scholarly journals Representing Knowledge Consistently Across Health Systems

2017 ◽  
Vol 26 (01) ◽  
pp. 139-147 ◽  
Author(s):  
S. T. Rosenbloom ◽  
R. J. Carroll ◽  
J. L. Warner ◽  
M. E. Matheny ◽  
J. C. Denny
Keyword(s):  
Knowledge Representation ◽  
Clinical Data ◽  
Information Technologies ◽  
The United States ◽  
Data Models ◽  
Research Network ◽  
Patient Centered ◽  
Health Information Technologies ◽  
Health Level 7 ◽  
Support Of Research

Summary Objectives: Electronic health records (EHRs) have increasingly emerged as a powerful source of clinical data that can be leveraged for reuse in research and in modular health apps that integrate into diverse health information technologies. A key challenge to these use cases is representing the knowledge contained within data from different EHR systems in a uniform fashion. Method: We reviewed several recent studies covering the knowledge representation in the common data models for the Observational Medical Outcomes Partnership (OMOP) and its Observational Health Data Sciences and Informatics program, and the United States Patient Centered Outcomes Research Network (PCORNet). We also reviewed the Health Level 7 Fast Healthcare Interoperability Resource standard supporting app-like programs that can be used across multiple EHR and research systems. Results: There has been a recent growth in high-impact efforts to support quality-assured and standardized clinical data sharing across different institutions and EHR systems. We focused on three major efforts as part of a larger landscape moving towards shareable, transportable, and computable clinical data. Conclusion: The growth in approaches to developing common data models to support interoperable knowledge representation portends an increasing availability of high-quality clinical data in support of research. Building on these efforts will allow a future whereby significant portions of the populations in the world may be able to share their data for research.

scholarly journals Representing Knowledge Consistently Across Health Systems

2017 ◽  
Vol 26 (01) ◽  
pp. 139-147
Author(s):  
S. T. Rosenbloom ◽  
R. J. Carroll ◽  
J. L. Warner ◽  
M. E. Matheny ◽  
J. C. Denny
Keyword(s):  
Knowledge Representation ◽  
Clinical Data ◽  
Information Technologies ◽  
The United States ◽  
Data Models ◽  
Research Network ◽  
Patient Centered ◽  
Health Information Technologies ◽  
Health Level 7 ◽  
Support Of Research

Summary Objectives: Electronic health records (EHRs) have increasingly emerged as a powerful source of clinical data that can be leveraged for reuse in research and in modular health apps that integrate into diverse health information technologies. A key challenge to these use cases is representing the knowledge contained within data from different EHR systems in a uniform fashion. Method: We reviewed several recent studies covering the knowledge representation in the common data models for the Observational Medical Outcomes Partnership (OMOP) and its Observational Health Data Sciences and Informatics program, and the United States Patient Centered Outcomes Research Network (PCORNet). We also reviewed the Health Level 7 Fast Healthcare Interoperability Resource standard supporting app-like programs that can be used across multiple EHR and research systems. Results: There has been a recent growth in high-impact efforts to support quality-assured and standardized clinical data sharing across different institutions and EHR systems. We focused on three major efforts as part of a larger landscape moving towards shareable, transportable, and computable clinical data. Conclusion: The growth in approaches to developing common data models to support interoperable knowledge representation portends an increasing availability of high-quality clinical data in support of research. Building on these efforts will allow a future whereby significant portions of the populations in the world may be able to share their data for research.

scholarly journals Fast Healthcare Interoperability Resources (FHIR) as a Meta Model to Integrate Common Data Models: Development of a Tool and Quantitative Validation Study

10.2196/15199 ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. e15199
Author(s):  
Emily Rose Pfaff ◽  
James Champion ◽  
Robert Louis Bradford ◽  
Marshall Clark ◽  
Hao Xu ◽  
...  
Keyword(s):  
Clinical Data ◽  
Data Model ◽  
Research Collaboration ◽  
Data Models ◽  
Research Network ◽  
Common Data Model ◽  
Patient Centered ◽  
Health Level 7 ◽  
Value Sets ◽  
Single Standard

