Workload and workflow implications associated with the use of electronic clinical decision support tools used by health professionals in general practice: a scoping review

Electronic health record and primary care physician self-reported quality of care: a multilevel study in China

BACKGROUND

Health information technology is one of the building blocks of a high-performing health system. However, the evidence regarding the influence of an electronic health record (EHR) on the quality of care remains mixed, especially in low- and middle-income countries.

OBJECTIVE

This study examines the association between greater EHR functionality and primary care physician self-reported quality of care.

METHODS

A total of 224 primary care physicians from 38 community health centres (CHCs) in four large Chinese cities participated in a cross-sectional survey to assess CHC care quality. Each CHC director scored their CHC's EHR functionality on the availability of ten typical features covering health information, data, results management, patient access, and clinical decision support. Data analysis utilised hierarchical linear modelling.

RESULTS

The availability of five EHR features was positively associated with physician self-reported clinical quality: share records online with providers outside the practice (β = 0.276, p = 0.04), access records online by the patient (β = 0.325, p = 0.04), alert provider of potential prescription problems (β = 0.353, p = 0.04), send the patient reminders for care (β = 0.419, p = 0.003), and list patients by diagnosis or health risk (β = 0.282, p = 0.04). However, no association was found between specific features availability or total features score and physician self-reported preventive quality.

CONCLUSIONS

This study provides evidence that the availability of EHR systems, and specific features of these systems, was positively associated with physician self-reported quality of care in these 38 CHCs. Future longitudinal studies focused on standardised quality metrics, and designed to control known confounding variables, will further inform quality improvement efforts in primary care.

The impact of eHealth use on general practice workload in the pre-COVID-19 era: a systematic review

BACKGROUND

In recent years, eHealth has received much attention as an opportunity to increase efficiency within healthcare organizations. Adoption of eHealth might consequently help to solve perceived health workforce challenges, including labor shortages and increasing workloads among primary care professionals, who serve as the first point of contact for healthcare in many countries. The purpose of this systematic review was to investigate the impact of general eHealth use and specific eHealth services use on general practice workload in the pre-COVID-19 era.

METHODS

The databases of CINAHL, Cochrane, Embase, IEEE Xplore, Medline ALL, PsycINFO, Web of Science, and Google Scholar were searched, using combinations of keywords including 'eHealth', 'workload', and 'general practice'. Data extraction and quality assessment of the included studies were independently performed by at least two reviewers. Publications were included for the period 2010 - 2020, before the start of the COVID-19 pandemic.

RESULTS

In total, 208 studies describing the impact of eHealth services use on general practice workload were identified. We found that two eHealth services were mainly investigated within this context, namely electronic health records and digital communication services, and that the largest share of the included studies used a qualitative study design. Overall, a small majority of the studies found that eHealth led to an increase in general practice workload. However, results differed between the various types of eHealth services, as a large share of the studies also reported a reduction or no change in workload.

CONCLUSIONS

The impact of eHealth services use on general practice workload is ambiguous. While a small majority of the effects indicated that eHealth increased workload in general practice, a large share of the effects also showed that eHealth use reduced workload or had no impact. These results do not imply a definitive conclusion, which underscores the need for further explanatory research. Various factors, including the study setting, system design, and the phase of implementation, may influence this impact and should be taken into account when general practices adopt new eHealth services.

STUDY REGISTRATION NUMBER

PROSPERO (International Prospective Register of Systematic Reviews) CRD42020199897; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=199897 .

Electronic health record-based behaviour change interventions aimed at general practitioners in the UK: a mixed methods systematic review using behaviour change theory

OBJECTIVES

Electronic health record (EHR) systems are used extensively in healthcare; their design can influence clinicians' behaviour. We conducted a systematic review of EHR-based interventions aimed at changing the clinical practice of general practitioners in the UK, assessed their effectiveness and applied behaviour change theory to identify lessons for other settings.

DESIGN

Mixed methods systematic review.

DATA SOURCES

MEDLINE, EMBASE, CENTRAL and APA PsycINFO were searched up to March 2023.

ELIGIBILITY CRITERIA

Quantitative and qualitative findings from randomised controlled trials (RCTs) controlled before-and-after studies and interrupted time series of EHR-based interventions in UK general practice were included.

DATA EXTRACTION AND SYNTHESIS

Quantitative synthesis was based on Cochrane's Synthesis without Meta-analysis. Interventions were categorised using the Behaviour Change Wheel and MINDSPACE frameworks and effectiveness determined by vote-counting using direction of effect. Inductive thematic synthesis was used for qualitative studies.

RESULTS

Database searching identified 3824 unique articles; 10 were included (from 2002 to 2021), comprising eight RCTs and two associated qualitative studies. Four of seven quantitative studies showed a positive effect on clinician behaviour and three on patient-level outcomes. Behaviour change techniques that may trigger emotions and required less cognitive engagement appeared to have positive effects. Qualitative findings indicated that interventions reassured clinicians of their decisions but were sometimes ignored.

