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BMC Health Services Research

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Open Access 01-12-2018 | Research article

Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims

Authors: Neda Ratanawongsa, Judy Quan, Margaret A. Handley, Urmimala Sarkar, Dean Schillinger

Published in: BMC Health Services Research | Issue 1/2018

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 < 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.

Available only for authorised users

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Title: Language-concordant automated telephone queries to assess medication adherence in a diverse population: a cross-sectional analysis of convergent validity with pharmacy claims
Authors: Neda Ratanawongsa
Judy Quan
Margaret A. Handley
Urmimala Sarkar
Dean Schillinger
Publication date: 01-12-2018
Publisher: BioMed Central
Published in: BMC Health Services Research / Issue 1/2018
Electronic ISSN: 1472-6963
DOI: https://doi.org/10.1186/s12913-018-3071-4

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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

Methods

Results

Conclusions

Trial registration

Keynote webinar | Spotlight on sleep in brain health

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

Trial registration

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