TY - JOUR
T1 - The SHOnet learning health system
T2 - Infrastructure for continuous learning in pediatric rehabilitation
AU - Koscielniak, Nikolas
AU - Jenkins, Diane
AU - Hassani, Sahar
AU - Buckon, Cathleen
AU - Tucker, Joshua S.
AU - Sienko, Susan
AU - Tucker, Carole A.
N1 - Publisher Copyright:
© 2022 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of the University of Michigan.
PY - 2022/7
Y1 - 2022/7
N2 - Introduction: To describe the development and implementation of learning health system (LHS) infrastructure for a pediatric specialty care health system to support LHS research in pediatric rehabilitation settings. Methods: An existing pediatric common data model (eg, PEDSnet) of standardized medical terminologies for research was expanded and leveraged for this stud, and applied to SHOnet, a clinical research data resource consisting of deidentified data extracted from the electronic health record (EHR) from the Shriners Hospitals for Children speacialty pediatric health care system. We mapped EHR data for laboratory, procedures, drugs, and conditions to standardized vocabularies including ICD-10, CPT, RxNorm, and LOINC to the common data model using an established extraction-transformation-loading process. Rigorous quality checks were conducted to ensure a high degree of data conformance, completeness, and plausibility. SHOnet data elements from all sources are de-identified and the server is managed by the SHC Information Systems Department. SHOnet data are refreshed monthly and data elements are continually expanded based on new research endeavors. Interventions: Not applicable. Results: The Shriners Health Outcomes Network (SHOnet) includes data for over 10 000 distinct observational data elements based on over two million patient encounters between 2011 and present. Conclusion: The systematic process to develop SHOnet is replicable and flexible for other pediatric rehabilitation research settings interested in building out their LHS capabilities. Challenges and facilitators may arise for building such LHS infrastructure for rehabilitation in areas of (a) data capture, curation, query, and governance, (b) generating knowledge from data, and (c) dissemination and implementation of new institutional knowledge. Further research studies are needed to evaluate these data resources for scalable system-learning endeavors. SHOnet is an exemplar of an LHS for rehabilitation and specialty care settings. The success of an LHS is dependent on engagement of multiple stakeholders, shared governance, effective knowledge translation, and deep commitment to long-term strategies for engaging clinicians, administration, and families in leveraging knowledge to improve clinical outcomes.
AB - Introduction: To describe the development and implementation of learning health system (LHS) infrastructure for a pediatric specialty care health system to support LHS research in pediatric rehabilitation settings. Methods: An existing pediatric common data model (eg, PEDSnet) of standardized medical terminologies for research was expanded and leveraged for this stud, and applied to SHOnet, a clinical research data resource consisting of deidentified data extracted from the electronic health record (EHR) from the Shriners Hospitals for Children speacialty pediatric health care system. We mapped EHR data for laboratory, procedures, drugs, and conditions to standardized vocabularies including ICD-10, CPT, RxNorm, and LOINC to the common data model using an established extraction-transformation-loading process. Rigorous quality checks were conducted to ensure a high degree of data conformance, completeness, and plausibility. SHOnet data elements from all sources are de-identified and the server is managed by the SHC Information Systems Department. SHOnet data are refreshed monthly and data elements are continually expanded based on new research endeavors. Interventions: Not applicable. Results: The Shriners Health Outcomes Network (SHOnet) includes data for over 10 000 distinct observational data elements based on over two million patient encounters between 2011 and present. Conclusion: The systematic process to develop SHOnet is replicable and flexible for other pediatric rehabilitation research settings interested in building out their LHS capabilities. Challenges and facilitators may arise for building such LHS infrastructure for rehabilitation in areas of (a) data capture, curation, query, and governance, (b) generating knowledge from data, and (c) dissemination and implementation of new institutional knowledge. Further research studies are needed to evaluate these data resources for scalable system-learning endeavors. SHOnet is an exemplar of an LHS for rehabilitation and specialty care settings. The success of an LHS is dependent on engagement of multiple stakeholders, shared governance, effective knowledge translation, and deep commitment to long-term strategies for engaging clinicians, administration, and families in leveraging knowledge to improve clinical outcomes.
KW - health informatics
KW - infrastructure
KW - learning health systems
KW - quality improvement
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U2 - 10.1002/lrh2.10305
DO - 10.1002/lrh2.10305
M3 - Article
C2 - 35860324
AN - SCOPUS:85124724755
SN - 2379-6146
VL - 6
JO - Learning Health Systems
JF - Learning Health Systems
IS - 3
M1 - e10305
ER -