An Adapted Model of Cost-Related Nonadherence to Medications Among People With Disabilities

Abstract

Despite emerging evidence on cost-related nonadherence (CRNA) to prescription medications, there is little conceptualization and exploration of this phenomenon with respect to disability. Specifically, there is a gap in the literature that explores factors influencing medication cost–adherence relationship among individuals living with a disability. To advance research on and policy for CRNA to medications among people with disabilities, we need a framework that can contribute towards guiding solutions to this problem. We examined the applicability of Piette and colleagues’ existing model for CRNA to the context of people with disabilities and suggested an adapted model (CRNA to medications for persons with disability [CRNA-d]) that can provide a more specific conceptualization of CRNA with respect to disability. The adapted CRNA-d model depicts that CRNA to prescription medications with respect to disability is a dynamic and multifaceted phenomenon, determined by various socioeconomic, disability-related, medication-related, prescriber-related, and system-related factors. We discuss how higher susceptibility to health complications, barriers to income and employment, additional health care costs, the complexity of medical regimens, limited access to physician services, and other policy-related factors increase the risk of persons with disabilities to face cost-related barriers to fulfill their necessary medications.

Keywords

Prescription medications play an important role in the treatment and prevention of disease and disability, and promotion of health and well-being (Bigdeli et al., 2013; World Health Organization [WHO], 2003). However, with the worldwide increase in the cost of medications, cost-related medication underuse has now become a public health concern (Cutler, Fernandez-Llimos, Frommer, Benrimoj, & Garcia-Cardenas, 2018). Evidence is emerging that many low-income persons who are chronically ill forgo their medications due to cost, which is commonly referred to as cost-related nonadherence (CRNA) to medications (Soumerai et al., 2006). Despite emerging evidence on cost-related underuse of prescription medications, there is little conceptualization or exploration of this phenomenon with respect to disability (Gupta, McColl, Guilcher, & Smith, 2018).

People with disabilities, that constitute around 15% of the world population, are often economically disadvantaged and are much more likely to live below the poverty line compared with their nondisabled counterparts (WHO, 2011). Globally, people with disabilities often remain unemployed or underemployed and experience greater frequency of financial stress for basic necessities such as housing, healthy food, or essential drugs (Smith, 2013). Knowing that people with disabilities incur additional cost of living (Mitra, Palmer, Kim, Mont, & Groce, 2017), costs associated with long-term use of medications further pose a lifetime economic burden (Jensen & Biering-Sørensen, 2014). However, the majority of the global literature on cost of medications and its impact on medication use or adherence does not well represent people with disabilities. Studies that do exist measure the prevalence of cost-related underuse or nonadherence to medications among people on social welfare or social assistance recipients at most (Kennedy & Erb, 2002; McLeod, Bereza, Shim, & Grootendorst, 2011; Naci et al., 2014). Thus, there is a gap in the literature that explores factors influencing medication cost–adherence relationship among individuals living with a disability.

To advance research and understand the phenomenon of CRNA to medications among people with disabilities, we need to have a framework, a system of concepts, assumptions, beliefs, or theories (Maxwell, 2011), that can contribute toward guiding solutions to this problem. An improved understanding of the cost-related barriers faced by those with disabilities will inform decision makers across the world while developing pharma-care policies to consider the needs of people with disabilities. Therefore, in this article, our purpose is to examine how the existing models for CRNA apply or do not apply to the context of people with disabilities and suggest an adapted model that can depict more specific conceptualization of CRNA with respect to disability.

For the purpose of our study, we adopted the definition of disability provided by the International Classification of Functioning, Disability and Health (ICF) that defines disability as an umbrella term for impairments, activity limitations, and participation restrictions and considers it as a complex phenomenon due to the interplay between persons’ nature of impairment and their socioeconomic environment (WHO, 2002). Our intent behind using the general definition was to suggest a conceptual model that broadly addresses persons with disabilities. Overall, our discussions are supported by the evidence from the global literature and our previous and current experiences of working with people with disabilities.

Existing Frameworks on CRNA to Medications

The most common frameworks that have been used in the literature to define, understand, or identify factors associated with CRNA to medications include the WHO’s (2003) framework of general medication adherence (De Vera, Mailman, & Galo, 2014; Després, Forget, Kettani, & Blais, 2016); Andersen and Newman’s (2005) health care utilization model (Kennedy & Morgan, 2006, 2009); and a model on medication cost pressures and nonadherence developed by Piette, Heisler, Horne, and Caleb Alexander (2006) (Kemp, Roughead, Preen, Glover, & Semmens, 2010). While the former two conceptualize general nonadherence to medication, the latter specifically focuses on cost-related medication nonadherence. Another recent notable work was by Goldsmith and colleagues wherein the authors have developed a typology of CRNA (Goldsmith et al., 2017).

In 2006, Piette and associates proposed the first conceptual model of CRNA to medications in patients who are chronically ill to set the stage for research, policy, and practice considerations to address the issue of CRNA among patients (Piette et al., 2006). Since then, the model is used widely to understand CRNA in various populations such as older adults and patients with chronic illnesses (Piette, 2009; Piette, Beard, Rosland, & McHorney, 2011; Wagner, Heisler, & Piette, 2008; Zhang et al., 2014).

According to this model, the cost–adherence relationship is determined by the interaction of a set of four factors: (a) patient characteristics (e.g., age, attitudes, and beliefs toward medications), (b) drug or treatment characteristics (e.g., reason for taking medications and complexity of dosing), (c) clinician factors (e.g., medication choice, support provided by the doctors, their attitudes, and communication about medication costs), and (d) health system factors (e.g., auditing clinicians’ prescribing and mechanisms to help low-income patients to get the financial assistance for filling necessary prescriptions) (Piette et al., 2006) (Figure 1).

Figure 1.

Conceptual model of cost-related nonadherence.

