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

2020 ◽  
Vol 27 (11) ◽  
pp. 1752-1763
Author(s):  
Julie Gandrup ◽  
Syed Mustafa Ali ◽  
John McBeth ◽  
Sabine N van der Veer ◽  
William G Dixon
Keyword(s):  
Systematic Review ◽  
Electronic Health Records ◽  
Clinical Care ◽  
Long Term Conditions ◽  
Health Records ◽  
Symptom Monitoring ◽  
Study Results ◽  
Patient Reported ◽  
Electronic Health

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.

scholarly journals Impact of Electronic Health Records on Long-Term Care Facilities: Systematic Review

2017 ◽  
Vol 5 (3) ◽  
pp. e35 ◽  
Author(s):  
Clemens Scott Kruse ◽  
Michael Mileski ◽  
Alekhya Ganta Vijaykumar ◽  
Sneha Vishnampet Viswanathan ◽  
Ujwala Suskandla ◽  
...  
Keyword(s):  
Systematic Review ◽  
Electronic Health Records ◽  
Long Term Care ◽  
Term Care ◽  
Health Records ◽  
Care Facilities ◽  
Electronic Health

scholarly journals Challenges in defining Long COVID: Striking differences across literature, Electronic Health Records, and patient-reported information

2021 ◽  
Author(s):  
Halie M. Rando ◽  
Tellen D. Bennett ◽  
James Brian Byrd ◽  
Carolyn Bramante ◽  
Tiffany J. Callahan ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Multiple Organ ◽  
Health Records ◽  
Health Crisis ◽  
Organ Systems ◽  
Wide Range ◽  
Patient Reported ◽  
Electronic Health ◽  
Novel Coronavirus

Since late 2019, the novel coronavirus SARS-CoV-2 has introduced a wide array of health challenges globally. In addition to a complex acute presentation that can affect multiple organ systems, increasing evidence points to long-term sequelae being common and impactful. As the worldwide scientific community forges ahead with efforts to characterize a wide range of outcomes associated with SARS-CoV-2 infection, the proliferation of available data has made it clear that formal definitions are needed in order to design robust and consistent studies of Long COVID that consistently capture variation in long-term outcomes. In the present study, we investigate the definitions used in the literature published to date and compare them against data available from electronic health records and patient-reported information collected via surveys. Long COVID holds the potential to produce a second public health crisis on the heels of the pandemic. Proactive efforts to identify the characteristics of this heterogeneous condition are imperative for a rigorous scientific effort to investigate and mitigate this threat.

scholarly journals AB1154 EHR-INTEGRATED PATIENT-GENERATED HEALTH DATA FOR SYMPTOM MONITORING IN LONG-TERM CONDITIONS: A SYSTEMATIC REVIEW

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1867.2-1868
Author(s):  
J. De Fonss Gandrup ◽  
S. Mustafa Ali ◽  
S. Van der Veer ◽  
J. Mcbeth ◽  
W. Dixon
Keyword(s):  
Systematic Review ◽  
Patient Management ◽  
Clinical Care ◽  
Health Data ◽  
Symptom Reporting ◽  
Long Term Conditions ◽  
Outcome Indicators ◽  
Symptom Monitoring ◽  
The Impact

