Digital transformation: Health systems’ investment priorities

Health systems around the world are facing a host of challenges, including rising costs, clinical-workforce shortages, aging populations requiring more care (for example, to treat chronic conditions), and increasing competition from nontraditional players.1 At the same time, consumers are expecting new capabilities (such as digital scheduling and telemedicine) and better experiences from health systems across their end-to-end care journeys.2 In response, health systems are increasing their focus on digital and AI transformation to meet consumer demands, address workforce challenges, reduce costs, and enhance the overall quality of care.3 However, despite acknowledging the importance of these efforts to future sustainability, many health system executives say their organizations are still not investing enough.

AI, traditional machine learning, and deep learning are projected to result in net savings of up to $360 billion in healthcare spending.

AI, traditional machine learning, and deep learning are projected to result in net savings of $200 billion to $360 billion in healthcare spending.4 But are health systems investing to capture these opportunities? We recently surveyed 200 global health system executives about their digital investment priorities and progress.5 Seventy-five percent of respondents reported their organizations place a high priority on digital and analytics transformation but lack sufficient resources or planning in this area.

Increasing prioritization

In line with other industries, the majority (nearly 90 percent) of health system executives surveyed, in both technical roles (such as chief information officer or chief technology officer) and nontechnical roles (for example, CEO or CFO), reported that a digital and AI transformation is a high or top priority for their organization. At the same time, 75 percent of respondents reported their organizations are not yet able to deliver on that priority because they have not sufficiently planned or allocated the necessary resources.


Health system digital investment priority areas and anticipated impact

For health system executives, current investment priorities do not always align with areas they believe could have the most impact. There is alignment in some areas, including virtual health and digital front doors, where about 70 percent of respondents expect the highest impact.1 In other areas, such as AI, 88 percent of respondents reported a high potential impact,2 yet about 20 percent of respondents do not plan to invest in the next two years. The absence of investment in a robust, modern data and analytics platform could delay value creation in areas that depend on these capabilities—such as efforts to close gaps in care, improve timely access for referrals, and optimize operating room throughput.

Major headwinds and slow progress

Given the current macroeconomic climate and increasing cost pressures on health systems, most respondents identified budget constraints as a key obstacle to investing at scale across all digital and AI categories of interest (51 percent of respondents ranked this obstacle among the top three). For example, a health system that is building a digital front door may lack the resources to simultaneously invest in the latest generative AI (gen AI) capabilities.

Respondents called out challenges with legacy systems as the second-greatest concern (after budget constraints). Core tech modernization is key to delivering on the digital promise,1 but health systems have typically relied on a smaller set of monolithic systems that have become a challenge to untangle.

Additional highly ranked challenges include data quality (33 percent), tech talent and recruiting (30 percent), and readiness to adopt and scale new technology (34 percent).

Satisfaction with digital investment

Most executives of health systems that have invested in digital priorities (72 percent) reported satisfaction across all investment areas. Among the comparatively fewer respondents who reported investing in robotics and advanced analytics, satisfaction was even higher, at 82 percent and 81 percent, respectively. Given that investments result in a high level of satisfaction and that 75 percent of executives reported they are not yet able to deliver on their digital transformation ambitions (as noted above), health systems may be facing a failure to scale their digital programs.

What health systems can do and how they can learn from other industries

The goal of digital and AI transformation is to fundamentally rewire how an organization operates, building capabilities to drive tangible business value (such as patient acquisition and experience, clinical outcomes, operational efficiency, and workforce experience and retention) through continuous innovation. Delivering digital value for health systems requires investment and new ways of working.