Gaps in the Existing CRNA Model

Although widely used in the United States, the Piette model has not been used to date with respect to people with disabilities, particularly in the developing countries. This is due to the fact that the model is based on American studies, which do not necessarily represent people with disabilities living worldwide, especially in the countries where health care is uncovered and paid out-of-pocket for people with disabilities. To examine this in depth, we will discuss the factors affecting CRNA, as described by Piette et al.’s (2006) model, one by one to assess its importance or applicability to people with disabilities.

A. Patient Characteristics

The first factor in the Piette model that affects CRNA to medication is patient’s demographic and socioeconomic characteristics. Piette and colleagues (2006) found that a person’s demographics, such as race, ethnicity, income, and age, have significant impact on CRNA. The authors also highlighted that individual’s medication-related beliefs and perceptions lead to general medication nonadherence. Although these factors may apply for people with disabilities, there are many more dimensions that may have a substantial effect on medication cost pressures and adherence for them. Some of these factors include the following: multidimensional nature of poverty resulting from disability; type, nature, and severity of disability; health complications or comorbidities leading to additional health care needs and costs; limited social support; and impact of age on disability.

Poverty due to disability

The World Report on Disability (2011) highlights that globally people with disabilities are much more likely to be less educated, unemployed, or underemployed and earn less than their nondisabled counterparts (WHO and the World Bank, 2011). In addition, they often face discrimination in employment and have limited access to transportation and resources to promote self-employment and livelihood activities, which in turn put them at risk of poverty (Banks, Kuper, & Polack, 2017; Maart & Jelsma, 2014; Mitra, Posarac, & Vick, 2013; Sommers, 2006). A study by She and Livermore (2007) using a national survey data showed that at the similar income level, individuals with disabilities are much more likely to experience material hardship than their peers without disabilities. This means that incomes of those with disabilities would need to be at least 3 times to reduce the prevalence of hardship to the level of others with incomes at the poverty level.

Evidence is robust that poverty and/or lack of regular employment is the primary predictor leading to CRNA to medications (Kapur & Basu, 2005; Kennedy & Morgan, 2006; Sanmartin, Hennessy, Lu, & Law, 2014), which is especially true for people with disabilities living in low- and middle-income countries (WHO, 2004). A study looking at the relationship between disability and five dimensions of economic well-being (education, employment, medical expenditures, assets, and expenditures) across 15 developing countries found that persons with disabilities experience higher rates and severity of multiple deprivations than persons without disabilities (Mitra et al., 2013). Overall, global evidence suggests that persons with disabilities are significantly more likely to be multidimensionally poor (Agyemang & van den Born, 2018; Mitra et al., 2017; Mitra et al., 2013; Pinilla-Roncancio, 2018), which in turn affects their affordability and access to health care, including prescription medications.

Type, nature, and severity of the disability

The nature of disability (i.e., physical, mental, sensory, neurological, or intellectual) has an effect on the medication use, costs, and adherence. People with disabilities may need medicines during an acute stage, a relapse, or at a chronic stage to treat various comorbidities or health conditions that may or may not be directly related to their disability (Brichetto, Uccelli, Mancardi, Solaro, & Brichetto, 2003; Jensen & Biering-Sørensen, 2014). Furthermore, a person’s disability itself can be static, episodic, or progressive; short term or long term; or painful or trivial (WHO and the World Bank, 2011). Due to the heterogeneous nature of disability, CRNA issues can be very different for people with a minor physical disability and major cognitive and, importantly, psychiatric or behavioral disabilities. For example, available research suggests that among people with disabilities, people with cognitive and developmental disabilities face more disparities in overall access to health care. Similarly, people with visual impairments as well as those with multiple limitations have been found at higher odds of forgone essential care (Horner-Johnson, Dobbertin, Lee, Andresen, & Expert Panel on Disability Health Disparities, 2014).

In addition, the type of disability changes the relationship between financial resources and important quality-of-life outcomes. For example, in Canada, poverty and unemployment rates vary by type of disability. People who have a combination of physical-sensory, cognitive, and mental disability are more commonly poor and jobless, followed by those with a mental-cognitive disability and a physical-sensory disability (Wall, 2017). Similarly, another study found that even with insurance, people with multiple disabilities had more unmet health care needs compared with people with a single disability (Reichard, Stransky, Phillips, McClain, & Drum, 2017). Therefore, the magnitude of the potential effects of disability on the relationship between medication cost and nonadherence will be greatly influenced by the disability status.

Susceptibility for health complications leading to additional health care costs

Susceptibility of persons with disabilities to develop additional complications, comorbidities, or chronic conditions is significantly higher compared with the general population (Gudlavalleti et al., 2014; WHO and the World Bank, 2011). Furthermore, disability can exacerbate comorbidity and lead to development of frailty, all of which lead to additional need for medications (Fried, Ferrucci, Darer, Williamson, & Anderson, 2004). Due to unmet health care needs, individuals with disabilities use more health professionals’ and other health services than nondisabled individuals (McColl, 2005; McColl, Jarzynowska, & Shortt, 2010). Apart from health care services, people with disabilities need extra services such as attendant care, assistive equipment, modifications to their home, special transportation, technological aids, or rehabilitation services, all of which lead to added health care costs and burden (Krueger, Noonan, Trenaman, Joshi, & Rivers, 2013; Maart & Jelsma, 2014; Mitra, Findley, & Sambamoorthi, 2009). However, most of these costs are either not covered through the social welfare schemes or disability benefit programs, or are being capped for the cost, volume, or amount, leading to additional out-of-pocket cost for those living with a disability (Mitra et al., 2017).

Lack of or inadequate family or social support

With respect to social support, evidence suggests that being married or living with a partner and having family support significantly increase adherence, whereas homelessness or loneliness decreases adherence to necessary medications (DiMatteo, 2004; Kardas, Lewek, & Matyjaszczyk, 2013). However, a substantial proportion of people having disabilities live alone, are homeless, have small social networks, or limited to no support from the family (Guilcher, Casciaro, et al., 2012; Morris, 2001; Nishio et al., 2017). Their social support diminishes over time, which often leads to depression, isolation, and poor health and well-being and makes them further vulnerable to CRNA (Beer et al., 2012; Mitra et al., 2017; Samuel, Alkire, Zavaleta, Mills, & Hammock, 2018).

