Ageism in the Health Care System: Providers, Patients, and Systems

13.2.1 Ageist Attitudes and Practices Among Health Care Professionals

There is an ample body of literature documenting negative attitudes towards older patients among health care providers, though conclusions are limited due to the use of a wide range of measurement approaches (for example, a number of different instruments have been used to assess “ageist” attitudes). Lookinland and Anson (1995) reported that registered nurses, as well as high school students interested in becoming nurses, exhibited negative attitudes and stereotypical beliefs related to ageing and older adults, with the latter exhibiting the least favorable attitudes and views. One study found that nurses tend to assign a lower status to geriatric nursing compared to other practice areas (Wells et al. 2004) and in another study, nursing trainees indicated a general lack of interest in working with older adults (Hayes et al. 2006). However, a recent survey study (Boswell 2012) among health care students in an undergraduate course on ageing found no clear tendency toward more negative or positive attitudes.

Several review articles have focused on attitudes toward older adults among health care providers. Attitudes among physicians are complex and mixed (Meisner 2012), with some studies of this population demonstrating clearly negative evaluations of older adults and others more neutral or positive evaluations. This also appears to be true of studies of attitudes toward ageing among nurses (Liu et al. 2013). There may be shifts in attitudes among health care professionals over time: results of a recent systematic review suggested an improvement in medical students and physician attitudes since 2000, but a decrease from positive to more neutral attitudes towards older people among nurses and nurse trainees (Liu et al. 2012). A review of studies examining nurses working in the acute health care setting revealed primarily positive attitudes toward ageing, though some studies reported negative attitudes, mainly reflecting a negative emotional evaluation of patients (Courtney et al. 2000). Most concerning, these authors found evidence in their review for an association between negative attitudes and clinical practice decisions.

Discrimination based on age may be reflected in clinical practice and decision-making among health care providers. Studies using both hypothetical decision-making scenarios and patient record review have demonstrated age-based disparities in diagnostic procedures as well as in the types of treatment offered to patients. These reports emerge from various fields of medicine including cardiology (Bowling 1999), oncology (Kagan 2008), and stroke treatment (Hadbavna and O’Neill 2013). For example, a study conducted in England revealed that though the prevalence of breast cancer is considerably higher among older women compared to younger women (40% of cases are over age 70), only 11% of these older women had received breast cancer screening examinations by their physician. Moreover, only 7% of the physicians participating in that study conducted breast examinations on older female patients on a routine basis (Haigney et al. 1997). A study conducted among physicians and second-year medical students indicated an age bias in beliefs regarding follow-up treatment for patients undergoing surgery for breast cancer (Madan et al. 2001, 2006). Younger patients described in vignettes were significantly more likely to be recommended for breast-conservation therapy, whereas a higher percentage of older patients were recommended for modified radical mastectomy. This study also found that younger patients were more likely to be recommended for breast reconstruction procedures following mastectomy. Among lung cancer patients in the U.K., the likelihood of being referred for surgery was lower for older people, despite clinical evidence that post-operative recovery outcomes are not dependent on age (Peake et al. 2003). The same trend has been found in cardiology: coronary heart disease in older patients, specifically older women, is more likely to be treated pharmacologically rather than surgically (Wenger 1997). A U.S. study found evidence of age-related under-treatment of heart attacks relative to national treatment guidelines, with older patients less likely to receive standard diagnostic procedures and recommended treatments (McLaughlin et al. 1996).

13.2.2 Ageist Communication by Health Care Professionals

Another aspect of age discrimination relates to the way health care providers communicate with older adults. A number of studies provide evidence that patronizing and ineffective communication can characterize discourse between providers and older patients (Ambady 2002). Overall, physicians involve older patients in medical decisions less frequently than they involve younger patients. Further, physicians tend to be less patient, less respectful, less involved, and less optimistic with older patients compared to younger patients (Greene et al. 1996). While there is certainly individual variability in patient preferences for the type of communication with a health care provider, there is no evidence that these attributes of interpersonal communication are preferred by older persons. Above and beyond the potentially negative emotional experience for older patients and family members in the face of a provider’s “poor bedside manner,” provider communication styles may have substantive negative health consequences for the patient (Nussbaum et al. 2005). For example, one research study analyzing videotaped encounters between a physical therapist and an older patient found that distancing and indifferent behaviors (e.g., not smiling; looking away from the client) were related to more negative short- and long-term cognitive and physical health outcomes for the patient (Ambady 2002).

