Physicians’ electronic inbox work patterns and factors associated with high inbox work duration

ObjectivesElectronic health record systems are increasingly used to send messages to physicians, but research on physicians’ inbox use patterns is limited. This study’s aims were to (1) quantify the time primary care physicians (PCPs) spend managing inboxes; (2) describe daily patterns of inbox use; (3) investigate which types of messages consume the most time; and (4) identify factors associated with inbox work duration.Materials and MethodsWe analyzed 1 month of electronic inbox data for 1275 PCPs in a large medical group and linked these data with physicians’ demographic data.ResultsPCPs spent an average of 52 minutes on inbox management on workdays, including 19 minutes (37%) outside work hours. Temporal patterns of electronic inbox use differed from other EHR functions such as charting. Patient-initiated messages (28%) and results (29%) accounted for the most inbox work time. PCPs with higher inbox work duration were more likely to be female (P < .001), have more patient encounters (P < .001), have older patients (P < .001), spend proportionally more time on patient messages (P < .001), and spend more time per message (P < .001). Compared with PCPs with the lowest duration of time on inbox work, PCPs with the highest duration had more message views per workday (200 vs 109; P < .001) and spent more time on the inbox outside work hours (30 minutes vs 9.7 minutes; P < .001).ConclusionsElectronic inbox work by PCPs requires roughly an hour per workday, much of which occurs outside scheduled work hours. Interventions to assist PCPs in handling patient-initiated messages and results may help alleviate inbox workload.     

Can decision support combat incompleteness and bias in routine primary care data?

ObjectiveRoutine primary care data may be used for the derivation of clinical prediction rules and risk scores. We sought to measure the impact of a decision support system (DSS) on data completeness and freedom from bias.Materials and MethodsWe used the clinical documentation of 34 UK general practitioners who took part in a previous study evaluating the DSS. They consulted with 12 standardized patients. In addition to suggesting diagnoses, the DSS facilitates data coding. We compared the documentation from consultations with the electronic health record (EHR) (baseline consultations) vs consultations with the EHR-integrated DSS (supported consultations). We measured the proportion of EHR data items related to the physician’s final diagnosis. We expected that in baseline consultations, physicians would document only or predominantly observations related to their diagnosis, while in supported consultations, they would also document other observations as a result of exploring more diagnoses and/or ease of coding.ResultsSupported documentation contained significantly more codes (incidence rate ratio [IRR] = 5.76 [4.31, 7.70] P < .001) and less free text (IRR = 0.32 [0.27, 0.40] P < .001) than baseline documentation. As expected, the proportion of diagnosis-related data was significantly lower (b = −0.08 [−0.11, −0.05] P < .001) in the supported consultations, and this was the case for both codes and free text.ConclusionsWe provide evidence that data entry in the EHR is incomplete and reflects physicians’ cognitive biases. This has serious implications for epidemiological research that uses routine data. A DSS that facilitates and motivates data entry during the consultation can improve routine documentation.     

How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis

ObjectiveTo conduct a systematic review and meta-analysis to assess: 1) changes in medication error rates and associated patient harm following electronic medication system (EMS) implementation; and 2) evidence of system-related medication errors facilitated by the use of an EMS.Materials and MethodsWe searched Medline, Scopus, Embase, and CINAHL for studies published between January 2005 and March 2019, comparing medication errors rates with or without assessments of related harm (actual or potential) before and after EMS implementation. EMS was defined as a computer-based system enabling the prescribing, supply, and/or administration of medicines. Study quality was assessed.ResultsThere was substantial heterogeneity in outcomes of the 18 included studies. Only 2 were strong quality. Meta-analysis of 5 studies reporting change in actual harm post-EMS showed no reduced risk (RR: 1.22, 95% CI: 0.18–8.38, P = .8) and meta-analysis of 3 studies reporting change in administration errors found a significant reduction in error rates (RR: 0.77, 95% CI: 0.72–0.83, P = .004). Of 10 studies of prescribing error rates, 9 reported a reduction but variable denominators precluded meta-analysis. Twelve studies provided specific examples of system-related medication errors; 5 quantified their occurrence.Discussion and ConclusionDespite the wide-scale adoption of EMS in hospitals around the world, the quality of evidence about their effectiveness in medication error and associated harm reduction is variable. Some confidence can be placed in the ability of systems to reduce prescribing error rates. However, much is still unknown about mechanisms which may be most effective in improving medication safety and design features which facilitate new error risks.     

