Article | August 5, 2020

Digital Health Innovation: The Predictive Impact Of Curated Real-World Data In Times Of Change

By Melva T. Covington, MPH, MBA, Ph.D.

Scientist Data

The projected costs of healthcare in the United States due to the novel coronavirus, or Sars-COV-19 (COVID-19), are eye-opening. Total costs will range between $56B and $556B by the end of 2021, according to a recent report commissioned by American’s Health Insurance Plans1. Hospitals will have a calculated loss of over $200B by mid-year 2020 or lose on average $51B per month over a four-month time period2. There have also been disruptions to routine surgical care, with over 28M surgeries postponed or canceled during the 12-week peak of the COVID-19 crisis3. In addition, exponential growth in the use of telehealth services, remote monitoring, and postal delivery of health products has occurred. One national retail pharmacy chain reported a 600% growth in demand for telehealth communications, virtual visits, and home delivery services during the first quarter as compared to the use of these services in Q1 2019. Retail pharmacies that have mini-clinics embedded in local communities have experienced rapid growth during this COVID-19 period. This is largely driven by the existence of trusted relationships and established interactions with consumers who seek health care goods and services within their community4.

On full display is the need to quickly understand the impact of these changing dynamics and address costly challenges within our health care system in real-time. One critical question is the extent to which digital technologies can be useful in informing our understanding of what works in health care delivery and what does not. Access to more complete data is crucial to empower a diverse range of stakeholders with the knowledge and ammunition needed to make informed choices about expenditures and the use of scarce health care resources. In this regard, we need to know the full range of factors associated with health care delivery versus data that is just good enough to make effective decisions.

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