Process-Based Measures of Quality: The Need for Detailed Clinical Data in Large Health Care Databases

The Institute of Medicine (IOM) defines health care quality as the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge [1]. Increasing the likelihood of desired health outcomes means achieving better personal health than would occur in the natural history of a person who does not seek health care. The phrase acknowledges that physicians cannot guarantee improved health; at best, they can provide services that influence the course and quality of life. The report emphasizes that the word desired in the phrase desired health outcomes indicates the need to satisfy patient preferences about the outcomes of health care. The phrase consistent with current professional knowledge emphasizes that higher-quality health care incorporates the best available scientific evidence on the services that are likely to improve outcomes. How can the medical community move from this definition to that of computing measurements of the quality of health care? Thirty years ago, Donabedian [2] proposed that data used to measure the quality of health care be classified according to the structure, processes, and outcomes of care as follows: 1) The structure of health care relates to adequacy of the facilities, personnel, and policies to deliver medical care; 2) the processes of health care are the services that are provided to or for patients or by patients themselves on medical advice; and 3) the outcomes of health care are the changes that are observed in the person's health status after allowing for everything other than health care, such as the patient's illness, severity of the illness, and availability of effective prevention or treatment [2]. Applying Donabedian's terminology to the IOM's definition suggests that quality measures can be based on data on health care outcomes as long as any change in outcomes can be attributed to the health care provided. Alternately, the IOM suggests that quality measures can be based on completing processes that experts agree improve outcomes, as shown by scientific evidence. In either case, patient preferences must guide the outcomes sought and the processes selected. This article addresses process-based measures. Computing Process-Based Measures Process-based measures of health care quality can be constructed as follows. First, experts combine evidence from many research studies to create evidence-based guidelines on clinical practices. These guidelines summarize recommendations for the care of patients with a given illness. Patients who are eligible to receive medical care on the basis of a specific guideline are then identified. A criterion for quality is also created to determine which patients actually received medical care as recommended by the guideline. The number of patients who received guideline-related care is divided by the number of patients who are eligible to receive that care. Rates that describe the extent to which patients receive processes of health care as recommended by evidence-based guidelines are thus computed [3]. One problem is obvious: Patients do not always fit neatly into guidelines. For example, a patient may decline recommended health care or a provider may appropriately reject a guideline recommendation on the basis of circumstances or patient preferences. In both examples, the guideline-related criterion misclassifies the patient as receiving inappropriate care and therefore represents a measurement error. Although measurement errors cannot be eliminated, they can be minimized by including obvious exceptions to a guideline in the quality of care criteria [4]. Because some measurement errors are inevitable, rates that compare different providers or the same provider at different times must be used with appropriate caution when it is being determined whether the quality of health care differs. Examples of Process-Based Measures Many potentially useful process-based measures of quality exist because a sequence of many processes of health care must be successfully completed to improve health outcomes. Failure at any step in the sequence decreases the likelihood of improved outcomes. Therefore, processes of health care criteria are often constructed as a set, with each criterion relating to one of many steps in a sequence. Successive criteria in a set may apply to different subgroups of patients because the criteria closely follow a clinical pathway that incorporates a branching logic of sound clinical practice (for example, if a given clinical finding exists, then choose test or treatment A; if it does not exist, then choose test or treatment B). When the clinical pathway branches, different subgroups of patients are formed. Because each subgroup requires different therapeutic management, different quality criteria apply. Some examples of questions that can be answered by measuring the quality of various processes follow. Accessibility of care. Do clinicians detect and treat treatable disease in their enrolled populations? For example, of patients with recent myocardial infarction and one to three diseased coronary arteries, what percentage has undergone percutaneous angioplasty or coronary artery bypass graft surgery? Measurement can be refined to minimize error by excluding patients who have common contraindications to either procedure. Adequacy of collecting clinical data on patients. Do clinicians collect and document data that are critical to confirming the diagnosis and selecting appropriate treatment when taking the patient's history and examining the patient? For example, what percentage of patients who are scheduled for coronary artery bypass graft surgery has had a determination of left ventricular ejection fraction to assess risk status? Accuracy of diagnosis. Are diagnoses missed? For example, of patients who attended primary care visits during the past year and cited probable depression on a screening questionnaire, what percentage was further evaluated or treated by the primary care physician or referred to a specialist? Are diagnoses supported by the information collected? For example, of patients in whom chronic obstructive pulmonary disease was diagnosed, what percentage had a productive cough that lasted 3 or more months for 2 consecutive years and dyspnea on exertion or a FEV1 of less than 60%? Correct diagnosis is vital for both patient care and valid comparisons of data on health care outcomes. Valid comparisons of diagnosis-specific outcomes cannot be made if some providers misdiagnose or fail to diagnose illnesses. Appropriate decision making on treatment regimens and self-care counseling. Do clinicians appropriately choose treatment regimens and counsel patients on self-care according to the presumed or provisional diagnosis and patient preferences? For example, what percentage of patients in whom peptic ulcer disease was diagnosed has been tested for Helicobacter pylori infection? What percentage of patients who tested positive for H. pylori infection is being treated with amoxicillin, tetracycline, metronidazole, or clarithromycin? This example demonstrates a sequence of two indicators that form a branching clinical pathway as previously described. Do physicians counsel patients on self-care when appropriate? For example, what percentage of persons with asthma who receive ongoing treatment has been instructed in the use of a peak flow meter for monitoring exacerbations of their disease? Disease monitoring and therapy. Do clinicians adequately monitor the chronic illnesses of patients to permit adjustments of therapy that control symptoms, improve function, and prevent or detect and treat complications? For example, what percentage of insulin-treated diabetic patients who receive ongoing treatment is monitored for glycemia control at defined intervals with a glycosylated hemoglobin test or the equivalent? Appropriate health promotion and disease prevention. Do persons in a target population have access to health promotion and disease prevention services that address each person's risk for disease? For example, of persons who are known tobacco smokers and are receiving ongoing treatment, what percentage has been advised to quit smoking in the past year? Safe, timely, and effective implementation of tests, procedures, and therapy. Are tests, procedures, and drug protocols managed competently, safely, and in an appropriate time frame to improve outcomes? For example, of patients who arrive in the emergency department with chest pains of more than 30 minutes but less than 6 hours in duration and had confirmed acute myocardial infarction without specific contraindications to thrombolytic therapy, what percentage receives thrombolytic agents within 2 hours of arrival? Communication with patients. Do patients obtain information and encouragement to mobilize their own resources to promote their health, and are they involved in decisions to the extent that they desire? For example, of patients who have had mastectomies for breast cancer, what percentage would answer yes to the question, Were you involved less than you wanted to be in the decision to have your mastectomy? The foregoing list of health care processes is only a brief discussion of the number and complexity of processes that contribute to improvement of health and satisfaction of recipients and that can be measured. However, a practical problem hinders large-scale use of process-based measures because sufficient details on clinical data are difficult to obtain. The complexities of clinical practice cannot be captured because most existing large databases lack these details and therefore cannot create measures that are credible to clinicians. The value of process-based measures reinforces the urgency to continue enriching large health care databases by adding important clinical data. Using Process-Based Measures Various parties are interested in defining and measuring health