Optimizing handover for family medicine outpatients using an electronic medical record-integrated tool.
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ABSTRACT:
SUBMITTER: Najarali Z
PROVIDER: S-EPMC8324165 | biostudies-literature | 2021 Apr
REPOSITORIES: biostudies-literature
Publications
Optimizing handover for family medicine outpatients using an electronic medical record-integrated tool.
Najarali Zainab Z Mah Heidi H Toubassi Diana D
Canadian family physician Medecin de famille canadien 20210401 4
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Project description:BackgroundThe introduction of the electronic medical record (EMR) has led to new communication skills that need to be taught and assessed. There is scarce literature on validated instruments measuring electronic-specific communication skills. The aim is to develop an assessment checklist that assesses the general and EMR-specific communication skills and evaluates their content validity and reliability.MethodsUsing the SEGUE theoretical framework for communication skills, the assessment checklist items were developed by the Communication Skills Working Group (CSWG) at the family medicine department using a literature review about the positive and negative aspects of EMR use on physician-patient communication. A group of faculty members rated real resident-patient encounters on two occasions, three weeks apart. Patients were asked to fill out the Communication Assessment Tool (CAT) at the end of the encounter.ResultsA total of 8 residents agreed to participate in the research, with 21 clinical encounters recorded. The average total score was 65.2 ± 6.9 and 48.1 ± 9.5 for the developed scale and the CAT scale, respectively. The scale reliability was good, with a Cronbach alpha of 0.694. The test-retest reliability was 0.873, p < 0.0001. For the total score on the developed checklist, the intraclass correlation coefficient between raters (ICC) was 0.429 [0.030,0.665], p-value of 0.019. The level of agreement between any two raters on the cumulative score of the 5 subsections ranged from 0.506 (interpersonal skills) to 0.969 (end encounter).ConclusionThis checklist is a reliable and valid instrument that combines basic and EMR-related communication skills.
| S-EPMC10103454 | biostudies-literature
Project description:Along with the increasing availability of electronic medical record (EMR) data, phenome-wide association studies (PheWAS) and phenome-disease association studies (PheDAS) have become a prominent, first-line method of analysis for uncovering the secrets of EMR. Despite this recent growth, there is a lack of approachable software tools for conducting these analyses on large-scale EMR cohorts. In this article, we introduce pyPheWAS, an open-source python package for conducting PheDAS and related analyses. This toolkit includes 1) data preparation, such as cohort censoring and age-matching; 2) traditional PheDAS analysis of ICD-9 and ICD-10 billing codes; 3) PheDAS analysis applied to a novel EMR phenotype mapping: current procedural terminology (CPT) codes; and 4) novelty analysis of significant disease-phenotype associations found through PheDAS. The pyPheWAS toolkit is approachable and comprehensive, encapsulating data prep through result visualization all within a simple command-line interface. The toolkit is designed for the ever-growing scale of available EMR data, with the ability to analyze cohorts of 100,000 + patients in less than 2 h. Through a case study of Down Syndrome and other intellectual developmental disabilities, we demonstrate the ability of pyPheWAS to discover both known and potentially novel disease-phenotype associations across different experiment designs and disease groups. The software and user documentation are available in open source at https://github.com/MASILab/pyPheWAS .
| S-EPMC9250547 | biostudies-literature
Project description:A prospective quasi-experimental before-and-after study of an electronic medical record-anchored intervention of embedded education on appropriate urine culture indications and indication selection reduced the number of urine cultures ordered for catheterized patients at an academic medical center. This intervention could be a component of CAUTI-reduction bundles. Infect Control Hosp Epidemiol 2017;38:486-488.
| S-EPMC7368995 | biostudies-literature
Project description:BackgroundCork University Hospital, Ireland's largest teaching hospital, faced challenges in maintaining consistent handover processes in its Acute Mental Health Unit (AMHU). Prior to 2019, handovers relied on informal methods, risking information loss and compromising patient care. This quality improvement (QI) initiative aimed to standardise handover practices using an electronic tool integrated with the ISBAR communication protocol.ObjectivesThe project aimed to ensure accurate clinical information recording, improve patient care and safety, centralise handover material, enhance clinical transparency and accountability, and measure handover quality using the electronic tool.MethodsUsing a Plan-Do-Study-Act (PDSA) model, the initiative began with a critical incident in July 2020, prompting the creation and piloting of an electronic 'handover tool' aligned with ISBAR. Subsequent PDSA cycles included mandatory policy implementation and educational interventions to reinforce tool usage and adherence to communication standards.ResultsThe electronic handover tool improved handover practices, with increased compliance to recommended criteria and enhanced tool utilisation. Notable improvements followed targeted educational interventions, leading to more comprehensive and standardised handover entries. These improvements enhanced communication and information transfer among NCHDs, contributing to better continuity of care and patient safety.ConclusionsThe QI initiative successfully standardised handover processes and improved communication among NCHDs in the AMHU. While improvements were observed, ongoing efforts are needed to address challenges and sustain effectiveness. Continuous training, feedback mechanisms and further refinement of the handover tool are essential for long-term success. Future directions include exploring additional technological solutions and reinforcing a culture of effective communication.
