Improving Health-Care Quality Through Measurement

What Is Quality in Health-Care?

Quality can be considered the gap between the care delivered and the care that should be delivered. As highlighted in the seminal publication Crossing the Quality Chasm , abundant evidence suggests that health-care falls short in six dimensions: (1) safety, (2) effectiveness, (3) patient-centeredness, (4) timeliness, (5) efficiency, and (6) equity. These six dimensions comprise the overall concept of health-care quality ( Table 45.1 ). Improving these six dimensions would therefore improve health-care quality by ensuring patients receive care that meets their needs and is based on the best scientific knowledge. Recognizing that health-care quality is multidimensional is the first step to being able to understand and, most importantly, to improve it.

In the United States, these six dimensions of quality are most prominent in the National Strategy for Quality Improvement in Health-care, or simply the National Quality Strategy (NQS). Led by the Agency for Health-care Research and Quality (AHRQ), the NQS was developed through a transparent and collaborative process with the goal to align health-care quality improvement efforts across national, federal, state, and private-sector stakeholders. Many agencies of the US Department of Health and Human Services (HHS) have adopted the NQS, including the Centers for Medicare and Medicaid Services (CMS), as a framework to improve health-care quality.

In addition to the inherent multidimensional nature of quality, there are two additional concepts that should be understood. First, improving quality along one of these dimensions does not exclude the ability to improve along any of the other dimensions of quality. That is, tradeoffs are not inherent. A corollary to this is that improvement along one dimension of quality does not necessarily result in improvement along another dimension. In many instances, although the dimensions of quality are all interconnected to some degree, effort must be spent on simultaneously improving all dimensions of quality.

Second, it is important to recognize that although all dimensions of quality are important, certain dimensions might be considered more important depending on which stakeholder is evaluating the health-care system. For instance, patients have different perspectives of what is “high quality” compared with what payers, policymakers, or providers might consider to be of high quality. Patients might value longer, unhurried face-to-face time during clinic visits with their health-care provider, whereas health-care administrators might wish to minimize this time to maximize the number of patients that can be seen in a day.

Why Improve Quality?

It is important to understand the motivators for measuring and improving quality: What drives quality? These motivations depend on the perspectives of the stakeholders evaluating the care provided and the types of rewards involved. Rewards can be categorized into those that are intrinsic or extrinsic. Intrinsic rewards represent motivations driven by philosophy, such as teaching, learning, or healing. Arguably, health-care professionals entered the profession for intrinsic rewards: to heal patients and to cure them of their ailments. Extrinsic rewards, in contrast, are material goals, such as financial gain. The challenge in health-care has been to figure out when each of these motivations is most effective as a lever to improve quality. Indeed, there exists concern that measuring and reporting of health-care quality might result in punitive action by administrative managers and policymakers, resulting in magnified conflicts between intrinsic and extrinsic rewards. Quality problems typically occur not because of a failure of goodwill, knowledge, effort, or resources devoted to health-care, but because of fundamental shortcomings in the ways care is organized, delivered, or both. Ideally, intrinsic (e.g., curing patients) and extrinsic (e.g., financial gain) motivators can work in tandem to improve health-care quality.

Framework for Measuring Quality

Quality measures (performance measures, metrics, indicators, etc.) are tools used to quantify the care provided to patients. When used in health-care, quality measures assist in determining how well care is provided for certain aspects of care, for certain conditions, or for various populations or communities. In 1966, Donabedian presented the most commonly used framework by which to measure quality in health-care today: structure, process, and outcome ( Box 45.1 ).

The types of measures used depends on the available scientific knowledge connecting them to the quality gap and on the resources needed to measure them. Measuring the totality of care, which often encompasses all types of quality measures across all six dimensions ( Table 45.1 ), is optimal. Structural measures are only as good and useful as the strength of their link to desired processes and outcomes ( Fig. 45.1 ). Similarly, process and outcome measures must be related to each other (i.e., causal) in measurable and reproducible ways to be truly valid and reliable measures of quality. Because of these concerns, outcomes, which represent the bottom line, are arguably more attractive to measure. However, as discussed, without a high level of rigor, there is the likelihood of misclassifying care, which can have unintended consequences, such as rewarding poor care or penalizing optimal care.

In addition to “structure,” “process,” and “outcome,” any combination of these measures can be combined to form a composite measure. A composite measure combines the results of two or more component quality measures, each of which individually reflect quality of care, combined into a single quality measure with a single score to provide a more summative picture. Although attractive because they can measure care across a continuum and can be easier to understand by patients, composite measures have their own share of difficulties. For instance, combining a measure in which performance is generally poor with a measure in which performance is generally good results in a composite measure that may appear average.

