Evidence map›Paper›PMID 33094073›Full record

ArticleCureus2020

Evaluating Medication Habits in Medical Mission Patients: A Cross-Sectional Study.

Jessica H Rehrig, Lucia Vitale, Divya L Padmanabhan, Sharmeen Jaffry, Jane Suh, AnneMarie Tomosky, Christopher Boni

Abstract read
In one paragraph

Article in Cureus, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Jessica H RehrigOsteopathic Medicine, University of New England, Biddeford, USA.
Lucia VitalePolitics Department, University of California, Santa Cruz, USA.
Divya L PadmanabhanOsteopathic Medicine, University of New England, Biddeford, USA.
Sharmeen JaffryOsteopathic Medicine, University of New England, Biddeford, USA.
Jane SuhOsteopathic Medicine, University of New England, Biddeford, USA.
AnneMarie TomoskyCollege of Science & Technology, Temple University, Philadelphia, USA.
Christopher BoniInternal Medicine, Waves of Health, Rutherford, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Short-term medical missions (STMMs) are a highly debated and largely understudied form of international volunteer work. With growing dedication to health care abroad, research evaluating their impact is crucial to ensure continued interventions are effective in improving medical care. STMM care varies in length, frequency, size, location, services offered, and country of origin and destination. This makes systematic evaluation of STMMs difficult. In addition, the transient nature of patient visits makes trending STMM's impact on long-term health outcomes complex. Despite intermittent availability, primary care missions offering pharmaceutical supplies have the unique opportunity to provide continued care to the community via free prescription supplies each visit. Given the challenges with measuring long-term outcomes in this population, it is unknown if these donated medications have any impact on patient health outcomes. As medication noncompliance is known to hinder health outcomes, our study chose to evaluate patient medication habits to see if these prescription supplies were being utilized appropriately. To our knowledge, no study has surveyed medical mission patients to explore their access and utilization of medication. Methods A cross-sectional study was conducted using a patient survey to identify risks and/or factors associated with medication noncompliance in patients visiting the medical mission, Waves of Health (WOH). For over 10 years, WOH has organized biannual seven-day trips to the Dominican Republic. The multi-question survey was translated into the native language, Spanish with Dominican dialect. Noncompliance was defined through the survey question "Did you run out of your prescription medication at all during the past year?" Spanish speaking participants, of both sexes and age ≥18 years old, who visited the mission clinic in November 2019 met inclusion for this study. Patients from Haiti or age <18 years old were excluded. Participation was voluntary. Survey items were dichotomized for univariate analysis to identify factors associated with running out of medication. To explore predictors of running out of medicine, we performed multivariate logistic regression analysis by ENTER method.  Results Of 127 patients, over half (58.3% [74]) reported running out of medication. Inadequate access to healthcare, daily medication use, and rationing personal medications were all significantly associated with running out of medicine. Frequency of WOH visits was not associated with running out of medication. Multivariate regression showed that being on daily medication and rationing personal medications were statistically significant predictors of running out of medicines. Access to healthcare, frequency of WOH visits, and WOH medication supply were not predictors of running out of medication. Conclusion  Mission interventions to improve medication practices should be explored due to the high number of patients who reported improper utilization of medication. In order to improve health outcomes in primary care settings, patients must play an active role in their care and understand the importance of taking their medication as prescribed for optimal disease management. Primary care STMMs may relieve short-term health concerns, but without proper utilization of chronic disease medications, it is unclear if STMMs role is impactful in long-term health outcomes.

Indexed as

global volunteeringinternational primary carelow income countriespublic healthshort term medical missions

Identifiers

PMID33094073
PMCPMC7574977

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Registered trials

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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.