Impact of age on disability

Several studies suggest that there are interrelationships between disability and frailty, which creates vulnerability toward adverse health outcomes, dependency, falls, need for complex care, and mortality (Boeckxstaens et al., 2015; Curcio, Henao, & Gomez, 2014; Fried et al., 2004; Kojima, 2017; Wong et al., 2010). The process of aging for people with disabilities begins earlier than usual, with the effects of aging getting superimposed on the effects of a disability (WHO, 2018). In addition, people with disabilities are often being prematurely removed or retired from the workforce while older persons in general population remain employed (Turcotte, 2014). A recent study reports that elderly people (>65 years of age) with disability experience higher out-of-pocket expenditures compared with other age groups (Mitra et al., 2017). Therefore, as the severity of disability or age of the person increases, health, income, and employment outcomes deteriorate (Hitzig, Campbell, McGillivray, Boschen, & Craven, 2010). This implies that although the need for medicines may increase with time, the financial capacity of people with disabilities declines, thereby posing them at a greater risk of CRNA.

B. Drug or Treatment Characteristics

Another important determinant of CRNA highlighted in the Piette model is the type of medications and diseases for which medications are being taken. Authors indicated that patients value those medications that treat life-threatening conditions or prevent future adverse events (essential medications). People are more likely to forgo symptomatic medications given for temporary relief or for less serious health problems (nonessential medications). Complexity of treatment regimen and propensity of side effects or adverse effects also affect people’s responses toward medication cost and adherence. Although all these factors will apply to the context of people with disabilities, there are additional medication-related factors that may have a varied influence on CRNA and therefore need to be considered differently.

Complex and long-term medical regimens

People with disabilities are often heavy users of prescription medications (Rouleau & Guertin, 2011). Specific to the nature or type of disability, many people with disabilities have long-term medication needs (Patel, Milligan, & Lee, 2017). In addition, people with disabilities are often at a higher risk of being prescribed complex regimens of medications (e.g., analgesics, narcotics, anticonvulsant, antidepressant), as well as multiple medications within each class (e.g., multiple analgesic-narcotics; Kitzman, Cecil, & Kolpek, 2017). The long-term use of complex medical regimens can either directly affect cost and adherence or indirectly lead to side effects which can limit one’s ability to return to work and gain financial flexibility to afford medications (Mohammed, Moles, & Chen, 2016; Sav et al., 2013; Wilson, Kataria, & McNeilly, 2013).

Need for over-the-counter substitutes and other health supplements

People with disabilities may need to use a wide range of health products apart from the prescription medications such as alternative therapies (e.g., naturopathy, Ayurveda, homeopathy) or other over-the-counter medications such as minerals, vitamins, amino acids, fish oil, or herbal products (Brichetto et al., 2003; Doan, Lennox, Taylor-Gomez, & Ware, 2013). These may have additional costs and therefore affect their decisions or behaviors related to the use of prescription medication. Therefore, there exists an intricate relationship between various health- and medication-related characteristics, beyond being essential or nonessential, that may either decrease or increase CRNA in people with disabilities.

C. Clinician Characteristics

Piette and colleagues highlighted various clinician-related factors that may have an influence on patients’ cost-related barriers to medications, and hence their adherence. For example, very often physicians have limited time to discuss or have little knowledge about the cost of the medications that can lead to nonadherence. On the contrary, patients might themselves be hesitant to discuss their economic insufficiency to access their prescriptions or are not able to build trust to have a clear communication with their physicians. The authors suggested that if clinicians are made aware, solutions could be developed to relieve patient’s cost pressures to medications (Piette et al., 2006). While all these elements are significant to the context of people with disabilities, there exists an additional barrier which people with disability face—that is having access to a primary care provider. One of the common factors highlighted by various studies associated with CRNA is having an access to a primary care physician or a regular health care provider and relationship between doctor and patients (Allin, Stabile, & Tuohy, 2010; Hunter et al., 2015; Kennedy & Morgan, 2006; Tamblyn, Eguale, Huang, Winslade, & Doran, 2014; Wang, Lia, Sweetmanb, & Hurleyb, 2015).

Access to a health care provider

Literature suggests that people with disabilities face various physical, attitudinal, and policy-related barriers to access services of their primary health care providers (Donnelly et al., 2007; Manns & May, 2007; McColl & Jongbloed, 2006; Stillman, Frost, Smalley, Bertocci, & Williams, 2014). Doctors may not have accessible clinics due to which people with disabilities are likely to miss their regular visits for health care or may require assistance to attend their appointments (Popplewell, Rechel, & Abel, 2014). Doctors often refuse to enroll patients with disability on their caseloads or roster as they do not have any financial incentives for extra efforts in terms of time or service demands (McColl et al., 2008). For example, with people having cognitive or auditory disabilities, history-taking and other procedures might take longer. This may not leave any time to discuss about prescription costs (McColl & Jongbloed, 2006). Doctors may not be aware of the financial situation of their patients, and the disability itself may limit the discussion of complex nuances. For a person having a disability, family physician acts as a channel to many disability-related benefits, including that for prescription drug coverage. However, none of these administrative visits are covered by the government and must be paid for out-of-pocket (McColl & Jongbloed, 2006). Therefore, all these barriers can influence whether persons with disabilities visit a doctor, which in turn may affect their decisions regarding medication-related cost pressures and adherence.