Building partnerships. Scale is crucial to value creation. But the definition of at-scale systems has changed in the past few years; today, it takes more than $13 billion to be a top 20 system by revenue, and many have reached their current position through inorganic growth.6 Partnerships (joint ventures and alliances) may offer a promising avenue to access new capabilities, increase speed to market, and achieve capital, scale, and operational efficiencies.7

Moving beyond off-the-shelf solutions. History shows that deploying technology—such as electronic health records (EHRs)—on top of broken processes and clinical workflows does not lead to value. Realizing value from healthcare technology will require a reimagination (and standardization) of clinical workflows and care models across organizations. For example, optimizing workflows to enable more appropriate delegation, with technical enablement, could yield a potential 15 to 30 percent net time savings over a 12-hour shift. This could help close the nursing workforce gap by up to 300,000 inpatient nurses.8

Using the cloud for modernization. Health systems are increasingly building cloud-based data environments with defined data products to increase data availability and quality. Health systems can also use cloud-hosted, end-user-focused platforms (such as patient or clinician apps) that integrate multiple other applications and experiences to simplify stakeholders’ interactions with the system.

Operating differently. Operating differently entails fundamental changes in structure (flatter, empowered, cross-functional teams), talent (new skill sets and fully dedicated teams), ways of working (outcome orientation, agile funding, and managing products, not projects), and technology (modular architecture, cloud-based data systems, and reduced reliance on the monolithic EHR). With these changes, some health systems have begun to see real value within six months. Building a digital culture helps the transformation succeed over time.9

Cautiously embracing gen AI. Gen AI has the potential to affect everything from continuity of care and clinical operations to contracting and corporate functions. Health system executives and patients have concerns about the risks of AI, particularly in relation to patient care and privacy. Managing these risks entails placing business-minded legal and risk-management teams alongside AI and data science teams.10 Organizations could also implement a well-informed risk-prioritization strategy.

Digital and AI investments provide health systems with opportunities to address the many challenges they face. Successful health systems will invest in areas with the greatest potential impact while removing barriers—for example, by upgrading legacy infrastructure. Health systems that make successful investments in digital and analytics capabilities could see substantial benefits and position themselves to benefit from the $200 billion to $360 billion opportunity.11

ABOUT THE AUTHOR(S)
Jack Eastburn is a partner in McKinsey’s Southern California office; Jen Fowkes is a partner in the Washington, DC, office; and Karl Kellner is a senior partner in the New York office. Brad Swanson is a consultant in the Denver office.

The authors wish to thank David Bueno, Camilo Gutierrez, Dae-Hee Lee, Audrey Manicor, Lois Schonberger, and Tim Zoph for their contributions to this article.

Πηγή: mckinsey.com
find more :https://eefam.gr/digital-transformation-health-systems-investment-priorities/

Discovering the multi-level contribution of AI to the NHS

Following the recent announcement of increased funding for artificial intelligence within the NHS by the Chancellor in the Spring 2024 programme highlights the importance of stabilising the healthcare system and securing the leading position in healthcare delivery on a global scale. In order to maximise the patient benefit and staff satisfaction through the full utilisation of the use of AI, it is useful to develop an action plan with proactive next steps.

Step 1: Focus on the right priorities

There are many high-impact use cases such as waiting list management. By developing AI algorithms and data-driven decision support tools to predict patient demand, optimize scheduling, and efficient allocation of resources, healthcare facilities can significantly reduce wait times and enhance patient satisfaction. Through our work with NHS Trusts it has been shown that the development of AI-based programming tools has resulted in An increase in patient preference within imaging. Artificial intelligence can also help to enhance the support of  office services. Experience so far has shown a significant reduction in the time to review a contract with the use of artificial intelligence.

