Feeling and thinking: can theories of human motivation explain how EHR design impacts clinician burnout?

Clinical decision fatigue: a systematic and scoping review with meta-synthesis

OBJECTIVE

Decision fatigue (DF) can lead to impaired judgement, decreased diagnostic accuracy and increased likelihood of medical errors. Research on DF is scarce, and little is known about its nature in the clinical context. The objective of the present review was to provide a comprehensive framework to understand how the construct of DF in medical settings has been defined and measured. This review aimed to understand DF determinants and consequences and capture motivational factors overlooked in the existing reviews.

DESIGN

Systematic and scoping review (ScR) with meta-synthesis.

ELIGIBILITY CRITERIA

Empirical and non-empirical papers on clinical DF or related constructs directly impacting clinical decision-making were considered, with doctors of all ages, sexes and nationalities as participants. The Preferred Reporting Item for Systematic Reviews and Meta-analyses scoping review checklist has been applied and checked.

INFORMATION SOURCES

Six databases were systematically searched by two independent researchers according to a predefined set of keywords.

RESULTS

43 papers were included, of which 25 were empirical. The quantitative studies outnumber the qualitative ones and primarily involved residents in Europe/UK and North America. Internal medicine and primary care were the most studied disciplines. Only one sequential cross-sectional study measured DF in the medical setting, and all other studies addressed the construct indirectly. A conceptual analysis of clinical DF, including narrative contributions, a thematic analysis of the data extracted and a meta-synthesis, is provided. Clinical DF was investigated mostly by individual risk factors analysed through multiple intertwined determinants involving cognitive, emotional, behavioural, social and ethical aspects. Relevant risks, protective factors and negative outcomes circularly increasing DF are outlined.

CONCLUSIONS

The review gives solid arguments for developing a clear and coherent definition of clinical DF that allows the implementation of preventive targeted intervention.

PROSPERO REGISTRATION NUMBER

This systematic review was pre-registered in PROSPERO on 8 November 2023 (available online at: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023476190, registration number CRD4202347619).

Electronic Health Record Adoption and Its Effects on Healthcare Staff: A Qualitative Study of Well-Being and Workplace Stress

Adopting electronic health records (EHRs) offers improved communication and information sharing and reduces medical staff errors. Despite these potential benefits, EHR adoption often introduces new challenges for healthcare staff, including increased administrative burdens and workplace stress. This study examines the impact of EHR systems on the well-being and workplace stress of healthcare staff in a hospital setting. Using a qualitative multi-perspective research approach, 16 guideline-based interviews were conducted to explore experiences, insight, and perceptions surrounding the anticipated introduction of EHRs. Data analysis reveals a complex interplay between the perceived advantages of EHRs, such as improved data accessibility and patient safety, and the challenges related to increased workload. Based on interviewers' perceptions, emerging themes were categorized as technostress creators or inhibitors. The findings highlight a dual impact of EHRs: while participants acknowledged improvements in patient safety and information access, they also expressed concerns about increased workload, technostress, and potential disruptions to team dynamics. This study identified two major themes: "EHR Adoption as a Double-Edged Sword" and "EHRs' Influence on Professional Dynamics". These findings underscore the need for organizational readiness and staff support to mitigate the negative impacts of EHRs on healthcare workers' well-being and job satisfaction.

Unveiling barriers to EHR implementation for effective decision support in tanzanian primary healthcare: Insights from practitioners

This study investigates the barriers to implementing electronic health records (EHR) systems for decision support in Tanzanian primary healthcare (PHC) facilities and proposes strategies to address these challenges. A qualitative, inductive approach was used, guided by the Diffusion of Innovations (DOI) theory, the Technology Acceptance Model (TAM), and the Sociotechnical Systems theory. Using snowball sampling, data were collected from 14 participants through semi-structured interviews in Dodoma, Tanzania. Thematic analysis identified key barriers. Critical barriers to EHR implementation include lack of leadership support, poor network infrastructure, increased workload, and resistance to technology due to concerns over professional autonomy. Technical challenges, such as system downtime and lack of skilled personnel, hinder EHR use, resulting in inefficiencies and incomplete system adoption, negatively affecting patient outcomes. This study offers unique insights into barriers to EHR adoption in Tanzanian PHC facilities. Grounded in multiple theoretical frameworks, the findings contribute to health informatics discourse in low-resource settings and provide practical recommendations for improving EHR implementation. The study's implications are relevant for policymakers, healthcare leaders, and IT developers in similar contexts.

