What Influences Free Clinic Usage by the Uninsured

What Influences Free Clinic Usage by the Uninsured

What Influences Free Clinic Usage by the Uninsured? By Shelli Thomason A Paper Submitted to Dr. Dayna McDaniel Research Methods PA6601 Term 5, 2012 Troy University July 27, 2012 TABLE OF CONTENTS CHAPTER 1 Introduction …………………………………………………………………….. 4 Statement of the Problem………………………………………………………. 5 2. 1 Purpose ……………………………………………………………. 6 2. 2 Problem Statement….. …………………………………………….. 6 2. 3 Research Questions………………………………………………… 6 2. 4 Scope………………………………………………………………. 1. Literature Review……………………………………………………………….. 9 Dependent variable……………………………………………………….. 9 1st Independent variable…………………………………………………… 11 2nd Independent variable………………………………………………….. 13 3rd Independent variable…………………………………………………… 14 4th Independent variable…………………………………………………… 16 4Hypothesis……………………………………………………………….. ……………18 4. 1 H1: hypothesis one………………………………………………….. 18 4. 2 H2: hypothesis two………………………………………………….. 18 4. 3 H3: hypothesis three…………………………………………………18 4. H4: hypothesis four…………………………………………………. 18 Chapter II: Methodology Design………………………………………………………………………………….. … 18 Population/Sample…………………………………………………………………………. 20 Variables……………………………………………………………………………………21 Dependent Variable………………………………………………………………… 21 Independent Variables………………………………………………….. ……. ……22 Data Collection………………………………………………………………………….. …22 Measuring Instrument………………………………………………………… ……. 22 Materials……………………………………………………………………………. 23 Delivery Method…………………………………………………………………….. 24

Data Analysis………………………………………. ……………………………. … 24 Chapter III: Anticipated Findings………………………………………………………….. 25 Chapter IV: Conclusion……………………………………. …………………………………25 Implications…………………………………………….. ………………………………………26 Recommendations………………………………………………………………………………26 References…………………………………………………………………………………28 – 30 Appendices Appendix A Schematic Model…. …………………………………………………. ………… ….. 31 Appendix B Formula for Calculating Population Sample Size…. ………………. …………….. 32 Appendix C Survey………………………………………………………………. …… … 33 – 35 Appendix D Demographics…………………………………………………………….. ………36 Appendix E Example of Multiple Regression results……………………………………………37 Chapter 1 Introduction Many United States residents delay or do without necessary healthcare because they lack the resources or knowledge to access it. There are 46 million people in the nation who have no health care coverage, and by not giving necessary attention to medical concerns and conditions, poor health risks increase, along with untimely mortality (Darnell, 2010).

A Kaiser Commission study from 2006 identifies there are 18,000 deaths yearly in the United States resulting from lack of health care coverage (Trask, 2011). Recent Census Bureau shows a slightly higher number of uninsured indicating there are 50 million uninsured, which would be the largest number on record, resulting from the national economic recession (Krisberg, 2010). According to Darnell (2010), there are 1007 free clinics in the nation, providing services during 3. 5 million clinic visits, by 1. 8 million uninsured patients, representing approximately 10% of uninsured adults of working age.

The patients have no other health care alternatives to a free clinic due to a variety of factors including: no ability to pay, language barriers, lack of or inadequate medical insurance, homelessness, inaccessibility, and immigration or ethnicity issues. As private non-profit organizations, free-clinics are not recipients of federal funding, so many rely on state funding, local funding, and donations. Depaul (2010) notes that the National Association of Free Clinics estimated four million patients were seen in 2008, which doubled in 2009.

It is also noted that free clinics have to turn away patients because they cannot meet the demands. In a white paper for the American College of Physicians, Gorman (2004) notes, those who do not receive annual exams and preventative screenings run the risk of a delayed diagnosis and subsequent treatment, resulting in premature mortality. Additionally, untreated chronic symptoms result in worsened conditions and costly emergency care, placing a financial burden on hospitals, families and ultimately on the community. Furthermore, workers who experience poor health have lower productivity which is costly to the economy.

Therefore, free clinics are a crucial component in the consortium of health care options in the United States. Isaacs and Jellinek (2007), state that 80 % of patients who receive primary care at a physician’s office are either uninsured or have Medicaid. Although physicians may see uninsured patients in their offices and take on a few of them as charitable cases, this practice is declining given lower insurance and Medicaid reimbursements and increased operational expenses. The nation has what is referred to as a safety net system to provide health care services for residents who are uninsured.

This system is comprised of hospital emergency rooms, publicly funded health centers, and free clinics. With costs of health care escalating, it is crucial to identify methods to effectively optimize these providers. It has been suggested that accessibility to free clinics, which may keep the uninsured from accessing the ER for non-emergent care, is one such method. Studies show uninsured persons utilizing a free clinic have fewer emergency room visits than those who do frequent the ER for their primary care, which renders cost savings (Trask, 2011). Statement of the Problem Purpose

The purpose in this research is to make determinations as to what factors influence an uninsured person’s decision to access the services of a free clinic. In an effort to answer this question, factors will be recognized, through research, significant to a person making the decision to visit a free clinic for medical care. Uncovering these factors could assist in discouraging the misuse of other types of medical safety net provisions. One study shows if the group studied did not have use of a free clinic, 80% of the visits would have resulted in ER visits for non-emergency treatments (Corso & Fertig, 2011).

This information could also assist in identifying strategies to effectively address the health care needs of constituents and provide funding sources with knowledge to make educated decisions on the most effective use of funds. Problem Statement This project will pinpoint the most acute variables influencing an uninsured person to seek treatment at a free health clinic, allowing local government leaders and medical providers to have access to research so they may further understand areas in which to place their focus and funding.

Furthermore, an ancillary reason for study is to show that by providing an uninsured person who is truly ill with a way to achieve wellness, they can become viable again, thus becoming a more productive worker, who may regain insurance and no longer need the free service, or any other type of medical care. If a person has a resource within which to address health concerns, that does not present them with barriers, they are likely to receive the necessary care needed, reducing further complications and costs, placing them in a position to become more sustainable.

