Effectiveness of clinical dashboards as audit and feedback or clinical decision support tools on medication use and test ordering: a systematic review of randomized controlled trials

Clinical dashboard development and implementation to standardize data capture and reporting across health-system specialty pharmacies

PURPOSE

To describe the development and implementation of clinical dashboards to standardize data capturing and reporting across multiple partner health systems.

SUMMARY

Between July and September 2020, clinical dashboards were developed and implemented across multiple partner health-system specialty pharmacies (HSSPs) located throughout the United States. The dashboards were developed via collaboration between personnel involved in clinical subcommittees, clinical outcomes, data analytics, information technology, and clinical and central operations. Utilizing a cloud-scale business intelligence service, patient clinical data documented in a shared patient management system was utilized to create customizable dashboards that displayed patient-reported outcome measures, collected laboratory or test results, and completed pharmacist interventions. Separate dashboards were developed for several disease states and/or medication classes. Based on specialty pharmacy recommendations, medical literature, and clinical guidelines, internally developed disease-specific protocols defined data included in the dashboards and ensured consistent data collection amongst partner health systems. Having access to real-time clinical information allows health systems to closely monitor performance metrics, track patient outcomes, and identify operational gaps.

CONCLUSION

Accurately capturing and reporting clinical metrics using clinical dashboards can assist HSSPs in delivering high-quality care. Having access to clinical outcome measures allows HSSPs to better understand the impact of their services on patients' health and quality of life. Health systems can utilize this data to analyze trends and recognize areas of opportunity so that measures can be taken to improve patient care.

Compulsory Indications in Hospital Prescribing Software Tested with Antibacterial Prescriptions

The aim was to assess how making the indication field compulsory in our electronic prescribing system influenced free text documentation and to visualise prescriber behaviour. The indication field was made compulsory for seven antibacterial medicines. Text recorded in the indication field was manually classified as 'indication present', 'other text', 'rubbish text', or 'blank'. The proportion of prescriptions with an indication was compared for four weeks before and after the intervention. Indication provision increased from 10.6% to 72.4% (p<0.01) post-intervention. 'Other text' increased from 7.6% to 25.1% (p<0.01), and 'rubbish text' from 0.0% to 0.6% (p<0.01). Introducing the compulsory indication field increased indication documentation substantially with only a small increase in 'rubbish text'. An interactive report was developed using a live data extract to illustrate indication provision for all medicines prescribed at our tertiary hospital. The interactive report was validated and locally published to support audit and quality improvement projects.

What is the quantity, quality and type of systematic review evidence available to inform the optimal prescribing of statins and antihypertensives? A systematic umbrella review and evidence and gap map

OBJECTIVES

We aimed to map the systematic review evidence available to inform the optimal prescribing of statins and antihypertensive medication.

DESIGN

Systematic umbrella review and evidence and gap map (EGM).

DATA SOURCES

Eight bibliographic databases (Cochrane Database of Systematic Reviews, CINAHL, EMBASE, Health Management Information Consortium, MEDLINE ALL, PsycINFO, Conference Proceedings Citation Index-Science and Science Citation Index) were searched from 2010 to 11 August 2020. Update searches conducted in MEDLINE ALL 2 August 2022. We searched relevant websites and conducted backwards citation chasing.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

We sought systematic reviews of quantitative or qualitative research where adults 16 years+ were currently receiving, or being considered for, a prescription of statin or antihypertensive medication. Eligibility criteria were applied to the title and abstract and full text of each article independently by two reviewers.

DATA EXTRACTION AND SYNTHESIS

Quality appraisal was completed by one reviewer and checked by a second. Review characteristics were tabulated and incorporated into an EGM based on a patient care pathway. Patients with lived experience provided feedback on our research questions and EGM.

