Evidence map›Paper›PMID 34838475›Full record

Trial reportJournal of the American Pharmacists Association : JAPhA

Pharmacists and community health workers improve medication-related process outcomes among Cambodian Americans with depression and risk for diabetes.

Christina M Polomoff, Angela Bermudez-Millan, Thomas Buckley, Orfeu M Buxton, Richard Feinn, Sengly Kong, Theanvy Kuoch, Mackenzie Lim, Mary Scully, Julie Wagner

Open access · greenAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of the American Pharmacists Association : JAPhA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
1.3field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 3 syntheses or guidelines pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Article
  7. Community Health Workers' and Pharmacists' Perspectives of a CHW-Pharmacist Collaboration Model to Support Medication Adherence.Health expectations : an international journal of public participation in health care and health policy · 2026
    Article
  8. Article
  9. Review
  10. The evolving role of pharmacists in depression care: a scoping review.International journal of clinical pharmacy · 2024
    Article
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Christina M Polomoff
Angela Bermudez-Millan
Thomas Buckley
Orfeu M Buxton
Richard Feinn
Sengly Kong
Theanvy Kuoch
Mackenzie Lim
Mary Scully
Julie Wagner

Funding

Lifestyle and Medication Management to Lower Diabetes Risk in Severe Mental IllnessR01DK103663 · NIDDK · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI WAGNER, JULIE A · 2015 to 2019
$3.0M
Business and regulatory development for Integrating sleep enhancement technology into clinical practiceR44AG056250 · NIA · PROACTIVE LIFE, INC. · PI GARTENBERG, DANIEL · 2020 to 2022
$2.5M
Non-pharmacological improvement of sleep structure in older peopleR43AG056250 · NIA · MOBILE SLEEP TECHNOLOGIES, LLC · PI GARTENBERG, DANIEL, GERASHCHENKO, DMITRY · 2017 to 2018
$696k
NIA NIH HHS R43 AG056250NIA NIH HHS R44 AG056250NIDDK NIH HHS R01 DK103663
6 · The paper itself

Abstract

backgroundCambodian Americans have high rates of cardiometabolic and psychiatric disorders and disadvantaged social determinants of health (SDOH). These factors can make it challenging to resolve drug therapy problems (DTPs) and improve medication-related outcomes. This manuscript reports planned analyses from a randomized controlled trial in which participants were randomized to one of 3 treatment arms: (1) community health worker (CHW)-delivered lifestyle intervention called Eat, Walk, sleep (EWS), (2) EWS plus pharmacist/CHW-delivered medication therapy management (EWS + MTM), or (3) social services (SS: control).

objectivesWe compared the 3 arms on changes in self-reported medication adherence, barriers, and beliefs. Within the EWS + MTM arm only, we assessed the impact of EWS + MTM on DTP resolution and examined predictors of DTP resolution.

methodsCambodian Americans at the age of 35-75 years at high risk of developing diabetes and meeting the criteria for likely depression (N = 188) were randomized (EWS, n = 67; EWS + MTM, n = 63; SS, n = 50; control). For all participants, self-reported surveys were collected at baseline, 12 months, and 15 months. DTPs were assessed on the same schedule but only for participants in the EWS + MTM.

resultsAll 3 groups reported a significant decrease in barriers to taking medications. Compared with the other arms, the EWS + MTM arm reported a decrease in forgetting to take medications at 15 months. In the EWS + MTM arm, mean DTPs per patient was 6.57 and 84% of DTPs were resolved. SDOH predictors of DTP resolution included years of education (odds ratio [OR] 0.94, P = 0.016), ability to write English (OR 0.73, P = 0.015), difficulty communicating with provider (OR 1.39, P < 0.001), private insurance (OR 1.99, P = 0.030), disability (OR 0.51, P = 0.008), and years living under Pol Pot (OR 0.66, P = 0.045). Medication barriers at baseline predicted DTP resolution (OR 0.79, P = 0.019) such that each additional barrier was associated with a 21% reduction (1-0.79) in the odds of having a resolution.

conclusionCHWs can reduce medications barriers and help pharmacists reduce DTPs in disadvantaged populations.

Indexed as

Diabetes MellitusPharmacistsAdultAgedAsianCommunity Health WorkersDepressionHumansMedication Therapy ManagementMiddle Aged

Identifiers

PMID34838475
PMCPMC8934259
OpenAlexW3208776868

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.