In one Healthcare Georgia study, evidence shows that free clinics can halt the escalation of health problems, reducing or eliminating the need for hospitalization (Corso & Fertig, 2011). Research questions This project will focus on four research questions that will aide in identifying specific factors that influence an uninsured person to use a free clinic (dependent variable). The primary question to be asked is “What factors influence an uninsured person to use a free clinic? Research questions inquiring about those influences (independent variables) are: 1) Does lack of alternative health care options influence an uninsured person to use a free clinic? 2) Does housing status influence an uninsured person to use a free clinic? 3) Does Hispanic ethnicity influence an uninsured person to use a free clinic? 4) Does age influence an uninsured person to use a free clinic? The independent variables thought to influence the dependent variable are defined so there is a clear understanding of their meaning.

Lack of other alternatives: Many users of free clinics may have no other options for health care than a free clinic. They may be employed, but cannot afford the health care premiums offered by their employer or the employer does not offer health coverage. 83 percent of the patients seen at free clinics come from a working household and may hold two or three part time jobs (DePaul, 2010). Federally funded community health centers, different from free clinics, are typically located in rural or inner-city areas and help serve a large number of patients in high-needs communities.

In 2009, the Government Accountability Office indicated that even with 8000 community health centers, there were still 43 percent of underserved areas without access (Whelan, 2010). Housing Status: The definition of “homeless” is a broader scope than merely the population living on the streets and includes individuals in a widespread range of unstable housing scenarios. Homeless individuals do not only live under bridges or in a car, but may also reside in emergency shelters; foster homes; HUD’s terminology of “doubling up” with relatives or friends; or tenants who have been served an eviction notice.

Unstable housing status is a high risk factor for health disparities, much like genetics or eating habits. On average, a homeless person has eight to nine coexisting health problems (Batra et al. , 2009). A study of 6,308 homeless Philadelphians determined the mortality rate among the homeless was 3. 5 times that of the city’s overall population. Earlier research has also noted the homeless have escalated rates of a vast array of health problems (Lewis, Andersen and Gelberg, 2003). Age: Different clinics have differing eligibility for the patients they serve.

Many states have the option to offer an insurance plan covering children through the passage of the Children’s Health Insurance Program Reauthorization Act (Llano, 2011), then those over age 65 have Medicare. Therefore many clinics tend to turn their efforts toward those uninsured patients between the ages of 18-64. A 2004 study shows that overall general health significantly declines for those between age 50 and 60 if they are uninsured, underinsured or sporadically insured, compared to their counterparts who have adequate health coverage (Inguanzo and Kaplan, 2011).

Hispanic Ethnicity: Llano (2011) states the greatest hindrance to health care for Hispanics is the language barrier. Providers of service have difficulty communicating with Spanish speaking patients if there is no interpreter available, which may cause compromised diagnoses, treatment options and specialty referrals. Census Bureau data reveals that in 2010, 38. 7 percent of uninsured American residents were Hispanic (Inguanzo & Kaplan, 2011). Scope A survey will be completed, as part of this research. This project’s scope will investigate what influences an uninsured person’s visit to a free clinic.

It will assist the free clinic administration in further developing strategic plans to make determinations on where their efforts should be focused. It may also contribute to local governments and other potential grantor’s decisions on making allocations. Free clinic usage is the primary focus, although the collective information may show related trends and concerns constructive to area healthcare providers and local governments. Each person surveyed will be treated equally. This study’s sample population will include patients of two free clinics: Community of Hope Health Clinic and Cahaba Valley Health Care Clinic in Shelby County, Alabama.

The clinic only sees uninsured patients on Mondays from 8:30 am to 4:30 pm and Thursdays from 5:30 pm to 8:30 pm. They must show proof of residency in Shelby County. Literature Review Dependent variable: Free clinic usage by the uninsured As stated earlier, experts concur that there are over 1000 free clinics in the nation, providing services during 3. 5 million clinic visits, by approximately 10% of uninsured adults of working age (Darnell, 2010; Gertz, Frank and Blixen, 2010; George Washington University Report to Congress, 2012).

This equates to approximately 90% of uninsured adults who are not utilizing a free clinic for their medical needs. Gertz, Frank and Blixen (2010) go further to say that since 1980, when there were 30 million uninsured people, there has been a 50% increase to 45 million. From a statewide perspective, Rhode Island remains consistent with national levels, as uninsured working age adults under age 64 doubled between 2000 and 2005, citing the waning of employer health care coverage (Gerber, et al. , 2008). The yearly cost associated with uncompensated medical treatment for the uninsured in the nation was $56 million in 2008.

Determinations were made to suggest that use of emergency rooms for non-emergent care, along with rising hospitalization which could have been prevented are on the rise and creating costly problems. Communities are seeking other solutions to provide health care to the uninsured, which might include free clinics, mobile clinics, and church and school sites to administer treatment (Fertig, A. , Corso, P. & Balasubramaniam, D. , 2011). As stated earlier, free clinics are an important part of the United States health safety net, serving mainly the uninsured, working poor.

Historically, given minimal resources and relying on volunteer health care providers, free clinics have focused on gap filling, temporary solutions to the population’s health problems. Implementing a new paradigm, free clinics are now making disease prevention and health promotion a top priority (Scariarti & Williams, 2007). A nationwide cross-sectional study using a survey was conducted by Gertz, Frank and Blixen (2010) which they compared to the only other known published study of its kind by Nadkarni, et. al from 2005 to determine free clinic characteristics.

Both studies revealed a mean of between 4,000 and 6,000 uninsured visits to the free clinics annually, and a third study agrees that most (67%) are located in the Southern region of the United States (Gertz, Frank & Blixen, 2010; George Washington University Report to Congress, 2012). Additionally, 77% of the respondents of the Gertz, Frank and Blixen study (2010) indicated the level of care received at free clinics was superior to prior medical care received, and 24% indicated if there was no free clinic available, they would not seek care, mainly due to cost.