Human-centered development of an electronic health record-embedded,interactive information visualization in the emergency department using fast healthcare interoperability resources

ObjectiveDevelop and evaluate an interactive information visualization embedded within the electronic health record (EHR) by following human-centered design (HCD) processes and leveraging modern health information exchange standards.Materials and MethodsWe applied an HCD process to develop a Fast Healthcare Interoperability Resources (FHIR) application that displays a patient’s asthma history to clinicians in a pediatric emergency department. We performed a preimplementation comparative system evaluation to measure time on task, number of screens, information retrieval accuracy, cognitive load, user satisfaction, and perceived utility and usefulness. Application usage and system functionality were assessed using application logs and a postimplementation survey of end users.ResultsUsability testing of the Asthma Timeline Application demonstrated a statistically significant reduction in time on task (P < .001), number of screens (P < .001), and cognitive load (P < .001) for clinicians when compared to base EHR functionality. Postimplementation evaluation demonstrated reliable functionality and high user satisfaction.DiscussionFollowing HCD processes to develop an application in the context of clinical operations/quality improvement is feasible. Our work also highlights the potential benefits and challenges associated with using internationally recognized data exchange standards as currently implemented.ConclusionCompared to standard EHR functionality, our visualization increased clinician efficiency when reviewing the charts of pediatric asthma patients. Application development efforts in an operational context should leverage existing health information exchange standards, such as FHIR, and evidence-based mixed methods approaches.     

The impact of time spent on the electronic health record after work and of clerical work on burnout among clinical faculty

ObjectiveTo identify specific thresholds of daily electronic health record (EHR) time after work and daily clerical time burden associated with burnout in clinical faculty.Materials and MethodsWe administered an institution-wide survey to faculty in all departments at Mount Sinai Health System from November 2018 to February 2019. The Maslach Burnout Inventory and Mayo Well-Being Index assessed burnout. Demographics, possible confounding variables, and time spent on EHR work/clerical burden were assessed.ResultsOf 4156 eligible faculty members, 1781(42.9%) participated in the survey. After adjustment for background factors, EHR frustration (odds ratio [OR]=1.64–1.66), spending >90 minutes on EHR-outside the workday by self-report (OR = 1.41–1.90) and >1 hour of self-reported clerical work/day (OR = 1.39) were associated with burnout. Reporting that one’s practice unloads clerical burden (OR = 0.50–0.66) and higher resilience scores (OR = 0.77–0.84) were negatively associated with burnout.Spending >90 minutes/day on EHR-outside work (OR = 0.66–0.67) and >60 minutes/day on clerical work (OR = 0.54–0.58) was associated with decreased likelihood of satisfactory work–life integration (WLI) and professional satisfaction (PS). Greater meaning in work was associated with an increasedlikelihoodof achieving WLI (OR = 2.51) and PS (OR = 21.67).ConclusionResults suggest there are thresholds of excessive time on the EHR-outside the workday (>90 minutes) and overall clerical tasks (>60 minutes), above which clinical faculty may be at increased risk for burnout, as well as reduced WLI and PS, independent of demographic characteristics and clinical work hours. These thresholds of EHR and clerical burden may inform interventions aimed at mitigating this burden to reduce physician burnout.     

Measuring time clinicians spend using EHRs in the inpatient setting: a national,mixed-methods study

