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BMC Health Services Research
Published in: BMC Health Services Research 1/2016

Open Access 01-12-2016 | Study protocol

Show Me My Health Plans: a study protocol of a randomized trial testing a decision support tool for the federal health insurance marketplace in Missouri

Authors: Mary C. Politi, Abigail R. Barker, Kimberly A. Kaphingst, Timothy McBride, Enbal Shacham, Carey S. Kebodeaux

Published in: BMC Health Services Research | Issue 1/2016

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Abstract

Background

The implementation of the ACA has improved access to quality health insurance, a necessary first step to improving health outcomes. However, access must be supplemented by education to help individuals make informed choices for plans that meet their individual financial and health needs.

Methods/Design

Drawing on a model of information processing and on prior research, we developed a health insurance decision support tool called Show Me My Health Plans. Developed with extensive stakeholder input, the current tool (1) simplifies information through plain language and graphics in an educational component; (2) assesses and reviews knowledge interactively to ensure comprehension of key material; (3) incorporates individual and/or family health status to personalize out-of-pocket cost estimates; (4) assesses preferences for plan features; and (5) helps individuals weigh information appropriate to their interests and needs through a summary page with “good fit” plans generated from a tailored algorithm. The current study will evaluate whether the online decision support tool improves health insurance decisions compared to a usual care condition (the healthcare.gov marketplace website). The trial will include 362 individuals (181 in each group) from rural, suburban, and urban settings within a 90 mile radius around St. Louis. Eligibility criteria includes English-speaking individuals 18–64 years old who are eligible for the ACA marketplace plans. They will be computer randomized to view the intervention or usual care condition.

Discussion

Presenting individuals with options that they can understand tailored to their needs and preferences could help improve decision quality. By helping individuals narrow down the complexity of health insurance plan options, decision support tools such as this one could prepare individuals to better navigate enrollment in a plan that meets their individual needs. The randomized trial was registered in clinicaltrials.gov (NCT02522624) on August 6, 2015.
Literature
1.
2.
3.
Long SK, Kenney GM, Zuckerman S, et al. The health reform monitoring survey: Addressing data gaps to provide timely insights into the Affordable Care Act. Health Aff. 2014;33:161–7.CrossRef
4.
Barnes AJ HY, Rice T. Determinants of coverage decisions in health insurance marketplaces: consumers’ decision-making abilities and the amoung of information in their choice environment. Health Serv Res. 2015;50(1):58–80.
5.
Cohen RM, ME. Health Insurance Coverage: early release of estimates from the national health interview survey, January-March 2015. In National Health Interview Survey. Center for Disease Control 2015.
6.
Politi MC, Kaphingst KA, Kreuter M, et al. Knowledge of health insurance terminology and details among the uninsured. Med Care Res Rev. 2014;71:85–98.CrossRefPubMed
7.
Long SKS, A; Politi MC. Low levels of self-reported literacy and numeracy create barriers to obtaining and using health insurance coverage. In The Urban Institute Health Reform Monitoring Survey Policy Brief. 2014.
8.
9.
Politi MC, Kaphingst KA, Liu JE, Perkins H, Furtado K, Kreuter MW, Shacham E, McBride T. A randomized trial examining three strategies for supporting health insurance decisions among the uninsured. Med Decis Making. 2015. [Epub ahead of print].
10.
Hibbard JH, Slovic P, Jewett JJ. Informing consumer decisions in health care: Implications from decision-making research. Milbank Q. 1997;75:395–414.PubMedCentralCrossRefPubMed
11.
Peters E, Dieckmann N, Dixon A, et al. Less is more in presenting quality information to consumers. Med Care Res Rev. 2007;64:169–90.CrossRefPubMed
12.
Hibbard JH, Jewett JJ, Engelmann S, Tusler M. Can Medicare beneficiaries make informed choices? Health Aff. 1998;17:181–93.CrossRef
13.
von Glahn T. Plan Choice Decision Support. New Jersey, USA: Robert Wood Johnson Foundation; 2015.
14.
Hibbard JH, Peters E. Supporting informed consumer health care decisions: data presentation approaches that facilitate the use of information in choice. Annu Rev Public Health. 2003;24:413–33.CrossRefPubMed
15.
16.
17.
Cranney A, O’Connor AM, Jacobsen MJ, et al. Development and pilot testing of a decision aid for postmenopausal women with osteoporosis. Patient Educ Couns. 2002;47:247–55.CrossRef
18.
Deen D, Lu WH, Weintraub MR, et al. The impact of different modalities for activating patients in a community health center setting. Patient Educ Couns. 2012;89:178–83.CrossRefPubMed
19.
Torres RY, Marks R. Relationships among health literacy, knowledge about hormone therapy, self-efficacy, and decision-making among postmenopausal health. J Health Commun. 2009;14:43–55.CrossRefPubMed
20.
O’Connor AM. Validation of a decisional conflict scale. Med Decis Mak. 1995;15:25–30.CrossRef
21.
22.
Song MK, Sereika SM. An evaluation of the Decisional Conflict Scale for measuring the quality of end-of-life decision making. Patient Educ Couns. 2006;61:397–404.CrossRefPubMed
23.
Katapodi MC, Munro ML, Pierce PF, Williams RA. Psychometric testing of the decisional conflict scale: genetic testing hereditary breast and ovarian cancer. Nurs Res. 2011;60:368–77.PubMedCentralCrossRefPubMed
24.
O’Donnell S, Cranney A, Jacobsen MJ, et al. Understanding and overcoming the barriers of implementing patient decision aids in clinical practice. J Eval Clin Pract. 2006;12:174–81.CrossRefPubMed
Metadata
Title
Show Me My Health Plans: a study protocol of a randomized trial testing a decision support tool for the federal health insurance marketplace in Missouri
Authors
Mary C. Politi
Abigail R. Barker
Kimberly A. Kaphingst
Timothy McBride
Enbal Shacham
Carey S. Kebodeaux
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Health Services Research / Issue 1/2016
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/s12913-016-1314-9

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