A high number of free clinics seem to function as a fixed source of medical care for their patients. The majority of free clinics describe the service they provide to their patients as continuing, 20 percent indicate the care as recurrent, and 5 percent depicted the care as irregular, only seeing a patient once (George Washington University Report to Congress, 2012).

In contrast, prior to the recent national economic recession, a study associated with the utilization of three Massachusetts free clinics was conducted to determine what factors influenced people to use the free clinics, when it appeared there were a variety of ample options for medical care irrespective of health care coverage or income level. Although the study unveiled the three free clinics saw patients who had insurance, 81% of the respondents were uninsured (Keis, DeGeus, Cashman & Savageau, 2004).

Lack of health care coverage, is the sixth-leading cause of death, equating to 18,000 deaths annually for adults between the ages of 25 and 64 (Groman, 2004). The uninsured person may encounter severe financial and wellness obstacles, limiting their ability to obtain medical care and many times become indebted and more ill, as a result. A study conducted by Becker (2001) found that not only did uninsured persons with chronic health conditions lack adequate health care; their illnesses were also inadequately managed.

Other findings were that with deficiencies of education regarding their health, those persons who are uninsured lacked the information, understanding, and resources that would allow them to manage their illnesses more effectively. Many uninsured patients can pay more than double the cost if they are forced to use a hospital for their care, due to the inability for price leveraging that medical insurance providers can afford (Groman, 2004). 1st independent variable: Lack of other options

The National Association of Free Clinics indicates they see patients they never thought would come to a free clinic, with 83% of free clinic patients come from working home, but cannot afford COBRA if they have lost a job and are now working several part time jobs. Patients have reported they would likely go the ER or not seek care if they did not have access to a free clinic (Depaul, 2010). Private practice doctors are the primary source of health care for the uninsured, mainly because, historically, they have been plentiful in numbers, with 720,000 providing care according to Isaacs & Jellinek (2007).

A second expert (Groman, R. 2004), agrees that free care by physicians is decreasing, which will greatly impact the medical safety net with growing numbers of uninsured. As stated earlier, the decline is largely the result of higher operating costs and inadequate Medicare reimbursement rates, prohibiting the doctors from being able to treat those who cannot pay (Isaacs & Jellinek, 2007). Even though charity from practicing physicians plays a vital role in treating the uninsured, they are not stand-ins for health insurance. Because of revisions to financing and rganization of medical care systems, doctors indicate in a New York Academy of Medicine study, they are unable to provide the same class of care to the uninsured, as they provide to patients who have health care coverage (Groman, R. , 2004). A recent report to Congress indicates that free clinics overall see millions of uninsured persons who may not achieve any level of care elsewhere. One study highlighted in the report revealed four main reason listed in order of percentage, people use a free clinic are: no health insurance (82%), referrals by others (59%), medications (38%), and no knowledge of where else to go (34%).

The report also states that three quarters of free clinic patients do not have a regular method of care except the free clinic or the ER, suggesting free clinics fill voids, offering services not available (or easily reached) somewhere else (George Washington University Report to Congress, 2012). The Keis, et al. (2004) study is in accord with the report to Congress in that one-third of survey respondent gave their reason for using a free clinic as not knowing where else to go to receive medical attention.

Another one-third cited lack of transportation, long wait times, finding child care or inability to leave work as the primary reasons they could not use other types of medical providers and instead sought treatment at a free clinic. As already learned, access to local safety net providers has limits to readiness in other ways as well. For example, in Jeffrey Trask’s unpublished dissertation (2011), he cites and agrees with the Keis study stating that other than the emergency room, many safety net providers aren’t open in the evenings or are scarce, so due to the need to work, a patient’s only option may be a free clinic open in the evenings.

Likewise, clients of free clinics forego after care or specialty care only a hospital can offer due to costs. Trask (2011) gives the example, when an uninsured person using a free clinic needs additional services outside the free clinic’s scope of care, sometimes old or bad debt is a major obstacle to receiving necessary treatment. Finally, options are limited for people who are not legally residing in the country. A collective characteristic of a free clinic is capacity to treat any patient without documentation regarding immigration status (Keis 2004).

In a 2010 national survey, a census, the first of its kind in 40 years, 764 clinics were deemed eligible out of 1188 surveys mailed. A finding from the study uncovered that free clinics are a more important aspect of the national safety net, especially in the area of ambulatory care that originally thought. However, only 188 of the clinics surveyed offered all-inclusive services, and the survey concluded that a free clinic is not a replacement for comprehensive primary care (Darnell, 2010). 2nd independent variable: Hispanic ethnicity Hispanic persons comprise approximately 16 percent of the population in the U.

S. but make up 25 percent of free clinic patients. Experts agree that unbalanced degree of Hispanic patients in free clinics indicates higher rates of lack of health care coverage among this group (George Washington University Report to Congress, 2012; Isaacs & Jellinek, 2007), with the latter authors citing an example from a Racine, Wisconsin clinic who had a one percent Hispanic patient base in late 1980s and a 50 percent Hispanic patients in 2006. Results were compared from two student-run free clinic studies on clinic characteristics and concurred that most of the patients were minorities.

One study of 59 clinics reported that 31% of the patients seen were Hispanic, while the other study of 39 clinics revealed 53% of patients were Hispanic. The student run clinics demographic is quite different from non-student run clinic who report a client base of mainly non-Hispanic people (Gertz, Frank & Blixen, 2010). Studies indicate that Hispanic persons are more likely than non-Hispanics to fail to complete the Medicaid application and miss important dates for submitting required documentation.

Furthermore, 43 percent of Hispanics who speak Spanish had communication problems with physicians compared to 16 percent of Caucasians; and non-English speakers had more difficulty in comprehending doctor orders (Llano, 2011). Because of non-existent health insurance and consequently no immunizations, a considerable outbreak of rubella plagued a Hispanic community in New York in the late 90s. The outbreak spread to adjacent communities and those with insurance were just as affected. In communities with high numbers of uninsured residents, it becomes more ifficult to provide disease control, and medical personnel have fewer opportunities to identify early onset of outbreaks, hampering containment efforts (Groman, 2004). In a report examining the unmet medical needs of the nation’s Latino population conducted by the American College of Physicians and the American Society of Internal Medicine, it was discovered that uninsured women had twice the likelihood as their non-Latino peers to be diagnosed with breast cancer in the later stages and uninsured Latino men were four times as likely to receive a prostate cancer diagnosis compared to non-Latino men.

