Abstract
Purpose:
To determine the effectiveness of an educational intervention in improving health insurance literacy and utilization of in vitro fertilization insurance benefits
Methods:
Randomized controlled trial, with 217 participants randomized in a 2:1 fashion to receive either an educational intervention or university-provided information sheet. Participants were aged 18 to 50 years, intending to conceive within a year, eligible for employee-offered health insurance coverage. The primary outcome was health insurance literacy. Secondary outcomes included comparing health insurance plans, plan selection, in vitro fertilization service utilization, benefit utilization, out-of-pocket costs and acceptability, appropriateness and feasibility of the intervention materials. Semi-structured interviews evaluated participant experiences with intervention materials, plan selection, benefit utilization, in vitro fertilization services and out-of-pocket costs.
Results:
Both groups reported low confidence using their health insurance (intervention: 1.00 [SD=0.90], usual care: 0.74 [SD=0.76], β=0.26, 95% CI −0.09, 0.62) and moderately high confidence being proactive when using their health insurance (intervention: 2.26 [SD=0.86], usual care: 2.47 [SD=0.58], β=−0.20, 95% CI −0.52, 0.11). Utilization of in vitro fertilization services was similar between groups (intervention: 40% [10/25], usual care: 45% [9/20]; p=0.35). Use of insurance to cover these services did not differ between groups (intervention: 36% [9/25], usual care: 40% [8/20]; p=0.78), and both groups experienced moderate out-of-pocket costs. Qualitative data revealed challenges in benefit utilization in both groups.
Conclusions:
Despite the educational intervention not significantly improving health insurance literacy or in vitro fertilization benefit utilization, our findings suggest that additional factors may influence navigation of IVF health insurance benefits and utilization to IVF services.
Trial registration number:
Trial registration date: December 12, 2022, retrospectively registered
Date of first patient’s enrollment: November 10, 2022
Keywords: Health insurance literacy, Health insurance benefit, In vitro fertilization, Health Education, Health services accessibility
Capsule:
An educational intervention designed for participants utilizing a new in vitro fertilization insurance benefit did not significantly improve health insurance literacy or benefit utilization.
Introduction
Infertility is a treatable condition affecting up to 15% of the U.S. population [1] [2]; yet, most insurance plans do not cover in-vitro fertilization (IVF), one of the effective and evidence-based treatment options. Out-of-pocket costs for a single IVF cycle in the United States is estimated at a median of $19,000, making it inaccessible for many individuals and leading to disparities in fertility care [3] [4]. States that mandate infertility coverage, particularly those with comprehensive requirements for IVF coverage (i.e., minimal eligibility restrictions, exemptions, and lifetime limits) have improved access to IVF by reducing out-of-pocket costs and increasing utilization [5] [6]. Comprehensive IVF insurance coverage has the potential to reduce financial stress, allows for better patient experiences, lower treatment discontinuation rates, improves live birth rates and improves access to evidence-based infertility treatments such as single embryo transfers [6] [7] [8].
In states without mandated infertility coverage, individuals must rely on their employers’ benevolence to offer health insurance infertility benefits. While infertility treatment represents a small portion of overall healthcare costs, cost-burden analysis has estimated that adding some fertility coverage could increase overall premiums by only 0.12–0.95% for affected plans [6]. For employers, the provision of an IVF insurance benefit can provide significant health and financial advantages to current employees, and serve as a valuable incentive for attracting new employees [9] [10]. Yet for employees, having access to an IVF insurance benefit alone is not sufficient as adequate health insurance literacy is essential for proper use of available health insurance benefits for healthcare services [6] [11].
Health insurance literacy refers to an individual’s ability to seek, obtain, and effectively utilize health insurance [12]. This skill is essential for making the most of healthcare services [13]. Individuals need to have a good understanding of health insurance basics, so they can comprehend the differences among various health plans and choose the best one based on their medical needs and financial situation. When people have low health insurance literacy, they may be discouraged from seeking care due to lack of confidence using health insurance or concerns about cost. Conversely, those with high health insurance literacy tend to use healthcare services appropriately [11]. Many insured adults encounter challenges when trying to navigate their insurance plans, such as understanding cost-sharing, accessing in-network providers and facilities, identifying benefits, dealing with delays in prior authorization, and managing denied claims [14] [15]. Previous studies among young cancer survivors indicate that a patient navigator-delivered health insurance program can successfully provide education on health insurance policies and coverage options and lead to improvements in health insurance literacy [16] [17] [18] [19]. To our knowledge, health insurance literacy in the context of IVF care has not been studied.
During the 2023 open enrollment period, a large public research university system introduced an expanded insurance benefit for IVF to eligible faculty and staff across all five insurance plans. The plans included three self-funded Preferred Provider Organizations (PPOs), a university-affiliated flex-funded Health Maintenance Organization (HMO), and a fully insured closed-system private HMO. Although all five plans were advertised as having a 50% co-insurance for up to two IVF cycles as part of infertility treatment, our team’s pre-study assessment identified mixed information regarding the plans’ coverage of advertised infertility services, related out-of-pocket costs and IVF network coverage. Based on these identified gaps in knowledge and the core principles of health insurance literacy, we designed an educational intervention to enhance employees’ confidence in selecting insurance plans and utilizing their new IVF insurance benefits. We conducted a randomized controlled trial with the hypothesis that the educational intervention would lead to improved health insurance literacy and utilization of IVF insurance benefits and be more acceptable than the standard university-provided materials.
Materials & Methods
This randomized controlled trial was conducted over 13 months at a public research university, with enrollment starting in November 2022 and participant assessments completed by December 2023. The trial is registered on ClinicalTrials.gov (NCT Identifier: 05663645) and was approved by the University of California San Diego Institutional Review Board on November 4, 2022. For this trial, we adhered to the guidelines from the Consolidated Standards of Reporting Trials [20]. Details of the study protocol have been published previously [21].
