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Non-medical Out-of-Pocket Expenses: Impact on Family’s Quality of Life
Property of DIssertation Writing
At a time when health care expenses are increasing, part of the cost burden to patients is being shifted from insurance companies by larger deductibles, co-insurance and increased copayments that lead to greater medical out-of-pocket (OOP) expenses (Goldman, Joyce, & Zheng, 2007; HCCI, 2014). In the meantime, non-medical out-of-pocket expenses (NOOPEs) have increased greatly; yet, little research was carried out about NOOPEs incurred by middle-income individuals and their families. For families with a parent who receives cancer treatment the NOOPEs are a major concern. Families can face burdensome OOP costs for travel, lodging, food, daycare services and domestic labor are not covered by insurance. Insurance companies usually do not compensate insurers for NOOPEs expenses (Bernard, Farr, & Fang, 2011).
The impact of OOP medical expenses on families, ranging from young people to senior citizens with different education and income status have been investigated in previous studies (Azzani, Roslani, & Su, 2015; Banthin, & Bernard, 2006; Bodenheimer, 2005; Stewart, 2004; Yu & Dick, 2012). For families who are financially secure, NOOPEs may simply be absorbed into the family's allowance (Leive, & Xu 2008; Pisu, 2010; Valtorta, & Hanratty, 2013). Most lower-income families who are Medicaid beneficiaries are supported either by public or private organizations for nearly all the costs of their cancer treatments (Valtorta, & Hanratty, 2013). By contrast, for a large number of middle-income families who need to undergo long periods of treatment cycles while they are excluded from most of the coverage plans and governmental supports, there are not enough developed strategies to minimize NOOPEs. Those suffering from the chronic illness of cancer are not spared from this escalating healthcare cost. The cost of Cancer diagnosis and treatment has increased substantially over time and the financial burden on families is anticipated to growth further due to early cancer detection, improvements made to treatment technologies, an expanding life expectancy, and the aging of the baby boomer population (Sigel, De Santis, & Virgo, 2012). The gap in previous research is that studies have not evaluated the cancer treatment NOOPEs impacts on financial status and quality of life in middle-income families who have a cancer parent. Under the conditions of rising NOOPEs, the current study seeks to accurately evaluate the financial burden and its impact on quality of life among middle-income families who live in Houston. This study will investigate the relationship of non-medical expenses and families’ ability to pay for essential living costs and maintaining the quality of life via a non-experimental, quantitative correlational design. This research would observe these impacts by conducting online surveys to a convenience sample of adult patients receiving treatments in Houston, and analyze and measure the degree of association. The study outcome could be a foundation for more studies and further crucial measurements to ensure safety nets are available for this group of families. Finally, the study findings may affect middle-income family decision making and pre-planning prior to being hospitalized or starting cancer treatments.
Background of the Study
The changes in medical care services are principally focused on the expenses determined by the public health delivery framework. Notably, the relevant authorities have given little consideration to the extent of OOP expenses that individuals and families have been forced to pay (Azzani, Roslani, & Su, 2015; Tsimicalis, et al., 2013). The authorities have typically disregarded the NOOPEs as well. As such, the economic weight brought about by NOOPEs substantially expands the aggregate expenses families must bear. Medical health specialists and policy makers the health sector must take note of these realities.
In spite of the fact that more health care consumers are gaining health insurance coverage, this does not by any means fully insulate them from the burden of medical expenses (Moran, & Short, 2011). Previous research shows that patients are paying larger health plan premiums as well as incurring more OOP cost sharing for all classes of health care services (Shankaran, 2012; Thomas, Daniel, Khuperkar, & Vadnerkar, 2012; Collins, et al., 2006).
Various literature indicated high OOPs for Americans (Banthin, & Bernard 2006; Waters, et al., 2004). In 2013, individuals who were covered by Employer-Sponsored Insurance (ESI) paid 16.4% of their health care spending as out-of-pocket (HCCI, 2014). About 12% of American families faced OOPs while covered by private insurance. These OOPs surpassed about 10% of their annual household income (Schoen, et al. 2005; Waters, et al. 2004). Previous studies show that the impact of the growing cancer treatment OOPs attracted the attention of researchers, health care administrators, and policy makers (Lauzier, et al., 2010). Private insurance covers about 35% of all health expenses, and since private insurance plans greatly vary, the OOPs could be significant (Abramowitz, & O’Hara, 2015). Cancer insurance provides reimbursement for OOPs for 3% of the patients (Arozullah, Calhoun, & Wolf, 2004). This reimbursement rate causes a financial burden among 98% of patients with an annual income of under or equal to $30,000 per household. The financial burden is for 46% for $30,001-$60,000 annual household income patients and about 26% for families with an annual household income over $60,000 (Arozullah, Calhoun, & Wolf, 2004).
