An Integrated Approach to Improving Itinerary Completion in Coordinated Care Networks

46 Pages Posted: 4 Nov 2020 Last revised: 13 Jan 2023

See all articles by Yiqiu Liu

Yiqiu Liu

Arizona State University (ASU) - Ira A. Fulton School of Engineering

Pengyi Shi

Purdue University - Krannert School of Management

Jonathan Helm

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies

Mark P. Van Oyen

University of Michigan at Ann Arbor

Lei Ying

University of Michigan at Ann Arbor

Todd Huschka

Mayo Clinic

Date Written: January 11, 2023

Abstract

Problem definition: Coordinated care network (CCN) is a burgeoning paradigm where patients' diagnosis and treatment plans are developed based on collaboration between multiple, co-located medical specialties to holistically address patients' health needs. A primary performance metric for CCNs is how quickly patients can complete their itinerary of appointments at multiple medical services in the network. Rapid completion is critical to care delivery but also presents a major operational challenge. Because information about a patient's condition and treatment options evolves over the course of the itinerary, care paths are not known a priori. Thus, appointments (except the first one) cannot be reserved in advance, which may result in significant delays if capacity is not allocated properly.

Methodology/results: We study capacity allocation for the patient's first (root) appointment as the primary operational lever to achieve rapid itinerary completion in CCNs. We develop a novel discrete-time queueing network and an integrated analytical framework to optimize this root appointment allocation, maximizing the proportion of patients completing care by pre-specified deadlines. Our framework accounts for the complex interactions among all patients in the network, which contrasts with conventional siloed planning. In particular, our framework incorporates salient features of CCNs and captures the key driver of itinerary completion -- the network blocking, linking the system-level capacity allocation and patient-level performance. We provide an exact characterization of the itinerary time and develop a mean-field approximation with convergence guarantees that permits tractable solutions for large-scale network problems. In a simulation case study of the Mayo Clinic, our solution improves on-time completion from 60% under the current plan to more than 93%.

Managerial implications:We demonstrate that root appointment allocation is a multifaceted problem and that ignoring any of those facets can lead to poor performance. Simultaneously accounting for all these complexities makes manual template design or traditional optimization methods inadequate, highlighting the significance of our integrated approach.

Keywords: Coordination, Queueing Networks with Deadlines, Mean-field Model

JEL Classification: I1, C02

Suggested Citation

Liu, Yiqui and Shi, Pengyi and Helm, Jonathan and Van Oyen, Mark P. and Ying, Lei and Huschka, Todd, An Integrated Approach to Improving Itinerary Completion in Coordinated Care Networks (January 11, 2023). Available at SSRN: https://ssrn.com/abstract=3667095 or http://dx.doi.org/10.2139/ssrn.3667095

Yiqui Liu

Arizona State University (ASU) - Ira A. Fulton School of Engineering ( email )

Tempe, AZ
United States

Pengyi Shi

Purdue University - Krannert School of Management ( email )

1310 Krannert Building
West Lafayette, IN 47907-1310
United States

Jonathan Helm (Contact Author)

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies ( email )

Business 670
1309 E. Tenth Street
Bloomington, IN 47401
United States

Mark P. Van Oyen

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Lei Ying

University of Michigan at Ann Arbor ( email )

Todd Huschka

Mayo Clinic ( email )

200 First Street SW
Rochester, MN (507) 284-2511 55905
United States

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