CONCLUSION

Despite widespread use, there is little high quality, up-to-date experimental evidence evaluating the effectiveness of EHR-based interventions in UK general practice. The evidence suggested EHR-based interventions may be effective at changing behaviour. Persistent, simple action-oriented prompts appeared more effective than complex interventions requiring greater cognitive engagement. However, studies lacked detail in intervention design and theory behind design choices. Future research should seek to optimise EHR-based behaviour change intervention design and delineate limitations, providing theory-based justification for interventions. This will be of increasing importance with the growing use of EHRs to influence clinicians' decisions.

PROSPERO REGISTRATION NUMBER

CRD42022341009.

Impact of Visit Volume on the Effectiveness of Electronic Tools to Improve Heart Failure Care

BACKGROUND

Electronic health record (EHR) tools can improve prescribing of guideline-recommended therapies for heart failure with reduced ejection fraction (HFrEF), but their effectiveness may vary by physician workload.

OBJECTIVES

This paper aims to assess whether physician workload modifies the effectiveness of EHR tools for HFrEF.

METHODS

This was a prespecified subgroup analysis of the BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure) cluster-randomized trial, which compared effectiveness of an alert vs message vs usual care on prescribing of mineralocorticoid antagonists (MRAs). The trial included adults with HFrEF seen in cardiology offices who were eligible for and not prescribed MRAs. Visit volume was defined at the cardiologist-level as number of visits per 6-month study period (high = upper tertile vs non-high = remaining). Analysis at the patient-level used likelihood ratio test for interaction with log-binomial models.

RESULTS

Among 2,211 patients seen by 174 cardiologists, 932 (42.2%) were seen by high-volume cardiologists (median: 1,853; Q1-Q3: 1,637-2,225 visits/6 mo; and median: 10; Q1-Q3: 9-12 visits/half-day). MRA was prescribed to 5.5% in the high-volume vs 14.8% in the non-high-volume groups in the usual care arm, 10.3% vs 19.6% in the message arm, and 31.2% vs 28.2% in the alert arm, respectively. Visit volume modified treatment effect (P for interaction = 0.02) such that the alert was more effective in the high-volume group (relative risk: 5.16; 95% CI: 2.57-10.4) than the non-high-volume group (relative risk: 1.93; 95% CI: 1.29-2.90).

CONCLUSIONS

An EHR-embedded alert increased prescribing by >5-fold among patients seen by high-volume cardiologists. Our findings support use of EHR alerts, especially in busy practice settings. (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure [BETTER CARE-HF]; NCT05275920).

Promoting new users' online health consultation services usage behavior strategically

Online consultation services have the potential to reduce the workload of healthcare staff, provide timely care to patients, and improve doctor-patient relationships. The COVID-19 pandemic has accelerated the development of these services and platforms, but it remains to be seen whether the general public will continue to use them after the pandemic is under control. This research proposes a framework to examine the factors contributing to UK adults' continued usage of online healthcare consultation services after COVID-19 restrictions have been lifted. A total of 430 new users completed surveys, and the results indicate that expectation confirmation, system quality, and information quality can positively impact users' self-efficacy toward using online consultation services. This, in turn, can influence their continued usage behavior. Furthermore, the results suggest that participants' perception of health risks can moderate the relationship between self-efficacy and continued usage behavior. The strategic implications of these findings are discussed.

Is the early identification and referral of suspected head and neck cancers by community pharmacists feasible? A qualitative interview study exploring the views of patients in North East England

INTRODUCTION

Head and neck cancer (HNC) is the eighth most common cancer in the United Kingdom. Survival rates improve when the cancer is diagnosed at an early stage, highlighting a key need to identify at-risk patients. This study aimed to explore opportunistic HNC identification and referral by community pharmacists (CPs) using a symptom-based risk assessment calculator, from the perspective of patients with a diagnosis of HNC.

METHODS

Purposive sampling was used to recruit patients from the HNC pathway in three large teaching hospitals in Northern England. Qualitative methodology was used to collect data through an iterative series of semistructured telephone interviews. Framework analysis was utilised to identify key themes.

RESULTS

Four main themes were constructed through the analytic process: (1) HNC presentation and seeking help; (2) the role of the CP; (3) public perception of HNC and (4) the role of a symptom-based risk calculator. Participants agreed that CPs could play a role in the identification and referral of suspected HNCs, but there were concerns about access as patients frequently only encounter the medicine counter assistant when they visit the pharmacy. HNC symptoms are frequently attributed to common or minor conditions initially and therefore considered not urgent, leading to delays in seeking help. While there is public promotion for some cancers, there is little known about HNC. Early presentation of HNC can be quite variable, therefore raising awareness would help. The use of a symptom-based risk calculator was considered beneficial if it enabled earlier referral and diagnosis. Participants suggested that it would also be useful if the public were made aware of it and could self-assess their symptoms.

CONCLUSION

In principle, CPs could play a role in the identification and referral of HNC, but there was uncertainty as to how the intervention would work. Future research is needed to develop an intervention that would facilitate earlier identification and referral of HNC while not disrupting CP work and that would promote HNC and the risk calculator more widely.

