Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: A systematic review.

Barriers and facilitators influencing medication-related CDSS acceptance according to clinicians: A systematic review.
Int J Med Inform. 2021 Aug;152:104506. doi: 10.1016/j.ijmedinf.2021.104506. 

• A systematic review of the literature identified 327 barriers and 291 facilitators for acceptance of medication-related CDSS. Factors most often reported were related to (a lack of) usefulness and relevance of information, and ease of use and efficiency of the system.

A systematic review of theoretical constructs in CDS literature and how they influence adoption and implementation

A systematic review of theoretical constructs in CDS literature.
BMC Med Inform Decis Making March 2021,  21, 102 (2021). https://doi.org/10.1186/s12911-021-01465-2

• This review seeks to understand the features that impact adoption of clinical decision support systems and in turn, successful patient outcomes, by examining the psychological mechanisms that are key to these types of interventions. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) model to explore the psychological characteristics of CDS interventions to predict adoption identified in published research.

And follow up research using UTAUT:

A theory-based meta-regression of factors influencing clinical decision support adoption and implementation.
J Am Med Inform Assoc. 2021 Aug 13:ocab160. doi: 10.1093/jamia/ocab160.

• Analysis of published research of trials that compared a CDS intervention with and without specific factors identified three positive factors which affect CDS effectiveness. They were: low effort to use, low controllability, and providing more infrastructure and implementation strategies to support the CDS. The multivariate analysis suggests that passive CDS could be effective if users believe the CDS is useful and/or social expectations to use the CDS intervention exist.

Clinical Decision Support Systems for Diagnosis in Primary Care: A Scoping Review

Clinical Decision Support Systems for Diagnosis in Primary Care: A Scoping Review. 

Int J Environ Res Public Health. 2021 Aug 10;18(16):8435. doi: 10.3390/ijerph18168435. 

• A review of the literature examining use of decision support systems in diagnosis in primary care concluded that while CDSS and reminder tools have significant effects on screening for common chronic diseases, CDSS has not yet been fully validated for the diagnosis of acute and uncommon chronic diseases.

Decision‐support tools via mobile devices to improve quality of care in primary healthcare settings.

Decision‐support tools via mobile devices to improve quality of care in primary healthcare settings.
Cochrane Database of Systematic Reviews 27 July 2021, Issue 7. Art. No.: CD012944. DOI: 10.1002/14651858.CD012944.pub2.

• A systematic review identified 8 RCTs (none from UK) of examining the effect of decision‐support tools on mobile phones on primary health care, but the evidence is not clear about the effects of these tools on patients' and clients' behaviour and on their health.

Modelling tool to support decision-making in the NHS Health Check programme

Modelling tool to support decision-making in the NHS Health Check programme: workshops, systematic review and co-production with users.
Health Technology Assessment 2021;25(35)

• This report discusses how delivery of the NHS Health Checks programme could be improved, in particular by the use of a web-based tool - workHORSE (working Health Outcomes Research Simulation Environment). A series of workshops with commissioners resulted in a useful ‘real-world’ tool for local commissioners that can calculate the current and potential future benefits of different programmes. The study examined different delivery programmes and their benefit in health and value and impact and reducing inequalities.

Barriers and facilitators to the adoption of electronic clinical decision support systems

Barriers and facilitators to the adoption of electronic clinical decision support systems: a qualitative interview study with UK general practitioners. 

BMC Med Inform Decis Mak. 2021 Jun 21;21(1):193. doi: 10.1186/s12911-021-01557-z.

• Interviews with 11 GPs in London and South England to discuss a hypothetical CDSS that could detect early signs of dementia identified three overarching themes: trust in individual CDSSs; usability of individual CDSSs; and usability of CDSSs in the broader practice context. Building on these findings the researchers make a number of recommendations for CDSS developers to consider when bringing a new CDSS into GP patient records systems.

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A thematic analysis to examine the feasibility of EHR-based clinical decision support for implementing Choosing Wisely® guidelines.

A thematic analysis to examine the feasibility of EHR-based clinical decision support for implementing Choosing Wisely® guidelines.
JAMIA Open. 2021 Jun 16;4(2):ooab031. doi: 10.1093/jamiaopen/ooab031.

