Medical Costs and Health Care Utilization Among Self-Insured Members with Carve-In Versus Carve-Out Pharmacy Benefits

J Manag Care Spec Pharm. 2020 Jun;26(6):766-774. doi: 10.18553/jmcp.2020.19411. Epub 2020 Mar 10.

Abstract

Background: Pharmacy benefit can be purchased as part of an integrated medical and pharmacy health package-a carve-in model-or purchased separately and administered by an external pharmacy benefit manager-a carve-out model. Limited peer-reviewed information is available assessing differences in use and medical costs among carve-in versus carve-out populations.

Objective: To compare total medical costs per member per year (PMPY) and utilization between commercially self-insured members receiving carve-in to those receiving carve-out pharmacy benefits overall and by 7 chronic condition subgroups.

Methods: This study used deidentified data of members continuously enrolled in Cambia Health Solutions self-insured Blue plans without benefit changes from 2017 through 2018. Cambia covers 1.6 million members in Oregon, Washington, Idaho, and Utah. The medical cost PMPY comparison was performed using multivariable general linear regression with gamma distribution adjusting for age, gender, state, insured group size, case or disease management enrollment, 7 chronic diseases, risk score (illness severity proxy), and plan paid to total paid ratio (benefit richness proxy). Medical event objectives were assessed using multivariable logistic regression comparing odds of hospitalization and emergency department (ED) visit adjusting for the same covariates. Sensitivity analyses repeated the medical cost PMPY comparison excluding high-cost members, greater than $250,000 annually. Chronic condition subgroup analyses were performed using the same methods separately for members having asthma, coronary artery disease, chronic obstructive pulmonary disease, heart failure, diabetes mellitus, depression, and rheumatoid arthritis.

Results: There were 205,835 carve-in and 125,555 carve-out members meeting study criteria. Average age (SD) was 34.2 years (18.6) and risk score (SD) 1.1 (2.3) for carve-in versus 35.2 years (19.3) and 1.1 (2.4), respectively, for carve-out. Members with carve-in benefits had lower medical costs after adjustment (4%, P < 0.001), translating into an average $148 lower medical cost PMPY ($3,749 carve-out vs. $3,601 carve-in annualized). After adjustment, the carve-in group had an estimated 15% (P < 0.001) lower hospitalization odds and 7% (P < 0.001) lower ED visit odds. Of 7 chronic conditions, significantly lower costs (12%-17% lower), odds of hospitalization (22%-36% lower), and odds of ED visit (16%-20% lower) were found among members with carve-in benefits for 5 conditions (all P < 0.05).

Conclusions: These findings suggest that integrated, carve-in pharmacy and medical benefits are associated with lower medical costs, fewer hospitalizations, and fewer ED visits. This study focused on associations, and defining causation was not in scope. Possible reasons for these findings include plan access to both medical and pharmacy data and data-informed care management and coordination. Future research should include investigation of integrated data use and its effect across the spectrum of integrated health plan offerings, provider partnerships, and analytic strategies, as well as inclusion of analyzing pharmacy costs to encompass total cost of care.

Disclosures: This study received no external funding. The study was jointly conducted by employees of Cambia Health Solutions and Prime Therapeutics, a pharmacy benefit manager servicing Cambia Health Solutions. Smith, Lam, Lockwood, and Pegus are employees of Cambia Health Solutions. Qiu and Gleason are employees of Prime Therapeutics.

Publication types

  • Comparative Study

MeSH terms

  • Chronic Disease / economics
  • Chronic Disease / therapy
  • Drug Costs / statistics & numerical data*
  • Emergency Service, Hospital / economics
  • Emergency Service, Hospital / statistics & numerical data
  • Employer Health Costs / statistics & numerical data*
  • Health Benefit Plans, Employee / economics
  • Health Benefit Plans, Employee / organization & administration*
  • Health Benefit Plans, Employee / statistics & numerical data
  • Hospitalization / economics
  • Hospitalization / statistics & numerical data
  • Humans
  • Insurance, Pharmaceutical Services / economics*
  • Insurance, Pharmaceutical Services / statistics & numerical data
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Retrospective Studies
  • United States