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Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims
BACKGROUND: Clinicians have difficulty accurately assessing medication non-adherence within chronic disease care settings. Health information technology (HIT) could offer novel tools to assess medication adherence in diverse populations outside of usual health care settings. In a multilingual urban...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5889590/ https://www.ncbi.nlm.nih.gov/pubmed/29625571 http://dx.doi.org/10.1186/s12913-018-3071-4 |
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author | Ratanawongsa, Neda Quan, Judy Handley, Margaret A. Sarkar, Urmimala Schillinger, Dean |
author_facet | Ratanawongsa, Neda Quan, Judy Handley, Margaret A. Sarkar, Urmimala Schillinger, Dean |
author_sort | Ratanawongsa, Neda |
collection | PubMed |
description | BACKGROUND: Clinicians have difficulty accurately assessing medication non-adherence within chronic disease care settings. Health information technology (HIT) could offer novel tools to assess medication adherence in diverse populations outside of usual health care settings. In a multilingual urban safety net population, we examined the validity of assessing adherence using automated telephone self-management (ATSM) queries, when compared with non-adherence using continuous medication gap (CMG) on pharmacy claims. We hypothesized that patients reporting greater days of missed pills to ATSM queries would have higher rates of non-adherence as measured by CMG, and that ATSM adherence assessments would perform as well as structured interview assessments. METHODS: As part of an ATSM-facilitated diabetes self-management program, low-income health plan members typed numeric responses to rotating weekly ATSM queries: “In the last 7 days, how many days did you MISS taking your …” diabetes, blood pressure, or cholesterol pill. Research assistants asked similar questions in computer-assisted structured telephone interviews. We measured continuous medication gap (CMG) by claims over 12 preceding months. To evaluate convergent validity, we compared rates of optimal adherence (CMG ≤ 20%) across respondents reporting 0, 1, and ≥ 2 missed pill days on ATSM and on structured interview. RESULTS: Among 210 participants, 46% had limited health literacy, 57% spoke Cantonese, and 19% Spanish. ATSM respondents reported ≥1 missed day for diabetes (33%), blood pressure (19%), and cholesterol (36%) pills. Interview respondents reported ≥1 missed day for diabetes (28%), blood pressure (21%), and cholesterol (26%) pills. Optimal adherence rates by CMG were lower among ATSM respondents reporting more missed days for blood pressure (p = 0.02) and cholesterol (p < 0.01); by interview, differences were significant for cholesterol (p = 0.01). CONCLUSIONS: Language-concordant ATSM demonstrated modest potential for assessing adherence. Studies should evaluate HIT assessments of medication beliefs and concerns in diverse populations. TRIAL REGISTRATION: NCT00683020, registered May 21, 2008. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-018-3071-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5889590 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58895902018-04-10 Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims Ratanawongsa, Neda Quan, Judy Handley, Margaret A. Sarkar, Urmimala Schillinger, Dean BMC Health Serv Res Research Article BACKGROUND: Clinicians have difficulty accurately assessing medication non-adherence within chronic disease care settings. Health information technology (HIT) could offer novel tools to assess medication adherence in diverse populations outside of usual health care settings. In a multilingual urban safety net population, we examined the validity of assessing adherence using automated telephone self-management (ATSM) queries, when compared with non-adherence using continuous medication gap (CMG) on pharmacy claims. We hypothesized that patients reporting greater days of missed pills to ATSM queries would have higher rates of non-adherence as measured by CMG, and that ATSM adherence assessments would perform as well as structured interview assessments. METHODS: As part of an ATSM-facilitated diabetes self-management program, low-income health plan members typed numeric responses to rotating weekly ATSM queries: “In the last 7 days, how many days did you MISS taking your …” diabetes, blood pressure, or cholesterol pill. Research assistants asked similar questions in computer-assisted structured telephone interviews. We measured continuous medication gap (CMG) by claims over 12 preceding months. To evaluate convergent validity, we compared rates of optimal adherence (CMG ≤ 20%) across respondents reporting 0, 1, and ≥ 2 missed pill days on ATSM and on structured interview. RESULTS: Among 210 participants, 46% had limited health literacy, 57% spoke Cantonese, and 19% Spanish. ATSM respondents reported ≥1 missed day for diabetes (33%), blood pressure (19%), and cholesterol (36%) pills. Interview respondents reported ≥1 missed day for diabetes (28%), blood pressure (21%), and cholesterol (26%) pills. Optimal adherence rates by CMG were lower among ATSM respondents reporting more missed days for blood pressure (p = 0.02) and cholesterol (p < 0.01); by interview, differences were significant for cholesterol (p = 0.01). CONCLUSIONS: Language-concordant ATSM demonstrated modest potential for assessing adherence. Studies should evaluate HIT assessments of medication beliefs and concerns in diverse populations. TRIAL REGISTRATION: NCT00683020, registered May 21, 2008. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12913-018-3071-4) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-06 /pmc/articles/PMC5889590/ /pubmed/29625571 http://dx.doi.org/10.1186/s12913-018-3071-4 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Ratanawongsa, Neda Quan, Judy Handley, Margaret A. Sarkar, Urmimala Schillinger, Dean Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims |
title | Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims |
title_full | Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims |
title_fullStr | Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims |
title_full_unstemmed | Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims |
title_short | Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims |
title_sort | language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5889590/ https://www.ncbi.nlm.nih.gov/pubmed/29625571 http://dx.doi.org/10.1186/s12913-018-3071-4 |
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