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

Informed Decision-making for Health Insurance Enrollment: Survey Study

Background

Health insurance enrollment is a difficult financial decision with large health impacts. Challenges such as low health insurance literacy and lack of knowledge about choosing a plan further complicate this decision-making process. Therefore, to support consumers in their choice of a health insurance plan, it is essential to understand how individuals go about making this decision.

Objective

This study aims to understand the sources of information used by individuals to support their employer-provided health insurance enrollment decisions. It seeks to describe how individual descriptive factors lead to choosing a particular type of information source.

Methods

An introduction was presented on health insurance plan selection and the sources of information used to support these decisions from the 1980s to the present. Subsequently, an electronic survey of 151 full-time faculty and staff members was conducted. The survey consisted of four sections: demographics, sources of information, health insurance literacy, and technology acceptance. Descriptive statistics were used to show the demographic characteristics of the 126 eligible respondents and to study the response behaviors in the remaining survey sections. Proportion data analysis was performed using the Cochran-Armitage trend test to understand the strength of the association between our variables and the types of sources used by the respondents.

Results

In terms of demographics, most of the respondents were women (103/126, 81.7%), represented a small household (1-2 persons; 87/126, 69%), and used their insurance 3-12 times a year (52/126, 41.3%). They assessed themselves as having moderate to high health insurance literacy and high acceptance of technology. The most selected and top-ranked sources were Official employer or state websites and Official Human Resources Virtual Benefits Counselor Alex. From our data analysis, we found that the use of official primary sources was constant across age groups and health insurance use groups. Meanwhile, the use of friends or family as a primary source slightly decreased as age and use increased.

Conclusions

In this exploratory study, we identified the main sources of health insurance information among full-time employees from a large state university and found that most of the respondents needed 2-3 sources to gather all the information that they desired. We also studied and identified the relationships between individual factors (such as age, gender, and literacy) and 2 dependent variables on the types of primary sources of information. We encountered several limitations, which will be addressed in future studies.

Improving Cancer Patients' Insurance Choices (I Can PIC): A Randomized Trial of a Personalized Health Insurance Decision Aid

BACKGROUND

Many cancer survivors struggle to choose a health insurance plan that meets their needs because of high costs, limited health insurance literacy, and lack of decision support. We developed a web-based decision aid, Improving Cancer Patients' Insurance Choices (I Can PIC), and evaluated it in a randomized trial.

MATERIALS AND METHODS

Eligible individuals (18-64 years, diagnosed with cancer for ≤5 years, English-speaking, not Medicaid or Medicare eligible) were randomized to I Can PIC or an attention control health insurance worksheet. Primary outcomes included health insurance knowledge, decisional conflict, and decision self-efficacy after completing I Can PIC or the control. Secondary outcomes included knowledge, decisional conflict, decision self-efficacy, health insurance literacy, financial toxicity, and delayed care at a 3-6-month follow-up.

RESULTS

A total of 263 of 335 eligible participants (79%) consented and were randomized; 206 (73%) completed the initial survey (106 in I Can PIC; 100 in the control), and 180 (87%) completed a 3-6 month follow-up. After viewing I Can PIC or the control, health insurance knowledge and a health insurance literacy item assessing confidence understanding health insurance were higher in the I Can PIC group. At follow-up, the I Can PIC group retained higher knowledge than the control; confidence understanding health insurance was not reassessed. There were no significant differences between groups in other outcomes. Results did not change when controlling for health literacy and employment. Both groups reported having limited health insurance options.

CONCLUSION

I Can PIC can improve cancer survivors' health insurance knowledge and confidence using health insurance. System-level interventions are needed to lower financial toxicity and help patients manage care costs.

IMPLICATIONS FOR PRACTICE

Inadequate health insurance compromises cancer treatment and impacts overall and cancer-specific mortality. Uninsured or underinsured survivors report fewer recommended cancer screenings and may delay or avoid needed follow-up cancer care because of costs. Even those with adequate insurance report difficulty managing care costs. Health insurance decision support and resources to help manage care costs are thus paramount to cancer survivors' health and care management. We developed a web-based decision aid, Improving Cancer Patients' Insurance Choices (I Can PIC), and evaluated it in a randomized trial. I Can PIC provides health insurance information, supports patients through managing care costs, offers a list of financial and emotional support resources, and provides a personalized cost estimate of annual health care expenses across plan types.

