scholarly journals Evaluation of the use of Swedish integrated electronic health records and register health care data as support clinical trials in severe asthma: the PACEHR study

2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Stefan Franzén ◽  
Christer Janson ◽  
Kjell Larsson ◽  
Max Petzold ◽  
Urban Olsson ◽  
...  
Keyword(s):  
Health Care ◽  
Clinical Trials ◽  
Electronic Health Records ◽  
Severe Asthma ◽  
Health Records ◽  
Health Care Data ◽  
Electronic Health

scholarly journals Identifying Multisite Chronic Pain with Electronic Health Records Data

Pain Medicine ◽  
2020 ◽  
Vol 21 (12) ◽  
pp. 3387-3392
Author(s):  
Michael Von Korff ◽  
Lynn L DeBar ◽  
Richard A Deyo ◽  
Meghan Mayhew ◽  
Robert D Kerns ◽  
...  
Keyword(s):  
Health Care ◽  
Chronic Pain ◽  
Electronic Health Records ◽  
Single Site ◽  
Self Report ◽  
Survey Questionnaire ◽  
Health Records ◽  
Health Care Data ◽  
Electronic Health ◽  
Weighted Prevalence

Abstract Background Multisite chronic pain (MSCP) is associated with increased chronic pain impact, but methods for identifying MSCP for epidemiological research have not been evaluated. Objective We assessed the validity of identifying MSCP using electronic health care data compared with survey questionnaires. Methods Stratified random samples of adults served by Kaiser Permanente Northwest and Washington (N = 2,059) were drawn for a survey, oversampling persons with frequent use of health care for pain. MSCP and single-site chronic pain were identified by two methods, with electronic health care data and with self-report of common chronic pain conditions by survey questionnaire. Analyses were weighted to adjust for stratified sampling. Results MSCP was somewhat less common when ascertained by electronic health records (14.7% weighted prevalence) than by survey questionnaire (25.9% weighted prevalence). Agreement of the two MSCP classifications was low (kappa agreement statistic of 0.21). Ascertainment of MSCP with electronic health records was 30.9% sensitive, 91.0% specific, and had a positive predictive value of 54.5% relative to MSCP identified by self-report as the standard. After adjusting for age and gender, patients with MSCP identified by either electronic health records or self-report showed higher levels of pain-related disability, pain severity, depressive symptoms, and long-term opioid use than persons with single-site chronic pain identified by the same method. Conclusions Identification of MSCP with electronic health care data was insufficiently accurate to be used as a surrogate or screener for MSCP identified by self-report, but both methods identified persons with heightened chronic pain impact.

Negotiating stigma in health care: disclosure and the role of electronic health records

2015 ◽  
Vol 24 (3) ◽  
pp. 227-241 ◽  
Author(s):  
Timothy Stablein ◽  
Joseph Lorenzo Hall ◽  
Chauna Pervis ◽  
Denise L. Anthony
Keyword(s):  
Health Care ◽  
Electronic Health Records ◽  
Health Records ◽  
Electronic Health

Implementing Health Care Quality Measures in Electronic Health Records: A Conceptual Model

2021 ◽  
Author(s):  
Claire M. Campbell ◽  
Daniel R. Murphy ◽  
George E. Taffet ◽  
Anita B. Major ◽  
Christine S. Ritchie ◽  
...  
Keyword(s):  
Health Care ◽  
Electronic Health Records ◽  
Conceptual Model ◽  
Health Care Quality ◽  
Quality Measures ◽  
Care Quality ◽  
Health Records ◽  
Electronic Health

A Framework for Systematic Assessment of Clinical Trial Population Representativeness Using Electronic Health Records Data

2021 ◽  
Vol 12 (04) ◽  
pp. 816-825
Author(s):  
Yingcheng Sun ◽  
Alex Butler ◽  
Ibrahim Diallo ◽  
Jae Hyun Kim ◽  
Casey Ta ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Electronic Health Records ◽  
The United States ◽  
Design Stage ◽  
Common Data Model ◽  
Free Text ◽  
Eligibility Criteria ◽  
Health Records ◽  
Electronic Health

Abstract Background Clinical trials are the gold standard for generating robust medical evidence, but clinical trial results often raise generalizability concerns, which can be attributed to the lack of population representativeness. The electronic health records (EHRs) data are useful for estimating the population representativeness of clinical trial study population. Objectives This research aims to estimate the population representativeness of clinical trials systematically using EHR data during the early design stage. Methods We present an end-to-end analytical framework for transforming free-text clinical trial eligibility criteria into executable database queries conformant with the Observational Medical Outcomes Partnership Common Data Model and for systematically quantifying the population representativeness for each clinical trial. Results We calculated the population representativeness of 782 novel coronavirus disease 2019 (COVID-19) trials and 3,827 type 2 diabetes mellitus (T2DM) trials in the United States respectively using this framework. With the use of overly restrictive eligibility criteria, 85.7% of the COVID-19 trials and 30.1% of T2DM trials had poor population representativeness. Conclusion This research demonstrates the potential of using the EHR data to assess the clinical trials population representativeness, providing data-driven metrics to inform the selection and optimization of eligibility criteria.

scholarly journals Secure Exchange of Electronic Health Records

2012 ◽  
pp. 1403-1424
Author(s):  
Alejandro Enrique Flores ◽  
Khin Than Win ◽  
Willy Susilo
Keyword(s):  
Health Care ◽  
Access Control ◽  
Electronic Health Records ◽  
Shared Care ◽  
Health Records ◽  
Discretionary Access Control ◽  
Attribute Based Encryption ◽  
Electronic Health ◽  
Role Based ◽  
Traditional Approaches

Protecting the confidentiality of a patient’s information in a shared care environment could become a complex task. Correct identification of users, assigning of access permissions, and resolution of conflict rise as main points of interest in providing solutions for data exchange among health care providers. Traditional approaches such as Mandatory Access Control, Discretionary Access control and Role-Based Access Control policies do not always provide a suitable solution for health care settings, especially for shared care environments. The core of this contribution consists in the description of an approach which uses attribute-based encryption to protect the confidentiality of patients’ information during the exchange of electronic health records among healthcare providers. Attribute-based encryption allows the reinforcing of access policies and reduces the risk of unauthorized access to sensitive information; it also provides a set of functionalities which are described using a case study. Attribute-based encryption provides an answer to restrictions presented by traditional approaches and facilitate the reinforcing of existing security policies over the transmitted data.

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