Insured patients are spending more OOPs for cancer treatments and the financial burden of cancer causes financial toxicity due to increased cost sharing (Eaddy, Cook, & O’Day, 2012; Tsimicalis et al., 2013; Yu, & Dick, 2012; Zafar, et al., 2013). Families of cancer patients drain their savings and acquire unaffordable debts (Williams, Williams, & Williams, 2014). They are forced to choose between cancer treatments and other essentials vital to living a decent life. This can affect the treatment decisions and deteriorate patients’ well-being (Zafar, et al., 2013). Other studies define the financial difficulties of cancer that are increasing in the United States due to significant intensity of prevention or health care service use and escalating cancer care expenses (Brown, & Yabroff, 2006; Collins, et al., 2006; Eaddy, Cook, & O’Day, 2012). The economic restrictions of OOPs for families with kids cause socioeconomic disparities which may end with the bankruptcy of these families (Azzani, Roslani, & Su, 2015; Fay, Hurst, & White, 2002; Galbraith, et al., 2009; Williams, Williams, & Williams, 2014; Wong, Kim, & Newacheck, 2005).
Research on the consequences of the financial burden imposed by cancer reveals that after a cancer diagnosis and through the treatment period, families have to make financial adjustments to cope economically (Bestvina, Zullig, & Zafar, 2014; Syse, Tretli, & Kravda, 2009). Financial distress is another consequence of the erosion of employment-based private insurance, and it has a greater impact on middle-income families (Timmons, Gooberman-Hill, & Sharp, 2013; Valtorta, & Hanratty, 2013). The financial toxicity of cancer needs to be noticed together with the physical and emotional toxicity of the illness itself; they are parallel effects (Syse, Tretli, & Kravda, 2009; Ubel, Abernethy, & Zafar, 2013; Williams, Williams, & Williams, 2014). Health insurance does not remove the financial distress and health disparities among cancer patients (Galbraith, Wong, Kim, & Newacheck, 2005; Zafar, & Abernethy, 2013; Zafar, et al., 2013).
Another important cancer-related burden on families is the emotional burden. This burden is mostly clouded by financial problems imposed on cancer individuals and their families (Gupta, Lis, & Grutsch, 2007; Zaidi, Ansari, & Khan, 2012). Patients and families may experience anger, fear, stress, anxiety and depression, which can be increased as a result of financial burdens (Julkunen, Gustavsson-Lilius, & Hietanen, 2009; Cotrim, & Pereira, 2008). Studies found an inter-relationship between emotional and economic problems of cancer. Social reaction and emotional response could increase the suffering and stress associated with either cancer or the toxicity of treatment alternatives (Q Ceileachair, et al., 2012). A large population of families with a cancer-diagnosed parent are challenged with emotional and mental distress and need consultation services (IM, 2007; Northouse, Mellon, Harden, & Schafenacker, 2008; Weaver, Rowland, Alfano, & McNeel, 2010).
Recommendations for means to assist families struggling with cancer have been indicated in the relevant literature. Studies suggest that in order to reduce financial distress and address the impact of costs on decision making with respect to treatment, individuals and clinicians should communicate about expenses (Alexander, Casalino, & Meltzer, 2003; Bullock, Hofstatter, Yushak, & Buss, 2012). Studies recommend that governmental and private organizational financial support programs should be established to assist with cancer treatment expenses (Zaidi, Ansari, & Khan, 2012; UDHS, 2014; Tucker-Seeley, & Yabroff, 2016). Other sources of back-ups include relatives, friends, workplaces and state health and social welfare services; these may provide dramatic mental and financial support before, through and after the treatment process (Q Ceileachair, et al., 2012; Wagner, et al., 2011; Weaver, Rowland, Alfano, & McNeel, 2010). Through statistical analysis this study aims to examine the relationship between NOOPEs and the quality of life among middle-income families as well as investigating if the affordability of living expenses is affected when a parent is receiving cancer treatment. The study results could be a foundation for healthcare policy makers for further crucial measurements to ensure safety nets are available for this group of families as well as helps in decision-making and pre-planning prior to being hospitalized or starting cancer treatments.
Recent data suggests that government policy makers have started to implement some strategies to reduce health care spending, including OOP costs (Tucker-Seeley, & Yabroff, 2016). Looking closely at this data we can see that NOOPEs continue to be neglected; government or healthcare officials have paid no significant attention to them. The focus of this study would be on assessing the relationship between NOOPEs of middle-income families and their financial abilities to shoulder the burden of expenses essential to living a quality life. The findings of this research may identify weather the middle-income families are at high risk of facing financial difficulty and how it affects family decision-making and pre-planning prior to being hospitalized or starting cancer treatments.
The general problem is that the OOPs elaboration along with NOOPEs is expected to continue since the health-related expenses for chronic or long-term illnesses continue to escalate, yet no coverage is available for out-of-pocket expenses (Azzani, Roslani, & Su, 2015; Porterfield, & DeRigne, 2011). Non-medical expenses for cancer families including meals, travel, lodging, daycare and domestic labor expenses and loss of employment or decreasing income and loss of productivity can exceed the entire hospitalization or treatment expenses (Martin, et al., 2014). The combination of escalating NOOPEs and OOPs can result in a significant deterioration of the families’ financial status throughout the cancer treatment period.
