare, including: Palantir Health Sciences: Health Sciences is a platform that can be used to improve the efficiency of drug discovery and development. Health Sciences can be used to manage clinical trials, track data, and make decisions. Palantir Clinical Trial Harmonization: Clinical Trial Harmonization is a platform that can be used to standardize clinical trials. This can help to improve the efficiency and accuracy of clinical trials. Palantir Cell Line Development: Cell Line Development is a platform that can be used to develop and characterize cell lines. This can help to improve the efficiency of drug discovery and development. Palantir's products have the potential to revolutionize healthcare. By providing clinicians with access to more data and insights, Palantir can help improve patient care, accelerate research, and improve drug development. c) Partner: strategic partnership with a HealthTech company? The most likely scenario is Palantir continues to invest in strategic partnerships across different healthcare specialties, geographies and industries. For example Palantir already has a number of strategic partnerships in healthcare, including: Pfizer: Palantir is working with Pfizer to accelerate the development of new drugs. Palantir's software is being used to manage the complex process of drug development, from research and development to clinical trials and regulatory approval. The NHS: Palantir is working with the NHS to help manage the COVID-19 pandemic. Palantir's software is being used to track the spread of the virus, identify patients who are at risk, and allocate resources to where they are needed most. The US Department of Veterans Affairs: Palantir is working with the US Department of Veterans Affairs to improve the quality of care for veterans. Palantir's software is being used to analyse patient data to identify patterns and trends that can help clinicians improve care. Cerner: Palantir is working with Cerner to improve the efficiency of healthcare operations. Palantir's software is being used to integrate and analyze data from a variety of sources, which can help clinicians make better decisions about treatment. Dell Technologies: Palantir is working with Dell Technologies to provide healthcare organizations with a secure and scalable platform for data analytics. Dell Technologies' infrastructure can help Palantir's software to run more efficiently and securely. These are just a few of Palantir's strategic partnerships in healthcare. As the company continues to develop its software, it is likely that Palantir will form even more partnerships with healthcare organizations. These partnerships will help Palantir to bring its software to more people and to improve patient care, accelerate research, and improve drug development. Thoughts, comments? Tweet @lloydgprice , or email lloyd@healthcare.digital and let's start a conversation :)

Author: Shaun van Niekerk Integrated Care Systems Priorities ICS Strategy - Lighthouse Projects Compliance/Board Assurance Service Availability/DR Patient Safety Cyber Essentials Plus/DSP Toolkit Maturity Training Continual Service Improvement Integrated Care Systems New Focus Areas A. Medical Devices B. Operational Technology C. IoT Defence in Depth - DID Defense in Depth is a strategy using multiple security measures to protect the integrity of information. This way of thinking is used to cover all angles of business security - intentionally being redundant when necessary. If one line of defense is compromised, additional layers of defense are in place to ensure that threats don’t slip through the cracks. This method addresses the security vulnerabilities that inevitably exist in technology, personnel, and operations within a network. As cyberthreats continue to evolve and tactics become more malicious and automated, Defense in Depth provides a solid, comprehensive approach to modern security for IT professionals. Cloud Security Cloud security is the whole bundle of technology, protocols, and best practices that protect cloud computing environments, applications running in the cloud, and data held in the cloud. Securing cloud services begins with understanding what exactly is being secured, as well as, the system aspects that must be managed. As an overview, backend development against security vulnerabilities is largely within the hands of cloud service providers. Aside from choosing a security-conscious provider, clients must focus mostly on proper service configuration and safe use habits. Additionally, clients should be sure that any end-user hardware and networks are properly secured Physical Security Physical security is an important consideration when protecting against a range of threats and vulnerabilities, including terrorism. When planning the introduction of any physical security measures, it’s imperative both safety and emergency responses are considered. Effective physical security of a crowded place is best achieved by multi-layering a variety of measures. This is what is commonly referred to as ‘defence-in-depth’. The concept is based on the principle that should one line of defence be compromised, the additional layers and measures in place would ensure the threat didn’t slip through. Perimeter Security The network perimeter is the boundary between an organization's secured internal network and the Internet — or