Conceptualizing lifer versus destination patients for optimized care delivery

Background Patients presenting to academic medical centers (AMC) typically receive primary care, specialty care, or both. Resources needed for each type of care vary, requiring different levels of care coordination. We propose a novel method to determine whether a patient primarily receives primary or specialty care to allow for optimization of care coordination. Objectives We aimed to define the concepts of a Lifer Patient and Destination Patient and analyze the current state of care utilization in those groups to inform opportunities for improving care coordination. Methods Using AMC data for a 36-month study period (FY17-19), we evaluated the number of unique patients by residence zip code. Patients with at least one primary care visit and patients without a primary care visit were classified as Lifer and Destination patients, respectively. Cohen’s effect sizes were used to evaluate differences in mean utilization of different care delivery settings. Results The AMC saw 35,909 Lifer patients and 744,037 Destination patients during the study period. Most patients were white, non-Hispanic females; however, the average age of a Lifer was seventy-two years whereas that of a Destination patient was thirty-eight. On average, a Lifer had three times more ambulatory care visits than a Destination patient. The proportion of Inpatient encounters is similar between the groups. Mean Inpatient length of stay (LOS) is similar between the groups, but Destination patients have more variance in LOS. The rate of admission from the emergency department (ED) for Destination patients is nearly double Lifers’. Conclusion There were differences in ED, ambulatory care, and inpatient utilization between the Lifer and Destination patients. Furthermore, there were incongruities between rate of hospital admissions and LOS between two groups. The Lifer and Destination patient definitions allow for identification of opportunities to tailor care coordination to these unique groups and to allocate resources more efficiently.