It is suggested that Hispanic and Latino immigrants are very unlikely to have the ability to access health care services due to governmental restrictions of the Personal Responsibility and Work Opportunity Reconciliation Act of 1996, and fear that their citizenship opportunities will be compromised by attempting to secure public aid assistance (Inguanzo and Kaplan, 2011). 3rd independent variable: Homelessness According to Wilson (2009), there are close to 800,000 homeless people in the nation, many of which have multiple disorders to include asthma, nutritional deficiencies, skin infections, wounds, and diabetes, to name a few.

Wilson’s and O’Connell’s research goes on to say that the homeless person’s ailments which are largely left untreated and worsen, lead to devastating illness. The mortality rate is excessively high in the homeless populace. O’Connell (2005) agrees with Wilson’s conclusions with regard to high mortality rates, and that homeless people are three to four times more likely to die than the general population. The risk is greatly increased in those homeless persons between the ages of 18 and 54, and that younger homeless women are four to 31 times more likely to die than their housed counterparts.

Life expectancy in the general population is 78 years of age, and falls to between 42 and 52 years of age for the homeless population (O’Connell, 2005). Approximately 9 to 15% of the US population becomes homeless during their lifetime. Those who are truly without a place to stay and are considered literally homeless may be included in this figure, although the homeless are transient and in and out of shelters. Additionally, this figure may include those who HUD calls “doubled up” or “couch-homeless”. Other developed countries have a lower rate of this ategory of homelessness than the United States (Hoback and Anderson, n. d. ). For the U. S. overall in 2000, the estimate is 1. 65% of the population is “couch-homeless” (Census Bureau, 2000). One study highlights the Columbia-Harlem Homeless Medical Partnership (CHHMP), a free clinic run by students, that targets Manhattan’s homeless, providing medical students with a service learning opportunity and simultaneously, providing a medical home for homeless patients. Free student-run clinics are an integral piece of the medical safety net.

In these learning settings, the requirements of medical students and in-need patients transect with the outcome of quality medical care. The disordered lifestyle of the homeless patient requires outreach to this population and a need for relationship building. This type of need is not feasible in the medical school setting but can be met at a student-run free clinic. Students are able to deal with the human side of public health disparity and learn more about other services and make referrals that can assist the whole patient, such as housing, health screenings, mental health providers, etc. (Batra, et al. , 2009).

In congruency with the independent variable of other options stated earlier, an interview study of 2578 homeless and sporadically housed persons indicated that housing instability, abuse, multiple arrests, physical and mental conditions, as well as substance abuse were contributing forces to causing heightened usage of emergency rooms with a trial study group revealing on average seven visits per year. Galwankar (2004) and Whitbeck (2009) both conducted studies which emphasized the need to decrease emergency room use among the homeless populations, by focusing on identified risk factors from a public health standpoint (Galwankar, 2004).

A large percentage of the homeless use hospital emergency departments for their primary care, even though it is not the most effective method of medical care for them, as it cannot provide continuity. Additionally, for hospitals and governments it is not cost effective (Whitbeck, 2009). Independent variable: Age Eighty percent of free clinic patients are between the ages of 18-64; with 12% being children and elderly being eight percent (George Washington University Report to Congress, 2012). Two pieces of literature agree with he statistic that one in every six people ages 51 to 61 partaking in the National Academies Health and Retirement Survey who were at the start of the survey, uninsured, developed a new finding of stroke, cancer or heart disease, over the next six year period (Institute of Medicine, 2012; Inguanzo & Kaplan, 2011). In agreement with an IOM report cited, a national trend study from 2007, looking at 10,088 uninsured older working age adults, found that this group is less likely to receive regular preventative screenings for breast cancer, prostate cancer and cholesterol that those with insurance in the same age group.

Additionally, women who are uninsured or are on Medicaid have a more advanced stage of breast cancer at first diagnosis and lower survival rate than their counterparts who have private health coverage (Gerber, et al. , 2008). In a 2009 Kaiser report, 30 percent of people between the ages of 19 and 29, are uninsured, the highest proportion of any age group. Though the majority of these young adults are working, they experience lower pay scales, and often find health coverage too expensive for their budget.

Most people in this age group reported they were in good health, but 10 percent indicated they were in poor or fair health; twice as many as those with medical insurance (Weaver, 2010). Now, in 2012, many of this age group, because of provisions under the Affordable Care Act, will now be able to remain a dependent on their parent’s insurance policy until age 26, thus likely reducing the high percentage of uninsured in this age group (The White House, 2010). The number of children nationwide with no healthcare coverage is on the rise, but the impact from being uninsured on a child’s health has not been heavily explored.

According to a Journal of Public Health article, in 2006 over one million children became uninsured, raising the total to 9. 4 million, or 12. 1% of all children in the United States. The spike in numbers can be credited to decreases in employer health coverage without corresponding growths in support provided by Medicaid or the State Children’s Health Insurance Program (SCHIP) (Abdullah, 2010). One study analyzed information from more than 23 million children, under age 18, in the United States, using two large patient databases, to evaluate the effect of health care coverage status on pediatric hospital stays.

The study resulted in findings that the rate of death for children who were uninsured was over 37 percent of the deaths studied (Abdullah, 2010). Hypotheses H1: The fewer options for medical treatment will influence an uninsured person to use a free clinic for health care. The more alternative options for medical treatment will influence less free clinic usage by an uninsured person. Other options is an independent variable that has a direct relationship with the dependent variable of free clinic usage by the uninsured.

H2: Hispanic ethnicity will influence an uninsured person to use a free clinic for their medical care needs. Hispanic ethnicity will not influence an uninsured person to use a free clinic for their medical care needs. Hispanic ethnicity is an independent variable that has a direct relationship with the dependent variable of free clinic usage by the uninsured. H3: Homelessness will influence a person to visit a free clinic. Homelessness will not influence a person to visit a free clinic. Homelessness is an independent variable that has a direct relationship with the dependent variable of free clinic usage by the uninsured.

