Design and Pilot Implementation of an Electronic Health Record-Based System to Automatically Refer Cancer Patients to Tobacco Use Treatment.
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SUBMITTER: Jose T
PROVIDER: S-EPMC7312526 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
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Design and Pilot Implementation of an Electronic Health Record-Based System to Automatically Refer Cancer Patients to Tobacco Use Treatment.
Jose Thulasee T Ohde Joshua W JW Hays J Taylor JT Burke Michael V MV Warner David O DO
International journal of environmental research and public health 20200606 11
Continued tobacco use after cancer diagnosis is detrimental to treatment and survivorship. The current reach of evidence-based tobacco treatments in cancer patients is low. As a part of the National Cancer Institute Cancer Center Cessation Initiative, the Mayo Clinic Cancer Center designed an electronic health record (EHR, Epic<sup>©</sup>)-based process to automatically refer ambulatory oncology patients to tobacco use treatment, regardless of intent to cease tobacco use("opt out"). The referra ...[more]
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Project description:Tobacco dependence treatment for hospitalized smokers results in long-term cessation if treatment continues at least 30 days post-discharge. Health information technology may facilitate ongoing tobacco dependence treatment after hospital discharge. To describe the use and impact of a new decision support tool and order set for inpatient physicians, addressing tobacco dependence treatment for hospitalized smokers, embedded in an electronic health record (EHR). In a cluster-randomized trial, 254 physicians were randomized (1:1) to either receive or not receive the decision support tool and order set, which were embedded in the Epic (Madison, WI) EHR used at 2 hospitals in a single city. When an adult patient was admitted to a medical service, an electronic alert appeared if the patient was coded in the EHR as a smoker. For physicians randomized to the intervention, the alert linked to an order set to prescribe tobacco treatment medications and refer the patient to the state tobacco quitline. Additionally, "tobacco use disorder" was added to the patient's problem list, and an e-mail was sent to the patient's primary care provider (PCP). In the control arm, an alert fired with no screen visibility. Generalized estimating equations were used to model the data. Since August 2013, the alert has appeared for 10,939 patients (5391 intervention, 5548 control). Compared to control physicians, intervention physicians were more likely to order tobacco treatment medication (35 vs. 29%, P < 0.0001), populate the problem list with tobacco use disorder (41 vs. 2%, P < 0.0001), and make a referral to the state smokers' quitline (30 vs. 0%, P < 0.0001). In addition, intervention physicians sent an e-mail to the patient's PCP 4152 (99%) times. Designing and implementing an order set and alert for tobacco treatment in an EHR is feasible and helps physicians place more orders for tobacco treatment medication, referrals to the state smokers' quitline, and e-mails to patients' PCPs. Data on cessation outcomes are pending.www.ClinicalTrials.gov (NCT01691105).
| S-EPMC5526813 | biostudies-literature
Project description:BackgroundThe predominant implementation paradigm of electronic health record (EHR) systems in low- and middle-income countries (LMICs) relies on standalone system installations at facilities. This implementation approach exacerbates the digital divide, with facilities in areas with inadequate electrical and network infrastructure often left behind. Mobile health (mHealth) technologies have been implemented to extend the reach of digital health, but these systems largely add to the problem of siloed patient data, with few seamlessly interoperating with the EHR systems that are now scaled nationally in many LMICs. Robust mHealth applications that effectively extend EHR systems are needed to improve access, improve quality of care, and ameliorate the digital divide.ObjectiveWe report on the development and scaled implementation of mUzima, an mHealth extension of the most broadly deployed EHR system in LMICs (OpenMRS).MethodsThe "Guidelines for reporting of health interventions using mobile phones: mobile (mHealth) evidence reporting assessment (mERA)" checklist was employed to report on the mUzima application. The World Health Organization (WHO) Principles for Digital Development framework was used as a secondary reference framework. Details of mUzima's architecture, core features, functionalities, and its implementation status are provided to highlight elements that can be adapted in other systems.ResultsmUzima is an open-source, highly configurable Android application with robust features including offline management, deduplication, relationship management, security, cohort management, and error resolution, among many others. mUzima allows providers with lower-end Android smartphones (version 4.4 and above) who work remotely to access historical patient data, collect new data, view media, leverage decision support, conduct store-and-forward teleconsultation, and geolocate clients. The application is supported by an active community of developers and users, with feature priorities vetted by the community. mUzima has been implemented nationally in Kenya, is widely used in Rwanda, and is gaining scale in Uganda and Mozambique. It is disease-agnostic, with current use cases in HIV, cancer, chronic disease, and COVID-19 management, among other conditions. mUzima meets all WHO's Principles of Digital Development, and its scaled implementation success has led to its recognition as a digital global public good and its listing in the WHO Digital Health Atlas.ConclusionsGreater emphasis should be placed on mHealth applications that robustly extend reach of EHR systems within resource-limited settings, as opposed to siloed mHealth applications. This is particularly important given that health information exchange infrastructure is yet to mature in many LMICs. The mUzima application demonstrates how this can be done at scale, as evidenced by its adoption across multiple countries and for numerous care domains.