Intervention
The usual care materials included a one-page guide [21] from the university describing the expanded IVF benefit in a few sentences and providing links to 1) the general benefits enrollment website; 2) virtual benefits counsellor chatbot; and 3) a virtual benefits office hour. Participants in the usual care condition received this guide.
Prior to the start of the 2023 open enrollment period, the study team reviewed the university provided one-page guide on the expanded IVF benefit and the general benefits enrollment website, contacted member services at each of the five health plans and reviewed their respective websites to compile details about each plan’s coverage information (e.g., premiums, deductibles, etc.) and key insurance basic terms to incorporate into the educational guide. Next, grounded in health behavior constructs from the Integrated Behavioral Model [22] and Andersen’s Model for Health Services Utilization [23], the educational guide was developed to target cognitive and self-efficacy factors with the goal of improving health insurance literacy and promoting utilization of the new infertility benefit. The educational guide was presented in English and Spanish at a 7.6 Flesch-Kincaid grade reading level and included: 1) An introduction to the new infertility benefit and key insurance terms (4 pages); 2) A comparison of premiums and deductibles across the five insurance plans tailored to the employee’s income bracket (1 page); 3) A worksheet for understanding premiums, deductibles and out-of-pocket costs for IVF care (3 pages); and 4) Guidance on finding in-network IVF providers (1 page). Participants in the intervention group received this educational guide along with usual care materials [21].
Trial design
During the 2023 open enrollment insurance selection period in November 2022, all faculty and staff at the university were invited to participate in the study. We sent a recruitment email to those identified through the institutional directory three weeks before the health plan selection was due. Interested individuals completed an eligibility screening online, and eligible individuals completed the online consent and baseline questionnaire. We randomized participants to the intervention or usual care condition in a 2:1 ratio. Only participants were blinded to the randomization.
After completing the baseline questionnaire, participants were emailed educational materials based on their assigned group. Participants were emailed follow-up questionnaires one month after open enrollment (Follow-up 1) and seven months post-enrollment (Follow-up 2). At the start of Follow-up 2, we conducted semi-structured interviews about participants’ IVF benefit utilization and satisfaction with the benefit and intervention materials. We used purposeful sampling to recruit equal numbers of participants from each health plan and exposure arm.
Participants
The inclusion criteria were being a university staff or faculty member of reproductive age (18–50 years), with the intention to conceive within one year (to identify those with higher likelihood of utilizing IVF), eligible for employee-offered health insurance plan, and with primary language English or Spanish.
Primary Outcome
The primary outcome was health insurance literacy at Follow-up 2. This was measured by nine items from the Health Insurance Literacy Measure [24] assessing two constructs of health insurance literacy: 1) confidence using health insurance plans (5 items) and 2) confidence being proactive when using health insurance plans (4 items), collected at baseline and Follow-up 2. Items for both constructs were scored from 0 (not at all confident) to 3 (very confident) with higher scores indicating better health insurance literacy. Questions were tailored to assess IVF services.
Secondary Outcomes
At Follow-up 1, we assessed: 1) confidence comparing health insurance plans measured by six items from the Health Insurance Literacy Measure [24]; 2) confidence understanding basic health insurance terms (e.g., co-insurance, co-payment, etc.); 3) acceptability, appropriateness and feasibility of educational materials, measured via the Intervention Appropriateness Measure, Acceptability of Intervention Measure, and Feasibility of Intervention Measure [25] and satisfaction with intervention; 4) health plan selection and satisfaction with plan selection; and 5) resources contacted to obtain information on the IVF benefit during open enrollment, including time spent and satisfaction with the resources.
At Follow-up 2, we assessed: 1) confidence understanding basic health insurance terms; 2) self-reported IVF utilization in 2023; 3) self-reported utilization of health insurance for IVF services prior to 2023; 4) out-of-pocket expenses related to IVF services in 2023 and satisfaction with IVF benefit.
Qualitative Outcomes
Open-ended questions in the surveys were asked to evaluate the educational materials and interactions with health plan members at Follow-up 1 and the IVF insurance benefit and service utilization at Follow-up 2. Semi-structured interviews explored 1) the perceived impact of the educational intervention in terms of the participants’ likes, dislikes, satisfaction with the materials and ways to improve them; 2) participant experiences with selecting a health plan during open enrollment, IVF benefit utilization, IVF services and related out-of-pocket costs.
Sample Size
Our a priori sample size of 200 participants was based on the feasibility of this pilot trial. Accounting for the 2:1 allocation ratio, we determined that a minimum sample size of 192 would provide 90% power at a two-tailed significance level of 0.05 to detect a medium effect size. The target accrual goal for semi-structured interviews was 40 participants or until saturation was attained. Saturation is the point at which additional data collection does not yield new insights and is the gold standard for sampling [26]. We used purposeful sampling to recruit participants from each health plan and exposure arm, and we reached saturation at 19 participants.
Randomization
Participants were randomized in a 2:1 fashion to the intervention versus usual care condition generated by a random number sequence in R version 4.2.2, 2022. Participants were blinded to intervention assignments.
Statistical Analyses
All primary analysis was intention-to-treat. We summarized continuous variables using descriptive statistics to determine the data spread, reported as standard deviations. For normally distributed data, means were calculated, otherwise medians were calculated. Categorical variables were summarized as frequencies and proportions. Baseline characteristics and outcomes were compared using Student’s t-test, Wilcoxon rank sum test, Chi-square test of proportions, and Fisher’s Exact tests, as appropriate. We estimated effect sizes using unadjusted logistic and linear regression models. For outcomes with repeated measures, we employed a simplified fixed-effects linear model when singular fit was observed in the linear mixed-effect model.
