Analysis of Patients’ Mobility Patterns
Insights From a Process Mining-Based Longitudinal Study
Bibliographic Data
| ID | 13775175 |
|---|---|
| Authors | Mansoureh Yari Eili (0000-0002-9031-3988, University of Qom, Iran), Fatemeh Hajialiasgari (Tehran University of Medical Sciences, Iran, corresponding author), Mohammad Hossein Roozbahani (0000-0001-7013-8775, Iran University of Science and Technology, Tehran, Iran), Jalal Rezaeenour (0000-0002-3759-2607, University of Qom, Iran), Mahdi Shafiee Sabet (0009-0006-8954-8428, Tehran University of Medical Sciences, Iran), Shima Mohammadi (Shahrood University of Medical Sciences, Iran), Alireza Atashi (0000-0002-9923-9665, Tehran University of Medical Sciences, Iran) |
| Year | 2026 |
| Volume | 63 |
| Pages | 469580261422675-469580261422675 |
| Publication date | 2026-03-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | INQUIRY The Journal of Health Care Organization Provision and Financing (JOURNAL) |
| Journal identifiers | ISSN: 0046-9580 • E-ISSN: 1945-7243 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1177/00469580261422675 |
| PMID | 41775656 |
| OpenAlex | W7133551999 |
| Language | EN |
| References cited | 30 |
Patient mobility is a crucial indicator in healthcare resource allocation and improvement. This mobility is due to the uneven distribution of healthcare facilities in its provincial sense. The objective here is to designate the Alzheimer's disease patients' mobility patterns in Iran. Through this longitudinal study, by applying process mining techniques on the 28 425 physician office visits recorded in the Salamat Health Insurance (SHI) database between 2019 and 2023, the inter-provincial patient mobility patterns across Iran are revealed. Based on the extracted knowledge about the most essential care flows, patient mobility patterns in provinces with the highest rates of trajectories are constructed, a task that traditional statistical methods cannot assess in healthcare. The inter-provincial process model of patients with the highest count of out-of-province patient mobility (more than 50%) is attributed to Ilam, Alborz, Sistan, and North and South Khorasan provinces; though, Tehran, Alborz, and Isfahan provinces are the preferred medical destinations for 70% of AD treatment. The provinces with the lowest count of patient mobility are Qom, Yazd, Fars, Gilan, Isfahan, Eastern Azerbaijan, and Khorasan Razavi, with rates <1%. The potential of process mining techniques in addressing new problems in healthcare services and the integration between the 2 disciplines is introduced here to better understand their contribution to the health industry. The top provinces with the highest counts of referrals from other provinces (eg, Tehran, Alborz, and Isfahan) have also a high count of the specialist share. Consequently, efforts should be made to promote a rational balance in medical resource allocation throughout provinces nationwide, thereby eliminating the monopolistic status of a particular province
Destinations · Distribution (mathematics · Health care · Health insurance · Health services research · Process (computing · Resource (disambiguation · Resource allocation · Task (project management · Business Process Modeling and Analysis · Customer churn and segmentation · Healthcare Operations and Scheduling Optimization
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| Highly cited | No |
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