A Systematic Review of Case-Identification Algorithms Based on Italian Healthcare Administrative Databases for Two Relevant Diseases of the Respiratory System: Asthma and Chronic Obstructive Pulmonary Disease.

OBJECTIVES: to identify and describe all asthma and Chronic Obstructive Pulmonary Disease (COPD) case-identification algorithms by means of Italian Healthcare Administrative Databases (HADs), through the review of papers published in the past 10 years. METHODS: this study is part of a project that systematically reviewed case-identification algorithms for 18 acute and chronic conditions by means of HADs in Italy. PubMed was searched for original articles, published between 2007 and 2017, in Italian or English. The search string consisted of a combination of free text and MeSH terms with a common part that focused on HADs and a disease-specific part. All identified papers were screened by two independent reviewers; exclusion criteria were the following: no description of reported algorithms, algorithm developed outside of the Italian context, exclusive use of death certificates, pathology register, general practitioner or pediatrician data. Pertinent papers were classified according to the objective for which the algorithm had been used, and only articles that used algorithms for primary objectives (I disease occurrence; II population/cohort selection; III outcome identification) were considered for algorithm extraction. The HADs used (hospital discharge records, drug prescriptions, etc.), ICD-9 and ICD-10 codes, ATC classification of drugs, follow-back periods, and age ranges applied by the algorithms have been reported. Further information on specific objective(s), accuracy measures, sensitivity analyses and the contribution of each HAD, have also been recorded. RESULTS: the search string led to the identification of 98 and 147 papers, respectively for asthma and COPD. By screening the references, 2 papers for asthma and 7 for COPD were added. At the end of the screening process, 14 pertinent papers were identified for asthma and 31 for COPD. Half of these used healthcare data covering a time period between 2008 and 2014. More than 75% considered the age range 6-17 for asthma and >=45 for COPD. About one-third of the articles used algorithms to estimate the occurrence of these diseases. Fourteen algorithms for asthma and 16 for COPD were extracted from the papers and characterized. The Drug Prescription Database (DPD) was used by almost all asthma case-identification algorithms, while only 7 COPD algorithms used this data source. The spectrum of active ingredients was strongly overlapping between the two diseases, with different combinations of drugs and administration routes, as well as specific number of prescriptions, follow-back years, and age ranges. Age class and chronic treatment were the main disease-specific traits that emerged from the algorithms. Three external validation processes have been performed for asthma and three for COPD. High accuracy levels have been found for asthma. COPD sensitivity analyses were unsatisfactory, while a high specificity was found for algorithms based on hospital discharge records. CONCLUSION: elements from the review on the use of healthcare administrative databases represent a useful tool to decide which algorithm to adopt, based on the algorithm's individual requirements, limits, and accuracy, taking into account the specific research objective.