Considering the existing knowledge, the affiliated expenses of NOOPEs in middle-income families with a cancer parent are not fully addressed. The specific problem is that the increasing NOOPEs adversely affect middle-income families’ ability to pay for life essentials and quality of life. The existing studies have indicated various components of medical OOP costs for the cancer patients at home and in the hospital but their analysis of the impacts of NOOPEs has been limited (Goldman, Joyce, & Zheng, 2007). Previous studies are lacking in the availability of extensive evidence showing the relationship between NOOPEs financial burden and families’ quality of life (Azzani, Roslani, & Su, 2015; Porterfield, & DeRigne, 2011). To fill this gap in knowledge, the current study investigates whether there is a relationship between NOOPEs and families’ ability to pay for housing and utilities as essential expenses as well as to pay for vacation, entertainment and additional classes for kids as components of a quality life.
Purpose of the Study
The purpose of this non-experimental quantitative correlational research is to explore if a relationship exists between NOOPEs and quality of life standards in middle-income families who have a cancer parent and live in Houston. A quantitative method is appropriate to reveal families’ financial burdens when facing cancer treatments. The research design is a correlational approach, determining the association of NOOPEs and middle-income families’ abilities to pay for essential expenses as well as maintaining a quality life. The correlational approach would be proper for this research to demonstrate association between variables (Polit, & Beck, 2012). The study’s primary research variables include direct non-medical costs, indirect costs and middle-income families’ ability to afford the expenses attendant to a quality life. Independent variables include costs of travel, lodging, food, daycare and domestic labor costs as well as unemployment including lost work time and reduced productivity. Dependent variables include ability to pay rent/mortgage, utility bills, entertainment and vacation expenses or additional classes for kids. The aim of this non-experimental correlational quantitative study is to assess if NOOPEs impacts the quality of the lives of middle-income families residing in Houston and facing a parent’s cancer costs. These impacts include: (a) the ability to pay housing expenses such as mortgage and rent, (b) the ability to pay utility bills such as water, phone, internet, gas, and electricity, (c) the ability to maintain quality life standards (e.g. vacation, entertainment and kids’ additional classes).
To achieve the purpose of the research, online surveys will be conducted through Survey Monkey to determine the relationship between NOOPEs and its impact on a family’s ability to pay for housing, utility bills as well as vacations and entertainment. Families who live in Houston, have one parent receiving cancer treatment, and have middle-income status will categorize the respondents. The middle-income status would be classified based on family income and the definition of middle-class on a federal level, in Texas, and more specifically, in Houston. The survey questions will indicate five levels of impact (Likert-type Scale). Number one indicates very low impact and number five indicates high level of impact.
Research Questions and Hypothesis
The questions posed by this research project are formulated with a view to the data gathering on the basis of a review of the relevant literature. The research questions address the aim of clarifying the main problems to be considered by this project. The study questions propose to test whether there is a relationship between the financial impacts of cancer NOOPEs and middle-income families’ ability to pay for essential expenses and to maintain the quality of life when a parent receives cancer treatments. Three sets of hypotheses serve as the basis for this research project with a view to answering such questions. According to Creswell (2014), hypotheses are a set of statements suggested to estimate a result or explain the association among variables. As Creswell (2014) posits, in a study the null hypotheses determine no relation or a non-status change among variables. In this study, the hypotheses and null hypotheses are generated according to the questions of the study. The outcomes of the present correlational quantitative research will help to provide answers for the following three research questions and the null and alternative hypotheses for each of the questions posed by this study:
Research Question 1 (RQ1): What is the relationship between NOOPEs and the ability of middle-income families in Houston with a cancer parent to pay for rent and mortgage?
H1O: A statistically significant relationship does not exist between NOOPEs and the ability of middle-income families in Houston with a cancer parent to pay for rent and mortgage.
H1A: A statistically significant relationship does exist between NOOPEs and the ability of middle-income families in Houston with a cancer parent to pay for rent and mortgage.
Research Question 2 (RQ2): What is the relationship between NOOPEs and the ability of middle-income families who live in Houston with a cancer parent to pay for utility expenses (water, gas, phone and electricity)?
H2O: A statistically significant relationship does not exist between NOOPEs and the ability of middle-income families living in Houston with cancer parent to pay for utility expenses (water, gas, phone and electricity).
H2A: A statistically significant relationship does exist between NOOPEs and the ability of Houston-dwelling middle-income families with a cancer parent to pay for utility expenses (water, gas, phone and electricity).
Research Question 3 (RQ3): What is the relationship between NOOPEs and the ability of middle-income families who live in Houston with a cancer parent to pay for expenses that maintain quality of life including vacation, entertainment and additional classes for kids?
H3O: A statistically significant relationship does not exist between NOOPEs and the ability of middle-income families who live in Houston with cancer parent to pay for expenses that maintain quality of life including vacation, entertainment and additional classes for kids.
H3A: A statistically significant relationship does exist between NOOPEs and the ability of middle-income families who live in Houston with a cancer parent to pay for expenses that maintain quality of life including vacation, entertainment and additional classes for kids.
