Data Quality of Chemotherapy-Induced Nausea and Vomiting Documentation

Objective  The objective of the study was to characterize the completeness and concordance of the electronic health record (EHR) documentation of cancer symptoms among multidisciplinary health care professionals. Methods  We examined the EHRs of children, adolescents, and young adults who received highly emetogenic chemotherapy and characterized the completeness and concordance of chemotherapy-induced nausea and vomiting (CINV) documentation by clinician type and by the International Classification of Diseases 10th Revision (ICD-10) coding choice. Results  The EHRs of 127 patients, comprising 870 patient notes, were abstracted and reviewed. A CINV assessment was documented by prescribers in 75% of patients, and by nurses in 58% of patients. Of the 60 encounters where both prescribers and nurses documented, 72% agreed on the presence/absence of CINV. Conclusion  Most patients receiving highly emetogenic chemotherapy had a documented assessment of CINV; however, many had incomplete or discordant documentation of CINV from different providers by role, implying the importance of incorporating pragmatic knowledge of EHR documentation patterns among multidisciplinary health professionals for EHR phenotyping and clinical decision support systems directed toward cancer-related symptom management.     

The Development and Piloting of the Ambulatory Electronic Health Record Evaluation Tool: Lessons Learned

Background  Substantial research has been performed about the impact of computerized physician order entry on medication safety in the inpatient setting; however, relatively little has been done in ambulatory care, where most medications are prescribed. Objective  To outline the development and piloting process of the Ambulatory Electronic Health Record (EHR) Evaluation Tool and to report the quantitative and qualitative results from the pilot. Methods  The Ambulatory EHR Evaluation Tool closely mirrors the inpatient version of the tool, which is administered by The Leapfrog Group. The tool was piloted with seven clinics in the United States, each using a different EHR. The tool consists of a medication safety test and a medication reconciliation module. For the medication test, clinics entered test patients and associated test orders into their EHR and recorded any decision support they received. An overall percentage score of unsafe orders detected, and order category scores were provided to clinics. For the medication reconciliation module, clinics demonstrated how their EHR electronically detected discrepancies between two medication lists. Results  For the medication safety test, the clinics correctly alerted on 54.6% of unsafe medication orders. Clinics scored highest in the drug allergy (100%) and drug–drug interaction (89.3%) categories. Lower scoring categories included drug age (39.3%) and therapeutic duplication (39.3%). None of the clinics alerted for the drug laboratory or drug monitoring orders. In the medication reconciliation module, three (42.8%) clinics had an EHR-based medication reconciliation function; however, only one of those clinics could demonstrate it during the pilot. Conclusion  Clinics struggled in areas of advanced decision support such as drug age, drug laboratory, and drub monitoring. Most clinics did not have an EHR-based medication reconciliation function and this process was dependent on accessing patients'' medication lists. Wider use of this tool could improve outpatient medication safety and can inform vendors about areas of improvement.     

Nursing Attitudes and Practices in Code Documentation Employing a New Electronic Health Record

Objective  Based on feedback from nurses regarding the challenges of code documentation following the implementation of a new electronic health record (EHR), we sought to better understand inpatient nurse attitudes and practices in code documentation and to identify opportunities for improvement. Methods  An anonymous electronic survey was distributed to all inpatient nurses working at a single, 999-bed, university-based, and quaternary care hospital. Participation in the study was voluntary and consent was implied by survey completion. Results  Overall, 432 (14%) of 3,121 inpatient nurses completed the survey. While nearly 80% of respondents indicated feeling very comfortable using computers for personal use, only 5% felt very comfortable navigating the EHR to document codes in real time. While 53% had documented codes in the new EHR, most admitted to documenting on paper with retroactive entry into the EHR. About 25% reported having participated in a code that was not accurately documented in the new EHR. All respondents provided specific suggestions for improving the EHR interface, and over 90% expressed interest in having opportunities to practice code documentation using simulated code events. Conclusion  Despite completion of training modules in code documentation in a new EHR, many inpatient nurses in a single institution feel uncomfortable documenting codes directly into the EHR, and some question the accuracy of this documentation. Improving EHR functionality based on specific recommendations from end-users coupled with more practice documenting simulated codes may ease EHR navigation, leading to nurses'' acceptance of the EHR tool, more accurate and efficient documentation, greater nurse satisfaction and more appropriate quality improvement measures.     