In a study of nurses, the quality of communication with and care provided to older patients was found to be associated with attitudes toward ageing (Caris-Verhallen et al. 1999). More negative nurse attitudes were related to shorter, more superficial, and more task-oriented conversations with older patients. The nurses tended to speak to the older patients in a patronizing tone and did not involve them in consultations or decisions. In a similar vein, McLafferty and Morrison (2004) found that nurses’ negative attitudes towards older patients were reflected in low expectations for rehabilitation as well as in more detached treatment of the patients. In this study, nurses were less likely to use humor with their older patients, and were less likely to remember the names of older patients compared to younger patients. A recent qualitative study which compared physicians, nurses, and social workers in Israel found that exclusion of older patients from conversations about their own medical care characterized the interactional styles across disciplines. These health care professionals tended to either “bypass” the older patient by approaching younger family members, or to make clinical decisions without any meaningful patient input. In follow-up interviews, health care providers listed several primary reasons for this type of communication style: (1) lack of self-awareness of this pattern; (2) “choosing the way that is easiest” (i.e., it is simpler to have health care discussions with a younger family member rather than the older patient); and (3) the provider “not relating to the patient [as a person]” (Ben-Harush et al. 2016).

13.2.3 Factors Associated with Ageism in the Medical Setting

Past research on patient factors in ageism, which has been primarily conducted among mental health providers, spawned the term “healthism” to describe negative perceptions of others based on poor health status, not purely on age (Gekoski and Knox 1990; James and Haley 1995). Because poor health is strongly associated with old age and older adult identity (Coupland and Coupland 1994; Vauclair et al. 2015), the potential impact of “healthism” on the quality of patient-provider interactions and on care in the health care system is worthy of brief discussion. (Bodner et al. 2018, Chap.  15 provide additional details on this construct in their chapter on ageism in the mental health care setting, in this volume.)

Health care providers may develop attitudes toward older patients based on their medical diagnoses, functional deficits, or symptoms. A bias against older adults who are medically ill was demonstrated in a sample of mental health therapists (James and Haley 1995). Among medical providers, Gunderson and colleagues (Gunderson et al. 2005) found that rurally-based physicians in the U.S. endorsed more negative views of “nursing home patients” compared to typical “older” patients, in terms of patients’ ability to change health behaviors and to learn new health-related information, their ability to offer important input during a medical visit, and their personality traits (e.g., “less warm and accepting”). Healthism may be related to the increasing “medicalization” of old age in Western societies identified by some scholars (Ng et al. 2015). Increased focus on the medical aspects of being old – to the exclusion of other dimensions of older age – is reflected at the level of policy and reimbursement in the geriatric health care setting, and has a clear impact on provider choices, service availability, and quality of care (Binney et al. 1990). A recent sociological study of changes in culture-based age stereotypes appearing in print over the past 200 years in the USA found an increasing association over time between the mention of an older adult and references to the medical status of that person, using words such as “sickness” or “stamina” (Ng et al. 2015). This increasing medicalization of old age was associated with increasingly negative age stereotypes, leading the authors to conclude that this increasing negativity toward older adults is systemic and pervasive throughout the culture.

The construct of healthism may be related to self-ageism (see below). In an effort to distance themselves from stereotypical views of old age and their own aging experience, older adults may tend to deny health problems to order to more easily present as exemplifying “healthy ageing” (Tanner 2003).