Step 2: Cultivating staff acceptance

An important aspect of any AI initiative is cultivating trust and acceptance from frontline staff. As clinicians focus on refining their clinical judgment and providing personalized care it makes sense that they approach the integration of AI with caution. To avoid this hesitation it is important that strict trials of an evidence-based implementation. Furthermore, the syndrome of ”that it was not manufactured here” prevents and forces individual executives to actively engage and convince their clinical communities of tangible evidence of AI adoption. One approach to fostering staff buy-in is active involvement from the outset in the design of the programme design.  The use of the “Net Promoter Score”, which measures staff enthusiasm for a particular technology, is a strong incentive for engagement and could potentially help. Also in cases where staff know that the technology is supported by their colleagues, after a pilot project, it is more more likely to want to participate themselves. Another useful approach is for the clinician to present his or her own prediction alongside any AI prediction, allowing the staff to make their own prediction to immediately see how the AI compares. Using this method, we can show that an AI algorithm was more predictive of the day a patient would be ready to leave than the clinician’s own estimate.

Step 3: Integrating the technology into the standard

Considering a user-driven approach to process redesign has the dual impact of bring the affected parties – for example, staff, patients and carers – together on the journey, while also helping to ensure that change is not just a digitisation of existing processes. THE NHS will need to fund the effort so that by supporting staff to trust and find the budget to deliver the necessary change programme.

Looking forward: A collaborative imperative

Vital to the whole effort will be the collaboration between government, the NHS leadership, frontline staff and the technology partners. Latest research has shown that 74% of organisations recognize that AI can make their operations more efficient, and a staggering 84% do not believe they are equipped to do so to make it a reality. While the Chancellor’s investment in AI represents a significant moment, the result is testament to how capable we are of navigating the complexities of implementation effectively and provide frontline organisations with the support they need.

Read more: Transforming through Data,page 116 Article from Jenny Lewis under the title ”  Unlocking the Potential of AI in the NHS: A Path Forward’

H.M._2-vol 24-2024 (1)

Digital-in-Health: Unlocking the Value for Everyone

Digital technology can strengthen health systems, improve health financing and public health, and increase reach to underserved populations, according to a new World Bank report launched today. The report also finds that digital technology and data are especially helpful to prevent and manage chronic diseases, care for both young and aging populations, and prepare for future health emergencies and health risks triggered by climate change.

The report, Digital-in-Health: Unlocking the Value for Everyone, was launched today during the G20 Health Ministers Meeting in Gandhinagar, India. It presents a new way of thinking from simple digitization of health data to fully integrating digital technology in health systems: Digital-in-health. This means, for example, infusing digital technologies in health financing, service delivery, diagnostics, medical education, pandemic preparedness, climate and health efforts, nutrition, and aging.

The report also underscores that the successful use of digital technologies must be inclusive of all population groups, and ensure access to digital infrastructure, modern technologies, and skills, especially for vulnerable people.

Designed with people at the center, digital technology can make health services more personal, prevent healthcare costs from increasing, reduce differences in care, and make the job easier for those who provide health services,” said Mamta Murthi, Vice President for Human Development, World Bank. “We hope that this report will give governments confidence and practical guidance, regardless of the country’s stage of digital maturity or fiscal challenges.

Improving health is getting harder, not easier. Health systems face serious and growing challenges and policy decisions are too often not based on reliable data.  It is estimated that some countries use less than 5% of health data to improve health which means that decisions are not based on data or data is not used effectively to make improvements. Within challenging fiscal environments, people-centered and evidence-based digital investments can help governments save up to 15% of health costs. The report presents pragmatic, low-cost actions to improve digital-in-health, no matter the maturity of a country’s systems or digital infrastructure. For example, better health data governance and standards to ensure systems can readily connect and exchange information are not costly but will be game changing in reducing siloed digital solutions and fragmentation.

In India, we have shown that digital innovations such as tele-consultations have reached more than 140 million people and provided accessible, affordable and efficient healthcare for everyone,” said Mansukh L Mandaviya, Minister for Health and Family Welfare, India. “We believe a digital-in-health approach can unlock the value of digital technologies and data and has the potential to prevent disease and lower healthcare costs while helping patients monitor and manage chronic conditions.” 