| S-EPMC8715359 | biostudies-literature
Project description:The hospital discharge summary is the primary method used to communicate a patient's plan of care to the next provider(s). Despite the existence of regulations and guidelines outlining the optimal content for the discharge summary and its importance in facilitating an effective transition to posthospital care, incomplete discharge summaries remain a common problem that may contribute to poor posthospital outcomes. Electronic health records (EHRs) are regularly used as a platform on which standardization of content and format can be implemented. The feasibility of designing and implementing a standardized discharge summary hospitalwide using an EHR was examined-to the authors' knowledge, for the first time.This large-scale project at the University of Wisconsin Hospital and Clinics was led by a task force that had been assembled to develop best practices for EHR notes. The evidence-based Replicating Effective Programs (REP) model was employed to guide the development and implementation during the project. REP outlines four stages in clinical health service intervention implementation: preconditions, preimplementation, implementation, and maintenance.At 18 months postimplementation, 90% of all hospital discharge summaries were written using the standardized format. Hospital providers found the template helpful and easy to use, and recipient providers perceived an improvement in the quality of discharge summaries compared to those previously sent from the hospital.Discharge summaries can be standardized and implemented hospitalwide with both author and recipient provider satisfaction, particularly if evidence-based implementation strategies are employed. The use of EHR tools to guide clinicians in writing comprehensive discharge summaries holds promise in improving the existing deficits in communication at transitions of care.
| S-EPMC5367268 | biostudies-literature
Project description:IntroductionDespite many innovations in information technology, many clinics still rely on paper-based medical records. Critics, however, claim that they are hard to read, because of illegible handwriting, and uncomfortable to use. Moreover, a chronological overview is not always easily possible, content can be destroyed or get lost. There is an overall opinion that electronic medical records (EMRs) should solve these problems and improve physicians' efficiency, patients' safety and reduce the overall costs in practice. However, to date, the evidence supporting this view is sparse.Methods and analysisIn this protocol, we describe a study exploring differences in speed and accuracy when searching clinical information using the paper-based patient record or the Elektronische DateneRfassung (EDeR). Designed as a randomised vignette study, we hypothesise that the EDeR increases efficiency, that is, reduces time on reading the patient history and looking for relevant examination results, helps finding mistakes and missing information quicker and more reliably. In exploratory analyses, we aim at exploring factors associated with a higher performance.Ethics and disseminationThe ethics committee of the Canton Lucerne, Switzerland, approved this study. We presume that the implementation of the EMR software EDeR will have a positive impact on the efficiency of the doctors, which will result in an increase of consultations per day. We believe that the results of our study will provide a valid basis to quantify the added value of an EMR system in an ophthalmological environment.