Findings from the literature review focused on direct and indirect costs of cancer either for Medicare beneficiaries or privately insured patients (Calhoun, & Bennett, 2003; Davidoff, et al., 2013; Jönsson, & Wilking, 2007; Meropol, Schrag, & Smith, 2009; Tangaka, et al., 2010). Various researches assess the association of emotional distress and the financial burden of cancer (Bestvina, Zullig, & Zafar, 2014; O’ Ceileachair, et al., 2012; Zafar, et al., 2013). A systemic review of financial restrictions experienced by individuals with cancer and their families noted that cancer treatments require high financial costs and the burden of expenses cause cancer patients and their families to struggle economically (Azzani, Roslani, & Su, 2014). The present study will examine the relationship between NOOPEs and middle-income Houston families’ ability to pay for essential expenses and maintaining quality of life while a parent is receiving cancer treatment. The outcomes of the study could be a base for healthcare policy makers for further crucial measurements to ensure safety nets are available for this group of families. The findings of the research could help families in decision-making and pre-planning prior to being hospitalized or starting cancer treatments.
Significance of the Study
Leadership Significance of the Study
Previous studies show that the excessive impacts of financial burdens on families who face cancer treatment expenses can result in problems with paying bills or even bankruptcy (Caswell, & O’Hara, 2010; Cunningham, & Bernard, 2008; Abramowitz, & O’Hara, 2015; Arozullah, Calhoun, & Wolf, 2004). Researchers have revealed that serious attention has never been paid to the NOOPEs for families, as compared to the few healthcare and medical services that obviously increase net costs incurred by cancer patients and their families (Baiker, & Goldman, 2011; Calhoun, & Bennett, 2003; Catlin, Poisal, & Cowan, 2015). This research may help leaders and policy makers consider developing tools to assist middle-income families in dealing with these expenses during the medical treatments of their parents. The analysis of the finding from this study will provide significant insights for government officials and insurance agencies regarding the effects of NOOPEs on the lives of middle-class families who live in Houston and are exposed to cancer’s direct and indirect expenses. Through such insights government officials and health care leaders may use the study findings to form new policies that may reduce NOOPEs for middle-income families in Houston or provide some adjustments and support nets before and through the cancer treatment process.
Cancer Support Significance
For higher-income families, NOOPEs can be simply merged into the budget of the family (Leive, & Xu 2008; Pisu, 2010; Valtorta, & Hanratty, 2013). However, many middle-income families who need to undergo a long treatment period need to develop adjustments to minimize NOOPEs, such as applying for discounted or free hospital lodging and demanding cafeteria and parking coupons. Current study may explore the degree of financial burden and the severity of NOOPEs impacts on middle-income families’ lives throughout a parent’s treatment period. In addition, this study may be a cornerstone for future researchers to build on the obtained knowledge. The study may show the importance of the non-medical financial burden from cancer as a lasting illness that requires noticeable financial expenses and may degrade families’ lives. The findings of this research may identify weather the middle-income families are at high risk of financial difficulties. The study outcome could be a foundation for more studies and further crucial measurements to ensure safety nets are available for this group of families. This study may help future researchers to explore the total (direct, indirect, and hidden) cost of cancer treatments and how it affects middle-income family decision making and pre-planning prior to being hospitalized or starting cancer treatments. NOOPEs also cause emotional and psychological stress on middle-income families’ that needs to be investigated in future research projects.
Nature of the Study
The current study incorporates a non-experimental quantitative method of research with a correlational approach by utilizing an online survey to determine the correlation between the dependent and independent variables (Creswell, 2014). A correlational approach is a quantitative systemic description of an area of interest or a condition that needs to obtain facts for testing a study’s hypothesis and by utilizing a representative sample of target population (Vogt, 2007). Current research focuses on quantitative data and analysis. The study does not involve a mixed-method or qualitative component.
According to Polit and Beck (2012), quantitative research could descriptively or experimentally indicate the relationship among variables. In order to find an appropriate research method, researcher must identify possible extraneous variables and conditions that need to be controlled or minimized through design element (Dwyer, & Brnauer, 2014). New populations or subpopulations that the study would be generalized based on, should be determined as well. A qualitative approach can be used to understand phenomenon of a study or to discover the meaning of that phenomenon (Greener, 2011). The mixed method design is a mixture of both qualitative and quantitative approaches consisting of the analytical process of deduction, induction, and abduction to avoid the restrictions of either quantitative or qualitative approaches (Greener, 2011). In the current study, a correlational quantitative method will be applied to test variable relationships and the extent to which the dependent variables might have been predicted by the independent variables. Based on Dwyer and Bernauer (2014), using the quantitative research method provides researchers with three major components of design, measurement, and statistics. Unlike qualitative or mixed-method approach, quantitative correlational design can identify the extent to which the variables can use covariance (Neuman, 2011). For this study, a qualitative research method cannot be chosen since it indicates the meaning and understanding of a phenomenon of study with no plan in advance to provide comparison (Cone, & Foster, 2006). Moreover, qualitative method is not applicable in the present study because a qualitative approach can be used to study research problems when what is required is the exploration and understanding of a central phenomenon, rather than testing existing hypotheses with a view to answering research questions. In comparison to quantitative research, qualitative approaches are focused on explaining human behavior within the framework of the social structure that is the context for a given form of behavior. For the current study, the researcher will apply online for a modified MPES-HC, Likert-type survey. Since there is no face-to-face contact with respondents, a quantitative approach would be the most appropriate method of study. By contrast, qualitative research provides a context to understand nuanced complicated situations where social vagueness and different interpretations exist (Greener, 2011). A qualitative method is appropriate for an explanative study wherein the investigator would be engaged in a continuous and thorough contact with respondents (Creswell, 2014). Meanwhile throughout the research process, the psychological distance between participants and investigators declines, so protection from the contamination of quantitative research data through the inadvertent use of a mixed-method is essential (Christensen, et al., 2010). Neither qualitative nor mixed-method approaches could produce quantifiable data to identify whether a correlation between the dependent and independent variables exists.