Background:Patients with long-term conditions (LTCs), including many RMDs, often require continuous management of care. Patient-generated health data (PGHD) collected between visits could inform ongoing care management and provide important insights into patient health and well-being. There is increasing interest in integrating PGHD in electronic health records (EHRs). However, integration is still largely aspirational with limited evidence of successful systems.Objectives:To map the landscape of EHR-integrated remote symptom monitoring systems in the field of LTCs. The objectives were to 1) characterise state of the art systems, 2) describe their clinical use, and 3) outline anticipated and realized benefits for clinical practice.Methods:A systematic search was conducted in three electronic databases up until November 2019. Titles and abstracts were independently screened by two reviewers. One reviewer screened full-text articles, identified those relevant for review and extracted data. Inclusion criteria included 1) symptom reporting systems in adult patients suffering a LTC, 2) integration of data into the EHR, 3) symptom data collected remotely, 4) evidence of use in clinical care. We did not exclude studies based on study design, quality, or sample size. Synthesis focused on describing system specifications and their use. For objective three we adopted a list of outcome indicators [1], which each of the studies were assessed against.Results:The initial search yielded 2040 articles. Only 12 studies reporting on ten unique systems were identified. Two systems were used in rheumatology, but the majority were used in oncology. Systems were highly heterogeneous in terms of technical and functional specifications. Nine systems were fully integrated (data viewable in the EHR) while the remaining system represented a partial integration (data viewable via link in the EHR). Five systems allowed repeated data collection at pre-defined intervals between visits with frequencies varying from daily to monthly. The remaining five made a single request before a scheduled clinic visit. The number of items requested from patients ranged from 9-48 per session. We identified three different clinical workflows: Simple (data only used during consultation, n=5), moderate (real-time alerts for providers when severe symptoms were reported, n=4) and on-demand (patient-initiated visits, n=1). Benefits of symptom reporting from each of the studies were categorised as anticipated, realized quantitative, and realized qualitative. We present summarised counts of these benefits in Figure 1. The most common anticipated benefits were better communication, changes to patient management and improved health outcomes. Most common realized benefits were detecting unrecognised problems and changes to patient management.Figure 1.Summarized counts of benefits from each included study assessed against Chen et al.’s 10 outcome indicators. Categorized in anticipated (orange), realized quantitative (light purple), and realized qualitative benefits (dark purple).Conclusion:There is growing interest and urge for integrating symptom data in the EHR and clinical care. Yet, this review has illustrated that there are limited published efforts to learn from. The heterogeneity in approaches underpins the need for a common framework. There is growing evidence from qualitative work in support of remote symptom-reporting in enabling better and patient-centred care in LTCs. The next step will be for robust, quantitative studies to provide evidence of benefits.References:[1]Chen J, Ou L, Hollis SJ. A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting. BMC Health Serv Res. 2013 Jun 11;13:211.Disclosure of Interests:Julie de Fonss Gandrup: None declared, Syed Mustafa Ali: None declared, Sabine van der Veer: None declared, John McBeth: None declared, William Dixon Consultant of: Bayer and Google

scholarly journals Accuracy of the Preferred Language Field in the Electronic Health Records of Two Canadian Hospitals

2020 ◽  
Vol 11 (04) ◽  
pp. 644-649
Author(s):  
Akshay Rajaram ◽  
Daniel Thomas ◽  
Faten Sallam ◽  
Amol A. Verma ◽  
Shail Rawal
Keyword(s):  
Electronic Health Records ◽  
English Language ◽  
Clinical Care ◽  
Real Data ◽  
Language Preference ◽  
Health Records ◽  
Patient Reported ◽  
Language Data ◽  
Electronic Health ◽  
Sensitivity Specificity

Abstract Background The collection of race, ethnicity, and language (REaL) data from patients is advocated as a first step to identify, monitor, and improve health inequities. As a result, many health care institutions collect patients' preferred languages in their electronic health records (EHRs). These data may be used in clinical care, research, and quality improvement. However, the accuracy of EHR language data are rarely assessed. Objectives This study aimed to audit the accuracy of EHR language data at two academic hospitals in Toronto, Ontario, Canada. Methods The EHR language was compared with a patient's stated preferred language by interview. Language was dichotomized to English or non-English. Agreement between language documented in the EHR and patient-reported preferred language was calculated using sensitivity, specificity, and positive predictive value (PPV). Results A total of 323 patients were interviewed, including 96 with a stated non-English preferred language. The sensitivity of the EHR for English-language preference was high at both hospitals: 100% at hospital A with a PPV of 88%, and 99% at hospital B with a PPV of 85%. However, the sensitivity of the EHR for non-English preference differed greatly between the two hospitals. The sensitivity was 81% with a PPV of 100% at hospital A and the sensitivity was 12% with a PPV of 60% at hospital B. Conclusion The accuracy of the EHR for identifying non-English language preference differed greatly between the hospitals studied. Language data must be accurate for it to be used, and regular quality assurance is required.