Sprint-inspired One-on-One Post-Go-Live Training Session (Mini-Sprint) Improves Provider Electronic Health Record Efficiency and Satisfaction

BACKGROUND

 Inefficient electronic health record (EHR) usage increases the documentation burden on physicians and other providers, which increases cognitive load and contributes to provider burnout. Studies show that EHR efficiency sessions, optimization sprints, reduce burnout using a resource-intense five-person team. We implemented sprint-inspired one-on-one post-go-live efficiency training sessions (mini-sprints) as a more economical training option directed at providers.

OBJECTIVES

 We evaluated a post-go-live mini-sprint intervention to assess provider satisfaction and efficiency.

METHODS

 NorthShore University HealthSystem implemented one-on-one provider-to-provider mini-sprint sessions to optimize provider workflow within the EHR platform. The physician informaticist completed a 9-point checklist of efficiency tips with physician trainees covering schedule organization, chart review, speed buttons, billing, note personalization/optimization, preference lists, quick actions, and quick tips. We collected postsession survey data assessing for net promoter score (NPS) and open-ended feedback. We conducted financial analysis of pre- and post-mini-sprint efficiency levels and financial data.

RESULTS

 Seventy-six sessions were conducted with 32 primary care physicians, 28 specialty physicians, and 16 nonphysician providers within primary care and other areas. Thirty-seven physicians completed the postsession survey. The average NPS for the completed mini-sprint sessions was 97. The proficiency score had a median of 6.12 (Interquartile range (IQR): 4.71-7.64) before training, and a median of 7.10 (IQR: 6.25-8.49) after training. Financial data analysis indicates that higher level billing codes were used at a greater frequency post-mini-sprint. The revenue increase 12 months post-mini-sprint was $213,234, leading to a return of $75,559.50 for 40 providers, or $1,888.98 per provider in a 12-month period.

CONCLUSION

 Our data show that mini-sprint sessions were effective in optimizing efficiency within the EHR platform. Financial analysis demonstrates that this type of training program is sustainable and pays for itself. There was high satisfaction with the mini-sprint training modality, and feedback indicated an interest in further mini-sprint training sessions for physicians and nonphysician staff.

Making the EHR Work for You-Modifications of an Electronic Health Record System to Improve Tracking and Management of Patients Receiving Outpatient Parenteral Antibiotic Therapy

Background

Managing the complex needs of outpatient parenteral antibiotic therapy (OPAT) patients is challenging and time-consuming. We describe development of multimodal interventions to facilitate patient management within an Epic® (Epic Systems Corporation)-based electronic health record (EHR) platform.

Methods

During 2016-2018, a multidisciplinary team created several modifications in our local EHR to improve gaps in OPAT care, including shared note templates, shared patient lists, automatically triggered notifications, and comprehensive order sets. A SmartForm was created, allowing collection of discrete, self-contained extractable data about each OPAT episode. We reviewed OPAT episodes from January 2019 through December 2022.

Results

The multimodal EHR interventions culminated in the creation of a patient report, the "OPAT Monitoring View" collating OPAT-relevant data from multiple sections of the chart onto 1 screen display. This view is accessible both within the patient chart and from multiple list-based, in-basket, and snapshot-anchored preview functions in the EHR. Implementation of the EHR bundle facilitated management of 3402 OPAT episodes from 2019 to 2022 (850 episodes/year), about 50% higher than anticipated based on 540 OPAT courses in 2016. The OPAT EHR bundle allowed efficient (<3 hours) multidisciplinary rounds for management of 130-145 patients each week, streamlining of care transitions, and increasing staff satisfaction.

Conclusions

Bundled multimodal modifications to the local EHR increased patient care efficiency and staff satisfaction and facilitated data collection to support a large OPAT program. These modifications apply commonly available EHR functionalities to OPAT care and could be adapted to other settings with different EHR platforms.

