Legitimization of Data Quality Practices in Health Management Information Systems Using DHIS2. Case of Malawi
Martin Bright Msendma, Wallace Chigona, Benjamin Kumwenda, Jens, Kaasb{\o}ll, Chipo Kanjo

TL;DR
This study explores how isomorphic processes legitimize data quality practices in Malawi's health management system using DHIS2, improving data accuracy and timeliness through organizational influences.
Contribution
It demonstrates the role of mimetic, normative, and cognitive isomorphism in legitimizing data quality practices within health information systems.
Findings
Mimetic isomorphism fosters moral and pragmatic legitimacy.
Normative isomorphism enhances cognitive legitimacy.
Legitimization improves data correctness and timeliness.
Abstract
Medical doctors consider data quality management a secondary priority when delivering health care. Medical practitioners find data quality management practices intrusive to their operations. Using Health Management Information System (HMIS) that uses DHIS2 platform, our qualitative case study establishes that isomorphism leads to legitimization of data quality management practices among health practitioners and subsequently data quality. This case study employed the methods of observation, semi structured interviews and review of artefacts to explore how through isomorphic processes data quality management practices are legitimized among the stakeholders. Data was collected from Ministry of Health's (Malawi) HMIS Technical Working Group members in Lilongwe and from medical practitioners and data clerks in Thyolo district. From the findings we noted that mimetic isomorphism led to moral…
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Taxonomy
TopicsData Quality and Management · Big Data and Business Intelligence · Biomedical Text Mining and Ontologies
