Effects of a computerized feedback intervention on safety performance by junior doctors: results from a randomized mixed method study

Assessment of a venous thromboembolism prophylaxis shared decision-making intervention (DASH-TOP) using the decisional conflict scale: a mixed-method study

BACKGROUND

Venous thromboembolism (VTE) in pregnancy is a major cause of maternal morbidity and death. The use of low-molecular-weight heparin (LMWH), despite being the standard of care to prevent VTE, comes with some challenges. Shared decision-making (SDM) interventions are recommended to support patients and clinicians in making preference-sensitive decisions. The quality of the SDM process has been widely assessed with the decisional conflict scale (DCS). Our aim is to report participants' perspectives of each of the components of an SDM intervention (DASH-TOP) in relation to the different subscales of the DCS.

METHODS

Design: A convergent, parallel, mixed-methods design.

PARTICIPANTS

The sample consisted of 22 health care professionals, students of an Applied Clinical Research in Health Sciences (ICACS) master program.

INTERVENTION

We randomly divided the participants in three groups: Group 1 received one component (evidence -based information), Group 2 received two components (first component and value elicitation exercises), and Group 3 received all three components (the first two and a decision analysis recommendation) of the SDM intervention.

ANALYSIS

For the quantitative strand, we used a non-parametric test to analyze the differences in the DCS subscales between the three groups. For the qualitative strand, we conducted a content analysis using the decisional conflict domains to deductively categorize the responses.

RESULTS

Groups that received more intervention components experienced less conflict and better decision-making quality, although the differences between groups were not statistically significant. The decision analysis recommendation improved the efficacy with the decision-making process, however there are some challenges when implementing it in clinical practice. The uncertainty subscale showed a high decisional conflict for all three groups; contributing factors included low certainty of the evidence-based information provided and a perceived small effect of the drug to reduce the risk of a VTE event.

CONCLUSIONS

The DASH-TOP intervention reduced decisional conflict in the decision -making process, with decision analysis being the most effective component to improve the quality of the decision. There is a need for more implementation research to improve the delivery of SDM interventions in the clinical encounter.

Uses of Electronic Health Record Data to Measure the Clinical Learning Environment of Graduate Medical Education Trainees: A Systematic Review

PURPOSE

This study systematically reviews the uses of electronic health record (EHR) data to measure graduate medical education (GME) trainee competencies.

METHOD

In January 2022, the authors conducted a systematic review of original research in MEDLINE from database start to December 31, 2021. The authors searched for articles that used the EHR as their data source and in which the individual GME trainee was the unit of observation and/or unit of analysis. The database query was intentionally broad because an initial survey of pertinent articles identified no unifying Medical Subject Heading terms. Articles were coded and clustered by theme and Accreditation Council for Graduate Medical Education (ACGME) core competency.

RESULTS

The database search yielded 3,540 articles, of which 86 met the study inclusion criteria. Articles clustered into 16 themes, the largest of which were trainee condition experience (17 articles), work patterns (16 articles), and continuity of care (12 articles). Five of the ACGME core competencies were represented (patient care and procedural skills, practice-based learning and improvement, systems-based practice, medical knowledge, and professionalism). In addition, 25 articles assessed the clinical learning environment.

CONCLUSIONS

This review identified 86 articles that used EHR data to measure individual GME trainee competencies, spanning 16 themes and 6 competencies and revealing marked between-trainee variation. The authors propose a digital learning cycle framework that arranges sequentially the uses of EHR data within the cycle of clinical experiential learning central to GME. Three technical components necessary to unlock the potential of EHR data to improve GME are described: measures, attribution, and visualization. Partnerships between GME programs and informatics departments will be pivotal in realizing this opportunity.

OUP accepted manuscript

Objectives

(1) Systematically review the literature on computerized audit and feedback (e-A&F) systems in healthcare. (2) Compare features of current systems against e-A&F best practices. (3) Generate hypotheses on how e-A&F systems may impact patient care and outcomes.

Methods

We searched MEDLINE (Ovid), EMBASE (Ovid), and CINAHL (Ebsco) databases to December 31, 2020. Two reviewers independently performed selection, extraction, and quality appraisal (Mixed Methods Appraisal Tool). System features were compared with 18 best practices derived from Clinical Performance Feedback Intervention Theory. We then used realist concepts to generate hypotheses on mechanisms of e-A&F impact. Results are reported in accordance with the PRISMA statement.

