Geriatric Medical Decisions: Factors Influencing ...

Copyright 1988 by The Gerontological Society of America

The value of different models for predicting treatment decisions of physicians, nurses, and social workers within acute and long term care settings was examined. Treatment choices were elicited to two case vignettes regarding decisions to allocate a scarce medical resource and to withhold treatment from a debilitated patient. Predictors of decisions varied between the vignettes. Primarily medical factors predicted the decision to allocate scarce resources, whereas a combination of medical, societal, and situational factors predicted the decision to withhold treatment. Key Words: Quality of life, VA, ICU, Intubation, Geriatric care

Terrie Wetle, PhD,2 Julie Cwikel, PhD,3 and Sue E. Levkoff, ScD4

As a result of the growing elderly population and the rapid expansion of medical technology, health care professionals face a complex set of problems in medical decision-making in geriatric care. Among the more controversial issues are how to allocate scarce resources among patients of different ages and when to withhold treatment from severely debilitated patients. In this period of cost containment, budget constraints, and corporate decision-making, the context in which decisions are made is undergoing dramatic change. A variety of medical, social, and institutional factors, as well as characteristics specific to the patient and the health care provider may influence treatment decisions. Therefore, a multifactor approach may provide a more accurate approximation of how these decisions are made. Tested in this study were different models designed to explain clinical decision-making among physicians, nurses, and social workers within the VA medical system. The interplay among selected medical, social, and institutional factors in clinical decision-making have been examined in empirical studies (review by Adelson & Kraus, 1983). Little is known, however, about the influence of other factors which have been argued to be important in clinical decisions, such as characteristics of the provider and the setting in which care is given (Eisenberg, 1979). Although it is unclear how factors such as professional affiliation or age of the clinician directly affect decision-making, the importance of provider's age may be inferred

1 This research was conducted with partial support from the Department of Medicine and Surgery of the Veterans Administration. Assistant Professor of Medicine, Harvard Medical School, Associate Director, Division on Aging, Division of Health Policy, Research and Education, 641 Huntington Ave., Boston, MA 02115. 3 Lecturer, Department of Social Work, Ben Gurion University of the Negev and Researcher, Brookdale Institute of Gerontology and Adult Human Development, Jerusalem, Israel. "•Instructor, Department of Social Medicine and Health Policy & Division on Aging, Harvard Medical School.

from attitude surveys and research into medical decision-making (Adelson & Kraus, 1983; Greenfield et al., 1987; Wetle, 1987). In several studies of the attitudes of health care professionals toward euthanasia, for example, it was indicated that both older physicians and nurses were less likely than their younger colleagues to approve of such actions (Brown et al., 1970; Brown et al., 1971). It is difficult, however, to distinguish between age effect and the cohort effects of training and experience. Pearlman and colleagues (1982), for example, elicited from physicians their choice regarding intubation of an elderly, chronically ill patient using a hypothetical case vignette. The three groups of physicians (residents in internal medicine, attending physicians and private practitioners) differed in their support of intubation, with residents being least likely to support intubation. Residents differed from the other two groups not only in experience, but also were, on average, more than 10 years younger. In another study in which hypothetical case material was used, first- and third- year residents were found to differ in the likelihood of ordering cardiopulmonary rescusitation (CPR) (Farber et al., 1984). First year residents were least likely to order CPR, particularly when the patient was elderly or had a history of social isolation or drug abuse. In addition to these socio-demographic characteristics, attitudes of health care professionals may also influence decision-making. In reviews of attitude research the pervasiveness of negative attitudes and stereotypes concerning elderly patients among health care professionals has been documented (Bennett & Eckman, 1983; Lutsky, 1980), but in only a few studies has the way these attitudes influence clinical decisions been examined. Crane (1975) suggested that physicians rely not only on physiological aspects of illness in making clinical decisions, but also consider social and psychological factors such as a patient's capacity to resume former roles and inter336

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Geriatric Medical Decisions: Factors Influencing Allocation of Scarce Resources and the Decision to Withhold Treatment1

