Implementation costs of hospital-based computerised decision support systems: a systematic review

Abstract

Background The importance of accurately costing implementation strategies is increasingly recognised within the field of implementation science. However, there is a lack of methodological guidance for costing implementation, particularly within digital health settings. This study reports on a systematic review of costing analyses conducted alongside implementation of hospital-based computerised decision support systems. Methods PubMed, Embase, Scopus and CINAHL databases were searched between January 2010 and August 2021. Two reviewers independently screened and selected original research studies that were conducted in a hospital setting, examined the implementation of a computerised decision support systems and reported implementation costs. The Expert Recommendations for Implementing Change Framework was used to identify and categorise implementation strategies into clusters. A previously published costing framework was applied to describe the methods used to measure and value implementation costs. The reporting quality of included studies was assessed using the Consolidated Health Economic Evaluation Reporting Standards checklist. Results Titles and abstracts of 1836 articles were screened, with nine articles eligible for inclusion in the review. Implementation costs were most frequently reported under the ‘evaluative and iterative strategies’ cluster, followed by ‘provide interactive assistance’. Labour was the largest implementation-related cost in the included papers, irrespective of implementation strategy. Other reported costs included consumables, durable assets and physical space, which was mostly associated with stakeholder training. The methods used to cost implementation were often unclear. There was variation across studies in the overall quality of reporting. Conclusions A relatively small number of papers have described computerised decision support systems implementation costs, and the methods used to measure and value these costs were not well reported. Priorities for future research should include establishing consistent terminology and appropriate methods for estimating and reporting on implementation costs. Trial registration The review protocol is registered with PROSPERO (ID: CRD42021272948).

Development of Cost-IS (costing implementation strategies) instrument for digital health solutions: a modified e-Delphi study

“…In the previous review, cost was de ned as the nancial impact of an implementation effort which included costs associated with the intervention, the implementation strategies used, and the location of service delivery. Cost-IS is focused on costing implementation strategies to support appropriate resourcing of implementation efforts and to address the knowledge gap in implementation science research [9].…”

“…The pragmatic approach combines an established business accounting technique (time-driven activitybased costing-TDABC) with an implementation science framework (the Proctor framework) to cost implementation strategies [2]. TDABC is similar to staff time tracking which Cost-IS was developed from because it was a common method used for costing implementation in practice [9]. As a result, Cost-IS shares some similarities with the TDABC pragmatic method.…”

“…An initial prototype of the implementation costing instrument was developed from the ndings of a literature review [6] and qualitative interview study [9]. It was observed in the literature review that there was considerable inconsistency and ambiguity in methods used to cost digital health implementation strategies.…”

“…Phase 1 involved a systematic literature review to identify the nature of implementation costs and the methods used to measure and value these costs, within the context of hospital-based clinical decision support systems initiatives [6]. Phase 2 consisted of qualitative semi-structured interviews that outlined current practices for capturing the costs associated with implementing digital health initiatives in hospital settings [9]. Here we report on the nal phase, which aimed to establish consensus regarding core components and design of the implementation costing instrument using a modi ed electronic-Delphi (e-Delphi) process.…”

Achieving Value by Risk Stratification With Machine Learning Model or Clinical Risk Score in Acute Upper Gastrointestinal Bleeding: A Cost Minimization Analysis

“…Implementation costs were estimated from published studies for hospital-based computerized decision support systems that covered a wide range of clinical tasks, settings, personnel availability, and expertise (see Supplementary Table 8, Supplementary Digital Content, http://links.lww.com/AJG/D58) (8,9).…”