Whitepaper: Appropriateness of care measurement

Reducing waste and improving outcomes through
evidence-based clinical best practices

The United States spends more money on health care than any other country and wastes more on it, as well. In 2017, total US health care costs reached roughly $3.5 trillion—18% of the gross domestic product. Of this, about 25% ($760–$935 billion) was wasted due to factors including failure of care delivery or coordination, overtreatment or low-value care, pricing failure, fraud, and administrative complexity.1

This isn’t news, exactly. In the 1980s and 1990s, rapidly rising health care expenses, coupled with a paucity of information about clinical decision-making, led to a variety of initiatives focused on improving quality of care and managing costs. New organizations, both governmental and in the private sector, dedicated themselves to quality research and the development of clinical practice guidelines. These included the Agency for Healthcare Research and Quality (AHRQ, which included the National Quality Measures Clearinghouse, a web-accessible database), and the professional organizations associated with various medical specialties, such as the American College of Physicians (ACP).

Such groups relied on outcomes literature—ideally, from randomized controlled trials—for the data necessary to develop these guidelines, as well as measures based on those guidelines. They also emphasized the urgency of standardizing the evaluation and treatment of widely prevalent diseases and conditions with elevated morbidity and mortality, high costs, and significant variations in treatment strategies and clinical outcomes. Chronic and expensive diseases such as diabetes, asthma, cancer, and cardiovascular disease received a lot of research attention and, for obvious reasons, still do.

For example, the National Quality Forum (NQF), a not-for-profit organization dedicated to improving health care practices and outcomes, has prioritized the top 20 high-impact Medicare conditions; the first five are major depression, congestive heart failure, ischemic heart disease, diabetes, and stroke/TIA.2 The NQF noted in the report that of surveyed stakeholders, most felt that new measures of “appropriateness/efficiency” of care should receive the highest priority moving forward.

The issues

Health systems, including managed care organizations, have long embraced an evidence-based approach to care, but limitations have become apparent over time.

First, organizations struggle to incorporate practice guideline updates into their care delivery workflow and operations. These difficulties are due in large part to a lack of effective mechanisms for achieving acceptance and adoption by providers. Performance measures are intended to serve as one such mechanism, but confidence in traditional measures isn’t high in the clinical community. For example, a 2016 survey found that 63% of American physicians felt existing performance measures failed to capture the quality of care provided.3

Second, it has always been difficult to measure adherence to guidelines at anything more granular than an organizational or group-practice level, and such broad measures are notoriously ineffective at modifying the behavior of individual physicians. Third, while the emphasis on prevalent and expensive diseases is important for obvious reasons, this focus may relegate other conditions to secondary status, even though patients suffering from such conditions would benefit significantly from a more rigorously researched approach to care quality.

Appropriate care

Partly in response to such concerns, in 2018 the ACP’s Performance Measurement Committee published a rating system for performance measurement validity with respect to five domains, including importance, appropriateness, clinical evidence, specifications, and feasibility/applicability.4

The authors noted significant inconsistencies among US organizations in judging the validity of care-quality measures. They also pointed out that inappropriate care may occur for two opposite reasons: overuse or underuse of services.

Appropriate care refers to evidence-based best practices in a given clinical specialty, with an emphasis on reducing unnecessary or harmful tests, procedures, and prescriptions. Decisions about appropriate care ideally include analysis of cost, quality, and potential for harm. Because appropriateness—clearly an important dimension of care delivery—has been overlooked or minimized in previous measures, nationally recognized physicians and thought leaders such as Motive Practicing Wisely Solutions and Marty Makary, MD, a surgeon at Johns Hopkins, have been collaborating to develop relevant guideline-based measures. The goal is for administrators, medical directors, and other organizational stakeholders to feel confident in the measures’ relevance and value in evaluating the clinical behavior of individual physicians.

The guideline-based measures aim to diminish the discrepancy between clinical practice guidelines and clinician behavior, as assessed by data on individual physician–patient interactions. As a tool, then, appropriate care measures are designed to be less of a blunt instrument and more of a scalpel.

