Development of an administrative definition for celiac disease

Objective The investigation and management of celiac disease places a high burden on the health care system. Accurate methods to ascertain cases of celiac disease (CD) in population-based administrative data can facilitate epidemiologic and health services research to guide disease management. The study aim was to develop and validate administrative data case definitions for CD to facilitate further studies about the effect of CD on osteoporosis and fracture risk. Results Population-based data from the Manitoba Bone Mineral Density (BMD) Program registry, which contains medical information on all individuals in the province of Manitoba, Canada who have received BMD testing, was used to define the study cohort. Linked hospital discharge abstracts and physician billing claims were used to ascertain diagnoses of celiac disease in administrative data. A population-based CD serologic registry was used as the validation database. One diagnosis code in hospital discharge abstracts or two or more diagnosis codes in physician billing claims optimized the detection of positive celiac serology with sensitivity of 84% (95% CI 80–88%), specificity of 97% (95% CI 80–88%), PPV of 80% (95% CI 80–88%), and NPV of 97% (95% CI 80–88%). Our administrative data case definition for celiac disease demonstrates good sensitivity and specificity for detecting positive celiac serology.

Validation of mechanical ventilation coding in hospital discharge abstracts: a population data linkage study

IntroductionMechanical ventilation (MV) is an important intervention used in critically ill patients. Accurately identifying MV use in Hospital Discharge Abstracts will be extremely useful in population-based research. Although Canadian Institute for Health Information collects information on MV for all hospitalization, its validity in intensive care unit (ICU) patients is unknown. Objectives and ApproachWe validated MV use within ICU patients in Hospital Discharge Abstracts. Winnipeg Regional Health Authority (WRHA) ICU database prospectively collects use of MV by trained nurses. All patients admitted to a WRHA ICU (82 beds) between April 1, 2000 and March 31, 2012 were identified in Hospital Discharge Abstracts. MV was identified in Hospital Discharge Abstracts through International Classification of Diseases (ICD-9-CM), prior to 2004, while Canadian Classification of Health Interventions (CCI) were used 2004 onwards. Agreement between the WRHA database (gold standard) and Hospital Discharge Abstracts for invasive ventilation, non-invasive ventilation or neither was calculated at ICU encounter level. ResultsThere were 54,680 WRHA ICU admission during the study period. The linking of these two sources was highly successful with accurate identification exceeding 99%. There were 26,083 mechanical ventilations (25,387 invasive; 696 non-invasive) from the Hospital Discharge Abstracts and 30,455 (28,315 invasive; 4,554 non-invasive) from the CIC data. Hospital Discharge Abstracts had a sensitivity of 82.8%, specificity of 96.4%, Positive Predictive Value (PPV) of 96.7%, and Negative Predictive Value (NPV) of 81.7% for identifying mechanical ventilation. For invasive ventilation, Sensitivity was 85.5%, Specificity was 95.6%, PPV was 95.4% and NPV was 86.0%. Validation of non-invasive ventilation was poor in sensitivity (9.38%) and PPV (61.35%): with specificity 99.5% and NPV 92.36%. Conclusion/ImplicationsHospital Abstracts data are a good source to identity mechanically ventilated patients for ICU containing hospital stays especially invasive mechanical ventilations. Future research needs to explore the poor agreement with non-invasive mechanical ventilation.

Rules to Identify Persons with Frailty in Administrative Health Databases

ABSTRACTThis study sought to develop frailty “identification rules” using population-based health administrative data that can be readily applied across jurisdictions for living and deceased persons. Three frailty identification rules were developed based on accepted definitions of frailty, markers of service utilization, and expert consultation, and were limited to variables within two common population-based administrative health databases: hospital discharge abstracts and physician claims data. These rules were used to identify persons with frailty from both decedent and living populations across five Canadian provinces. Participants included persons who had died and were aged 66 years or older at the time of death (British Columbia, Alberta, Ontario, Quebec, and Nova Scotia) and living persons 65 years or older (British Columbia, Alberta, Ontario, and Quebec). Descriptive statistics were computed for persons identified using each rule. The proportion of persons identified as frail ranged from 58.2-78.1 per cent (decedents) and 5.1-14.7 per cent (living persons).