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Quality Measurement and the Ubiquitous Electronic Health Record

The Veterans Health Administration was an early adopter of quality measurement, performance accountability, and the use of electronic health records (EHRs) in the 1990s. These steps were seen as important to uniformly implementing evidence-based practices in prevention and chronic disease care across our entire delivery system. Largely as a result of the influence of quality measurement and EHRs on clinician behavior, VA achieved "best care anywhere" levels of performance on the Joint Commission's Core Hospital Quality Measures and the National Committee for Quality Assurance (NCQA) Healthcare Effectiveness Data and Information Set (HEDIS).

Now that VA is well into its second decade of using quality measures and EHRs to guide its care of Veterans, the constraints of this approach are becoming more apparent. Most nationally-recognized quality measures were implemented in a "one size fits all" manner--appropriate perhaps when performance levels were under 50 percent, but not at current levels, which exceed 85 percent for most measures. Both qualitative and quantitative studies are now raising concern that trying to improve performance on our existing measures might direct clinical resources toward interventions that have either low benefit for Veterans, or the potential to cause more harm than good.1, 2 Since most of our quality measures focus on a single episode of care, they may also fail to capture appropriate clinical decisions and changes in the patient's health status and risk over a longitudinal timeframe. And, given that many Veterans obtain at least part of their medical care elsewhere,3 can we ever say with confidence that VA care is a good value for the nation?

Our electronic health record, VistA-CPRS, remains limited in its ability to capture clinical concepts using standardized data elements. As a result, VA currently uses chart abstraction on a sample of Veterans to estimate performance on HEDIS and Joint Commission measures. Not only does this cost more than $12 million annually, it causes delayed and inadequate clinical feedback to treatment teams at the point of care. When structured clinical data is captured electronically, it often occurs through relatively inflexible clinical reminders, which can create challenges for harried clinicians due to the poor context-sensitivity of the reminders and their interference with workflow.

These limitations might have mattered little when VA was among the few large U.S. health systems using the EHR and had unmatched performance statistics. That reality will soon change. Nearly $20 billion of incentive payments have been made available to eligible hospitals and providers to accelerate EHR adoption as part of the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009. Providers and hospitals that adopt certified EHRs must demonstrate "Meaningful Use" by, among other requirements, generating and reporting electronic quality measures and public health information, and implementing clinical decision support systems. Although many commercially available EHRs currently share many of the same constraints as VistA, HITECH is expected to stimulate considerable innovation to address these shortcomings.

Stage 2 and 3 of Meaningful Use will also include a demonstration of the ability to electronically send and receive information across providers using nationally recognized data standards. Other federally-supported initiatives, such as the development of the Nationwide Health Information Network (NwHIN), VA's own Blue Button technology (http://bluebuttondata.org), the population health tracking tools developed by Indian Health Service (http://www.ihs.gov/CIO/ca/icare/index.cfm), and the joint VA Department of Defense commitment to develop an open-source integrated EHR (iEHR), offer a vision in which health information is shared seamlessly across multiple health systems and providers. Finally, rapid advances in computer science, especially the use of natural language processing for complex analytics (e.g., IBM's Watson system) are allowing use of much richer information to provide context-sensitive, patient-centric decision support.

The future in which the EHR is ubiquitous and health data is exchanged across providers and systems in real time allows news ways to measure quality, such as:

1. Longitudinal quality measurement incorporating clinical actions: assessing the adequacy of clinical care not just by the presence/absence of a given finding or intervention, but by the degree to which clinical actions over the course of time are consistent with scientific evidence and patient wishes.

2. Risk-tailored quality measurement: using the predicted risk of poor outcome to inform appropriate interventions. Risk is determined from the totality of available health data and modeled from populations that are relevant to the specific patient and situation.

3. Patient-centered quality measurement: allowing patients, and their loved ones, to identify realistic and desired health outcomes, expressed in terms that reflect personal values and goals for well-being and functioning in the community.

Any of these scenarios represents a major shift for quality measurement in VA and the nation. Several are already being tested and deployed--for example, we are implementing clinically-appropriate action measures for diabetes and a predictive model for mortality and hospital admission within primary care (albeit, at present, only with data obtained from VistA). Expanding this work will require deep and ongoing collaboration with informaticians and health services researchers who can provide the technical expertise and scientific objectivity to pilot, refine, and evaluate the measures themselves. Core challenges include developing means of capturing appropriate information, such as patient preferences, without interrupting clinical workflow, and establishing the psychometric properties of metrics that are based on personalized goals. The Office of Analytics and Business Intelligence looks forward to these partnerships.

  1. Powell, A.A. et al. "Unintended Consequences of Implementing a National Performance Measurement System into Local Practice," Journal of General Internal Medicine 2012; 27:405-12.
  2. Kerr, E.A. et al. "Monitoring Performance for Blood Pressure Management among Patients with Diabetes Mellitus: Too Much of a Good Thing?" Archives of Internal Medicine 2012; 172:938-45.
  3. Trivedi, A.N. et al. "Duplicate Federal Payments for Dual Enrollees in Medicare Advantage Plans and the Veterans Affairs Healthcare System," Journal of the American Medical Association 2012; 308:67-72.

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