Cook, David A.

Abstract Objective The study sought to identify barriers to and facilitators of point-of-care information seeking and use of knowledge resources. Materials and Methods We searched MEDLINE, Embase, PsycINFO, and Cochrane Library from 1991 to February 2017. We included qualitative studies in any language exploring barriers to and facilitators of point-of-care information seeking or use of electronic knowledge resources. Two authors independently extracted data on users, study design, and study quality. We inductively identified specific barriers or facilitators and from these synthesized a model of key determinants of information-seeking behaviors. Results Forty-five qualitative studies were included, reporting data derived from interviews (n = 26), focus groups (n = 21), ethnographies (n = 6), logs (n = 4), and usability studies (n = 2). Most studies were performed within the context of general medicine (n = 28) or medical specialties (n = 13). We inductively identified 58 specific barriers and facilitators and then created a model reflecting 5 key determinants of information-seeking behaviors: time includes subthemes of time availability, efficiency of information seeking, and urgency of information need; accessibility includes subthemes of hardware access, hardware speed, hardware portability, information restriction, and cost of resources; personal skills and attitudes includes subthemes of computer literacy, information-seeking skills, and contextual attitudes about information seeking; institutional attitudes, cultures, and policies includes subthemes describing external individual and institutional information-seeking influences; and knowledge resource features includes subthemes describing information-seeking efficiency, information content, information organization, resource familiarity, information credibility, information currency, workflow integration, compatibility of recommendations with local processes, and patient educational support. Conclusions Addressing these determinants of information-seeking behaviors may facilitate clinicians' question answering to improve patient care.

The objective was to quantitatively evaluate clinician characteristics associated with unwarranted practice variation, and how clinical care algorithms influence this variation. Participants (142 physicians, 53 nurse practitioners, and 9 physician assistants in family medicine, internal medicine, and cardiology) described their management of 4 clinical vignettes, first based on their own practice (unguided), then using care algorithms (guided). The authors quantitatively estimated variation in management. Cardiologists demonstrated 17% lower variation in unguided responses than generalists (fold-change 0.83 [95% confidence interval (CI) 0.68, 0.97]), and those who agreed that practice variation can realistically be reduced had 16% lower variation than those who did not (fold-change 0.84 [CI, 0.71, 0.99]). A 17% reduction in variation was observed for guided responses compared with baseline (unguided) responses (fold-change 0.83 [CI, 0.76, 0.90]). Differences were otherwise similar across clinician subgroups and attitudes. Unwarranted practice variation was similar across most clinician subgroups. The authors conclude that care algorithms can reduce variation in management.

Purpose The authors sought to summarize quantitative and qualitative research addressing electronic knowledge resources and point-of-care learning in a scoping review. Method The authors searched MEDLINE, Embase, PsycINFO, and the Cochrane Database for studies addressing electronic knowledge resources and point-of-care learning. They iteratively revised inclusion criteria and operational definitions of study features and research themes of interest. Two reviewers independently performed each phase of study selection and data extraction. Results Of 10,811 studies identified, 305 were included and reviewed. Most studies (225; 74%) included physicians or medical students. The most frequently mentioned electronic resources were UpToDate (88; 29%), Micromedex (59; 19%), Epocrates (50; 16%), WebMD (46; 15%), MD Consult (32; 10%), and LexiComp (31; 10%). Eight studies (3%) evaluated electronic resources or point-of-care learning using outcomes of patient effects, and 36 studies (12%) reported objectively measured clinician behaviors. Twenty-five studies (8%) examined the clinical or educational impact of electronic knowledge resource use on patient care or clinician knowledge, 124 (41%) compared use rates of various knowledge resources, 69 (23%) examined the quality of knowledge resource content, and 115 (38%) explored the process of point-of-care learning. Two conceptual clarifications were identified, distinguishing the impact on clinical or educational outcomes versus the impact on test setting decision support, and the quality of information content versus the correctness of information obtained by a clinician–user. Conclusions Research on electronic knowledge resources is dominated by studies involving physicians and evaluating use rates. Studies involving nonphysician users, and evaluating resource impact and implementation, are needed.