 

To help countries embrace a digital-in-health approach, the report proposes three essential areas to guide investments:

  1. Prioritizeevidence-based digital investments that tackle the biggest problems and focus on the needs of patients and providers.
  2. Connect the regulatory, governance, information, and infrastructure dots so that patients know that data is safe and health workers can use digital solutions transparently.
  3. Scale digital health for the long run based on trust with sustainable financing, and improved capacity and skills for digital solutions.

It will take global, regional, and country leadership to make digital-in-health a reality. The report recommends strong country leadership involving all relevant sectors and stakeholders, including civil society. Digital technology and data improvements will involve investments beyond the health sector and new partnerships with the private sector. A digital-in-health mindset needs to be a routine aspect of annual health system planning, budgeting, and implementation.

The World Bank is committed to helping low-and middle-income countries to make digital-in-health a reality to improve health for everyone. Over the past decade, the World Bank has invested almost $4 billion in digital health including in health information systems, digital governance, identification systems, and infrastructure.

For more information, including a copy of the new report, Digital-in-Health: Unlocking the Value for Everyone, please visit:

Website: www.worldbank.org/en/topic/health

Twitter: http://www.twitter.com/WBG_Health

Facebook: http://www.facebook.com/worldbank

YouTube: http://www.youtube.com/worldbank

 

Conceptualizing the Mechanisms of Social Determinants of Health: A Heuristic Framework to Inform Future Directions for Mitigation

A large body of scientific work examines the mechanisms through which social determinants of health (SDOH) shape health inequities. However, the nuances described in the literature are infrequently reflected in the applied frameworks that inform health policy and programming.

We synthesize extant SDOH research into a heuristic framework that provides policymakers, practitioners, and researchers with a customizable template for conceptualizing and operationalizing key mechanisms that represent intervention opportunities for mitigating the impact of harmful SDOH.

In light of scarce existing SDOH mitigation strategies, the framework addresses an important research-to-practice translation gap and missed opportunity for advancing health equity.

Conceptualizing the Mechanisms of Social Determinants of Health!

I. SDOH
Health inequities are most often understood as associated with the social determinants of health (SDOH)

II. Opportunity
A practical, heuristic framework for policymakers, practitioners, and researchers is needed to serves as a roadmap for conceptualizing and targeting the key mechanisms of SDOH influence

  • Unifying principles

1. SDOH are underlying causes of health inequities
-> Meaningful community engagement in data generation and interpretation for understanding and mitigating underlying health inequity drivers and multilevel resilience factors

2. SDOH shape health inequities through contextual influences
-> Development, evaluation, and scale up of multilevel interventions that address the mechanisms of SDOH at the structural, psychosocial, and clinical/biomedical levels

3. SDOH contextual disadvantage is not deterministic
-> Adoption of individualized/differentiated, decentralized, and community-based service delivery models

4. SDOH shape health over the life course
-> Proactive intervention focused on prevention and health promotion as well as restorative care to maintain and improve physical, mental, and psychosocial functioning and quality of life

5. SDOH operate through biological embedding
-> Greater prioritization of harmful SDOH mechanisms and mitigation of their biological impact in clinical education and practice, including investment in biomarkers for early detection of and intervention on emerging disease trajectories

6.SDOH operate intergenerationally
-> Prioritization of family-based approaches to restorative health care, prevention, and health promotion

7. SDOH shape clustering and synergies of health inequities
-> Greater integration of comprehensive, interdisciplinary, team-based health services delivered within a value-based framework and at the top of providers’ licenses

8. SDOH mechanisms to produce health inequities
-> Departure from vulnerability- and deficiency-focused paradigms for understanding health inequities toward multilevel resilience-focused paradigms for reducing health inequitiess

An Organizing Framework of SDOH Mechanisms

1. Underlying causal factors
-> Two distinct classes of social influence: SDOH capital and SDOH processes

2. Mediating factors
-> Two mechanisms: environmental and behavioral exposure and biological susceptibility

3. Moderating factors
-> Resilience – as collective action that supports the ability of communities to thrive when confronted with structural challenge