Applicability of the Selected Design
Many elements support the selected quantitative methodology for this research. The goal for this non-experimental quantitative correlational research is to assess how the NOOPEs influence middle-income families’ abilities to afford the expenses attendant to living a quality life while a parent is receiving cancer treatments. The quantitative methodology could be appropriate to provide quantifiable responses to the questions of this study. The aim of the study is to indicate whether there is a correlation between the independent variables (travel, lodging, food, daycare and domestic labor expenses and unemployment including lost work time and reduced productivity) and dependent variables (ability to pay for housing, utilities, vacation, entertainment and additional classes for kids). By using a quantitative correlational research design, correlational statistics can be applied to evaluate and describe the degree of association among the independent and dependent variables of the research. Correlational design can be applied when investigators do not launch an intervention but intend to evaluate the relationship among variables instead of assessing the effect of one variable on the other variable (Christensen, et al., 2010).
A self-administered questionnaire (SAQ) will be used to gather background and demographic information including gender, age, size of family, socioeconomic status, highest level of education, employment status and residence area. Moreover, to describe perceptions of financial burden on the middle-income families that have one parent being treated for cancer, a modified MEPS-HC quantitative Likert-type survey would be applicable to test dependent and independent variables in order to provide answers. Survey design can appropriately help to collect the data for correlational statistical analyses (Dwyer, & Brnauer, 2014). By utilizing a five-point Likert-type survey, participants can rate the relationship between NOOPEs expenses of cancer treatment and the ability to maintain quality living standards as well as the affordability of housing and utilities. Inferential analysis would be applied to address the study questions.
The quantitative approach is built on a positivist epistemology and a top-down methodology, involving an objective framework, standards of precision, reasoning, and replication. The correlational research design, with its closed questions, can assess the quantitative influence of the independent variables of out-of-pocket expenses on the dependent variables of quality of life and the affordability of mortgage, rent, and utility payments. The Likert-type survey is appropriately conducted online because previous studies revealed that the self-report information allows for the participation of various families (Greenberg, et al., 2010). The Likert-type survey provides a fixed choice reply format and is designed to evaluate respondents’ viewpoints (Vogt, 2007). The MPES survey based on a Likert-type scale is a highly reliable validated instrument which will be applied to measure the correlation between NOOPEs and quality of life as well as other necessary expenses. A Likert-type scale provides one metric of very low impact and five levels of high impact (Vogt, 2007). The sample of the study included middle-income families who live in Houston and are faced with medical costs due to a parent’s cancer treatment. Families above or below the middle-income range would not be considered as samples and those who do not include a cancer parent will be excluded from the study population. The middle-income status would be classified based on family income, and the federal and Texas state definitions of middle-class. Using a correlational matrix will show the dependency relationship between variables (Christensen, et al., 2010).
The Characteristics of Population and Sample
The considered population for the non-experimental quantitative correlational study will include families who live in Houston, have one parent receiving medical treatment, and are of middle-income status, which according to the United States Census Bureau (USCB, 2015) mean that they have an annual household income of between $34,496 and $103,408. While in the same year (2015) in Houston the median income was $48,604 per household, and the Texas State median income was $55,653 (City-Data, 2015). Based on the City Data website, in 2015, 47% of a total of 884,000 households in Houston were middle-income families, which amounts to 397,000 households. According to the Texas Cancer Registry (2017), the number of cancer incidence in Houston was 8,915 in 2013. Assuming a 95% confidence level, with a -/+5 confidence interval, and a population of 8,915 cancer cases, a sample size of 368 is targeted (Survey System, 2017). Families whose parent is not diagnosed and treated with cancer will be excluded. Other households except middle-income families will not be part of the study population. The middle-income status would be classified based on family income, and federal and Texas state definitions of middle-income. According to Houston City Data website (2017), the middle-class is defined as those making between 67% and 200% of the state’s median income. The recruitment of participants is via public announcement research study participation flier on Facebook social media boosted in the Houston area, such as personal news feed, Iranian Community of University of Houston page (ICUH), Iranian Renaissance Cultural Foundation page, Iranian Cultural Foundation of Houston (ICF). The flyer includes the description of the problem under investigation, description and goals of the study, participants' requirements and the incentive for participating in the research. The survey link Is included in the flyer. The flier determines the participants' specifications required for the study (middle-income cancer patients live in Houston and going to volunteer 20 minutes of their time to answer an online survey). Among returned applications only those who live in Houston whose families' income is in the range for middle income with a cancer parent will be selected. The others who complete the survey and do not meet these requirements will be excluded. In a quantitative correlational study, smaller samples are needed for homogeneous populations (Leedy, & Ormond, 2010). According to Collins (2003), for a correlational quantitative study to be statistically significant there must be a minimum of 30 questionnaires returned for each variable. For this non-experimental quantitative correlational study, the usual sample size needs to be about 30 families as a pilot and can be increased to provide sample saturation. To clarify the purpose of study a description of the study will be included in the flyer as well as contact information to contact for any question regarding the study. It is expected that one third of surveys will be replied to and returned. The researcher started analyzing the data when 45 surveys returned.
