Process Mining for Quality Improvement in Malawi...36th Medical Informatics Europe (MIE) Conference, May 25-28, 2026, Genoa, Italy.
For non-communicable disease (NCD) program management in Malawi, long waiting times are frequently cited as a reason for poor clinic attendance and treatment default. Current quality-improvement (QI) practices, such as root-cause analysis, are often subjective. This study introduces process mining (...
| Published in: | Studies in Health Technology & Informatics Vol. 336; pp. 1953 - 1955 |
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| Main Authors: | , , |
| Format: | proceedings research Journal Article |
| Published: |
Sage Publications Inc.
2026
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194019222&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194019222 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2026 vid: 336 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 194019222 194019222 194019222 10.3233/SHTI260588 194019222 ppf: 1953 ppct: 2 formats: tig: atl: Process Mining for Quality Improvement in Malawi...36th Medical Informatics Europe (MIE) Conference, May 25-28, 2026, Genoa, Italy. aug: au: NKHOMA, Dumisani JOHN, Matthias IQBAL, Usman affil: Institute of Evidence Based Healthcare, Faculty of Health Sciences and Medicine, Bond University, 14 University Drive, Robina, 4226, QLD, Australia. sug: subj: Data Mining Utilization Quality Improvement Methods Noncommunicable Diseases Health Care Delivery Malawi Congresses and Conferences Italy Italy Malawi Multimethod Studies Focus Groups Quantitative Studies Comparative Studies Interviews Qualitative Studies Thematic Analysis Workflow Algorithms Pilot Studies Program Evaluation Electronic Health Records Quality of Health Care Data Analysis Software Time ab: For non-communicable disease (NCD) program management in Malawi, long waiting times are frequently cited as a reason for poor clinic attendance and treatment default. Current quality-improvement (QI) practices, such as root-cause analysis, are often subjective. This study introduces process mining (PM) as an objective, data-driven approach to complement existing QI methods through analysis of patient records and facility registers. We describe the first protocol to implement PM in the Malawian healthcare system. The study employs a sequential mixed-methods design combining two focus group discussions (FGDs) conducted before and after quantitative PM, key-informant interviews, and document review. Qualitative data will be analysed thematically to identify perceived workflow bottlenecks, while quantitative PM will involve data extraction, pre-processing, clustering, mining, and visualisation using discovery algorithms such as the Heuristic or Fuzzy miner. Results will be displayed as Business Process Model and Notation (BPMN) nets to reveal process variations and inefficiencies. This work aims to demonstrate the feasibility and utility of PM for clinical efficiency and quality-improvement initiatives within Malawi’s NCD program. With increasing adoption of electronic health-record systems and the national Quality of Care program, PM can provide a scalable tool for evidence-based monitoring of healthcare processes. pubtype: Academic Journal doctype: proceedings research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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