TY - JOUR
T1 - Analysis of root causes of problems affecting the quality of hospital administrative data
T2 - A systematic review and Ishikawa diagram
AU - Carvalho, Roberto
AU - Lobo, Mariana
AU - Oliveira, Mariana
AU - Oliveira, Ana Raquel
AU - Lopes, Fernando
AU - Souza, Júlio
AU - Ramalho, André
AU - Viana, João
AU - Alonso, Vera
AU - Caballero, Ismael
AU - Santos, João Vasco
AU - Freitas, Alberto
N1 - Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/12
Y1 - 2021/12
N2 - Introduction: Administrative hospital databases represent an important tool for hospital financing in many national 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 administrative hospital data, creating a catalogue of potential issues for data quality 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. Studies’ titles and abstracts were screened by two reviewers independently. Three researchers independently selected the screened studies based on their full texts and then extracted the potential root causes inferred from them. These were subsequently classified according to the Ishikawa model based on 6 categories: ”Personnel”, “Material”, “Method”, “Machine”, “Mission” and “Management”. Results: The result of our investigation and the contribution of this paper is a classification of the potential (105) root causes found through a systematic review of the 77 relevant studies we have identified and analyzed. The result was represented by an Ishikawa diagram. Most of the root causes (25.7%) were associated with the category “Personnel” – people's knowledge, preferences, education and culture, mostly related to clinical coders and health care providers activities. The quality of hospital documentation, within category “Material”, and aspects related to financial incentives or disincentives, within category “Mission”, were also frequently cited in the literature as relevant root causes for data quality issues. Conclusions: The resultant catalogue of root causes, systematized using the Ishikawa framework, provides a compilation of potential root causes of data quality issues to be considered prior to reusing these data and that can point to actions aimed at improving data quality.
AB - Introduction: Administrative hospital databases represent an important tool for hospital financing in many national 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 administrative hospital data, creating a catalogue of potential issues for data quality 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. Studies’ titles and abstracts were screened by two reviewers independently. Three researchers independently selected the screened studies based on their full texts and then extracted the potential root causes inferred from them. These were subsequently classified according to the Ishikawa model based on 6 categories: ”Personnel”, “Material”, “Method”, “Machine”, “Mission” and “Management”. Results: The result of our investigation and the contribution of this paper is a classification of the potential (105) root causes found through a systematic review of the 77 relevant studies we have identified and analyzed. The result was represented by an Ishikawa diagram. Most of the root causes (25.7%) were associated with the category “Personnel” – people's knowledge, preferences, education and culture, mostly related to clinical coders and health care providers activities. The quality of hospital documentation, within category “Material”, and aspects related to financial incentives or disincentives, within category “Mission”, were also frequently cited in the literature as relevant root causes for data quality issues. Conclusions: The resultant catalogue of root causes, systematized using the Ishikawa framework, provides a compilation of potential root causes of data quality issues to be considered prior to reusing these data and that can point to actions aimed at improving data quality.
KW - Administrative hospital data
KW - Clinical coding
KW - Data quality
KW - Data quality issue root cause
UR - http://www.scopus.com/inward/record.url?scp=85116557023&partnerID=8YFLogxK
U2 - 10.1016/j.ijmedinf.2021.104584
DO - 10.1016/j.ijmedinf.2021.104584
M3 - Review article
C2 - 34634526
AN - SCOPUS:85116557023
SN - 1386-5056
VL - 156
JO - International Journal of Medical Informatics
JF - International Journal of Medical Informatics
M1 - 104584
ER -