To address missing data at Follow-up 1 and 2, we evaluated data losses by performing missingness and sensitivity analyses. We determined the type of missingness in the dataset by comparing baseline variables between participants with complete and incomplete data, and by study arm. Sensitivity analysis with multiple imputation for completely random missing values was performed using the Multivariate Imputation by Chained Equation (MICE) package [27]. We used predictive mean matching to input missing values using fifty iterations to generate five imputed-datasets, which we pooled together to generate a single averaged value dataset for subsequent analysis [27]. Next, logistic regression analysis was used to compare imputed and original data results. All analysis were performed using R version 4.3.3, 2023.
We conducted a thematic analysis of qualitative data (open-ended survey responses and interviews) in MaxQDA software [28]. Two team members read each transcript to become familiar with the text and developed initial codes. Next, two team members independently coded three transcripts iteratively and discussed disagreements to create and refine the final codebook by consensus. Inductive (related to primary and secondary outcomes) and deductive [related to implementing IVF insurance benefits using the exploration, preparation, implementation, and sustainment (EPIS) framework [29] [30]] codes were applied to all transcripts using consensus coding (two coders independently coded each transcript and resolved discrepancies by consensus). Code summaries were developed that described the breadth and depth of each theme, and final themes and subthemes were generated. Following the taxonomy of mixed methods designs [29] [31], we integrated the qualitative and quantitative data by exposure group and health plans to better explain the process through which participants selected a health plan and accessed IVF benefits and to describe the effectiveness of the intervention.
Results
Baseline Characteristics
Email invitations were sent to 19,136 faculty and staff; 394 individuals expressed interest and were screened for eligibility. Of these, 217 completed the baseline questionnaire, with 142 randomized to the intervention group and 75 to the usual care group (Figure 1). Nineteen participants (14 interventions, 5 usual care) completed semi-structured interviews, at which point we reached saturation (no new themes identified). A total of 146 participants (67%) completed Follow-up 1, and 100 (46%) completed Follow-up 2. There were no significant differences in baseline characteristics between participants who completed the follow-ups and those lost to follow-up, except for household income and education level in the control group at Follow-up 1 and Follow-up 2, respectively (Supplemental Tables 1 and 2).
Figure 1:
CONSORT diagram
Baseline characteristics were similar between groups (Table 1). Forty-five percent of the study population were white, 29% Asian, 26% other races, and 18% Hispanic. Participants were predominantly female (81%), married (63%), and staff employees (72%). Mean gravidity was higher in females in the usual care group (intervention: 0.84 [SD=1.34], usual care: 1.45 [SD=1.81], p value=0.02). Mean parity was similar between groups (female intervention: 0.41 [SD=1.10], usual care: 0.48 [SD=0.75], p value=0.62; male intervention: 0.46 [SD=0.71], usual care: 0.47 [SD=0.83], p value=0.98). Participants in both groups had low confidence using health insurance (intervention: 1.06 out of 3.00 [SD=0.73], usual care: 0.98 out of 3.00 [SD=0.81], β=0.08, 95% CI −0.14, 0.29) and moderate confidence being proactive when using health insurance (intervention: 2.02 out of 3.00 [SD=0.69], usual care: 2.05 out of 3.00 [SD=0.69], β=−0.02, 95% CI −0.2, 0.2), with no significant differences between groups.
Table 1.
Baseline characteristics by group
| Total n = 217 |
Intervention n = 142 |
Usual care n = 75 |
P value | ||
|---|---|---|---|---|---|
| Demographics | |||||
|
Race
n (%) |
White | 98 (45.2) | 61 (43.0) | 37 (49.3) | 0.63 |
| Asian | 63 (29.0) | 42 (29.6) | 21 (28.0) | ||
| Other | 56 (25.8) | 39 (27.4) | 17 (22.7) | ||
|
Hispanic
n (%) |
Yes | 39 (18.0) | 27 (19.0) | 12 (16.0) | 0.58 |
|
Gender
n (%) |
Heterosexual | 189 (87.1) | 124 (87.3) | 65 (86.7) | 0.89 |
| LGBTQ/other | 28 (12.9) | 18 (12.7) | 10 (13.3) | ||
|
Sex
n (%) |
Female | 176 (81.1) | 116 (81.7) | 60 (80.0) | 0.86 |
| Male | 41 (18.9) | 26 (18.3) | 15 (20.0) | ||
|
Marital status
n (%) |
Married | 137 (63.1) | 89 (62.7) | 48 (64.0) | 0.67 |
| Partnered | 36 (16.6) | 22 (15.5) | 14 (18.7) | ||
| Single | 44 (20.3) | 31 (21.8) | 13 (17.3) | ||
|
Education
n (%) |
≤ College | 75 (34.1) | 48 (33.8) | 26 (34.7) | 0.90 |
| Postgraduate | 142 (65.9) | 94 (66.2) | 49 (65.3) | ||
|
Type of employee
n (%) |