The study recruitment flyer invites participants from middle-income families with a cancer parent who live in the greater Houston to reply the online MEPS-HC survey. The Household Component of the Medical Expenditure Panel Survey (MEPS-HC), is a nationally characteristic survey of the U.S. non-institutionalized population which is developed by the Agency for Healthcare Research and Quality (AHRQ, 2017). The MEPS questionnaire can collect comprehensive data on medical spending, socio-demographic and employment features. The household component of this survey explores health care use and payment by individuals, and their families that is a self-administered questionnaire (SAQ) administered by AHRQ in association with the Centers for Disease Control and Prevention, the National Cancer Institute, and the American Cancer Society in 2011. Questions regarding study variables, search families’ attitudes about the impact of the economic difficulties of NOOPEs on the quality of life of families. The adjusted MPES survey includes questions about direct and indirect non-medical costs. The MEPS questionnaire would be slightly revised to represent questions to assess whether NOOPEs affect families’ ability to pay for housing, utility, vacation, entertainment and additional classes for kids’ expenses.
In this study, a quantitative survey is appropriate to examine dependent and independent variables to provide answers to research questions. The online MEPS survey will be hosted on the Houstonian Cancer Experience website. Because the study is trying to measure families’ attitudes and opinions about the financial impact of NOOPEs on a family’s ability to pay for both the essentials of life and, beyond this, to maintain a quality life, a Likert-type scale is one of the most reliable survey scales. A Likert-type scale measures viewpoints using answer choices that range from one extreme to another. Unlike a simple yes / no question, a Likert-type scale accurately uncovers the degree of relationship among variables of the NOOPEs and its effects on a middle-income family’s quality of life. The survey questions will indicate five levels of impact. Number one indicates very low impact and number five indicates a high level of impact.
Conceptual / Theoretical Framework
The financial impact of NOOPEs can greatly inflate the overall expenses that patients and families must undergo (Newackeck, & Kim, 2005). The financial obligations of families would be affected significantly during the treatment and these obligations can impact a family’s quality of life. The escalating cancer-related financial hardship on patients and families is confirmed by the American Society of Clinical Oncology (Meropol, Schrag, & Smith, 2009). Non-medical costs represent a large part of families’ expenditure throughout the treatment period (Cunningham, 2009). NOOPEs are clearly a serious burden to families in particular and the society as a whole, but they become generally invisible in economic analyses done from a more restricted perspective (Abramowitz, & O’Hara, 2015). Evaluating the financial burden caused by medical expenses has, over the course of the past decade, become the subject of extensive research. (Waters, Anderson, & Mays, 2004; Arozullah, Calhoun, & Wolf, 2004; Caswell, & O’Hara, 2010; Zafar, 2013). The review of literature provides a complete inspection of previous researches on conceptual or theoretical frameworks, patient costs, explanation of various types of expenses, approaches to evaluate the cancer expenses, information about income and its usage as an indicator, gaps in knowledge and methodological issues. Various theories and approaches are used in previous studies with regards to the economic dimensions of health care (Waters, Weinberg, & Bennett, 1998; Smith, Clarke, & Berry, 2001), including the Economic Burden of cancer (Brown, & Yabroff, 2006; Menses, 2007; Pisu, et al., 2010; Sherwood, et al., 2008), Micro-costing Approach (Schreyogg, 2008; Zafar, & Abernethy, 2013), and Health Financing Transition Theory (De Ferratini, 2007; Savedof, et al., 2012; Fan, & Savedof, 2014). Different research explores the impacts of OOP medical spending on American families (Chernew, Gibson, & Yu, 2008). Theoretically, these OOP expenses help to constrain the demand for medical services, and can lead to a cost-related decrease in seeking medical services, which contributes to worse health outcomes (Eaddy, 2012; Himmelstein, Thorne, & Warren, 2009; Weaver, Rowland, & Bellizzi, 2010). Yet deliberations, discussions, and studies have not focused on impacts of cancer NOOPEs on middle-income families’ financial status and quality of life.
A variety of theoretical frameworks can be considered to understand the various aspects of the financial burden of cancer. Theoretical frameworks, which are used by other researchers enhance understanding of other dimensions of cancer difficulties that patients and families face (such as costs of cancer or treatment outcomes) rather than the NOOPEs impacts on the quality of life status of families (Brown, & Yabroff, 2006, Menses, 2007; Pisu, et al., 2010, Sherwood, et al., 2008). The relationship between NOOPEs and its influence on middle-income families’ ability to pay for housing expenses, utility bills and maintaining living standards (e.g. vacation, entertainment and additional classes for kids) while a parent is receiving treatment, would be examined in the present study. In this research, consideration of the Micro-costing Approach and Health Financing Transition Theory aid in the conceptualization of NOOPEs impacts and outcomes on families’ survival and maintenance of quality of life when a parent is faced with cancer treatment (Collins, 2014; Cunningham, 2009: Tangaka, Trogdon, & Richardson, 2010). The concept of the current research study would be framed as follows, based on the relationship between cancer’s direct and indirect NOOPEs, and the ability to pay for essential expenses and maintain quality of life: (Fig 1).
