Beyond COVID-19: How will ‘Digital Health Innovation (DHI)’ grow and evolve in the Post-Pandemic era?

I would like to dedicate this blogpost to our fearless Doctors, Clinicians, Nurses, Technicians and First Responders in the US of A and across the World, as they put their health and their lives at risk to heal and save the rest of us, in the days and weeks ahead – God bless them!

Introduction

We find ourselves in unprecedented times indeed! The deleterious and catastrophic impact of the COVID-19 novel Coronavirus Pandemic from both a public health and an economic perspective will stay with us for a long, long time to come! Matter of fact, going forward, we will likely refer to the “pre-Pandemic era” and “the post-Pandemic era”, given the unforgettable impact to our lives, our careers and our collective psyche!

I have articulated the 12 most urgent challenges and imperatives confronting healthcare providers in my recent blogpost [Ref 1], ‘#COVID19, #HIMSS20 and the Digital Transformation of Healthcare’, which has received positive feedback from practitioners across providers, payers, bio-pharma, medical devices and diagnostics.

Some of these unforeseen and unprecedented challenges which are morphing Healthcare into “the only capacity-constrained industry”, are culminating in devastating consequences manifested in these striking, appalling vignettes that we will never forget:

Nurses constrained to wear trash bags in the absence of needed Personal Protective Equipment (PPE). Source: the New York Post [Ref 4]

• The shocking and devastating deaths of physicians, clinicians, nurses, technicians, and first responders who are being afflicted with COVID-19 from engaging with infected patients, resulting in shocking, demoralizing deaths and fatalities – over 60 doctors died in Italy last month, and over 100 across the world while treating COVID-10 patients [Ref 2]!
• Doctors and nurses in NYC constrained to make excruciating, gut wrenching decisions on which patients with COVID-19 complications severely impacting their respiratory systems, get an ICU/ER bed with a ventilator, given that the number of these high-risk patients far outnumber the number of ICU/ER beds with ventilators [Ref 3]!
• Nurses and technicians in the US and in the UK, two of the most developed and affluent countries on the planet, constrained to wear trash bags to protect themselves from infection, given a shortage of personal protective equipment (PPE), masks, gowns and gloves [Ref 4]!

"Many of the changes in Healthcare Delivery enabled by Digital Health Innovation (DHI) which are astronomically growing in the wake of COVID-19 as we speak, will not only persist but also grow incrementally in the post-Pandemic "new normal" when 'Social Distancing' morphs into a distant memory!"

It is my humble assertion that many of the changes re: screening, diagnosing and treating patients leveraging ‘Digital Health Innovation (DHI)’ which I have highlighted in my previous blogpost [Ref 1], ‘#COVID19, #HIMSS20 and the Digital Transformation of Healthcare’, will not only persist beyond the pandemic, but grow incrementally in the ‘Post-Pandemic era’ when 'Social Distancing' is a distant memory (the "new normal"), given the measurable benefits for patients, providers, physicians, providers and policy makers.

These measurable benefits include:

1.   Higher levels of safety for patients (especially high-risk patients) and physicians, nurses and technicians treating them while assuring better patient outcomes

2.   Lower cost of healthcare delivery while assuring quality and safety, inviting competitive reimbursement from both payers and the government

3.   Mitigating risk of 30 and 90 day re-admissions, denials and loss of revenue while ensuring the best possible patient outcomes from the treatment

4.   Optimal utilization and return on investment (ROI) on constrained, high value resources like ICU and ED beds, and medical equipment like ventilators and complementary medical devices and diagnostic equipment

5.   Higher levels of Disease / Pandemic outbreak readiness as well as responsiveness to ensure that the unforeseen and shocking vignettes articulated in the previous section can minimized or precluded.

Strategy Blueprint: How will ‘Digital Health Innovation (DHI)’ grow and evolve in the post-Pandemic era?