Faculty | 58 (26.7) | 36 (25.4) | 22 (29.3) | 0.53 |
| Staff | 159 (73.3) | 106 (74.6) | 53 (70.7) | ||
|
Household income
n (%) |
Amount undisclosed | 46 (21.2) | 31 (21.8) | 15 (20.0) | 0.30 |
| ≤ $129,000 | 81 (37.3) | 57 (40.2) | 24 (32.0) | ||
| $129,001–194,000 | 42 (19.4) | 28 (19.7) | 14 (18.7) | ||
| ≥ $194,001 | 48 (22.1) | 26 (18.3) | 22 (29.3) | ||
| Fertility History | |||||
|
Gravidity
mean (SD) |
Female participants | 1.06 (1.54) | 0.84 (1.34) | 1.45 (1.81) | 0.02 |
|
Parity
mean (SD) |
Female participants | 0.44 (1.00) | 0.41 (1.10) | 0.48 (0.75) | 0.62 |
| Male participants | 0.46 (0.74) | 0.46 (0.71) | 0.47 (0.83) | 0.98 | |
|
Unsuccessful pregnancy attempt for 1 year
n (%) |
Female participants | 88 (40.6) | 58 (40.8) | 30 (40.0) | 0.87 |
| Male participants | 30 (13.8) | 17 (12.0) | 13 (17.3) | 0.70 | |
|
Prior fertility specialist visit
n (%) |
Yes | 130 (59.9) | 84 (59.7) | 46 (61.9) | 0.77 |
|
Prior IVF with frozen embryo transfer
n (%) |
Yes | 61 (28.1) | 40 (28.5) | 21 (28.3) | 1.00 |
Primary Outcome
At Follow-up 2, both groups reported low confidence using their health insurance (intervention: 1.00 out of 3.00 [SD =0.90], usual care: 0.74 out of 3.00 [SD=0.76], β=0.26, 95% CI −0.09, 0.62, p=0.15), and moderately high confidence being proactive when using their health insurance (intervention: 2.26 out of 3.00 [SD =0.86], usual care: 2.47 out of 3.00 [SD=0.58], β=−0.20, 95% CI −0.52, 0.11, p=0.21), with no significant differences between groups (Table 2). In interviews participants reported that although they contacted available resources (being proactive), some were unable to use their insurance successfully. One participant stated, “I called Health Net, and I asked them, “what facilities? What IVF centers are you going to approve for the 50% coverage?” And they came back and told me they didn’t know. I couldn’t wait around for an answer, essentially. So, I just moved forward with an alternative solution.” (Intervention, university-affiliated HMO). Sensitivity analysis using multiple imputation was consistent with these findings (Table 3). Accounting for repeated measures at baseline and Follow-up 2, there was no significant difference in health insurance literacy scores at both time points for confidence using (β=0.09, 95% CI −0.10, 0.28, p=0.36) and being proactive (β=−0.07, 95% CI −0.26, 0.14, p=0.52).
Table 2.
Primary outcome: Health insurance literacy at Follow-up 2
| Total n = 95 mean (SD) |
Intervention n = 58 mean (SD) |
Usual care n = 37 mean (SD) |
β [95% CI] |
P value | |
|---|---|---|---|---|---|
| Confidence using health insurance plans | 0.90 (0.86) | 1.00 (0.90) | 0.74 (0.76) | 0.26 [−0.09, 0.62] |
0.15 |
| Being proactive when using health insurance plans | 2.34 (0.76) | 2.26 (0.86) | 2.47 (0.58) | −0.20 [−0.52, 0.11] |
0.21 |
Response scale (0–3): 0 not at all confident, 1 slightly confident, 2 moderately confident, 3 very confident
Table 3.
Sensitivity analysis using multiple imputation for primary outcome: Health insurance literacy at Follow-up 2 by group
| Total n = 217 mean (SD) |
Intervention n = 142 mean (SD) |
Usual care n = 75 mean (SD) |
β [95% CI] |
P value | |
|---|---|---|---|---|---|
| Confidence using health insurance plans | 0.93 (0.65) | 0.97 (0.66) | 0.88 (0.62) | 0.09 [−0.10, 0.28] |
0.36 |
| Being proactive when using health insurance plans | 2.19 (0.63) | 2.16 (0.55) | 2.23 (0.67) | −0.07 [−0.26, 0.14] |
0.52 |
Response scale (0–3): 0 not at all confident, 1 slightly confident, 2 moderately confident, 3 very confident
Secondary Outcomes Follow-up 1
When assessing confidence comparing health insurance plans, both groups expressed moderate to high confidence in comparing health plans, with higher confidence in usual care group (intervention: mean=1.98 out of 3.00 [SD=0.81], usual care: mean=2.24 out of 3.00 [SD=0.61], β=−0.26, 95% CI −0.51, −0.01, p=0.04). Participants also expressed moderate confidence in comprehension of health insurance terms (intervention: cumulative mean=1.98 out of 3.00 [SD=0.75], usual care: cumulative mean=2.08 out of 3.00 [SD=0.75], β=−0.10, 95% CI −0.35, 0.16, p=0.45) (Table 4). For assessment of the educational materials, intervention participants rated the educational materials as more acceptable (β=0.30, 95% CI 0.03, 0.56, p=0.03), feasible (β=0.30, 95% CI 0.06, 0.58, p=0.02), and appropriate (β=0.32, 95% CI 0.05, 0.63, p=0.02) compared to the usual care group (Table 5). The intervention group also expressed higher satisfaction with the materials (91% vs. 67%, RR=2.14, 95% CI 1.23, 3.71, p=0.0005) (Table 4). While both groups highlighted the need for better dissemination of IVF benefit details, usual care participants specifically requested more education on health insurance terms and how these terms vary across the five health plan options (Table 6).
Table 4.
