Title

On the Impact of Treatment Restrictions for the Indigent Suffering from a Chronic Disease: The Case of Compassionate Dialysis

Publication Date

5-14-2021

Abstract

We analyze a congested healthcare delivery setting due to emergency treatment of a chronic disease on a regular basis. A prominent example of the problem of interest is congestion in the emergency room (ER) at a publicly-funded safety net hospital due to recurrent arrivals of uninsured end-stage renal disease (ESRD) patients needing dialysis (a.k.a., compassionate dialysis). Unfortunately, this is the only treatment option for un-/under-funded patients (e.g., undocumented immigrants) with ESRD, and it is available only when the patient's clinical condition is deemed as life-threatening after a mandatory protocol including an initial screening assessment in the ER as dictated and communicated by hospital administration and county policy. After the screening assessment, the so-called treatment restrictions are in place and a certain percentage of patients are sent back home{ER, thus, serves as a screening stage. The intention here is to control system-load, and, hence, overcrowding, via restricting service (i.e. dialysis) for recurrent arrivals due to the chronic nature of the underlying disease. In order to develop a deeper understanding of potential unintended consequences, we model the problem setting as a stylized queueing network with recurrent arrivals and restricted service subject to the mandatory screening assessment in the ER. We obtain analytical expressions of fundamental quantitative metrics related to network characteristics along with more sophisticated performance measures. The performance measures of interest include both traditional and new problem-specific metrics, such as those that are indicative of deterioration in patient welfare due to rejections and treatment delays. We identify cases where treatment restrictions alone may alleviate or lead to severe congestion and treatment delays, thereby impacting both the system operation and patient welfare. The fundamental insight we offer is centered around the finding that the impact of mandatory protocol on network characteristics as well as traditional and problem-specific performance measures is nontrivial and counterintuitive. However, impact is analytically and/or numerically quantifiable via our approach. Overall, our quantitative results demonstrate that the thinking behind the mandatory protocol is potentially naïve. This is because the approach does not necessarily serve its intended purpose of controlling system-load and overcrowding.

Document Type

Article

Keywords

Open Jackson Networks, Queueing Theory, Healthcare Operations

DOI

10.2139/ssrn.3835238

Source

SMU Cox: IT & Operations Management (Topic)

Language

English

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