Vol. 28, No. 3,1988

preferences regarding interventions for all patients admitted to hospital during one month (Charlson et al., 1986). Admitting residents were asked to indicate their treatment choices, which ranged from full intervention, including intubation, to comfort measures only. The three primary factors predictive of intervention preferences were patient age (over 75 or not), medical residents' estimates of long term prognosis, and ability to function. The age of the patient has been shown to be a critical decision-making criterion when physicians consider the allocation of treatments or scarce medical resources. This was evident in studies in which hypothetical cases were used to examine physicians' selection of 1 of 3 possible treatments for thyroid disease (Moore et al., 1974) and of choices of patients suitable for hemodialysis (Taylor et al., 1975). It can be inferred from these two studies that physicians are less likely to choose these specialized treatments for older patients, although this was not specifically examined. Research concerning medical decision-making has shown that, in general, the medical model of clinical decision-making has predominated (Mechanic, 1976). The medical model posits that a patient's symptoms are evaluated independent of his or her social and personal characteristics. Some patient characteristics, such as age, however, have been found to be key elements in formulating a diagnostic picture (Moore et al., 1974; Taylor et al., 1975). On the other hand, when the decision concerns withholding treatment, research results have been equivocal as to whether age of the patient has a significant effect on the decision (Cady, 1984; Charlson et al., 1986). The importance of any specific type of decision-making determinant appears to be a function, in part, of the nature of the decision being made, as well as who is involved in the decision. In this research, the interest was in examining factors that influence important clinical decisions. Three decision-making models were examined as predictors of the outcomes of decisions in response to two case vignettes: one involving the allocation of scarce medical resources and the other regarding withholding treatment. Specific factors to be included in the models were identified through literature review and clinical observations. Model I consists of those factors for which the respondents provided a direct assessment of importance for each decision of interest. They included medical factors, patient characteristics, and institutional or societal constraints. Model II consists of those observed provider and setting characteristics that were constant across decisions. These characteristics included factors descriptive of the health care professional such as age, professional affiliation, preferred age group of patients, as well as the type of care offered at the respondent's primary facility. In Model III both the self-reported, decision-specific variables (Model I) and the provider and setting characteristics (Model II) are combined. This aims of this study were first to compare factors

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act with others. She found that patients under age 40 were most likely to be treated aggressively whereas those over 79 were the least likely to be given such treatment. The professional socialization of physicians, nurses, and social workers differs in many respects. There is little research, however, in which is documented how these divergent backgrounds affect clinical decision-making in care of elderly patients. Coe (1967) showed that conceptions of aging were likely to vary by health care profession. Physicians tended to stress the physiological aspects of aging, whereas nurses and social workers attached greater importance to the psycho-social factors associated with aging. The institutional environment, in which professionals care for geriatric patients, can be expected to influence treatment decisions through many pathways, including the organization of care, how health care is financed, the patient population, and the types of medical problems treated (e.g., Eisenberg, 1979; Mechanic, 1975). Labelling theory posits that medical judgments of health practitioners are affected by the institutional environment and by patients' social characteristics (Scheff, 1975). But investigations into the influence of situational characteristics on clinical decision-making in the care of elderly patients are relatively rare. Morgan (1985) found that setting characteristics, such as the size of the institution and the average age of residents of the institution, together with other medical and social characteristics of patients, influenced nurses' perceptions of mental disorientation in elderly patients. Although this study was restricted to nursing homes, the importance of setting characteristics in determining a central aspect of geriatric care was documented. The difficult decisions regarding withholding treatment in severely debilitated patients have been studied more extensively (e.g., The President's Commission for the Study of Ethical Problems in Medicine and Biomedical and Behavioral Research, 1983). In an overview of the bioethical considerations of withholding treatment, Oden (1976) proposed that the most important factors in the decision to forego lifesustaining treatment in debilitated adults should be cognitive function, life-expectancy, and expected quality of life following treatment. Patient and family preferences and the patient's degree of physical impairment and comfort were recommended as important factors, but to a lesser extent. In a study of nurses' choices in the decision to withhold treatment, Cady (1984) found that nurses indicated similar determinants as important in response to case vignettes, but also observed that institutional guidelines such as written documentation of DNR (do not resuscitate) orders, formal policies, and the potential for legal liability weighed in their decisions. With respect to foregoing life-sustaining treatment, age of the patient was regarded as relatively unimportant (Cady, 1984; Oden, 1976). These qualitative findings are in contrast to the empirical results of a prospective study of physicians'

important in two different types of difficult clinical choices: allocation of scarce medical resources and withholding treatment from a debilitated patient; second, to examine which factors within each model are associated with decision outcomes; and third, to test which model can be used to best explain decision outcomes. Methods

units, were chosen purposively on several criteria.

The VA acute care facilities were chosen because they are large medical centers with close contact with major medical schools. The VA combined acute and long term care facility was chosen because of the presence of the long term care program. The three sites were widely dispersed geographically. In the final stage of the multistage sampling framework, the secondary sampling units, the health care providers, were randomly selected for inclusion in the study from each facility's staff roster. Lists of all physicians, nurses, and social workers were obtained from each of the facilities. The total population of physicians from specific services which were known to provide the bulk of health care to geriatric patients, as well as all the social workers, were approached to participate in the study. A random sample of approximately two-thirds of the nurses was selected. To optimize response rate, copies of the survey instrument were mailed to the individuals selected to participate. Data were collected through pre-arranged telephone interviews. Of the 294 selected respondents, 251 successfully completed questionnaires, resulting in a response rate of 85.4%. The resulting sample included 96 physicians, 121 nurses, and 31 social workers, for a total of 248 respondents, because the three PhD psychologists were excluded from these analyses. The mean time to complete the telephone interviews was 18 minutes; most respondents had read through the instrument and determined responses before the scheduled interview. The research questionnaire was developed and pretested in a pilot study supported by Harvard University's Division of Health Policy Research and Education. A more detailed description of the instrument development process has been reported elsewhere (Wetle & Levkoff; 1984).