Secondary outcomes measured at Follow-up 1
| Total n = 146 |
Intervention n = 90 |
Usual care n = 56 |
β [95% CI] |
P value | |
|---|---|---|---|---|---|
|
Confidence comparing health insurance plans
*
mean (SD) |
2.08 (0.75) | 1.98 (0.81) | 2.24 (0.61) | −0.26 [−0.51, −0.01] |
0.04 |
|
Confidence understanding health insurance terms
*
mean (SD) |
2.02 (0.75) | 1.98 (0.75) | 2.08 (0.75) | −0.10 [−0.35, 0.16] |
0.45 |
| RR | |||||
|
University-affiliated HMO
n (%) |
75 (51.4) | 48 (53.3) | 27 (48.7) | ref | |
|
Private HMO
n (%) |
36 (24.6) | 21 (23.3) | 15 (27.1) | 0.91 [0.66, 1.26] |
0.68 |
|
Combined PPO
n (%) |
35 (24.0) | 21 (24.4) | 14 (25.2) | 0.95 [0.70, 1.30] |
0.83 |
|
No contact of resources prior to health plan selection
n (%) |
97 (66.4) | 62 (68.9) | 35 (62.5) | 1.10 [0.83, 1.46] |
0.59 |
|
Contact health insurance plan
n (%) |
40 (27.4) | 23 (25.6) | 17 (30.4) | 0.90 [0.67, 1.22] |
0.57 |
|
Contact fertility clinic n (%) |
18 (12.3) | 11 (12.2) | 7 (12.5) | 0.99 [0.67, 1.46] |
1.00 |
|
Satisfied with the process of selecting health insurance plan
n (%) |
128 (87.7) | 80 (89.8) | 48 (86.6) | 1.13 [0.73, 1.74] |
0.61 |
|
Satisfied with the educational materials that you were provided as part of the study
n (%) |
118 (80.8) | 81 (90.9) | 37 (66.7) | 2.14 [1.23, 3.71] |
0.0005 |
Response scale (0–3): 0 not at all confident, 1 slightly confident, 2 moderately confident, 3 very confident
Table 5.
Intervention Rating at Follow-up 1
| Educational material was: | Total n = 138 mean (SD) |
Intervention n = 86 mean (SD) |
Usual care n = 53 mean (SD) |
β [95% CI] |
P value |
|---|---|---|---|---|---|
| Acceptable | 2.73 (0.78) | 2.84 (0.68) | 2.54 (0.88) | 0.30 [0.03, 0.56] |
0.03 |
| Feasible | 2.69 (0.77) | 2.81 (0.66) | 2.49 (0.89) | 0.32 [0.06, 0.58] |
0.02 |
| Appropriate | 2.67 (0.81) | 2.79 (0.74) | 2.47 (0.88) | 0.32 [0.05, 0.63] |
0.02 |
Response scale (0–4): 0 completely disagree, 1 disagree, 2 neither agree nor disagree, 3 agree, 4 completely agree
Table 6.
Qualitative findings (n=19)
| Topic | Theme(s) | Quote(s) |
|---|---|---|
| Health insurance plan contact | Participants who expressed confidence advocating for themselves were largely dissatisfied with their contact experience. | “I called [health plan], and I asked them. I said, ‘What facilities? What IVF centers are you going to approve for the 50% coverage?’ And they came back and told me they didn’t know. I couldn’t wait around for an answer, essentially. So, I just moved forward with an alternative solution.” (Intervention, University-affiliated HMO) “It was so glaring that even when you called, they were looking at the exact same thing [evidence of coverage] that I was looking at. It wasn’t like they had additional knowledge.” (Intervention, PPO). |
| Contacting health plans did not help determine which of the five plans offered the best IVF coverage. | “They (Health plan) weren’t able to answer any of my questions, and so ultimately, I ended up going out of state for my IVF because it was cheaper. And I couldn’t figure out on how to use it in San Diego.” (Intervention, University-affiliated HMO) “I have a relationship with my doctor, I have a relationship with my pharmacy, and they wouldn’t tell me whether they would be included or not. So, when I call, I said, ‘Who will my doctor be?’ they said, ‘We won’t know until January 1.’ Which I thought was an odd answer. And the same thing with my pharmacy. I said, ‘Can I still go to the pharmacy that I’ve already built a relationship with?’ They said they don’t know, and they won’t know until later.” (Intervention, PPO) “I think they need to be clearer about which policy includes IVF benefits, and which does not and what is the different payment policies in terms of you know, out-of-pocket and co-pay?” (Usual care, PPO) |
|
| Educational materials | Participants stressed the need for better awareness of the new IVF benefit. | “I really would not have encountered [the new IVF benefit announcement] if it wasn’t that I opened the email from the IVF study. And so, I think it would be great if it was part of the Benefits Office rollout, and it was, like, more accessible.” (Intervention, University-affiliated HMO) “When we talk about coinsurance or when we talk about your out-of-pocket. I understand this stuff, because I work in healthcare… but not everybody would. And so, I think that [education on insurance terms] probably would be more helpful.” (Usual care, PPO). |
| IVF network inadequacy | University affiliated HMO plan’s lack of in-network clinics and providers caused long delays in using covered benefits. | “ I thought I was good with my choice. And, like, had I known that there were no in-network providers. I may have opted for the more expensive PPO plan because the process is just very difficult with the HMO, because there are no in-network providers.” (Intervention, University-affiliated HMO) |
| IVF benefit coverage | Participants expressed challenges using IVF services compared to non-IVF services. IVF care is less accessible, provides less coverage, and is more difficult to navigate than non-IVF services. | “It bothers me that IVF is not covered completely like any other service. Nobody chooses to have to build a family in this way, in particular, I mean, you have other options of course. To me, it’s a medical condition, and it should just be covered, not 50% covered, because 50% is still, you know, 15 grand a cycle.” (Intervention, PPO). “[IVF care is] more complicated, because, you know, you’d have to check [bills, coverage] more carefully.” (Intervention, PPO). |
| IVF financial costs | Participants still had high out-of-pocket costs. | “So, I think my medications everything added up to around $10,000 something.” (Intervention, Private HMO) “I’m at, I think, around 40k now, so this [benefit] is something that would have been very helpful if we really had those benefits, but those benefits are out there saying it’s there, but you cannot use it.” (Usual care, Private HMO) |
| Satisfaction with IVF benefit | Satisfaction with IVF benefit was mixed. | “I think it’s great that now we have these benefits. I’m happy to have access to those. In our case, [we] required more than two cycles, so that’s a significant limitation. And so, it’s quite limited, but it’s better than nothing. So, I am happy that we have it.” (Intervention, PPO) “Well, I’m not (satisfied), that’s what I’m trying to say. Like, the current situation is they have improved it with two 50% IVF services. But that’s not enough, because of the cost of the entire thing. We went through it, we know how much it costs, you know, just one IVF trial, that’s a huge burden on, the faculty or students’ income. I think they should just cover it 100% And then they should also provide additional guidance and benefits. So to make it better, and to make it useful” (Usual care, PPO) |