Figure 1: This study will be operated based on a conceptual framework that will assess cancer’s financial burden on families’ ability to pay for life essentials and maintain quality of life.
The study considers direct and indirect non-medical costs as expenses that do not include the treatment itself, and consist of travel, lodging, food or dietary needs, daycare and domestic labor expenses, and unemployment including lower working hours and loss of productivity.
Thorough review of the literature with regards to NOOPEs impacts on middle-income families’ quality of life failed to provide a theoretical framework for this study (Bona, 2013; Calhoun, & Bennett, 2003; Greenberg, et al., 2010; Gupta, Lis, & Grutsch, 2007). However, some aspects from previous research, recalibrated to the goals of the present study, can provide a conceptual framework. The majority, of the specific data about cancer-related expenses is for direct OOPs of medical costs (Arozullah, Calhoun, & Wolf, 2004; Catlin, Poisal, & Cowan, 2015; De Souza, & Wong, 2013; Cunningham, 2009; Caswell, & O’Hara, 2010; Noel-Miller, 2013) rather than for direct and indirect non-medical costs. To indicate NOOPEs, the current study will consider the expenses burden of middle-income patients and families for travel, lodging, food and dietary expenses, daycare for kids and domestic labor as well as unemployment including lower working hours and loss of productivity. Non-medical expenses do not directly involve cancer treatment, but they consequently occur and it is important to provide a comprehensive image of invisible financial burdens, through factorizing NOOPEs in detail.
The conceptual framework of this quantitative correlational study would be established based on the Economic Burden of Cancer conceptual framework that is administered by Brown and Yabroff (2006), who explain the financial difficulty as loss of opportunity and economic resources related to the occurrence of cancer (Fig 2). Based on the conceptual model of Brown and Yabroff, financial difficulty can be evaluated by three expense categories of direct; indirect; and psychosocial expenses. Yabroff then determines direct expenses as medical related expenses for cancer treatment including hospital bills, physician fees, pharmacy and diagnostic services. Third party payers cover medical expenses when patients are insured, and cancer patients and their families would pay the OOPs. According to Yabroff (2006), non-medical direct expenses are necessary expenses that are paid to acquire treatment including travel to a medical organization and physicians’ offices, lodging, food or dietary needs and daycare and domestic labor services (Brown, & Yabroff, 2006). Yabroff further posits that non-medical indirect costs refer to other financial restrictions such as forgoing vacation, entertainment and additional classes for kids, consuming savings for retirement, delaying education and schooling plans. Ultimately psychosocial expenses are highlighted by various studies, including treatment costs for psychological side effects generated by cancer such as anxiety, depression, insomnia, marital discord and negative impacts of family and social relationship changes (Menses, et al., 2007; Sherwood, et al., 2008; Yabroff, & Brown, 2006).
Figure 2. The conceptual framework of the Economic Burden of Cancer, adopted from: Brown and Yabroff, 2006.
This research also overviews the theory of “The Health Financing Transition” which shows that when health spending per person increases, the share of OOP expenditure on medical services falls. This conceptual framework is proposed first by De Ferratini in 2007 and then developed by Savedoff, et al. in 2012. The theory showed remarkable consequences for equity and growth of public health. By using health-financing transition, Savedoff, et al. (2012) illustrate a growth in overall per person health expenditure, associated with less of a raise in OOP spending. Fan and Savedoff (2014), utilize health-financing transition to show that overall health care OOPs have no connection with income level, but are affected by increasing general revenue related to a country’s capacity. Various researchers assume that the OOP share is affected by age, sex, illness and health insurance more than other elements (Galbraith, et al., 2005; Wagner, et al., 2011). By contrast, some researchers claim that for higher-income families the health expenditure consists a smaller portion of income (Leive, & Xu 2008; Valtorta, & Hanratty, 2013). However, growth of family income and health insurance demands can cause pooled health expenditure to experience long-term growth (Valtorta, & Hanratty, 2013).
This non-experimental quantitative correlational study may also consider the conceptual framework of “Micro Costing Approach”, since this approach is a method for expense estimation that provides detailed evaluation of economic expenses of direct and indirect medical services. The approach tries to accurately estimate expenses and benefits of health services, and consists of all variable and fixed expenses of medical and non-medical services for patients at local prices. Micro costing also tries to estimate hidden expenses including patient’s consumed time and relatives' work time loss, by utilizing interpolation expenses or shadow prices. Neyt, Albrecht and Cocquyt (2006), applied this method to evaluate the cost of medication (Herceptin) utilization in cancer treatment. Micro costing helps the investigator to speak with confidence about the medical costs as well as indirect expenses that are not directly paid for the treatment but valued as money. These expenses include direct non-medical costs, meaning time, buying non-medical services, and lastly, intangible expenses that include non-financial consequence of illness and health care (Fan, & Savedoff, 2014).