Table 1. Allocation of Scarce Resources Vignette A'

Choice 35 Year-old 75 Year-old Neither Missing data Total

%of Respondents

% of Those making a choice

122 52 54 20

53.5 22.8 23.7

70.1 29.9

248

100.0%

100.0%

N

a

Two patients have just been admitted to your hospital, a 75year-old man and a 35-year-old man. Both require treatment in the Intensive Care Unit (ICU). Both have clear cognitive function. Neither is married. The prognosis for each is equivalent. All other things being equal, if only one ICU bed were available, which patient would you recommend?

Table 2. The Decision to Withhold Treatment Vignette B* Response6 Do not support intubation Moderately support intubation Very strongly support intubation Missing data Total

N

%

182 27 35 4

74.6 11.1 14.3

248

100.0%

a

Study Design and Data Analysis Respondents were asked to make clinical judgments using two case vignettes. The method of using case vignettes is derived from social judgment theory which is an outgrowth of cognitive psychology. It

Mr. L. is an 85-year-old widower. He is disoriented, bedridden, and incontinent as a result of severe senile dementia. He develops acute respiratory failure associated with chronic obstructive pulmonary disease, which has taken a progressive and probably terminal course. How strongly would you support intubation and placement on a ventilator? "Collapsed from 5 response categories.

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Sample The sample of physicians, nurses, and social workers used in this study was selected from two Veterans Administration Medical Center (VAMC) acute care hospitals and a VA combined acute care and long term care facility, using a multistage, clustered sampling approach. The VAMCs, the primary sampling

allows the researcher to investigate and rank the factors influencing the clinical judgments of clinicians by describing how information is weighted and used in the decision process (Elstein et al., 1982). Typically, standardized vignettes are used which approximate actual clinical situations. The technique allows variables of interest to be controlled and thus is useful for analyzing the relative contribution of conflicting values in decision-making. In the first vignette (A) the allocation of scarce resources was examined by eliciting an intergenerational choice between a 35-year old man and a 75-year old man, both in need of treatment in an ICU unit. The patients were described as being similar on parameters of cognitive function, marital status, and prognosis. Respondents were asked which patient to recommend for the one remaining ICU bed. The second vignette (B) involved a decision to withhold treatment by describing an elderly patient whose health status is quite poor, both in cognitive and functional ability. He has acute respiratory failure with a very poor prognosis. Respondents were asked how strongly they would support intubation in this case. In addition, for each vignette respondents were asked to indicate the importance of factors thought to influence care decisions (factors found in Model I), including medical considerations, institutional and societal constraints, and patient characteristics. The appropriateness of the different decisionmaking models for explaining the variance in the

Results

Table 3. Description and Distribution of Independent Variables: Situation and Provider Characteristics

Independent variables Situational characteristic Type of care Provider characteristics Age of provider Preferred age of patients

Description

Distribution of respondents (n = 248)

acute care (n = 2) combined acute and chronic care (n = 1)

75% 25%

mean age in years

42.5

18-44 45-64 65 + no preference

22% 42% 18% 18%

physician nurse social worker

31% 58%

Professional affiliation

11%

Table 4. Mean Level of Importance of Decision Factors' (n = 248)

