Techniques to Improve Physicians' Use of Diagnostic Tests

Objectives.— To review the published literature on interventions aimed at improving physicians' testing practices and propose methodologic standards for these studies and to review selected studies using the PRECEDE framework, a behavioral model that helps categorize interventions based on which behavioral factors are being affected. Data Sources.— MEDLINE, EMBASE, and HEALTHStar databases were searched for the years 1966 to January 1, 1998, for English-language articles pertaining to diagnostic testing behavior; bibliographies were scanned to identify articles of potential interest; and researchers in health services, health behavior, and behavior modification were contacted for proprietary and other unpublished articles. Study Selection.— A total of 102 articles were identified that described the results of interventions aimed at changing physicians' testing practices. We included the 49 studies that compared diagnostic testing practices in intervention and control groups. Data Extraction.— Two investigators independently reviewed each article in a blinded fashion using a standard data collection form to obtain a methodologic score and to abstract the key elements of each intervention. Data Synthesis.— On a 38-point methodologic criteria scale, the mean±SD score was 13 ± 4.4. The desired behavior change was reported in the intervention group in 37 (76%) of 49 studies. Twenty-four (86%) of 28 interventions targeted at many behavioral factors were successful, while 13 (62%) of 21 studies aimed at a single behavioral factor were successful (P=.12). Conclusions.— A majority of interventions to improve physicians' testing practices reported in the literature claimed success, with interventions based on multiple behavioral factors trending toward being more successful. While methodologic flaws hamper drawing strong conclusions from this literature, application of a behavioral framework appears to be useful in explaining interventions that are successful and can facilitate interpretation of intervention results. DIAGNOSTIC TESTING and imaging are essential tools for disease screening, diagnosis, and monitoring. These aspects of medical care represent an enormous expenditure1 and studies suggest wide variation in test ordering behavior for seemingly similar indications.2- 4 Several factors that may explain this variation include physicians' inability to estimate test performance characteristics, inaccurate interpretation of diagnostic test results,5- 12 and rapid advances in diagnostic technology that make it difficult for clinicians to stay abreast of the most effective testing strategies. Improving the appropriateness of testing behavior is a major focus of quality improvement, and many interventions have targeted laboratory and radiographic test ordering. Intervention strategies have included educational programs, guideline development and implementation, utilization audits, and economic incentives. Studies of interventions to modify physicians' test ordering behavior suggest that behavior change rarely can be accomplished solely through education, feedback of laboratory utilization data has inconsistent effects, rewarding physicians for improved ordering practices may result in short-term behavior change only, and testing guidelines have a variable effect depending on the implementation of the guidelines.13- 17 Nearly every strategy has had both success and failure, providing limited guidance for designing new or more effective strategies. Past reviews of this subject14- 18 have not discriminated among tests used for screening, diagnosis, or monitoring—clinical situations that profoundly impact physicians' motivation and willingness to tolerate uncertainty and their test ordering behavior. Interventions aimed at screening generally have used accepted algorithms and attempt to enhance test usage, quite a different challenge than tests used for diagnosis, which are generally overused. No standardized evaluation of the methodology used in these interventions has been applied. Finally, and perhaps most importantly, the literature provides no evidence that the interventions utilized known behavioral theory. The PRECEDE model of behavior change18 is a standardized framework that has been used to design successful, large-scale health interventions.19,20 PRECEDE incorporates 3 types of factors that precipitate or inhibit behavior change—predisposing, enabling, and reinforcing—and can be described through a clinical example. A 45-year-old man complains of chronic lower back pain and sciatica. His physician believes that this patient is at risk for metastatic cancer, leading him to order an imaging study. This physician's perception of his patient's risk for cancer exemplifies a predisposing factor, which includes other cognitive attributes such as attitudes or knowledge, underlying testing behavior. Enabling factors are skills, resources, or structural barriers that facilitate or prevent behavior. Extending the above example, if the physician had access to a specialist in his practice whom he could consult, he might learn that sciatica rarely represents metastatic cancer in patients younger than 50 years.21 Hence, proximity to an expert opinion might enable the physician to take a "wait and see" approach instead of ordering imaging. Reinforcing factors reward a specific behavior through feedback. In this example, on follow-up the patient's back and leg pain remits, reinforcing the importance of examining for sciatica and that a wait and see approach is often appropriate in lower back pain. Predisposing, enabling, and reinforcing factors can facilitate or hinder behaviors. They are not mutually exclusive nor are their effects the same in all settings. For instance, a diagnostic guideline outlining indications for imaging studies printed on a radiology ordering form may guide physicians who do not know current recommendations, thus changing attitudes or predisposing factors, but reinforce the ordering practices of others who are more knowledgeable. These guidelines may also act as a memory aid for other clinicians who have heard about the recommendations, but do not remember them. Thus, the guideline-based order form can act to enable appropriate ordering. Analysis of behavior change in terms of predisposing, reinforcing, and enabling factors has proven robust in behavior change planning for a variety of behaviors at many levels, including individual, institutional, and community.18 These groupings of variables encapsulate much of what has been learned empirically in the fields of psychology, sociology, and planned change. Because most behaviors are determined by multiple factors, it follows that interventions that address several key factors are more likely to be successful than unidimensional interventions. This observation was made by Oxman et al,22 who have developed a typology of interventions to change physician behavior. We elected to use the PRECEDE framework to categorize studies in our review since we believe it has greater explanatory power. We reviewed the literature on interventions to modify physician testing behavior for methodologic rigor and whether known and effective behavioral principles were utilized. We hypothesized that multidimensional interventions that target more than 1 behavioral factor would be most effective.