any other uncontrolled external network. In other words, the network perimeter is the edge of what an organization has control over. Suppose an office has an internal network to which a rack of servers, several dozen employee desktop computers, a few printers, and networking equipment such as routers and switches are connected. If an employee brings their personal laptop into the office, the laptop is outside the network perimeter — unless they are able to connect it to the network. Network Security Network security is a broad term that covers a multitude of technologies, devices and processes. In its simplest term, it is a set of rules and configurations designed to protect the integrity, confidentiality and accessibility of computer networks and data using both software and hardware technologies. Host Security Host security refers to a category of security tools which are deployed at the host level. Installing updates and deploying a HIDS, a tool used to monitor traffic to and from the computer in which it is deployed, are examples of host-based security tools EndPoint Security Endpoint security is the practice of securing endpoints or entry points of end-user devices such as desktops, laptops, and mobile devices from being exploited by malicious actors and campaigns. Endpoint security systems protect these endpoints on a network or in the cloud from cybersecurity threats. Endpoint security has evolved from traditional antivirus software to providing comprehensive protection from sophisticated malware and evolving zero-day threats. Organizations of all sizes are at risk from nation-states, hacktivists, organized crime, and malicious and accidental insider threats. Endpoint security is often seen as cybersecurity's frontline, and represents one of the first places organizations look to secure their enterprise networks. As the volume and sophistication of cybersecurity threats have steadily grown, so has the need for more advanced endpoint security solutions. Today’s endpoint protection systems are designed to quickly detect, analyze, block, and contain attacks in progress. To do this, they need to collaborate with each other and with other security technologies to give administrators visibility into advanced threats to speed detection and remediation response times. Application Security Application security is the process of developing, adding, and testing security features within applications to prevent security vulnerabilities against threats such as unauthorized access and modification. SIEM Security information and event management is a field within the field of computer security, where software products and services combine security information management and security event management. They provide real-time analysis of security alerts generated by applications and network hardware. SOC A security operations center (SOC), also called an information security operations center (ISOC), is a centralized location where an information security team monitors, detects, analyzes and responds to cybersecurity incidents, typically on a 24/7/365 basis. SOAR SOAR refers to technologies that enable organizations to collect inputs monitored by the security operations team. For example, alerts from the SIEM system and other security technologies — where incident analysis and triage can be performed by leveraging a combination of human and machine power — help define, prioritize and drive standardized incident response activities. SOAR tools allow an organization to define incident analysis and response procedures in a digital workflow format. Zero Trust Zero Trust is a strategic initiative that helps prevent successful data breaches by eliminating the concept of trust from an organization’s network architecture. Rooted in the principle of “never trust, always verify,” Zero Trust is designed to protect modern digital environments by leveraging network segmentation, preventing lateral movement, providing Layer 7 threat prevention, and simplifying granular user-access control. Source: https://www.linkedin.com/posts/shaun-van-niekerk-cissp-19144b45_nhs-ciso-healthcare-activity-6864200863527788544-9rZi/

Author: Dr Joe Taylor Not only can you silently sweep past queues of panic buying hydrocarbon car owners but owning the latest and greatest in automobile innovations might just save your life. When I bought my Tesla I was reprimanded by the charming chap on the phone for wishing to purchase a car. He told me in no uncertain terms that Tesla was a software company and not a car company. It was a disappointment at the time as I really did want a car, but now I get the point. A slew of exciting healthcare dedicated technologies is now in the market to monitor our health and fitness, but there is a much more exciting revolution around the corner. Your smart car will be your own personal state-of-the-art diagnostic laboratory. Why ‘Dr Tesla’ could already have seen you now The logic of turning an everyday consumer essential into a healthcare platform is a well-trodden path. You wear a watch to tell the time, it happens therefore to be conveniently placed to record continuous healthcare information too, so you integrate those functions and now telling the time becomes a secondary feature. Cars are increasingly intelligent, none more so than Teslas. These cars are collecting a huge amount of data to