• A thematic analysis of interviews with experts discussing the feasibility of implementing “Choosing Wisely” clinical practice guidelines (CPGs) (see UK version here) as clinical decision support (CDS). 
• The research identified five themes:
•  concern about data quality impacts implementation planning; 
• the availability of data in a computable format is a primary factor for implementation feasibility;
•  customized strategies are needed to mitigate uncertainty and ambiguity when translating CPGs to an electronic health record-based tool; 
• misalignment of expected CDS with pre-existing clinical workflows impact implementation; 
• and individual level factors of end-users must be considered when selecting and implementing CDS tools.

Ethics, Transparency and Accountability Framework for Automated Decision-Making

Ethics, Transparency and Accountability Framework for Automated Decision-Making
Cabinet Office, Central Digital & Data Office and the Office for Artificial Intelligence 13 May 2021

• A 7 point framework which will help government departments with the safe, sustainable and ethical use of automated or algorithmic decision-making systems.

The implementation, use and sustainability of a clinical decision support system for medication optimisation in primary care: A qualitative evaluation.

The implementation, use and sustainability of a clinical decision support system for medication optimisation in primary care: A qualitative evaluation.
PLoS One. 2021 May 3;16(5):e0250946. doi: 10.1371/journal.pone.0250946.

• Participants from CCGs and general practices (n=33) were interviewed in a study to understand the factors that influenced the successful implementation and sustained use in primary care of a clinical decision support (CDS) system.

The effects of CDSS for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis.

The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis.
BMC Med Inform Decis Mak. 2021 Mar 10;21(1):98. doi: 10.1186/s12911-020-01376-8.

• Analysis of 45 studies of clinical decision making systems (CDSS) for prescribing show that the use of CDSS in some diseases has positive effects on patient outcomes and physician performance while it has no significant effect on others. In addition, the types of outcomes and the effects of CDSS on the diseases are different.

Use of machine learning to predict clinical decision support compliance, reduce alert burden, and evaluate duplicate laboratory test ordering alerts.

Use of machine learning to predict clinical decision support compliance, reduce alert burden, and evaluate duplicate laboratory test ordering alerts.
JAMIA Open. 2021 Mar 1;4(1):ooab006. doi: 10.1093/jamiaopen/ooab006.

• Researchers sought to develop machine learning models to predict whether a clinician will accept the advice provided by a CDS alert.. The best-performing predictive model achieved an area under the receiver operating characteristic curve (AUC) of 0.82. Incorporating this model into the alerting logic could have averted more than 1900 alerts at a cost of fewer than 200 additional duplicate tests.

Recommendations for the safe, effective use of adaptive CDS in the US healthcare system: an AMIA position paper.

Recommendations for the safe, effective use of adaptive CDS in the US healthcare system: an AMIA position paper.
J Am Med Inform Assoc. 2021 Jan 15:ocaa319. doi: 10.1093/jamia/ocaa319.

• The development and implementation of clinical decision support (CDS) that trains itself and adapts its algorithms based on new data-here referred to as Adaptive CDS-present unique challenges and considerations. In this AMIA position paper, the authors describe current and emerging challenges to the safe use of Adaptive CDS and lay out recommendations for the effective management and monitoring of Adaptive CDS.

Optimizing clinical decision support alerts in electronic medical records

Optimizing clinical decision support alerts in electronic medical records: a systematic review of reported strategies adopted by hospitals.
J Am Med Inform Assoc. 2021 Jan 15;28(1):177-183. doi: 10.1093/jamia/ocaa279.

• A literature review to identify and summarize the current internal governance processes adopted by hospitals for selecting, optimizing, and evaluating clinical decision support (CDS) alerts identified eight papers, seven of which focussed on medication related CDS alerts. A multidisciplinary committee, often in combination with other approaches (eg use of clinician feedback, alert data, literature and drug references, and a visual dashboard) was the most frequent strategy reported by hospitals to optimize their CDS alerts.