ObjectiveTo understand hospitals’ use of EHR audit-log-based measures to address burden associated with inpatient EHR use.Materials and MethodsUsing mixed methods, we analyzed 2018 American Hospital Association Information Technology Supplement Survey data (n = 2864 hospitals; 64% response rate) to characterize measures used and provided by EHR vendors to track clinician time spent documenting. We interviewed staff from the top 3 EHR vendors that provided these measures. Multivariable analyses identified variation in use of the measures among hospitals with these 3 vendors.Results53% of hospitals reported using EHR data to track clinician time documenting, compared to 68% of the hospitals using the EHR from the top 3 vendors. Among hospitals with EHRs from these vendors, usage was significantly lower among rural hospitals and independent hospitals (P < .05). Two of these vendors provided measures of time spent doing specific tasks while the third measured an aggregate of auditable activities. Vendors varied in the underlying data used to create measures, measure specification, and data displays.DiscussionTools to track clinicians’ documentation time are becoming more available. The measures provided differ across vendors and disparities in use exist across hospitals. Increasing the specificity of standards underlying the data would support a common set of core measures making these measures more widely available.ConclusionAlthough half of US hospitals use measures of time spent in the EHR derived from EHR generated data, work remains to make such measures and analyses more broadly available to all hospitals and to increase its utility for national burden measurement.     

A visual representation of microbiological culture data improves comprehension: a randomized controlled trial

ObjectiveWhile the judicious use of antibiotics takes past microbiological culture results into consideration, this data’s typical format in the electronic health record (EHR) may be unwieldy when incorporated into clinical decision-making. We hypothesize that a visual representation of sensitivities may aid in their comprehension.Materials and MethodsA prospective parallel unblinded randomized controlled trial was undertaken at an academic urban tertiary care center. Providers managing emergency department (ED) patients receiving antibiotics and having previous culture sensitivity testing were included. Providers were randomly selected to use standard EHR functionality or a visual representation of patients’ past culture data as they answered questions about previous sensitivities. Concordance between provider responses and past cultures was assessed using the kappa statistic. Providers were surveyed about their decision-making and the usability of the tool using Likert scales.Results518 ED encounters were screened from 3/5/2018 to 9/30/18, with providers from 144 visits enrolled and analyzed in the intervention arm and 129 in the control arm. Providers using the visualization tool had a kappa of 0.69 (95% CI: 0.65–0.73) when asked about past culture results while the control group had a kappa of 0.16 (95% CI: 0.12–0.20). Providers using the tool expressed improved understanding of previous cultures and found the tool easy to use (P < .001). Secondary outcomes showed no differences in prescribing practices.ConclusionA visual representation of culture sensitivities improves comprehension when compared to standard text-based representations.     

Comparison of five equations for estimating resting energy expenditure in Chinese young,normal weight healthy adults

Background

Most resting energy expenditure (REE) predictive equations for adults were derived from research conducted in western populations; whether they can also be used in Chinese young people is still unclear. Therefore, we conducted this study to determine the best REE predictive equation in Chinese normal weight young adults.

Methods

Forty-three (21 male, 22 female) healthy college students between the age of 18 and 25 years were recruited. REE was measured by the indirect calorimetry (IC) method. Harris-Benedict, World Health Organization (WHO), Owen, Mifflin and Liu’s equations were used to predictREE (REEe). REEe that was within 10% of measured REE (REEm) was defined as accurate. Student’s t test, Wilcoxon Signed Ranks Test, McNemar Test and the Bland-Altman method were used for data analysis.

Results

REEm was significantly lower (P < 0.05 or P < 0.01) than REEe from equations, except for Liu’s, Liu’s-s, Owen, Owen-s and Mifflin in men and Liu’s and Owen in women. REEe calculated by ideal body weight was significantly higher than REEe calculated by current body weight ( P < 0.01), the only exception being Harris-Benedict equation in men. Bland-Altman analysis showed that the Owen equation with current body weight generated the least bias. The biases of REEe from Owen with ideal body weight and Mifflin with both current and ideal weights were also lower.

Conclusions

Liu’s, Owen, and Mifflin equations are appropriate for the prediction of REE in young Chinese adults. However, the use of ideal body weight did not increase the accuracy of REEe.     