Purpose To evaluate the validity of scores from three instruments measuring achievement goal motivation-related constructs: a shortened version of Dweck’s Implicit Theories of Intelligence Scale (ITIS-S), measuring incremental and entity mindsets; Elliot’s Achievement Goal Questionnaire–Revised (AGQ-R), measuring mastery-approach, mastery-avoidance, performance-approach, and performance-avoidance achievement goals; and Midgley’s Patterns of Adaptive Learning Scales (PALS), measuring mastery, performance-approach, and performance-avoidance achievement goals. Method High school students participating in a medical simulation training activity in May 2017 completed each instrument. The authors evaluated internal structure using reliability and factor analysis and relations with other variables using the multitrait–multimethod matrix. Results There were 178 participants. Internal consistency reliability (Cronbach alpha) was > 0.70 for all subscores. Confirmatory factor analysis of ITIS-S scores demonstrated good model fit. Confirmatory factor analysis of AGQ-R scores demonstrated borderline fit; exploratory factor analysis suggested a three-domain model (approach, mastery-avoidance, performance-avoidance). Confirmatory factor analysis of PALS scores also demonstrated borderline fit; exploratory factor analyses suggested consistent distinction between mastery and performance goals but inconsistent distinction between performance-approach and performance-avoidance goals. Correlations among AGQ-R and PALS scores were large for mastery ( r = 0.72) and moderate for performance (≥ 0.45) domains; correlations among incremental and mastery scores were moderate (≥ 0.34). Contrary to expectations, correlations between entity and performance scores were negligible. Correlations between conceptually unrelated domains were small or negligible. Conclusions All instrument scores had good internal consistency and generally appropriate relations with other variables, but empirically determined domain structures did not consistently match theory.

Purpose To determine whether “chronometric pressure” (i.e., a verbal prompt to increase speed) could predictably alter medical learners’ speed–accuracy trade-off during a simulated surgical task, thus modifying the challenge. Method The authors performed a single-task, interrupted time-series study, enrolling surgery residents and medical students from two institutions in September and October 2015. Participants completed 10 repetitions of a simulated blood vessel ligation (placement of two ligatures 1 cm apart). Between repetitions 5 and 6, participants were verbally encouraged to complete the next repetition 20% faster than the previous one. Outcomes included time and accuracy (ligature tightness, placement distance). Data were analyzed using random-coefficients spline models. Results The authors analyzed data from 78 participants (25 medical students, 16 first-year residents, 37 senior [second-year or higher] residents). Overall, time decreased from the 1st (mean [standard deviation] 39.8 seconds [18.4]) to the 10th (29.6 [12.5]) repetition. The spline model showed a decrease in time between repetitions 5 and 6 of 8.6 seconds (95% confidence interval: −11.1, −6.1). The faster time corresponded with declines in ligature tightness (unadjusted difference −19%; decrease in odds 0.86 [0.76, 0.98]) and placement accuracy (unadjusted difference −5%; decrease in odds 0.86 [0.75, 0.99]). Significant differences in the speed–accuracy trade-off were seen by training level, with senior residents demonstrating the greatest decline in accuracy as speed increased. Conclusions Chronometric pressure influenced the speed–accuracy trade-off and modified the challenge level in a simulated surgical task. It may help unmask correctable deficiencies or false plateaus in learners’ skill development.

Introduction Clinical practice guidelines facilitate optimal clinical practice. Point of care access, interpretation and application of such guidelines, however, is inconsistent. Informatics-based tools may help clinicians apply guidelines more consistently. We have developed a novel clinical decision support tool that presents guideline-relevant information and actionable items to clinicians at the point of care. We aim to test whether this tool improves the management of hyperlipidaemia, atrial fibrillation and heart failure by primary care clinicians. Methods/analysis Clinician care teams were cluster randomised to receive access to the clinical decision support tool or passive access to institutional guidelines on 16 May 2016. The trial began on 1 June 2016 when access to the tool was granted to the intervention clinicians. The trial will be run for 6 months to ensure a sufficient number of patient encounters to achieve 80% power to detect a twofold increase in the primary outcome at the 0.05 level of significance. The primary outcome measure will be the percentage of guideline-based recommendations acted on by clinicians for hyperlipidaemia, atrial fibrillation and heart failure. We hypothesise care teams with access to the clinical decision support tool will act on recommendations at a higher rate than care teams in the standard of care arm. Ethics and dissemination The Mayo Clinic Institutional Review Board approved all study procedures. Informed consent was obtained from clinicians. A waiver of informed consent and of Health Insurance Portability and Accountability Act (HIPAA) authorisation for patients managed by clinicians in the study was granted. In addition to publication, results will be disseminated via meetings and newsletters. Trial registration number NCT02742545 .