Cancer diagnostic tools to aid decision-making in primary care

Cancer diagnostic tools to aid decision-making in primary care: mixed-methods systematic reviews and cost-effectiveness analysis.
Health Technol Assess November 2020;24(66)

• Two systematic reviews have been published which examine the clinical effectiveness (review 1) and the development, validation and accuracy (review 2) of diagnostic prediction models for aiding general practitioners in cancer diagnosis. 
• Results: Systematic review 1 – five studies, of different design and quality, reporting on three diagnostic tools, were included. We found no evidence that using the tools was associated with better outcomes. Systematic review 2 – 43 studies were included, reporting on prediction models, in various stages of development, for 14 cancer sites (including multiple cancers). Most studies relate to QCancer® (ClinRisk Ltd, Leeds, UK) and risk assessment tools.

Integrating the Practical Robust Implementation and Sustainability Model With Best Practices in Clinical Decision Support Design

Integrating the Practical Robust Implementation and Sustainability Model With Best Practices in Clinical Decision Support Design: Implementation Science Approach.
J Med Internet Res. 2020 Oct 29;22(10):e19676. doi: 10.2196/19676.

• Description of an integrated approach toward applying an existing implementation science framework (Practical Robust Implementation and Sustainability Model (PRISM)) with Clinical Design Support design best practices to improve the effectiveness, sustainability, and reproducibility of Clinical Decision Support implementations.

Translating an evidence-based clinical pathway into shareable Clinical Decision System

Translating an evidence-based clinical pathway into shareable CDS: developing a systematic process using publicly available tools.
J Am Med Inform Assoc. 2020 Oct 29:ocaa257. doi: 10.1093/jamia/ocaa257.

• The researchers developed a systematic and transparent process using publicly available tools (eGLIA, GEM Cutter, VSAC, and the CDS Authoring Tool) to translate an evidence-based clinical pathway into a Clinical Quality Language (CQL)-encoded Clinical Decision System artifact.

Clinical decision support tools - NIHR collection

Clinical decision support tools
NIHR Collection 19 October 2020

• This Collection brings together 8 pieces of NIHR research on the use of different clinical decision support tools in various areas of healthcare delivery and includes commentary fro professionals and service users.
• The Alerts included in this collection are:
• A simple test may predict the risk of hospitalisation for flare-up in patients with COPD, a common lung disease
• Decision aids quickly and accurately rule out heart attack for almost half of all patients tested
• Computerised decision support can improve antibiotic prescribing in hospitals
• Tools for GPs can help reduce unnecessary antibiotic prescribing
• Interactive dashboard identifies patients at risk of unsafe prescribing in a flexible and sustainable way
• ICU admission decision support tool showed promise but was rarely used
• Early warning scores for detecting deterioration in adult hospital patients: systematic review and critical appraisal of methodology
• New tool for assessing the severity of type 2 diabetes could help personalise treatment and improve outcomes

Clinical Decision Support May Link Multiple Domains to Improve Patient Care: Viewpoint.

Clinical Decision Support May Link Multiple Domains to Improve Patient Care: Viewpoint. 

JMIR Med Inform. 2020 Oct 16;8(10):e20265. doi: 10.2196/20265.

• A practical overview of current and evolving applications of Clinical Decision Support approaches in a large academic setting [USA] and discussion of the successes and challenges.

GatewayC Cancer Maps

GatewayC Cancer Maps

• The Cancer Maps is an interactive reference tool for GPs based on the NICE NG12 cancer guidelines. Primarily, the tool is designed to enable GPs to take symptoms that patients present with during a consultation and map them on possible suspected cancer pathways.
• There are 4 main ways to use The Cancer Maps :
• As a quick reference to NICE guidance
• As a decision support tool
• As an educational tool
• With patients to reassure or safety net

Testing an individualized digital decision assist system for the diagnosis and management of mental and behavior disorders in children and adolescents.

Testing an individualized digital decision assist system for the diagnosis and management of mental and behavior disorders in children and adolescents.
BMC Med Inform Decis Mak 20, 232 (2020). https://doi.org/10.1186/s12911-020-01239-2

• IDDEAS (Individualised Digital DEcision Assist System) is a [Norway] CDSS for diagnosis and treatment of child and adolescent mental health disorders. The aim of IDDEAS is to enhance quality, competency, and efficiency in child and adolescent mental health services (CAMHS).