Risk factors associated with medication ordering errors

ObjectiveWe utilized a computerized order entry system–integrated function referred to as “void” to identify erroneous orders (ie, a “void” order). Using voided orders, we aimed to (1) identify the nature and characteristics of medication ordering errors, (2) investigate the risk factors associated with medication ordering errors, and (3) explore potential strategies to mitigate these risk factors.Materials and MethodsWe collected data on voided orders using clinician interviews and surveys within 24 hours of the voided order and using chart reviews. Interviews were informed by the human factors–based SEIPS (Systems Engineering Initiative for Patient Safety) model to characterize the work systems–based risk factors contributing to ordering errors; chart reviews were used to establish whether a voided order was a true medication ordering error and ascertain its impact on patient safety.ResultsDuring the 16-month study period (August 25, 2017, to December 31, 2018), 1074 medication orders were voided; 842 voided orders were true medication errors (positive predictive value = 78.3 ± 1.2%). A total of 22% (n = 190) of the medication ordering errors reached the patient, with at least a single administration, without causing patient harm. Interviews were conducted on 355 voided orders (33% response). Errors were not uniquely associated with a single risk factor, but the causal contributors of medication ordering errors were multifactorial, arising from a combination of technological-, cognitive-, environmental-, social-, and organizational-level factors.ConclusionsThe void function offers a practical, standardized method to create a rich database of medication ordering errors. We highlight implications for utilizing the void function for future research, practice and learning opportunities.     

Impact of a problem-oriented view on clinical data retrieval

ObjectiveThe electronic health record (EHR) data deluge makes data retrieval more difficult, escalating cognitive load and exacerbating clinician burnout. New auto-summarization techniques are needed. The study goal was to determine if problem-oriented view (POV) auto-summaries improve data retrieval workflows. We hypothesized that POV users would perform tasks faster, make fewer errors, be more satisfied with EHR use, and experience less cognitive load as compared with users of the standard view (SV).MethodsSimple data retrieval tasks were performed in an EHR simulation environment. A randomized block design was used. In the control group (SV), subjects retrieved lab results and medications by navigating to corresponding sections of the electronic record. In the intervention group (POV), subjects clicked on the name of the problem and immediately saw lab results and medications relevant to that problem.ResultsWith POV, mean completion time was faster (173 seconds for POV vs 205 seconds for SV; P < .0001), the error rate was lower (3.4% for POV vs 7.7% for SV; P = .0010), user satisfaction was greater (System Usability Scale score 58.5 for POV vs 41.3 for SV; P < .0001), and cognitive task load was less (NASA Task Load Index score 0.72 for POV vs 0.99 for SV; P < .0001).DiscussionThe study demonstrates that using a problem-based auto-summary has a positive impact on 4 aspects of EHR data retrieval, including cognitive load.ConclusionEHRs have brought on a data deluge, with increased cognitive load and physician burnout. To mitigate these increases, further development and implementation of auto-summarization functionality and the requisite knowledge base are needed.     

Reducing electronic health record-related burnout in providers through a personalized efficiency improvement program

ObjectiveTo give providers a better understanding of how to use the electronic health record (EHR), improve efficiency, and reduce burnout.Materials and MethodsAll ambulatory providers were offered at least 1 one-on-one session with an “optimizer” focusing on filling gaps in EHR knowledge and lack of customization. Success was measured using pre- and post-surveys that consisted of validated tools and homegrown questions. Only participants who returned both surveys were included in our calculations.ResultsOut of 1155 eligible providers, 1010 participated in optimization sessions. Pre-survey return rate was 90% (1034/1155) and post-survey was 54% (541/1010). 451 participants completed both surveys. After completing their optimization sessions, respondents reported a 26% improvement in mean knowledge of EHR functionality (P < .01), a 19% increase in the mean efficiency in the EHR (P < .01), and a 17% decrease in mean after-hours EHR usage (P < .01). Of the 401 providers asked to rate their burnout, 32% reported feelings of burnout in the pre-survey compared to 23% in the post-survey (P < .01). Providers were also likely to recommend colleagues participate in the program, with a Net Promoter Score of 41.DiscussionIt is possible to improve provider efficiency and feelings of burnout with a personalized optimization program. We ascribe these improvements to the one-on-one nature of our program which provides both training as well as addressing the feeling of isolation many providers feel after implementation.ConclusionIt is possible to reduce burnout in ambulatory providers with personalized retraining designed to improve efficiency and knowledge of the EHR.     