Respondents reacted differently to the vignettes Vignette B Vignette A presented, as shown in Tables 1 and 2. In the vignette allocation decision to regarding the allocation of scarce resources (Viof scarce withhold gnette A), a sizeable number refused to answer the Decision factors treatment resources question and of those who did answer, almost onequarter chose neither patient. When probed, non- Medical factors Medical risk to patient 3.87*** 4.45 respondents indicated that it was impossible to Expected quality of life choose or that a way would be found to treat both 4.25 following treatment 4.48** Degree of pain and suffering 4.19 4.44*** men. In allocating the ICU bed, 54% of respondents Cognitive functioning 6 3.58 3.54 chose the younger man, which represents 70% of Institutional and societal constraints those making a choice. A sizeable proportion, 30% of Informal and formal rule; respondents who made a choice and 23% of respon3.34* of institution1 3.24 3.14 3.33** dents overall, allocated the bed to the older man. In Potential for legal liability Patient factors responding to the vignette concerning the decision 4.34 4.27 Prior wishes of the patient to withhold treatment (Vignette B), 75% chose not to Age of the patient 3.37 3.23 intubate, whereas 25% were more inclined to supFamily considerations 3.61 3.95*** port intubation. It is evident that health care practiindependent Variables are scaled on a 5-point scale, 1 = least tioners were more comfortable in making the deciimportant, 5 = most important in response to question: In reachsion to withhold treatment than in making an ing your decision how important are the following to you? b intergenerational choice concerning the allocation lndex combined: 1) current cognitive function and 2) preof a scarce medical resource. existing dementia (alpha coefficient, Vignette A = .75; Vignette B = .82). The distribution of the independent variables repc lndex combined: 1) formal rules of the institution and 2) inforresenting provider characteristics (Model II) is mal practices of the institution (alpha coefficient, Vignette A = shown in Table 3. As was mentioned, the sample was .76; Vignette B = .80) drawn from three VA sites, two acute-care medical *p.O5 facilities and one combined acute and chronic care **p .01 site. As the two acute care sites did not differ signifi***p.001 cantly as predictors of the outcomes of the decisionmaking, they were combined to control for the effect of site-specific differences. The ages of the responcognitive functioning was judged less important than dents ranged from 20 to 72 years. Health care profes- other medical factors. sionals most preferred to work with patients beIn comparing the importance of the factors between the ages of 45-64, with the younger and older tween the two vignettes, medical risk was relatively groups preferred by about the same proportion of more important in the allocation of scarce resources respondents. than in the decision to withhold treatment. In the allocation of scarce resources vignette, family conAs shown in Table 4, respondents generally residerations, expected quality of life following treatported medical factors as most important in deciment, the degree of pain and suffering, as well as sions made in response to each vignette. The prior rules of the institution and the potential for legal wishes of the patient were also given relatively greater importance compared with other patient or liability were reported to be less important than they institutional and societal factors. For both vignettes, were in the decision to withhold treatment. Vol. 28, No. 3,1988

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decision-making outcomes was tested using a series of multivariate analyses, in which each model was analyzed separately, with all variables introduced as a block, and then with the Models combined. In the case of the allocation vignette (Vignette A), in which a dichotomous choice was made between two patients, logistic regression was used. Logistic regression is derived from ordinary least-squares regression and is appropriate for assessing the individual and joint effects of a set of independent variables in predicting the probability of a certain event. The logit of risk is the log-odds of a specific choice and can be interpreted as the linear function of the factors important in the decision (Schlesselman, 1982). In the withholding treatment vignette (Vignette B), in which responses ranged over a 5-point scale, ordinary least squares (OLS) regression was used. Indices were formed when there were high levels of colinearity among the factors.

ent-aged men. Therefore, self-reported decision-factors, Model I, were adequate to explain variance in this decision. As shown in Table 6, multiple regression analyses were used to indicate the predictive ability of the models for the decision to support intubation, as is summarized by the percent of variance explained (R2), adjusted for sample size and number of predictors. Model I indicated that a variety of factors were involved in the decision to provide or withhold treatment. Associated with support of intubation were the factors of medical risk to the patient and both variables associated with institutional and societal constraints (rules of the institution and the potential for legal liability). Associated with not supporting intubation (withholding treatment) were the factors of the expected quality of life following treatment and the cognitive functioning of the patient. The total amount of variance explained in this model was 50%. Variables in Model II also contributed to the variance among respondents with respect to how strongly they supported intubation. Because both site and professional affiliation were dummy variables, the regression coefficient for each included group is equivalent to the difference between the mean of the included and the mean of the excluded group (Kerlinger & Pedhazur, 1973). Hence, the significant regression coefficients associated with being a physician or a nurse showed that of the professional groups, nurses and physicians were more likely than social workers to support withholding treatment. Those respondents who

Table 5. Standardized Regression Coefficients from Logistic Regression Models Predicting Choice of Old Rather than Young Patient (Vignette A) (n = 178)

Model tested Independent variables Medical factors Medical risk to patient Expected quality of life following treatment Degree of pain and suffering Cognitive functioning Institutional and societal constraints Informal and formal rules of institution Potential for legal liability Patient factors Prior wishes of the patient Age of the patient Family considerations Situational characteristic Acute care site (acute = 1; chronic = 0) Provider characteristics Age of provider Preference for age group of patients Physician (1 = MD, 0 = others) Nurse (1 = MD, 0 = others) Intercept Fraction of concordant pairs between predicted and actual responses

Model I Beta

Model II Beta

.96** -.95*** -.33 -.13

1.07* -.98** -.15 -.07

.25* .10

.21 -.04

-.23 -.25 .01

.99 .80***

Model III Beta

-.22 -.24 -.18 -.77

-.51

-.01 -.04 .30 .39 -.03

.02 -.20 .34 .90 1.91

.59

.80**