H4: Age is a factor that influences free clinic usage by the uninsured. Age does not influence free clinic usage by the uninsured. Age is an independent variable that has an inverse relationship with the dependent variable of free clinic usage by the uninsured. Chapter II: Methodology Design This study will concentrate on one central research question: What impacts do availability of other medical care options, Hispanic ethnicity, homelessness and age have on the usage of a free clinic by people who are uninsured?

These questions will pose the following hypotheses: H1: The fewer options for medical treatment will influence an uninsured person to use a free clinic for health care. The more alternative options for medical treatment will influence less free clinic usage by an uninsured person. Access to other options is an independent variable that has a direct relationship with the dependent variable of free clinic usage by the uninsured. H2: Hispanic ethnicity will influence an uninsured person to use a free clinic for their medical care needs.

Hispanic ethnicity will not influence an uninsured person to use a free clinic for their medical care needs. Hispanic ethnicity is an independent variable that has a direct relationship with the dependent variable of free clinic usage by the uninsured. H3: Homelessness will influence a person to visit a free clinic. Homelessness will not influence a person to visit a free clinic. Homelessness is an independent variable that has a direct relationship with the dependent variable of free clinic usage by the uninsured.

H4: Age is a factor that influences free clinic usage by the uninsured. Age does not influence free clinic usage by the uninsured. Age is an independent variable that has an inverse relationship with the dependent variable of free clinic usage by the uninsured. A schematic model illustrates the correlation between these variables. The model can be reviewed in Appendix A. The research question and problem will be answered by using a survey design study conducted by a convenience sample over a six week period.

The reason behind using a cross-sectional design is that data on all variables of interest can be collected at the same time and is an efficient method for a large group (O’Sullivan, Rassel & Berner, 2008). The three page survey, written at a fifth grade level, in English and in Spanish, will make inquiries and gather information about the independent variables, and about the dependent variable. Attempts will be made to approach every patient signed in at the clinics during the study period. Internal and external validity, then, are important to maintain when surveying a sample population and asking questions on sensitive issues.

The goal is to ensure that the independent variables of interest indeed caused changes to the dependent variable and not something else; along with certifying the outcomes are general of the population and can be reproduced in any location. The development and reliability of the research questions are integral to maintaining internal validity within the study. Cognitive pretesting of 10 patients will be performed before beginning the study to ensure the questions are commonly understood and to confirm that the survey questions are capturing the intended outcomes.

Additionally, in order to ensure external validity, the results of the study can be implemented by other governments and non-profit agencies. Population/Sample The population for this study is patients visiting two free clinics in Shelby County, Alabama, ages 19-64. This limits the population to a specific age range of persons in the county, as it has been determined that those outside this age range are eligible for coverage through government offered insurance programs, even if they have not applied for it.

A Shelby County Development Services Department Profile indicates from 2010 Census data; the population for Shelby County, Alabama is 195,084 residents. Of those approximately 7% are uninsured, equating to around 10,000 uninsured residents. County demographics reveal an almost even division of males (49. 3%) to females (50. 7%). 83. 6% of the population is white, 10. 6% is Black/African American and 1. 5% is Asian (See Appendix D). An anomaly in demographics is observed in ethnicity, specifically Hispanic/Latino residents who are documented at 4. % (8,389) of the total population with an additional 4. 2% who ‘speak non-English language at home’ and 1. 6% who ‘speak English less than ‘very well. ’ If the results of a University of Alabama at Birmingham study are applied to undocumented Hispanics in Shelby County, the total would be more accurately reported at 37,314 (Patino, 2002). Given the fact that both clinics have eligibility requirement for the patients they see, the sampling frame will include only people ages 19-64, who have no insurance and who reside in Shelby County or indicate they are homeless.

The sample will consist of those who randomly visit the clinic, and are signed in on a first come, first served basis and are waiting to receive treatment at the clinics during the study period, representative of the near 2000 patients who actually received treatment in 2011. This total number of patients is captured from clinic data gathered and reported by the clinics. The sample will be chosen through convenience sampling methods. This method was chosen for its ease of execution and cost effectiveness, although it has a higher risk of bias.

The sample size was chosen using a formula that calculated a 95 percent confidence level that the sample size will accurately represent the total population of patients. The sample size will be 563 patients. See Appendix B. Variables Dependent Variable For this study, a free clinic is operationally defined as being a privately run non-profit agency not receiving any federal funding, that offers general medical services, medication and dental care to individuals who have no health care coverage. Volunteer, licensed medical providers administer the care at minimal or no cost (Darnell, 2010).

The dependent variable is measured using nominal scales, with letters of the alphabet used as labels instead of numerals. Questions in the survey that address the dependent variable specifically are Question 4 and Questions 9-13 (see Appendix C). Independent Variables The first independent variable: lack of other options, can be conceptually defined as locations where the uninsured might seek medical treatment, other than a free clinic. To measure this variable, use of other options will be measured using a series of questions asking questions related to medical care history.

Since the survey will be given to uninsured patients who may not have a high level of education, literacy, or understanding of terminology, the operational definition for the second independent variable of housing status in the survey will measure living arrangements. This will be accomplished by measuring the frequency of responses using nominal scales. The third independent variable, ethnicity, especially Hispanic ethnicity, has been defined as being of Hispanic origin. Per the US Census Bureau, persons of Hispanic origin are determined on the basis of question that asked for self-identification of the person’s origin or descent.

Persons of Hispanic origin, in particular, are those who indicated that their origin was Mexican-American, Chicano, Mexican, Mexicano, Puerto Rican, Cuban, Central or South American, or other Hispanic (U. S. Census Bureau). The fourth and final independent variable, used in this model is age, and is intended to measure which age groups of working age adults visit a free clinic most often; and if age is a factor for visiting the clinic. In the study, variable is operationally defined as working age adults between the ages of 19-64.

