Closing the quality gap: revisiting the state of the science (vol. 3: quality improvement interventions to address health disparities).

Objective: This review evaluates the effectiveness of quality improvement (QI) strategies in reducing disparities in health and health care.

Data sources: We identified papers published in English between 1983 and 2011 from the MEDLINE® database, the Cumulative Index of Nursing and Allied Health Literature (CINAHL), Web of Science Social Science Index, and PsycINFO.

Review methods: All abstracts and full-text articles were dually reviewed. Studies were eligible if they reported data on effectiveness of QI interventions on processes or health outcomes in the United States such that the impact on a health disparity could be measured. The review focused on the following clinical conditions: breast cancer, colorectal cancer, diabetes, heart failure, hypertension, coronary artery disease, asthma, major depressive disorder, cystic fibrosis, pneumonia, pregnancy, and end-stage renal disease. It assessed health disparities associated with race or ethnicity, socioeconomic status, insurance status, sexual orientation, health literacy/numeracy, and language barrier. We evaluated the risk of bias of individual studies and the overall strength of the body of evidence based on risk of bias, consistency, directness, and precision.

Results: Nineteen papers, representing 14 primary research studies, met criteria for inclusion. All but one of the studies incorporated multiple components into their QI approach. Patient education was part of most interventions (12 of 14), although the specific approach differed substantially across the studies. Ten of the studies incorporated self-management; this would include, for example, teaching individuals with diabetes to check their blood sugar regularly. Most (8 of 14) included some sort of provider education, which may have focused on the clinical issue or on raising awareness about disparities affecting the target population. Studies evaluated the effect of these strategies on disparities in the prevention or treatment of breast or colorectal cancer, cardiovascular disease, depression, or diabetes. Overall, QI interventions were not shown to reduce disparities. Most studies have focused on racial or ethnic disparities, with some targeted interventions demonstrating greater effect in racial minorities--specifically, supporting individuals in tracking their blood pressure at home to reduce blood pressure and collaborative care to improve depression care. In one study, the effect of a language-concordant breast cancer screening intervention was helpful in promoting mammography in Spanish-speaking women. For some depression care outcomes, the collaborative care model was more effective in less-educated individuals than in those with more education and in women than in men.

Conclusions: The literature on QI interventions generally and their ability to improve health and health care is large. Whether those interventions are effective at reducing disparities remains unclear. This report should not be construed to assess the general effectiveness of QI in the health care setting; rather, QI has not been shown specifically to reduce known disparities in health care or health outcomes. In a few instances, some increased effect is seen in disadvantaged populations; these studies should be replicated and the interventions studied further as having potential to address disparities.