PATIENT OR PUBLIC CONTRIBUTION

Patient and public involvement and engagement (PPIE) was integrated throughout the project. Initially, the proposal was discussed during a Cancer Head and Neck Group Experience (CHANGE) PPIE meeting. CHANGE was set up to support HNC research in 2018. The group is composed of seven members (four female, three male) with an age range of 50-71 years, who were diagnosed at Sunderland Royal Hospital. A patient representative from the University of Sunderland PPIE group and a trustee of the Northern HNC Charity were recruited as co-applicants. They attended project management group meetings and reviewed patient-facing documentation.

Barriers and facilitators to utilizing digital health technologies by healthcare professionals

Digital technologies change the healthcare environment, with several studies suggesting barriers and facilitators to using digital interventions by healthcare professionals (HPs). We consolidated the evidence from existing systematic reviews mentioning barriers and facilitators for the use of digital health technologies by HP. Electronic searches were performed in five databases (Cochrane Database of Systematic Reviews, Embase®, Epistemonikos, MEDLINE®, and Scopus) from inception to March 2023. We included reviews that reported barriers or facilitators factors to use technology solutions among HP. We performed data abstraction, methodological assessment, and certainty of the evidence appraisal by at least two authors. Overall, we included 108 reviews involving physicians, pharmacists, and nurses were included. High-quality evidence suggested that infrastructure and technical barriers (Relative Frequency Occurrence [RFO] 6.4% [95% CI 2.9-14.1]), psychological and personal issues (RFO 5.3% [95% CI 2.2-12.7]), and concerns of increasing working hours or workload (RFO 3.9% [95% CI 1.5-10.1]) were common concerns reported by HPs. Likewise, high-quality evidence supports that training/educational programs, multisector incentives, and the perception of technology effectiveness facilitate the adoption of digital technologies by HPs (RFO 3.8% [95% CI 1.8-7.9]). Our findings showed that infrastructure and technical issues, psychological barriers, and workload-related concerns are relevant barriers to comprehensively and holistically adopting digital health technologies by HPs. Conversely, deploying training, evaluating HP's perception of usefulness and willingness to use, and multi-stakeholders incentives are vital enablers to enhance the HP adoption of digital interventions.

Meaningful time-related aspects of alerts in Clinical Decision Support Systems. A unified framework

Alerts are a common functionality of clinical decision support systems (CDSSs). Although they have proven to be useful in clinical practice, the alert burden can lead to alert fatigue and significantly reduce their usability and acceptance. Based on a literature review, we propose a unified framework consisting of a set of meaningful timestamps that allows the use of state-of-the-art measures for alert burden, such as alert dwell time, alert think time, and response time. In addition, it can be used to investigate other measures that could be relevant as regards dealing with this problem. Furthermore, we provide a case study concerning three different types of alerts to which the framework was successfully applied. We consider that our framework can easily be adapted to other CDSSs and that it could be useful for dealing with alert burden measurement thus contributing to its appropriate management.

Trialling a Large Language Model (ChatGPT) in General Practice With the Applied Knowledge Test: Observational Study Demonstrating Opportunities and Limitations in Primary Care

BACKGROUND

Large language models exhibiting human-level performance in specialized tasks are emerging; examples include Generative Pretrained Transformer 3.5, which underlies the processing of ChatGPT. Rigorous trials are required to understand the capabilities of emerging technology, so that innovation can be directed to benefit patients and practitioners.

OBJECTIVE

Here, we evaluated the strengths and weaknesses of ChatGPT in primary care using the Membership of the Royal College of General Practitioners Applied Knowledge Test (AKT) as a medium.

METHODS

AKT questions were sourced from a web-based question bank and 2 AKT practice papers. In total, 674 unique AKT questions were inputted to ChatGPT, with the model's answers recorded and compared to correct answers provided by the Royal College of General Practitioners. Each question was inputted twice in separate ChatGPT sessions, with answers on repeated trials compared to gauge consistency. Subject difficulty was gauged by referring to examiners' reports from 2018 to 2022. Novel explanations from ChatGPT-defined as information provided that was not inputted within the question or multiple answer choices-were recorded. Performance was analyzed with respect to subject, difficulty, question source, and novel model outputs to explore ChatGPT's strengths and weaknesses.

RESULTS

Average overall performance of ChatGPT was 60.17%, which is below the mean passing mark in the last 2 years (70.42%). Accuracy differed between sources (P=.04 and .06). ChatGPT's performance varied with subject category (P=.02 and .02), but variation did not correlate with difficulty (Spearman ρ=-0.241 and -0.238; P=.19 and .20). The proclivity of ChatGPT to provide novel explanations did not affect accuracy (P>.99 and .23).

CONCLUSIONS

Large language models are approaching human expert-level performance, although further development is required to match the performance of qualified primary care physicians in the AKT. Validated high-performance models may serve as assistants or autonomous clinical tools to ameliorate the general practice workforce crisis.