4. Health inequity outcomes
-> The impact of SDOH mechanisms on health inequities is dependent on the broader patterns of morbidity within the community of interest

Check out the article by Marco Thimm-KaiserAdam Benzekri and Vincent Guilamo-Ramos here:

https://lnkd.in/e57GXthQ

Essential cancer screening and diagnosis services must be included in UHC schemes to reduce mortality

The earlier a cancer is detected, the easier it is to treat successfully, often with fewer side effects, and at a lower cost. In many high-income regions, such as Europe and the United States, survival rates for cancer have risen in past decades, in part thanks to routine screening that detects cancers at an early stage. It’s especially true for common cancers like cervical, breast, colorectal, and prostate, where routine screening offers a clear test and methodology for early detection.

Investing in routine screening programmes for asymptomatic cancers as well as the early detection of symptomatic cancers and diagnostic and referral services is, therefore, a cost-efficient approach to mitigate the public health costs of cancer. These are estimated to reach USD 458 billion globally by 2030, and cut the projected global economic cost of cancers, estimated at USD 25.2 trillion for the period 2020-2050.

Such investments in services must be accompanied by clear communication about the necessity and benefits of such measures. It is also critical that the general public have access to reliable information on possible early signs of certain cancers (notably, breast, cervical, lung, prostate, ovarian and testicular) and primary healthcare staff must be equipped to spot signs of cancer – with rapid referral options for screening and then treatment.

Unfortunately, many people around the world still lack access to these essential services. In low- and middle-income countries in particular, cancer prevention, diagnosis and care remain a luxury that is out of reach for many.

A significant number of people, particularly those from low-income communities, face barriers that prevent them from accessing necessary health services, such as the distance to healthcare facilities and costs of healthcare – with the risk of financial toxicity if they must be paid for out of pocket.

A weak health system and an absence of knowledgeable healthcare providers can also stand in the way of timely cancer detection and diagnosis.

To close these gaps, routine screening, cancer diagnosis and referral services must be included in health insurance benefits packages.

UHC cannot be achieved unless everyone has access to affordable cancer care. At the same time, without the benefits offered by UHC, access to potentially life-saving screenings remains limited. This means someone may die of a cancer that could have been detected and treated at an earlier stage, but either an early detection programme was not available or that person could not access it, for financial or other reasons. A cost-efficient national cancer control plan with essential services – including routine screening and diagnosis – covered by national health insurance schemes available to everyone – can break down these barriers to accessibility, availability and affordability.

Indeed, often cancer treatment by national health insurance schemes but not screening. Issues of stigma that surround many cancer tests (for instance, those that concern sexual organs) therefore compound concerns about cost or fears of a diagnosis (e.g. cancer may be considered a death sentence, so why get tested?) to prevent high numbers of people getting a timely diagnosis, resulting in many patients presenting with late-stage cancers.

At the second High-level Meeting on Universal Health Coverage taking place on 21 September 2023, Governments are expected to adopt a set of new commitments to accelerate UHC implementation. This meeting will provide an opportunity for UICC to advocate for including comprehensive cancer prevention and control measures in UHC benefits packages.

In preparation for this pivotal meeting, UICC reached out to its members to learn about their concerns and inform its advocacy strategy in the lead-up to the UN HLM on UHC.

UICC is also organising a series of Virtual Dialogues intended to facilitate discussions around UHC and its impact on cancer control. The first dialogue organised in early May looked at UHC and prevention. A second Virtual Dialogue on UHC and early detection will take place on 20 July, and look at examples of successful advocacy to include screening and early detection in UHC benefit packages (for instance, mammography reimbursement in Algeria) and the use of legislation to support screening and early detection programmes and referral to treatment.