| S-EPMC11751932 | biostudies-literature
Project description:PurposeThe Electronic Medical Record Search Engine (EMERSE) is a software tool built to aid research spanning cohort discovery, population health, and data abstraction for clinical trials. EMERSE is now live at three academic medical centers, with additional sites currently working on implementation. In this report, we describe how EMERSE has been used to support cancer research based on a variety of metrics.MethodsWe identified peer-reviewed publications that used EMERSE through online searches as well as through direct e-mails to users based on audit logs. These logs were also used to summarize use at each of the three sites. Search terms for two of the sites were characterized using the natural language processing tool MetaMap to determine to which semantic types the terms could be mapped.ResultsWe identified a total of 326 peer-reviewed publications that used EMERSE through August 2019, although this is likely an underestimation of the true total based on the use log analysis. Oncology-related research comprised nearly one third (n = 105; 32.2%) of all research output. The use logs showed that EMERSE had been used by multiple people at each site (nearly 3,500 across all three) who had collectively logged into the system > 100,000 times. Many user-entered search queries could not be mapped to a semantic type, but the most common semantic type for terms that did match was "disease or syndrome," followed by "pharmacologic substance."ConclusionEMERSE has been shown to be a valuable tool for supporting cancer research. It has been successfully deployed at other sites, despite some implementation challenges unique to each deployment environment.
| S-EPMC7265780 | biostudies-literature
Project description: Not available
| S-EPMC9315947 | biostudies-literature
Project description:Family health history (FHH) screening plays a key role in disease risk identification and tailored disease prevention strategies. Primary care physicians (PCPs) are in a frontline position to provide personalized medicine recommendations identified through FHH screening; however, adoption of FHH screening tools has been slow and inconsistent in practice. Information is also lacking on PCP facilitators and barriers of utilizing family history tools with clinical decision support (CDS) embedded in the electronic health record (EHR). This study reports on PCPs' initial experiences with the Genetic and Wellness Assessment (GWA), a patient-administered FHH screening tool utilizing the EHR and CDS. Semi-structured interviews were conducted with 24 PCPs who use the GWA in a network of community-based practices. Four main themes regarding GWA implementation emerged: benefits to clinical care, challenges in practice, CDS-specific issues, and physician-recommended improvements. Sub-themes included value in improving patient access to genetic services, inadequate time to discuss GWA recommendations, lack of patient follow-through with recommendations, and alert fatigue. While PCPs valued the GWA's clinical utility, a number of challenges were identified in the administration and use of the GWA in practice. Based on participants' recommendations, iterative changes have been made to the GWA and workflow to increase efficiency, upgrade the CDS process, and provide additional education to PCPs and patients. Future studies are needed to assess a diverse sample of physicians' and patients' perspectives on the utility of FHH screening utilizing EHR-based genomics recommendations.
| S-EPMC7295926 | biostudies-literature
Project description:To characterize patterns of electronic medical record (EMR) use at pediatric primary care acute visits.Direct observational study of 529 acute visits with 27 experienced pediatric clinician users.For each 20 s interval and at each stage of the visit according to the Davis Observation Code, we recorded whether the physician was communicating with the family only, using the computer while communicating, or using the computer without communication. Regression models assessed the impact of clinician, patient and visit characteristics on overall visit length, time spent interacting with families, and time spent using the computer while interacting.The mean overall visit length was 11:30 (min:sec) with 9:06 spent in the exam room. Clinicians used the EMR during 27% of exam room time and at all stages of the visit (interacting, chatting, and building rapport; history taking; formulation of the diagnosis and treatment plan; and discussing prevention) except the physical exam. Communication with the family accompanied 70% of EMR use. In regression models, computer documentation outside the exam room was associated with visits that were 11% longer (p=0.001), and female clinicians spent more time using the computer while communicating (p=0.003).The 12 study practices shared one EMR.Among pediatric clinicians with EMR experience, conversation accompanies most EMR use. Our results suggest that efforts to improve EMR usability and clinician EMR training should focus on use in the context of doctor-patient communication. Further study of the impact of documentation inside versus outside the exam room on productivity is warranted.
| S-EPMC3005866 | biostudies-other
Project description:This column describes the potential of an enhanced electronic medical record (EMR) to advance best practices by displaying patient history, measuring progress, and facilitating clinical research. To create a graphical, single-page display of patient history, the authors examined data in the Minneapolis Department of Veterans Affairs EMR system, including 1.8 million encounters for 50,000 mental health patients. The prototype dashboard presents information on a patient's current and past providers, diagnoses, therapeutic interventions, prescriptions, dosages, and outcomes. To provide needed outcome data to monitor patient progress, the authors tested two questions with 212 patients. Patient and clinician responses to the questions provide reliable and clinically useful data that can be used in the EMR to track patient change over time. Use of EMRs can bridge gaps between science and practice to inform diagnosis and treatment decisions and permit more accurate prognoses.
| S-EPMC5770979 | biostudies-literature
Project description:IntroductionFamily health history can be a valuable indicator of risk to develop certain cancers. Unfortunately, patient self-reported family history often contains inaccuracies, which might change recommendations for cancer screening. We endeavored to understand the difference between a patient's self-reported family history and their electronic medical record (EMR) family history. One aim of this study was to determine if family history information contained in the EMR differs from patient-reported family history collected using a focused questionnaire.MethodsWe created the Hereditary Cancer Questionnaire (HCQ) based on current guidelines and distributed to 314 patients in the Department of Family Medicine waiting room June 20 to August 1, 2018. The survey queried patients about specific cancers within their biological family to assess their risk of an inherited cancer syndrome. We used the questionnaire responses as a baseline when comparing family histories in the medical record.ResultsAgreement between the EMR and the questionnaire data decreased as the patients' risk for familial cancer increased. Meaning that the more significant a patient's family cancer history, the less likely it was to be recorded accurately and consistently in the EMR. Patients with low-risk levels, or fewer instances of cancer in the family, had more consistencies between the EMR and the questionnaire.ConclusionsGiven that physicians often make recommendations on incomplete information that is in the EMR, patients might not receive individualized preventive care based on a more complete family cancer history. This is especially true for individuals with more complicated and significant family history of cancer. An improved method of collecting family history, including increasing patient engagement, may help to decrease this disparity.
| S-EPMC8796064 | biostudies-literature