Structure-Process-Outcome Quality Measures

Structure Measures

Structure measures refers to the conditions under which care is provided, with the notion that if the structure is appropriate, good-quality medical care will follow. Material resources such as adequacy of facilities and equipment are taken into consideration, as are professional and organizational resources that support and direct provision of care (e.g., staff credentials, facility-operating capacities, performance review, and fiscal organization). Donabedian's concept of structure is especially relevant for organizational learning, in terms of encompassing the more stable characteristics of the care delivery system: staffing, equipment, facilities, and the way these are organized to deliver care. It also includes formalized organizational routines, such as the process of passing patient information across shifts.

Using structure to measure the quality of care leads to relatively concrete and accessible information. Structure data are essential to system-level organizational learning and improvement. The primary limitation in using structure is that the relationship between structure and process or structure and outcomes is rarely well established.

Process measures

Process measures of quality refer to things done to or for the patient by practitioners in the course of treatment, including clinical history taking, the appropriateness and thoroughness of physical examinations, the number and type of diagnostic tests given, and technical competence in diagnostic and therapeutic procedures such as surgery. Other process measures include preventive management, coordination and continuity of care, referral criteria, and patient education. Estimates of quality obtained through process measures are not as stable or final as those obtained from outcome measures. Many times, process measures are used to identify whether medicine was practiced properly or not. Process-of-care evaluation has several advantages. It is directly related to the practice of medicine and is relatively easy to conduct. Many diseases have established, peer-reviewed models on which to base evaluations. In addition, data can be analyzed for population studies or health delivery systems where computerized data networks are available. Such measurements provide direct indicators to the areas needing quality improvement.

Two methods are used to measure process quality: explicit and implicit review. Explicit review is based on analyzing medical care from medical records. Under ideal circumstances, the analysis should be based on a set of concrete values formulated by experts or recognized professional organizations such as the American Heart Association. The measurement criteria are developed after careful evaluation of clinical trials, cohort studies, and established practice protocols to produce evidence-based quality indicators. Explicit reviews suffer some drawbacks in that the complexity and variety of medical care makes congruency in formulating such indicators difficult, and each organization can have different criteria. Also, they can be incomplete and fail to reflect the totality of care offered to a patient, as not only physicians are involved in care. To make explicit reviews more meaningful, there is a need to identify the processes that truly improve outcomes and correlate them with clinical judgments individually and not collectively, as each person can have unique factors that can influence outcomes.

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