Effects of computerised clinical decision support systems (CDSS) on nursing and allied health professional performance and patient outcomes: a systematic review of experimental and observational studies

Abstract

ObjectiveComputerised clinical decision support systems (CDSS) are an increasingly important part of nurse and allied health professional (AHP) roles in delivering healthcare. The impact of these technologies on these health professionals’ performance and patient outcomes has not been systematically reviewed. We aimed to conduct a systematic review to investigate this.Materials and methodsThe following bibliographic databases and grey literature sources were searched by an experienced Information Professional for published and unpublished research from inception to February 2021 without language restrictions: MEDLINE (Ovid), Embase Classic+Embase (Ovid), PsycINFO (Ovid), HMIC (Ovid), AMED (Allied and Complementary Medicine) (Ovid), CINAHL (EBSCO), Cochrane Central Register of Controlled Trials (Wiley), Cochrane Database of Systematic Reviews (Wiley), Social Sciences Citation Index Expanded (Clarivate), ProQuest Dissertations & Theses Abstracts & Index, ProQuest ASSIA (Applied Social Science Index and Abstract), Clinical Trials.gov, WHO International Clinical Trials Registry (ICTRP), Health Services Research Projects in Progress (HSRProj), OpenClinical(www.OpenClinical.org), OpenGrey (www.opengrey.eu), Health.IT.gov, Agency for Healthcare Research and Quality (www.ahrq.gov). Any comparative research studies comparing CDSS with usual care were eligible for inclusion.ResultsA total of 36 106 non-duplicate records were identified. Of 35 included studies: 28 were randomised trials, three controlled-before-and-after studies, three interrupted-time-series and one non-randomised trial. There were ~1318 health professionals and ~67 595 patient participants in the studies. Most studies focused on nurse decision-makers (71%) or paramedics (5.7%). CDSS as a standalone Personal Computer/LAPTOP-technology was a feature of 88.7% of the studies; only 8.6% of the studies involved ‘smart’ mobile/handheld-technology.DiscussionCDSS impacted 38% of the outcome measures used positively. Care processes were better in 47% of the measures adopted; examples included, nurses’ adherence to hand disinfection guidance, insulin dosing, on-time blood sampling and documenting care. Patient care outcomes in 40.7% of indicators were better; examples included, lower numbers of falls and pressure ulcers, better glycaemic control, screening of malnutrition and obesity and triaging appropriateness.ConclusionCDSS may have a positive impact on selected aspects of nurses’ and AHPs’ performance and care outcomes. However, comparative research is generally low quality, with a wide range of heterogeneous outcomes. After more than 13 years of synthesised research into CDSS in healthcare professions other than medicine, the need for better quality evaluative research remains as pressing.

The Effect of Clinical Decision Support Systems on Patients, Nurses, and Work Environment in ICUs

“…Other studies in the literature supported these findings, reporting that the use of CDSS in ICU reduced medication errors, the length of hospital stay, and mortality rates and facilitated the clinical follow-up of patients. 5,6 Contrary to these findings, only two studies included in our study described the adverse effects of CDSS use on patient care outcomes in the ICU. 11, 23 Furukawa et al 11 stated that lack of adaptation and limited information on the use of CDSS in ICUs may cause adverse events, especially those related to medication management.…”

“…[3][4][5] The CDSS shortens the length of hospital stay and increases the quality of patient care by supporting nurses in reaching correct clinical decisions. [4][5][6] The CDSS is an essential component of the ICU. Therefore, ICU nurses need to understand and evaluate the functions and algorithms of CDSS correctly.…”

Artificial intelligence in clinical decision support systems for oncology

“…However, the CDSS can only be regarded as a member of the MDT team as shown in Figure 2 . After more than 20 years of development, the CDSS has played an important role in disease management, radiation dose calculation, image analysis, blood bank systems, nursing and other fields 34 - 36 . At present, most clinical studies on the reliability of CDSS has compared the schemes of MDT and MDT plus CDSS to explore the help provided by the AI system to doctors at different levels and for different diseases, which is closely related to the ethics of AI technology in clinical diagnosis and treatment decision-making 37 .…”

Surveillance and patient safety in nursing research: A bibliometric analysis from 1993 to 2023

“…With regard to the organizational context of surveillance, nurse staffing and nursing resources have been associated to patient outcomes and safety (Griffiths et al, 2018; West et al, 2009), as well as the healthcare organization's culture and safety climate (Peet et al, 2019; Thornton Bacon et al, 2021). As to the technological context, nurses' surveillance interventions may be enabled by their use of health information technology (IT)‐based systems such as clinical information systems (CIS; Islam et al, 2018), clinical decision support systems (CDSS; Mebrahtu et al, 2021), artificial intelligence (AI)‐based systems (Raymond et al, 2022) and early warning systems (EWS) in particular (Lee et al, 2020). And apart from their professional and regulatory context, the environmental context of nurses' surveillance interventions has been characterized by their adherence to practice guidelines (Pella et al, 2018) and standards (Gorski et al, 2021), and by their membership in practice communities (Terry et al, 2020).…”