Free clinics trends have shown most patients are non-elderly adults (Darnell, 2010). This will be accomplished by measuring the frequency of responses using nominal scales. Data Collection Measuring Instrument The use of free clinics by the uninsured between ages of 19-64 and the relationships of the factors that influence usage, will be gauged by using a survey comprised of 20 questions (Appendix C), consisting of issues related to accessibility, reasons for use, medical insurance status, health status, employment status, housing status, current diagnoses, and general demographic information.

These questions include both ordinal and nominal scales. Two questions will provide an open-ended answer option where space will be provided to write in an answer. Some questions for the survey were extracted from previously tested and validated instruments, such as the National Health Interview Survey. The survey will be translated into Spanish, and for those who need assistance, an already on-site Spanish interpreter will assist in the introduction of the study as well as offer explanation for completion of the survey.

The survey should take no longer than 10 minutes to complete. Materials The materials and expense necessary to execute the survey are marginal. Copies required for each respondent total 4 pages (one page is the introduction and confidentiality notice and three pages for the survey) each totaling 2252 multiplied by $. 05 equals approximately $112. 60. Office supplies including three dozen writing pens and a stapler and staples will also be purchased for around $25. 00. Additionally, incentives in the form of refreshments are an additional cost.

Bottled water and healthy snacks such as granola bars, pretzels or crackers will be purchased in volume to reduce costs. 25 cases of water totals $180. 00 and snacks will be approximately $150. 00. Therefore the total cost to administer the survey with incentive is approximately $467. 60. The study will be given during clinic operating hours where clinic volunteers will be recruited to administer the introduction and surveys providing additional cost savings. Delivery Method In order to allow every patient in the convenience sample the same opportunity to participate in the survey, upon their arrival and egistration, a clinic caseworker will share with them a scripted introduction explaining the purpose for the survey and assure them it is voluntary and it will in no way cause them any risk and will in no way compromise their clinic visit nor treatment. The introduction will also discuss confidentiality. These measures will help to ensure internal validity since the orientation may provide a level of comfort for the respondent who in turn may be inclined to answer the questions more honestly.

The survey will be administered to the patients during regular clinic hours on Mondays between 8:30 am and 4:30 pm and Thursdays between 5:30 pm and 8:30 pm, while they wait to be seen. To improve response rates, healthy refreshments will be provided to participants. Patients who have been waiting to register for hours, to be one of 30 patients seen during a given clinic, have likely not eaten and may welcome refreshment as incentive to participate in the study. Dr.

Eleanor Singer, a population studies professor and researcher at Columbia University summarized the evidence on incentives from the standpoint of the survey literature in the use of incentives in her 2002 book. She uncovered that incentives improve response rates across all approaches. The effect has proven to be undeviating, larger incentives have superior effects on response rates. Those patients who are first in line to see a medical provider will have equal opportunity to participate in the incentive and the study upon completion of their visit. Data Analysis

Once the surveys are collected the data will first be cleaned. It is very important that the data collected from the surveys be able to be interpreted properly in order to accurately measure the relationships between the dependent and independent variables. Each question on the survey will be coded with a value prior to being administered. Data will be entered into a SDSS program and a multiple aggression analysis will be performed. From this analysis it will be possible to find the correlating relationships between each individual independent variable and the dependent variable to show significance.

Ultimately the computer program will show which factors strongly influence free clinic usage, which ones are less influential and which factors together may increase the relationship further. See the example in Appendix E. Chapter III: Anticipated Findings The literature that has been reviewed in relation to the variables in this study, along with the suggested approaches, in tandem offers backing to the outcomes that are expected of this study.

It is anticipated that there will be a relationship between use of a free clinic by the uninsured and each of the four independent variables provided: lack of other options for health care, age, Hispanic ethnicity and homelessness. The expectation is that the computer software used in analyzing the findings will show relationships between the variables, contradicting the null hypotheses. A multiple aggression analysis would be used to show these relationships by entering the data into a computer program designed to perform the computations and ends up showing a prototype of realism (Simon, 2003).

Each of the four independent variables, are believed to have direct relationships with the dependent variable. Ultimately, it is anticipated that each of the four corresponding hypotheses will be conclusive. Chapter IV: Conclusion Studies provide support for the need to address reasoning behind free clinic usage by the uninsured population. The literature review has assisted in understanding each variable’s definition, emphasizing the ideas and findings of other scholarly studies, and establishing the integrity of the links between each independent variable and the dependent variable.

As an example, the Kaiser report assists with understanding of the independent variable of age being a factor in why uninsured use a free clinic for their health care needs. It showed that younger working age adults in a certain age range were the group who are most often uninsured, and that this age group is forced to use free health care or have none at all, ultimately having medical conditions worsen, thus costing hospitals and tax payers more in the end. There is currently a staggering estimated $70 billion in uncompensated medical care from 2008 alone by uninsured patients (US Dept. f Health and Human Services, 2011). Therefore it is imperative that those with no medical insurance have access to some form of free or affordable health care in their community, with free clinics being an important piece of the equation. Implications The findings of this research are expected to be beneficial to the Shelby County local government, health and human service non-profit agencies and the medical system as the study will be proving assumed information, along with providing ancillary supportive data about the health care needs and gaps to serve uninsured residents of Shelby County, Alabama.

In knowing information about what factors contribute to the free clinic usage among the uninsured, the community collaborative can propose modifications, improvements and additions for programming that may assist in lessening the burden, and ultimately solving the problem. While the outcomes from the study may not be exact to national trends, they should be very reflective and allow for reproduction of successful interventions. Recommendations

The provided research will give evidence on four factors that contribute to the use of free clinics for medical treatment by the uninsured population of Shelby County, Alabama thus allowing for a community collaborative to be formed from local government, health care providers, faith based community, caseworkers, immigration and homelessness advocates, university department heads and others. Therefore, it is strongly suggested that this study be performed in order to gather this necessary information to determine if a more detailed needs assessment should be conducted.

