Measures of care fragmentation: Mathematical insights from population genetics

Abstract

Objective To identify novel properties of health care fragmentation measures, drawing on insights from mathematically equivalent measures of genetic diversity. Study Design We describe mathematical relationships between two measures: (a) Breslau's Usual Provider of Care (UPC), the proportion of care with the most frequently visited provider, analogous to the “frequency of the most frequent allele” at a genetic locus; and (b) Bice‐Boxerman's Continuity of Care Index (COCI), a measure of care dispersion across multiple providers, analogous to “Nei's estimator of homozygosity” in genetics. Principal Findings Just as the frequency of the most frequent allele places a tight constraint on homozygosity, the proportion of care with the most frequently visited provider (UPC) places lower and upper bounds on dispersion of care (COCI), and vice versa. This property presents the possibility of a normalized COCI given UPC (NCGU) measure, which reflects a bounded range of care dispersion dependent on the number of visits with the most frequently visited provider. Mathematical aspects of UPC and COCI also suggest thresholds for the minimal number of patient visits to use when studying fragmentation. Conclusions Applying knowledge from population genetics elucidated relationships between care fragmentation measures and produced novel insights for care fragmentation studies.

Fragmented care and chronic illness patient outcomes: A systematic review

“…Other studies have reversed the Continuity of Care Index to measure the fragmentation of care (Kern et al, 2017 ; Kerm et al, 2018; Kern et al, 2021 ). However, there are constraints to using this index to measure care fragmentation (Rosenberg & Zulman, 2020 ). All of these scales were used because there is no current standard operative measurement for fragmented care (Frandsen et al, 2015 ; Rosenberg & Zulman, 2020 ).…”

“…However, there are constraints to using this index to measure care fragmentation (Rosenberg & Zulman, 2020 ). All of these scales were used because there is no current standard operative measurement for fragmented care (Frandsen et al, 2015 ; Rosenberg & Zulman, 2020 ). Thus, it is recommended that a measurement or tool be developed and validated to quantify care fragmentation mathematically (Rosenberg & Zulman, 2020 ).…”

“…However, few such mechanisms were explicitly connected to individuals with chronic illnesses. Identifying these mechanisms is difficult because healthcare systems are complicated and rarely provide the exact density of multiple healthcare providers or explicitly identify poor care (Liu & Yeung, 2013 ; Rosenberg & Zulman, 2020 ). Therefore, more rigorous research is needed to better understand the mechanisms of fragmented care.…”

Anticipating VA/non-VA care coordination demand for Veterans at high risk for hospitalization

“…The VA Office of Community Care has introduced a Care Coordination Model. [18] Through this Model, the VA Office of Community Care can use a Screening/Triage tool to determine the level of care coordination needed—basic, moderate, complex/chronic, or urgent. The level of care is based initially on CAN scores and then updated by clinicians if other factors (such as social support) should be incorporated.…”

“…The VA's Office of Community Care, charged with helping to coordinate VA and non-VA care, uses the CAN score to assign Veterans into levels of care coordination when Veterans receive Community Care. [18] …”