Results

Our search yielded 4301 unique articles. We included 88 studies evaluating 65 e-A&F systems, spanning a diverse range of clinical areas, including medical, surgical, general practice, etc. Systems adopted a median of 8 best practices (interquartile range 6–10), with 32 systems providing near real-time feedback data and 20 systems incorporating action planning. High-confidence hypotheses suggested that favorable e-A&F systems prompted specific actions, particularly enabled by timely and role-specific feedback (including patient lists and individual performance data) and embedded action plans, in order to improve system usage, care quality, and patient outcomes.

Conclusions

e-A&F systems continue to be developed for many clinical applications. Yet, several systems still lack basic features recommended by best practice, such as timely feedback and action planning. Systems should focus on actionability, by providing real-time data for feedback that is specific to user roles, with embedded action plans.

Protocol Registration

PROSPERO CRD42016048695.

Reducing medication errors for adults in hospital settings

BACKGROUND

Medication errors are preventable events that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the healthcare professional or patient. Medication errors in hospitalised adults may cause harm, additional costs, and even death.

OBJECTIVES

To determine the effectiveness of interventions to reduce medication errors in adults in hospital settings.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, five other databases and two trials registers on 16 January 2020.  SELECTION CRITERIA: We included randomised controlled trials (RCTs) and interrupted time series (ITS) studies investigating interventions aimed at reducing medication errors in hospitalised adults, compared with usual care or other interventions. Outcome measures included adverse drug events (ADEs), potential ADEs, preventable ADEs, medication errors, mortality, morbidity, length of stay, quality of life and identified/solved discrepancies. We included any hospital setting, such as inpatient care units, outpatient care settings, and accident and emergency departments.

DATA COLLECTION AND ANALYSIS

We followed the standard methodological procedures expected by Cochrane and the Effective Practice and Organisation of Care (EPOC) Group. Where necessary, we extracted and reanalysed ITS study data using piecewise linear regression, corrected for autocorrelation and seasonality, where possible.  MAIN RESULTS: We included 65 studies: 51 RCTs and 14 ITS studies, involving 110,875 participants. About half of trials gave rise to 'some concerns' for risk of bias during the randomisation process and one-third lacked blinding of outcome assessment. Most ITS studies presented low risk of bias. Most studies came from high-income countries or high-resource settings. Medication reconciliation -the process of comparing a patient's medication orders to the medications that the patient has been taking- was the most common type of intervention studied. Electronic prescribing systems, barcoding for correct administering of medications, organisational changes, feedback on medication errors, education of professionals and improved medication dispensing systems were other interventions studied. Medication reconciliation Low-certainty evidence suggests that medication reconciliation (MR) versus no-MR may reduce medication errors (odds ratio [OR] 0.55, 95% confidence interval (CI) 0.17 to 1.74; 3 studies; n=379). Compared to no-MR, MR probably reduces ADEs (OR 0.38, 95%CI 0.18 to 0.80; 3 studies, n=1336 ; moderate-certainty evidence), but has little to no effect on length of stay (mean difference (MD) -0.30 days, 95%CI -1.93 to 1.33 days; 3 studies, n=527) and quality of life (MD -1.51, 95%CI -10.04 to 7.02; 1 study, n=131).  Low-certainty evidence suggests that, compared to MR by other professionals, MR by pharmacists may reduce medication errors (OR 0.21, 95%CI 0.09 to 0.48; 8 studies, n=2648) and may increase ADEs (OR 1.34, 95%CI 0.73 to 2.44; 3 studies, n=2873). Compared to MR by other professionals, MR by pharmacists may have little to no effect on length of stay (MD -0.25, 95%CI -1.05 to 0.56; 6 studies, 3983). Moderate-certainty evidence shows that this intervention probably has little to no effect on mortality during hospitalisation (risk ratio (RR) 0.99, 95%CI 0.57 to 1.7; 2 studies, n=1000), and on readmissions at one month (RR 0.93, 95%CI 0.76 to 1.14; 2 studies, n=997); and low-certainty evidence suggests that the intervention may have little to no effect on quality of life (MD 0.00, 95%CI -14.09 to 14.09; 1 study, n=724).  Low-certainty evidence suggests that database-assisted MR conducted by pharmacists, versus unassisted MR conducted by pharmacists, may reduce potential ADEs (OR 0.26, 95%CI 0.10 to 0.64; 2 studies, n=3326), and may have no effect on length of stay (MD 1.00, 95%CI -0.17 to 2.17; 1 study, n=311).  Low-certainty evidence suggests that MR performed by trained pharmacist technicians, versus pharmacists, may have little to no difference on length of stay (MD -0.30, 95%CI -2.12 to 1.52; 1 study, n=183). However, the CI is compatible with important beneficial and detrimental effects. Low-certainty evidence suggests that MR before admission may increase the identification of discrepancies compared with MR after admission (MD 1.27, 95%CI 0.46 to 2.08; 1 study, n=307). However, the CI is compatible with important beneficial and detrimental effects. Moderate-certainty evidence shows that multimodal interventions probably increase discrepancy resolutions compared to usual care (RR 2.14, 95%CI 1.81 to 2.53; 1 study, n=487). Computerised physician order entry (CPOE)/clinical decision support systems (CDSS) Moderate-certainty evidence shows that CPOE/CDSS probably reduce medication errors compared to paper-based systems (OR 0.74, 95%CI 0.31 to 1.79; 2 studies, n=88).  Moderate-certainty evidence shows that, compared with standard CPOE/CDSS, improved CPOE/CDSS probably reduce medication errors (OR 0.85, 95%CI 0.74 to 0.97; 2 studies, n=630). Low-certainty evidence suggests that prioritised alerts provided by CPOE/CDSS may prevent ADEs compared to non-prioritised (inconsequential) alerts (MD 1.98, 95%CI 1.65 to 2.31; 1 study; participant numbers unavailable). Barcode identification of participants/medications Low-certainty evidence suggests that barcoding may reduce medication errors (OR 0.69, 95%CI 0.59 to 0.79; 2 studies, n=50,545). Reduced working hours Low-certainty evidence suggests that reduced working hours may reduce serious medication errors (RR 0.83, 95%CI 0.63 to 1.09; 1 study, n=634). However, the CI is compatible with important beneficial and detrimental effects. Feedback on prescribing errors Low-certainty evidence suggests that feedback on prescribing errors may reduce medication errors (OR 0.47, 95%CI 0.33 to 0.67; 4 studies, n=384). Dispensing system Low-certainty evidence suggests that dispensing systems in surgical wards may reduce medication errors (OR 0.61, 95%CI 0.47 to 0.79; 2 studies, n=1775).

