Evidence map›Paper›PMID 41775656›Full record

ArticleInquiry : a journal of medical care organization, provision and financing

Analysis of Patients' Mobility Patterns: Insights From a Process Mining-Based Longitudinal Study.

Mansoureh Yari Eili, Fatemeh Hajialiasgari, Mohammad Hossein Roozbahani, Jalal Rezaeenour, Mahdi Shafiee Sabet, Shima Mohammadi, Alireza Atashi

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Article in Inquiry : a journal of medical care organization, provision and financing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Mansoureh Yari EiliUniversity of Qom, Iran.ORCID 0000-0002-9031-3988
Fatemeh HajialiasgariTehran University of Medical Sciences, Iran.
Mohammad Hossein RoozbahaniIran University of Science and Technology, Tehran, Iran.ORCID 0000-0001-7013-8775
Jalal RezaeenourUniversity of Qom, Iran.ORCID 0000-0002-3759-2607
Mahdi Shafiee SabetTehran University of Medical Sciences, Iran.
Shima MohammadiShahrood University of Medical Sciences, Iran.
Alireza AtashiTehran University of Medical Sciences, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Alzheimer DiseaseData MiningHumansIranLongitudinal StudiesAlzheimer’s diseasecare processdigital healthhealth facilitiesmedical tourismpatient mobilityprocess mining

Identifiers

PMID41775656
PMCPMC12961099

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