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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.


ABSTRACT: 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?

SUBMITTER: Ratanawongsa N 

PROVIDER: S-EPMC5889590 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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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.

Ratanawongsa Neda N   Quan Judy J   Handley Margaret A MA   Sarkar Urmimala U   Schillinger Dean D  

BMC health services research 20180406 1


<h4>Background</h4>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  ...[more]

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