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Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence

BACKGROUND: Medication non-adherence is prevalent. We assessed the effect of electronic prescribing (e-prescribing) with formulary decision support on preferred formulary tier usage, copayment, and concomitant adherence. METHODS: We retrospectively analyzed 14,682 initial pharmaceutical claims for a...

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Autores principales: Pevnick, Joshua M, Li, Ning, Asch, Steven M, Jackevicius, Cynthia A, Bell, Douglas S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236533/
https://www.ncbi.nlm.nih.gov/pubmed/25167807
http://dx.doi.org/10.1186/1472-6947-14-79
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author Pevnick, Joshua M
Li, Ning
Asch, Steven M
Jackevicius, Cynthia A
Bell, Douglas S
author_facet Pevnick, Joshua M
Li, Ning
Asch, Steven M
Jackevicius, Cynthia A
Bell, Douglas S
author_sort Pevnick, Joshua M
collection PubMed
description BACKGROUND: Medication non-adherence is prevalent. We assessed the effect of electronic prescribing (e-prescribing) with formulary decision support on preferred formulary tier usage, copayment, and concomitant adherence. METHODS: We retrospectively analyzed 14,682 initial pharmaceutical claims for angiotensin receptor blocker and inhaled steroid medications among 14,410 patients of 2189 primary care physicians (PCPs) who were offered e-prescribing with formulary decision support, including 297 PCPs who adopted it. Formulary decision support was initially non-interruptive, such that formulary tier symbols were displayed adjacent to medication names. Subsequently, interruptive formulary decision support alerts also interrupted e-prescribing when preferred-tier alternatives were available. A difference in differences design was used to compare the pre-post differences in medication tier for each new prescription attributed to non-adopters, low user (<30% usage rate), and high user PCPs (>30% usage rate). Second, we modeled the effect of formulary tier on prescription copayment. Last, we modeled the effect of copayment on adherence (proportion of days covered) to each new medication. RESULTS: Compared with non-adopters, high users of e-prescribing were more likely to prescribe preferred-tier medications (vs. non-preferred tier) when both non-interruptive and interruptive formulary decision support were in place (OR 1.9 [95% CI 1.0-3.4], p = 0.04), but no more likely to prescribe preferred-tier when only non-interruptive formulary decision support was in place (p = 0.90). Preferred-tier claims had only slightly lower mean monthly copayments than non-preferred tier claims (angiotensin receptor blocker: $10.60 versus $11.81, inhaled steroid: $14.86 versus $16.42, p < 0.0001). Medication possession ratio was 8% lower for each $1.00 increase in monthly copayment to the one quarter power (p < 0.0001). However, we detected no significant direct association between formulary decision support usage and adherence. CONCLUSION: Interruptive formulary decision support shifted prescribing toward preferred tiers, but these medications were only minimally less expensive in the studied patient population. In this context, formulary decision support did not significantly increase adherence. To impact cost-related non-adherence, formulary decision support will likely need to be paired with complementary drug benefit design. Formulary decision support should be studied further, with particular attention to its effect on adherence in the setting of different benefit designs.
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spelling pubmed-42365332014-11-19 Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence Pevnick, Joshua M Li, Ning Asch, Steven M Jackevicius, Cynthia A Bell, Douglas S BMC Med Inform Decis Mak Research Article BACKGROUND: Medication non-adherence is prevalent. We assessed the effect of electronic prescribing (e-prescribing) with formulary decision support on preferred formulary tier usage, copayment, and concomitant adherence. METHODS: We retrospectively analyzed 14,682 initial pharmaceutical claims for angiotensin receptor blocker and inhaled steroid medications among 14,410 patients of 2189 primary care physicians (PCPs) who were offered e-prescribing with formulary decision support, including 297 PCPs who adopted it. Formulary decision support was initially non-interruptive, such that formulary tier symbols were displayed adjacent to medication names. Subsequently, interruptive formulary decision support alerts also interrupted e-prescribing when preferred-tier alternatives were available. A difference in differences design was used to compare the pre-post differences in medication tier for each new prescription attributed to non-adopters, low user (<30% usage rate), and high user PCPs (>30% usage rate). Second, we modeled the effect of formulary tier on prescription copayment. Last, we modeled the effect of copayment on adherence (proportion of days covered) to each new medication. RESULTS: Compared with non-adopters, high users of e-prescribing were more likely to prescribe preferred-tier medications (vs. non-preferred tier) when both non-interruptive and interruptive formulary decision support were in place (OR 1.9 [95% CI 1.0-3.4], p = 0.04), but no more likely to prescribe preferred-tier when only non-interruptive formulary decision support was in place (p = 0.90). Preferred-tier claims had only slightly lower mean monthly copayments than non-preferred tier claims (angiotensin receptor blocker: $10.60 versus $11.81, inhaled steroid: $14.86 versus $16.42, p < 0.0001). Medication possession ratio was 8% lower for each $1.00 increase in monthly copayment to the one quarter power (p < 0.0001). However, we detected no significant direct association between formulary decision support usage and adherence. CONCLUSION: Interruptive formulary decision support shifted prescribing toward preferred tiers, but these medications were only minimally less expensive in the studied patient population. In this context, formulary decision support did not significantly increase adherence. To impact cost-related non-adherence, formulary decision support will likely need to be paired with complementary drug benefit design. Formulary decision support should be studied further, with particular attention to its effect on adherence in the setting of different benefit designs. BioMed Central 2014-08-28 /pmc/articles/PMC4236533/ /pubmed/25167807 http://dx.doi.org/10.1186/1472-6947-14-79 Text en Copyright © 2014 Pevnick et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Pevnick, Joshua M
Li, Ning
Asch, Steven M
Jackevicius, Cynthia A
Bell, Douglas S
Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence
title Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence
title_full Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence
title_fullStr Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence
title_full_unstemmed Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence
title_short Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence
title_sort effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4236533/
https://www.ncbi.nlm.nih.gov/pubmed/25167807
http://dx.doi.org/10.1186/1472-6947-14-79
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