Understanding communication breakdown in the outpatient referral process in Latin America: a cross-sectional study on the use of clinical correspondence in public healthcare networks of six countries.

Abstract

An adequate use of referral and reply letters—the main form of communication between primary care (PC) and out-patient secondary care (SC)—helps to avoid medical errors, test duplications and delays in diagnosis. However, it has been little studied to date in Latin America. The aim is to determine the level and characteristics of PC and SC doctors’ use of referral and reply letters and to explore influencing factors in public healthcare networks of Argentina, Brazil, Chile, Colombia, Mexico and Uruguay. A cross-sectional study was conducted through a survey of PC and SC doctors working in public healthcare networks (348 doctors per country). The COORDENA questionnaire was applied to measure the frequency of use and receipt of referral and reply letters, quality of contents, timeliness and difficulties in using them. Descriptive analyses were conducted and a multivariate logistic regression model was generated to assess the relationship between frequent use and associated factors. The great majority of doctors claim that they send referral letters to the other level. However, only half of SC doctors (a higher proportion in Chile and Mexico) report that they receive referral letters and <20% of PC doctors receive a reply from specialists. Insufficient recording of data is reported in terms of medical history, tests and medication and the reason for referral. The factor associated with frequent use of the referral letter is doctors’ age, while the use of reply letters is associated with identifying PC doctors as care coordinators, knowing them and trusting in their clinical skills, and receiving referral letters. Significant problems are revealed in the use of referral and reply letters which may affect quality of care. Multifaceted strategies are required that foster a direct contact between doctors and a better understanding of the PC-based model.