13.2.4 Self-Ageism in the Health Care Setting

Ageist biases or assumptions held by older adults themselves (i.e. “self-ageism”) may also impact their interactions with the medical system and quality of health care. Among older adults, the development of negative attitudes toward ageing or older people can be considerable, and in fact may be inevitable in an ageist society (Levy 2001). These biases may lead to irrational illness perceptions, for example, that pain and suffering are to be expected in old age. One recent qualitative study on back pain – one of the most common medical conditions among older adults around the globe – found that many older patients believe that pain is a “normal” part of old age (Makris et al. 2015). They are less likely to seek treatment for unmet medical needs, due to low expectancies of being helped because of their advanced age (Walters et al. 2001). These self-directed biases can also impact health and healthcare outcomes for the geriatric patient. Over a series of studies, Levy and colleagues have demonstrated a relationship between negative age self-stereotypes and health outcomes (Hausdorff et al. 1999; Levy and Banaji 2002). For example, one longitudinal study found that the endorsement of negative statements about older adults (e.g., “old people are helpless”) was related to a higher risk for cardiovascular events over the next 38 years, controlling for cardiovascular risk factors (Levy et al. 2009). A more recent report revealed an association between negative age stereotypes held earlier in life and a later increased risk for Alzheimer’s brain pathology (Levy et al. 2016). Moreover, a meta-analysis of 19 longitudinal studies concluded that positive subjective ageing (defined as positive ageing attitudes and youthful identities) contributes to better health and increased longevity in later life (Westerhof et al. 2014). Potential explanations may include that self-ageist ideas or negative views on ageing make it less likely for older adults to embrace positive health behaviors such as physical activity (Wurm et al. 2010), take preventive health measures, or adhere to recommended treatments (Levy and Myers 2004).

In summary, there is evidence of age-based bias at the micro, or interpersonal, level. This is reflected in attitudes and behaviors toward older adults among health care workers, and research suggests that these attitudes affect clinician behavior and clinical decision making. Patient factors, such as self-ageism, also impact the processes and outcomes of health care. Thus far, data regarding specific provider or patient factors which may predict prejudice and discrimination based on age in the health care setting appear to be mixed. In the next section, we examine ageism at the macro-level within this setting.

13.3.1 Age Discrimination Exists in the Health Care System

Complaints of age bias in care, beyond the level of provider attitudes or provider-level behaviors, have been reported within a variety of health care systems (European Commission 2008; International Longevity Center 2006; Jacobsen 2015; Williams 2009). A recent European Union-commissioned study across several EU countries reported that the frail, medically complex older adults comprise one of the populations at risk of “falling through [the] safety net” of public health care coverage programmes, resulting in reduced access to quality health care (European Commission 2008). This study found evidence, across most nations examined, of less access to necessary medical care among older adults compared to younger adults. Multiple so-called “supply-side” or system-level barriers to health care access for older adults were identified. These included requirements for patient-borne cost sharing of services and medications, which can result in a deleterious interaction between older adults’ higher service needs and more limited financial resources; geographic barriers and lack of transportation options, resulting in limited access to care due to mobility restrictions; inadequate numbers of geriatrics-trained providers; a shortage of preventive and rehabilitation-focused care options for older patients; and age-discriminatory clinical decision making by providers. “Demand-side” or patient-level factors contributing to health disparities for older EU citizens include lower expectations of health care services, leading to minimal demand for change; more limited health literacy; and heightened challenges in managing their own care within a bureaucratic, fragmented service organization (European Commission 2008). As others have noted (Nies and Berman 2004), despite the fact that care coordination has long been identified as a quintessential pillar of quality geriatric care, current geriatric health care systems in the EU are generally not based on principles of collaborative partnership with social care systems and informal caregivers.

Access to care following a stroke, or cardiovascular accident (CVA), is one example that has been studied by researchers. In general, age-based bias in stroke treatment – referring to differences in care that are not justified by clinical evidence or best-practice guidelines – appears to be quite common, according to a recent systematic review (Luker et al. 2011). One study found a significant impact of age of the patient on the quality and type of immediate care for CVA in several UK countries, with older persons less likely to receive care consistent with current guidelines (Rudd et al. 2007). Another large pan-European study found that while older stroke patients have equal or better access to specialized stroke care, rates of standard diagnostic and therapeutic procedures, as well as rehabilitation services, were lower for older patients compared to their younger counterparts (Bhalla et al. 2004). These results are concerning in light of data that suggest that health outcomes after stroke do not vary by age when guideline-level care is provided (Saposnik et al. 2009). Of note, it is likely that the age-based differences identified in these studies represent the interaction of micro-level age-based attitudes (such as clinician decisions or patient preferences) and institutional or cultural norms in stroke care. However, clear instances of age-related bias in formal policy regarding stroke care can be found in a number of countries. For example, Greece has a policy governing decisions in inpatient stroke care, with patients over 65 sent for admission to a general internal medicine ward rather than a neurology specialty service (Theofanidis 2015). In Finland, a recently revamped policy does not provide coverage for medical rehabilitation – services to address deficits in activities of daily living following an illness – for persons over age 65 (AGE Platform Europe 2016), despite functional rehabilitation being part of standard care for many patients with stroke.

