The global effect of digital health technologies on health workers' competencies and health workplace: an umbrella review of systematic reviews and lexical-based and sentence-based meta-analysis

Abstract

Systematic reviews have quantified the effectiveness, feasibility, acceptability, and cost-effectiveness of digital health technologies (DHTs) used by health-care workers. We aimed to collate available evidence on technologies' effect on health-care workers' competencies and performance. We searched the Cochrane Database of Systematic Reviews, Embase, MEDLINE, Epistemonikos, and Scopus for reviews published from database inception to March 1, 2023. Studies assessing the effects of DHTs on the organisational, socioeconomic, clinical, and epidemiological levels within the workplace, and on health-care workers' performance parameters, were included. Data were extracted and clustered into 25 domains using vote counting based on the direction of effect. The relative frequency of occurrence (RFO) of each domain was estimated using R software. AMSTAR-2 tool was used to appraise the quality of reporting, and the Confidence in the Evidence from Reviews of Qualitative research approach developed by Grading of Recommendations Assessment, Development and Evaluation was used to analyse the certainty of evidence among included studies. The 12 794 screened reviews generated 132 eligible records for assessment. Top-ranked RFO identifiers showed associations of DHT with the enhancement of health-care workers' performance (10·9% [95% CI 5·3-22·5]), improvement of clinical practice and management (9·8% [3·9-24·2]), and improvement of care delivery and access to care (9·2% [4·1-20·9]). Our overview found that DHTs positively influence the daily practice of health-care workers in various medical specialties. However, poor reporting in crucial domains is widely prevalent in reviews of DHT, hindering our findings' generalisability and interpretation. Likewise, most of the included reviews reported substantially more data from high-income countries. Improving the reporting of future studies and focusing on low-income and middle-income countries might elucidate and answer current knowledge gaps.

Figure 1

PRISMA flow diagram Reason 1=wrong intervention or platform was unclear. Reason 2=the study did not provide any relevant outcome influencing health-care workers. Reason 3=targeted population was not health-care workers. Reason 4=study design used did not match our inclusion criteria. *Studies can be accessed upon request.

Figure 2

Relative frequency of occurrence of higher level domains, by major modality of digital health technologies AI=artificial intelligence. CDSS=clinical decision support system. EMR=electronic medical record.