Patient–provider relationship and communication

Multiple studies suggest that health care provider–patient relationship, concordance, and communication, such as doctor’s ability to provide appropriate information on drug administration, offering enough time to the patient, and doctor’s ability to demonstrate empathy and elicit or respect patient’s concerns, have a great impact on patient’s decision to take or stop taking their medications (Kardas et al., 2013; Stavropoulou, 2011). However, evidence is emerging that these information and communication needs of people with disabilities remain particularly unmet (McColl, Aiken, McColl, Sakakibara, & Smith, 2012; McColl et al., 2008). People with disabilities often need to consult multiple health care providers and medication prescribers, face poor coordination among providers, and have limited duration of visits with physicians and specialists, which further limit the discussion on difficulties with insurance or finances and result in inadequate information provision (De Vries McClintock et al., 2016). Primary care providers themselves acknowledge that they lack disability-specific knowledge, which limit their ability to explain things to their clients with disabilities and propensity of developing therapeutic relationship with them (Kroll, Beatty, & Bingham, 2003; McColl et al., 2008). These elements leading to poor patient–provider relationship or communication may put people with disabilities at an increased risk of engaging in medication nonadherence.

D. Health System Characteristics

In the Piette model, health system characteristics have been identified as having a significant influence on patient’s extent of burden and responses to medication-related costs. The authors mentioned that determinants such as being insured or uninsured for prescription drug benefits or being treated in public or private systems could influence patient’s responses to medication cost burdens. They also highlighted the long wait times or cumbersome application process to access assistance programs affecting medication adherence negatively.

Complexity of health and social care

While all this is true for people with disabilities, the barriers related to health care programs or policies faced by people with disabilities are much more complex, dynamic, and heterogeneous (Guilcher, Munce, et al., 2017). In addition to policies related to health care, other policies or programs that are related to income security or housing also influence people with disabilities in accessing resources to afford therapies to maintain their health (Williamson et al., 2006). Moreover, these social assistance policies vary across countries or even in jurisdictions within countries or ministries (McColl, Jaiswal, & Roberts, 2017). For example, in Canada, depending on the eligibility criteria, the extent of prescription drug coverage varies extensively across provinces. Consequently, prescription drug costs vary for individuals having same prescription needs (Demers et al., 2008; Kratzer, Chang, Allin, & Law, 2015).

Even when people with disabilities are eligible to be covered by public insurance, they have to share the costs of medications in the form of copayments and deductibles that may lead to negative consequences on medication use (Alan, Crossley, Grootendorst, & Veall, 2002). Also, sometimes the more expensive or new drugs or drugs required to treat uncommon conditions are not available on the public drug formulary despite the potential clinical benefits for people with disabilities (Guilcher, Munce, et al., 2017). Consequently, the complexity and variability in policies need to be analyzed for their impact on medicine-related financial pressures for people with disabilities.

In summary, the model developed by Piette and colleagues (2006) has done the important groundwork by laying the foundation for the most common factors that could increase the risk of cost-related medication nonadherence in chronically ill patients. However, we would need to advance this knowledge and adapt the model with respect to the complex and heterogeneous barriers faced by people with disabilities while accessing their medications.

An Adapted Framework

To present specific conceptualization of CRNA with respect to people with disabilities, we propose an adapted model and name it CRNA-d (cost-related nonadherence to medications for persons with disability). This adapted model depicts that CRNA to prescription medications with respect to disability is a dynamic and multifaceted phenomenon, determined by various demographic (including socioeconomic), disability-related, medication-related, prescriber-related, and system-related factors (Figure 2). This proposed model is framed by taking the additional barriers faced by people with disabilities into consideration, which poses them at a greater risk of experiencing financial barriers to fulfill their prescription medication needs. These factors are listed below:

Demographic or socioeconomic factors: age; marital status or availability of social support; employment status (unemployed, underemployed, employed); income; and access to nonemployment-related resources (pensions, loans, or disability benefits). All these factors can compound the impact of disability on CRNA to medications.

Disability-related factors: nature or type of disability (temporary or long term; static or progressive; physical, mental, intellectual, or sensory); severity of disability; presence of any comorbidities (psychological issues or cognitive, physical impairment); and additional health care costs (attendant care, home modifications, adaptive equipment).

Medication-related factors: type of medications (prescriptions, over-the-counter, natural health products, alternative therapies); conditions for which medications are taken; frequency of taking medications; out-of-pocket costs on medications; availability and type of drug insurance; and cost-sharing mechanisms (premiums, copayments, deductibles).

Prescriber-related factors: access to physician services; relationship with doctor and communication regarding medication cost; coordination of care; accessibility to clinics (accessible parking, or transportation); and prescriber knowledge of disability and disability-specific services.

System-related factors: availability and access to drug benefit programs; public drug formulary; availability and access to other social or health care services; and funding and resources for alternative therapies or equipment.

Figure 2.

An adapted model: cost-related nonadherence with respect to disability (CRNA-d).

In the pictorial representation of the adapted model, solid lines highlight predominant factors (socioeconomic and medication-related factors) that affect CRNA among people with disabilities directly; dotted lines with arrows indicate the factors that moderate the effect of predominant factors (demographic and disability-related factors) or indirectly affect CRNA among people with disabilities (prescriber-related and system-related factors); and dotted lines without arrows indicate the interaction among these factors. Also note that while some of the factors are concurrent with the previous model developed by Piette and colleagues, there are many other factors that are added to the model to depict more specific conceptualization of CRNA with respect to disability. We believe that a systematic investigation with further research would be required to find and quantify the potential impact of most relevant factors (especially disability-related factors) that determine cost–adherence relationship for people with disabilities.

Implications for Policy

Growing evidence on the barriers faced by many people living in both developed and developing countries to access and afford necessary medications has given a strong push to the international debate (Agyemang & van den Born, 2018; Ahmadiani & Nikfar, 2016). Over the last few decades, many health care groups, advocacy associations, and health policy researchers have called for national policies that can provide improved access to medicines for all (Gupta, 2016; Persaud & Ahmad, 2017). There have been efforts by the international organizations such as World Trade Organization as well as governments across the world to manage the issues related to drug shortages, manufacturing quality, marketing and price regulation, supply chain management, procurement processes, patenting, generic drug availability, and essential list of medications (Bigdeli, Peters, & Wagner, 2014; WHO & United Nations Development Programme, 2003). However, inquiry on extent, determinants, and consequences of cost-related barriers to medications, especially among socially disadvantaged groups such as people with disabilities, has been inadequate (Gupta et al., 2018).

