Module 3: Measuring Quality in the Quality Enterprise

Published Online: July 28, 2013
L. Allen Dobson, Jr, MD; Marcia Guida James, MS, MBA; Margaret E. O’Kane, MPH; Peter Salgo, MD; and Jed Weissberg, MD
Introduction

Continuous improvement is a core tenet of the quality enterprise, and measurement is necessary to gauge improvement. Therefore, there is a growing emphasis on measurement throughout the healthcare spectrum.

To meet the demands of the quality enterprise, the measurement field must continue to expand and evolve. Healthcare reform legislation will accelerate and shape the trajectory of that evolution. Along the way, significant barriers to proper measurement must be addressed.

Measuring Quality: Challenges and Limitations

In the reform era, measuring and gauging quality are essential but problematic. The major barriers are discussed below.

Inherent system complexity equals variations, lack of consensus, and lack of coordination

The US healthcare matrix is vast and extremely complex. Complex problems defy simple solutions. There are few national consensus measures. Existing quality-related definitions, approaches, mandates, and measures vary widely between stakeholders and from place to place, and often overlap and conflict. At present, the federal government (eg, CMS, Agency for Healthcare Research and Quality [AHRQ]), the Joint Commission, the NCQA, professional associations and societies (eg, AMA’s Physician Consortium for Performance Improvement), private corporations, and individual researchers have all developed measures used by health plans, hospitals, physician practices, and long-term care providers to compare performance.

Although some stakeholders are capable of measuring their own performance, they measure only against themselves, and information is seldom shared. Moreover, because quality standards are still evolving, many hospitals and health plans distrust the available data and have not committed to the systemwide measurement effort, although the PPACA will require sharing and measurement. To some extent, mistrust and reluctance to share might be understandable.

Quality Measurement: 10 Key Areas of Evolution

  1. Patient-level outcomes—better health

    • Linking health risks and outcomes

    • Avoiding complications (eg, hospital-acquired infections, medical errors, and medication errors)

    • Patient-reported functional status, health-related quality of life, and experience of care


  2. Processes of care—better care
  3. • Technical effectiveness

    • Coordination of care and transitions to care settings

    • Alignment with patient preferences: shared decision making

  4. Cost and resource use (overuse, misuse, waste)
  5. • Total cost of care across episodes of care

    • Appropriateness

    • Indirect cost: employee absence or reduced productivity

  6. Developing ways to aggregate complex information for measuring continuumwide performance (eg, composite metrics, efficiency data, deltas, dashboards)


  7. Measuring disparities throughout the continuum (eg, stratification, clinical and socioeconomic status risk profiles)


  8. Harmonizing measures across sites and providers


  9. Shared accountability across patient-focused episodes of care


  10. Meaningful use of HIT and clinical decision support


  11. Measures for patients with multiple chronic conditions


  12. Measuring and reporting performance systemwide


Under a VBP construct, reporting data and quality results can impact provider compensation.

Moving targets

In the dynamic and evolving reform environment, “best practices,” “quality,” and “quality improvement” are moving targets. Definitive quality solutions are therefore elusive.

Measuring at the population level

Patient-centered care is a cornerstone of reform and VBP. “After all,” said Ms James, “patients are on the receiving end of the care we deliver.” For overall reform to succeed, measurement must extend beyond individual patients to the patient population, the community, and beyond, to wider geographical regions and the entire nation.

Unaligned legacy system

The measures currently used in the quality enterprise were developed for other purposes, and are not readily adaptable for publicly reporting and rewarding quality performance. Although the legacy system does report some performance measures, those measures are not necessarily aligned with identified national priorities. The reverse is also true: some national priorities have been identified without corresponding performance measures.

Lack of/incomplete information and metrics; limits of HIT

Randomized controlled trials are the gold standard of evidence- based medicine; their results inform best practices for attaining optimum outcomes. However, the evidence base is lacking, incomplete, or mixed for many conditions, and especially for patients with multiple comorbid conditions. In those instances, discrete metrics are either unavailable or not yet feasible. For example, most trials exclude the frail elderly with multiple comorbidities, who often react to treatment differently from healthy young people or people with a single condition.

Even when the evidence base is sufficient, developing meaningful quality metrics is time-consuming, expensive, and difficult. Multiple, disparate data points must be aggregated and integrated. EHRs and other HIT should help resolve the problem. “The evolution of quality management pivots on automated records,” said Mr White. “That’s where many outcome measures can be found—not just outcomes for individual patients, but for an entire practice or population.”

The quality enterprise poses nuanced performance questions. To answer them, HIT must be configured to identify gaps in care, report outcomes in the same format from one record to the next, and help improve practice- or populationwide patient management. However, full HIT capability is not yet widely available or easily linked to other essential data, and current EMRs fall short. In 2000, RAND Health published quality measures specifically for frail elderly patients that took their multiple health issues into account. “A great measure set,” said Dr Weissberg. However, those measures are not readily extractable from claims data or EMRs. Dr Dobson commented, “I need—but current EMRs don’t provide— all the information I need to manage all of the patients I care for, whether or not they’re physically sitting in my office.”

On the other hand, HIT capability in general, and EMRs in particular, do not translate into better quality management or measurement unless properly used. For example, a physician might use EMRs to manage the care of patients who make appointments, but not use them to monitor the balance of the patient roster.

Finally, even if the necessary evidence base and HIT infrastructure were in place, no uniform standards currently exist for collecting, aggregating, and publicly reporting data. Proposed regulations have been issued under the PPACA to establish those standards.

Outcomes versus process: best medical practice versus best-practice delivery

Quality measurement involves not only the outcomes of care, but the process of care—how care is delivered. Process reaches beyond clinicians, physically administering treatment to patients. Process includes how patients enter, exit, and are routed through the system and its various care settings; process also includes patient preferences and shared decision making.

The current apparatus seems to be stimulating development of measures, but they may not be particularly meaningful for improving practice. Experts debate the relative utility of outcomes versus process measures, and the debate has implications for overall quality measurement. The panelists discussed the benefits of monitoring outcomes. Dr Weissberg noted that data about whether a patient with diabetes has taken a hemoglobin A1C test do not reveal whether the patient is in control according to accepted therapeutic targets. According to Mr White, employers want to know if their employees are healthier today than they were last month. Dr Dobson mentioned that a narrow focus on measuring process raises the risk that people will perform only to satisfy the measures, and lose touch with the results.

Having meaningful outcomes measures also raises the prospect that different paths could produce the same results, and provides the opportunity to justify care decisions based solely on cost. Future measurement systems should therefore be able to compare systems and identify the differences and similarities that yield positive outcomes.

The above debate, although relevant, relates only to clinical process and outcomes. Clearly, there is more to improving the quality of care as contemplated in the quality enterprise. The call to increase efficiency, and to reduce systemic waste and overuse of procedures, also involves process in a business operations sense. Said Ms O’Kane: “We’re sending people to see 7 different doctors and assigning a care manager to fill the gaps.” New processes are layered on top of old, and none of it is efficiently coordinated.

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