support their semi-autonomous driving capabilities, but their healthcare potential remains untapped. When getting into the driving seat of one of latest generation of smart cars you are potentially entering into the one of the most advanced diagnostic clinical environments imaginable. It’s difficult to overstate how rich the dataset being collected about the Tesla driver is. As a neuroscience researcher at Oxford 15 years ago I was collecting a tiny fraction of the amount of data at huge cost and with enormous effort, and in clinical practice we had next to none of this data to support diagnoses. The power of longitudinal data A one-off snapshot is very weak compared to data that spans long-periods. Subtle changes in health gradually evolving over time often go unnoticed by people and those close to them. Objective trend data is therefore of enormous value in spotting drift in healthcare variables. In the case of Tesla your personal account follows you from car-to-car and the loyalty of Tesla owners to the platform means that driver data could potentially span many years. What could we currently achieve with existing car technology? Tesla vehicles regularly receive over-the-air software updates that add new features and functionality. The car is constantly evolving through software changes in the context of static hardware. Consequently, there are many healthcare functions that could be added to vehicles already on the road rather than requiring redesign of the cars or new inventory to come onto the market. 1. How are your reaction times evolving? As our cars can ‘see’ what’s going on around us they are stepping in to keep us safe when we’re not quick enough to do act ourselves. Slowing reaction times to suddenly slowing cars, dogs running out into the road or changing traffic signals could indicate a cognitive problem and warrant formal assessment. 2. Are your hands shaking at the wheel? As Tesla drivers already know that ‘nanny-nag’ is an often-annoying feature that means unless you have your hands applying pressure to the wheel every so often the car will refuse to drive itself. The feature relies on torsional force on the wheel not on grip pressure so that even when the steering wheel is straight the twisting pressure being applied is being measured. If your previously steady hands start to shake at the wheels this could indicate that you have a developing movement disorder. One of the most important clinical diagnostic differences between tremor is whether you shake at rest or during intentional movements. Given that driving involves both periods of rest and active steering then there is the ability to differentiate between tremors with two very different groups of causes. 3. Do you have to play the radio at increasingly high volumes? Maybe you bought your Tesla to belt out Bruce Springsteen as part of your midlife crisis. I’m not one to judge. However, if over time the average volume you have the tunes at is increasing this may indicate hearing loss. Not to worry – your car will know where the nearest hearing test is available and maybe you could give them a call from now at its suggestion? 4. Why do you have the heating on in summer? People with hypothyroidism are always too cold, their body doesn’t have enough of the thyroid hormone signal to burn energy creating internal heat. If you used to be a free-wheeling wind in your hair sort of driver and gradually enjoy being cocooned in the toasty embrace of your car’s heated seats on max then maybe you should consider getting your thyroid levels measured. 5. Should you be making better use of your gym membership? Weight sensors in the seats of cars are there to alert you to an unsecured passenger, but they could easy tell if you were piling on the pounds. I’m afraid your car also knows when your visits to the gym fall from those earnest weeks immediately after signing that 12-month contract. I would quickly fall out with my car if it started to be overly judgemental, but if it suggested that my planned route would enable me to swing by the gym I would be less likely to take a sledge hammer to it. Future innovations 1. ‘Who you looking at?’ In the latest Tesla models cameras are not just looking out at the road but also looking at the driver. This opens a world of new opportunities for continuous healthcare monitoring. Vision-based healthcare monitoring has become increasingly capable. Oxehealth’s Oxevision system can derive medical grade cardio-respiratory vital signs. Whilst the company is currently using specialist hardware, it is possible to apply these same data extraction approaches to video feed from ‘normal’ cameras. 2. Keep your hands on the wheel For the moment we still have our hands on the steering wheels of our cars offering the opportunity for integration of contact sensors into those wheels. Hyundai’s car healthcare system concept proposes that this is an ideal point to measure ECG data. 3. Integration with wearables To provide a truly 24-hour monitoring solution, the healthcare features of our cars would need to be integrated with information about what we are up to when outside of our cars. Either integration with existing ubiquitous wearables or development of entirely new technologies is the natural solution. When you buy a healthcare enabled car, it is likely to come with an accompanying wearable that seamlessly integrates the data from when you’re at the wheel to when you’re outside of that environment. 