Abstract
BackgroundAdministrative healthcare databases are widespread and are often standardized with regard to their content and data coding, thus they can be used also as data sources for surveillance and epidemiological research. Chronic dialysis requires patients to frequently access hospital and clinic services, causing a heavy burden to healthcare providers. This also means that these patients are routinely tracked on administrative databases, yet very few case definitions for their identification are currently available. The aim of this study was to develop two algorithms derived from administrative data for identifying incident chronic dialysis patients and test their validity compared to the reference standard of the regional dialysis registry.MethodsThe algorithms are based on data retrieved from hospital discharge records (HDR) and ambulatory specialty visits (ASV) to identify incident chronic dialysis patients in an Italian region. Subjects are included if they have at least one event in the HDR or ASV databases based on the ICD9-CM dialysis-related diagnosis or procedure codes in the study period. Exclusion criteria comprise non-residents, prevalent cases, or patients undergoing temporary dialysis, and are evaluated only on ASV data by the first algorithm, on both ASV and HDR data by the second algorithm. We validated the algorithms against the Emilia-Romagna regional dialysis registry by searching for incident patients in 2014 and performed sensitivity analyses by modifying the criteria to define temporary dialysis.ResultsAlgorithm 1 identified 680 patients and algorithm 2 identified 676 initiating dialysis in 2014, compared to 625 patients included in the regional dialysis registry. Sensitivity for the two algorithms was respectively 90.8 and 88.4%, positive predictive value 84.0 and 82.0%, and percentage agreement was 77.4 and 74.1%.ConclusionsAlgorithms relying on retrieval of administrative records have high sensitivity and positive predictive value for the identification of incident chronic dialysis patients. Algorithm 1, which showed the higher accuracy and has a simpler case definition, can be used in place of regional dialysis registries when they are not present or sufficiently developed in a region, or to improve the accuracy and timeliness of existing registries.
Highlights
Administrative healthcare databases are widespread and are often standardized with regard to their content and data coding, they can be used as data sources for surveillance and epidemiological research
Algorithms We describe two algorithms designed to identify the incident chronic dialysis patients in a selected time period using data obtained from the regional hospital discharge records (HDR) and ambulatory specialty visits (ASV) databases
680 incident chronic dialysis patients were identified by algorithm 1 and 676 by algorithm 2
Summary
Administrative healthcare databases are widespread and are often standardized with regard to their content and data coding, they can be used as data sources for surveillance and epidemiological research. Chronic dialysis requires patients to frequently access hospital and clinic services, causing a heavy burden to healthcare providers. This means that these patients are routinely tracked on administrative databases, yet very few case definitions for their identification are currently available. To implement and regularly maintain a regional dialysis registry a large amount of dedicated human resources would be needed This is true in Italy, that conferred data from only 8 out of 21 regions for the last published ERA-EDTA registry report [11]. This algorithm relies on ICD9-CM coding and can be adapted to be utilized in other region and countries, where it could aid to implement a new registry of chronic dialysis patients or improve the quality of existing registries
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