Background In a multisite clinical research collaboration, institutions may or may not use the same common data model (CDM) to store clinical data. To overcome this challenge, we proposed to use Health Level 7’s Fast Healthcare Interoperability Resources (FHIR) as a meta-CDM—a single standard to represent clinical data. Objective In this study, we aimed to create an open-source application termed the Clinical Asset Mapping Program for FHIR (CAMP FHIR) to efficiently transform clinical data to FHIR for supporting source-agnostic CDM-to-FHIR mapping. Methods Mapping with CAMP FHIR involves (1) mapping each source variable to its corresponding FHIR element and (2) mapping each item in the source data’s value sets to the corresponding FHIR value set item for variables with strict value sets. To date, CAMP FHIR has been used to transform 108 variables from the Informatics for Integrating Biology & the Bedside (i2b2) and Patient-Centered Outcomes Research Network data models to fields across 7 FHIR resources. It is designed to allow input from any source data model and will support additional FHIR resources in the future. Results We have used CAMP FHIR to transform data on approximately 23,000 patients with asthma from our institution’s i2b2 database. Data quality and integrity were validated against the origin point of the data, our enterprise clinical data warehouse. Conclusions We believe that CAMP FHIR can serve as an alternative to implementing new CDMs on a project-by-project basis. Moreover, the use of FHIR as a CDM could support rare data sharing opportunities, such as collaborations between academic medical centers and community hospitals. We anticipate adoption and use of CAMP FHIR to foster sharing of clinical data across institutions for downstream applications in translational research.

Modeling Patient-Centered Cognitive Work for High-Value Care Goals

2016 ◽  
Vol 5 (1) ◽  
pp. 112-119 ◽  
Author(s):  
Stephanie K. Furniss ◽  
Matthew M. Burton ◽  
David W. Larson ◽  
David R. Kaufman
Keyword(s):  
Information Flow ◽  
Distributed Cognition ◽  
Information Technologies ◽  
Cognitive Resources ◽  
Clinical Workflow ◽  
Patient Centered ◽  
Health Information Technologies ◽  
Care Plans ◽  
Safety Risks ◽  
Effective Use

Patient-centered cognitive support has been shown to be critically important to facilitate the effective use of health information technologies (HIT). There is a well-documented need to better understand HIT-mediated clinical workflow. Current technologies can burden clinicians’ cognitive resources, which is associated with patient safety risks and medical errors. We sought to employ a distributed cognition approach to examine how information flows across the activity system to support clinicians’ problem-solving. Specifically, we studied the propagation of representational states across media, conversations, actors and time in the coordination of patient-care processes. We examined multiple instances of work and information flow in a real-world setting, revealing problems in information flow: a) use of paper artifacts has limitations to facilitating coordination of care, b) clinicians challenged in developing shared awareness, c) responsibility of representing patient states is distributed across documents, d) clinical reasoning that informed care plans was absent from documents. Findings surface a challenge to automated monitoring of care goals; much of the information is present only in clinicians’ minds and in informal documents.

Racial and Ethnic Distribution of Inflammatory Bowel Disease in the United States

2021 ◽  
Author(s):  
Edward L Barnes ◽  
William B Nowell ◽  
Shilpa Venkatachalam ◽  
Angela Dobes ◽  
Michael D Kappelman
Keyword(s):  
United States ◽  
Ethnic Groups ◽  
Ethnic Diversity ◽  
The United States ◽  
Research Network ◽  
Patient Centered ◽  
Black Patients ◽  
Hispanic Patients ◽  
National Patient ◽  
Relative Prevalence

Abstract Background The current burden of Crohn’s disease (CD) and ulcerative colitis (UC) in minority populations is largely unknown. We sought to evaluate the relative prevalence of CD and UC across racial and ethnic groups within the National Patient-Centered Clinical Research Network (PCORnet). Methods We queried electronic health records from 337 centers from January 2013 to December 2018. We compared the relative prevalence of CD and UC across racial/ethnic groups to the general PCORnet populations using χ 2 and univariable logistic regression. Results Among 39,864,077 patients, 114,168 had CD, and 98,225 had UC. Relative to the overall PCORnet population, Black adult patients were significantly less likely than White patients to have a diagnosis of CD (odds ratio [OR], 0.53; 95% CI, 0.52–0.54) or UC (OR, 0.41; 95% CI, 0.40–0.43). Pediatric Black patients were also less likely to have a diagnosis of CD (OR, 0.41; 95% CI, 0.39–0.43) or UC (OR, 0.38; 95% CI, 0.35–0.41). Adult Hispanic patients were less likely to have a diagnosis of CD (OR, 0.33; 95% CI, 0.32–0.34) or UC (OR, 0.45; 95% CI, 0.44–0.46) compared with non-Hispanic patients. Similarly, pediatric Hispanic patients were less likely to have a diagnosis of CD (OR, 0.34; 95% CI, 0.32–0.36) or UC (OR, 0.50; 95% CI, 0.47–0.53). Conclusions Despite the increasing racial and ethnic diversity in the United States, these data suggest that CD and UC are modestly less prevalent among patients of non-White races and Hispanic ethnicity.

scholarly journals Patient-Centred Coordinated Care in Times of Emerging Diseases and Epidemics