Figure 1. Strategy Blueprint - The five (5) Digital Health Technologies and Capabilities which will grow and evolve in the post-Pandemic era. Copyright Andy Dé. All rights reserved.

In the figure above, I have modified and adapted this strategy blueprint from a seminal article entitled, ’Eager Buyers and Stony Sellers – Understanding the Psychology of New Product Adoption’ by John T. Gourville, Harvard Business Review (HBR), [Ref 5], to craft this 2X2 Strategy Matrix to articulate 5 (five) innovative and promising Digital Health technologies and capabilities that are astronomically growing over 2020-21, and will continue to grow in adoption even when 'Social Distancing' will become a distant memory in the post-Pandemic era.

The X-Axis maps ‘Patient resistance to Digital Health adoption’ high to low while the Y-Axis maps the ‘Change in Behavior needed from the other key stakeholders in healthcare such as Physicians, Providers, Payers, Policy Makers and the Government (given that it is by far the largest payer for healthcare services today) from high to low.

The Predictive Power of this Matrix can be leveraged as follows:

* Upper Right Quadrant – low patient resistance to adoption with low change in behavior required from other stakeholders like physicians and providers can be prognosis for “Smash Hits” – technologies like Telehealth, Telemedicine, Remote Patient Monitoring, and associated medical devices and instrumentation and analytics

* Upper Left Quadrant – relatively high patient resistance (demands some effort) to adoption but demanding low change behavior from other Stakeholders is classified as “Easy Sells” – technologies like wearables and medical devices and apps to capture vital sign data from Patients with manual/automated entry into patient portals.

* Lower Right Quadrant- low patient resistance to adoption demanding high changes in behavior from other healthcare stakeholders like providers, physicians and payers signify “Long Hauls”- investments in next generation analytics and artificial intelligence (AI) including machine learning, deep learning, natural language processing (NLP) and robotics that will enable predictive and prescriptive analytics capabilities across the healthcare enterprise.

* Lower Left Quadrant – high patient resistance to adoption with high changes in behavior required from other key stake holders is a non-starter or recipe for “Sure Failures” and little to no potential traction. Key message – proceed here at your own peril and risk!

The key premise is that the greater the change in behavior needed (physicians, nurses, providers, payers and policy makers), to deliver new products or services, the greater the barrier to customer (patient) adoption, despite the promise of value delivered by the new product or technology. Professor Gourville drives home the point that producers of innovation often overestimate the customer adoption by a factor of 3X while consumers allocate significant value to their current product or service and demand a value proposition that is practically 9X times that offered (perceived) by their current product or service.

Let us leverage this strategy framework to map the 5 innovative and disruptive Digital Health technologies and capabilities which are not only growing astronomically as we speak, but are here to stay for the long term even after the COVID-19 pandemic is a distant memory. Matter of fact, I predict that these five technologies will be segments of astronomical growth that will contribute to the overall growth of the healthcare and life sciences industry, unlike every other industry that will be demand constrained over the Pandemic and beyond.

1. ‘SMASH HIT’: Telehealth for screening, triage and follow on appointments

Telehealth is growing astronomically as we speak at a 300-500% growth rate given the advent of COVID-19 and is here to stay beyond the pandemic [Ref 6]. Seniors above 65 years as well as patients with chronic conditions like Cancer, Chronic Obstructive Pulmonary Disease (COPD), Cardiovascular disease etc. are most vulnerable to death if afflicted by the COVID-19 virus and are also locomotion challenged. Leveraging Telehealth to diagnose and treat them remotely for conditions that are not acute, will lower risks of infection for both these vulnerable patients as well as care givers.

Just how much things have changed dawned on me this week when my face-to-face visit with my endocrinologist at Baylor Scott and White was changed to a tele-health visit 48 hours prior! Since the embedded tele-health app within their Epic Patient Portal did not work as expected, the engagement was facilitated over FaceTime which worked well, especially since I was doing really well at managing my conditions and at monitoring my vital signs – guess this will likely be a way of life for ‘Patients like me’ in the foreseeable future. The conclusion of my Telehealth call triggered an email informing me that I had been charged for my co-pay and my Health Plan for the balance, which was fairly reassuring and also signaled a high level of healthcare IT competence.

