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COVID-19 and its Impact on Healthcare and Public Health

Technology   |   Andy Dé   |   Apr 7, 2020

For healthcare providers and public health, the novel coronavirus (COVID-19) pandemic is creating unprecedented challenges — from disrupted supply chains and the inability to adequately protect patients and healthcare personnel, to a massive shortage of capacity, personnel, drugs, devices, testing kits, and supplies.


Here, I articulate 12 primary and urgent challenges (by no means exhaustive) confronting hospitals, health systems, and public health agencies which is driving unprecedented strategic digital transformation, now and in the foreseeable future.


1. Track Pandemic/ Disease Outbreak, deploy surveillance and enable rapid response


Challenge: Aggregating, transforming, and reporting on data pertaining to the outbreak of a disease or a pandemic like COVID-19 is mission-critical to tracking the outbreak, surveillance, and the rapid response to contain the spread.


The Center for Systems Science and Engineering at John Hopkins University has launched a live dashboard that pulls data from the World Health Organization (WHO) — as well as the Centers for Disease Control (CDC) in the U.S., China, and Europe — to show all confirmed and suspected cases of the coronavirus, along with recovered patients and deaths. The data below is visualized through a real-time graphic information system (GIS).



Prognosis: Healthcare providers and health systems will proactively collaborate with the CDC, HHS, and CMS to ensure that the plan for similar and unforeseen disease, epidemic or pandemic outbreaks as part of their strategic planning process to ensure that they will act on advance intelligence and not be caught off guard, as was the case with the COVID-19 outbreak.


2. Identify and Secure Buffer Facilities and Locations for Additional Hospital Beds, Especially ICU, ER, OR, and Observation Rooms


Challenge: Healthcare systems in large metros are facing prospects of not having the needed ER, OR, and observation rooms to deal with the surge of patients infected with COVID-19.


Prognosis: Strategically identify additional facilities that can be used for additional capacity in the event of a surge will spell the difference between lives lost and saved when the surge strikes.


3. Recruit Retired or Soon-to-Graduate Physicians, Nurses and Technicians

Challenge: Given the surge of COVID-19 patients are exceeding capacity, providers do not have enough doctors, nurses and technicians to diagnose and treat them.


Prognosis: Hire retired clinicians and nurses to meet this need and help alleviate the burden while potentially saving lives. Enabling fast track immigration from countries like India and the rest of Asia is also under consideration, as 20% of all U.S. medical professionals and nurses are of Indian origin, despite people of Indian origin constituting less than 3% of the U.S. population today.


4. Proactively Identify the Most At-Risk Patients and Segments in the Population

Challenge: Healthcare providers are challenged to segment non-COVID patients from those infected with COVID-19, and also stratify these patients based on risk (e.g. seniors over 65 and those with chronic conditions like cancer, Chronic Obstructive Pulmonary Disease (COPD), and cardiovascular disease.)


Prognosis: Risk-stratify patients based on demographics, electronic medical records (EMR), and socio-economic determinants of health to proactively identify the most vulnerable patients who are most at-risk for preferential treatment to save lives.


Adopting both descriptive analytics, predictive analytics, and leveraging machine learning and natural language processing (NLP) is imperative to enabling a risk-based approach to population health segmentation and ensure that the most at-risk patients can be proactive identified for advanced clinical protocols needed to assure optimal patient outcomes.


It is indeed encouraging to see leaders like Apple and Medtronic offer just-in-time (JIT) solutions to enable seniors and at-risk patients to diagnose their condition and risk of COVID-19 in collaboration with their care teams. Even more compelling is the Abbott Laboratories COVID-19 test which can deliver positive results in as little as five minutes.


5. Proactively triage At-Risk Patients via Telehealth/Telemedicine Before or at Admission

Challenge: Seniors (above 65) as well as immunocompromised patients are most vulnerable to death if afflicted by the COVID-19 virus. Additionally, these populations are often locomotion-challenged and struggle to access healthcare.


Prognosis: Leverage telehealth/telemedicine to triage, diagnose and treat them remotely for conditions that are not acute will lower risks of infection for both these vulnerable patients as well as caregivers.


As I’ve discovered from personal experience, many health systems require patients experiencing mild symptoms, or those exposed to individuals with confirmed cases of COVID-19, to use virtual visits to check in with their providers. 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.


6. Proactively Manage Employee (Clinician, Nurses & Tech) Health, Safety, And Burnout

Challenge: Doctors, nurses, and technicians are incredibly stressed and overworked as they try to meet the demands triggered by the surge, and often without the necessary personal protective equipment (PPE), masks, gloves etc., to keep themselves safe.