| Feedback | Participants recommended additional resources to improve IVF benefit access. | “Like a data sheet, CPT codes would be amazing, services or procedures would be amazing.” (Intervention, University-affiliated HMO) “What is the difference between fresh and frozen? because there are clinics who don’t do fresh. Then [you] can get any benefits because my clinic is like that. Those kinds of things that I think needs to be more understandable to the clients.” (Usual care, Private HMO) “I think that it needs to lay out, where that benefit can be used, and by what policies. So not just a blanket statement of all five of our big policies, give you 50% coinsurance, like, that’s not true if they claim that but then there’s not a single clinic in the state that would use that insurance in-network. So like, why claim that you have a benefit? If there’s no clinic that then takes your insurance?” (Usual care, Private HMO) |
For assessment of health plan selection and satisfaction, the university-affiliated HMO remained the most selected plan (51.4%) after open enrollment, followed by 24.6% for private HMO plan (RR=0.91, 95% CI 0.66, 1.26, p=0.68), and 24% for PPO plans (RR=0.95, 95% CI 0.70, 1.30, p=0.83), with no group differences (Table 4). In interviews, participants who selected the university-affiliated HMO plan reported delays in using the new benefit, primarily due to the unavailability of in-network clinics (Table 6). One participant shared, “The clinic had submitted the paperwork and approval and everything for insurance. But then nothing happened, and it was a contract issue. And there was really nothing they could do [they said] that I was one of at least a dozen patients in the same situation … so, it was a much longer process than anticipated.” (Intervention, university-affiliated HMO). Despite this, overall participants reported high satisfaction with the process of selecting a health plan (intervention 89.8% vs. usual care 86.6, p=0.61) (Table 4).
Most participants did not contact available resources prior to selecting a health insurance plan (intervention: 68.9%, usual care 62.5%, p=0.59). Those who did, primarily contacted fertility clinics and health insurance plans and found them to be unhelpful (Table 4). In interviews, participants who were proactive in contacting health insurance plans about the IVF benefit found these resources to be unhelpful, primarily due to lack of information on the IVF coverage information (Table 6). One participant stated, “I feel comfortable contacting places and getting information, but I can’t figure this out [how to use benefit]—I’m at a total dead end” (Intervention, University-affiliated HMO). These participants reported spending a few hours to months contacting health insurance plans about benefits. One participant said “we saw them in January and we are still working with them, we havent accessed the benefits yet. In January they told us we’re working on this, we are trying to get contracts for you all to access IVF and now its August” (Intervention, University-affiliated HMO)
Secondary Outcomes Follow-up 2
When assessing understanding of basic health insurance terms, both groups expressed moderate confidence (intervention: cumulative mean=1.89 out of 3.00 [SD=0.94], usual care: mean=1.89 out of 3.00 [SD=0.80], β=−0.0008, 95% CI −0.37, 0.37, p=0.98). In addition, self-reported IVF service utilization did not differ by group (Table 8). A total of 40% (25/62) of respondents in the intervention group and 52% (20/38) in the usual care group had an IVF consultation (OR 0.64, 95% CI 0.28, 1.48, p=0.30). Among those who had a consultation, 73% (33/45) across both groups had some form of fertility treatment (Table 8). Of the participants who had IVF services, 89.5% (17/19) used their health insurance to pay for IVF services. In comparison, 30% of respondents reported utilization of IVF services prior to participating in the study (intervention: 21% (13/62), usual care: 44.7% (14/38) p=0.02), with only 7% of those respondents using their health insurance to pay for IVF services (intervention: 3.2%, usual care: 13.2% p=0.38) (Table 7). When comparing their experience with IVF care to other medical care, many participants found other medical care to be more accessible, with better cost coverage, and much easier to navigate than IVF services (Table 6). One participant stated, “It was night and day from what my typical medical experience is like” (Usual care, private HMO).
Table 8.
IVF service utilization among those who had a fertility specialist consultation in 2023 reported at Follow-up 2 by group
| Total n=45 n (%) |
Intervention n=25 n (%) |
Usual care n=20 n (%) |
OR [95% CI] |
P value | |
|---|---|---|---|---|---|
| Did any fertility treatments | 33 (73.3) | 20 (80.0) | 13 (65.0) | 2.15 [0.56, 8.25] |
0.26 |
| Had IVF services for infertility | 19 (42.0) | 10 (40.0) | 9 (45.0) | 0.62 [0.23, 1.70] |
0.35 |
| University-affiliated HMO | 8 (17.8) | 5 (20.0) | 3 (15.0) | 1.18 [0.59, 2.38] |
1.00 |
| Private HMO | 6 (13.2) | 3 (12.0) | 3 (15.0) | 1.00 [0.28, 3.54] |
1.00 |
| PPO combined | 5 (11.1) | 2 (8.0) | 3 (15.0) | 0.50 [0.16, 1.59 |
0.52 |
| Used health insurance to either fully or partially pay for IVF services | 17 (37.8) | 9 (36.0) | 8 (40.0) | 0.84 [0.25, 2.83] |
0.78 |
| Out-of-pocket costs for IVF services | |||||
| < $3,000 | 7 (15.6) | 4 (16.0) | 3 (15.0) | ref | ref |
| $3,0001-$10,000 | 4 (8.9) | 3 (12.0) | 1 (5.0) | 2.25 [0.15, 34.0] |
0.56 |
| $10,001-$20,000 | 2 (4.4) | 0 (0.0) | 2 (10.0) | 0 [0.0, 0.0] |
0.88 |
| > $20,000 | 3 (6.7) | 2 (8.0) | 1 (5.0) | 1.50 [0.09, 25.4] |
0.78 |
| Chose not to undergo fertility treatments because of the cost | 20 (44.4) | 13 (52.0) | 7 (35.0) | 2.01 [0.60, 6.74] |
0.26 |
| University-affiliated HMO | 11 (24.4) | 6 (24.0) | 5 (25.0) | 0.95 [0.47, 1.93] |
1.00 |
| Private HMO | 3 (6.7) | 2 (8.0) | 1 (5.0) | 1.56 [0.48, 5.02] |
1.00 |
| PPO combined | 6 (13.3) | 5 (20.0) | 1 (5.0) | 3.33 [0.59, 18.9] |
0.19 |
| Somewhat or very satisfied with your IVF insurance benefits | 26 (57.8) | 16 (64.8) | 10 (50.0) | 1.05 [0.42, 2.66] |
0.91 |
Table 7.