Primary care physicians and specialists are also turning to Telehealth for their regular clinic visits as patients self-quarantine to stem the spread of the coronavirus.

Washington based Providence St. Joseph’s Health was among the first to treat COVID-19 patients and reported that virtual visits increased 20 to 30-fold in the first few weeks of the pandemic [Ref 6]. The system reported confusion around billing for the virtual visits, and it had to act quickly to spread the correct coding and billing information.

New York is one of the hardest-hit states with COVID-19 cases, and demand for Telehealth services has increased 312 % amid the pandemic. Stony Brook (N.Y.) University Hospital has seen an increase in demand for telecommunications within the hospital and is in search of resources to support those visits. Stony Brook University Hospital has asked community members to donate iPads to connect inpatients to their providers and families. IT is in need of around 100 iPads as of March 25 [Ref 6].

This astronomical adoption of Telehealth to screen, triage and treat patients especially seniors and those with chronic conditions is here to stay and is being supported by new regulations and new CMS and payer supported reimbursement models according to industry leaders like Dr. Eric Topol and other healthcare practitioners [Ref 7 & 8].

But are patients open and receptive to embracing Telehealth as a medium to engage with their PCPs and specialists, as well as care coordinators and care teams, which is critical to long term adoption and sustenance?

According to a recent survey by Amwell (formerly American Well) [Ref 9] consumers remain interested in Telehealth, with 66% reporting they are willing to use it. Unsurprisingly, the younger demographics are most open to Telehealth, with 74% of 18-34-year-olds and 72% of 35-44-year-olds saying they are willing to use it. While the senior population has the lowest interest overall, 52% of seniors are still open to using Telehealth.

That means that of the 47.8 million Americans over the age of 65, 24.85 million are willing to use Telehealth, which makes this a “Smash Hit” already.

Hospitals and Health Systems that would like to adopt and scale Telehealth across their systems will need to think thru the following challenges from an IT and Analytics perspective:

• Segmenting the attributed population based on risk (seniors above 65, those with chronic conditions like Cancer, heart disease and COPD) to identify them as candidates for Telehealth engagement pre-admission or post-discharge, while validating their eligibility and coverage – leverage data from the EMR and Rev. Cycle Management systems with predictive analytics using machine learning to do so.
• Demand-Supply Matching of Patients with Providers: Telehealth’s sweet spot is following on routine appointments for Diabetes, Cardiovascular disease, COPD, Neurology etc. especially for patients in far flung areas, as well as Tele-ICU where ICU doctors are not available. A key analytics challenge is matching each patient with the appropriate physician or clinician to ensure the best outcomes with machine learning and scheduling algorithms, while also allocating capacity for emergency/ on-demand engagement.
• Billing, Coding, Denials and Reimbursement: Large healthcare systems that have standardized their clinical and RCM processes on Epic, Cerner, AllScripts, Athena Health etc. can potentially handle most of these digitally on one EMR. For smaller hospitals, with fragmented processes, aggregating data from these disparate systems and running analytics re: inaccurate coding, denials, payers who do not reimburse at pre-contracted rates etc. will be critical
• Benchmarking Performance by User Group and across Providers: monitoring, analyzing, measuring, reporting and benchmarking impact on patient outcomes and cost of care delivery across user groups (Diabetes vs. Cardiovascular vs. COPD for instance) and across multiple providers within the same Healthcare Systems, or against thought leaders like the Mayo Clinic, the Cleveland Clinic, Providence Health and Intermountain Healthcare is critical to success and enable continuous improvement.

