Evidence map›Paper›PMID 33011082›Full record

ArticleResearch in social & administrative pharmacy : RSAP2021

Use of path modeling to inform a clinical decision support application to encourage osteoporosis medication use.

Michael J Miller, Tzuchen Jou, Maria I Danila, Amy S Mudano, Elizabeth J Rahn, Ryan C Outman, Kenneth G Saag

Open access · greenAbstract read
In one paragraph

Article in Research in social & administrative pharmacy : RSAP, 2021. 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, top 85% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  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 at 2 institutions in 1 country.

Michael J MillerMid-Atlantic Permanente Research Institute (MAPRI), 2101 East Jefferson Street, Rockville, MD, 20852, USA. Electronic address: michael.j1.miller@kp.org.
Tzuchen JouPGY1 Pharmacy Resident, Memorial Hermann Southwest Hospital, Houston, TX, 77074, USA. Electronic address: tzuchenj@gmail.com.
Maria I DanilaMedicine - Immunology and Rheumatology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294-2182, USA. Electronic address: mdanila@uabmc.edu.
Amy S MudanoSchool of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294-2182, USA. Electronic address: amymudano@uabmc.edu.
Elizabeth J RahnDepartment of Medical Education, University of Alabama at Birmingham, Birmingham, AL, 35294-2182, USA. Electronic address: rahneli@uab.edu.
Ryan C OutmanDivision of Hematology and Oncology, UAB Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294-2182, USA. Electronic address: routman@uabmc.edu.
Kenneth G SaagMedicine - Immunology and Rheumatology, Vice Chair, Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, 35294-2182, USA. Electronic address: ksaag@uabmc.edu.
University of Alabama at Birmingham · USMemorial Hermann · US

Funding

Activating Patients to Reduce Osteoporosis (APROPOS)R01AR060240 · NIAMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI SAAG, KENNETH G · 2011 to 2015
$3.2M
Genetic Architecture of Rheumatoid Arthritis in African-AmericansK23AR062100 · NIAMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DANILA, MARIA IOANA · 2012 to 2016
$674k
NIAMS NIH HHS K23 AR062100NIAMS NIH HHS R01 AR060240
6 · The paper itself

Abstract

backgroundOsteoporosis medication use is suboptimal. Simple interventions personalized to a patients' stage of readiness are needed to encourage osteoporosis medication use.

objectivesTo estimate interrelationships of sociodemographic factors, perceived fracture risk, health literacy, receipt of medication information, medication trust and readiness to use osteoporosis medication; and apply observed relationships to inform design specifications for a clinical decision support application that can be used for personalized patient counseling.

methodsData from a national sample of older women (n = 1759) with self-reported history of fractures and no current use of osteoporosis medication treatment were used to estimate an acceptable path model that describes associations among key sociodemographic characteristics, health literacy, perceived fracture risk, receipt of osteoporosis medication information within the past year, trust in osteoporosis medications, and readiness to use osteoporosis medication. Path model results were used to inform an application for personalized patient counseling that can be easily integrated into clinical decision support systems.

resultsIncreased age (β = 0.13), trust for medications (β = 0.12), higher perceived fracture risk (β = 0.21), and having received medication information within the past year (β = 0.21) were all positively associated with readiness to use osteoporosis medication (p < 0.0001). Whereas, health literacy (β = -0.09) was inversely associated with readiness to use osteoporosis medication (p < 0.0001). Using these results, a brief 6-item question set was constructed for simple integration into clinical decision support applications. Patient responses were used to inform a provider dashboard that integrates a patient's stage of readiness for osteoporosis medication use, predictors of readiness, and personalized counseling points appropriate to their stage of readiness.

conclusionContent of counseling strategies must be aligned with a patient's stage of readiness to use treatment. Path modeling can be effectively used to identify factors for inclusion in an evidenced-based clinical decision support application designed to assist providers with personalized patient counseling and osteoporosis medication use decisions.

Indexed as

Decision Support Systems, ClinicalFractures, BoneHealth LiteracyOsteoporosisAgedFemaleHumansMedication AdherenceTrustClinical decision supportMedication adherenceOsteoporosisPath modelingStage of readiness

Identifiers

PMID33011082
PMCPMC9261504
OpenAlexW3088009624

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.