Considerations for using predictive models that include race as an input variable: The case study of lung cancer screening

Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models. Thus, there is a need for a pragmatic framework to help model users think through how to include race in their chosen model so as to avoid inadvertently exacerbating disparities. In this paper, we use the case study of lung cancer screening to propose a simple framework to guide how model users can approach the use (or non-use) of race inputs in the predictive models they are tasked with leveraging in electronic health records and clinical workflows.

Going paperless - Qualitative monitoring of staff morale during the transition from paper to electronic health records

Background

Organisational change is an important part of development and growth. Transitioning from paper-based hospital records to electronic health records improves efficiency and patient safety by streamlining data access and reducing the risk of errors, ultimately leading to enhanced patient care and outcomes. In October 2020, a large NHS trust underwent the transition from paper notes to a fully electronic health records system. Therefore, the purpose of this study was to monitor staff morale during this organisational change; to highlight any issues arising that may impact on the smooth transition; to encourage feedback.

Methods

A questionnaire was distributed to all members of the maxillofacial outpatients department on a regular basis. The qualitative responses were analysed using NVivo, following a framework analysis model.

Results

The analysis generated 1319 codes, which were placed into 68 groups. The three main themes were 'Transformational Advancements in Healthcare Delivery'; 'Obstacles to Seamless EHR Integration; 'Navigating the Transition and Evolving Perceptions'.

Discussion

Regular monitoring of morale and staff opinion allows for smoother transition in a large-scale organisational change. The results of this project will help future hospitals and trusts undergoing similar transitions.

A Systematic Review of Quantitative Methods for Evaluating Electronic Medication Administration Record and Bar-Coded Medication Administration Usability

BACKGROUND

Although electronic medication administration records (eMARs) and bar-coded medication administration (BCMA) have improved medication safety, poor usability of these technologies can increase patient safety risks.

OBJECTIVES

The objective of our systematic review was to identify the impact of eMAR and BCMA design on usability, operationalized as efficiency, effectiveness, and satisfaction.

METHODS

We retrieved peer-reviewed journal articles on BCMA and eMAR quantitative usability measures from PsycInfo and MEDLINE (1946-August 20, 2019), and EMBASE (1976-October 23, 2019). Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we screened articles, extracted and categorized data into the usability categories of effectiveness, efficiency, and satisfaction, and evaluated article quality.

RESULTS

We identified 1,922 articles and extracted data from 41 articles. Twenty-four articles (58.5%) investigated BCMA only, 10 (24.4%) eMAR only, and seven (17.1%) both BCMA and eMAR. Twenty-four articles (58.5%) measured effectiveness, 8 (19.5%) efficiency, and 17 (41.5%) satisfaction. Study designs included randomized controlled trial (n = 1; 2.4%), interrupted time series (n = 1; 2.4%), pretest/posttest (n = 21; 51.2%), posttest only (n = 14; 34.1%), and pretest/posttest and posttest only for different dependent variables (n = 4; 9.8%). Data collection occurred through observations (n = 19, 46.3%), surveys (n = 17, 41.5%), patient safety event reports (n = 9, 22.0%), surveillance (n = 6, 14.6%), and audits (n = 3, 7.3%).

CONCLUSION

Of the 100 measures across the 41 articles, implementing BCMA and/or eMAR broadly resulted in an increase in measures of effectiveness (n = 23, 52.3%) and satisfaction (n = 28, 62.2%) compared to measures of efficiency (n = 3, 27.3%). Future research should focus on eMAR efficiency measures, utilize rigorous study designs, and generate specific design requirements.

Evolution - removing paper and digitising the hospital

Purpose

A transition from paper to Electronic Health Records has numerous benefits, including better communication and information exchange and decreased errors by medical staff. However, if managed poorly, it can result in frustration, causing errors in patient care and reduced patient-clinician interaction. Furthermore, a drop in staff morale and clinician burnout due to familiarising themselves with the technology has been mentioned in previous studies. Therefore, the aim of this project is to monitor the change in morale of staff of the Oral and Maxillofacial Department in a hospital which underwent the change in October 2020. Objectives: To observe staff morale during transition from paper to Electronic Health Records; to encourage feedback.