Use,Impact, Weaknesses,and Advanced Features of Search Functions for Clinical Use in Electronic Health Records: A Scoping Review

Objective  Although vast amounts of patient information are captured in electronic health records (EHRs), effective clinical use of this information is challenging due to inadequate and inefficient access to it at the point of care. The purpose of this study was to conduct a scoping review of the literature on the use of EHR search functions within a single patient''s record in clinical settings to characterize the current state of research on the topic and identify areas for future study. Methods  We conducted a literature search of four databases to identify articles on within-EHR search functions or the use of EHR search function in the context of clinical tasks. After reviewing titles and abstracts and performing a full-text review of selected articles, we included 17 articles in the analysis. We qualitatively identified themes in those articles and synthesized the literature for each theme. Results  Based on the 17 articles analyzed, we delineated four themes: (1) how clinicians use search functions, (2) impact of search functions on clinical workflow, (3) weaknesses of current search functions, and (4) advanced search features. Our review found that search functions generally facilitate patient information retrieval by clinicians and are positively received by users. However, existing search functions have weaknesses, such as yielding false negatives and false positives, which can decrease trust in the results, and requiring a high cognitive load to perform an inclusive search of a patient''s record. Conclusion  Despite the widespread adoption of EHRs, only a limited number of articles describe the use of EHR search functions in a clinical setting, despite evidence that they benefit clinician workflow and productivity. Some of the weaknesses of current search functions may be addressed by enhancing EHR search functions with collaborative filtering.     

Are We Ready for Video Recognition and Computer Vision in the Intensive Care Unit? A Survey

Objective  Video recording and video recognition (VR) with computer vision have become widely used in many aspects of modern life. Hospitals have employed VR technology for security purposes, however, despite the growing number of studies showing the feasibility of VR software for physiologic monitoring or detection of patient movement, its use in the intensive care unit (ICU) in real-time is sparse and the perception of this novel technology is unknown. The objective of this study is to understand the attitudes of providers, patients, and patient''s families toward using VR in the ICU. Design  A 10-question survey instrument was used and distributed into two groups of participants: clinicians (MDs, advance practice providers, registered nurses), patients and families (adult patients and patients'' relatives). Questions were specifically worded and section for free text-comments created to elicit respondents'' thoughts and attitudes on potential issues and barriers toward implementation of VR in the ICU. Setting  The survey was conducted at Mayo Clinic in Minnesota and Florida. Results  A total of 233 clinicians'' and 50 patients'' surveys were collected. Both cohorts favored VR under specific circumstances (e.g., invasive intervention and diagnostic manipulation). Acceptable reasons for VR usage according to clinicians were anticipated positive impact on patient safety (70%), and diagnostic suggestions and decision support (51%). A minority of providers was concerned that artificial intelligence (AI) would replace their job (14%) or erode professional skills (28%). The potential use of VR in lawsuits (81% clinicians) and privacy breaches (59% patients) were major areas of concern. Further identified barriers were lack of trust for AI, deterioration of the patient–clinician rapport. Patients agreed with VR unless it does not reduce nursing care or record sensitive scenarios. Conclusion  The survey provides valuable information on the acceptance of VR cameras in the critical care setting including an overview of real concerns and attitudes toward the use of VR technology in the ICU.     