Differences between the barriers faced by those with and without disabilities perpetuate the inequities in the availability of and access to prescription drugs (Guilcher, Munce, et al., 2017). The proposed model (CRNA-d) is framed by taking additional barriers faced by people with disabilities into consideration, which poses them at a greater risk of experiencing financial barriers to fulfill their prescription medication needs. Therefore, this study will be crucial and timely to this context and contribute to the limited understanding on the medication cost pressures among people with disabilities to inform policy makers whether a national drug coverage or targeted policy efforts are required to ensure burden-free access to medications for all. We believe that a systematic investigation with further research is warranted to find the most relevant variables that predict CRNA in people with disabilities and its relationship with specific types of disabilities.

Conclusion

Despite emerging evidence on CRNA to prescription medications among people with chronic conditions, there is little conceptualization or exploration of the phenomenon of CRNA with respect to disability. In this article, we tried to adapt the already existing framework developed by Piette and colleagues in 2006 that aimed to understand the factors associated with CRNA among chronically ill patients. Although most of the factors highlighted in their model may apply to people with disabilities, there exists an array of additional barriers that people with disabilities face while accessing their necessary medications. Several of these include higher susceptibility to health complications or comorbidities, barriers to income and employment, additional health care needs, other health care costs, barriers to access physician services, and other policy-related barriers. Therefore, the adapted CRNA-d model highlights the core elements and different dimensions that should be considered while examining the phenomenon of CRNA among people with disabilities. However, this model will need to be tested through research for the development of more specific and nuanced conceptualization of CRNA with respect to disability, and therefore formulating strategies to reduce the extent and impact of CRNA among people with disabilities.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was conducted as part of the doctoral thesis work of Shikha Gupta. Her work is supported through the doctoral studentship awarded by Queen’s University. Sara Guilcher is supported by the Canadian Institutes for Health Research Embedded Clinician Scientist Salary Award on Transitions in Care.

ORCID iD

Shikha Gupta

References

Agyemang

van den Born

B. J.

(2018). Limited access to CVD medicines in low-income and middle-income countries: Poverty is at the heart of the matter. The Lancet Global Health, 6(3), e234–e235. doi:10.1016/S2214-109X(18)30048-2

Ahmadiani

Nikfar

(2016). Challenges of access to medicine and the responsibility of pharmaceutical companies: A legal perspective. DARU, Journal of Pharmaceutical Sciences, 24(1), 1–7. doi:10.1186/s40199-016-0151-z

Alan

Crossley

T. F.

Grootendorst

Veall

M. R.

(2002). The effects of drug subsidies on out-of-pocket prescription drug expenditures by seniors: Regional evidence from Canada. Journal of Health Economics, 21, 805–826. doi:10.1016/S0167-6296(02)00012-7

Allin

Stabile

Tuohy

C. H.

(2010). Financing models for non-Canada health act services in Canada : Lessons from local and international experiences with social insurance. Ottawa, Ontario: Canadian Health Services Research Foundation.

Banks

L. M.

Kuper

Polack

(2017). Poverty and disability in low- and middle-income countries: A systematic review. PLoS ONE, 12(12), e0189996. doi:10.1371/journal.pone.0189996

Beer

Baker

Mallett

Batterham

Pate

Lester

Mission

M. C.

(2012). Addressing homelessness amongst persons with a disability: Identifying and enacting best practice. Canberra, Australia: Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA).

Bigdeli

Jacobs

Tomson

Laing

Ghaffar

Dujardin

(2013). Access to medicines from a health system perspective. Health Policy and Planning, 28, 692–704. doi:10.1093/heapol/czs108

Bigdeli

Peters

D. H.

Wagner

A. K.

(2014). Medicines in health systems. Geneva, Switzerland: The World Health Organization.

Boeckxstaens

Vaes

Legrand

Dalleur

De Sutter

Degryse

J. M.

(2015). The relationship of multimorbidity with disability and frailty in the oldest patients: A cross-sectional analysis of three measures of multimorbidity in the BELFRAIL cohort. European Journal of General Practice, 21, 39–44. doi:10.3109/13814788.2014.914167

10.

Brichetto

Uccelli

M. M.

Mancardi

Solaro

Brichetto

(2003). Symptomatic medication use in multiple sclerosis. Multiple Sclerosis, 9, 458–460.

11.

Curcio

C.-L.

Henao

G.-M.

Gomez

(2014). Frailty among rural elderly adults. BMC Geriatrics, 14(1), Article 2. doi:10.1186/1471-2318-14-2

12.

Cutler

R. L.

Fernandez-Llimos

Frommer

Benrimoj

Garcia-Cardenas

(2018). Economic impact of medication non-adherence by disease groups: A systematic review. BMJ Open, 8(1), Article 13. doi:10.1136/bmjopen-2017-016982

13.

Demers

Melo

Jackevicius

Cox

Kalavrouziotis

Rinfret

… Pilote

(2008). Comparison of provincial prescription drug plans and the impact on patients’ annual drug expenditures. Canadian Medical Association Journal, 178(4), 405-409. doi: 10.1503/cmaj.070587

14.

Després

Forget

Kettani

F.-Z.

Blais

(2016). Impact of patient reimbursement timing and out-of-pocket expenses on medication adherence in patients covered by private drug insurance plans. Journal of Managed Care & Specialty Pharmacy, 22, 539–547. doi:10.18553/jmcp.2016.22.5.539

15.

De Vera

M. A.

Mailman

Galo

J. S.

(2014). Economics of non-adherence to biologic therapies in rheumatoid arthritis. Current Rheumatology Reports, 16(11), 460. doi:10.1007/s11926-014-0460-5

16.