4. Co-ordination with static healthcare services In an acute emergency, such as a heart attack, stroke or fit the car could automatically use its communication capabilities to alert emergency services and even the local hospital. As autonomy improves not only is the car likely to bring you to a safe stop in the case of an acute incapacitating event, but in the future may drive you to the nearest appropriate healthcare service. 5. Healthcare interventions The diagnostic potential of smart cars is clear, but could they intervene to improve our health? I often loose against my car at chess whilst waiting for it to charge – it turns out it’s smarter than I am. If the car suspects you are getting a bit sluggish in your cognition, it could suggest some brain training on screen whilst you’re next waiting. Our cars will be able to detect rising levels of stress, and there could be mental health interventions such as a breathing exercises, that the car could suggest to calm you down when road rage looks to be your next destination. The power of AI and mass recordings The value of continuous driver monitoring will only be truly realised through the application of AI to the massive amounts of data from potentially many millions of drivers. Developing useful AI is costly and time-consuming. Fortunately, this is not a problem Tesla is unfamiliar with and other manufacturers are quickly having to come to terms with. The development of self-driving capabilities in Tesla vehicles has required collection of a mass of data. The solution to autonomous driving is training a large neural network. It is this same approach that we will see transform healthcare. There are more than a million Teslas on the road sending information back to the ‘transformer’ – a single giant neural network. This model is data hungry and eight external cameras in addition to the new internal camera feed back into this beast. Tesla is vertically integrating its AI strategy by creating custom silicon to speed up the training process for its net, recently revealing details of its D1 chip to speed up the machine-learning algorithm behind Autopilot. An AI semi-autonomous driving model might incidentally become a diagnostic healthcare platform without that being its primary goal. A neural network that has enough information to optimise its primary goals may find value in incorporating indicators of health and wellbeing. Challenges to smart cars becoming healthcare environments There are natural privacy concerns regarding how much information is being collected, how it is being used, stored, and distributed. These are the same questions we grapple with across the tech sphere, but given people tend to anthropomorphise their cars rather than their other tech perhaps this is platform people will be more willing to place their trust in. It is also possible that as the car becomes a diagnostic clinical environment we will have to grapple with their regulatory status. The fitbit sense has FDA 510k approval for the detection of Atrial Fibrillation and it’s likely that similar considerations will have to be considered for the health functions of smart cars. The capability and legality of truly autonomous driving on our roads is much closer than most imagine, within five years we are unlikely to be required to pay active attention to the cars that drive us. This limits the amount and type of healthcare information that can be recorded but there will be many cars that will require active driver participation for a couple of decades to come. When we become used to cars as diagnostic healthcare environments, we are unlikely to let go of that value with the establishment of autonomous driving and will still consider getting into a car as a healthcare choice. I anticipate this will first be manifest in the development of healthcare diagnostic tools that are aimed at monitoring passengers – key indicators such as their eye movements in response to the outside world can provide some of the information that can be gleaned from drivers’ interaction with the environment. Conclusions Perhaps it’s ironic that the innovation that has supposed our sedentary lifestyles during the 20th century could be the most important vehicle for delivering healthcare improvement in the 21st. Apple’s much awaited entry into the smart car space is likely to come with a big health and wellness aspect, and we should expect plenty of other manufacturers to realise the untapped healthcare potential of their smart cars. As all automotive manufacturers fight for their existence in an industry rocked by technology this is likely to prove a key battlefield. Author: Dr Joe Taylor https://www.linkedin.com/in/joe-taylor-654950a/

