In the past decade, health systems have seen tremendous investment, progress and yield in information technology. But one can’t help but think that there is still something missing.
“In population health, the focus is less encounter driven and more holistic across inpatient, outpatient and post-acute”
We have had massive EMR implementations, mainstream data warehouse usage and advanced analytics applications. But in all of this work–where is the patient?We have had meaningful use compliance and HIMSS stages of achievement. But in all ofthis accomplishment–where is the patient?
We can create score cards, measure clinical efficiency and operational performance. But in all of these analytics–where is the patient?
Most health systems claim to be patient-centric. And the term “patient centered” has even become a bit of a buzzword. But our new era of population health and value based payment requires a transformation of our operations–including IT–to truly include the patient at the center for all that is done. In population health, the focus is less encounter driven and more holistic across inpatient, outpatient and post-acute. For clinicians to manage across this continuum effectively, they need to go deeper on their understanding not of the encounter–but of the patient. While it is still helpful to understand that someone was admitted to the hospital last month, the larger need is to understand what led up to that admission–was there a doctor’s visit or ED visit prior? What was diagnosed during those visits? Where was the patient then discharged to? Was there a follow-up visit? In other words, understanding how we could we have managed the patient more optimally.
Most organizations fall woefully short of being able to fulfill the information needs of these new care models and general objectives of population health–regardless of MU compliance and HIMSS level. The reason? Despite the obvious need, the industry has historically never put the patient in the center. Data and information traditionally has been captured as a single visit or encounter, reflecting the legacy of fee for service reimbursement. And although EMRs are now more widespread and well utilized there are still significant gaps in leveraging their information and capability. This includes tying all clinical and claims data together regardless of EMR vendor or source); a single identifier that tracks patients inside and outside a health system;and tools that enable patients to easily access all of their healthcare data.
As a large ACO, Advocate Healthcare has embraced the shift to value based care. Currently, we have almost 900,000 attributed lives across a variety of full risk or shared savings contracts. Within 5 years Advocate has gone from 18 percent of revenue being in some form of value based payment to about 66 percent today.
For Advocatethe amount of change within IT and analytics needed to support value based payment–and putting the patient at the center—has been significant. The foundational step was the creation of a single platform that brings together data from 6 different EMRs and over 30 claim files across the care continuum. This process took over 24 months and still continues as new data sources are identified. Although we might benchmark this platform in terms of data sources and size, the most appropriate and meaningful measure is the number of patients –close to 5 million individuals. Pulling this patient data together also created a clear business need for an enterprise master patient index (empi). Without an empi, bringing all the data together would have little to no value. Now–we have all our patient data tied together for a complete picture of care provided to an individual.
Creating a true patient centered data platform has allowed us to start asking questions beyond just those related to a single episode of care. Now, we can dig deeper and provide analytics that allow us to predict and mitigate the risk of readmission; models that determine the right post-acute care setting following hospitalization; and algorithms to appropriately allocate interventions, like care management, to the right populations. We are also redefining our population health risk stratification methods by using clinical and claims data (and not just cost) to identify patients for better clinical management.
Our progress to date has been encouraging and personally rewarding. But there are still significant opportunities. Additionalsources of data that reflect social, environmental, and geographic attributes need to be sourced and appended to clinical and claims data. Data that reflects care provided by other outside physicians and institutions needs to be transparent and readily accessible to both clinicians and patients.
This future state could bring us to the tipping point to answer the deepest and most meaningful questions to guide the delivery of high quality, cost effective care. And although much of this work has been motivated by new payment incentives, we need to look beyond just cost and payment. We need to return the conversation back to improving health outcomes, maintaining well-being and placing individual health at the center. This is the real “value” to value based payment.