Thoracic epidural anesthesia improves outcomes in patients undergoing cardiac surgery: meta-analysis of randomized controlled trials

To assess the efficacy of thoracic epidural anesthesia (TEA) with or without general anesthesia (GA) versus GA in patients who underwent cardiac surgery, PubMed, Embase, the Cochrane online database, and Web of Science were searched with the limit of randomized controlled trials (RCTs) relevant to ‘thoracic epidural anesthesia’ and ‘cardiac surgery’. Studies were identified and data were extracted by two reviewers independently. The quality of included studies was also assessed according to the Cochrane handbook. Outcomes of mortality, cardiac and respiratory functions, and treatment-associated complications were pooled and analyzed. The comprehensive search yielded 2,230 citations, and 25 of them enrolling 3,062 participants were included according to the inclusion criteria. Compared with GA alone, patients received TEA and GA showed reduced risks of death, myocardial infarction, and stroke, though there were no significant differences (P > 0.05). With regard to treatment-related complications, the pooled results for respiratory complications (risk ratio (RR), 0.69; 95% CI: 0.51, 0.91, P < 0.05), supraventricular arrhythmias (RR, 0.61; 95% CI: 0.42, 0.87, P < 0.05), and pain (mean difference (MD), −1.27; 95% CI: −2.20, −0.35, P < 0.05) were 0.69, 0.61, and −1.27, respectively. TEA was also associated with significant reduction of stays in intensive care unit (MD, −2.36; 95% CI: −4.20, −0.52, P < 0.05) and hospital (MD, −1.51; 95% CI: −3.03, 0.02, P > 0.05) and time to tracheal extubation (MD, −2.06; 95% CI:−2.68, −1.45, P < 0.05). TEA could reduce the risk of complications such as supraventricular arrhythmias, stays in hospital or intensive care unit, and time to tracheal extubation in patients who experienced cardiac surgery.

Electronic supplementary material

The online version of this article (doi:10.1186/s40001-015-0091-y) contains supplementary material, which is available to authorized users.     

The correlation between fear of falling and upper extremity muscle strength

Objectives:To determine the relationship between fear of falling (FOF) and upper extremity muscle strength.Methods:This cross-sectional study included 112 hospitalized, mobile patients. Forty-seven (42%) were males and 65 (58%) were females, and the mean age was 72.3. The study was carried out between September 2018 and September 2019 at Balikli Rum Hospital Nursing Homes, Istanbul, Turkey. Patients were tested using geriatric tools (such as Mini-Mental State Examination) and physical tests such as handgrip, key pinch and 6-meter up and go tests.Results:The average annual falling number of elderly people with FOF was statistically significantly higher than that in those without FOF (p=0.001). Right handgrip, left handgrip, right key pinch, and left key-pinch mean values in elderly individuals with FOF were statistically significantly lower than those without FOF (p< 0.001, p< 0.001, p< 0.001, p< 0.001, respectively).Conclusion:The measurement of upper extremity strength could be a predicting parameter of FOF.     

Examining association between cohesion and diversity in collaboration networks of pharmaceutical clinical trials with drug approvals

ObjectiveClinical trials ensure that pharmaceutical treatments are safe, efficacious, and effective for public consumption, but are extremely complex, taking up to 10 years and $2.6 billion to complete. One main source of complexity arises from the collaboration between actors, and network science methodologies can be leveraged to explore that complexity. We aim to characterize collaborations between actors in the clinical trials context and investigate trends of successful actors.Materials and MethodsWe constructed a temporal network of clinical trial collaborations between large and small-size pharmaceutical companies, academic institutions, nonprofit organizations, hospital systems, and government agencies from public and proprietary data and introduced metrics to quantify actors’ collaboration network structure, organizational behavior, and partnership characteristics. A multivariable regression analysis was conducted to determine the metrics’ relationship with success.ResultsWe found a positive correlation between the number of successful approved trials and interdisciplinary collaborations measured by a collaboration diversity metric (P < .01). Our results also showed a negative effect of the local clustering coefficient (P < .01) on the success of clinical trials. Large pharmaceutical companies have the lowest local clustering coefficient and more diversity in partnerships across biomedical specializations.ConclusionsLarge pharmaceutical companies are more likely to collaborate with a wider range of actors from other specialties, especially smaller industry actors who are newcomers in clinical research, resulting in exclusive access to smaller actors. Future investigations are needed to show how concentrations of influence and resources might result in diminished gains in treatment development.