scholarly journals Pragmatic (trial) informatics: a perspective from the NIH Health Care Systems Research Collaboratory

2017 ◽  
Vol 24 (5) ◽  
pp. 996-1001 ◽  
Author(s):  
Rachel L Richesson ◽  
Beverly B Green ◽  
Reesa Laws ◽  
Jon Puro ◽  
Michael G Kahn ◽  
...  
Keyword(s):  
Health Care ◽  
Health System ◽  
Health Care Systems ◽  
Pragmatic Trial ◽  
Heterogeneous Systems ◽  
Full Potential ◽  
Systems Research ◽  
Pragmatic Clinical Trials ◽  
Care Systems ◽  
Electronic Health

Abstract Pragmatic clinical trials (PCTs) are research investigations embedded in health care settings designed to increase the efficiency of research and its relevance to clinical practice. The Health Care Systems Research Collaboratory, initiated by the National Institutes of Health Common Fund in 2010, is a pioneering cooperative aimed at identifying and overcoming operational challenges to pragmatic research. Drawing from our experience, we present 4 broad categories of informatics-related challenges: (1) using clinical data for research, (2) integrating data from heterogeneous systems, (3) using electronic health records to support intervention delivery or health system change, and (4) assessing and improving data capture to define study populations and outcomes. These challenges impact the validity, reliability, and integrity of PCTs. Achieving the full potential of PCTs and a learning health system will require meaningful partnerships between health system leadership and operations, and federally driven standards and policies to ensure that future electronic health record systems have the flexibility to support research.

scholarly journals Patient-Reported Outcomes Collected as Part of the Medicare Annual Wellness Visit in the Health Care Systems Research Network

2016 ◽  
Vol 3 (3) ◽  
pp. 168 ◽  
Author(s):  
Heather Tabano ◽  
Thomas Gill ◽  
Kathryn Anzuoni ◽  
Heather Allore ◽  
Ann Gruber-Baldini ◽  
...  
Keyword(s):  
Health Care ◽  
Patient Reported Outcomes ◽  
Health Care Systems ◽  
Research Network ◽  
Systems Research ◽  
Patient Reported ◽  
Care Systems

scholarly journals An Examination of Mentoring and Training in the Health Care Systems Research Network

2016 ◽  
Vol 3 (3) ◽  
pp. 217
Author(s):  
Sharon L Larson ◽  
Marc Williams ◽  
Ella Thompson ◽  
Amber Eruchalu ◽  
Lela McFarland
Keyword(s):  
Health Care ◽  
Health Care Systems ◽  
Research Network ◽  
Systems Research ◽  
Care Systems ◽  
And Training

scholarly journals Sharing Experiences and Expertise: The Health Care Systems Research Network Workshop on Patient Engagement in Research

2016 ◽  
Vol 3 (3) ◽  
pp. 159-166 ◽  
Author(s):  
Sarah Madrid ◽  
Leah Tuzzio ◽  
Cheryl D Stults ◽  
Leslie A Wright ◽  
Gina Napolitano ◽  
...  
Keyword(s):  
Health Care ◽  
Patient Engagement ◽  
Health Care Systems ◽  
Research Network ◽  
Systems Research ◽  
Care Systems ◽  
Patient Engagement In Research

scholarly journals CLINICIAN ENGAGEMENT IN THE NIH HEALTH CARE SYSTEMS RESEARCH COLLABORATORY

2016 ◽  
Vol 19 (3) ◽  
pp. A284 ◽  
Author(s):  
R.M. Moloney ◽  
E.S. Tambor ◽  
S. Tunis
Keyword(s):  
Health Care ◽  
Health Care Systems ◽  
Systems Research ◽  
Care Systems

scholarly journals PS2-9: The NIH Health Care Systems Research Collaboratory

2013 ◽  
Vol 11 (3) ◽  
pp. 152-152
Author(s):  
J. Brown ◽  
A. Cook ◽  
K. Lane ◽  
E. Larson ◽  
L. Li ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Systems ◽  
Systems Research ◽  
Care Systems

Full Disclosure When Bad Things Happen

2007 ◽  
Vol 26 (2) ◽  
pp. 131-132 ◽  
Author(s):  
Sherri Lee Simons
Keyword(s):  
Health Care ◽  
Health System ◽  
Health Care Providers ◽  
Health Care Systems ◽  
Institute Of Medicine ◽  
Care Providers ◽  
Full Disclosure ◽  
Care Systems

SINCE THE RELEASE OF THE Institute of Medicine report “To Err Is Human: Building a Safer Health System,” much attention has been focused on redesigning health care systems and implementing safer practices.1 At the same time, health care providers continue to grapple with the ways in which institutions and caregivers respond when preventable injuries occur.2–5

scholarly journals An efficient approach for surveillance of childhood diabetes by type derived from electronic health record data: the SEARCH for Diabetes in Youth Study

2016 ◽  
Vol 23 (6) ◽  
pp. 1060-1067 ◽  
Author(s):  
Victor W Zhong ◽  
Jihad S Obeid ◽  
Jean B Craig ◽  
Emily R Pfaff ◽  
Joan Thomas ◽  
...  
Keyword(s):  
Health Care ◽  
Electronic Health Record ◽  
Health Care Systems ◽  
Diabetes Type ◽  
Health Record ◽  
Childhood Diabetes ◽  
Electronic Health Record Data ◽  
Efficient Approach ◽  
Care Systems ◽  
Electronic Health

Abstract Objective To develop an efficient surveillance approach for childhood diabetes by type across 2 large US health care systems, using phenotyping algorithms derived from electronic health record (EHR) data. Materials and Methods Presumptive diabetes cases <20 years of age from 2 large independent health care systems were identified as those having ≥1 of the 5 indicators in the past 3.5 years, including elevated HbA1c, elevated blood glucose, diabetes-related billing codes, patient problem list, and outpatient anti-diabetic medications. EHRs of all the presumptive cases were manually reviewed, and true diabetes status and diabetes type were determined. Algorithms for identifying diabetes cases overall and classifying diabetes type were either prespecified or derived from classification and regression tree analysis. Surveillance approach was developed based on the best algorithms identified. Results We developed a stepwise surveillance approach using billing code–based prespecified algorithms and targeted manual EHR review, which efficiently and accurately ascertained and classified diabetes cases by type, in both health care systems. The sensitivity and positive predictive values in both systems were approximately ≥90% for ascertaining diabetes cases overall and classifying cases with type 1 or type 2 diabetes. About 80% of the cases with “other” type were also correctly classified. This stepwise surveillance approach resulted in a >70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods. Conclusion EHR data may be used to establish an efficient approach for large-scale surveillance for childhood diabetes by type, although some manual effort is still needed.

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