The relation between selective contracting and healthcare expenditures in private health insurance plans in the United States

Many healthcare systems, including The Netherlands, Germany and Switzerland, have incorporated elements of managed competition, whereby insurers compete for enrollees in a marketplace organized or facilitated by a government or governing entity. In these countries, managed competition was introduced with the idea that the system would contain cost growth while maximizing value for consumers and employers. An important mechanism to control costs is selective contracting: the process of contracting providers into a network and offer insurance packages with varying levels of provider coverage. In these systems, enrollees are expected to choose lower cost plans which offer access to only contracted providers in the network. The questions is, however, if restricting provider choice leads to reduced healthcare expenditures. In the United States, enrollees often have a choice between plans with restricted networks of providers and plans that offer more provider choice, where care outside the contracted network of providers is (partly) covered. The purpose of this study is to understand whether insurance plans with restrictions on provider access in the United States have reduced healthcare expenditures and to identify the mechanism by which that reduction occurred. We used data from the Medical Expenditure Panel Survey (MEPS), a nationally representative sample of families and individuals. We estimated expenditures for enrollees in restricted network plans using two-part models and generalized linear models. We found that restricted network plans, on average, save $761 per enrollee. Our results suggest that cost savings due to restricted network plans are largely a result of price reductions rather than utilization reductions, although both play a role in cost savings. When introducing reforms shifting from a supply-oriented to a demand-oriented health care system, these findings might be worth considering by other countries.

Association Between Health Insurance Literacy and Avoidance of Health Care Services Owing to Cost

IMPORTANCE

Navigating health insurance and health care choices requires considerable health insurance literacy. Although recommended preventive services are exempt from out-of-pocket costs under the Affordable Care Act, many people may remain unaware of this provision and its effect on their required payment. Little is known about the association between individuals' health insurance literacy and their use of preventive or nonpreventive health care services.

OBJECTIVE

To assess the association between health insurance literacy and self-reported avoidance of health care services owing to cost.

DESIGN, SETTING, AND PARTICIPANTS

In this survey study, a US national, geographically diverse, nonprobability sample of 506 US residents aged 18 years or older with current health insurance coverage was recruited to participate in an online survey between February 22 and 23, 2016.

MAIN OUTCOMES AND MEASURES

The validated 21-item Health Insurance Literacy Measure (HILM) assessed individuals' self-rated confidence in selecting and using health insurance (score range, 0-84, with higher scores indicating greater levels of health insurance literacy). Dependent variables included delayed or foregone preventive and nonpreventive services in the past 12 months owing to perceived costs, and preventive and nonpreventive use of services. Covariates included age, sex, race/ethnicity, income, educational level, high-deductible health insurance plan, health literacy, numeracy, and chronic health conditions. Analyses included descriptive statistics and bivariate and multivariable logistic regression.

RESULTS

A total of 506 of 511 participants who began the survey completed it (participation rate, 99.0%). Of the 506 participants, 339 (67.0%) were younger than 35 years (mean [SD] age, 34 [10.4] years), 228 (45.1%) were women, 406 of 504 who reported race (80.6%) were white, and 245 (48.4%) attended college for 4 or more years. A total of 228 participants (45.1%) had 1 or more chronic health condition, 361 of 500 (72.2%) who responded to the survey item had seen a physician in the outpatient setting in the past 12 months, and 446 of the 501 (89.0%) who responded to the survey item had their health insurance plan for 12 or more months. One hundred fifty respondents (29.6%) reported having delayed or foregone care because of cost. The mean (SD) HILM score was 63.5 (12.3). In multivariable logistic regression, each 12-point increase in HILM score was associated with a lower likelihood of both delayed or foregone preventive care (adjusted odds ratio [aOR], 0.61; 95% CI, 0.48-0.78) and delayed or foregone nonpreventive care (aOR, 0.71; 95% CI, 0.55-0.91).

CONCLUSIONS AND RELEVANCE

This study's findings suggest that lower health insurance literacy may be associated with greater avoidance of both preventive and nonpreventive services. It appears that to improve appropriate use of recommended health care services, including preventive health services, clinicians, health plans, and policymakers may need to communicate health insurance concepts in accessible ways regardless of individuals' health insurance literacy. Plain language communication may be able to improve patients' understanding of services exempt from out-of-pocket costs.

Dissemination of a Web-Based Tool for Supporting Health Insurance Plan Decisions (Show Me Health Plans): Cross-Sectional Observational Study

Background

The rate of uninsured people has decreased dramatically since the Affordable Care Act was passed. To make an informed decision, consumers need assistance to understand the advantages and disadvantages of health insurance plans. The Show Me Health Plans Web-based decision support tool was developed to improve the quality of health insurance selection. In response to the promising effectiveness of Show Me Health Plans in a randomized controlled trial (RCT) and the growing need for Web-based health insurance decision support, the study team used expert recommendations for dissemination and implementation, engaged external stakeholders, and made the Show Me Health Plans tool available to the public.