As discussed earlier, the perspective of which outcome is important to measure often varies by stakeholder. For example, a patient who did not experience any complications may be dissatisfied with the surgery she received because she was not able to return to her usual activities of daily living as she had hoped, or because her postoperative pain did not resolve as she might have expected and compromised her quality of life. In these situations, the patient perspective can be a more meaningful measure of success. Patient-reported outcome performance measures (PRO-PMs) are quality measures based upon aggregated patient-reported outcomes (PROs) data. PROs measure a patient’s health status, quality of life, health behavior, or experience of care using information that comes directly from the patient, family, or caregiver without interpretation by a health-care provider or anyone else. PRO-PMs share the same qualities of traditional outcome measures (i.e., need for risk adjustment) except they are evaluated from the patient perspective.

Development and Endorsement of Quality Measures

Numerous stakeholders are involved in improving health-care quality, including federal (e.g., AHRQ, CMS) and state government, payers (e.g., Blue Cross Blue Shield), purchasers (e.g., Pacific Business Group on Health), professional societies (e.g., American Medical Association), provider organizations (e.g., American Hospital Association), industries (e.g., Pfizer), nonprofit organizations (e.g., National Committee on Quality Assurance), community health agencies (e.g., Wisconsin Collaborative for Health-care Quality), patients and patient advocates (e.g., National Partnership for Women and Families), and foundations (e.g., Robert Wood Johnson Foundation). Accordingly, just as many have developed and continue to develop quality measures, both broadly across different health-care settings and specific to their agendas, specialties, and constituencies’ needs. Although there are many general principles that should be followed to develop measures that are meaningful, valid, and reliable, Donabedian astutely condensed them into four basic questions :

• 1.

  Who is being assessed?

• 2.

  What are the activities being assessed?

• 3.

  How are these activities supposed to be conducted?

• 4.

  What are they meant to accomplish?

Overall, it is most important to answer the last question and to define the purpose of the quality measure: what is the gap that, when addressed, will improve quality? In general, this involves compiling the evidence base to identify the current practice and what is the “best practice” as supported by current scientific knowledge. The difference between what is done and what should be done is the quality gap. Once these questions are answered, then the technical details of the measure, such as inclusion/exclusion criteria, risk adjustment variables, validity, reliability, can be specified, tested, and implemented ( Box 45.2 ).

Endorsement by the National Quality Forum (NQF) is considered by many to be an essential stamp of approval for quality measures. Founded on recommendation of the 1998 President’s Advisory Commission on Consumer Protection and Quality in the Health-care Industry, the NQF is an independent organization that brings together public- and private-sector stakeholders from across the health-care system to determine high-value measures for improving the nation’s health and health-care. The NQF measure endorsement process, also referred to as the Consensus Development Process, provides the nation with a centralized portfolio of quality measures that meet rigorous evaluation criteria and could be implemented in both accountability and quality improvement programs. Examples of NQF-endorsed perioperative measures are shown in Table 45.2 . In addition to endorsement, the NQF aims to accelerate development of needed measures, to identify high-priority measures, to harmonize measures, to drive more effective implementation of priority measures, and to understand better what does and does not work in quality measurement.

Although NQF endorsement is important and a recognizable achievement, quality measure endorsement is not always necessary. The process of NQF endorsement takes considerable time, which must be weighed against the need for improvement. NQF endorsement is often sought for “high stakes” measures used for purposes of national, large-scale accountability programs (i.e., public reporting or pay-for-performance), such as the CMS Quality Payment Program (QPP) or CMS Hospital Value-based Purchasing Program. The need for quality measure endorsement thus depends on how the quality measure will be used.

Uses of Quality Measures

Quality measures, once developed, specified, and potentially NQF-endorsed, are commonly used in four ways: (1) improving care services and delivery, (2) accreditation and verification, (3) public reporting, and (4) incentive payments or value-based care. All uses share the same goal of improving the quality of health-care delivered but do so with different means depending on the perspective of the stakeholder and the motivation for reward. For instance, clinicians, motivated by intrinsic rewards, use quality measures to assess clinical practices better and to track their implementation. Payers and insurers, motivated by extrinsic rewards, use quality measures to reward success financially and penalize failure. Public reporting of quality measures increases transparency, allowing patients to make more informed choices about providers and facilities.

Quality Improvement

Quality measures have been traditionally used for internal monitoring and quality and improvement (QI/PI) activities. Using quality measures in this way helps providers and institutions track ways to improve care and is related to professional and personal commitments to care as well as institutional expectations. Although quality measures have long been used for internal monitoring and reporting, providers have not been able to compare themselves easily with others because the data elements and collection instruments have not been synchronized. Collecting and reporting the same data using the same specifications helps organizations and providers understand how they perform compared with other organizations. It also enables them to identify opportunities for focused quality improvement efforts ( Box 45.3 ). With the rise of national quality programs, registries, and “big data,” groups of hospitals can network with each other and learn which interventions worked or failed at everyone’s respective institutions.

Accreditation and Verification

Accreditation, or verification, refers to an approval process conducted by independent (nongovernmental) bodies to certify that an institution or individual has met certain standards. Although there are multiple types of accrediting bodies, such as educational (e.g., Accreditation Council for Graduate Medical Education) and professional societies (e.g., ACS Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program), the most well-known accrediting bodies are the Joint Commission for hospitals and the National Committee for Quality Assurance (NCQA) for health plans.