TY - JOUR
T1 - Testing an Automated Approach to Identify Variation in Outcomes among Children with Type 1 Diabetes across Multiple Sites
AU - Addison, Jessica
AU - Razzaghi, Hanieh
AU - Bailey, Charles
AU - Dickinson, Kimberley
AU - Corathers, Sarah D.
AU - Hartley, David M.
AU - Utidjian, Levon
AU - Carle, Adam C.
AU - Rhodes, Erinn T.
AU - Alonso, G. Todd
AU - Haller, Michael J.
AU - Gannon, Anthony W.
AU - Indyk, Justin A.
AU - Arbeláez, Ana Maria
AU - Shenkman, Elizabeth
AU - Forrest, Christopher B.
AU - Eckrich, Daniel
AU - Magnusen, Brianna
AU - Davies, Sara Deakyne
AU - Walsh, Kathleen E.
N1 - Publisher Copyright:
© 2022 by the Author(s).
PY - 2022/9/8
Y1 - 2022/9/8
N2 - Introduction: Efficient methods to obtain and benchmark national data are needed to improve comparative quality assessment for children with type 1 diabetes (T1D). PCORnet is a network of clinical data research networks whose infrastructure includes standardization to a Common Data Model (CDM) incorporating electronic health record (EHR)-derived data across multiple clinical institutions. The study aimed to determine the feasibility of the automated use of EHR data to assess comparative quality for T1D. Methods: In two PCORnet networks, PEDSnet and OneFlorida, the study assessed measures of glycemic control, diabetic ketoacidosis admissions, and clinic visits in 2016-2018 among youth 0-20 years of age. The study team developed measure EHR-based specifications, identified institution-specific rates using data stored in the CDM, and assessed agreement with manual chart review. Results: Among 9,740 youth with T1D across 12 institutions, one quarter (26%) had two or more measures of A1c greater than 9% annually (min 5%, max 47%). The median A1c was 8.5% (min site 7.9, max site 10.2). Overall, 4% were hospitalized for diabetic ketoacidosis (min 2%, max 8%). The predictive value of the PCORnet CDM was >75% for all measures and >90% for three measures. Conclusions: Using EHR-derived data to assess comparative quality for T1D is a valid, efficient, and reliable data collection tool for measuring T1D care and outcomes. Wide variations across institutions were observed, and even the best-performing institutions often failed to achieve the American Diabetes Association HbA1C goals (<7.5%).
AB - Introduction: Efficient methods to obtain and benchmark national data are needed to improve comparative quality assessment for children with type 1 diabetes (T1D). PCORnet is a network of clinical data research networks whose infrastructure includes standardization to a Common Data Model (CDM) incorporating electronic health record (EHR)-derived data across multiple clinical institutions. The study aimed to determine the feasibility of the automated use of EHR data to assess comparative quality for T1D. Methods: In two PCORnet networks, PEDSnet and OneFlorida, the study assessed measures of glycemic control, diabetic ketoacidosis admissions, and clinic visits in 2016-2018 among youth 0-20 years of age. The study team developed measure EHR-based specifications, identified institution-specific rates using data stored in the CDM, and assessed agreement with manual chart review. Results: Among 9,740 youth with T1D across 12 institutions, one quarter (26%) had two or more measures of A1c greater than 9% annually (min 5%, max 47%). The median A1c was 8.5% (min site 7.9, max site 10.2). Overall, 4% were hospitalized for diabetic ketoacidosis (min 2%, max 8%). The predictive value of the PCORnet CDM was >75% for all measures and >90% for three measures. Conclusions: Using EHR-derived data to assess comparative quality for T1D is a valid, efficient, and reliable data collection tool for measuring T1D care and outcomes. Wide variations across institutions were observed, and even the best-performing institutions often failed to achieve the American Diabetes Association HbA1C goals (<7.5%).
UR - http://www.scopus.com/inward/record.url?scp=85139281866&partnerID=8YFLogxK
U2 - 10.1097/pq9.0000000000000602
DO - 10.1097/pq9.0000000000000602
M3 - Article
AN - SCOPUS:85139281866
SN - 2472-0054
VL - 7
SP - E602
JO - Pediatric Quality and Safety
JF - Pediatric Quality and Safety
IS - 5
ER -