De Vries McClintock

H. F.

Barg

F. K.

Katz

S. P.

Stineman

M. G.

Krueger

Colletti

P. M.

. . . Bogner

H. R.

(2016). Health care experiences and perceptions among people with and without disabilities. Disability and Health Journal, 9, 74–82. doi:10.1016/j.dhjo.2015.08.007

17.

DiMatteo

M. R.

(2004). Social support and patient adherence to medical treatment: A meta-analysis. Health Psychology, 23, 207–218. doi:10.1037/0278-6133.23.2.207

18.

Doan

T. N.

Lennox

N. G.

Taylor-Gomez

Ware

R. S.

(2013). Medication use among Australian adults with intellectual disability in primary healthcare settings: A cross-sectional study. Journal of Intellectual & Developmental Disability, 38, 177–181. doi:10.3109/13668250.2013.778968

19.

Donnelly

McColl

M. A.

Charlifue

Glass

O’Brien

Savic

Smith

(2007). Utilization, access and satisfaction with primary care among people with spinal cord injuries: A comparison of three countries. Spinal Cord, 45, 25–36. doi:10.1038/sj.sc.3101933

20.

Fried

L. P.

Ferrucci

Darer

Williamson

J. D.

Anderson

(2004). Untangling the concepts of disability, frailty, and comorbidity: Implications for improved targeting and care. The Journals of Gerontology, 59, M255–M263. doi:10.1093/gerona/59.3.M255

21.

Goldsmith

L. J.

Kolhatkar

Popowich

Holbrook

A. M.

Morgan

S. G.

Law

M. R.

(2017). Understanding the patient experience of cost-related non-adherence to prescription medications through typology development and application. Social Science and Medicine, 194, 51–59. doi:10.1016/j.socscimed.2017.10.007

22.

Gudlavalleti

M. V.

John

Allagh

Sagar

Kamalakannan

Ramachandra

S. S.

(2014). Access to health care and employment status of people with disabilities in South India, the SIDE (South India disability evidence) study. BMC Public Health, 14, Article 1125. doi:10.1186/1471-2458-14-1125

23.

Guilcher

S. J. T.

Casciaro

Lemieux-Charles

Craven

McColl

M. A.

Jaglal

S. B.

(2012). Social networks and secondary health conditions: The critical secondary team for individuals with spinal cord injury. The Journal of Spinal Cord Medicine, 35, 330–342. doi:10.1179/2045772312Y.0000000035

24.

Guilcher

S. J. T.

Munce

Conklin

Packer

Verrier

Marras

. . . Jaglal

(2017). The financial burden of prescription drugs for neurological conditions in Canada: Results from the National Population Health Study of Neurological Conditions. Health Policy, 121, 389–396. doi:10.1016/j.healthpol.2017.01.010

25.

Gupta

(2016). Impact of global policy reforms on equity in access to medicines in India. BMJ Global Health, 1(Suppl. 1), A2–A43.

26.

Gupta

Mccoll

M. A.

Guilcher

S. J.

Smith

(2018). Cost-related nonadherence to prescription medications in Canada: A scoping review. Patient Preference and Adherence, 12, 1699–1715. doi:10.2147/PPA.S170417

27.

Hitzig

S. L.

Campbell

K. A.

McGillivray

C. F.

Boschen

K. A.

Craven

B. C.

(2010). Understanding age effects associated with changes in secondary health conditions in a Canadian spinal cord injury cohort. Spinal Cord, 48, 330–335. doi:10.1038/sc.2009.135

28.

Horner-Johnson

Dobbertin

Lee

J. C.

Andresen

E. M.

, & Expert Panel on Disability Health Disparities. (2014). Disparities in health care access and receipt of preventive services by disability type: Analysis of the medical expenditure panel survey. Health Services Research, 49, 1980–1999. doi:10.1111/1475-6773.12195

29.

Hunter

C. E.

Palepu

Farrell

Gogosis

O’Brien

Hwang

S. W.

(2015). Barriers to prescription medication adherence among homeless and vulnerably housed adults in three Canadian cities. Journal of Primary Care & Community Health, 6, 154–161. doi:10.1177/2150131914560610

30.

Jensen

E. K.

Biering-Sørensen

(2014). Medication before and after a spinal cord lesion. Spinal Cord, 52, 358–363. doi:10.1038/sc.2014.20

31.

Kapur

Basu

(2005). Drug coverage in Canada : Who is at risk ? Health Policy, 71, 181–193. doi:10.1016/j.healthpol.2004.08.006

32.

Kardas

Lewek

Matyjaszczyk

(2013). Determinants of patient adherence: A review of systematic reviews. Frontiers in Pharmacology, 4, 91–91. Advance online publication. doi:10.3389/fphar.2013.00091

33.

Kemp

Roughead

Preen

Glover

Semmens

(2010). Determinants of self-reported medicine underuse due to cost: A comparison of seven countries. Journal of Health Services Research & Policy, 15, 106–114. doi:10.1258/jhsrp.2009.009059

34.

Kennedy

Erb

(2002). Prescription noncompliance due to cost among adults with disabilities in the United States. American Journal of Public Health, 92, 1120–1124. doi:10.2105/AJPH.92.7.1120

35.

Kennedy

Morgan

(2006). A cross-national study of prescription nonadherence due to cost: Data from the joint Canada-United States survey of health. Clinical Therapeutics, 28, 1217–1224. doi:10.1016/j.clinthera.2006.07.009

36.

Kennedy

Morgan

(2009). Cost-related prescription nonadherence in the united states and Canada: A system-level comparison using the 2007 international health policy survey in seven countries. Clinical Therapeutics, 31, 213–219. doi:10.1016/j.clinthera.2009.01.006

37.

Kitzman

Cecil

Kolpek

J. H.

(2017). The risks of polypharmacy following spinal cord injury. The Journal of Spinal Cord Medicine, 40, 147–153. doi:10.1179/2045772314Y.0000000235

38.

Kojima

(2017). Frailty as a predictor of disabilities among community-dwelling older people: A systematic review and meta-analysis. Disability and Rehabilitation, 39, 1897–1908. doi:10.1080/09638288.2016.1212282

39.