2015 ◽  
Vol 24 (01) ◽  
pp. 207-15 ◽  
Author(s):  
E. Cummings ◽  
J. W. Dexheimer ◽  
Y. Gong ◽  
S. Kennebeck ◽  
A. Kushniruk ◽  
...  
Keyword(s):  
Information Technologies ◽  
New Technologies ◽  
Disease Outbreaks ◽  
Emerging Diseases ◽  
Emerging Disease ◽  
Coordinated Care ◽  
Patient Centered ◽  
Health Information Technologies ◽  
Recent Outbreak ◽  
Centered Care

Summary Objectives: In this paper the researchers describe how existing health information technologies (HIT) can be repurposed and new technologies can be innovated to provide patient-centered care to individuals affected by new and emerging diseases. Methods: The researchers conducted a focused review of the published literature describing how HIT can be used to support safe, patient-centred, coordinated care to patients who are affected by Ebola (an emerging disease). Results: New and emerging diseases present opportunities for repurposing existing technologies and for stimulating the development of new HIT innovation. Innovative technologies may be developed such as new software used for tracking patients during new or emerging disease outbreaks or by repurposing and extending existing technologies so they can be used to support patients, families and health professionals who may have been exposed to a disease. The paper describes the development of new technologies and the repurposing and extension of existing ones (such as electronic health records) using the most recent outbreak of Ebola as an example.

scholarly journals Patient-Centered Network of Learning Health Systems: Developing a resource for clinical translational research

2017 ◽  
Vol 1 (1) ◽  
pp. 40-44 ◽  
Author(s):  
L. J. Finney Rutten ◽  
A. Alexander ◽  
P. J. Embi ◽  
G. Flores ◽  
C. Friedman ◽  
...  
Keyword(s):  
Health System ◽  
Translational Research ◽  
Clinical Data ◽  
Health Care Systems ◽  
Research Network ◽  
Research Networks ◽  
Patient Centered ◽  
Learning Health System ◽  
Challenges And Opportunities ◽  
Care Systems

IntroductionThe Learning Health System Network clinical data research network includes academic medical centers, health-care systems, public health departments, and health plans, and is designed to facilitate outcomes research, pragmatic trials, comparative effectiveness research, and evaluation of population health interventions.MethodsThe Learning Health System Network is 1 of 13 clinical data research networks assembled to create, in partnership with 20 patient-powered research networks, a National Patient-Centered Clinical Research Network.Results and ConclusionsHerein, we describe the Learning Health System Network as an emerging resource for translational research, providing details on the governance and organizational structure of the network, the key milestones of the current funding period, and challenges and opportunities for collaborative science leveraging the network.

scholarly journals Digital Health Solutions to Control the COVID-19 Pandemic in Countries With High Disease Prevalence: Literature Review

10.2196/19473 ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. e19473
Author(s):  
Sharareh R Niakan Kalhori ◽  
Kambiz Bahaadinbeigy ◽  
Kolsoum Deldar ◽  
Marsa Gholamzadeh ◽  
Sadrieh Hajesmaeel-Gohari ◽  
...  
Keyword(s):  
Information Technologies ◽  
Digital Health ◽  
Developed Countries ◽  
The United States ◽  
Digital Learning ◽  
Digital Tool ◽  
Health Information Technologies ◽  
Health Products ◽  
Novel Coronavirus ◽  
Google Search

Background COVID-19, the disease caused by the novel coronavirus SARS-CoV-2, has become a global pandemic, affecting most countries worldwide. Digital health information technologies can be applied in three aspects, namely digital patients, digital devices, and digital clinics, and could be useful in fighting the COVID-19 pandemic. Objective Recent reviews have examined the role of digital health in controlling COVID-19 to identify the potential of digital health interventions to fight the disease. However, this study aims to review and analyze the digital technology that is being applied to control the COVID-19 pandemic in the 10 countries with the highest prevalence of the disease. Methods For this review, the Google Scholar, PubMed, Web of Science, and Scopus databases were searched in August 2020 to retrieve publications from December 2019 to March 15, 2020. Furthermore, the Google search engine was used to identify additional applications of digital health for COVID-19 pandemic control. Results We included 32 papers in this review that reported 37 digital health applications for COVID-19 control. The most common digital health projects to address COVID-19 were telemedicine visits (11/37, 30%). Digital learning packages for informing people about the disease, geographic information systems and quick response code applications for real-time case tracking, and cloud- or mobile-based systems for self-care and patient tracking were in the second rank of digital tool applications (all 7/37, 19%). The projects were deployed in various European countries and in the United States, Australia, and China. Conclusions Considering the potential of available information technologies worldwide in the 21st century, particularly in developed countries, it appears that more digital health products with a higher level of intelligence capability remain to be applied for the management of pandemics and health-related crises.

