Análise de causas de problemas que afetam a qualidade de dados hospitalares baseados em Grupos de Diagnósticos Homogéneos: revisão sistemática e diagrama Ishikawa

Abstract

Introduction: Administrative hospital databases built around Diagnosis Related Group (DRG) represent an important tool for hospital financing in several health systems and are also an important data source for clinical, epidemiological and health services research. Therefore, the data quality of such databases is of utmost importance. This paper aims to present a systematic review of root causes of data quality problems affecting DRG-based hospital data, creating a catalogue of potential issues for data analysts to explore. Methods: The MEDLINE and Scopus databases were searched using inclusion criteria based on two following concept blocks: (1) administrative hospital databases and (2) data quality. Three researchers read each article and extracted root causes. These were subsequently classified according to the Ishikawa model based on 6 categories. Results: We identified and analyzed 77 of 2009 relevant peer-reviewed papers published between 1990 and 2019 in English language. One hundred and five root causes were extracted. Most of the root causes were associated with people's knowledge, preferences, education and culture. Conclusions: This Ishikawa framework facilitates the analysis and the efforts to solve these problems that affect data quality in DRG-based administrative hospital data.