Read more :

https://www.linkedin.com/pulse/essential-cancer-screening-diagnosis-services-must-included-uhc-schemes%3FtrackingId=yU3y0j6Af4hHzyucBwUSyw%253D%253D/?trackingId=yU3y0j6Af4hHzyucBwUSyw%3D%3D

 

Digital and digital non-clinical solutions

➡️What will be the digital and digital non-clinical solutions for people with cancer in the future 🧐
This post aims to consider some possible digital solutions to bring medical resources and information to patients in the future.

➡️📱Mobile Apps: Mobile cancer apps can play a crucial role in patient education, symptom management and treatment monitoring.
These apps could provide information about cancer, medications, side effects, proper diets, as well as reminders for medications and medical appointments.

➡️⌨️Connected objects and wearables:
Wearable devices such as smart watches, bracelets and monitoring sensors could be used to monitor the vital signs of cancer patients in real time.

➡️Artificial Intelligence
(Al) and Data
Analytics: Al can be used to analyze large amounts of medical data and help identify patterns, correlations and predictions. This could contribute to a better understanding of risk factors,
treatment responses and patient
outcomes.

➡️Virtual Reality (VR):
Virtual reality can be used to help cancer
patients manage pain, anxiety and stress. Calming and interactive virtual environments can be created to distract patients during medical treatments or to help them relax during difficult times

For more just read: E-Health4Cancer : Sharing good practices in the use of nonclinical e-health solutions for cancer patients and their caregivers in Europe. Non-profit Organizations

https://www.linkedin.com/company/ehealth4cancer/

WHO/Europe explores collaborations to improve quality of health information online

The WHO Office on Quality of Care and Patient Safety in Athens recently joined forces with YouTube Health to host a workshop in Berlin to enhance the quality of health information online and support Member States’ efforts in this area. This collaborative endeavour lays the groundwork to promote health literacy and make high-quality health information universally accessible.

“We are very much looking forward to working together for a world where people can access the health information they need online without having to guess its accuracy,” noted Dr Natasha Azzopardi-Muscat, Director of WHO/Europe’s Division of Country Health Policies and Systems, at the workshop.

The role of digital platforms in health

The COVID-19 pandemic brought into the spotlight the prominent role of digital platforms in disseminating health-related information and the importance of reliable information, while also exposing the potential perils of misinformation and disinformation. Data indicates that, in the WHO European Region, a large share of consultations now take place online, as people’s initial approach is to search for symptoms and medical advice online. Health-related searches make up 7% of daily online searches, with approximately 4 billion results related to COVID-19.

In 2021, YouTube had over 110 billion views of health condition videos globally and is working on raising high-quality health content to make it easier for people to identify credible information that can help answer their questions. Commenting on the platform’s impact in the online space, Dr Nira Goren, Clinical Lead at YouTube Health, said, “People use platforms like YouTube to seek answers to questions, such as how do I live with breast cancer or how do I take care of myself.” An increasing number of individuals are also turning to online platforms to share personal stories, alleviate acute distress, and build a community to help decrease feelings of isolation.

However, online health information that is inaccurate or misleading can pose a significant risk to one’s health. A recent WHO review showed that infodemics and misinformation negatively affect people’s health behaviours. The distorted understanding of health hazards, such as smoking, alcohol intake, unhealthy eating habits, or physical inactivity, can result in various life-altering and potentially fatal noncommunicable diseases (NCDs), such as cancer or diabetes.

Empowering health through high-quality health information online

High-quality health information can empower individuals to take control of their health, make informed decisions about their treatment options, and improve their overall well-being and quality of life. With more and more people relying on the internet for medical advice, it is essential that the information available is reliable, accurate, easy to understand, and up-to-date. Collaboration with health care stakeholders in Member States across the Region is needed to ensure this. It also requires fostering inclusive partnerships that bring together patients, health care professionals, ministries, nongovernmental organizations, and major social media platforms.