Methods

After carrying out a Patient & Public Involvement consultation and receiving local research and development approval, a questionnaire was distributed to all members of the maxillofacial outpatients department on a regular basis.

Results

On average, around 25 members responded to the questionnaire during each collection. There was a noticeable divergence in responses week on week according to job role and age, but minimal difference is noted from gender point of view after the first week. The study emphasised the position that not all members were happy with the new system but only a small minority would want to return to paper notes.

Conclusion

Staff members adapt to change at different rates, which are multifactorial in nature. A change of this scale should be monitored closely to allow for a smoother transition and ensure staff burnout is minimised.

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.

Change in nurses’ psychosocial characteristics pre- and post-electronic medical record system implementation coinciding with the SARS-CoV-2 pandemic: pre- and post-cross-sectional surveys

Background

The impacts of electronic medical record implementation on nurses, the largest healthcare workforce, have not been comprehensively examined. Negative impacts on nurses have implications for quality of patient care delivery and workforce retention.

Objective

To investigate changes in nurses’ well-being, intention to stay, burnout, work engagement, satisfaction, motivation and experience using technology pre- and post-implementation of an organisation-wide electronic medical record in Victoria, Australia.

Methods

The natural experiment comprised an electronic medical record system implementation across six hospitals of a large tertiary healthcare organisation. Cross-sectional surveys were collected pre-electronic medical record implementation prior to the SARS-CoV-2 pandemic in 2019, and 18-months post-electronic medical record implementation during the pandemic in 2020, and findings compared.

Results

A total of 942 surveys were analysed (550 pre-electronic medical record (response rate 15.52%) and 392 post-electronic medical record (response rate 9.50%)). Post-electronic medical record, nurses’ work satisfaction (r = 0.23, p=<0.001), intention to stay (r = 0.11, p = 0.001) and well-being (r = 0.17, p=<0.001) decreased. Nurses’ perceived competence increased (r = 0.10, p = 0.002) despite decreased autonomy (r = 0.10, p = 0.003). Two of three dimensions of work engagement worsened (vigour r = 0.13, p=<0.001; dedication r = 0.13, p=<0.001) and all dimensions of burnout increased (exhaustion r = 0.08, p = 0.012, cynicism r = 0.07, p = 0.04 and reduced efficiency r = 0.32, p=<0.001). Nurses reported more burnout symptoms (95% CI 4.6–4.7%, p = 0.036), were less engaged (95% CI 49.6–49.9%, p=<0.001) and career trajectory satisfaction decreased (r = 0.15, p=<0.001). Matched data from 52 nurses showed changes in the same direction for all items except career trajectory satisfaction, hence validated findings from the larger unmatched sample.

Conclusions

Implementation of an electronic medical record immediately followed by the SARS-CoV-2 pandemic was associated with negative changes in nurses’ well-being, intention to stay, burnout, work engagement and satisfaction.

Roadmap to a more useful and usable electronic health record

Background

A decade after the Health Information Technology for Economic and Clinical Health (HITECH) Act, electronic health records (EHRs) largely remain poorly designed and contribute to clinician burnout.

Objective

The purpose of this study was to understand clinicians’ wants, needs, and perceived barriers imposed by the EHR; implement best practices in user-centered design; and create a clinician-centered EHR framework validated via a functional EHR prototype.

Methods

Usability evaluations were performed using a simulated patient with a complex clinical scenario. Convergent parallel mixed methods linked to action research and agile development were used to create an EHR prototype based on clinician-centered design. Prototype functionality was validated via a final usability evaluation.

Results

Between 2015 and 2017, 53 clinicians from 8 cardiology practices (4 academic and 4 private) participated in initial evaluations of their installed EHR. In 2019, 25 clinicians participated in final evaluations of their EHR vs our EHR prototype. Initial evaluations documented that clinicians judged the EHRs as poorly designed, scoring a mean of 47.1 on the System Usability Scale. Clinicians expressed that EHRs impeded workflow and communication and prolonged their workday. In the final evaluations, no improvement in installed EHRs was found (mean score 48.1); however, the EHR prototype was assessed as significantly more usable (mean score 77.8; P <.001).