AUTHORS' CONCLUSIONS

Low- to moderate-certainty evidence suggests that, compared to usual care, medication reconciliation, CPOE/CDSS, barcoding, feedback and dispensing systems in surgical wards may reduce medication errors and ADEs. However, the results are imprecise for some outcomes related to medication reconciliation and CPOE/CDSS. The evidence for other interventions is very uncertain. Powered and methodologically sound studies are needed to address the identified evidence gaps. Innovative, synergistic strategies -including those that involve patients- should also be evaluated.

How do stakeholders experience the adoption of electronic prescribing systems in hospitals? A systematic review and thematic synthesis of qualitative studies

Background

Electronic prescribing (ePrescribing) or computerised provider/physician order entry (CPOE) systems can improve the quality and safety of health services, but the translation of this into reduced harm for patients remains unclear. This review aimed to synthesise primary qualitative research relating to how stakeholders experience the adoption of ePrescribing/CPOE systems in hospitals, to help better understand why and how healthcare organisations have not yet realised the full potential of such systems and to inform future implementations and research.

Methods

We systematically searched 10 bibliographic databases and additional sources for citation searching and grey literature, with no restriction on date or publication language. Qualitative studies exploring the perspectives/experiences of stakeholders with the implementation, management, use and/or optimisation of ePrescribing/CPOE systems in hospitals were included. Quality assessment combined criteria from the Critical Appraisal Skills Programme Qualitative Checklist and the Standards for Reporting Qualitative Research guidelines. Data were synthesised thematically.

Results

79 articles were included. Stakeholders’ perspectives reflected a mixed set of positive and negative implications of engaging in ePrescribing/CPOE as part of their work. These were underpinned by further-reaching change processes. Impacts reported were largely practice related rather than at the organisational level. Factors affecting the implementation process and actions undertaken prior to implementation were perceived as important in understanding ePrescribing/CPOE adoption and impact.

