Lessons for emerging state Children's Health Insurance Premium Assistance programs: Case study of the Massachusetts Masshealth Family Assistance Program (MHFAP)

Providing health insurance coverage for vulnerable populations such as low-income high-risk children with limited access to health care is a challenge for many states. Over the past decade, higher private insurance premiums and unpredictable labor markets have increased the number of uninsured and underinsured children nationwide. Due to recent economic downfalls, many states such as Texas, have expressed interest in using premium assistance programs to increase enrollment of low income children and families in private coverage through employer sponsored health insurance. Massachusetts has been especially successful in reducing the number of uninsured children through the implementation of MassHealth Family Assistance Program (MHFAP), an employer based premium assistance program. The purpose of this study is to identify key implementation factors of a fully established premium assistance program which may provide lessons and facilitate implementation of emerging premium assistance programs. ^ The case study of the fully established MassHealth Family Assistance Program (MHFAP) has illustrated the ability of states to expand their Medicaid and SCHIP programs in order to provide affordable health coverage to uninsured and underinsured low income children and their families. As demonstrated by MHFAP, the success of a premium assistance program depends on four key factors: (1) determination of participant and employer eligibility; (2) determination of employer benefits meeting benchmark equivalency (Medicaid or State Children's Health Insurance Program); (3) the use of appropriate marketing and outreach strategies; and (4) establishment of adequate monitoring and reporting techniques. Successful implementation strategies, revealed by the case study of the Massachusetts MassHealth Family Assistance Program, may be used by emerging premium assistance programs, such as Texas Children's Health Insurance Premium Assistance Program (CHIP-PA) toward establishment of an effective, efficient, and equitable employer sponsored health program.^

Evaluating the Harris County TexHealth 3-Share Plan: An exploratory study

An important health issue in the United States today is the large number of people who have problems accessing needed health care because they lack health insurance coverage. Providing health insurance coverage for the working uninsured is a particularly significant challenge in Texas, which has the highest percentage of uninsured in the nation. In response to the low rate of employer-sponsored coverage in the Houston area and the growing numbers of uninsured, the Harris County Health Care Alliance (HCHA) developed and implemented the Harris County 3-Share Plan. A 3-Share Plan is not insurance, but provides health coverage in the form of a benefits package to employers who subscribe to the program and offer it to their employees. ^ A cross sectional study design was conducted to describe 3-Share employer and employee participants and evaluate their outcomes after its first year of operation. Between September and December 2011, 85% of employers enrolled in the 3-Share Plan completed a survey about the affordability of the 3-Share Plan, their satisfaction with the Plan, and the Plan's impact on employee recruitment, retention, productivity, and absenteeism. Forty-five percent of employees enrolled in the 3-Share Plan responded to a survey asking about the affordability of the 3-Share plan, accessibility of health care, availability of providers on the plan, health plan availability, utilization of primary care providers and the ER, and satisfaction with the plan. ^ A summary of the findings shows employers and employees say that they joined the plan because of the low-cost, and once they had participated in the Plan, the majority of employers and employees found that it is affordable for them. The majority of employees say they are getting access easily and without delay, but for those who aren't able to get access, or are delayed, the main cause is related to non-financial barriers to care. Ultimately, employees are satisfied with the 3-Share, and they plan to continue with health coverage under the 3-Share Plan. The 3-Share Plan will keep people in a system of care, and promote health, which will benefit the individuals, the businesses and the community of Harris County.^

Evaluating the Harris County TexHealth 3-Share plan: An exploratory study

An important health issue in the United States today is the large number of people who have problems accessing needed health care because they lack health insurance coverage. Providing health insurance coverage for the working uninsured is a particularly significant challenge in Texas, which has the highest percentage of uninsured in the nation. In response to the low rate of employer-sponsored coverage in the Houston area and the growing numbers of uninsured, the Harris County Health Care Alliance (HCHA) developed and implemented the Harris County 3-Share Plan. A 3-Share Plan is not insurance, but provides health coverage in the form of a benefits package to employers who subscribe to the program and offer it to their employees. ^ A cross sectional study design was conducted to describe 3-Share employer and employee participants and evaluate their outcomes after its first year of operation. Between September and December 2011, 85% of employers enrolled in the 3-Share Plan completed a survey about the affordability of the 3-Share Plan, their satisfaction with the Plan, and the Plan's impact on employee recruitment, retention, and productivity. Forty-five percent of employees enrolled in the 3-Share Plan responded to a survey asking about the affordability of the 3-Share plan, accessibility of providers on the plan, satisfaction, and utilization of primary care providers and the ER. ^ A summary of the findings shows employers and employees say that they joined the plan because of the low-cost, and once they had participated in the Plan, the majority of employers and employees found that it is affordable for them. The majority of employees say they are getting access easily and without delay, but for those who aren't able to get access, or are delayed, the main cause is related to non-financial barriers to care. Ultimately, employees are satisfied with the 3-Share, and they plan to continue with health coverage under the 3-Share Plan. The 3-Share Plan will keep people in a system of care, and promote health, which will benefit the individuals, the businesses and the community of Harris County.^

The cost of insuring the uninsured in the U.S.