Conclusion

A decade after the HITECH Act, EHRs still receive low usability scores. By applying user-centered design, an EHR prototype with improved features, functionality, and workflow integration was developed. Clinician testing of the EHR prototype demonstrated it was significantly more useful and usable to clinicians, thus identifying a framework and pathway for substantive improvement of EHR systems.

Human Factors and Organizational Issues Section Synopsis IMIA Yearbook 2021

OBJECTIVE

To select the best papers that made original and high impact contributions in the area of human factors and organizational issues in biomedical informatics in 2020.

METHODS

A rigorous extraction process based on queries from Web of Science® and PubMed/Medline was conducted to identify the scientific contributions published in 2020 that address human factors and organizational issues in biomedical informatics. The screening of papers on titles and abstracts independently by the two section editors led to a total of 1,562 papers. These papers were discussed for a selection of 12 finalist papers, which were then reviewed by the two section editors, two chief editors, and by three external reviewers from internationally renowned research teams.

RESULTS

The query process resulted in 12 papers that reveal interesting and rigorous methods and important studies in human factors that move the field forward, particularly in clinical informatics and emerging technologies such as brain-computer interfaces. This year three papers were clearly outstanding and help advance in the field. They provide examples of applying existing frameworks together in novel and highly illuminating ways, showing the value of theory development in human factors. Emerging themes included several which discussed physician burnout, mobile health, and health equity. Those concerning the Corona Virus Disease 2019 (Covid-19) were included as part of that section.

CONCLUSION

The selected papers make important contributions to human factors and organizational issues, expanding and deepening our knowledge of how to apply theory and applications of new technologies in health.

Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions

Clinical decision-making is based on knowledge, expertise, and authority, with clinicians approving almost every intervention-the starting point for delivery of "All the right care, but only the right care," an unachieved healthcare quality improvement goal. Unaided clinicians suffer from human cognitive limitations and biases when decisions are based only on their training, expertise, and experience. Electronic health records (EHRs) could improve healthcare with robust decision-support tools that reduce unwarranted variation of clinician decisions and actions. Current EHRs, focused on results review, documentation, and accounting, are awkward, time-consuming, and contribute to clinician stress and burnout. Decision-support tools could reduce clinician burden and enable replicable clinician decisions and actions that personalize patient care. Most current clinical decision-support tools or aids lack detail and neither reduce burden nor enable replicable actions. Clinicians must provide subjective interpretation and missing logic, thus introducing personal biases and mindless, unwarranted, variation from evidence-based practice. Replicability occurs when different clinicians, with the same patient information and context, come to the same decision and action. We propose a feasible subset of therapeutic decision-support tools based on credible clinical outcome evidence: computer protocols leading to replicable clinician actions (eActions). eActions enable different clinicians to make consistent decisions and actions when faced with the same patient input data. eActions embrace good everyday decision-making informed by evidence, experience, EHR data, and individual patient status. eActions can reduce unwarranted variation, increase quality of clinical care and research, reduce EHR noise, and could enable a learning healthcare system.

Analysis of the cognitive demands of electronic health record use

The goal of this study was to elicit the cognitive demands facing clinicians when using an electronic health record (EHR) system and learn the cues and strategies expert clinicians rely on to manage those demands. This study differs from prior research by applying a joint cognitive systems perspective to examining the cognitive aspects of clinical work. We used a cognitive task analysis (CTA) method specifically tailored to elicit the cognitive demands of an EHR system from expert clinicians from different sites in a variety of inpatient and outpatient roles. The analysis of the interviews revealed 145 unique cognitive demands of using an EHR, which were organized into 22 distinct themes across seven broad categories. In addition to confirming previously published themes of cognitive demands, the main emergent themes of this study are: 1) The EHR does not help clinicians develop and maintain awareness of the big picture; 2) The EHR does not support clinicians' need to reason about patients' current and future states, including effects of potential treatments; and 3) The EHR limits agency of clinicians to work individually and collaboratively. Implications for theory and EHR design and evaluation are discussed.