Searching the PDF Haystack: Automated Knowledge Discovery in Scanned EHR Documents

Background  Clinicians express concern that they may be unaware of important information contained in voluminous scanned and other outside documents contained in electronic health records (EHRs). An example is “unrecognized EHR risk factor information,” defined as risk factors for heritable cancer that exist within a patient''s EHR but are not known by current treating providers. In a related study using manual EHR chart review, we found that half of the women whose EHR contained risk factor information meet criteria for further genetic risk evaluation for heritable forms of breast and ovarian cancer. They were not referred for genetic counseling. Objectives  The purpose of this study was to compare the use of automated methods (optical character recognition with natural language processing) versus human review in their ability to identify risk factors for heritable breast and ovarian cancer within EHR scanned documents. Methods  We evaluated the accuracy of the chart review by comparing our criterion standard (physician chart review) versus an automated method involving Amazon''s Textract service (Amazon.com, Seattle, Washington, United States), a clinical language annotation modeling and processing toolkit (CLAMP) (Center for Computational Biomedicine at The University of Texas Health Science, Houston, Texas, United States), and a custom-written Java application. Results  We found that automated methods identified most cancer risk factor information that would otherwise require clinician manual review and therefore is at risk of being missed. Conclusion  The use of automated methods for identification of heritable risk factors within EHRs may provide an accurate yet rapid review of patients'' past medical histories. These methods could be further strengthened via improved analysis of handwritten notes, tables, and colloquial phrases.     

The Effect of Electronic Health Record Burden on Pediatricians' Work–Life Balance and Career Satisfaction

Objectives  To examine pediatricians'' perspectives on administrative tasks including electronic health record (EHR) documentation burden and their effect on work–life balance and life and career satisfaction. Methods  We analyzed 2018 survey data from the American Academy of Pediatrics (AAP) Pediatrician Life and Career Experience Study (PLACES), a longitudinal cohort study of early and midcareer pediatricians. Cohorts graduated from residency between 2002 and 2004 or 2009 and 2011. Participants were randomly selected from an AAP database (included all pediatricians who completed U.S. pediatric residency programs). Four in 10 pediatricians (1,796 out of 4,677) were enrolled in PLACES in 2012 and considered participants in 2018. Data were weighted to adjust for differences between study participants and the overall population of pediatricians. Chi-square and multivariable logistic regression examined the association of EHR burden on work–life balance (three measures) and satisfaction with work, career, and life (three measures). Responses to an open-ended question on experiences with administrative tasks were reviewed. Results  A total of 66% of pediatrician participants completed the 2018 surveys (1,192 of 1,796; analytic sample = 1,069). Three-fourths reported EHR documentation as a major or moderate burden. Half reported such burden for billing and insurance and 42.7% for quality and performance measurement. Most pediatricians reported satisfaction with their jobs (86.7%), careers (84.5%), and lives (66.2%). Many reported work–life balance challenges (52.5% reported stress balancing work and personal responsibilities). In multivariable analysis, higher reported EHR burden was associated with lower scores on career and life satisfaction measures and on all three measures of work–life balance. Open-ended responses ( n  = 467) revealed several themes. Two predominant themes especially supported the quantitative findings—poor EHR functionality and lack of support for administrative burdens. Conclusion  Most early to midcareer pediatricians experience administrative burdens with EHRs. These experiences are associated with worse work–life balance including more stress in balancing responsibilities and less career and life satisfaction.     

Satisfaction of health‐care providers with electronic health records and perceived barriers to its implementation in the United Arab Emirates

The integration of electronic health records (EHRs) has shown promise in improving health‐care quality. In the United Arab Emirates, EHRs have been recently adopted to improve the quality and safety of patient care. A cross‐sectional survey of 680 health‐care providers (HCPs) was conducted to assess the satisfaction of HCPs in the United Arab Emirates with EHRs' impact on access/viewing, documentation and medication administration and to explore the barriers encountered in their use. Data were collected over 6 months from April to September 2014. High overall satisfaction with EHRs was reported by HCPs, suggesting their acceptance. Physicians reported the greatest overall satisfaction with EHRs, although nurses showed significantly higher satisfaction with the impact on medication administration compared with other HCPs. The most significant barriers reported by nurses were lack of belief in the value of EHRs for patients and lack of adequate computer skills. Given the large investment in technology, additional research is necessary to promote the full utilization of EHRs. Nurses need to be aware of the value of EHRs for patient care and be involved in all stages of EHR implementations to maximize its meaningful use for better clinical outcomes.     

