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Performance Measures for Health Care Systems

David R. Nerenz, PhD, Henry Ford Health System
Nancy Neil, PhD, Virginia Mason Medical Center

An overview of performance measures and their successful implementation provides a valuable template for enhancing any health care organization’s performance measurement programs.

The history of performance measurement in health care goes at least as far back as Florence Nightingale, who developed an elaborate data collection and statistical analysis system focusing on in-hospital mortality during the Crimean War era.  Her system enabled comparisons from hospital to hospital, from unit to unit within hospitals, and within the same hospitals over time.  Graphical presentations highlighted key findings for unsophisticated audiences.  This explicit, objective measurement system was the basis of significant breakthroughs in understanding the relationship between sanitary conditions and hospital morbidity and mortality.  Nightingale’s methodology also serves as an illustration of three key questions that—according to Drs. Nerenz and Neil—underlie virtually all other considerations about effective performance measures, past or present.  What is the entity being measured?  Who is using the information?  What core organizational processes or skills are the measures designed to reflect?

As the authors move from historical overview to describing the implementation of performance measures in modern health care systems, Nerenz and Neil caution health care executives to approach the implementation process with a clear understanding of today’s health care environment.  Among the trends the authors note are on-going:

  • strong interest in comparative performance information by public and private purchasers;
  • challenge of coordinating performance measures for external/public use with those for internal management and quality improvement use;
  • difficulty focusing measurement on “bottom-line” patient outcomes;
  • and development of evidence-based medicine.

There is little debate that performance measures in health care should include some mix of clinical quality, patient (or member) satisfaction, efficiency, utilization and financial performance.  The authors observe that the real challenge is in the selection and implementation of a balanced set of measures and the effective use of those measures for external accountability and internal quality improvement purposes.  Practical strategies for meeting that challenge are included in the study and are demonstrated by specific examples of health care systems engaged in innovative, successful work in the area of performance measurement.  Among the systems and performance measurements described are:

  • Veterans Health Administration’s National Surgical Quality Improvement Program, a model for large-scale surgical quality improvement efforts.  The Program uses risk- and severity-adjusted functional status and mortality data to compare hospitals, track trends over time, and promote improvement toward benchmark levels.
  • Henry Ford Health System’s “layered” approach.  A basic set of measures are collected, reported, and applied at the system level, then related sets of performance measures are collected, reported, and applied at the level of operating units (e.g., individual hospitals or health plan), smaller units within legal operating units (e.g., inpatient units of a single hospital, departments in the medical group, primary care sites), and ultimately to the level of individual clinicians.
  • Scripps Health, where the performance measurement system is based on two organizing principles: the “dashboard” and the “balanced scorecard.”  The dashboard concept suggests a set of measures useful for those who are “driving” or “steering” the system.  A set of measures are available that display, in an easy to understand and concise fashion, what the system’s current status is on those measures.  The balanced scorecard concept suggests that measures must be drawn from a set of clinical, administrative, patient satisfaction, and community service domains rather than all from just one or two domains.
  • Sharp HealthCare, whose “Outcome Tracking Initiative” system includes more than 3,000 indicators of clinical and financial performance.  These measures are focused on 30 disease states or clinical conditions.  Many of the measures are analyzed and reported at the facility level, but reports on important areas of non-hospital care (e.g., ongoing management of patients with diabetes) are also prepared for individual physicians within the hospital and individual affiliated physicians.

Nerenz and Neil conclude the report with several invaluable observations for those seeking to enhance their organizations’ performance measurement programs.  First, they note that even as the general concept of a “balanced scorecard” gains favor, the perfect measurement set has not yet been invented.  Every measure has one or more flaws, as do data available to support them.  However, performance measures need not be perfect in order to be useful.  “Good enough” performance measure (i.e., showing evidence of a problem when there really is one or reflecting a trend in the actual direction of change) may be all that is needed to take the organization to the next level of improvement.

Secondly, even accurate data can be useless if there is too much (or too little) “organizational distance” between the unit of analysis for the data and the unit of control for making change.  To combat this, several successful organizations have instituted a top-down, “layered” approach to performance measurement in their systems.

And, finally, performance measurement is best supported when it rests on a clear scientific and statistical foundation.  While there is no doubt that professional-level research methods and statistics are sometimes useful, it is also true that basic principles and clear thinking around data issues are often all that is necessary to reach meaningful conclusions.

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