Secondary outcomes measured at Follow-up 2
| Total n = 100 |
Intervention n = 62 |
Usual care n = 38 |
β [95% CI] |
P value | |
|---|---|---|---|---|---|
|
Understand health insurance terms
*
Cumulative mean (SD) |
1.89 (0.88) | 1.89 (0.94) | 1.89 (0.80) | −0.0008 [−0.37, 0.37] |
0.98 |
| Utilization of IVF Insurance & Services BEFORE study enrollment | OR [95% CI] | ||||
| Contacted health insurance plan about IVF services n (%) |
22 (22.2) | 9 (14.5) | 13 (34.2) | 0.69 [0.14, 3.52] |
0.66 |
| Had IVF services n (%) |
30 (30.0) | 13 (21.0) | 17 (44.7) | 0.34 [0.14, 0.83] |
0.02 |
| Used health insurance to pay for IVF services n (%) |
7 (7.0) | 2 (3.2) | 5 (13.2) | 0.44 [0.07, 2.73] |
0.38 |
| Was not satisfied with IVF insurance benefits n (%) |
26 (26.0 | 12 (19.4) | 14 (36.8) | 0.44 [0.04, 4.25] |
0.39 |
Response scale (0–3): 0 not at all confident, 1 slightly confident, 2 moderately confident, 3 very confident
Over half of these participants had unreimbursed out-of-pocket costs exceeding $3000, with no differences between groups (Table 8). Sensitivity analyses using multiple imputation reaffirmed the robustness of these findings (data not shown). Intervention participants were more likely to forgo fertility treatments due to cost (intervention 52% vs. usual care 35%, OR=2.01 95% CI 0.60, 6.74, p=0.26) (Table 8). Despite this, over half of participants (58%) were satisfied with having an IVF benefit, yet ongoing dissatisfaction was expressed over high out-of-pocket costs despite using the new benefit (Tables 6 and 8). One participant shared, “I thought that the appointment with the doctor would be considered a regular doctor’s appointment. And then the extra appointments would be 50%, but everything, even just talking to the doctor about different [IVF] options was, 50% out-of-pocket.” (Intervention, private HMO). Participants recommended additional resources to improve IVF benefit access, including a clear list of covered services, improved benefit roll out with contracts in place, improved communication between clinics, insurance, and physicians and more insurance education to help navigate the benefit (Table 6).
Discussion
In this study evaluating health insurance literacy in the context of IVF care, we found that the educational intervention was not associated with improvements in health insurance literacy. The intersection of health insurance literacy in the domains of confidence and being proactive when using health insurance and the complexities of health insurance implementation may help explain these findings. While high health insurance literacy is expected to translate to better health services utilization, the intervention did not improve health insurance literacy, as such we were unable evaluate the intervention’s full impact on IVF service utilization. Despite participants reporting moderate confidence in understanding health insurance terms and proactive engagement when using their insurance plans, many participants who attempted to use the new IVF benefit, found IVF services to be unaffordable and encountered barriers to benefit utilization.
While prior health insurance literacy studies have focused on evaluation of primary and preventive care [11], our intervention focused on the specialized care of IVF. The yearlong study conducted during the IVF benefit roll out provided a unique window into factors that may have limited the usability of knowledge provided in the intervention. Factors such as attaining prior authorizations for IVF services, IVF medication coverage limits, and inconsistencies in availability of in-network physicians and affiliated clinics were reported in interviews as barriers to understanding and using the new IVF benefit. These unforeseen barriers, possibly unique to this health system, delayed or prevented IVF insurance benefit utilization. This is further supported by participants’ comparison of IVF services to non-IVF services, which participants reported the latter was easier to navigate and involved less cost-sharing. This suggests that interventions targeting health insurance literacy in context of IVF may need to be tailored for the unique insurance environment of IVF services.
Both intervention and usual care participants reported low confidence using health plans, with no significant differences between groups at Baseline or at Follow-up 2. This finding could be due to a few reasons, such as the larger than anticipated loss to follow-up, how thoroughly participants reviewed the educational materials, or the network inadequacies reported by participants in both groups. Although sensitivity analysis showed that participants lost to follow-up were like those retained, it is possible that retained participants faced higher barriers to using their health plan and continued with the study to seek additional support. Since we did not measure how participants interacted or used the intervention materials, we were unable to determine how much time participants spent reviewing the provided material. In addition, the prolonged time between study time points (7–12 months) could have impacted the retention of knowledge and thus the reported health insurance literacy rating at Follow-up 2. Further, network inadequacies reported in interviews may have impacted participants’ ability to utilize health insurance literacy knowledge gained as part of the intervention.
