Dataset Information

Remote symptom monitoring integrated into electronic health records: A systematic review.

ABSTRACT: OBJECTIVE:People with long-term conditions require serial clinical assessments. Digital patient-reported symptoms collected between visits can inform these, especially if integrated into electronic health records (EHRs) and clinical workflows. This systematic review identified and summarized EHR-integrated systems to remotely collect patient-reported symptoms and examined their anticipated and realized benefits in long-term conditions. MATERIALS AND METHODS:We searched Medline, Web of Science, and Embase. Inclusion criteria were symptom reporting systems in adults with long-term conditions; data integrated into the EHR; data collection outside of clinic; data used in clinical care. We synthesized data thematically. Benefits were assessed against a list of outcome indicators. We critically appraised studies using the Mixed Methods Appraisal Tool. RESULTS:We included 12 studies representing 10 systems. Seven were in oncology. Systems were technically and functionally heterogeneous, with the majority being fully integrated (data viewable in the EHR). Half of the systems enabled regular symptom tracking between visits. We identified 3 symptom report-guided clinical workflows: Consultation-only (data used during consultation, n?=?5), alert-based (real-time alerts for providers, n?=?4) and patient-initiated visits (n?=?1). Few author-described anticipated benefits, primarily to improve communication and resultant health outcomes, were realized based on the study results, and were only supported by evidence from early-stage qualitative studies. Studies were primarily feasibility and pilot studies of acceptable quality. DISCUSSION AND CONCLUSIONS:EHR-integrated remote symptom monitoring is possible, but there are few published efforts to inform development of these systems. Currently there is limited evidence that this improves care and outcomes, warranting future robust, quantitative studies of efficacy and effectiveness.

SUBMITTER: Gandrup J

PROVIDER: S-EPMC7671621 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Remote symptom monitoring integrated into electronic health records: A systematic review.

Gandrup Julie J Ali Syed Mustafa SM McBeth John J van der Veer Sabine N SN Dixon William G WG

Journal of the American Medical Informatics Association : JAMIA 20201101 11

<h4>Objective</h4>People with long-term conditions require serial clinical assessments. Digital patient-reported symptoms collected between visits can inform these, especially if integrated into electronic health records (EHRs) and clinical workflows. This systematic review identified and summarized EHR-integrated systems to remotely collect patient-reported symptoms and examined their anticipated and realized benefits in long-term conditions.<h4>Materials and methods</h4>We searched Medline, We ...[more]

PMID: 32968785

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Project description:BackgroundAs the availability of interoperable electronic health records (iEHRs) or health information exchanges (HIEs) continues to increase, there is greater need and opportunity to assess the current evidence base on what works and what does not regarding the adoption, use, and impact of iEHRs.ObjectiveThe purpose of this project is to assess the international evidence base on the adoption, use, and impact of iEHRs.MethodsWe conducted a systematic review, searching multiple databases-MEDLINE, Embase, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL)-with supplemental searches conducted in Google Scholar and grey literature sources (ie, Google, Grey Literature Report, and OpenGrey). All searches were conducted in January and February 2017. Articles were eligible for inclusion if they were published in English, were published from 2006 to 2017, and were either an original research study or a literature review. In order to be included, articles needed to focus on iEHRs and HIEs across multiple health care settings, as well as on the impact and effectiveness of iEHR adoption and use.ResultsWe included 130 articles in the synthesis (113 primary studies, 86.9%; 17 reviews, 13.1%), with the majority focused on the United States (88/130, 67.7%). The primary studies focused on a wide range of health care settings; the three most prevalent settings studied included acute care (59/113, 52.2%), primary care (44/113, 38.9%), and emergency departments (34/113, 30.1%). We identified 29 distinct measurement items in the 113 primary studies that were linked to 522 specific measurement outcomes. Productivity and quality were the two evaluation dimensions that received the most attention, accounting for 14 of 29 (48%) measurement items and 306 of 522 (58.6%) measurement outcomes identified. Overall, the majority of the 522 measurement outcomes were positive (298/522, 57.1%). We also identified 17 reviews on iEHR use and impact, 6 (35%) that focused on barriers and facilitators to adoption and implementation and 11 (65%) that focused on benefits and impacts, with the more recent reviews finding little generalizable evidence of benefit and impact.ConclusionsThis review captures the status of an evolving and active field focused on the use and impact of iEHRs. While the overall findings suggest many positive impacts, the quality of the primary studies were not evaluated systematically. When broken down by specific measurement item, the results directed attention both to measurement outcomes that were consistently positive and others that were mostly negative or equivocal.

Project description:Long-term care (LTC) facilities are an important part of the health care industry, providing care to the fastest-growing group of the population. However, the adoption of electronic health records (EHRs) in LTC facilities lags behind other areas of the health care industry. One of the reasons for the lack of widespread adoption in the United States is that LTC facilities are not eligible for incentives under the Meaningful Use program. Implementation of an EHR system in an LTC facility can potentially enhance the quality of care, provided it is appropriately implemented, used, and maintained. Unfortunately, the lag in adoption of the EHR in LTC creates a paucity of literature on the benefits of EHR implementation in LTC facilities.The objective of this systematic review was to identify the potential benefits of implementing an EHR system in LTC facilities. The study also aims to identify the common conditions and EHR features that received favorable remarks from providers and the discrepancies that needed improvement to build up momentum across LTC settings in adopting this technology.The authors conducted a systematic search of PubMed, Cumulative Index of Nursing and Allied Health (CINAHL), and MEDLINE databases. Papers were analyzed by multiple referees to filter out studies not germane to our research objective. A final sample of 28 papers was selected to be included in the systematic review.Results of this systematic review conclude that EHRs show significant improvement in the management of documentation in LTC facilities and enhanced quality outcomes. Approximately 43% (12/28) of the papers reported a mixed impact of EHRs on the management of documentation, and 33% (9/28) of papers reported positive quality outcomes using EHRs. Surprisingly, very few papers demonstrated an impact on patient satisfaction, physician satisfaction, the length of stay, and productivity using EHRs.Overall, implementation of EHRs has been found to be effective in the few LTC facilities that have implemented them. Implementation of EHRs in LTC facilities caused improved management of clinical documentation that enabled better decision making.