2.   ‘SMASH HIT’ – Remote Patient Monitoring (RPM) and Analytics for Care Teams and Clinicians

Like Telehealth, Remote Patient Monitoring (RPM) adoption is exploding as we speak and will be here to stay in the post-Pandemic era. For high risk Seniors, patients with chronic diseases like Cancer, COPD, cardiovascular diseases, diabetes with complications and kidney disease, having care coordinators leverage RPM to reduce the number of office visits by patients, while still receiving substantial compensation from CMS presents a sustainable opportunity for healthcare providers to reduce 30 and 90 day re-admission risk, while assuring better patient outcomes.

Innovative and disruptive RPM systems help care teams monitor, manage and engage patients in the comfort of their homes, which contributes to reducing cost, mitigate risk while improving outcomes and increasing reimbursements.

These systems continuously stratify patient risk via Artificial Intelligence (AI) driven algorithms and alerting, empowering care teams with optimal windows of opportunities to intervene, when needed. Automated visual/audio reminders and phone calls enable higher patient engagement, medication adherence, with integration with Telehealth, and virtual video conferencing and visits which enables rapid patient health assessment, optimized for various chronic diseases.

According to a 2019 Spyglass Consulting report referenced in a recent article in Healthcare IT News [Ref 6], over 88% of hospitals in the US have plans to invest in RPM in 2020, which have been accelerated in the wake of the Pandemic, validating my assessment that RPM, like Telehealth is a “Smash Hit” that will grow and see significant adoption post-Pandemic.

In addition to the IT and Analytics needed for Telehealth as above, hospitals adopting RPM at scale will need a modern, next-gen RPM system which will enable them to:

• Add new patients in minutes without any hassles
• Ships all in-home monitors, devices and equipment directly to patients
• Operates on both WI-FI and cellular connectivity
• Captures and records patient vital signs data automatically, or with minimal effort
• Provides a web-based portal, or integrates with the Healthcare systems Patient Portals
• Triggers automated alerts to patients (reminders) and to the care team via text, email or calls
• Enables coordination with UBER, LYFT or cab services to transport mobility challenged patients to hospitals and clinics to comply with scheduled appointments
• Enables easy integration with self-service analytics platforms for healthcare systems to capture and aggregate the RPM data from their high-risk patients and integrate this with the data from the EMR, Revenue Cycle Management (RCM) and other Healthcare IT systems, to enable a 360-degree view and insights of their Patients

3.   ‘SMASH HIT’ – Pandemic / Disease Outbreak Readiness Monitoring and Response Center

Figure 2. The Live COVID-19 Dashboard delivering insights on the number of COVID-19 induced cases and deaths across the world, by country. Source: The Center of Systems Science and Engineering at the Johns Hopkins University.

A key challenge experienced at a national, state and at a local level was the lack of readiness to the Pandemic which culminated in the crisis situation on a state by state basis with hospitals in hard hit areas being completely overwhelmed!

Going forward, thought leaders in healthcare will institute a Pandemic and Disease Outbreak Readiness Monitoring and Response Center as part of their strategic, scenario and policy planning initiatives even at a health system level. Equipped with data streams from the CMS, HHS etc. and leveraging self-service analytics platforms and visual analytics tools, these leaders will stand up a War-room(s) with dashboards that will not only monitor disease and epidemic outbreaks in other parts of the world, but will also provide actionable insights via visual analytics dashboards (see figure 2 above) which will proactively, monitor, analyze and measure both the demand as well as the supply side implications as below:

• Estimating and monitoring vulnerable segments in the attributed population (seniors over 65, patients with chronic diseases like cancer, COPD, cardiovascular disease etc.) who have a high risk of being infected by the disease or pandemic
• Projecting (what-if and scenario analysis) the number of total hospital beds as well as the constrained capacity of ICU and ER beds that will be needed to deal with a potential outbreak, as well as the ability to deploy additional buffer capacity, if needed
• Monitoring the number of usable ventilators and vital signs monitoring medical devices and equipment on hand, potential shortfall, as well as sources like state and national stockpiles from where these can be resourced in an emergency
• Securing at least a 100-day buffer supply of Personal Protective Equipment (PPE), masks, gloves and protective gear mission-critical to protect doctors, nurses, technicians and first responders from infection while screening and treating patients afflicted with an infectious or contagious disease or epidemic