Conclusions

Implementing organisations and teams should consider the breadth and depth of changes that ePrescribing/CPOE adoption can trigger rather than focus on discrete benefits/problems and favour implementation strategies that: consider the preimplementation context, are responsive to (and transparent about) organisational and stakeholder needs and agendas and which can be sustained effectively over time as implementations develop and gradually transition to routine use and system optimisation.

Clinical Performance Feedback Intervention Theory (CP-FIT): a new theory for designing, implementing, and evaluating feedback in health care based on a systematic review and meta-synthesis of qualitative research

BACKGROUND

Providing health professionals with quantitative summaries of their clinical performance when treating specific groups of patients ("feedback") is a widely used quality improvement strategy, yet systematic reviews show it has varying success. Theory could help explain what factors influence feedback success, and guide approaches to enhance effectiveness. However, existing theories lack comprehensiveness and specificity to health care. To address this problem, we conducted the first systematic review and synthesis of qualitative evaluations of feedback interventions, using findings to develop a comprehensive new health care-specific feedback theory.

METHODS

We searched MEDLINE, EMBASE, CINAHL, Web of Science, and Google Scholar from inception until 2016 inclusive. Data were synthesised by coding individual papers, building on pre-existing theories to formulate hypotheses, iteratively testing and improving hypotheses, assessing confidence in hypotheses using the GRADE-CERQual method, and summarising high-confidence hypotheses into a set of propositions.

RESULTS

We synthesised 65 papers evaluating 73 feedback interventions from countries spanning five continents. From our synthesis we developed Clinical Performance Feedback Intervention Theory (CP-FIT), which builds on 30 pre-existing theories and has 42 high-confidence hypotheses. CP-FIT states that effective feedback works in a cycle of sequential processes; it becomes less effective if any individual process fails, thus halting progress round the cycle. Feedback's success is influenced by several factors operating via a set of common explanatory mechanisms: the feedback method used, health professional receiving feedback, and context in which feedback takes place. CP-FIT summarises these effects in three propositions: (1) health care professionals and organisations have a finite capacity to engage with feedback, (2) these parties have strong beliefs regarding how patient care should be provided that influence their interactions with feedback, and (3) feedback that directly supports clinical behaviours is most effective.

CONCLUSIONS

This is the first qualitative meta-synthesis of feedback interventions, and the first comprehensive theory of feedback designed specifically for health care. Our findings contribute new knowledge about how feedback works and factors that influence its effectiveness. Internationally, practitioners, researchers, and policy-makers can use CP-FIT to design, implement, and evaluate feedback. Doing so could improve care for large numbers of patients, reduce opportunity costs, and improve returns on financial investments.

TRIAL REGISTRATION

PROSPERO, CRD42015017541.

Optimising feedback for early career professionals: a scoping review and new framework

CONTEXT

Meta-analyses have shown that feedback can be a powerful intervention to increase learning and performance but there is significant variability in impact. New trials are adding little to the question of whether feedback interventions are effective, so the focus now is how to optimise the effect. Early career professionals (ECPs) in busy work environments are a particularly important target group. This literature review aimed to synthesise information to support the optimal design of feedback interventions for ECPs.

METHODS

We undertook a scoping literature review, using search terms such as 'feedback' and 'effectiveness' in MEDLINE, MEDLINE-In-Process, PsycINFO, CINAHL, Education Research Complete, Education Resources Information Center, the Cochrane Database of Systematic Reviews, the Social Sciences Citation Index and Applied Social Sciences Index and Abstracts, to identify empirical studies describing feedback interventions in busy workplaces published in English since 1990. We applied inclusion criteria to identify studies for the mapping stage and extracted key data to inform the next stage. We then selected a subset of papers for the framework development stage, which were subjected to a thematic synthesis by three authors, leading to a new feedback framework and a modified version of feedback intervention theory specifically for ECPs.

RESULTS

A total of 80 studies were included in the mapping stage, with roughly equal studies from hospital settings and school classrooms, and 17 papers were included in the framework development stage. The feedback framework comprised three main categories (audit, feedback and goal setting) and 22 subcategories. The review highlighted the limited empirical research focusing solely on feedback for ECPs, which was surprising given the particular nuances in feedback for ECPs identified through this study.

CONCLUSIONS

We offer the feedback framework to optimise the design of future feedback interventions for early career professionals and encourage future feedback research to move away from generic models and tailor work to specific target audiences.

