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The Development and Use of an EHR-Linked Database for Glomerular Disease Research and Quality Initiatives.
Eikstadt, Richard N; Desmond, Hailey E; Lindner, Clare; Chen, Liz Yao; Courtlandt, Cheryl D; Massengill, Susan F; Kamil, Elaine S; Lafayette, Richard; Pesenson, Anne; Elliott, Matthew; Gipson, Patrick E; Gipson, Debbie S.
Afiliação
  • Eikstadt RN; Division of Nephrology, Department of Pediatrics and Communicable Diseases, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, Michigan, USA.
  • Desmond HE; Division of Nephrology, Department of Pediatrics and Communicable Diseases, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, Michigan, USA.
  • Lindner C; Division of Nephrology, Department of Pediatrics and Communicable Diseases, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, Michigan, USA.
  • Chen LY; The Lundquist Institute at Harbor-UCLA Medical Center, Los Angeles, California, USA.
  • Courtlandt CD; Division of Pediatric Nephrology, Department of Pediatrics, Levine Children's Hospital, Charlotte, North Carolina, USA.
  • Massengill SF; Division of Pediatric Nephrology, Department of Pediatrics, Levine Children's Hospital, Charlotte, North Carolina, USA.
  • Kamil ES; Division of Pediatric Nephrology, Department of Pediatrics, Cedars-Sinai Medical Center, David Geffen School of Medicine at the University of California, Los Angeles, California, USA.
  • Lafayette R; Division of Nephrology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
  • Pesenson A; The Polyclinic, Seattle, Washington, USA.
  • Elliott M; Metrolina Nephrology Associates, Charlotte, North Carolina, USA.
  • Gipson PE; Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
  • Gipson DS; Division of Nephrology, Department of Pediatrics and Communicable Diseases, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, Michigan, USA.
Glomerular Dis ; 1(4): 173-179, 2021 Oct.
Article em En | MEDLINE | ID: mdl-36751383
Background and Objective: The use of electronic health record (EHR) data can facilitate efficient research and quality initiatives. The imprecision of ICD-10 codes for kidney diagnoses has been an obstacle to discrete data-defined diagnoses in the EHR. This manuscript describes the Kidney Research Network (KRN) registry and database that provide an example of a prospective, real-world data glomerular disease registry for research and quality initiatives. Methods: KRN is a multicenter collaboration of patients, physicians, and scientists across diverse health-care settings with a focus on improving treatment options and outcomes for patients with glomerular disease. The registry and data warehouse amasses retrospective and prospective data including EHR, active research study, completed clinical trials, patient reported outcomes, and other relevant data. Following consent, participating sites enter the patient into KRN and provide a physician-confirmed primary kidney diagnosis. Kidney biopsy reports are redacted and uploaded. Site programmers extract local EHR data including demographics, insurance type, zip code, diagnoses, encounters, laboratories, procedures, medications, dialysis/transplant status, vitals, and vital status monthly. Participating sites transform data to conform to a common data model prior to submitting to the Data Analysis and Coordinating Center (DACC). The DACC stores and reviews each site's EHR data for quality before loading into the KRN database. Results: As of January 2021, 1,192 patients have enrolled in the registry. The database has been utilized for research, clinical trial design, clinical trial end point validation, and supported quality initiatives. The data also support a dashboard allowing enrolling sites to assist with clinical trial enrollment and population health initiatives. Conclusion: A multicenter registry using EHR data, following physician- and biopsy-confirmed glomerular disease diagnosis, can be established and used effectively for research and quality initiatives. This design provides an example which may be readily replicated for other rare or common disease endeavors.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Clinical_trials Idioma: En Ano de publicação: 2021 Tipo de documento: Article