Impact of sociodemographic patient characteristics on the efficacy of decision AIDS: a patient-level meta-analysis of 7 randomized trials

Circ Cardiovasc Qual Outcomes. 2014 May;7(3):360-7. doi: 10.1161/HCQ.0000000000000006. Epub 2014 May 13.

Abstract

Background: Decision aids (DAs) increase patient knowledge, reduce decisional conflict, and promote shared decision making (SDM). The extent to which they do so across diverse sociodemographic patient groups is unknown.

Methods and results: We conducted a patient-level meta-analysis of 7 randomized trials of DA versus usual care comprising 771 encounters between patients and clinicians discussing treatment options for chest pain, myocardial infarction, diabetes mellitus, and osteoporosis. Using a random effects model, we examined the impact of sociodemographic patient characteristics (age, sex, education, income, and insurance status) on the outcomes of knowledge transfer, decisional conflict, and patient involvement in SDM. Because of small numbers of people of color in the study population, we were not powered to investigate the role of race. Most patients were aged ≥65 years (61%), white (94%), and women (59%); two thirds had greater than a high school education. Compared with usual care, DA patients gained knowledge, were more likely to know their risk, and had less decisional conflict along with greater involvement in SDM. These gains were largely consistent across sociodemographic patient groups, with DAs demonstrating similar efficacy when used with vulnerable patients such as the elderly and those with less income and less formal education. Differences in efficacy were found only in knowledge of risk in 1 subgroup, with greater efficacy among those with higher education (35% versus 18%; P=0.02).

Conclusions: In this patient-level meta-analysis of 7 randomized trials, DAs were efficacious across diverse sociodemographic groups as measured by knowledge transfer, decisional conflict, and patient involvement in SDM. To the extent that DAs increase patient knowledge and participation in SDM, they have potential to impact health disparities related to these factors.

Keywords: decision making; decision support techniques.

Publication types

  • Evaluation Study
  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Decision Making
  • Decision Support Techniques*
  • Female
  • Humans
  • Male
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Patient Participation
  • Randomized Controlled Trials as Topic
  • Socioeconomic Factors*
  • United States