The last few weeks has seen a lot of debate about big technology companies involvement in healthcare, what they are getting right, what they are getting wrong and why big names such as Google have made the decision to withdraw from the market again, having previously scaled down their interest in 2012. According to a leaked memo, Google is dissolving its single unified health division and reassigning all consumer and enterprise projects across myriad teams internally, consisting of 570 employees. Examples of health projects being reassigned include consumer-facing products like sleep tracking tech with its Nest Hub smart home devices, Fitbit wearables, clinical initiatives like its Care Studio EHR search tool and health AI tools previously with Deepmind. So why are big trillion dollar tech companies not succeeding despite their significant track record in a myriad of other industries? Build it and they will come Over and over again we have witnessed big tech companies building products and services for the mainstream, for everyone, the silicon valley mantra of “build it and they will come”. So here lies the first problem, digital maturity in healthcare is not at the same level as other markets, the target market in healthcare is not everyone, it’s predominantly the over 70’s. The scale and confidence in using software and hardware products in healthcare is nowhere near 50% and the potential “tipping point” in mainstream innovation adoption curves. This is mainly due to the age and demographic of users, plus other social determinants of health like income, access to broadband, levels of education and current behaviours. Big tech needs to understand the audiences in healthcare better, how niche, individual and nuanced they are. Big tech also needs to listen a lot more to users and their needs, instead of rolling out the “growth hacking playbooks”, killer features, designing for network effects and viral growth spurts. Improving outcomes or algorithms? Next, we come to arguably the biggest reason big tech companies are not succeeding in healthcare .. data. A lot of stakeholders across the healthcare ecosystem strongly believe big tech should be defending the data, helping make data more secure, tagged and categorised. If Google can make the world’s information searchable, why can’t it make health records, prescriptions, medical imaging or clinical notes searchable? Instead there is an uneasy feeling that big tech wants to own, exploit and mine data which has created significant levels of mistrust. Here in lies the first “frenemy” principle, big tech comes across as a friend when in fact it is a rival or an enemy in the eyes of many healthcare stakeholders. What does big tech really want? Do they really want to help us deliver care more efficiently? Do they really care about improving outcomes or their own algorithms? Software is eating the world and healthcare For a lot of people in healthcare big tech is more of a threat to them, their job, career path and day to day life, than it is a friend. Here in lies the second “frenemy” principle, big tech is disguising their true intentions, in reality they want to learn how pathways, procedures, decisions, analysis and outcomes work, how they are structured, how they mitigate clinical risk. Big tech needs these data points, inputs and variables to solve problems, update machine learning algorithms, deep learning and neural networks etc.. The problem is healthcare is a people business, a very labour intensive people business. In the eyes of many healthcare administrators and staff, “software is eating the world”, to phrase Marc Andreessen’s famous quote from 2011 and they are very aware of the implications voice to text translation, image analysis, robotic process automation and other technologies can have on their jobs. So why help my new big tech friends, when in reality they have the tools and are developing the solutions to replace me? Why help big tech innovate and improve the delivery of care to the point it runs as efficiently as an Amazon warehouse? Despite all these cultural challenges, hope is not lost. Big tech can get a lot of things right in healthcare and really help, particularly post Covid when the world became remote, decentralised, more digitally mature and significantly affected by the “zoom boom.” For example big tech could deploy its arsenal of solutions to support cyber security in healthcare, in May the Health Service Executive of Ireland suffered a major ransomware cyberattack that caused all of its IT systems nationwide to be shut down. In July, hackers who targeted hospitals in New Zealand's Waikato district released patient information to media outlets just as health systems struggled to come back online. Last year a wave of attacks on US hospitals led the FBI to issue a warning that US healthcare systems were facing an “increased and imminent” risk of cyber attack. Big tech could also help with a range of automation projects in healthcare; the mass translation of patient advice and guidance into 100+ languages, the deployment of voice to text software to transcribe thousands of hours of clinical notes, application of machine learning algorithms to pattern match the most vulnerable on outpatient waiting lists, as well as many other use cases. In summary, big tech needs to be more of a game keeper not a poacher in order to rebuild trust with patients, clinicians and healthcare executives. Defender of the healthcare realm, not an invading force, a true friend to healthcare, not a frenemy… Author: Lloyd Price @lloydgprice

