Edward J Arous1, Theodore P McDade1, Jillian K Smith1, Sing Chau Ng1, Mary E Sullivan1, Ralph J Zottola2, Paul J Ranauro2, Shimul A Shah3, Giles F Whalen1, Jennifer F Tseng4. 1. Surgical Outcomes Analysis & Research (SOAR), Department of Surgery, University of Massachusetts Medical School, Worcester, Massachusetts. 2. Office of Information Systems, Massachusetts Integrated Clinical Academic Research Database, University of Massachusetts Medical School, Worcester, Massachusetts. 3. Surgical Outcomes Analysis & Research (SOAR), Department of Surgery, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Surgery, University of Cincinnati School of Medicine, Cincinnati, Ohio. 4. Surgical Outcomes Analysis & Research (SOAR), Department of Surgery, University of Massachusetts Medical School, Worcester, Massachusetts; Department of Surgery, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts. Electronic address: jennifer.tseng@mac.com.
Abstract
BACKGROUND: A novel data warehouse based on automated retrieval from an institutional health care information system (HIS) was made available to be compared with a traditional prospectively maintained surgical database. METHODS: A newly established institutional data warehouse at a single-institution academic medical center autopopulated by HIS was queried for International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes for pancreatic neoplasm. Patients with ICD-9-CM diagnosis codes for pancreatic neoplasm were captured. A parallel query was performed using a prospective database populated by manual entry. Duplicated patients and those unique to either data set were identified. All patients were manually reviewed to determine the accuracy of diagnosis. RESULTS: A total of 1107 patients were identified from the HIS-linked data set with pancreatic neoplasm from 1999-2009. Of these, 254 (22.9%) patients were also captured by the surgical database, whereas 853 (77.1%) patients were only in the HIS-linked data set. Manual review of the HIS-only group demonstrated that 45.0% of patients were without identifiable pancreatic pathology, suggesting erroneous capture, whereas 36.3% of patients were consistent with pancreatic neoplasm and 18.7% with other pancreatic pathology. Of the 394 patients identified by the surgical database, 254 (64.5%) patients were captured by HIS, whereas 140 (35.5%) patients were not. Manual review of patients only captured by the surgical database demonstrated 85.9% with pancreatic neoplasm and 14.1% with other pancreatic pathology. Finally, review of the 254 patient overlap demonstrated that 80.3% of patients had pancreatic neoplasm and 19.7% had other pancreatic pathology. CONCLUSIONS: These results suggest that cautious interpretation of administrative data rely only on ICD-9-CM diagnosis codes and clinical correlation through previously validated mechanisms. Published by Elsevier Inc.
BACKGROUND: A novel data warehouse based on automated retrieval from an institutional health care information system (HIS) was made available to be compared with a traditional prospectively maintained surgical database. METHODS: A newly established institutional data warehouse at a single-institution academic medical center autopopulated by HIS was queried for International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes for pancreatic neoplasm. Patients with ICD-9-CM diagnosis codes for pancreatic neoplasm were captured. A parallel query was performed using a prospective database populated by manual entry. Duplicated patients and those unique to either data set were identified. All patients were manually reviewed to determine the accuracy of diagnosis. RESULTS: A total of 1107 patients were identified from the HIS-linked data set with pancreatic neoplasm from 1999-2009. Of these, 254 (22.9%) patients were also captured by the surgical database, whereas 853 (77.1%) patients were only in the HIS-linked data set. Manual review of the HIS-only group demonstrated that 45.0% of patients were without identifiable pancreatic pathology, suggesting erroneous capture, whereas 36.3% of patients were consistent with pancreatic neoplasm and 18.7% with other pancreatic pathology. Of the 394 patients identified by the surgical database, 254 (64.5%) patients were captured by HIS, whereas 140 (35.5%) patients were not. Manual review of patients only captured by the surgical database demonstrated 85.9% with pancreatic neoplasm and 14.1% with other pancreatic pathology. Finally, review of the 254 patient overlap demonstrated that 80.3% of patients had pancreatic neoplasm and 19.7% had other pancreatic pathology. CONCLUSIONS: These results suggest that cautious interpretation of administrative data rely only on ICD-9-CM diagnosis codes and clinical correlation through previously validated mechanisms. Published by Elsevier Inc.
Entities:
Keywords:
Data warehouse; Database; EMR; Electronic medical record; Pancreatic cancer
Authors: Alan E Greenberg; Harlen Hays; Amanda D Castel; Thilakavathy Subramanian; Lindsey Powers Happ; Maria Jaurretche; Jeff Binkley; Mariah M Kalmin; Kathy Wood; Rachel Hart Journal: J Am Med Inform Assoc Date: 2015-12-31 Impact factor: 4.497
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