RESULTS

Eighty reviews were included within the EGM. The highest quantity of evidence focused on evaluating interventions to promote patient adherence to antihypertensive medication. Key gaps included a lack of reviews synthesising evidence on experiences of specific interventions to promote patient adherence or improve prescribing practice. The evidence was predominantly of low quality, limiting confidence in the findings from individual reviews.

CONCLUSIONS

This EGM provides an interactive, accessible format for policy developers, service commissioners and clinicians to view the systematic review evidence available relevant to optimising the prescribing of statin and antihypertensive medication. To address the paucity of high-quality research, future reviews should be conducted and reported according to existing guidelines and address the evidence gaps identified above.

Acceptance and use of a clinical decision support system in musculoskeletal pain disorders - the SupportPrim project

BACKGROUND

We have developed a clinical decision support system (CDSS) based on methods from artificial intelligence to support physiotherapists and patients in the decision-making process of managing musculoskeletal (MSK) pain disorders in primary care. The CDSS finds the most similar successful patients from the past to give treatment recommendations for a new patient. Using previous similar patients with successful outcomes to advise treatment moves management of MSK pain patients from one-size fits all recommendations to more individually tailored treatment. This study aimed to summarise the development and explore the acceptance and use of the CDSS for MSK pain patients.

METHODS

This qualitative study was carried out in the Norwegian physiotherapy primary healthcare sector between October and November 2020, ahead of a randomised controlled trial. We included four physiotherapists and three of their patients, in total 12 patients, with musculoskeletal pain in the neck, shoulder, back, hip, knee or complex pain. We conducted semi-structured telephone interviews with all participants. The interviews were analysed using the Framework Method.

RESULTS

Overall, both the physiotherapists and patients found the system acceptable and usable. Important findings from the analysis of the interviews were that the CDSS was valued as a preparatory and exploratory tool, facilitating the therapeutic relationship. However, the physiotherapists used the system mainly to support their previous and current practice rather than involving patients to a greater extent in decisions and learning from previous successful patients.

CONCLUSIONS

The CDSS was acceptable and usable to both the patients and physiotherapists. However, the system appeared not to considerably influence the physiotherapists' clinical reasoning and choice of treatment based on information from most similar successful patients. This could be due to a smaller than optimal number of previous patients in the CDSS or insufficient clinical implementation. Extensive training of physiotherapists should not be underestimated to build understanding and trust in CDSSs.

Post-implementation optimization of medication alerts in hospital computerized provider order entry systems: a scoping review

OBJECTIVES

A scoping review identified interventions for optimizing hospital medication alerts post-implementation, and characterized the methods used, the populations studied, and any effects of optimization.

MATERIALS AND METHODS

A structured search was undertaken in the MEDLINE and Embase databases, from inception to August 2023. Articles providing sufficient information to determine whether an intervention was conducted to optimize alerts were included in the analysis. Snowball analysis was conducted to identify additional studies.

RESULTS

Sixteen studies were identified. Most were based in the United States and used a wide range of clinical software. Many studies used inpatient cohorts and conducted more than one intervention during the trial period. Alert types studied included drug-drug interactions, drug dosage alerts, and drug allergy alerts. Six types of interventions were identified: alert inactivation, alert severity reclassification, information provision, use of contextual information, threshold adjustment, and encounter suppression. The majority of interventions decreased alert quantity and enhanced alert acceptance. Alert quantity decreased with alert inactivation by 1%-25.3%, and with alert severity reclassification by 1%-16.5% in 6 of 7 studies. Alert severity reclassification increased alert acceptance by 4.2%-50.2% and was associated with a 100% acceptance rate for high-severity alerts when implemented. Clinical errors reported in 4 studies were seen to remain stable or decrease.

DISCUSSION

Post-implementation medication optimization interventions have positive effects for clinicians when applied in a variety of settings. Less well reported are the impacts of these interventions on the clinical care of patients, and how endpoints such as alert quantity contribute to changes in clinician and pharmacist perceptions of alert fatigue.