As data gathering instrument, a modified survey of Medical Expenditure Panel Survey-Household Questionnaire (MEPS-HC) would be applied. MEPS can collect detailed data on health care expenditures, socio-demographic, and employment characteristics. The modified questions include the assessment of direct non-medical costs including travel, lodging, food or dietary needs and daycare and domestic labor as well as indirect non-medical costs including lower working hours and loss of productivity. The survey can be applied to 18 years old and older participants, through email-back surveys that consist of the Consumer Assessment of Health Plans (CAHPS) questions as well as the EuroQol 5D, the SF-12, and viewpoint questions. The added demographic questionnaire to the beginning of MEPS was administered in 2000 for the first time (AHRQ, 2017).
The MEPS survey does not explore intangible costs like physical and long-lasting psychological effects of cancer treatment, which represent non-financial outcomes of cancer and medical care that nonetheless also burden families (AHRQ, 2017). The generated questionnaire of the study will further examine concepts of decreasing the ability of middle-income families to pay essential expenses and maintain families’ quality of life related to NOOPEs when a parent is being treated for cancer. The researcher will explore whether the study data can confirm the literature results about determinants of NOOPEs impacts on the quality of life of Houston middle-income families when a parent’s cancer forces them to face invisible expenses. To prepare a variable matrix for the present study, the independent variables include costs of travel, lodging, food, daycare and domestic labor costs, as well as unemployment including lower working hours and loss of productivity. Dependent variables of the study include ability to pay for rent or mortgage, pay for utility bills, and pay for entertainment, vacation and additional classes for kids. Travel, lodging, food, daycare and domestic labor expenses are considered direct non-medical costs for patients and families, while indirect costs include lower working hours and loss of productivity. The modified MEPS survey can be considered as data gathering instrument for this research.
Variable/ Survey Table of the Study
|Variables||Modified MPES-HC||Modified SAQ||Data Type||Questionnaire Modification|
|Travel expenses||NA||Prospective Quantitative Data (PQD)
|Self-reported measure based on 5 scale Likert-type|
|Longing expenses||NA||PQD, interval||Self-reported, Likert-type|
|Food costs||NA||PQD, interval||Self-reported, Likert-type|
|Daycare and domestic labor costs||NA||PQD, interval||Self-reported, Likert-type|
|Lower working hours||NA||Q8,Q9,Q11||PQD, ratio||Self-reported, Likert-type|
|Loss of productivity||NA||Q36,Q37,Q39||PQD, ratio||Self-reported, Likert-type|
|Ability to pay rent/mortgage||NA||PQD, ordinal||Self-reported, Likert-type|
|Ability to pay for utilities||NA||PQD, ordinal||Self-reported, Likert-type|
|Ability to pay for entertainment /vacation||NA||PQD, ordinal||Self-reported, Likert-type|
Scope and Delimitations
The current research is a non-experimental quantitative correlational study that examines the relationship between NOOPEs and middle-income families’ ability to pay for housing, utilities, vacation, entertainment and additional classes for kids to keep a quality life during the cancer treatment period of a parent. The independent variables are expenses with regards to obtaining treatments including travel, lodging, food, daycare and domestic labor, as well as unemployment including lower working hours and loss of productivity. The dependent variables of the study are the ability to pay for housing and utility bills, and maintaining the quality of life includes paying for vacations and entertainment. The scope of the study would be restricted to middle-income families, who live in Houston and have a parent who received cancer treatments. The respondents would be included from the respondents to the research study flyer posted on public social media (Facebook pages of Iranian Renaissance, Iranian community of University of Houston and personal news feed). The study instrument would consist of a web-based survey modified from MEPS that will also include a demographic profile designed to gather personal information about each respondent includes gender, age, size of family, socioeconomic status, highest level of education, employment status and residence location. The online survey link would be mentioned in the research flyer. The respondents’ information would be accumulated securely and keep confidential, in a way that does not identify the participants even after submission the completed surveys.
Delimitations highlight the borders of the study, explain the assessment parameters and identify what is not included in the study (Leedy, & Ormrod, 2010). Delimitations to the research can lower the study results’ generalization. The study sample demographic would be limited to Houston, which would lower the generalizability of the findings to all cancer families around the country. The research would be limited to middle-income families and will not be inclusive of other family statuses. The financial burden of NOOPEs impacts on families’ ability to pay for essential life expenses and quality of life would be examined in the current research. Because of the broad psychological effects of cancer on patients and families, expenses attendant to the evaluation of the psychological consequences would be excluded from this study. Only the financial burden of NOOPEs for cancer during the treatment period will be analyzed in the present research project, and not the long-term effects of this financial burden. The NOOPEs effects among middle-income families who have a parent with cancer will be evaluated and the cancer treatment of other family members, such as children or grandparents, will be excluded.
Assumptions and Limitation
Assumptions are unproved original beliefs and points in a concept or theory that are essential in generating a conceptual or theoretical framework upon which research is based. (Neuman, 2011). In the present study the first assumption would be that a representative sample of at least 30 families from 368 participants out of the 8,915 populations of cancer patients would truthfully report the impacts of financial burden of NOOPEs on the families’ financial status and quality of life. In this study participants’ answers will be presented as part of a pool and not individually, so there would be no reason for the study respondents to make false statements. Per Collings (2003), a research project needs to have statistical significance. In this regard, a minimum of 30 questionnaires must be returned. According to this figure, the study sample would be large enough and the final numbers would depend on response rates. As the second assumption suggests, the validity and reliability of the study instr