Implementing an Application Programming Interface for PROMIS Measures at Three Medical Centers

Background  There is an increasing body of literature advocating for the collection of patient-reported outcomes (PROs) in clinical care. Unfortunately, there are many barriers to integrating PRO measures, particularly computer adaptive tests (CATs), within electronic health records (EHRs), thereby limiting access to advances in PRO measures in clinical care settings. Objective  To address this obstacle, we created and evaluated a software integration of an Application Programming Interface (API) service for administering and scoring Patient-Reported Outcomes Measurement Information System (PROMIS) measures with the EHR system. Methods  We created a RESTful API and evaluated the technical feasibility and impact on clinical workflow at three academic medical centers. Results  Collaborative teams (i.e., clinical, information technology [IT] and administrative staff) performed these integration efforts addressing issues such as software integration as well as impact on clinical workflow. All centers considered their implementation successful based on the high rate of completed PROMIS assessments (between January 2016 and January 2021) and minimal workflow disruptions. Conclusion  These case studies demonstrate not only the feasibility but also the pathway for the integration of PROMIS CATs into the EHR and routine clinical care. All sites utilized diverse teams with support and commitment from institutional leadership, initial implementation in a single clinic, a process for monitoring and optimization, and use of custom software to minimize staff burden and error.     

Interaction Time with Electronic Health Records: A Systematic Review

Background  The amount of time that health care clinicians (physicians and nurses) spend interacting with the electronic health record is not well understood. Objective  This study aimed to evaluate the time that health care providers spend interacting with electronic health records (EHR). Methods  Data are retrieved from Ovid MEDLINE(R) and Epub Ahead of Print, In-Process and Other Non-Indexed Citations and Daily, (Ovid) Embase, CINAHL, and SCOPUS. Study Eligibility Criteria  Peer-reviewed studies that describe the use of EHR and include measurement of time either in hours, minutes, or in the percentage of a clinician''s workday. Papers were written in English and published between 1990 and 2021. Participants  All physicians and nurses involved in inpatient and outpatient settings. Study Appraisal and Synthesis Methods  A narrative synthesis of the results, providing summaries of interaction time with EHR. The studies were rated according to Quality Assessment Tool for Studies with Diverse Designs. Results  Out of 5,133 de-duplicated references identified through database searching, 18 met inclusion criteria. Most were time-motion studies (50%) that followed by logged-based analysis (44%). Most were conducted in the United States (94%) and examined a clinician workflow in the inpatient settings (83%). The average time was nearly 37% of time of their workday by physicians in both inpatient and outpatient settings and 22% of the workday by nurses in inpatient settings. The studies showed methodological heterogeneity. Conclusion  This systematic review evaluates the time that health care providers spend interacting with EHR. Interaction time with EHR varies depending on clinicians'' roles and clinical settings, computer systems, and users'' experience. The average time spent by physicians on EHR exceeded one-third of their workday. The finding is a possible indicator that the EHR has room for usability, functionality improvement, and workflow optimization.     

Clinician and Health Care Leaders' Experiences with—and Perceptions of—COVID-19 Documentation Reduction Policies and Practices

Background  Substantial strategies to reduce clinical documentation were implemented by health care systems throughout the coronavirus disease-2019 (COVID-19) pandemic at national and local levels. This natural experiment provides an opportunity to study the impact of documentation reduction strategies on documentation burden among clinicians and other health professionals in the United States. Objectives  The aim of this study was to assess clinicians'' and other health care leaders'' experiences with and perceptions of COVID-19 documentation reduction strategies and identify which implemented strategies should be prioritized and remain permanent post-pandemic. Methods  We conducted a national survey of clinicians and health care leaders to understand COVID-19 documentation reduction strategies implemented during the pandemic using snowball sampling through professional networks, listservs, and social media. We developed and validated a 19-item survey leveraging existing post-COVID-19 policy and practice recommendations proposed by Sinsky and Linzer. Participants rated reduction strategies for impact on documentation burden on a scale of 0 to 100. Free-text responses were thematically analyzed. Results  Of the 351 surveys initiated, 193 (55%) were complete. Most participants were informaticians and/or clinicians and worked for a health system or in academia. A majority experienced telehealth expansion (81.9%) during the pandemic, which participants also rated as highly impactful (60.1–61.5) and preferred that it remain (90.5%). Implemented at lower proportions, documenting only pertinent positives to reduce note bloat (66.1 ± 28.3), c hanging compliance rules and performance metrics to eliminate those without evidence of net benefit (65.7 ± 26.3), and electronic health record (EHR) optimization sprints (64.3 ± 26.9) received the highest impact scores compared with other strategies presented; support for these strategies widely ranged (49.7–63.7%). Conclusion  The results of this survey suggest there are many perceived sources of and solutions for documentation burden. Within strategies, we found considerable support for telehealth, documenting pertinent positives, and changing compliance rules. We also found substantial variation in the experience of documentation burden among participants.     