4.   ‘EASY SELLS’ – Cloud and Patient Portals compatible AI and mHealth Apps offering Data Capture and Recording of Vital Signs

One of the biggest barriers triggered by the COVID-10, was the availability of test kits to detect the novel corona virus infection in patients. Further exacerbating this serious challenge was that it took 10-20 days to capture samples, process and send them to the diagnostics vendors (who were overwhelmed by the volumes) and then waiting for the results to return and then communicate those to patients. Many patients who were in fact positive deteriorated and often had to be admitted to ICUs and ERs further overloading these hospitals, given their constrained capacity of ICU/ER beds with ventilators as well as testing kits, drugs, devices and therapies to treat these patients.

Happily, leaders as well as disruptive start-ups in the healthcare industry have responses to this dire crisis with a plethora and portfolio of cloud based AI powered apps deployable in mobile devices and tablets (mHealth) many of which can capture and record vital signs onto patient portals for instant access by care teams and clinicians.

Perhaps the most impactful innovation given the massive shortage of testing kits for the COVID-19 and the days it takes to get back test results is the 5-minute COVID-19 Test from Abbott Labs. Abbott Labs has received emergency use authorization (EUA) from the U.S. Food and Drug Administration (FDA) for the fastest available molecular point-of-care test for the detection of novel coronavirus (COVID-19), delivering positive results in as little as five minutes and negative results in 13 minutes [Ref 11].

Apple released a new screening tool and set of resources to help people stay informed and take the proper steps to protect their health during the spread of COVID-19, based on the latest CDC guidance. The new COVID-19 website, and COVID-19 app available on the App Store, were created in partnership with the CDC,1 the White House Coronavirus Task Force and FEMA. [Ref 12]

Medtronic’s COVID-19 Virtual Care Evaluation and Monitoring Solution uses a virtual assistant to evaluate patients thru a CDC guideline survey for COVID-19 symptoms, while the Respiratory Infectious Disease Health Check helps patients with chronic, co-morbid health conditions who are at the highest risk for complications or mortality associated with COVID-19 track their respiratory infectious disease symptoms and body temperature through daily health checks. 

The program reacts dynamically during the health check to present symptom questions based on the patient’s previous responses and provides patient education to encourage and support self-care. Data is aggregated for clinician review and action if additional intervention is needed. [Ref 13].

Besides Abbott Labs, Medtronic and Apple, healthcare leaders like the Cleveland Clinic in partnership with Microsoft and startups like Buoy Health have developed and rolled out chat bot based COVID-19 screeners [Ref 14]. Many other startups have developed AI driven apps to screen both patients and care givers for signs of COVID-19, proactively detect and segregate patients infected with the corona virus from those who are not, predict which patients will likely develop complications and deteriorate demanding an ICU with a ventilator, and also monitor patients post discharge, detailed in a compelling STAT article [Ref 14].

It is my humble prediction that given the new regulations from the FDA as well as new CMA reimbursement models which has spurred this innovation in the wake of COVID-19, we will see an explosion of new AI powered cloud-based apps and mHealth devices for proactive screening, testing, analysis, monitoring, capture and recording of vital signs integrated with current Patient Portals. These will include electronic thermometers, pulse oximeters, blood pressure, blood sugar and respiratory disease vital sign monitoring.

Real-World Case Study: As an e-Patient (empowered patient), I have personally embraced continuous glucose monitoring (CGM) using the Abbott Labs Free Libre 14-day CGM system, with a coin sensor I wear on my arm, and capture my sugar levels using an app running on my iPhone on a 24x7 basis, as shown above. Not only does this enable me to monitor, calibrate my diet and control my blood glucose levels, but also communicate and instantaneously share my reports and charts with my endocrinologist, ensuring fact based and data-driven consultations and engagement.