How health care services are reimbursed can differently affect older adults compared to younger patients. Health care reimbursement is a topic of great interest currently, as policy makers in many different countries work to address anticipated budget shortfalls due to ageing populations. As others have noted, current payment mechanisms incentivize medical procedures and technology-driven tests, but do not reimburse providers for the often complicated and time-consuming process of geriatric care (Alliance for Aging Research 2002). In addition, in many publicly-funded health care systems, there is an ongoing and heated debate about the rights of older persons to receive any health care benefits, and about how to manage the financial “burden” related to the care of older persons. Surveys within such countries reveal public opinion supporting the idea of an age cut-off for medical services; for example, in Belgium, persons over 85 years old are considered by many citizens as “not worthy of care” (AGE Platform Europe 2016). Within the UK’s National Health Service, discussions about rationing of care have frequently pointed to long-standing age-based discrimination at a systemic level (Shaw 1994). For example, until recently, the UK’s National Health Service breast cancer screening program offered regular mammography only to women under the age of 65 (the program has recently been extended up to age 70). A performance indicator in the United Kingdom sets the undesirable outcome “premature death” as occurring at or below age 75. Thus, this is a policy which does not differentiate patients based on comorbidities or clinical presentation, but on age alone. The policy also implies that human life after age 75 has less inherent worth compared to life at a younger age (AGE Platform Europe 2016). Vascular disease screening invitations in the UK are also age-based, despite the high prevalence of cardiovascular disease among older adults (Lievesley 2009). These are not isolated examples. Upper age limits on funding for diagnostic tests, screening procedures, and health-related social benefits are part of policy in many European countries (AGE Platform Europe 2016).

In the US, the existence of the federally funded and regulated Medicare health care insurance program for citizens over age 65 has resulted in a health care coverage system for older adults that is effectively separate from coverage programs for other age groups. Medicare policies on reimbursement for medications, equipment, and services have a profound and wide-reaching effect on health care for older adults in the US. One example is Medicare’s payment policy for inpatient rehabilitation, usually provided within a long-term care setting. Current Medicare benefits provide for a maximum of 100 days of reimbursement, creating an incentive for facilities to keep patients in the rehabilitation setting for this full time period, whether or not the patient is benefitting from the care or able to participate in rehabilitation treatments such as physical therapy. Medicare reimbursement policies are not structured to provide incentives to delay or prevent entry into a long-term care facility. There was no coverage for preventive care until recently, and preventive services that would benefit a majority of older adults (and reduce health care costs), such as a falls risk screening or home safety assessment, are still excluded. Medicare neither reimburses comprehensive outpatient geriatric care, despite evidence of good outcomes (Boult et al. 2001), nor the relatively low costs of part-time custodial care at home (e.g., assistance with cooking, cleaning, shopping, bathing) to keep frail patients safe and functioning outside of an institution. Of note, until recently, Medicare did not provide reimbursement for care costs incurred during participation in clinical research trials.

It should be noted that changes in the US public health care programs are gradually occurring as the Patient Protection and Affordable Care Act (ACA) of 2010 continues implementation, and there may be additional positive impacts on health care services for older adults (Goyal et al. 2012). The ACA includes a mandate for the expansion of the scope of routine care to include mental health care and chronic disease self-management, and places an emphasis on a patient-centered care experience and quality of life as measurable outcomes. Financial payment incentives are being realigned, especially for primary care providers who work in geriatrics, and there is increased attention to the development of care coordination and disease management programs for older adults to prevent unnecessary medical interventions and reduce costs. Thus, there may be reduction of age bias at the systemic level as we move toward the future.

