Abstract
BackgroundTracing frequent users of health care services is highly relevant to policymakers and clinicians, enabling them to avoid wasting scarce resources. Data collection on frequent users from all possible health care providers may be cumbersome due to patient privacy, competition, incompatible information systems, and the efforts involved.ObjectiveThis study explored the use of a single key source, emergency medical services (EMS) records, to trace and reveal frequent users’ health care consumption patterns.MethodsA retrospective study was performed analyzing EMS calls from the province of Drenthe in the Netherlands between 2012 and 2017. Process mining was applied to identify the structure of patient routings (ie, their consecutive visits to hospitals, nursing homes, and EMS). Routings are used to identify and quantify frequent users, recognizing frail elderly users as a focal group. The structure of these routes was analyzed at the patient and group levels, aiming to gain insight into regional coordination issues and workload distributions among health care providers.ResultsFrail elderly users aged 70 years or more represented over 50% of frequent users, making 4 or more calls per year. Over the period of observation, their annual number and the number of calls increased from 395 to 628 and 2607 to 3615, respectively. Structural analysis based on process mining revealed two categories of frail elderly users: low-complexity patients who need dialysis, radiation therapy, or hyperbaric medicine, involving a few health care providers, and high-complexity patients for whom routings appear chaotic.ConclusionsThis efficient approach exploits the role of EMS as the unique regional “ferryman,” while the combined use of EMS data and process mining allows for the effective and efficient tracing of frequent users’ utilization of health care services. The approach informs regional policymakers and clinicians by quantifying and detailing frequent user consumption patterns to support subsequent policy adaptations.
Highlights
A large part of regional health care consumption is attributed to “frequent users” [1]
This efficient approach exploits the role of emergency medical services (EMS) as the unique regional “ferryman,” while the combined use of EMS data and process mining allows for the effective and efficient tracing of frequent users’ utilization of health care services
The high workload and costs incurred by frequent users make them a relevant target group for regional policymakers and clinicians to consider as they attempt to make the best use of scarce resources
Summary
A large part of regional health care consumption is attributed to “frequent users” (ie, patients who make repeated calls to hospital and nursing health care services) [1]. Due to the various health care needs related to advanced age, the “frail elderly” are known to be frequent users [6,7,8,9] Their frailty is related to their status of being extremely vulnerable to endogenous and exogenous stressors, exposing them to a higher risk of negative health-related outcomes [8]. They are often confronted with fragmented health care [6], inappropriate or delayed triage at EDs [10], and incorrect referrals. Data collection on frequent users from all possible health care providers may be cumbersome due to patient privacy, competition, incompatible information systems, and the efforts involved
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