The appropriateness of care measures target clinical areas in which significant practice variation exists, and where such variation leads to avoidable cost or harm, as shown by the evidence. The program addresses fields including cardiovascular disease, gastroenterology, orthopedics, primary care, allergy and immunology, endocrinology, infectious disease, neurology, obstetrics and gynecology, ophthalmology, psychiatry, surgery, and over a dozen more specialties.

Examples of existing guideline-based appropriate care measures include:

Cardiology

Unnecessary and inappropriate diagnostic testing and procedures

Gastroenterology

Unnecessary colonoscopies, biopsies, and esophagogastro-duodenoscopies, as well as poorly coordinated care

Ophthalmology

Inappropriate use of antibiotics, diagnostic procedures, or treatments, as well as correct management of chronic conditions

Primary care

Inappropriate use of medications and imaging, best use of prevention and wellness, and optimal chronic disease management

Measuring and guiding physician behavior

As noted, broad organizational or systemwide practice guidelines typically provide guidance for clinical decision-making that physicians may or may not choose to utilize.

Because administrators have not been able to measure individual behaviors—at least, until now—persuading physicians to embrace practice guidelines has been challenging for the reasons cited earlier.

The appropriateness of care measurement approach relies on engaging clinicians as professionals and colleagues who want to provide their patients the best possible care. Case studies have demonstrated that doctors often change their practice patterns if they are made aware of the difference between their own patterns and those of their colleagues within a group, a network, a region, or nationally.

Appropriateness of care measurement can help organizations:

  • Understand their areas of strength and opportunities for improvement
  • Identify outliers beyond the range of better practice
  • Encourage physicians to improve with peer comparisons as interventions
  • Promote peer sharing among clinicians in groups or networks

Concurrently, at the network level, achieving optimal effectiveness includes:

  • Prioritizing clinical initiatives and improvement opportunities
  • Referring patients to the most appropriate specialists
  • Integrating guideline-based appropriateness measures into specialist profiling programs
  • Inspiring improvement by rewarding performance with incentives, such as those provided under risk-based contracts or through other types of value-based care arrangements

Appropriate Practice Scores (APS)

Compare your practice patterns to peers with Motive appropriateness measures.

An Appropriate Practice Score (APS) helps stakeholders make these decisions. For example, Motive has developed the APS based on what providers do and payers pay.

Both of these are abstracted from databases covering more than a billion claims from physician–patient encounters. The data are aggregated and analyzed in terms of harm, cost, and quality. The results are summarized in a simple 0–10 rating—that is, the APS. An APS of 5 indicates average performance; higher scores are better, lower scores worse.

The APS is bracketed by a range of better practice (ROBP), which accounts for factors not easily captured in claims data. These may include a variety of subtle clinical factors that affect care decisions, including the patient’s symptoms, as well as personal or family medical histories. It may also allow for the clinical resources available to a given practice, geographic considerations, and issues related to referral.

The APS relies on quantitative metadata such as local treatment costs, Medicare treatment costs, and complications; strong statistical testing; and validated evidence. It is adjudicated by a 600-member network of subject-matter experts, whose judgment is informed by Motive Practicing Wisely’s ROBP methodology. This approach honors clinicians’ concerns by acknowledging that the real world of clinical practice comprises far more variations than absolutes. But it also emphasizes the importance of knowing what constitutes appropriate care in any given circumstances, and achieving it when possible.


1. Shrank WH, Rogstad TL, Parekh N. Waste in the US health care system: estimated costs and potential for savings. JAMA. 2019;322(15):1501-1509.

2. NQF. Measure Prioritization Advisory Committe Report: Prioritization of High-Impact Medicare Conditions and Measure Gaps. Available at http://www.qualityforum.org/Publications/2010/05/Committee_Report,_Prioritization_of_High-Impact_Medicare_Conditions_and_Measure_Gaps.aspx. Published May 2010.

3. Casalino LP, Gans D, Weber R, et al. US physician practices spend more than $15.4 billion annually to report quality measures. Health Aff. 2016;35(3):401-406.

4. MacLean CH, Kerr EA, Qaseem A. Time out—charting a path for improving performance measurement. N Engl J Med. 2018;378(19):1757-1761.