While there are additional independent variables that may contribute to the usage of a free clinic, only four have been highlighted for this study. Others additional factors should be investigated to identify other challenges that strain the health care system, ultimately contributing to the occurrence of free clinic use. REFERENCES Abdullah, F. et al. , (2009). Analysis of 23 million US hospitalizations: uninsured children have higher all-cause in-hospital mortality. Journal of Public Health, 32 (2), 236–244. doi:10. 093/pubmed/fdp099 Batra, P. , Chertok, J. , Fisher, C. , Manseau, M. , Manuelli, V. , & Spears, J. (2009). The Columbia-Harlem homeless medical partnership: A new model for learning in the service of those in medical need. Journal of Urban Health: Bulletin of the New York Academy of Medicine, 86 (5). doi:10. 1007/s11524-009-9386-z Becker, G. , (2001). Effects of being uninsured on ethnic minorities’ management of chronic illness. West Journal of Medicine, 175(1), 19–23. Corso, P. & Fertig, A. , (2011). ROI and free clinics in Georgia.

HealthVoices, University of Georgia College of Public Health, Healthcare Georgia Foundation, Publication 51. Darnell, J. S. (2010). Free clinics in the United States: A nationwide survey. ARCH Intern Medicine, 170 (11), 946-956. Depaul, J. (2010). Free clinics: America’s best-kept secret. The Fiscal Times. Retrieved from: http://www. thefiscaltimes. com/Articles/2010/05/03/Free-Clinics-Lifeline-for-America. aspx#page1 Fertig, A. , Corso, P. , & Balasubramaniam, D. (2011). Benefits and costs of a free community-based primary care clinic.

Retrieved from: http://hogwarts. spia. uga. edu/~afertig/policy1/FreeClinic_JHHSArevision_singlespace1. pdf Galwankar, S. , (2004). Role of homeless and uninsured patients in overcrowded emergency departments. Retrieved from: http://www. bmj. com/rapid-response/2011/10/30/role-homeless-and-uninsured-patients-overcrowded-emergency-departments George Washington University, Department of Health Policy, School of Public Health and Health Services (2012). Quality incentives for federally qualified health centers, rural health clinics and free clinics: A report to Congress.

Washington, DC. Gerber, R. et al. , (2008). A place to be healthy: Blueprint for a new free clinic for the medically uninsured of Rhode Island. Medicine & Health/Rhode Island, 91(4), 105-108. Gertz, A. , Frank,S. & Blixen, C. (2011). A survey of patients and providers at free clinics across the United States. Journal of Community Health, 36, 83-93. doi: 10. 1007/s 10900-010-9286-x Groman, R. , (2004). American College of Physicians white paper on the cost of lack of health insurance [White Paper]. Retrieved from: http://www. acponline. rg/advocacy/where_we_stand/access/cost. pdf Hoback, A. & Anderson, S. (n. d. ). Proposed method for estimating local population of precariously housed. Retrieved from: http://www. nationalhomeless. org/publications/precariouslyhoused/index. html Inguanzo, M. & Kaplan, M. , (2011). The social implications of health care reform: reducing access barriers to health care services for uninsured Hispanic and Latino Americans in the United States, Harvard Journal of Hispanic Policy, 23, 83. Institute of Medicine (2003). Hidden costs, values lost: Uninsurance in America.

The National Academies Press. Washington, D. C. Retrieved from: http://www. nap. edu/catalog. php? record_id=10719 Isaacs, S. L. & Jellinek, P, (2007). Is there a (volunteer) doctor in the house? Free clinics and volunteer physician referral networks in the United States. Health Affairs, 26 (3), 871-876. doi: 10. 1377/hlthaff. 23. 3. 871 Keis, R. M. , DeGeus, L. G. , Cashman, S. , & Savageau, J. (2004). Characteristics of patients at three free clinics. Journal of Health Care for the Poor and Underserved, 15 (4), 603-617. Krisberg, K. , (2010).

Jump in uninsured signals need to implement health reform: Economy takes a toll on health coverage. The Nation’s Health, 40 (9), Retrieved from: http://go. galegroup. com. libproxy. troy. edu/ps/i. do? id=GALE%7CA241780634&v= 2. 1&u=troy25957&it=r&p=AONE&sw=w Lewis, J. H. , Andersen, R. M. & Gelberg, L. , (November 2003). Health care for homeless women: Unmet needs and barriers to care. Journal of General Internal Medicine, 18, 921-928. Llano, R. , (2011). Immigrants and barriers to healthcare: Comparing policies in the United States and the United Kingdom.

Stanford Journal of Public Health, Retrieved from: http://www. stanford. edu/group/sjph/cgi-bin/sjphsite/2011/06/immigrants-and-barriers-to-healthcare-comparing-policies-in-the-united-states-and-the-united-kingdom/ O’Connell, J. , (2005). Premature mortality in homeless populations: A review of the literature. National Health Care for the Homeless Council, Inc. , Nashville. Patino, F. , (2002). Material and child health services utilization by Hispanics in Alabama (doctoral dissertation). Birmingham, AL: The University of Alabama School of Public Health. Scariarti, P. & Williams, C. , (2007).

The utility of a health risk assessment in providing care for a rural free clinic population. Osteopathic Medicine & Primary Care, 1(8). doi: 10. 1186/1750-4732-1-8 Simon, G. , (2003). Multiple regression basics. Retrieved from: http://people. stern. nyu. edu/wgreene/Statistics/MultipleRegressionBasicsCollection. pdf Singer, E. , (2002). The use of incentives to reduce nonresponse in household surveys. Survey Nonresponse, John Wiley & Sons, Inc. , New York, 163-177. Trask, J. , (2011). The relationship between primary care access to free clinics and emergency room usage (Unpublished doctoral dissertation).

Graduate College of the University of Illinois at Urbana-Champaign. United States Census Bureau (2001). Households and families 2000, Census 2000 brief. US Department of Commerce. United States Census Bureau. Hispanic population of the United States. Retrieved from http://www. census. gov/population/www/socdemo/hispanic/ho00def. html U. S. Department of Health and Human Services (2011). ASPE Research Brief: The value of health insurance: Few of the uninsured have adequate resources to pay potential hospital bills. Weaver, C. , (2010).

