Summary: Objectives: To review the current state of research on designing and implementing clinical decision support (CDS) using four current interoperability standards: Fast Healthcare Interoperability Resources (FHIR); Substitutable Medical Applications and Reusable Technologies (SMART); Clinical Quality Language (CQL); and CDS Hooks. Methods: We conducted a review of original studies describing development of specific CDS tools or infrastructures using one of the four targeted standards, regardless of implementation stage. Citations published any time before the literature search was executed on October 21, 2020 were retrieved from PubMed. Two reviewers independently screened articles and abstracted data according to a protocol designed by team consensus. Results: Of 290 articles identified via PubMed search, 44 were included in this study. More than three quarters were published since 2018. Forty-three (98%) used FHIR; 22 (50%) used SMART; two (5%) used CQL; and eight (18%) used CDS Hooks. Twenty-four (55%) were in the design stage, 15 (34%) in the piloting stage, and five (11%) were deployed in a real-world setting. Only 12 (27%) of the articles reported an evaluation of the technology under development. Three of the four articles describing a deployed technology reported an evaluation. Only two evaluations with randomized study components were identified. Conclusion: The diversity of topics and approaches identified in the literature highlights the utility of these standards. The infrequency of reported evaluations, as well as the high number of studies in the design or piloting stage, indicate that these technologies are still early in their life cycles. Informaticists will require a stronger evidence base to understand the implications of using these standards in CDS design and implementation.

Background: On April 23, 2014, US media outlets broadcast reports of excessive wait times and “secret” waitlists at some Veterans Affairs (VA) hospitals, precipitating legislation to increase Veterans’ access to private sector health care. Objective: The aims were to assess changes in Veterans’ distrust in the VA health care system before and after the media coverage and explore sex and racial/ethnic differences in the temporal patterns. Methods: Veterans completed semistructured interviews on health care satisfaction from June 2013 to January 2015, including a validated scale of health system distrust (range: 1–5). We used linear splines with knots at 90-day intervals to assess changes in distrust before and after April 23, 2014 (“day 0”) in linear mixed models. To explore sex and racial/ethnic differences in temporal patterns, we stratified models by sex and tested for interactions of race/ethnicity with time. Results: For women (n=600), distrust scores (mean=2.09) increased by 0.45 in days 0–90 (P<0.01), then decreased by 0.45 in days 90–180 (P<0.01). Among men (n=575), distrust scores (mean=2.05) increased by 0.18 in days 0–90 (P=0.059). Distrust levels were significantly higher for Black versus White women (time adjusted mean difference=0.21) and for Black and Hispanic versus White men (differences=0.26 and 0.18). However, the temporal patterns did not vary by race/ethnicity for women or men (interaction P=0.85 and 0.21, respectively). Conclusions: Health system distrust increased in women following media coverage of VA access problems and was higher in Black/Hispanic versus White Veterans at all time periods. Such perceptions could influence Veteran decisions to seek health care in the community rather than VA.