The Economic Implications of Hyperkalemia in a Medicaid Managed Care Population.

Medicaid managed care plan RAAS inhibitors cardiorenal comorbidities chronic kidney disease diabetes healthcare utilization heart failure hyperkalemia patiromer sodium zirconium cyclosilicate

Journal

American health & drug benefits
ISSN: 1942-2962
Titre abrégé: Am Health Drug Benefits
Pays: United States
ID NLM: 101479877

Informations de publication

Date de publication:
Nov 2019
Historique:
entrez: 15 2 2020
pubmed: 15 2 2020
medline: 15 2 2020
Statut: ppublish

Résumé

Hyperkalemia, defined as a serum potassium level >5 mEq/L that results from multiple mechanisms, is a serious medical condition that can lead to life-threatening arrhythmias and sudden cardiac death. The coexistence of cardiac and renal diseases (ie, cardiorenal syndrome) significantly increases the complexity of care, but its economic impact is not well-characterized in this understudied Medicaid managed care population with hyperkalemia. To calculate the economic impact of hyperkalemia on patients with cardiorenal syndrome in a Medicaid managed care population in the United States using real-world data. In this retrospective cohort study, we used a proprietary Medicaid managed care database from 1 southern state. The total study population included 3563 patients, including 973 patients with hyperkalemia and 2590 controls (without hyperkalemia), who were matched based on age, comorbidities, and Medicaid eligibility status and duration, during a 30-month period between 2013 and 2016. The inclusion criteria for the hyperkalemia cohort were age ≥18 years, Medicaid-only insurance status, coded cardiorenal diagnosis, and a claim for hyperkalemia during the study period. The cost was determined using paid claims data. The mean healthcare costs (medical and pharmacy per member per year [PMPY] for patients with hyperkalemia was higher than that for the control cohort without hyperkalemia ($56,002 vs $23,653, respectively). These cost differences were driven by medical costs accrued in the hyperkalemia and in the control cohorts ($49,648 and $18,399 PMPY, respectively). Two of the largest drivers of the medical cost variance were inpatient costs ($33,116 vs $10,629 PMPY for the hyperkalemia and control cohorts, respectively) and dialysis costs ($2716 vs $810 PMPY, respectively). The medical loss ratios were 552% for the hyperkalemia cohort and 260% for the control cohort. Both cohorts had revenue deficits to the health plan, but the hyperkalemia cohort had double the medical loss ratio compared with the control cohort. The findings from this Medicaid managed care population suggest that hyperkalemia increases healthcare utilization and costs, which were primarily driven by the costs associated with inpatient care and dialysis. Our findings demonstrate that the Medicaid beneficiaries who have cardiorenal comorbidities accrue high costs to the Medicaid health plan, and these costs are even higher if a hyperkalemia diagnosis is present. The very high medical loss ratio for the hyperkalemia cohort in our analysis indicates that enhanced monitoring and management of patients with hyperkalemia should be considered.

Sections du résumé

BACKGROUND BACKGROUND
Hyperkalemia, defined as a serum potassium level >5 mEq/L that results from multiple mechanisms, is a serious medical condition that can lead to life-threatening arrhythmias and sudden cardiac death. The coexistence of cardiac and renal diseases (ie, cardiorenal syndrome) significantly increases the complexity of care, but its economic impact is not well-characterized in this understudied Medicaid managed care population with hyperkalemia.
OBJECTIVE OBJECTIVE
To calculate the economic impact of hyperkalemia on patients with cardiorenal syndrome in a Medicaid managed care population in the United States using real-world data.
METHODS METHODS
In this retrospective cohort study, we used a proprietary Medicaid managed care database from 1 southern state. The total study population included 3563 patients, including 973 patients with hyperkalemia and 2590 controls (without hyperkalemia), who were matched based on age, comorbidities, and Medicaid eligibility status and duration, during a 30-month period between 2013 and 2016. The inclusion criteria for the hyperkalemia cohort were age ≥18 years, Medicaid-only insurance status, coded cardiorenal diagnosis, and a claim for hyperkalemia during the study period. The cost was determined using paid claims data.
RESULTS RESULTS
The mean healthcare costs (medical and pharmacy per member per year [PMPY] for patients with hyperkalemia was higher than that for the control cohort without hyperkalemia ($56,002 vs $23,653, respectively). These cost differences were driven by medical costs accrued in the hyperkalemia and in the control cohorts ($49,648 and $18,399 PMPY, respectively). Two of the largest drivers of the medical cost variance were inpatient costs ($33,116 vs $10,629 PMPY for the hyperkalemia and control cohorts, respectively) and dialysis costs ($2716 vs $810 PMPY, respectively). The medical loss ratios were 552% for the hyperkalemia cohort and 260% for the control cohort. Both cohorts had revenue deficits to the health plan, but the hyperkalemia cohort had double the medical loss ratio compared with the control cohort.
CONCLUSIONS CONCLUSIONS
The findings from this Medicaid managed care population suggest that hyperkalemia increases healthcare utilization and costs, which were primarily driven by the costs associated with inpatient care and dialysis. Our findings demonstrate that the Medicaid beneficiaries who have cardiorenal comorbidities accrue high costs to the Medicaid health plan, and these costs are even higher if a hyperkalemia diagnosis is present. The very high medical loss ratio for the hyperkalemia cohort in our analysis indicates that enhanced monitoring and management of patients with hyperkalemia should be considered.

Identifiants

pubmed: 32055283
pmc: PMC6996620

Types de publication

Journal Article

Langues

eng

Pagination

352-361

Informations de copyright

Copyright © 2019 by Engage Healthcare Communications, LLC.

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Auteurs

Nihar R Desai (NR)

Assistant Professor of Medicine, Yale School of Medicine, New Haven, CT.

Pamala Reed (P)

Senior Director, Outcomes Research and Analysis, Intelligent Health Analytics, Tallahassee, FL.

Paula J Alvarez (PJ)

Senior Director, Managed Care Health Outcomes, Relypsa, a Vifor Pharma Group Company, Redwood City, CA.

Jeanene Fogli (J)

Executive Director, Medical Affairs, Relypsa, a Vifor Pharma Group Company, Redwood City, CA.

Steven D Woods (SD)

Senior Director, Managed Care Health Outcomes, Relypsa, a Vifor Pharma Group Company, Redwood City, CA.

Mary Kay Owens (MK)

President and Chief Executive Officer, Intelligent Health Analytics.

Classifications MeSH