Is evidence of effectiveness a driver for clinical decision support selection? A qualitative descriptive study of senior hospital staff

Abstract

Background Limited research has focused on understanding if and how evidence of health information technology (HIT) effectiveness drives the selection and implementation of technologies in practice. This study aimed to explore the views of senior hospital staff on the role evidence plays in the selection and implementation of HIT, with a particular focus on clinical decision support (CDS) alerts in electronic medication management systems. Methods A qualitative descriptive design was used. Twenty senior hospital staff from six Australian hospitals in New South Wales and Queensland took part in a semi-structured interview. Interviews were audio-recorded, transcribed, and a general inductive content analysis approach used to identify themes. Results Participants acknowledged the importance of an evidence-base, but reported that selection of CDS alerts, and HIT more broadly, was rarely underpinned by evidence that technologies improve patient care. Instead, investments in technologies were guided by the expectation that benefits will be achieved, bolstered by vendor assurances, and a perception that implementation of HIT is unavoidable. Postponing implementation of a technology until an evidence-base is available was not always feasible. Although some technologies were seen as not requiring an evidence-base, stakeholders viewed evidence as extremely valuable for informing decisions about selection of CDS alerts. Conclusion : Decisions to implement CDS, and technology more broadly, are rarely evidence-based. In the absence of evidence, evaluation or monitoring of technologies post-implementation is critical, particularly to identify new errors or risks associated with HIT implementation and use. Increased transparency from vendors, with technology evaluation outcomes made directly available to healthcare organizations, may result in less reliance on logic, intuition, and vendor assertions, and more evidence-based selection of HIT.

Influential factors in the adoption of clinical decision support systems in hospital settings: a systematic review and meta-synthesis of qualitative studies

“…Similarly, literature has traced many of the setbacks occurring in the implementation and maintenance phase to initial decisions and initiatives made by the leadership of the organisation as to adopting CDSS (Ahmadi et al, 2015(Ahmadi et al, , 2018White et al, 2023). This lends support to the calls for studies aggregating influential factors in the selection and contracting phases of CDSS adoption (Baysari et al, 2023;Liberati et al, 2017;Sutton et al, 2020;Venkatesh et al, 2020).…”

“…There was a lack of consistency with regard to studies' foci so only six studies solely focused on procurement and adoption as the purpose of the study (Baysari et al, 2023;Cresswell et al, 2015Cresswell et al, , 2017Joshi et al, 2022;Lee et al, 2016;Liberati et al, 2017) while the rest mainly focused on development, implementation and utilisation of CDSS. Technology context.…”

“…The lack of evidence-based approach in the selection of CDSS by managers and leaders regarding the actual impact of CDSS on clinical performance and relying on vendors' assurance was reported in the literature. It came as a surprise to clinicians that controlling mechanisms for medical and drug interventions are generally available but for CDSS technologies these rarely exist (Baysari et al, 2023). According to Ash et al (2015), CEOs are heavily motivated to increase their revenue by adopting CDSS and their expectation of what a CDSS can do is surreal.…”

Barriers to Adoption of Tailored Drug–Drug Interaction Clinical Decision Support

“…39 Transcripts were read several times and meaning units were tagged with codes annotated in Microsoft Word. Every set of initial codes generated from individual interviews was constantly compared with previously analyzed data, discussed and validated with another researcher (S.G.), triangulated with previous DDI alert performance and implementation studies, 4,14,40,41 and later categorized into subthemes. Three researchers (T.Z., S.G., and V.S.)…”

“…This question is important because our study suggests that, while technical adoption issues associated with the EHR vendors were the common complaints about implementation inertia, it was the health care organizations that primarily impact the implementation of DDI alerts, which is consistent with previous studies. 14,41 As health care organizations emphasize DDI alerts' impact on costs, productivity, and efficiency, it is imperative to have value metrics that health care systems prioritize (e.g., higher ratings from external quality organizations) to gain the momentum for implementing tailored DDI alerts. However, defining and quantifying these value metrics is challenging and there are no agreed-upon value measures, 11 which presents opportunities for further studies.…”