scholarly journals Lifestyle and the Prevention of Type 2 Diabetes: A Status Report

2015 ◽  
Vol 12 (1) ◽  
pp. 4-20 ◽  
Author(s):  
Karla I. Galaviz ◽  
K. M. Venkat Narayan ◽  
Felipe Lobelo ◽  
Mary Beth Weber
Keyword(s):  
United States ◽  
Clinical Practice ◽  
Diabetes Prevention ◽  
Information Technologies ◽  
Healthy Lifestyle ◽  
Health Care Systems ◽  
The United States ◽  
Status Report ◽  
Prevention Strategies ◽  
Health Information Technologies

Diabetes is a costly disease affecting 387 million individuals globally and 28 million in the United States. Its precursor, prediabetes, affects 316 and 86 million individuals globally and in the United States, respectively. People living with elevated blood glucose levels are at high risk for all-cause mortality and numerous cardiometabolic ailments. Fortunately, diabetes can be prevented or delayed by maintaining a healthy lifestyle and a healthy body weight. In this review, we summarize the literature around lifestyle diabetes prevention programs and provide recommendations for introducing prevention strategies in clinical practice. Overall, evidence supports the efficacy and effectiveness of lifestyle diabetes prevention interventions across clinical and community settings, delivery formats (eg, individual-, group-, or technology-based), and implementers (eg, clinicians, community members). Evidence-based diabetes prevention strategies that can be implemented in clinical practice include brief behavior change counseling, group-based education, community referrals, and health information technologies. These strategies represent opportunities where practitioners, communities, and health care systems can work together to provide individuals with education, support and opportunities to maintain healthy, diabetes-free lifestyles.

Role of health plan administrative claims data in participant recruitment for pragmatic clinical trials: An Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-term Effectiveness (ADAPTABLE) example

2020 ◽  
Vol 17 (2) ◽  
pp. 212-222 ◽  
Author(s):  
Qian Shi ◽  
Sonali Shambhu ◽  
Amanda Marshall ◽  
Elaine Rose-Kennedy ◽  
Holly Robertson ◽  
...  
Keyword(s):  
Health Plan ◽  
Clinical Data ◽  
Phase 1 ◽  
Research Network ◽  
Administrative Claims ◽  
Phase 2 ◽  
Patient Centered ◽  
Pragmatic Clinical Trials ◽  
Patient Centric

Aim: The purpose of this study is to evaluate HealthCore/Anthem Research Network recruitment strategies, compare response and enrollment rates for different recruitment strategies, and describe demographic and clinical characteristics of responders and enrollees. Methods: HealthCore/Anthem Research Network, a part of the Health Plan Research Network of the Patient-Centered Clinical Data Research Network, used administrative claims data to identify eligible health plan members for potential participation in the Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-term Effectiveness study. We approached health plan members, identified with a validated Patient-Centered Clinical Data Research Network common data model computable phenotype, and their clinical providers during November 2017 to August 2018. Providers were offered the option to exclude their patients’ participation in Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-term Effectiveness prior to our direct patient (member) outreach. Member identification was in two phases: Phase 1: 1 January 2006 to 1 April 2017, and Phase 2: 1 January 2006 to 2 February 2018. Phase 1 consisted of two batches of mail and one phone call per patient. In Phase 2, which included two similar batches of patients, outreach was via either mail or brochure and one phone call. Results: Phase 1 and Phase 2 included 133,373 and 51,777 members, respectively. We engaged 28,593 providers in Phase 1, and 5077 in Phase 2. In Phase 1, 264,158 mixed email/mail messages were delivered to 133,373 members, followed by 90,481 phone calls from November 2017 to February 2018. In Phase 2, after simple randomization to letter or brochure, 51,777 members were sent email/mail or mailed brochure in three waves from May 2018 to July 2018. In this 9-week period, 51,623 communications were sent to 25,914 members in the email/mail group, and 50,160 brochures to 25,863 in the brochure group. Following email/mail or mailed brochure outreach, 16,624 and 16,580 calls were made to the groups, respectively. Overall, 1549 health plan members visited the study portal by 1 September 2018; 355 electronically signed the Informed Consent Form and enrolled. Mailed brochures drove more portal visits in Phase 2, but a lower percentage of responders enrolled. Recruitment was better in Phase 2—2.3 enrollees per 1000 outreach members versus 1.8 in Phase 1. Conclusion: This study showed the ability of a health plan within Patient-Centered Clinical Data Research Network to identify potential study participants with administrative claims, and use different outreach methods to facilitate recruitment and enrollment for pragmatic clinical trials.

Sign in / Sign up

Export Citation Format

Share Document