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Project description:BackgroundElectronic Health Records (EHRs) are now widely used to create a single, shared, and reliable source of patient data throughout healthcare organizations. However, health professionals continue to experience mismatches between their working practices and what the EHR allows or directs them to do. Health professionals adopt working practices other than those imposed by the EHR to overcome such mismatches, known as workarounds. Our study aims to inductively develop a typology of enduring EHR workarounds and explore their consequences by answering the question: What types of EHR workarounds persist, and what are the user-perceived consequences?MethodsThis single case study was conducted within the Internal Medicine department of a Dutch hospital that had implemented an organization-wide, commercial EHR system over two years ago. Data were collected through observations of six EHR users (see Additional file 1, observation scheme) and 17 semi-structured interviews with physicians, nurses, administrators, and EHR support staff members. Documents were analysed to contextualize these data (see Additional file 2, interview protocol).ResultsThrough a qualitative analysis, 11 workarounds were identified, predominantly performed by physicians. These workarounds are categorized into three types either performed while working with the system (in-system workflow sequence workarounds and in-system data entry workarounds) or bypassing the system (out-system workarounds). While these workarounds seem to offer short-term benefits for the performer, they often create threats for the user, the patient, the overall healthcare organization, and the system.ConclusionThis study increases our understanding of the enduring phenomenon of working around Electronic Health Records by presenting a typology of those workarounds that persist after adoption and by reflecting on the user-perceived risks and benefits. The typology helps EHR users and their managers to identify enduring types of workarounds and differentiate between the harmful and less harmful ones. This distinction can inform their decisions to discourage or obviate the need for certain workarounds, while legitimating others.
| S-EPMC8186102 | biostudies-literature
Project description:BackgroundDetection, monitoring and treatment of adverse drug reactions (ADRs) are paramount to patient safety. The use of a comprehensive electronic health record (EHR) system has the potential to address inadequacies in ADR documentation and to facilitate ADR reporting to health agencies. However, effective methods to maintain the quality of documented ADRs within an EHR have not been well studied.ObjectiveTo evaluate the accuracy and effectiveness of ADR documentation transfer throughout the implementation of a comprehensive EHR system.MethodsRetrospective analysis of ADR documentation at a tertiary care pediatric hospital between January 2013 and June 2014. ADRs documented in the newly implemented ambulatory EHR, pharmacy system and hybrid health record system were extracted. Documentation inconsistencies and processes for managing ADR documentation within the EHR were reviewed.ResultsA total of 115 patients with 260 unique ADRs were identified. Only 155 (60 %) of the identified ADRs were found in the ambulatory EHR system. The remaining 105 ADRs (40 %) were missing from the EHR when it was compared with the other systems. Seventy-two patients (63 %) returned for a follow-up visit, and each had their ADR documentation reviewed in the ambulatory EHR. Following the visit, 44 % of these ambulatory EHR records still included incorrect information.ConclusionsWe identified discrepancies in ADR documentation within hospital systems, which need to be addressed as healthcare institutions transition to EHRs. Processes related to the transfer of ADR information into the EHR should be clearly defined. To improve the quality of ADR documentation, steps to force complete and continual ADR verification should be introduced at early stages of implementation of a new EHR, and all responsible providers should play a role.
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Project description:ObjectiveTobacco use is the leading cause of preventable morbidity and mortality in the United States. Quitlines are effective telephone-based tobacco cessation services but are underutilized. The goal of this project was to describe current clinical workflows for Quitline referral and design an optimal electronic health record (EHR)-based workflow for Ask-Advice-Connect (AAC), an evidence-based intervention to increase Quitline referrals.Materials and methodsTen Community Health Center systems (CHC), which use three different EHRs, participated in this study. Methods included: 9 group discussions with CHC leaders; 33 observations/interviews of clinical teams' workflow; surveys with 57 clinical staff; and assessment of the EHR ecosystem in each CHC. Data across these methods were integrated and coded according to the Fit between Individual, Task, Technology and Environment (FITTE) framework. The current and optimal workflow were notated using Business Process Modelling Notation. We compared the requirements of the optimal workflow with EHR capabilities.ResultsCurrent workflows are inefficient in data collection, variable in who, how, and when tobacco cessation advice and referral are enacted, and lack communication between referring clinics and the Quitline. In the optimal workflow, medical assistants deliver a standardized AAC intervention during the visit intake. Referrals are submitted electronically, and there is bidirectional communication between the clinic and Quitline. We implemented AAC within all three EHRs; however, deviations from the optimal workflow were necessary.ConclusionCurrent workflows for Quitline referral are inefficient and ineffective. We propose an optimal workflow and discuss improvements in EHR capabilities that would improve the implementation of AAC.