13.3.2 Older Persons Participate Minimally in Clinical Trials

Another aspect of age bias at the structural level concerns clinical research trial participation. As Topinkova and colleagues note (Topinkova et al. 2012), “the health care industry and regulatory authorities have for a long time negated the age-specific needs of older drug consumers. Only recently the European Medicines Agency has begun recognizing the need for a specific ‘geriatric’ approach in both drug development and registration” (p. 479). Older patients are typically excluded from the development and testing of new compounds, from ongoing drug efficacy monitoring programs, and from undergoing age-appropriate outcome evaluations. In clinical drug trials for cancer and coronary artery disease, both conditions for which incidence increases with age, persons over the age of 65 are systematically underrepresented (Witham and McMurdo 2007). The same trend can be seen in research on intervention for strokes and on stroke rehabilitation: in both cases, there is global evidence of age bias, as the mean age of participants in clinical trials reported in the stroke literature was a decade younger than the average age of stroke patients (Gaynor et al. 2014; Hadbavna and O’Neill 2013).

A systematic review of recruitment of older cancer patients into clinical trials identified age-related barriers to equal inclusion in four broad domains: trial design, physician factors, patient factors, and trial logistics (Townsley et al. 2005). In the majority of clinical trials, protocol design stipulates exclusion criteria such as impaired functional status, past cancer illnesses, and medical comorbidities. This effectively screens out many older patients. Indeed, in a recent prospective study, not being eligible was the most common reason for lower enrollment of older persons (Javid et al. 2012). Further, a recent study of heart failure trials (Cherubini et al. 2011) found that almost 50% of the trials included what the authors termed “poorly justified” exclusionary criteria, resulting in lower participation by patients over 65 years old. At least one study has found similar age-based bias in non-pharmacological health behavior clinical research (Levy et al. 2006).

Physician-related barriers to referral of older adults to clinical trials include provider concerns about co-morbidities and potential adverse events related to study participation, factors which are evaluated in the context of patient age (Townsley et al. 2005). There is no evidence that provider characteristics impact referral rates. A U.S. study compared rates of physicians offering clinical trial participation to older versus younger breast cancer patients, and found no significant associations with physician demographic or professional experience variables. Patient age and stage of disease were the only significant predictors of referral (Kemeny et al. 2003). In terms of patient-level barriers, both older and younger patients most frequently explained their nonparticipation in trials by a reluctance to experience limitations on their choice of treatment. Some scholars, however, assert that older adults’ health literacy and knowledge about participation in clinical trials may be at a lower level compared to younger persons, preventing fully informed decision-making in these situations (Townsley et al. 2005).

Factors related to patient safety and scientific integrity, such as risk of adverse events and ensuring sample homogeneity, are often cited for this age-based exclusion. These are important concerns. However, the nonparticipation of older patients in clinical trials likely has a profound impact on health care for older adults. Lack of older adults’ participation prevents the generalization of study results to older patients and therefore may contribute to “double discrimination”: without clinical evidence supporting the use of novel treatments in the older population, the chance is reduced that older patients will receive these treatments. This may happen due to age-biased beliefs that continue unchallenged without newly emerging research on older populations, or due to clinicians’ uncertainty about safety and benefits for older patients and a resultant reluctance to pursue screening or treatment (Walter et al. 2005). Thus, age-based barriers to access to medical therapy might be partially attributed to the under-representation of the older age population in clinical trials. Further, the treatments that older adults receive should be based on solid clinical evidence relevant to that population, which is not currently the case (Cherubini et al. 2011). Indeed, it can be argued that underrepresentation of the older patient population in clinical trials is not only one of the consequences of ageism in medicine, but may also be one of its major perpetuating factors.

13.3.3 Training of Health Care Professionals

Another systemic factor which may sustain the age bias which exists within the health care system is the type of training received by health care professionals. Several scholars have argued that training programs do too little to actively combat existing negative views of older adults and to positively promote geriatrics or gerontology as practice fields. Some years ago, Levenson (1981) asserted that “medical students’ attitudes have reflected a prejudice against older persons surpassed only by their racial prejudice” (p. 161). More recent research has demonstrated that medical residents perceive themselves to have a gap in geriatric training and exposure to older patients (Chodosh et al. 1999), and that both US and European nursing students and nurses viewed the care of older people as a topic that currently receives too little attention in professional education programs (Kydd et al. 2014). Of note, however, a recent study of US medical schools reported improvements in the past decade in geriatric-specific physician training (Bragg et al. 2012). Thus, while inadequate training in geriatrics remains a problem to solve, it appears that institutions charged with health care education may be progressing in the right direction.