Measuring Electronic Health Record Use in the Pediatric ICU Using Audit-Logs and Screen Recordings

Background  Time spent in the electronic health record (EHR) has been identified as an important unit of measure for health care provider clinical activity. The lack of validation of audit-log based inpatient EHR time may have resulted in underuse of this data in studies focusing on inpatient patient outcomes, provider efficiency, provider satisfaction, etc. This has also led to a dearth of clinically relevant EHR usage metrics consistent with inpatient provider clinical activity. Objective  The aim of our study was to validate audit-log based EHR times using observed EHR-times extracted from screen recordings of EHR usage in the inpatient setting. Methods  This study was conducted in a 36-bed pediatric intensive care unit (PICU) at Lucile Packard Children''s Hospital Stanford between June 11 and July 14, 2020. Attending physicians, fellow physicians, hospitalists, and advanced practice providers with ≥0.5 full-time equivalent (FTE) for the prior four consecutive weeks and at least one EHR session recording were included in the study. Citrix session recording player was used to retrospectively review EHR session recordings that were captured as the provider interacted with the EHR. Results  EHR use patterns varied by provider type. Audit-log based total EHR time correlated strongly with both observed total EHR time ( r  = 0.98, p  < 0.001) and observed active EHR time ( r  = 0.95, p  < 0.001). Each minute of audit-log based total EHR time corresponded to 0.95 (0.87–1.02) minutes of observed total EHR time and 0.75 (0.67–0.83) minutes of observed active EHR time. Results were similar when stratified by provider role. Conclusion  Our study found inpatient audit-log based EHR time to correlate strongly with observed EHR time among pediatric critical care providers. These findings support the use of audit-log based EHR-time as a surrogate measure for inpatient provider EHR use, providing an opportunity for researchers and other stakeholders to leverage EHR audit-log data in measuring clinical activity and tracking outcomes of workflow improvement efforts longitudinally and across provider groups.     

An Analysis of Electronic Health Record Work to Manage Asynchronous Clinical Messages among Breast Cancer Care Teams

Objective  Asynchronous messaging is an integral aspect of communication in clinical settings, but imposes additional work and potentially leads to inefficiency. The goal of this study was to describe the time spent using the electronic health record (EHR) to manage asynchronous communication to support breast cancer care coordination. Methods  We analyzed 3 years of audit logs and secure messaging logs from the EHR for care team members involved in breast cancer care at Vanderbilt University Medical Center. To evaluate trends in EHR use, we combined log data into sequences of events that occurred within 15 minutes of any other event by the same employee about the same patient. Results  Our cohort of 9,761 patients were the subject of 430,857 message threads by 7,194 employees over a 3-year period. Breast cancer care team members performed messaging actions in 37.5% of all EHR sessions, averaging 29.8 (standard deviation [SD] = 23.5) messaging sessions per day. Messaging sessions lasted an average of 1.1 (95% confidence interval: 0.99–1.24) minutes longer than nonmessaging sessions. On days when the cancer providers did not otherwise have clinical responsibilities, they still performed messaging actions in an average of 15 (SD = 11.9) sessions per day. Conclusion  At our institution, clinical messaging occurred in 35% of all EHR sessions. Clinical messaging, sometimes viewed as a supporting task of clinical work, is important to delivering and coordinating care across roles. Measuring the electronic work of asynchronous communication among care team members affords the opportunity to systematically identify opportunities to improve employee workload.     

