Bottleneck Analysis to Reduce Primary Care to Specialty Care Referral Delay

Abstract

Reducing delays between primary care and specialty care visits is critical to improving continuity of ambulatory care delivery. To comply with referral protocols, personnel involved in patients’ care pathways process and record pertinent information to ensure appropriate care is rendered, and missing necessary information might cause “dropping of the baton” during the patient transition. The objective of this paper is to analyze the information flow along patients’ primary care to specialty care referral pathway, and identify system bottlenecks to enhance the workflow design and workforce configuration. A semi-Markov process is introduced to describe information transition and the operations of involved personnel are modeled as capacity-constrained service queues at every stage of referral pathway. Analytical formulas are derived to evaluate the overall referral delay, and a continuous improvement method is developed to identify the most critical factor that impedes the referral process. The proposed systems approach is applied to the clinics of a large academic medical center, and the analysis stresses the importance of building a health information system that supports breaking silos and adapting providers’ workflows to the information system to facilitate smart and connected care delivery. Note to Practitioners —The ambulatory care delivery system is plagued by delays that dissatisfy patients, physicians, and other medical staff, and adversely affect patient outcomes. While many extant industrial engineering/operations research (IE/OR) articles focus on reducing physician appointment delays or waiting times during visits to a medical office, this paper seeks to address the lag between primary care visits and specialty care visits, i.e., the waiting for access to specialty care once the primary care physician has decided to refer the patient. This paper establishes a novel analytical framework to model primary care to specialty care referral processes with an emphasis on the information transition along patient pathway. The rigorous analytical model unveils the insights that might not be easily identified using qualitative approaches, and enjoys higher computational efficiency compared to simulation methods. What emerges from the study is the need to integrate health information technology into medical personnel’s workflow and redesign the process to allow effective communication, which will lead to improved care, efficiency, and satisfaction.