Objectives: This study included two overarching objectives. Through a systematic review of the literature published between 1990 and 2012, the first objective aimed to assess whether insuring the uninsured would result in higher costs compared to insuring the currently insured. Studies that quantified the actual costs associated with insuring the uninsured in the U.S. were included. Based upon 2009 data from the Medical Expenditure Panel Survey (MEPS), the second objective aimed to assess and compare the self-reported health of populations with four different insurance statuses. The second part of this study involved a secondary data analysis of both currently insured and currently uninsured individuals who participated in the MEPS in 2009. The null hypothesis was that there were no differences across the four categories of health insurance status for self-reported health status and healthcare service use. The alternative hypothesis was that were differences across the four categories of health insurance status for self-reported health status and healthcare service use. Methods: For the systematic review, three databases were searched using search terms to identify studies that actually quantified the cost of insuring the uninsured. Thirteen studies were selected, discussed, and summarized in tables. For the secondary data analysis of MEPS data, this study compared four categories of health insurance status: (1) currently uninsured persons who will become eligible for Medicaid under the Patient Protection and Affordable Care Act (PPACA) healthcare reforms in 2014; (2) currently uninsured persons who will be required to buy private insurance through the PPACA health insurance exchanges in 2014; (3) persons currently insured under Medicaid or SCHIP; and (4) persons currently insured with private insurance. The four categories were compared on the basis of demographic information, health status information, and health conditions with relatively high prevalence. Chi-square tests were run to determine if there were differences between the four groups in regard to health insurance status and health status. With some exceptions, the two currently insured groups had worse self-reported health status compared to the two currently uninsured groups. Results: The thirteen studies that met the inclusion criteria for the systematic review included: (1) three cost studies from 1993, 1995, and 1997; (2) four cost studies from 2001, 2003, and 2004; (3) one study of disabilities and one study of immigrants; (4) two state specific studies of uninsured status; and (5) two current studies of healthcare reform. Of the thirteen studies reviewed, four directly addressed the study question about whether insuring the uninsured was more or less expensive than insuring the currently insured. All four of the studies provided support for the study finding that the cost of insuring the uninsured would generally not be higher than insuring those already insured. One study indicated that the cost of insuring the uninsured would be less expensive than insuring the population currently covered by Medicaid, but more expensive to insure than the populations of those covered by employer-sponsored insurance and non-group private insurance. While the nine other studies included in the systematic review discussed the costs associated with insuring the uninsured population, they did not directly compare the costs of insuring the uninsured population with the costs associated with insuring the currently insured population. For the MEPS secondary data analysis, the results of the chi-square tests indicated that there were differences in the distribution of disease status by health insurance status. As anticipated, with some exceptions, the uninsured reported lower rates of disease and healthcare service use. However, for the variable attention deficit disorder, the uninsured reported higher disease rates than the two insured groups. Additionally, for the variables high blood pressure, high cholesterol, and joint pain, the currently insured under Medicaid or SCHIP group reported a lower rate of disease than the two currently insured groups. This result may be due to the lower mean age of the currently insured under Medicaid or SCHIP group. Conclusion: Based on this study, with some exceptions, the costs for insuring the uninsured should not exceed healthcare-related costs for insuring the currently uninsured. The results of the systematic review indicated that the U.S. is already paying some of the costs associated with insuring the uninsured. PPACA will expand health insurance coverage to millions of Americans who are currently uninsured, as the individual mandate and insurance market reforms will require. Because many of the currently uninsured are relatively healthy young persons, the costs associated with expanding insurance coverage to the uninsured are anticipated to be relatively modest. However, for the purposes of construing these results, it is important to note that once individuals obtain insurance, it is anticipated that they will use more healthcare services, which will increase costs. (Abstract shortened by UMI.)^

Government initiatives to expand access to employer-based health insurance

Employer-based health insurance is declining at records rates, which leaves an increasing number of people without access to affordable health insurance. As a result, municipalities are experiencing financial difficulties to provide health care services for their growing uninsured population. In attempt to combat this issue, three health polices have emerged within the last ten years, called Living Wage with a health insurance provision, Pay or Play, and Health Care Preference. These policies are gaining popularity as civic leaders recognize their ability to promote a public health goal by leveraging the power of city and county contracts to include a health insurance component in the competitive bidding practice for government contracts. ^ This is the first paper to conduct a retrospective analysis on whether these three health policies have been able to increase access to employer-based health insurance and/or support the local health care safety net based on the experiences of six municipalities over a 5-year period from 2001-2006. Although there was variation between the effectiveness of the policies, all three demonstrated success in that a number of contractors extended existing health insurance to employees not previously covered and the increased cost of contracting for the local government was, on average, less than 1 percent of the total operating budget. ^