How health overhaul would affect the uninsured. Kaiser Health News. Retrieved from: http://www. kaiserhealthnews. org/stories/2009/september/21/uninsured-explainer-npr. aspx Whelan, E. M, (2010). The importance of community health centers: Engines of economic activity and job creation. Center for American Progress. Whitbeck, L. (2009). Mental health and emerging adulthood among homeless young people. Psychology Press, Taylor & Francis Group, New York. White House, (2010). Department of Health and Human Services. Retrieved from: http://www. whitehouse. ov/blog/2010/05/10/a-long-overdue-change-help-young-adults-get-coverage [pic] [pic] |Appendix B | | |Required Sample Size† | | | | | | | | | | | | |  |0. 05 |0. 035 |0. 025 |0. 01 |  |0. 05 |0. 035 |0. 25 | |  | |10 |  |10 |10 |10 |10 |  |10 |10 |10 | | | |20 |  |19 |20 |20 |20 |  |19 |20 |20 | | | |30 |  |28 |29 |29 |30 |  |29 |29 |30 | | | |50 |  |44 |47 |48 |50 |  |47 |48 |49 | | | |75 |  |63 |69 |72 |74 |  |67 |71 |73 | | | |100 |  |80 |89 |94 |99 |  |87 |93 |96 | | | |150 |  |108 |126 |137 |148 |  |122 |135 |142 | | | |200 |  |132 |160 |177 |196 |  |154 |174 |186 | | | |250 |  |152 |190 |215 |244 |  |182 |211 |229 | | | |300 |  |169 |217 |251 |291 |  |207 |246 |270 | | | |400 |  |196 |265 |318 |384 |  |250 |309 |348 | | | |500 |  |217 |306 |377 |475 |  |285 |365 |421 | | | |600 |  |234 |340 |432 |565 |  |315 |416 |490 | | | |700 |  |248 |370 |481 |653 |  |341 |462 |554 | | | |800 |  |260 |396 |526 |739 |  |363 |503 |615 | | | |900 |  |269 |419 |568 |823 |  |382 |541 |672 | | | |1,000 |  |278 |440 |606 |906 |  |399 |575 |727 | | | |1,200 |  |291 |474 |674 |1067 |  |427 |636 |827 | | | |1,500 |  |306 |515 |759 |1297 |  |460 |712 |959 | | | |2,000 |  |322 |563 |869 |1655 |  |498 |808 |1141 | | | |2,500 |  |333 |597 |952 |1984 |  |524 |879 |1288 | | | |3,500 |  |346 |641 |1068 |2565 |  |558 |977 |1510 | | | |5,000 |  |357 |678 |1176 |3288 |  |586 |1066 |1734 | | | |7,500 |  |365 |710 |1275 |4211 |  |610 |1147 |1960 | | | |10,000 |  |370 |727 |1332 |4899 |  |622 |1193 |2098 | | | |25,000 |  |378 |760 |1448 |6939 |  |646 |1285 |2399 | | | |50,000 |  |381 |772 |1491 |8056 |  |655 |1318 |2520 | | | |75,000 |  |382 |776 |1506 |8514 |  |658 |1330 |2563 | | | |100,000 |  |383 |778 |1513 |8762 |  |659 |1336 |2585 | | | |250,000 |  |384 |782 |1527 |9248 |  |662 |1347 |2626 | | | |500,000 |  |384 |783 |1532 |9423 |  |663 |1350 |2640 | | | | Appendix C Health Care Survey Questionnaire Circle your answer: 1. What is your age? a. 19-24 b. 25-34 c. 35-44 d. 45-54 e. 44-64 2. What would you classify your ethnicity? a. Caucasian or white b.

African American or black c. Hispanic/Latino d. Asian e. Other________________ 3. What is your employment status? a. Full time employee b. Part time employee c. Self employed d. Unemployed – looking for work e. Unemployed f. Retired 4. Reason for no health care coverage/insurance? a. Employer does not offer b. Don’t work enough hours c. Became unemployed and lost coverage d. Cannot afford 5. What is your highest level of completed education? a. Did not complete High school/did not obtain GED b. High School Diploma / GED c. Technical/Trade school d. Some college e. College degree f. Graduate degree g. Doctoral degree 6. What is your housing status? a.

Own home b. Rent home/apartment c. Live with family/friends d. Reside at shelter/transitional housing e. Not housed 7. What language do you speak most often at home? a. English b. Spanish c. Other__________________ 8. Are there children living in your household ages 18 and younger? a. Yes b. No 9. When was the last time you received medical care before today’s visit? a. Within last week b. Within last month c. Within last three months d. Within last six months e. Within last year f. Longer than one year 10. Where did you last receive medical treatment before today’s visit? a. Doctor office b. Hospital ER c. Public health department d. Free Clinic 11.

Which best describes the reason you chose the location for your last medical treatment? a. Location b. Hours of operation c. Recommended by family/friend d. Did not know where to go 12. Did you have medical insurance the last time you received medical treatment? a. Yes b. No c. I don’t know 13. How would you rate your satisfaction level of your most recent medical treatment? a. Very satisfied b. Somewhat satisfied c. Somewhat dissatisfied d. Not satisfied 14. How would you describe your health? a. Excellent b. Good c. Fair d. Poor 15. Are you experiencing an ongoing health problem? a. Yes b. No c. I don’t know 16. Have you had a diagnosis for your health problem? a. Yes b. No c. I don’t know 17.

Are you taking prescription medications? a. Yes b. No 18. If you are taking prescription medications, is a needed refill the reason for your visit today? a. Yes b. No c. Not applicable 19. How are you able to afford your medications? a. Medication assistance b. Lower cost generics c. Samples d. Self-pay full price e. I cannot afford them 20. Please discuss any other issues you are having where assistance may be needed, so referrals may be offered. 21. Please describe in detail what you hope to receive from your visit today. Appendix D [pic] Shelby County Development Services Profile Appendix E – Example of a Multiple Regression results chart [pic] [pic]