“Social media platforms are crucial tools to improve and disseminate high-quality health information online and we should work on that together, involving everyone in this process. Our primary focus should be to actively listen to community concerns, promote understanding of risk and health expert advice, engage and empower communities to take positive action, and support health professionals and

Moreover, fostering trust in authoritative online health information sources at the population level entails working with academia and other partners to create further scientific evidence on the impact of misinformation on quality of care, acting as a lighthouse in consolidating the creation of scientific evidence.

“Empowering communities with education is essential to helping people live healthier lives. YouTube Health is delighted to interact with WHO and authoritative health sources across Europe to increase access to evidence-based, equitable and engaging health information,” noted Dr Garth Graham, Director and Global Head, Healthcare and Public Health, YouTube.

Πηγή: who.int

How A.I. Could Help Medical Professionals Spend Less Time on Admin Work and More Time on Care

Some entrepreneurs are betting that generative A.I. tech like ChatGPT can provide a solution to the medical industry’s burnout crisis.

A survey of 1,000 Americans and 500 health care professionals conducted by Tebra–an all-in-one digital platform used by medical providers to manage their practices–showed that one in 10 providers is currently using A.I., while 50 percent of surveyed respondents signaled an intention to adopt the tech in the future, particularly in use cases involving data entry, appointment scheduling, and medical research.

Luke Kervin, Tebra’s founder, says that if A.I. can help providers to stave off burnout by increasing efficiency, saving costs, and allowing them to spend less time on admin work and more time helping people, it will likely see mass adoption by the industry. “When we talk to our providers about what keeps them up at night, it’s always burnout,” adds Kervin, “and a lot of that burnout comes from having so much admin work to do.”

Ironically, the advent of electronic medical records (EMRs) was meant to help physicians save time that had previously been spent maintaining analog health charts, but some practitioners are now spending an increasing amount of time behind the computer. Indeed, a 2017 study published in the Annals of Family Medicine found that in an 11.4-hour workday, physicians spent an average of nearly six hours on tasks related to administrative tasks, like data entry and inbox management, which contributed to their burnout.
Some solutions are already available, such as from Microsoft-owned A.I. business solutions provider Nuance. According to a case study, physicians at the Nebraska Medicine health system were frustrated with the time and effort required to complete patient notes, so Nuance provided an A.I.-powered voice recognition solution, allowing providers to fill out notes using just their voice. The change was a success, with 94.2 percent of surveyed physicians saying that the tech helped them to save time and do their job better.

Another company working on A.I.-powered solutions for both providers and patients is New York-based mental health employee benefits company Spring Health, which has raised nearly $400 million and attained a $2.5 billion valuation since its 2016 founding. Once a client has signed up for the service, they fill out a short assessment containing a series of questions about both their medical history and the current state of their mental health. The company’s machine-learning algorithm then crafts a personalized care plan that includes both wellness recommendations like daily routines, and specific recommendations for nearby mental health care providers.

Spring Health co-founder Adam Chekroud says that they’ve barely begun to scratch the surface of how automation could improve business for health care providers, adding that the company recently rolled out a new functionality that enables providers to “translate” their shorthand notes from patient meetings into full sentences with the use of a large language learning model.

Chekroud is also excited about the possibility of integrating chatbots as a way of helping people find providers who are a perfect fit for them, and described one prototype in development. “Our chatbot could ask, ‘Is there anything you want us to know that would help us find you a provider?’” According to Chekroud, the patient could answer with something like, “I’m very religious and I want a provider who could do faith-based treatment” or “I’m going through some gender identity issues and I want to have a provider that understands that.” The chatbot would then scan through the Spring Health network to surface providers with those desired traits.

A small number of providers are even beginning to use A.I. to help them make diagnoses by using tools such as Med-PaLM, Google’s large language model for medical information. But when it comes to using chatbots as virtual therapists, Chekroud is much less convinced. He concedes that generative A.I. is surprisingly capable of imitating empathy, “but we still have this fundamental problem that you’re talking to a robot. A robot can’t know what you’re going through. Nothing can replace that human connection.”

Πηγή: inc.com