Identifying and removing barriers to cycling as a viable means of transportation in Houston, Texas

The citizens of Houston, Texas, spend much time commuting. It has repeatedly been named among the “Fattest Cities” by Men’s Fitness Magazine (The fittest and fattest cities in America – Men’s Fitness. ). Obesity is one of its major public health problems as Houstonians often do not engage in enough physical activity to help them maintain their ideal weights. The use of bicycles provides a healthy and ecological alternative to commuting by driving. However, because urban cyclists must often share the roads with motorized vehicles, cyclists are often exposed to high levels of emissions. As vulnerable users of the roadways, urban cyclists also face the threat of injury. Nevertheless, there are some programs that encourage the use of bicycles. Laws and ordinances not only reveal public policy relating to bicycling but are a means to develop policy which can encourage bicycling. ^

Endemic tuberculosis, the homeless, and public transportation: A merging of geographical information systems surveillance and the Houston Tuberculosis Initiative Surveillance project

To reach the goals established by the Institute of Medicine (IOM) and the Centers for Disease Control's (CDC) STOP TB USA, measures must be taken to curtail a future peak in Tuberculosis (TB) incidence and speed the currently stagnant rate of TB elimination. Both efforts will require, at minimum, the consideration and understanding of the third dimension of TB transmission: the location-based spread of an airborne pathogen among persons known and unknown to each other. This consideration will require an elucidation of the areas within the U.S. that have endemic TB. The Houston Tuberculosis Initiative (HTI) was a population-based active surveillance of confirmed Houston/Harris County TB cases from 1995–2004. Strengths in this dataset include the molecular characterization of laboratory confirmed cases, the collection of geographic locations (including home addresses) frequented by cases, and the HTI time period that parallels a decline in TB incidence in the United States (U.S.). The HTI dataset was used in this secondary data analysis to implement a GIS analysis of TB cases, the locations frequented by cases, and their association with risk factors associated with TB transmission. ^ This study reports, for the first time, the incidence of TB among the homeless in Houston, Texas. The homeless are an at-risk population for TB disease, yet they are also a population whose TB incidence has been unknown and unreported due to their non-enumeration. The first section of this dissertation identifies local areas in Houston with endemic TB disease. Many Houston TB cases who reported living in these endemic areas also share the TB risk factor of current or recent homelessness. Merging the 2004–2005 Houston enumeration of the homeless with historical HTI surveillance data of TB cases in Houston enabled this first-time report of TB risk among the homeless in Houston. The homeless were more likely to be US-born, belong to a genotypic cluster, and belong to a cluster of a larger size. The calculated average incidence among homeless persons was 411/100,000, compared to 9.5/100,000 among housed. These alarming rates are not driven by a co-infection but by social determinants. The unsheltered persons were hospitalized more days and required more follow-up time by staff than those who reported a steady housing situation. The homeless are a specific example of the increased targeting of prevention dollars that could occur if TB rates were reported for specific areas with known health disparities rather than as a generalized rate normalized over a diverse population. ^ It has been estimated that 27% of Houstonians use public transportation. The city layout allows bus routes to run like veins connecting even the most diverse of populations within the metropolitan area. Secondary data analysis of frequent bus use (defined as riding a route weekly) among TB cases was assessed for its relationship with known TB risk factors. The spatial distribution of genotypic clusters associated with bus use was assessed, along with the reported routes and epidemiologic-links among cases belonging to the identified clusters. ^ TB cases who reported frequent bus use were more likely to have demographic and social risk factors associated with poverty, immune suppression and health disparities. An equal proportion of bus riders and non-bus riders were cultured for Mycobacterium tuberculosis, yet 75% of bus riders were genotypically clustered, indicating recent transmission, compared to 56% of non-bus riders (OR=2.4, 95%CI(2.0, 2.8), p<0.001). Bus riders had a mean cluster size of 50.14 vs. 28.9 (p<0.001). Second order spatial analysis of clustered fingerprint 2 (n=122), a Beijing family cluster, revealed geographic clustering among cases based on their report of bus use. Univariate and multivariate analysis of routes reported by cases belonging to these clusters found that 10 of the 14 clusters were associated with use. Individual Metro routes, including one route servicing the local hospitals, were found to be risk factors for belonging to a cluster shown to be endemic in Houston. The routes themselves geographically connect the census tracts previously identified as having endemic TB. 78% (15/23) of Houston Metro routes investigated had one or more print groups reporting frequent use for every HTI study year. We present data on three specific but clonally related print groups and show that bus-use is clustered in time by route and is the only known link between cases in one of the three prints: print 22. (Abstract shortened by UMI.)^