I am happy to share that this data and insights driven collaborative approach with my endocrinologist has actually helped me 'flatten my glucose curve' which I have detailed, with an overview of other innovative products and services re: diabetes monitoring, management and improvement in my recent blogpost, ‘How will AI and Analytics empower Patients to monitor, manage and even reverse Chronic Diseases like Diabetes?’ [Ref 15]

5.   ‘LONG HAUL’ – Artificial Intelligence (AI) and Analytics Investments to enable Predictive and Prescriptive Analytics Insights across the Healthcare Enterprise, including Medical Robotics

In my previous blogpost, ‘The Convergence of Artificial Intelligence (AI) and Data Analytics and its implications for Healthcare Providers and Payers’,  [Ref 16] I had predicted the convergence of AI (comprising machine learning, natural language processing (NLP), deep learning and robotics) and Analytics to drive measurable improvements in business, clinical and patient outcomes. This has also been validated in a recent research survey ‘Data Analytics in Healthcare’ by HIMSS Media. [Ref 16]

There are significant barriers (hence qualified as a “Long Haul”) to adoption identified by the research, including working with unstructured data and collecting data from diverse, disparate sources, investing enough resources in AI, and optimizing/automating analytical models. [Ref 16]

Despite these challenges, leaders in healthcare see tremendous potential in AI and Analytics to deliver on the promise of higher quality care at a lower cost by empowering their executives, business leaders, clinicians and nurses by harnessing the power of predictive and prescriptive analytics. Many healthcare organizations are seeking to harness the vast potential of Artificial Intelligence (AI) and its four components — machine learning (ML), natural language processing (NLP), deep learning, and robotics — to transform their clinical and business processes. They seek to apply these advanced technologies to make sense of an ever-increasing ‘Tsunami’ of structured and unstructured data, and to automate iterative operations that previously required manual processing. Matter of fact, the Social Distancing imperative imposed by the COVID-19 novel corona virus has also seen the advent and deployment of Medical Robots for novel, out-of-the-box applications, ranging from capturing vital signs from Patients, acting as a Telehealth medium or intermediary, to serving them food and medicine (photo below) - a promising area of AI Innovation whose time has come. [Ref 18 & 19]

Here is my prognosis of 20 innovative use cases where healthcare care leaders will be deploying AI (machine learning, NLP, deep learning and robotics) + Analytics over 2020-21, to empower their executives, line of business (LOB) leaders, physicians, clinicians, nurses, analytics and data scientists with predictive and prescriptive analytics powered proactive and actionable insights to enable superior business, clinical, patient and population health outcomes:

1.   Proactively identifying Patients at risk for adverse health events like heart failure and heart attacks, as well those most at risk of being impacted by infectious and contagious diseases and epidemics

2.   Predicting patient utilization patterns (e.g. missed appointments and optimizing inpatient / clinical throughput)

3.   Population health stratification including risk scoring for chronic diseases like cardiovascular disease, COPD, diabetes and cancer

4.   Projecting (what-if and scenario analysis) the number of total hospital beds as well as the constrained capacity of ICU and ER beds that will be needed to deal with a potential outbreak, as well as the ability to deploy additional buffer capacity, if needed

5.   Monitoring the number of usable ventilators and vital signs monitoring medical devices and equipment on hand, potential shortfall, as well as sources like state and national stockpiles from where these can be resourced in an emergency

6.   Predicting demand for Telehealth and Remote Patient Monitoring services and then mapping and matching with physicians, clinicians, nurses, care-coordinators and technicians to meet the demand and assure superior outcomes

7.   Blending data from multiple EMRs, standardize curated data sets to secure a ‘single version of the truth’ re: the patient

8.   Enabling a 360-degree view of the patient for clinicians and nurses at the patient bedside with predictive analysis that will alert clinicians and nurses on deteriorating conditions

9.   Advancing Precision Medicine and personalized treatment of patients predicated on an analysis of genomic profiles and mapping, comparing and contrasting these to the mainstream population of that country or continent, with gap identification triggering proactive treatment [Ref 17]