Both intervention and usual care participants reported moderate confidence comparing health insurance plans at Follow-up 1 and being proactive when using health plans at Follow-up 2. However, usual care participants had a higher rating at Follow-up 1 for comparing health insurance plans and at Follow-up 2 for being proactive when using health plans when compared to intervention participants. Since usual care participants only received the one-page university-provided guide, they likely had to search for details on the new IVF benefit independently. This self-explorative exercise could have improved their confidence beyond the intervention group who were provided additional details as part of the educational materials. Unlike confidence using health plans, which remained the same from Baseline to Follow-up 2, there was a slight increase in ratings towards very confident being proactive when using health plans from Baseline to Follow-up 2 in both groups.
Although intervention participants rated the educational materials higher, they had similar health insurance literacy scores as usual care. Despite 69% of our population being post-graduates and the educational materials being written at a 7th grade reading level, the length of the educational materials, content, or formatting may have been challenging to fully digest and understand. Our qualitative findings support the positive reception of the educational materials but also reveal barriers that may have limited participants’ confidence in using and being proactive with health insurance. One key barrier was access to plan-specific IVF benefit details during plan selection (“open enrollment”). While participants were confident contacting health insurance plans, most found this to be unhelpful in determining which plan offered the best IVF coverage. Additionally, usual care participants expressed a need for education on health insurance terms—content that was included in the educational materials.
Despite 42% of our population reporting an income greater than $129,000 and having 50% co-insurance for IVF services, the magnitude of IVF costs remained a hindrance to IVF service utilization, with one in five participants opting out of IVF care due to cost. Although overall participant cost-sharing improved with the IVF benefit, some still reported out-of-pocket expenses greater than $10,000. To allow for equitable access, an IVF benefit should be comprehensive, including provisions for current diagnostic criteria for infertility, cost estimates, and IVF coverage (inclusive of diagnostic tests and treatments, medication, storage fees, and genetic testing). In this health system, the criteria for infertility diagnosis, network adequacy, and details of covered services differed across the available health plans. This inconsistency in health plans could have added to the lower health insurance literacy rating for confidence using health plans and comparing health plans.
Although not the focus of this study, interviews revealed barriers in the IVF benefit implementation process, which may have influenced our trial outcomes. The downstream implementation of an IVF benefit involves 1) availability of health plans with IVF coverage options; 2) appropriate plan selection (includes knowledgeable human resources and health plan support services); 3) availability of in-network physicians, clinics and labs; 4) availability of cost estimates for procedures and treatments; 5) and availability of approved pharmacies with transparent out-of-pocket medication costs. Our qualitative data showed that some health plans left participants navigating an illusion of a benefit amid administrative gridlocks, due to non-comprehensive benefit design, lack of in-network providers/clinics, and communication barriers between human resources, health plans, and providers/clinics. Our study was not powered to quantify differences between study groups by health plan.
A key strength of this study is its mixed-methods design, offering an in-depth view of how participants’ health insurance literacy interacts with service utilization. Conducting the study during plan selection and at two additional time points provided real-time insights into benefit roll out and participant experiences. The main limitation was a high loss to follow-up; however, sensitivity analyses were similar to intention-to-treat results, suggesting that dropouts likely had similar outcomes as those who were not lost to follow-up. Since 88% of participants had some prior exposure to fertility care (this includes non-IVF treatment), the intervention may have had limited impact on health insurance literacy due to preexisting experience with navigating health insurance in the context of infertility. Future studies on health insurance literacy in the context of IVF care should explore socioeconomic factors, as our high-income, highly educated participant pool limited assessment of possible disparities in health insurance literacy and IVF benefit utilization.
Conclusions
Our findings contribute to the IVF health insurance benefit literature by highlighting that education targeting health insurance literacy in the context of IVF care is complex. Unlike established medical services (e.g., primary, maternity, emergency care), IVF care coverage is not fully covered by insurance thus complicating the interaction of patients, clinics, and health plans. The best way to educate patients on how to navigate this system, including health insurance literacy is ongoing. Our findings suggest that targeting health insurance literacy through improvement of confidence using health plans, confidence being proactive when using health plan, and basic knowledge of health insurance terms may require better curated and tailored educational materials. As state mandates require large employers to expand IVF insurance coverage, identifying better tools to help patient understand and navigate their IVF health benefit is necessary to ensure effective utilization and equitable access to IVF care.
Supplementary Material
Acknowledgements
The authors would like to thank the study participants and research staff for their contributions to this study.
Funding
Research reported in this article was supported through funding by the National Institutes of Health / National Center for Research Resources (UL1TR001442) and National Research Service Award (T32 HD007203). The statements presented in this work are solely the responsibility of the authors and do not necessarily represent the views of the National Institutes of Health.
Footnotes
Ethical Approval
The trial was approved by the University of California San Diego Institutional Review Board on November 4, 2022.
Conflict of Interest Statement
All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Contributor Information
Olumayowa Dayo, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, California USA.
Bonnie N. Kaiser, Anthropology Department and Global Health Program, University of California San Diego, La Jolla, California USA.
Ricardo E. Flores Ortega, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, California USA.
Victoria Turcotte, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, California USA.
Breanna Reyes, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, California USA.
Natasha Bisarya, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, California USA.
Brian Kwan, Department of Health Science, California State University Long Beach, Long Beach, California USA.
Gregory A. Aarons, Department of Psychiatry and ACTRI Dissemination and Implementation Science Center, University of California San Diego, La Jolla, California USA.
Sara B McMenamin, Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, California USA.
H. Irene Su, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, California USA.
Sally A. D. Romero, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, California USA.
Availability of Data and Materials
The datasets generated during and/or analyzed during the current study will be available from the principal investigator (H. Irene Su) on reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets generated during and/or analyzed during the current study will be available from the principal investigator (H. Irene Su) on reasonable request.