How data and analytics are changing healthcare delivery

The historic response to the pandemic points the way for addressing new challenges and ongoing disparities in health services.

C-suite executives know that data and analytics are no longer nice-to-haves, they are now essential to daily business functions and decision-making. But having the right data is not enough. Organizations need to be able to interpret it accurately to be successful, as the pandemic so clearly demonstrated. Businesses depend on these figures to make the right decisions, and health officials to preserve lives and livelihoods.

With COVID-19 steadily trending down, some optimism and stability have returned to America’s healthcare sector, even as the industry manages through staff burnout, attrition and shortages. But even with COVID-19 numbers down, public health officials, healthcare providers and insurers all know that risks remain—and will require ongoing monitoring. Applying data and analytics will be critical to managing those risks.

Early insights, ongoing vigilance

One of the biggest challenges of COVID-19 was its early classification by the CDC in late 2019 as a “novel” virus—something never seen before, and thus with no baseline data to work from.

In record time, though, scientists were able to assemble and test growing amounts of data that became increasingly more reliable thanks to ongoing analytics feedback loops and expanding sources and volumes—from data on hundreds to thousands to millions of people. That data-driven process drove vaccine development, testing, rollouts and updates; it continues to track variants and their related infection, hospitalization and death rates—and at detailed demographic levels; and it also guides public policy on things like mask recommendations and other precautions.

Data and analytics will also play a leading role in the major go-forward question about the COVID-19 virus: Will it become endemic and less threatening, similar to the seasonal flu and other viruses that the world has learned to cohabitate with on a predictable basis? Or it will it continue to mutate, causing more unpredictable flare-ups in different regions and at different times of the year? Scientists will rely on data to monitor and ultimately answer that question.

Fighting a pandemic in the age of big data

In comparison to previous pandemics, the world had one major advantage in attacking COVID-19: the wealth of data available and the speed at which it can be processed. Since 2013, the amount of healthcare data in America has been growing at almost 50 percent per year1. Additionally, organizations now have better tools and more computing power to analyze the data—the most powerful supercomputer today is more than 200 times as fast as its counterpart a decade ago2. This is helping healthcare agencies and providers deliver solutions as well as identify strengths and weaknesses in the response faster.

These data and analytics capabilities have been critical in addressing the inequities in healthcare provision, too. Like previous calamities, COVID-19 has impacted disadvantaged communities disproportionately, leading to higher hospitalization and morbidity rates of these population groups. Multiple factors have contributed to these outcomes, including a higher degree of existing medical preconditions, a higher likelihood of living and working in more exposed areas, and the vulnerability associated with being uninsured, underinsured or having to choose between getting paid or seeing a doctor. Distrust in authorities and sources of information outside communities, language barriers and limited access to the internet are additional challenges that need to be overcome to successfully vaccinate disadvantaged communities.




Since 2013, the amount of healthcare data in America has been growing at almost 50 percent per year. 


The most powerful computer today is 200x faster than its counterpart a decade ago, providing better tools for data analysis. 

To address these challenges, the Atlanta-based Morehouse School of Medicine developed the National COVID-19 Resiliency Network (NRCN). With the help of KPMG and Salesforce, the NCRN offers community-based organizations (CBO) multiple tools to close information gaps, facilitate the finding of healthcare services, and develop communication and outreach strategies tailored to the specific needs of each community. Additionally, by capturing data on which measures work and which don’t, the NCRN platform can give a head-start to anyone seeking to provide help to the same communities in the future.

“You can’t look at a data set and say, OK, this data set is going to solve the issues for all our patient population,” says Dr. Todd Ellis, Principal of Health & Government Solutions, KPMG. “It should never be a one-size-fits-all. That’s what we’re learning. Based on a person’s different ethnic background, you’re going to use different data sets on how you approach them from a care delivery perspective. That’s what we’re seeing come out of the Morehouse project. … Organizations should be able to understand what’s going on at the ZIP code level and precisely engage with that community. That is precision community engagement.”

You can’t look at a data set and say, OK, this data set is going to solve the issues for all our patient population. It should never be a one-size-fits-all. That’s what we’re learning.
Dr. Todd Ellis, Principal of Health & Government Solutions, KPMG

Lessons for the future

The COVID-19 pandemic fundamentally changed the way businesses, individuals and communities operate. Remote working has been facilitated by digital technologies, households have reverted to online shopping and digital entertainment, and healthcare providers have invested in telematic medicine solutions. Not all new digital trends require data and analytics to function, but they do offer the potential for the collection of more data. Many businesses are already using data and analytics to enhance customers’ shopping experience, suggest TV shows and movies, and give healthcare providers a more complete picture of a patient’s medical history and potential ailments.

There is no one-size-fits-all data and analytics solution to the many challenges the healthcare industry is facing these days. But each solution does require following similar steps. These are:


Listing what internal and external data are readily available, what sources can be tapped into and what data could be sitting around unused is critical to identifying the building blocks of any solution. Especially in healthcare, more data often leads to better results.


Identifying the right data or combination of data and converting these into signals and indicators is an iterative process of trial-and-error. Your employees, patients and other relevant stakeholders might intuitively know what signals to look for. Revisit your assumptions, signals and algorithms as new data becomes available.


Making data accessible is an equally important component. With access to data, innovative solutions can be found faster. Providing your employees with tools that help them think outside the confines of their day-to-day responsibilities will help them identify new connections and opportunities that can lead to new solutions. Similarly, providing patients with relevant and insightful data can help them take preventive care and necessary actions to improve their health.


Artificial intelligence (AI) modules can enhance analytical processes by trawling through billions of data points at a faster rate. As a result, the application of AI allows for the exploration of more relationships between variables and thus the discovery of connections unknown to date.


When analyzing the strength of an algorithm or other data and analytics process, also consider ethical questions, such as how well diverse population groups are factored in. Ignoring these can lead to inaccurate or even false conclusions.


Pulling all the signals together in a visual dashboard will provide one of the essential tools for monitoring progress. Dashboards can often summarize information better than reports and highlight key areas that require focused attention. Additionally, well-designed dashboards offer users tools to explore the data further and uncover relevant insights that are key to them.

Discover more insights and opportunities to harness the power of big data:

This content outlines initial considerations meriting further consultation with life sciences organizations, healthcare organizations, clinicians, and legal advisors to explore feasibility and risks.
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Contact us

Todd Ellis

Todd Ellis

Principal, Health & Government Solutions, KPMG US

+1 678-761-3063