Prognosis: Protecting healthcare providers from infection and burnout will be key to success. Monitoring their mental and physical state of readiness while having access to recuperation rooms as well as additional staff to meet the surge-triggered demand will maximize staff availability to response to the surge. Predictive analytics will be key to enabling these insights.


7. Maximize ED, OR, and Observation Room Utilization & Patient Throughput

Challenge: Given the anticipated surge of COVID-19 patients, many hospitals are/will be severely capacity constrained on their ICU, ED, OR, and observation rooms, as well as lack ventilators for their ICU beds.


Prognosis: Planning for this surge with the flexibility to repurpose hospital beds into ED beds with additional ventilators and medical devices and diagnostic equipment will be critical for saving lives. Analytics to enable this demand-supply matching will be critical.


8. Accurately Forecast Demand for Critical Drugs, Devices, Vaccines, Masks, Personal Protective Equipment (PPE) & Supplies for Medical Personnel

Challenge: The COVID-19 pandemic is presenting unprecedented and unforeseen challenges in terms of medical staff, equipment, protective attire, drugs, and devices for hospitals.


Prognosis: Leveraging the demand data from previous epidemics (H1N1, Ebola, etc.) to forecast demand for COVID-19 with predictive analytics will potentially help address the huge shortages anticipated. Incorporating the demand data from this pandemic within your ERP or supply chain planning system, augmented with advanced predictive analysis, will drive the level of readiness needed to deal with the next disease outbreak or pandemic in the foreseeable future.


9. Manage and Balance Supply Chain Disruption

Challenge: Hospitals are struggling with the process of identifying and securing new suppliers for masks, testing kits, PPE, gloves etc., while managing their current supply chain. Additionally, maverick (off-contract) buying is a huge challenge facing healthcare providers today, which will likely be exacerbated by the pandemic.


Prognosis: Hospitals need to collaborate with entirely new suppliers and create new supply chains for ventilators, masks, personal protection equipment (PPE), COVID-19 testing kits etc., while managing and balancing this with their existing supply chain to meet the needs of patients not afflicted by COVID-19. Also, leveraging self-service analytics to integrate data from ERP, EMR, and procurement to pinpoint maverick buying will save hospitals millions.


10. Stratify Admitted Patients Based on 30 Day Re-admission Risk Leveraging Predictive Analytics

Challenge: Given the surge on many hospitals triggered by the large numbers of patients who are infected with the COVID-19 corona virus, segmenting and stratifying patients based on risk will be critical to saving vulnerable lives.


Prognosis: Admitted patients will need to be isolated in the ICU with ventilators for 20-30 days at a time, while treating and discharging patients at lower risk to turn around hospital beds and free up capacity for newer patients infected with COVID-19 who are being admitted. Machine learning algorithms can be used to proactively identify the most vulnerable population of patients and prioritize them for advanced and more intensive care protocols in the ICUs with ventilators vs. younger patients less at risk.



Risk-based Patient Risk Stratification to match constrained capacity with the patients most at risk


11. Monitor Hospital Infections (HACs) to Improve Quality, Patient Safety, and Outcomes

Challenge: Hospital-acquired infections (HAIs) or hospital-acquired conditions (HACs), along with sepsis, are real-world concerns, given the massive numbers of COVID-19 afflicted patients, which would further exacerbate their condition, especially for vulnerable patients.


Prognosis: Leveraging self-service descriptive and predictive analytics to monitor metrics and KPIs (like CAUTI, CLABSI etc.) to laser-focus on these metrics and reduce them have been demonstrated to positively impact patient outcomes.


12. Empower Care Coordinators/ Nurses to Monitor the Most At-Risk Patients Post-Discharge Across the Care Continuum

Challenge: Vulnerable patients will be susceptible to additional infections following discharge, and need to be proactively monitored for medication compliance, vital signs reporting, and follow-up appointments by care coordinators.


Prognosis: Leveraging analytics to predict patients most at risk and proactively engaging with them using telehealth, remote patient monitoring, and videoconferencing will empower care coordinators to minimize 30-day re-admission risk while assuring superior patient outcomes. Leveraging Uber and Lyft to transport patients who are economically or physically challenged to make their appointments has been demonstrated to improve compliance.


In closing, I would like to dedicate this blog to our fearless doctors, clinicians, nurses, technicians, and first responders 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.



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