Authors: Saira Ghafur, Emilia Grass, Nick R Jennings, Ara Darzi As modern technology becomes indispensable in health care, the vulnerabilities to cyber-threats continue to increase, compromising the health information and safety of millions of people. This threat can happen in several ways: data can be stolen; data might be deleted or corrupted in a way that is not obvious until years later; and medical devices can be hacked, causing direct harm to patients. In May, 2017, the WannaCry ransomware encrypted data and files on 230 000 computers in 150 countries, and impaired the functionality of the National Health Service (NHS) in England.1 Key systems were blocked, preventing staff from accessing patient data and critical services. However, the WannaCry attack was not directly targeted at the NHS. Other major organisations were affected, including Telefonica, FedEx, Nissan, Russian Railways, and the Bank of China. However, the biggest effect was undoubtedly felt by the NHS.2 While health systems worldwide watched, it became apparent how susceptible health care is to any cyber threat. Today, at a global scale, the number of cyberattacks across all industries is rising, and the financial impact is accumulating: the average cost of a data breach globally is, according to a 2018 report3from IBM, US$3·86 million. Although health-care organisations might be less likely than financial services or public-sector bodies to be targets of cyberattack, the cost per capita for a data breach in health care was $408, nearly double that of financial services, which ranked second. Health-care organisations also take substantially longer than other industries to contain data breaches because of a lack of resources, both financial resources and trained personnel, and inefficient infrastructure.3The problems seen in the NHS, a publicly funded nationalised health-care system, might help other countries to determine their security priorities going forward. In general, limited budgets and time-consuming approval processes are attenuating the NHS's ability to adapt to evolving technological challenges. Since the WannaCry attack, the NHS has taken several steps to increase its cyber resilience, and accountabilities have been assigned to the Department of Health and Social Care and Arm's Length Bodies (ALBs), as shown in the figure. The figure highlights the substantial complexity of NHS organisational structures because of the large number of ALBs and sovereign organisations. A new ALB, NHS X, will be launched in July, 2019, with the remit of overseeing digital transformation in the NHS, including setting cyber security standards. How this will alter the above accountabilities remains to be seen. Uncoordinated processes and overlapping competencies result in higher costs, inefficiency, and wasted resources. This problem is not new and, despite the complexity of doing so, most NHS services are delivered in a joined-up way, which, has not been the case for cybersecurity functions. One of the biggest problems for cybersecurity has been navigating accountability, making it difficult for frontline organisations to seek appropriate resources and help. Furthermore, the information technology (IT) landscape within the NHS is highly heterogeneous and inconsistent. To date, to our knowledge, no catalogue exists to systematically list all software and hardware deployed within the NHS, leading to a severe lack of awareness of vulnerabilities.FigureNational accountabilities for cyber security of the UK Department of Health and Social Care and Arm's Length Bodies. Although cyber incidents are required to be reported and registered in the NHS, the data are not systematically processed and assessed, resulting in missed opportunities to understand risks and threats. Risks and vulnerabilities are not measured at a local level, making it difficult to assess the effect of a cyberattack on NHS IT infrastructure, data, and patients in advance. Health care is the only industry globally for which the biggest threat to data breaches comes from internal sources.4 In 2017, 46% of breaches were due to employee behaviour (eg, by clicking on infected links in e-mails, employee negligence, or abusing access to data).5 Currently, online training is mandatory for all NHS staff members, although evidence from 2018 shows that only 12% of NHS Trusts have reached this mark.6 Given the risk human error presents to data breaches in health care, instructions and training on cybersecurity for all employees need to be given greater precedence. There has been chronic underinvestment in health-care IT, especially compared with other market sectors; this investment can be as little as 1–2% of the annual budget on IT compared with 4–10% in other sectors.7 To embed a security culture, progressive investment needs to be made in IT and an economic impact assessment to understand what is working. Since the WannaCry attack, substantial capital has been invested to upgrade systems and to improve cybersecurity capabilities across the NHS.1 However, with limited budgets, health systems are faced with difficult choices in allocating resources and cybersecurity investment is often not a priority. This choice of resource allocation is often seen as a trade-off in all sectors, although the potential consequences for health-care—both patient safety and economic—could be staggering if not addressed. What will be the tipping point before cultural and organisational changes are made across the board? Our case study highlights issues that are clearly relevant and applicable to health systems globally. Yet we should ask what lessons can disparate health systems learn from each other, and how can we scale and spread this learning