10. Improving supply chain management (SCM) efficiencies, including predicting stock outs for drugs, devices, life-saving equipment like ventilators and supplies as well as expired drugs, while saving $ MM

11. Proactively identifying and mitigating cybersecurity risks, including medical fraud

12. Identifying and classifying anomalies and imaging and incidental findings from automated scanning of X-ray, MRI and CAT scans, to proactively alert radiologists on patients at risk of a cardiovascular event like heart attack or stroke, for instance

13.  Proactively detecting fraud, waste and abuse pertaining to employee overtime and agency costs

14.  Minimizing issues with reimbursement and payments including fraud, waste, abuse

15. Ensuring ICD-10 coding and billing accuracy given new protocols, testing kits, instruments, devices, and supplies

16. Predicting denials, identifying root causes and managing these to revenue realization

17. Forecasting demand for all levels of staff needed to meet growth projections, and matching demand with supply of doctors, nurses, and technicians from known sources, as well as tapping into pools of retired doctors and nurses, as well as soon to graduate MDs and nurses to meet unforeseen demand when disease/Pandemic outbreaks happen.

18. Predictive analytics on cellphone data and sentiment analytics to identify disease outbreaks and hotspots for Pandemics, which was done in China recently.

19. Medical Robots for capturing vital signs like temperature (touch-less sensing), pressure and glucose levels, as well as those for serving food, medicine, and applying bandages to patients (photo above), ensuring minimal contact in the event of contagious and infectious diseases [Ref 18 & 19]

20. Automating Executive and Performance Dashboards delivering key metrics and performance indicators instituted by senior executives, and then cascading these across the enterprise with complete transparency on performance against company and department targets, like the 'Balanced Scorecard' system with its origins from Harvard Business School (HBS) that is now ubiquitous across other industries [Ref 20]

In closing...

The unforeseen disruption triggered by COVID-19 is inducing unplanned growth across Healthcare which finds itself capacity constrained vs. just about every other industry which unfortunately find themselves demand constrained and will likely undergo contraction post Pandemic! Healthcare however will continue its expansion beyond the Pandemic and key changes in healthcare processes, protocols and technologies accelerated by COVID-19, will persist and continue to expand even after the crusade against the Pandemic has been won!

In this blogpost, I have endeavored to analyze and highlight five (5) innovative, disruptive, and promising ‘Digital Health’ Technologies and Capabilities which are not only growing astronomically in the wake of COVID-19 novel corona virus, but will also find incremental adoption in the post-Pandemic era, to impact patient screening, triage, engagement and outcomes. I have analyzed and calibrated these technologies leveraging a seminal strategy framework from Harvard Business School Professor John Gourville, predicated on the resistance to patient adoption, as well the degree of change behavior needed from physicians, clinicians, nurses, providers, payers, policy makers and the government, which will likely assure a high probability of success, in my humble opinion and will inform post-Pandemic strategy blueprints and scenario+ policy planning from these entities and stakeholders.

My concluding questions for you….

• Was this post-Pandemic strategy blueprint and my analysis useful for you and your organization?
• What have I missed in this analysis and strategic blueprint that is top of mind for you in these trying times and for the foreseeable future?

As always, I welcome your comments and feedback here on this blogpost, and on Twitter at @HITstrategy. 

Disclaimer: The perspective and views expressed in this Blog post are my own and do not represent those of my current or previous employers.

#postCOVID-19 #PostPandemicStrategy #ArtificialIntelligence #AI #mHealth #HealthcareAnalytics #Telehealth #Telemedicine #RemotePatientMonitoring #AIAnalyticsConvergence #Clinical #PopulationHealth #ACO #HealthcareQuality #EvidenceBasedMedicine #PrecisionMedicine #PersonalizedHealthcare #CareCoordination #ValueBasedCare #AnalyticsProcessAutomation

References

1.  ‘#COVID19, #HIMSS20 and the Digital Transformation of Healthcare’, blogpost by Andy Dé , March 2020.