Kratzer

Chang

Allin

Law

M. R.

(2015). The Impact of Private Insurance Coverage on Prescription drug use in Ontario, Canada. Healthcare Policy, 10(4), 62–74. doi:10.12927/hcpol.2015.24212

40.

Kroll

Beatty

P. W.

Bingham

(2003). Primary care satisfaction among adults with physical disabilities: Role of patient-provider communication. Managed Care Quarterly, 11, 11–19.

41.

Krueger

Noonan

V. K.

Trenaman

L. M.

Joshi

Rivers

C. S.

(2013). The economic burden of traumatic spinal cord injury in Canada. Chronic Diseases and Injuries in Canada, 33, 113–122.

42.

Maart

Jelsma

(2014). Disability and access to health care-a community based descriptive study. Disability and Rehabilitation, 36, 1489–1493. doi:10.3109/09638288.2013.807883

43.

Manns

P. J.

May

L. A.

(2007). Perceptions of issues associated with the maintenance and improvement of long-term health in people with SCI. Spinal Cord, 45, 411–419. doi:10.1038/sj.sc.3101973

44.

Maxwell

J. A.

(2011). Conceptual framework: What do you think is going on? Qualitative research design: An interactive approach. London, England: SAGE.

45.

McColl

M. A.

(2005). Disability studies at the population level: Issues of health service utilization. American Journal of Occupational Therapy, 59, 516–526.

46.

McColl

M. A.

Aiken

McColl

Sakakibara

Smith

(2012). Primary care of people with spinal cord injury: Scoping review. Canadian Family Physician, 58(11), 1207–1216, e626–e635. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23152456

47.

McColl

M. A.

Forster

Shortt

S. E. D.

Hunter

Dorland

Godwin

Rosser

(2008). Physician experiences providing primary care to people with disabilities. Healthcare Policy/Politiques De Santé, 4, e129–e147.

48.

McColl

M. A.

Jaiswal

Roberts

(2017). A review of disability policy in Canada. Ottawa, Ontario: Canadian Disability Policy Alliance.

49.

McColl

M. A.

Jarzynowska

Shortt

S. E. D.

(2010). Unmet health care needs of people with disabilities: Population level evidence. Disability & Society, 25, 205–218. doi:10.1080/09687590903537406

50.

McColl

M. A.

Jongbloed

(2006). Disability and social policy in Canada. Concord, Ont: Captus Press.

51.

McLeod

Bereza

B. G.

Shim

Grootendorst

(2011). Financial burden of household out-of-pocket expenditures for prescription drugs: Cross-sectional analysis based on national survey data. Open Medicine, 5(1), e1–e9.

52.

Mitra

Findley

P. A.

Sambamoorthi

(2009). Health care expenditures of living with a disability: Total expenditures, out-of-pocket expenses, and burden, 1996 to 2004. Archives of Physical Medicine and Rehabilitation, 90, 1532–1540. doi:10.1016/j.apmr.2009.02.020

53.

Mitra

Palmer

Kim

Mont

Groce

(2017). Extra costs of living with a disability: A review and agenda for research. Disability and Health Journal, 10, 475–484. doi:10.1016/j.dhjo.2017.04.007

54.

Mitra

Posarac

Vick

(2013). Disability and poverty in developing countries: A multidimensional study. World Development, 41(1), 1–18. doi:10.1016/j.worlddev.2012.05.024

55.

Mohammed

M. A.

Moles

R. J.

Chen

T. F.

(2016). Medication-related burden and patients’ lived experience with medicine: A systematic review and metasynthesis of qualitative studies. BMJ Open, 6(2), Article e010035. doi:10.1136/bmjopen-2015-010035

56.

Morris

(2001). Social exclusion and young disabled people with high levels of support needs. Critical Social Policy, 21, 161–183. doi:10.1177/026101830102100202

57.

Naci

Soumerai

S. B.

Ross-Degnan

Zhang

Briesacher

B. A.

Gurwitz

J. H.

Madden

J. M.

(2014). Persistent medication affordability problems among disabled Medicare beneficiaries after Part D, 2006-2011. Medical Care, 52, 951–956. doi:10.1097/MLR.0000000000000205

58.

Nishio

Horita

Sado

Mizutani

Watanabe

Uehara

Yamamoto

(2017). Causes of homelessness prevalence: Relationship between homelessness and disability. Psychiatry and Clinical Neurosciences, 71, 180–188. doi:10.1111/pcn.12469

59.

Patel

Milligan

Lee

(2017). Medication-related problems in individuals with spinal cord injury in a primary care-based clinic. The Journal of Spinal Cord Medicine, 40, 54–61. doi:10.1179/2045772315Y.0000000055

60.

Persaud

Ahmad

(2017). Canadian list of essential medications potential and uncertainties. Canadian Family Physician, 63, 266–268.

61.

Piette

J. D.

(2009). Cost-related medication underuse: A window into patients’ medication-related concerns. Diabetes Spectrum, 22, 77–80. doi:10.2337/diaspect.22.2.77

62.

Piette

J. D.

Beard

Rosland

A. M.

McHorney

C. A.

(2011). Beliefs that influence cost-related medication non-adherence among the “haves” and “have nots” with chronic diseases. Patient Preference and Adherence, 5, 389–396. doi:10.2147/PPA.S23111

63.

Piette

J. D.

Heisler

Horne

Caleb Alexander

(2006). A conceptually based approach to understanding chronically ill patients’ responses to medication cost pressures. Social Science and Medicine, 62, 846–857. doi:10.1016/j.socscimed.2005.06.045

64.

Pinilla-Roncancio

(2018). The reality of disability: Multidimensional poverty of people with disability and their families in Latin America. Disability and Health Journal, 11, 398–404. doi:10.1016/j.dhjo.2017.12.007

65.

