title: A fundamental metric for continuity of care: modeling and performance evaluation.
abstract: The concept of continuity in medicine is fundamental and it refers to the delivery of medical care to a patient by a care provider in an uninterrupted and coordinated manner and in accordance with the medical care needs of the patient. Principal limitations of previous studies include the following. First, there is the absence of a deliberate effort to schedule a patient's successive visits with the same provider. Second, in most cases, the reported measures are derived from the data collected through questionnaires that patients and doctors are asked to complete from memory. This introduces an unreliability factor. Third, the reported continuity-related measures are restricted to the available patient sample and, as a result, they do not necessarily reflect a representative patient distribution by age in a typical community. Fourth, the relationship between the patient-doctor interaction interval and the continuity of medical care has never been explored systematically in the literature. This paper models continuity for a representative staff model health maintenance organization (HMO) clinic in suburban Arizona and simulates patient visits that are stochastically generated through utilizing representative numbers of patient visits and care providers. It focuses on individual-based continuity delivered by a primary care provider, i.e., a general practitioner. In the simulation, the visit patterns of patients, their ages, and the length of the interaction episodes are synthesized stochastically. The distributions reflect both the patient visit profile, by age, inherent in the 90,000+ patient electronic records collected at the CIGNA HMO clinic at Chandler, AZ, over a three-year period, and the population distribution inherent in the CIGNA records. A key characteristic of the model is that it aims at deliberately maximizing continuity by making a strong effort to schedule both a patient's regular visit and follow-ups with the primary care provider, subject to the provider's availability and schedule. This paper proposes a new definition of continuity, fundamental continuity of care index (FCCI), and argues that, fundamentally, a primary care provider's depth of understanding of the patient is directly proportional to the total length of interaction between the patient and the primary care provider. Utilizing the CIGNA summary data, this paper organizes patients into five age groups: 0-5 years, 5-15 years, 15-45 years, 45-60 years, and 60+ and synthesizes the corresponding arrival distributions. Performance results, obtained for a total of 55,056 patient visits over a three-year period indicate that, while 94-97% of the patient visits are with the primary care provider, patients spend 76-77% of the nominal total visit time with their primary care provider, leading to FCCI values ranging from 0.72 to 0.75. Performance results indicate that for different choices of the mean of the patient-doctor interaction duration, the average FCCI values, obtained following simulation, reveal an approximate bell-shaped graph. For values of the mean ranging from 5 to 10, 15, 20, 25, 35, 45, and 55 min, the average FCCI measure starts at 0.49, increases to a maximum of 0.88 corresponding to a mean of 25 min, and then decreases to 0.60. Thus, for a medical clinic, constrained by the number of care providers servicing a fixed number of patients, for a given population distribution by age, an optimum value for the average patient-doctor interaction duration may be obtained empirically that yields the maximal continuity measure.
authors.affiliation: Department of Computer Science and Engineering, Arizona State University, Tempe 85287, USA. rc@enpc732.eas.asu.edu; sumit.ghosh@asu.edu
authors.forename: R
authors.initials: R
authors.lastname: Citro
authors.forename: S
authors.initials: S
authors.lastname: Ghosh
authors.forename: P G
authors.initials: PG
authors.lastname: Churgin
mesh_terms: D001130:Arizona; D003198:Computer Simulation; D003266:Continuity of Patient Care; D006279:Health Maintenance Organizations; D006801:Humans; D013269:Stochastic Processes; D013997:Time Factors