2.  ‘Over 100 Doctors and Nurses have died combating Coronavirus across the World’, Soo Kim in Newsweek, April 3rd, 2020.

3.  ‘How Hospitals will decide who lives and who dies in the COVID-19 crisis’, Robert Klitzman in the Hill, March 29th, 2020

4.  ‘Nurses at NYC Hospital receive gowns after trash bag expose’, Carl Campanile and Ebony Bowden, New York Post, April 2nd, 2020.

5. ’Eager Buyers and Stony Sellers – Understanding the Psychology of New Product Adoption’ by John T. Gourville, Harvard Business Review (HBR), June 2006.

6.  ‘What happened at 4 health systems when Telehealth demand spiked’, Laura Dyrda in Becker’s Hospital Review, March 26th, 2020.

7. ‘Dr. Eric Topol: Why remote healthcare will be here to stay after COVID-19’, Becker’s Healthcare Review, April 1st, 2020.

8.  ‘COVID-19 is a hurricane, changing the landscape of medicine forever’, Dr. Sylvia Romm, MD, MPH, Chief Innovation Officer at Atlantic Health System, Linked-In Blogpost, April 2nd, 2020.

9.  Amwell’s Telehealth Index: 2019 Consumer Survey, 2019. Source: Amwell Inc.

10. ‘Remote Patient Monitoring (RPM) to gain big momentum in 2020’, Nathan Eddy in Healthcare IT News, January 21st, 2020.

11. ‘Detect COVID-19 in as little as 5 minutes’, Abbott Labs Press Release, March 27th, 2020

12. ‘Apple releases new COVID-19 app and website based on CDC guidance’, Apple Press Release, March 27th, 2020. 

13. ‘Medtronic expands respiratory remote monitoring solutions in fight against COVID-19’, Medtronic Press Release, March 27th, 2020.

14. ‘STAT’s guide to how Hospitals are using AI to fight COVID-19’, Casey Ross, Rebecca Robbins and Erin Brodwin, STAT, March 31st, 2020.

15.  How will AI and Analytics empower Patients to monitor, manage and even reverse Chronic Diseases like Diabetes?’, blogpost by Andy Dé, April 2019.

16. ‘The Convergence of Artificial Intelligence (AI) and Data Analytics and its implications for Healthcare Providers and Payers’, blogpost by Andy Dé , February 2020.

17. 'Precision Medicine and Population Health Management (PHM)', blogpost by Andy Dé , August 2016.

18. 'How Hospitals are using Artificial Intelligence (AI) to battle COVID-19' by Kelly Wittbold, Colleen Carroll, Marco Iansiti, Haipeng Mark Zhang and Adam B, Landman, Harvard Business Review (HBR), April 3rd, 2020.

19. 'The COVID-19 Pandemic is a Crisis that Robots were built for', Matt Simon in Wired Magazine, March 25th, 2020.

20. ‘The Balanced Scorecard – Measures that drive Performance’ by Robert S, Kaplan and David P. Norton, Harvard Business Review (HBR), January-February 1992.

Additional Relevant Reading from Health Science Strategy Blog:

1. 'Beyond COVID-19: How will Medical Robots enable Digital Patient Engagement' in the Post-Pandemic "New Normal"?
2. ‘Beyond COVID-19: How will ‘Virtual Healthcare Delivery’ enable ‘Digital Patient Engagement’ in the Post-Pandemic “New Normal”?
3. Beyond COVID-19: How will Healthcare Providers treat their “Financial Epidemic” and resuscitate their Revenue and Profit Margins?’ 
4. ‘Beyond COVID-19: How will Healthcare Providers leverage AI and Analytics to minimize “Supply Chain Disruption” in the post-Pandemic era?’ 
5. ‘#COVID19, #HIMSS20 and the Digital Transformation of Healthcare’