Nurse, Patient, and Care Partner Perceptions of a Personalized Safety Plan Screensaver

A patient safety plan dashboard was developed that captures disparate data from the electronic health record that is then displayed as a personalized bedside screensaver. The dashboard aligns all care team members, including patients and families, in the safety plan. The screensaver content includes icons that pertain to common geriatric syndromes. In two phases, interviews were conducted with nurses, nursing assistants, patients, and informal caregivers in a large, tertiary care center. End user perceptions of the content and interface of the personalized safety plan screensavers were identified and strategies to overcome the barriers to use for future iterations were defined. Many themes were identified, ranging from appreciation of the clinical decision support provided by the screensavers to the value of the safety-centric content. Differences emerged stemming from each group of end users' role on the care team. All feedback will inform requirements for improvements to the personalized safety plan screensaver. [Journal of Gerontological Nursing, 43(4), 15-22.].

Developmental Surveillance and Screening in the Electronic Health Record

Effective well-child care includes developmental surveillance and screening to identify developmental delays and subsequent interventions. Electronic health records (EHRs) have been widely adopted to improve efficiency and appropriate clinical practice. Developmental surveillance tools have been introduced. This article summarizes a conceptual framework for application and highlights the principles and tools of EHRs applied to developmental assessment, including interoperability, health information exchange, clinical decision support systems, consumer health informatics, dashboards, and patient portals. Further investigation and dedicated resources will be required for successful application to developmental surveillance and screening.

A review of dashboards for data analytics in nursing

Dashboards are data-driven clinical decision support tools used to analyze data from multiple databases using easy-to-read, color-coded graphical displays, much like the dashboards of automobiles. Dashboards can be used to promote data-driven decision making and improve adherence to evidence-based practice guidelines. The purpose of this article was to provide a review of dashboards used to query electronic health records for the purpose of guiding clinical practice and research. An inductive content analysis approach was used to identify emerging themes directly from the literature. Five basic dashboard properties identified include the type of database integration, visual properties, purpose, time focus (ie, retrospective, real time, or predictive), and type of process monitored. These dashboard properties are determined by the characteristics of the specific organization, user, and purpose of data analysis. Using dashboards to perform automated analytical reviews of clinical data will prove more efficient when data elements stored in electronic health records become standardized. Other limitations of dashboard use include user anxiety, information overload, and technology overload. The increased use of electronic documentation in healthcare settings will provide a wealth of data, and dashboards will play a pivotal role in converting these data into actionable knowledge.

The effect of registry-based performance feedback via short text messages and traditional postal letters on prescribing parenteral steroids by general practitioners--A randomized controlled trial

BACKGROUND

It is conjectured that providing feedback on physicians' prescribing behavior improves quality of drug prescriptions. However, the effectiveness of feedback provision and mode of feedback delivery is not well understood. The objective of this study was to assess and compare the effect of traditional paper letters (TPL) and short text message (STM) feedback on general practitioners' prescribing behavior of parenteral steroids (PSs).

METHODS

In a single-blind randomized controlled trial, 906 general practitioners (GPs) having at least 10 monthly prescriptions were randomly recruited into two interventions and one control study arms with 1:1 allocation, stratified by percentage of prescriptions. The intervention was the provision of 3 feedback messages containing prescribing indices in TPL and STM (in the first two arms) versus the control arm (CG) with an interval of 3 months between these messages. We calculated the PS Defined Daily Dose (DDD) for every GP, every month, and compared between the 3 arms, before and after the interventions. The expected primary outcome was to reduce prescription of parenteral steroids by participants. The study was performed in the Kerman Social Security Organization in Iran.

RESULTS

A total of 906 GPs were selected for the trial, but only 721 of them (TPL=191, STM=228, CG=302) were recruited for the 1st feedback. The mean age of GPs was 44 and 59% of them were male. The prescribed parenteral steroid DDDs at baseline were similar (TPL=121.62, STM=127.49, CG=115.68, P>0.5). At the end of the study, DDDs in the TPL and STM arms were similar (TPL=104.38, STM=101.90, P>0.9) but DDDs in each intervention arm was statistically significantly lower than in CG (CG=156.17, P<0.0001). Being in TPL and STM arms resulted in 36.1 and 41.7 units of decrease in DDD respectively, compared to the control arm (P<0.02 and P<0.005) after the one-year duration of the study.

CONCLUSION

Feedback by TPLs and STMs on prescribing performance effectively reduced prescribing PSs by GPs. STM, being a cheap and fast tool, is potentially powerful and efficient for drug prescription rationalization.