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Development of a Pharmacoeconomic Model to Demonstrate the Effect of Clinical Pharmacist Involvement in Diabetes Management
BACKGROUND: A data collection tool was developed and nationally deployed to clinical pharmacists (CPs) working in advanced practice provider roles within the Department of Veterans Affairs to document interventions and associated clinical outcomes. Intervention and short-term clinical outcome data d...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Academy of Managed Care Pharmacy
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398278/ https://www.ncbi.nlm.nih.gov/pubmed/29694293 http://dx.doi.org/10.18553/jmcp.2018.24.5.449 |
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author | Ourth, Heather Nelson, Jordan Spoutz, Patrick Morreale, Anthony P. |
author_facet | Ourth, Heather Nelson, Jordan Spoutz, Patrick Morreale, Anthony P. |
author_sort | Ourth, Heather |
collection | PubMed |
description | BACKGROUND: A data collection tool was developed and nationally deployed to clinical pharmacists (CPs) working in advanced practice provider roles within the Department of Veterans Affairs to document interventions and associated clinical outcomes. Intervention and short-term clinical outcome data derived from the tool were used to populate a validated clinical outcomes modeling program to predict long-term clinical and economic effects. OBJECTIVE: To predict the long-term effect of CP-provided pharmacotherapy management on outcomes and costs for patients with type 2 diabetes. METHODS: Baseline patient demographics and biomarkers were extracted for type 2 diabetic patients having > 1 encounter with a CP using the tool between January 5, 2013, and November 20, 2014. Treatment biomarker values were extracted 12 months after the patient’s initial visit with the CP. The number of visits with the CP was extracted from the electronic medical record, and duration of visit time was quantified by Current Procedural Terminology codes. Simulation modeling was performed on 3 patient cohorts—those with a baseline hemoglobin A1c of 8% to < 9%, 9% to < 10%, and ≥ 10%—to estimate long-term cost and clinical outcomes using modeling based on pivotal trial data (the Archimedes Model). A sensitivity analysis was conducted to assess the extent to which our results were dependent on assumptions related to program effectiveness and costs. RESULTS: A total of 7,310 patients were included in the analysis. Analysis of costs and events on 2-, 3-, 5-, and 10-year time horizons demonstrated significant reductions in major adverse cardiovascular events (MACEs), myocardial infarctions (MIs), episodes of acute heart failure, foot ulcers, and foot amputations in comparison with a control group receiving usual guideline-directed medical care. In the cohort with a baseline A1c of ≥ 10%, the absolute risk reduction was 1.82% for MACE, 1.73% for MI, 2.43% for acute heart failure, 5.38% for foot ulcers, and 2.03% for foot amputations. The incremental cost-effectiveness ratios for cost per quality-adjusted life-year during the 2-, 3-, 5-, and 10-year time horizons were cost-effective for the cohorts of patients with a baseline A1c of 9% to < 10% and ≥ 10%. CONCLUSIONS: CPs acting as advanced practice providers reduced A1c from baseline for veterans with type 2 diabetes compared with modeled usual care. Archimedes modeling of the A1c reductions projects a decreased incidence of diabetes complications and overall health care spending when compared with modeled usual care. |
format | Online Article Text |
id | pubmed-10398278 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Academy of Managed Care Pharmacy |
record_format | MEDLINE/PubMed |
spelling | pubmed-103982782023-08-04 Development of a Pharmacoeconomic Model to Demonstrate the Effect of Clinical Pharmacist Involvement in Diabetes Management Ourth, Heather Nelson, Jordan Spoutz, Patrick Morreale, Anthony P. J Manag Care Spec Pharm Research BACKGROUND: A data collection tool was developed and nationally deployed to clinical pharmacists (CPs) working in advanced practice provider roles within the Department of Veterans Affairs to document interventions and associated clinical outcomes. Intervention and short-term clinical outcome data derived from the tool were used to populate a validated clinical outcomes modeling program to predict long-term clinical and economic effects. OBJECTIVE: To predict the long-term effect of CP-provided pharmacotherapy management on outcomes and costs for patients with type 2 diabetes. METHODS: Baseline patient demographics and biomarkers were extracted for type 2 diabetic patients having > 1 encounter with a CP using the tool between January 5, 2013, and November 20, 2014. Treatment biomarker values were extracted 12 months after the patient’s initial visit with the CP. The number of visits with the CP was extracted from the electronic medical record, and duration of visit time was quantified by Current Procedural Terminology codes. Simulation modeling was performed on 3 patient cohorts—those with a baseline hemoglobin A1c of 8% to < 9%, 9% to < 10%, and ≥ 10%—to estimate long-term cost and clinical outcomes using modeling based on pivotal trial data (the Archimedes Model). A sensitivity analysis was conducted to assess the extent to which our results were dependent on assumptions related to program effectiveness and costs. RESULTS: A total of 7,310 patients were included in the analysis. Analysis of costs and events on 2-, 3-, 5-, and 10-year time horizons demonstrated significant reductions in major adverse cardiovascular events (MACEs), myocardial infarctions (MIs), episodes of acute heart failure, foot ulcers, and foot amputations in comparison with a control group receiving usual guideline-directed medical care. In the cohort with a baseline A1c of ≥ 10%, the absolute risk reduction was 1.82% for MACE, 1.73% for MI, 2.43% for acute heart failure, 5.38% for foot ulcers, and 2.03% for foot amputations. The incremental cost-effectiveness ratios for cost per quality-adjusted life-year during the 2-, 3-, 5-, and 10-year time horizons were cost-effective for the cohorts of patients with a baseline A1c of 9% to < 10% and ≥ 10%. CONCLUSIONS: CPs acting as advanced practice providers reduced A1c from baseline for veterans with type 2 diabetes compared with modeled usual care. Archimedes modeling of the A1c reductions projects a decreased incidence of diabetes complications and overall health care spending when compared with modeled usual care. Academy of Managed Care Pharmacy 2018-05 /pmc/articles/PMC10398278/ /pubmed/29694293 http://dx.doi.org/10.18553/jmcp.2018.24.5.449 Text en Copyright © 2018, Academy of Managed Care Pharmacy. All rights reserved. https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Research Ourth, Heather Nelson, Jordan Spoutz, Patrick Morreale, Anthony P. Development of a Pharmacoeconomic Model to Demonstrate the Effect of Clinical Pharmacist Involvement in Diabetes Management |
title | Development of a Pharmacoeconomic Model to Demonstrate the Effect of Clinical Pharmacist Involvement in Diabetes Management |
title_full | Development of a Pharmacoeconomic Model to Demonstrate the Effect of Clinical Pharmacist Involvement in Diabetes Management |
title_fullStr | Development of a Pharmacoeconomic Model to Demonstrate the Effect of Clinical Pharmacist Involvement in Diabetes Management |
title_full_unstemmed | Development of a Pharmacoeconomic Model to Demonstrate the Effect of Clinical Pharmacist Involvement in Diabetes Management |
title_short | Development of a Pharmacoeconomic Model to Demonstrate the Effect of Clinical Pharmacist Involvement in Diabetes Management |
title_sort | development of a pharmacoeconomic model to demonstrate the effect of clinical pharmacist involvement in diabetes management |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398278/ https://www.ncbi.nlm.nih.gov/pubmed/29694293 http://dx.doi.org/10.18553/jmcp.2018.24.5.449 |
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