Objective

The purpose of this study was to implement the public dissemination of the Show Me Health Plans tool in the state of Missouri and to evaluate its impact compared to the RCT.

Methods

This study used a cross-sectional observational design. Dissemination phase users were compared with users in the RCT study across the same outcome measures. Time spent using the Show Me Health Plans tool, knowledge, importance rating of 9 health insurance features, and intended plan choice match with algorithm predictions were examined.

Results

During the dissemination phase (November 2016 to January 2017), 10,180 individuals visited the SMHP website, and the 1069 users who stayed on the tool for more than one second were included in our analyses. Dissemination phase users were more likely to live outside St. Louis City or County (P<.001), were less likely to be below the federal poverty level (P<.001), and had a higher income (P=.03). Overall, Show Me Health Plans users from St. Louis City or County spent more time on the Show Me Health Plans tool than those from other Missouri counties (P=.04); this association was not observed in the RCT. Total time spent on the tool was not correlated with knowledge scores, which were associated with lower poverty levels (P=.009). The users from the RCT phase were more likely to select an insurance plan that matched the tool’s recommendations (P<.001) compared with the dissemination phase users.

Conclusions

The study suggests that a higher income population may be more likely to seek information and online help when making a health insurance plan decision. We found that Show Me Health Plans users in the dissemination phase were more selective in the information they reviewed. This study illustrates one way of disseminating and implementing an empirically tested Web-based decision aid tool. Distributing Web-based tools is feasible and may attract a large number of potential users, educate them on basic health insurance information, and make recommendations based on personal information and preference. However, using Web-based tools may differ according to the demographics of the general public compared to research study participants.

A Comparison Between Subjective and Objective Methods of Predicting Health Care Expenses to Support Consumers' Health Insurance Plan Choice

Objective. Numerous electronic tools help consumers select health insurance plans based on their estimated health care utilization. However, the best way to personalize these tools is unknown. The purpose of this study was to compare two common methods of personalizing health insurance plan displays: 1) quantitative healthcare utilization predictions using nationally representative Medical Expenditure Panel Survey (MEPS) data and 2) subjective-health status predictions. We also explored their relations to self-reported health care utilization. Methods. Secondary data analysis was conducted with responses from 327 adults under age 65 considering health insurance enrollment in the Affordable Care Act (ACA) marketplace. Participants were asked to report their subjective health, health conditions, and demographic information. MEPS data were used to estimate predicted annual expenditures based on age, gender, and reported health conditions. Self-reported health care utilization was obtained for 120 participants at a 1-year follow-up. Results. MEPS-based predictions and subjective-health status were related (P < 0.0001). However, MEPS-predicted ranges within subjective-health categories were large. Subjective health was a less reliable predictor of expenses among older adults (age × subjective health, P = 0.04). Neither significantly related to subsequent self-reported health care utilization (P = 0.18, P = 0.92, respectively). Conclusions. Because MEPS data are nationally representative, they may approximate utilization better than subjective health, particularly among older adults. However, approximating health care utilization is difficult, especially among newly insured. Findings have implications for health insurance decision support tools that personalize plan displays based on cost estimates.

Show Me My Health Plans: Using a Decision Aid to Improve Decisions in the Federal Health Insurance Marketplace

Introduction: Since the Affordable Care Act was passed, more than 12 million individuals have enrolled in the health insurance marketplace. Without support, many struggle to make an informed plan choice that meets their health and financial needs. Methods: We designed and evaluated a decision aid, Show Me My Health Plans (SMHP), that provides education, preference assessment, and an annual out-of-pocket cost calculator with plan recommendations produced by a tailored, risk-adjusted algorithm incorporating age, gender, and health status. We evaluated whether SMHP compared to HealthCare.gov improved health insurance decision quality and the match between plan choice, needs, and preferences among 328 Missourians enrolling in the marketplace. Results: Participants who used SMHP had higher health insurance knowledge (LS-Mean = 78 vs. 62; P < 0.001), decision self-efficacy (LS-Mean = 83 vs. 75; P < 0.002), confidence in their choice (LS-Mean = 3.5 vs. 2.9; P < 0.001), and improved health insurance literacy (odds ratio = 2.52, P < 0.001) compared to participants using HealthCare.gov. Those using SMHP were 10.3 times more likely to select a silver- or gold-tier plan (P < 0.0001). Discussion: SMHP can improve health insurance decision quality and the odds that consumers select an insurance plan with coverage likely needed to meet their health needs. This study represents a unique context through which to apply principles of decision support to improve health insurance choices.