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Project description:BackgroundThe Meaningful Use (MU) program has increased the national emphasis on electronic measurement of hospital quality.ObjectiveTo evaluate stroke MU and one VHA stroke electronic clinical quality measure (eCQM) in national VHA data and determine sources of error in using centralized electronic health record (EHR) data.DesignOur study is a retrospective cross-sectional study of stroke quality measure eCQMs vs. chart review in a national EHR. We developed local SQL algorithms to generate the eCQMs, then modified them to run on VHA Central Data Warehouse (CDW) data. eCQM results were generated from CDW data in 2130 ischemic stroke admissions in 11 VHA hospitals. Local and CDW results were compared to chart review.Main measuresWe calculated the raw proportion of matching cases, sensitivity/specificity, and positive/negative predictive values (PPV/NPV) for the numerators and denominators of each eCQM. To assess overall agreement for each eCQM, we calculated a weighted kappa and prevalence-adjusted bias-adjusted kappa statistic for a three-level outcome: ineligible, eligible-passed, or eligible-failed.Key resultsIn five eCQMs, the proportion of matched cases between CDW and chart ranged from 95.4 %-99.7 % (denominators) and 87.7 %-97.9 % (numerators). PPVs tended to be higher (range 96.8 %-100 % in CDW) with NPVs less stable and lower. Prevalence-adjusted bias-adjusted kappas for overall agreement ranged from 0.73-0.95. Common errors included difficulty in identifying: (1) mechanical VTE prophylaxis devices, (2) hospice and other specific discharge disposition, and (3) contraindications to receiving care processes.ConclusionsStroke MU indicators can be relatively accurately generated from existing EHR systems (nearly 90 % match to chart review), but accuracy decreases slightly in central compared to local data sources. To improve stroke MU measure accuracy, EHRs should include standardized data elements for devices, discharge disposition (including hospice and comfort care status), and recording contraindications.
| S-EPMC4803676 | biostudies-literature
Project description:BackgroundElectronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research.ObjectiveThe objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences.MethodsWe used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results.ResultsWe present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized.ConclusionsThe Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.
| S-EPMC10757236 | biostudies-literature
Project description:OBJECTIVE: To describe physicians' patterns of using an Electronic Medical Record (EMR) system; to reveal the underlying cognitive elements involved in EMR use, possible resulting errors, and influences on patient-doctor communication; to gain insight into the role of expertise in incorporating EMRs into clinical practice in general and communicative behavior in particular. DESIGN: Cognitive task analysis using semi-structured interviews and field observations. PARTICIPANTS: Twenty-five primary care physicians from the northern district of the largest health maintenance organization (HMO) in Israel. RESULTS: The comprehensiveness, organization, and readability of data in the EMR system reduced physicians' need to recall information from memory and the difficulty of reading handwriting. Physicians perceived EMR use as reducing the cognitive load associated with clinical tasks. Automaticity of EMR use contributed to efficiency, but sometimes resulted in errors, such as the selection of incorrect medication or the input of data into the wrong patient's chart. EMR use interfered with patient-doctor communication. The main strategy for overcoming this problem involved separating EMR use from time spent communicating with patients. Computer mastery and enhanced physicians' communication skills also helped. CONCLUSIONS: There is a fine balance between the benefits and risks of EMR use. Automaticity, especially in combination with interruptions, emerged as the main cognitive factor contributing to errors. EMR use had a negative influence on communication, a problem that can be partially addressed by improving the spatial organization of physicians' offices and by enhancing physicians' computer and communication skills.
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