Using Electronic Health Records for Quality Measurement and Accountability in Care of the Seriously Ill: Opportunities and Challenges

Abstract

Background: As our population ages and the burden of chronic illness rises, there is increasing need to implement quality metrics that measure and benchmark care of the seriously ill, including the delivery of both primary care and specialty palliative care. Such metrics can be used to drive quality improvement, value-based payment, and accountability for population-based outcomes.

Methods: In this article, we examine use of the electronic health record (EHR) as a tool to assess quality of serious illness care through narrative review and description of a palliative care quality metrics program in a large healthcare system.

Results: In the search for feasible, reliable, and valid palliative care quality metrics, the EHR is an attractive option for collecting quality data on large numbers of seriously ill patients. However, important challenges to using EHR data for quality improvement and accountability exist, including understanding the validity, reliability, and completeness of the data, as well as acknowledging the difference between care documented and care delivered. Challenges also include developing achievable metrics that are clearly linked to patient and family outcomes and addressing data interoperability across sites as well as EHR platforms and vendors. This article summarizes the strengths and weakness of the EHR as a data source for accountability of community- and population-based programs for serious illness, describes the implementation of EHR data in the palliative care quality metrics program at the University of Washington, and, based on that experience, discusses opportunities and challenges. Our palliative care metrics program was designed to serve as a resource for other healthcare systems.

Discussion: Although the EHR offers great promise for enhancing quality of care provided for the seriously ill, significant challenges remain to operationalizing this promise on a national scale and using EHR data for population-based quality and accountability.

Keywords: accountability in care; electronic health records; palliative care; quality metrics; seriously ill patient population.

FIG. 1.

Trends in inpatient care for patients hospitalized at the two largest UW Medicine hospitals during the last 30 days of life, from 2010 through 2015, patients with one or more chronic conditions. Significant negative linear effect—fewer people with hospitalizations as time progressed (p < 0.001). Curvilinear effect was not statistically significant (p = 0.084 for the unadjusted model, as shown in the graph below; p = 0.780—after adjustment for age at death, racial/ethnic minority status, and number of diagnoses).

FIG. 2.

Trends in ICU use for patients hospitalized at the two largest UW Medicine hospitals during the last 30 days of life, from 2010 through 2015, patients with one or more chronic conditions. Significant negative linear effect—fewer people with hospitalizations as time progressed (p < 0.001). Curvilinear effect was not statistically significant (p = 0.075 before adjustment, as shown in the graph below; p = 0.066 after adjustment for number of diagnoses).

FIG. 3.

Trends in inpatient readmission for patients hospitalized at the two largest UW Medicine hospitals within 30 days of discharge during the last 90 days of life, from 2010 through 2015, patients with one or more chronic conditions. Significant linear effect: fewer people with readmits as time progressed (p = 0.020). No significant curvilinear effect.

FIG. 4.

Trends in EHR documentation of advance directives, from 2010 through 2015, patients with one or more chronic conditions. Significant positive linear effect—more documentation as time progressed (p < 0.001). There was also a significant curvilinear effect with the overall positive effect (p = 0.003) becoming even more positive as time progressed (p < 0.001). EHR, electronic health record.