Popplewell

N. T. A.

Rechel

B. P. D.

Abel

G. A.

(2014). How do adults with physical disability experience primary care ? A nationwide cross-sectional survey of access among patients in England. BMJ Open, 4(8), Article e004714. doi:10.1136/bmjopen-2013-004714

66.

Reichard

Stransky

Phillips

McClain

Drum Charles

J. D.

(2017). Prevalence and reasons for delaying and foregoing necessary care by the presence and type of disability among working-age adults. Disability and Health Journal, 10, 39–47. doi:10.1016/j.dhjo.2016.08.001

67.

Rouleau

Guertin

P. A.

(2011). Traumatic and nontraumatic spinal-cord-injured patients in Quebec, Canada. Part 3: Pharmacological characteristics. Spinal Cord, 49, 186–195. doi:10.1038/sc.2010.70

68.

Samuel

Alkire

Zavaleta

Mills

Hammock

(2018). Social isolation and its relationship to multidimensional poverty. Oxford Development Studies, 46, 83–97. doi:10.1080/13600818.2017.1311852

69.

Sanmartin

Hennessy

Law

M. R.

(2014). Trends in out-of-pocket health care expenditures in Canada, by household income, 1997 to 2009. Health Reports, 25(4), 13–17.

70.

Sav

Kendall

Mcmillan

S. S.

Kelly

Whitty

J. A.

King

M. A.

Wheeler

A. J.

(2013). “You say treatment, I say hard work”: Treatment burden among people with chronic illness and their carers in Australia. Health and Social Care in the Community, 21, 665–674. doi:10.1111/hsc.12052

71.

She

Livermore

G. A.

(2007). Material hardship, poverty, and disability among working-age adults. Social Science Quarterly, 88, 970–989. doi:10.1111/j.1540-6237.2007.00513.x

72.

Smith

D. L.

(2013). Disability, employment and stress regarding ability to pay for housing and healthy food. Work, 45, 449–463. doi:10.3233/WOR-121552

73.

Sommers

S. A.

(2006). Access to health insurance, barriers to care and service use among adults with disabilities. Inquiry, 43, 393–405. doi:10.5034/inquiryjrnl

74.

Soumerai

S. B.

Pierre-Jacques

Zhang

Ross-Degnan

Adams

A. S.

Gurwitz

. . . Safran

D. G.

(2006). Cost-related medication nonadherence among elderly and disabled Medicare beneficiaries: A national survey 1 year before the Medicare drug benefit. Archives of Internal Medicine, 166, 1829–1835. doi:10.1001/archinte.166.17.1829

75.

Stavropoulou

(2011). Non-adherence to medication and doctor-patient relationship: Evidence from a European survey. Patient Education and Counseling, 83, 7–13. doi:10.1016/j.pec.2010.04.039

76.

Stillman

M. D.

Frost

K. L.

Smalley

Bertocci

Williams

(2014). Health care utilization and barriers experienced by individuals with spinal cord injury. Archives of Physical Medicine and Rehabilitation, 95, 1114–1126. doi:10.1016/j.apmr.2014.02.005

77.

Tamblyn

Eguale

Huang

Winslade

Doran

(2014). The incidence and determinants of primary nonadherence with prescribed medication in primary care: A cohort study. Annals of Internal Medicine, 160, 441–450. doi:10.7326/M13-1705

78.

Turcotte

(2014). Insights on Canadian society: Persons with disabilities and employment. Ottawa, Ontario: Statistics Canada.

79.

Wagner

T. H.

Heisler

Piette

J. D.

(2008). Prescription drug co-payments and cost-related medication underuse. Health Economics, Policy, and Law, 3, 51–67.

80.

Wall

(2017). Low income among persons with a disability in Canada. Insights on Canadian Society. Retrieved from https://www150.statcan.gc.ca/n1/pub/75-006-x/2017001/article/54854-eng.pdf

81.

Wang

Lia

Sweetmanb

Hurleyb

(2015). Mandatory universal drug plan, access to health care and health: Evidence from Quebec, Canada. Journal of Health Economics, 44, 80–96. doi:10.1016/j.jhealeco.2015.08.004

82.

Wilson

P. M.

Kataria

McNeilly

(2013). Patient and carer experience of obtaining regular prescribed medication for chronic disease in the English National Health Service. BMC Health Services Research, 13, Article 192. doi:10.1186/1472-6963-13-192

83.

Williamson

D. L.

Stewart

M. J.

Hayward

Letourneau

Makwarimba

Masuda

. . . Wilson

(2006). Low-income Canadians’ experiences with health-related services: Implications for health care reform. Health Policy, 76(1), 106-121. doi:10.1016/j.healthpol.2005.05.005

84.

Wong

C. H.

Weiss

Sourial

Karunananthan

Quail

J. M.

Wolfson

Bergman

(2010). Frailty and its association with disability and comorbidity in a community-dwelling sample of seniors in Montreal: A cross-sectional study. Aging Clinical and Experimental Research, 22, 54–62. doi:10.3275/6675

85.

World Health Organization. (2003). Adherence to long-term therapies: Evidence for action. Geneva, Switzerland: Author.

86.

World Health Organization. (2004). The world medicines situation. Retrieved from https://www.who.int/medicines/areas/policy/world_medicines_situation/en/

87.

World Health Organization. (2018). Disability and health. Retrieved from https://www.who.int/news-room/fact-sheets/detail/disability-and-health

88.

World Health Organization and the World Bank. (2011). World report on disability. The Lancet, 377, 1977–2054.

89.

World Health Organization & United Nations Development Programme. (2003). Access to affordable essential medicines (Vol. 3). Retrieved from https://www.who.int/medicines/mdg/MDG08ChapterEMedsEn.pdf

90.

Zhang

J. X.

Lee

J. U.

Meltzer

D. O.

Zhang

J. X.

Lee

J. U.

Meltzer

D. O.

(2014). Risk factors for cost-related medication non-adherence among older patients with diabetes. World Journal of Diabetes, 5, 945–950. doi:10.4239/wjd.v5.i6.945