Transformation of Electronic Health Records and Questionnaire Data to OMOP CDM: A Feasibility Study Using SG_T2DM Dataset

Background  Diabetes mellitus (DM) is an important public health concern in Singapore and places a massive burden on health care spending. Tackling chronic diseases such as DM requires innovative strategies to integrate patients'' data from diverse sources and use scientific discovery to inform clinical practice that can help better manage the disease. The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) was chosen as the framework for integrating data with disparate formats. Objective  The study aimed to evaluate the feasibility of converting Singapore based data source, comprising of electronic health records (EHR), cognitive and depression assessment questionnaire data to OMOP CDM standard. Additionally, we also validate whether our OMOP CDM instance is fit for the purpose of research by executing a simple treatment pathways study using Atlas, a graphical user interface tool to conduct analysis on OMOP CDM data as a proof of concept. Methods  We used de-identified EHR, cognitive, and depression assessment questionnaires data from a tertiary care hospital in Singapore to convert it to version 5.3.1 of OMOP CDM standard. We evaluate the OMOP CDM conversion by (1) assessing the mapping coverage (that is the percentage of source terms mapped to OMOP CDM standard); (2) local raw dataset versus CDM dataset analysis; and (3) Implementing Harmonized Intrinsic Data Quality Framework using an open-source R package called Data Quality Dashboard. Results  The content coverage of OMOP CDM vocabularies is more than 90% for clinical data, but only around 11% for questionnaire data. The comparison of characteristics between source and target data returned consistent results and our transformed data did not pass 38 (1.4%) out of 2,622 quality checks. Conclusion  Adoption of OMOP CDM at our site demonstrated that EHR data are feasible for standardization with minimal information loss, whereas challenges remain for standardizing cognitive and depression assessment questionnaire data that requires further work.     

Evaluation of Electronic Health Record-Based Suicide Risk Prediction Models on Contemporary Data

Background  Suicide risk prediction models have been developed by using information from patients'' electronic health records (EHR), but the time elapsed between model development and health system implementation is often substantial. Temporal changes in health systems and EHR coding practices necessitate the evaluation of such models in more contemporary data. Objectives  A set of published suicide risk prediction models developed by using EHR data from 2009 to 2015 across seven health systems reported c-statistics of 0.85 for suicide attempt and 0.83 to 0.86 for suicide death. Our objective was to evaluate these models'' performance with contemporary data (2014–2017) from these systems. Methods  We evaluated performance using mental health visits (6,832,439 to mental health specialty providers and 3,987,078 to general medical providers) from 2014 to 2017 made by 1,799,765 patients aged 13+ across the health systems. No visits in our evaluation were used in the previous model development. Outcomes were suicide attempt (health system records) and suicide death (state death certificates) within 90 days following a visit. We assessed calibration and computed c-statistics with 95% confidence intervals (CI) and cut-point specific estimates of sensitivity, specificity, and positive/negative predictive value. Results  Models were well calibrated; 46% of suicide attempts and 35% of suicide deaths in the mental health specialty sample were preceded by a visit (within 90 days) with a risk score in the top 5%. In the general medical sample, 53% of attempts and 35% of deaths were preceded by such a visit. Among these two samples, respectively, c-statistics were 0.862 (95% CI: 0.860–0.864) and 0.864 (95% CI: 0.860–0.869) for suicide attempt, and 0.806 (95% CI: 0.790–0.822) and 0.804 (95% CI: 0.782–0.829) for suicide death. Conclusion  Performance of the risk prediction models in this contemporary sample was similar to historical estimates for suicide attempt but modestly lower for suicide death. These published models can inform clinical practice and patient care today.     

