title: Electronic medical record: research tool for pancreatic cancer?
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.
authors: Surgical Outcomes Analysis & Research (SOAR), Department of Surgery, University of Massachusetts Medical School, Worcester, Massachusetts.
authors: Edward J
authors: EJ
authors: Arous
authors: Surgical Outcomes Analysis & Research (SOAR), Department of Surgery, University of Massachusetts Medical School, Worcester, Massachusetts.
authors: Theodore P
authors: TP
authors: McDade
authors: Surgical Outcomes Analysis & Research (SOAR), Department of Surgery, University of Massachusetts Medical School, Worcester, Massachusetts.
authors: Jillian K
authors: JK
authors: Smith
authors: Surgical Outcomes Analysis & Research (SOAR), Department of Surgery, University of Massachusetts Medical School, Worcester, Massachusetts.
authors: Sing Chau
authors: SC
authors: Ng
authors: Surgical Outcomes Analysis & Research (SOAR), Department of Surgery, University of Massachusetts Medical School, Worcester, Massachusetts.
authors: Mary E
authors: ME
authors: Sullivan
authors: Office of Information Systems, Massachusetts Integrated Clinical Academic Research Database, University of Massachusetts Medical School, Worcester, Massachusetts.
authors: Ralph J
authors: RJ
authors: Zottola
authors: Office of Information Systems, Massachusetts Integrated Clinical Academic Research Database, University of Massachusetts Medical School, Worcester, Massachusetts.
authors: Paul J
authors: PJ
authors: Ranauro
authors: 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.
authors: Shimul A
authors: SA
authors: Shah
authors: Surgical Outcomes Analysis & Research (SOAR), Department of Surgery, University of Massachusetts Medical School, Worcester, Massachusetts.
authors: Giles F
authors: GF
authors: Whalen
authors: 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.
authors: Jennifer F
authors: JF
authors: Tseng
mesh_terms: D000046:Academic Medical Centers; D000368:Aged; D035843:Biomedical Research / Q000379:methods*; D016208:Databases, Factual / Q000592:standards*; D057286:Electronic Health Records / Q000592:standards*; D005260:Female; D006751:Hospital Information Systems / Q000592:standards*; D006801:Humans; D038801:International Classification of Diseases; D008297:Male; D008875:Middle Aged; D010190:Pancreatic Neoplasms / Q000175:diagnosis* / Q000601:surgery*; D015203:Reproducibility of Results
keywords: Data warehouse; Database; EMR; Electronic medical record; Pancreatic cancer