Characterizing, Assessing, and Improving Healthcare Referral Communication

Author: Adol Esquivel, MD, MS (2008)

Primary Advisor: Kim Dunn, MD, PhD

Committee Members: James P. Turley, PhD, RN; Jiajie Zhang, PhD; Dov Te' eni, PhD

PhD Thesis, The University of Texas School of Health Information Sciences at Houston.

 
A healthcare referral is a common and important component of primary care. Healthcare providers often refer their patients to other services or providers to obtain advice on diagnosis or management, to obtain a specialized procedure, or to obtain a second opinion. Almost a third of all visits to primary care providers in the United States will result in referrals to specialty services. As with other healthcare processes, referrals are susceptible to breakdowns. These breakdowns in the referral process can lead to poor continuity of care, slow diagnostic processes, delays and repetition of tests, patient and provider dissatisfaction, and can lead to a loss of confidence in providers. These facts and the necessity for a deeper understanding of referrals in healthcare served as the motivation to conduct a comprehensive study of referrals. The research began with the real problem and need to understand referral communication as a mean to improve patient care. Despite previous efforts by researchers to explain referrals, the dynamics and interrelations of the variables that influence referrals and the elements that constitute a referral in healthcare, there is not a common, contemporary, and accepted definition of what a referral is in the healthcare context. The research agenda conducted was guided by the urgent need to explore referrals as an abstract concept by: 1) developing a conceptual definition of referrals, and 2) developing a model of referrals, to finally propose a 3) comprehensive research framework. This dissertation has resulted in a standard conceptual definition of referrals and a model of referrals that includes the 12 defining attributes of referrals. In addition a mixed-method framework to evaluate referrals was proposed, which consist of a systematic approach to the study of referrals. And finally a data driven model was developed to predict whether a referral would be approved when reviewed by a specialty service using available variables related to the particular referral process. The three manuscripts included in this dissertation present the basis for studying and assessing referrals using a common framework that should allow an easier comparative research agenda to improve referrals taking into account the context where referrals occur.