Methods to Describe Referral Patterns in a Canadian Primary Care Electronic Medical Record Database: Modelling Multilevel Count Data

Abstract

Background:  A referral from a family physician (FP) to a specialist is an inflection point in the patient journey, with potential implications for clinical outcomes and health policy. Primary care electronic medical record (EMR) databases offer opportunities to examine referral patterns. Until recently, software techniques were not available to model these kinds of multi-level count data. Objective:  To establish methodology for determining referral rates from FPs to medical specialists using the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) EMR database. Method: Retrospective cohort study, mixed effects and multi-level negative binomial regression modelling with 87,258 eligible patients between 2007 and 2012. Mean referrals compared by patient sex, age, chronic conditions, FP visits, and urban/rural practice location.  Proportion of variance in referral rates attributable to the patient and practice levels. Results:  On average, males had 0.26, and females 0.31 referrals in a 12-month period.  Referrals were significantly higher for females, increased with age, FP visits, and number of chronic conditions (p