Novel Nonproprietary Measures of Ambulatory Electronic Health Record Use Associated with Physician Work Exhaustion

Background  Accumulating evidence indicates an association between physician electronic health record (EHR) use after work hours and occupational distress including burnout. These studies are based on either physician perception of time spent in EHR through surveys which may be prone to bias or by utilizing vendor-defined EHR use measures which often rely on proprietary algorithms that may not take into account variation in physician''s schedules which may underestimate time spent on the EHR outside of scheduled clinic time. The Stanford team developed and refined a nonproprietary EHR use algorithm to track the number of hours a physician spends logged into the EHR and calculates the Clinician Logged-in Outside Clinic (CLOC) time, the number of hours spent by a physician on the EHR outside of allocated time for patient care. Objective  The objective of our study was to measure the association between CLOC metrics and validated measures of physician burnout and professional fulfillment. Methods  Physicians from adult outpatient Internal Medicine, Neurology, Dermatology, Hematology, Oncology, Rheumatology, and Endocrinology departments who logged more than 8 hours of scheduled clinic time per week and answered the annual wellness survey administered in Spring 2019 were included in the analysis. Results  We observed a statistically significant positive correlation between CLOC ratio (defined as the ratio of CLOC time to allocated time for patient care) and work exhaustion (Pearson''s r  = 0.14; p  = 0.04), but not interpersonal disengagement, burnout, or professional fulfillment. Conclusion  The CLOC metrics are potential objective EHR activity-based markers associated with physician work exhaustion. Our results suggest that the impact of time spent on EHR, while associated with exhaustion, does not appear to be a dominant factor driving the high rates of occupational burnout in physicians.     

Clinician Perceptions on the Use of Free-Text Communication Orders

Objective  The aim of this study was to investigate (1) why ordering clinicians use free-text orders to communicate medication information; (2) what risks physicians and nurses perceive when free-text orders are used for communicating medication information; and (3) how electronic health records (EHRs) could be improved to encourage the safe communication of medication information. Methods  We performed semi-structured, scenario-based interviews with eight physicians and eight nurses. Interview responses were analyzed and grouped into common themes. Results  Participants described eight reasons why clinicians use free-text medication orders, five risks relating to the use of free-text medication orders, and five recommendations for improving EHR medication-related communication. Poor usability, including reduced efficiency and limited functionality associated with structured order entry, was the primary reason clinicians used free-text orders to communicate medication information. Common risks to using free-text orders for medication communication included the increased likelihood of missing orders and the increased workload on nurses responsible for executing orders. Discussion  Clinicians'' use of free-text orders is primarily due to limitations in the current structured order entry design. To encourage the safe communication of medication information between clinicians, the EHR''s structured order entry must be redesigned to support clinicians'' cognitive and workflow needs that are currently being addressed via the use of free-text orders. Conclusion  Clinicians'' use of free-text orders as a workaround to insufficient structured order entry can create unintended patient safety risks. Thoughtful solutions designed to address these workarounds can improve the medication ordering process and the subsequent medication administration process.     

Multidisciplinary Sprint Program Achieved Specialty-Specific EHR Optimization in 20 Clinics

Objective  The objective of the study was to highlight and analyze the outcomes of software configuration requests received from Sprint, a comprehensive, clinic-centered electronic health record (EHR) optimization program. Methods  A retrospective review of 1,254 Sprint workbook requests identified (1) the responsible EHR team, (2) the clinical efficiency gained from the request, and (3) the EHR intervention conducted. Results  Requests were received from 407 clinicians and 538 staff over 31 weeks of Sprint. Sixty-nine percent of the requests were completed during the Sprint. Of all requests, 25% required net new build, 73% required technical investigation and/or solutions, and 2% of the requests were escalated to the vendor. The clinical specialty groups requested a higher percentage of items that earned them clinical review (16 vs. 10%) and documentation (29 vs. 23%) efficiencies compared with their primary care colleagues who requested slightly more order modifications (22 vs. 20%). Clinical efficiencies most commonly associated with workbook requests included documentation (28%), ordering (20%), in basket (17%), and clinical review (15%). Sprint user requests evaluated by ambulatory, hardware, security, and training teams comprised 80% of reported items. Discussion  Sprint requests were categorized as clean-up, break-fix, workflow investigation, or new build. On-site collaboration with clinical care teams permitted consensus-building, drove vetting, and iteration of EHR build, and led to goal-driven, usable workflows and EHR products. Conclusion  This program evaluation demonstrates the process by which optimization can occur and the products that result when we adhere to optimization principles in health care organizations.