to ensure we can minimise the effect of any future cyberattacks. The most recent well publicised cyber-attack on health care was in Singapore in 2018, in which the health data of 1·5 million Singaporeans, including the country's Prime Minister, was stolen.8 A Committee of Inquiry was subsequently appointed and some of the major recommendations included the review of all systems and networks fully and regularly by Singapore's Ministry of Health; the training of all staff in cybersecurity practices; the requirement of enhanced security checks on critical systems; and regulation of responses to attacks to prevent damage.8A so-called cyber-siege, in 2007, led the Estonian government to create its cybersecurity strategy, which has built many aspects of cybersecurity into the country's law.9 The Estonian Information System Authority publishes an annual cybersecurity report, which found that nearly 11 000 cybersecurity incidents occurred in 2018, although only 122 of all these cases, ten of which were in health care, directly affected the functionality of the systems.9 To combat cybersecurity threats in health care, Estonia introduced blockchain technology to securely manage electronic patient records creating a time-stamped record of anyone coming in contact with it, and adding or omitting information. Estonia is a digitally advanced society, where patients use electronic identification cards to access their health information and decide with who this information can be shared with.9The USA has had some of the most highly publicised cyberattacks on health care; in 2015, criminals stole 80 million records from Anthem, a US health insurance company.7 Federal regulations for protecting patient health information are covered under the Health Insurance Portability and Accountability Act of 1996 and the Health Information Technology for Economic and Clinical Health Act of 2009.10 The most recent development has been the launch of the US National Institute of Standards and Technology cybersecurity framework11 in 2018, which represents a collaboration between the US government and private entities to improve cyber infrastructures throughout the country. This framework, which is voluntary, is used across crucial sectors and is the most frequently used to improve cyber-resilience in health care in the USA.11Although these three examples hail from different contexts, they highlight common cyber security problems and subsequent principles of best practice that are universal to improve cyber resilience in health care. Because of the NHS's complex structure, there is a lack of clearly defined responsibilities and security preparedness in the face of a cyberattack, making it near impossible to assess the NHS's resilience and the potential effect an event would have on the health and social care system. The available NHS response and mechanism of accountability are not clear. Addressing this issue requires a concerted effort, not only to clarify frameworks but also to promote and instil a single understanding of cybersecurity. The alternative is to face substantial reputational and financial loss, and, most importantly, risk patients' safety. Source: https://www.thelancet.com/journals/landig/article/PIIS2589-7500(19)30005-6/fulltext References: 1.Lessons learned review of the WannaCry ransomware cyber attack. Department of Health & Social Care, London2018https://www.england.nhs.uk/wp-content/uploads/2018/02/lessons-learned-review-wannacry-ransomware-cyber-attack-cio-review.pdf Date accessed: February 12, 2019 2. WannaCry: list of major companies and networks hit by ransomware around the globe. International Business Times. May 16, 2017; https://www.ibtimes.co.uk/wannacry-list-major-companies-networks-hit-by-deadly-ransomware-around-globe-1621587 Date accessed: February 12, 2019 3.2018 cost of a data breach study: global overview. https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=55017055USEN&Date: 2018 Date accessed: February 12, 2019 4. 2018 Data Breach Investigations Report. https://enterprise.verizon.com/resources/reports/DBIR_2018_Report_execsummary.pdfDate: 2018 Date accessed: February 12, 2019 5. Five industries that top the hit list of cyber criminals in 2017. http://www.infoguardsecurity.com/5-industries-top-hit-list-cyber-criminals-2017/Date: 2017 Date accessed: February 12, 2019 6. REDSCAN reveals a large disparity in cybersecurity skills and spending across NHS. https://www.redscan.com/news/nhs-cybersecurity-skills-survey/Date: 2018 Date accessed: February 12, 2019 7.Cybersecurity and healthcare: how safe are we?. BMJ.2017 8. SingHealth cyberattack: Committee of Inquiry appointed, report due end-2018. Channel NewsAsia. July 24, 2018; https://www.channelnewsasia.com/news/singapore/singhealth-cyberattack-committee-of-inquiry-appointed-report-due-10557724 Date accessed: February 12, 2019 9.e-Estonia Cyber security report 2018: investing in the security of information systems to secure digital lifestyle. https://e-estonia.com/cyber-security-report-2018/Date: 2018 Date accessed: February 12, 2019 10. Cybersecurity in hospitals: a systematic, organizational perspective. J Med Internet Res. 2018; 20: e10059View in Article 11. National Institute of Standards and Technology Cybersecurity framework. https://www.nist.gov/industry-impacts/cybersecurityDate: 2018 Date accessed: February 12, 2019