A Global Socio-economic-medico-legal Model for the Sustainability of Longitudinal Electronic Health Records

2006 ◽  
Vol 45 (03) ◽  
pp. 240-245 ◽  
Author(s):  
A. Shabo
Keyword(s):  
Electronic Health Records ◽  
Healthcare Providers ◽  
Financial Assets ◽  
Healthcare Organizations ◽  
Health Records ◽  
Record Keeping ◽  
Proposed Model ◽  
Legal Model ◽  
Electronic Health

Summary Objectives: This paper pursues the challenge of sustaining lifetime electronic health records (EHRs) based on a comprehensive socio-economic-medico-legal model. The notion of a lifetime EHR extends the emerging concept of a longitudinal and cross-institutional EHR and is invaluable information for increasing patient safety and quality of care. Methods: The challenge is how to compile and sustain a coherent EHR across the lifetime of an individual. Several existing and hypothetical models are described, analyzed and compared in an attempt to suggest a preferred approach. Results: The vision is that lifetime EHRs should be sustained by new players in the healthcare arena, who will function as independent health record banks (IHRBs). Multiple competing IHRBs would be established and regulated following preemptive legislation. They should be neither owned by healthcare providers nor by health insurer/payers or government agencies. The new legislation should also stipulate that the records located in these banks be considered the medico-legal copies of an individual’s records, and that healthcare providers no longer serve as the legal record keepers. Conclusions: The proposed model is not centered on any of the current players in the field; instead, it is focussed on the objective service of sustaining individual EHRs, much like financial banks maintain and manage financial assets. This revolutionary structure provides two main benefits: 1) Healthcare organizations will be able to cut the costs of long-term record keeping, and 2) healthcare providers will be able to provide better care based on the availability of a lifelong EHR of their new patients.

scholarly journals The impact of electronic health records on healthcare quality: a systematic review and meta-analysis

2015 ◽  
Vol 26 (1) ◽  
pp. 60-64 ◽  
Author(s):  
Paolo Campanella ◽  
Emanuela Lovato ◽  
Claudio Marone ◽  
Lucia Fallacara ◽  
Agostino Mancuso ◽  
...  
Keyword(s):  
Systematic Review ◽  
Electronic Health Records ◽  
Meta Analysis ◽  
Healthcare Quality ◽  
Health Records ◽  
Electronic Health ◽  
The Impact

scholarly journals Validity of acute cardiovascular outcome diagnoses in European electronic health records: a systematic review protocol

BMJ Open ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. e031373 ◽  
Author(s):  
Jennifer Anne Davidson ◽  
Amitava Banerjee ◽  
Rutendo Muzambi ◽  
Liam Smeeth ◽  
Charlotte Warren-Gash
Keyword(s):  
Systematic Review ◽  
Electronic Health Records ◽  
Predictive Value ◽  
Grey Literature ◽  
Cochrane Library ◽  
Free Text ◽  
Health Records ◽  
Coronary Syndrome ◽  
Validation Measure ◽  
Electronic Health

IntroductionCardiovascular diseases (CVDs) are among the leading causes of death globally. Electronic health records (EHRs) provide a rich data source for research on CVD risk factors, treatments and outcomes. Researchers must be confident in the validity of diagnoses in EHRs, particularly when diagnosis definitions and use of EHRs change over time. Our systematic review provides an up-to-date appraisal of the validity of stroke, acute coronary syndrome (ACS) and heart failure (HF) diagnoses in European primary and secondary care EHRs.Methods and analysisWe will systematically review the published and grey literature to identify studies validating diagnoses of stroke, ACS and HF in European EHRs. MEDLINE, EMBASE, SCOPUS, Web of Science, Cochrane Library, OpenGrey and EThOS will be searched from the dates of inception to April 2019. A prespecified search strategy of subject headings and free-text terms in the title and abstract will be used. Two reviewers will independently screen titles and abstracts to identify eligible studies, followed by full-text review. We require studies to compare clinical codes with a suitable reference standard. Additionally, at least one validation measure (sensitivity, specificity, positive predictive value or negative predictive value) or raw data, for the calculation of a validation measure, is necessary. We will then extract data from the eligible studies using standardised tables and assess risk of bias in individual studies using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Data will be synthesised into a narrative format and heterogeneity assessed. Meta-analysis will be considered when a sufficient number of homogeneous studies are available. The overall quality of evidence will be assessed using the Grading of Recommendations, Assessment, Development and Evaluation tool.Ethics and disseminationThis is a systematic review, so it does not require ethical approval. Our results will be submitted for peer-review publication.PROSPERO registration numberCRD42019123898

Sign in / Sign up

Export Citation Format

Share Document