Project description:ObjectivesThe objective of this study was to assess the impact of electronic health records (EHRs) on health outcomes and care of displaced people with chronic health conditions and determine barriers and facilitators to EHR implementation in displaced populations.DesignA systematic review protocol was developed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Systematic Reviews.Data sourcesMEDLINE, Embase, PsycINFO, CINAHL, Health Technology Assessment, Epub Ahead of Print, In-Process and Other Non-Indexed Citations, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews was searched from inception to 12 April 2021.Eligibility criteria for selected studiesInclusion criteria were original research articles, case reports and descriptions of EHR implementation in populations of displaced people, refugees or asylum seekers with related chronic diseases. Grey literature, reviews and research articles unrelated to chronic diseases or the care of refugees or asylum populations were excluded. Studies were assessed for risk of bias using a modified Cochrane, Newcastle-Ottawa and Joanna Briggs Institute tools.Data extraction and synthesisTwo reviewers independently extracted data from each study using Covidence. Due to heterogeneity across study design and specific outcomes, a meta-analysis was not possible. An inductive thematic analysis was conducted using NVivo V.12 (QSR International, Melbourne, Australia). An inductive analysis was used in order to uncover patterns and themes in the experiences, general outcomes and perceptions of EHR implementation.ResultsA total of 32 studies across nine countries were included: 14 in refugee camps/settlements and 18 in asylum countries. Our analysis suggested that EHRs improve health outcomes for chronic diseases by increasing provider adherence to guidelines or treatment algorithms, monitoring of disease indicators, patient counselling and patient adherence. In asylum countries, EHRs resource allocation to direct clinical care and public health services, as well as screening efforts. EHR implementation was facilitated by their adaptability and ability to integrate into management systems. However, barriers to EHR development, deployment and data analysis were identified in refugee settings.ConclusionOur results suggest that well-designed and integrated EHRs can be a powerful tool to improve healthcare systems and chronic disease outcomes in refugee settings. However, attention should be paid to the common barriers and facilitating actions that we have identified such as utilising a user-centred design. By implementing adaptable EHR solutions, health systems can be strengthened, providers better supported and the health of refugees improved.

Project description:BACKGROUND:Adverse events in health care entail substantial burdens to health care systems, institutions, and patients. Retrospective trigger tools are often manually applied to detect AEs, although automated approaches using electronic health records may offer real-time adverse event detection, allowing timely corrective interventions. OBJECTIVE:The aim of this systematic review was to describe current study methods and challenges regarding the use of automatic trigger tool-based adverse event detection methods in electronic health records. In addition, we aimed to appraise the applied studies' designs and to synthesize estimates of adverse event prevalence and diagnostic test accuracy of automatic detection methods using manual trigger tool as a reference standard. METHODS:PubMed, EMBASE, CINAHL, and the Cochrane Library were queried. We included observational studies, applying trigger tools in acute care settings, and excluded studies using nonhospital and outpatient settings. Eligible articles were divided into diagnostic test accuracy studies and prevalence studies. We derived the study prevalence and estimates for the positive predictive value. We assessed bias risks and applicability concerns using Quality Assessment tool for Diagnostic Accuracy Studies-2 (QUADAS-2) for diagnostic test accuracy studies and an in-house developed tool for prevalence studies. RESULTS:A total of 11 studies met all criteria: 2 concerned diagnostic test accuracy and 9 prevalence. We judged several studies to be at high bias risks for their automated detection method, definition of outcomes, and type of statistical analyses. Across all the 11 studies, adverse event prevalence ranged from 0% to 17.9%, with a median of 0.8%. The positive predictive value of all triggers to detect adverse events ranged from 0% to 100% across studies, with a median of 40%. Some triggers had wide ranging positive predictive value values: (1) in 6 studies, hypoglycemia had a positive predictive value ranging from 15.8% to 60%; (2) in 5 studies, naloxone had a positive predictive value ranging from 20% to 91%; (3) in 4 studies, flumazenil had a positive predictive value ranging from 38.9% to 83.3%; and (4) in 4 studies, protamine had a positive predictive value ranging from 0% to 60%. We were unable to determine the adverse event prevalence, positive predictive value, preventability, and severity in 40.4%, 10.5%, 71.1%, and 68.4% of the studies, respectively. These studies did not report the overall number of records analyzed, triggers, or adverse events; or the studies did not conduct the analysis. CONCLUSIONS:We observed broad interstudy variation in reported adverse event prevalence and positive predictive value. The lack of sufficiently described methods led to difficulties regarding interpretation. To improve quality, we see the need for a set of recommendations to endorse optimal use of research designs and adequate reporting of future adverse event detection studies.

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Remote symptom monitoring integrated into electronic health records: A systematic review.

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Remote symptom monitoring integrated into electronic health records: A systematic review.

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