CONCLUSION

Well conducted alert optimization can reduce alert fatigue by reducing overall alert quantity, improving clinical acceptance, and enhancing clinical utility.

Clinical decision support and electronic interventions to improve care quality in chronic liver diseases and cirrhosis

Significant quality gaps exist in the management of chronic liver diseases and cirrhosis. Clinical decision support systems-information-driven tools based in and launched from the electronic health record-are attractive and potentially scalable prospective interventions that could help standardize clinical care in hepatology. Yet, clinical decision support systems have had a mixed record in clinical medicine due to issues with interoperability and compatibility with clinical workflows. In this review, we discuss the conceptual origins of clinical decision support systems, existing applications in liver diseases, issues and challenges with implementation, and emerging strategies to improve their integration in hepatology care.

Use of a Medication Safety Audit and Feedback Tool in the Emergency Department Is Affected by Prescribing Characteristics

BACKGROUND

The Enhancing Quality of Prescribing Practices for Older Veterans Discharged from the Emergency Department (EQUIPPED) program developed an audit and feedback health information technology (IT) solution with the intent to replace the in-person academic detailing service provided by the program. The EQUIPPED dashboard provides emergency department (ED) providers with a personalized view of their prescribing performance.

OBJECTIVES

Here, we analyze the association between ED provider characteristics and viewership of the EQUIPPED dashboard, adding insight into strategies for addressing barriers to initial use.

METHODS

We performed a retrospective analysis of EQUIPPED dashboard viewership among four Veterans Affairs (VA) EDs. We extracted quantitative data from user interaction logs to determine evidence of dashboard use. Provider characteristics and baseline potentially inappropriate medication (PIM) prescribing rate were extracted from the VA's Corporate Data Warehouse. Logistic regression was used to examine the association between dashboard use and provider characteristics.

RESULTS

A total of 82 providers were invited to receive audit and feedback via the EQUIPPED dashboard. Among invited providers, 40 (48.7%) had evidence of at least 1 dashboard view during the 1-year feedback period. Adjusted analyses suggest that providers with a higher baseline PIM prescribing rate were more likely to use the dashboard (odds ratio [OR]: 1.22; 95% confidence interval [CI]: 1.01-1.47). Furthermore, providers at ED site D were more likely to use the dashboard in comparison to the other sites (OR: 9.99; 95% CI: 1.72-58.04) and reportedly had the highest site-level baseline PIM rate.

CONCLUSION

Providers with lower PIM prescribing rates (i.e., <5%) receive communication from an integrated dashboard reminder system that they are "optimal prescribers" which may have discouraged initial attempts to view the dashboard. Site D had the highest baseline PIM rate, but further qualitative investigation is warranted to better understand why site D had the greatest users of the dashboard.

The Effectiveness of Interactive Dashboards to Optimise Antibiotic Prescribing in Primary Care: A Systematic Review

Governments and healthcare organisations collect data on antibiotic prescribing (AP) for surveillance. This data can support tools for visualisations and feedback to GPs using dashboards that may prompt a change in prescribing behaviour. The objective of this systematic review was to assess the effectiveness of interactive dashboards to optimise AP in primary care. Six electronic databases were searched for relevant studies up to August 2022. A narrative synthesis of findings was conducted to evaluate the intervention processes and results. Two independent reviewers assessed the relevance, risk of bias and quality of the evidence. A total of ten studies were included (eight RCTs and two non-RCTs). Overall, seven studies showed a slight reduction in AP. However, this reduction in AP when offering a dashboard may not in itself result in reductions but only when combined with educational components, public commitment or behavioural strategies. Only one study recorded dashboard engagement and showed a difference of 10% (95% CI 5% to 15%) between intervention and control. None of the studies reported on the development, pilot or implementation of dashboards or the involvement of stakeholders in design and testing. Interactive dashboards may reduce AP in primary care but most likely only when combined with other educational or behavioural intervention strategies.