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Psychosomatic Medicine 69:115-123 (2007)
© 2007 American Psychosomatic Society

ORIGINAL ARTICLES

Patient Satisfaction With Treatment After Acute Myocardial Infarction: Role of Psychosocial Factors

Lisa C. Barry, PhD, MPH, Judith H. Lichtman, PhD, John A. Spertus, MD, MPH, John S. Rumsfeld, MD, PhD, Viola Vaccarino, MD, Philip G. Jones, MS, Mary E. Plomondon, PhD, MSPH, Susmita Parashar, MD and Harlan M. Krumholz, MD, SM

From the Department of Internal Medicine/Geriatrics (L.C.B.), the Department of Epidemiology and Public Health (J.H.L., H.M.K.), and the Department of Internal Medicine (H.M.K.), Yale University School of Medicine, New Haven, CT; the Department of Medicine (J.A.S., P.G.J.), Mid America Heart Institute, and Univesity of Missouri-Kansas City, MO; the Section of Cardiology (J.S.R., M.E.P.), Denver Veterans Affairs Medical Center, Denver, CO; and the Department of Medicine (V.V., S.P.), Emory University School of Medicine, Atlanta, GA.

Address correspondence and reprint requests to Lisa C. Barry, Program on Aging, Yale University School of Medicine, 300 George Street, Suite 775, New Haven, CT 06511. E-mail: lisa.barry{at}yale.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Objective: To determine if psychosocial status influences treatment satisfaction, a quality-of-care indicator, of patients who were hospitalized for acute myocardial infarction (AMI).

Methods: Psychosocial variables (social support, dispositional optimism, and depression) were assessed in 1847 AMI patients who completed a 1-month assessment in Prospective Registry Evaluating Myocardial Infarction: Events and Recovery (PREMIER), a multicenter, prospective cohort study. Patients' treatment satisfaction was determined using the Treatment Satisfaction scale of the Seattle Angina Questionnaire. The association between psychosocial variables and treatment satisfaction—adjusted for site, sociodemographics, medical history, clinical presentation, and treatment procedures—was evaluated using a censored normal model.

Results: Study participants were primarily white (77.6%) and male (68.8%), with a mean age of 60.6 ± 12.7 (SD) years. Satisfaction with posthospitalization treatment following AMI increased as social support (Wald {chi}2 = 35.02, p < .001) and dispositional optimism (ß = 1.42; 95% CI 0.24, 2.60) increased. Participants with mild (–3.10, 95% CI –5.77, –0.44), moderate (–4.77, 95% CI –8.16, –1.38), moderately severe (–8.49, 95% CI –13.47, –3.52), and severe (–11.65, 95% CI –18.77, –4.53) depression had significantly worse treatment satisfaction compared with the nondepressed participants.

Conclusion: Assessing psychosocial variables, such as social support, dispositional optimism, and depression severity before hospital discharge, may indicate who is likely to be more satisfied with posthospitalization cardiac care 1 month following AMI. Without controlling for psychosocial status, treatment satisfaction may be a biased indicator of quality. Future studies should evaluate whether psychosocial intervention after AMI can improve satisfaction.

Key Words: treatment satisfaction • psychosocial • outcomes • myocardial infarction • registry

Abbreviations: ACS = acute coronary syndrome; AMI = acute myocardial infarction; CABG = coronary artery bypass grafting; CI = confidence interval; CPK-MB = creatine phosphokinase-2; ENRICHD = Enhancing Recovery in Coronary Heart Disease; ESSI = ENRICHD Social Support Instrument; IQR = interquartile range; LOT-R = Life Orientation Test-Revised; NSTEMI = non-ST segment elevation myocardial infarction; OR = odds ratio; PCI = percutaneous cardiac intervention; PHQ-9 = Patient Health Questionnaire-9; PREMIER = Prospective Registry Evaluating Myocardial Infarction: Events and Recovery; RR = relative risk; SAQ = Seattle Angina Questionnaire; SAS = Statistical Analysis Systems; SD = standard deviation; TIA = transient ischemic attack; TIMI = thrombolysis in myocardial infarction.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Patient satisfaction with treatment is an important goal of healthcare delivery, given the beneficial outcomes associated with higher satisfaction. Satisfied patients are more likely to comply with treatment (1,2), maintain a relationship with a specific healthcare provider (3–5), and report better health status (6,7). Earlier studies have demonstrated small but significant associations between sociodemographic characteristics and patient satisfaction, suggesting that lower satisfaction is associated generally with being younger, female, and more educated (8–14). Yet, the magnitudes of these associations are generally small, with correlations <0.14. Because healthcare institutions often use patient satisfaction with treatment as a benchmark for healthcare quality (15–17), it is important to consider if other patient-related factors may influence who is more or less likely to be satisfied with their care. Furthermore, better insight into the factors associated with satisfaction may offer opportunities for targeting patient healthcare improvement in areas such as service delivery and patient-centered communication.

Psychosocial factors, such as depression, social support, and optimism, have been indicated as contributing to the "burden of illness" of acute myocardial infarction (AMI) due to their strong association with post-AMI prognosis (18,19). For example, patients with depression post-AMI are at increased risk for subsequent cardiac events (20), comorbid illness (21,22), and mortality (23–29). Also, low levels of social support and low optimism are reportedly associated with increased morbidity and mortality after AMI (30–35). Whether psychosocial factors are associated with treatment satisfaction posthospitalization for AMI, however, is unknown.

The primary objective of this study was, therefore, to assess whether psychosocial factors at the time of hospitalization for AMI are associated with 30-day treatment satisfaction. Specifically, we evaluated whether social support, optimism, and/or depression were independently associated with 1-month treatment satisfaction in a multicenter cohort of patients with AMI. This study is intended to expand knowledge about factors associated with post-AMI treatment satisfaction so that opportunities to improve satisfaction regarding patients' care after hospitalization for AMI may be identified. Furthermore, identifying the patient-centered sources of variation in treatment satisfaction can improve the methodology of using satisfaction scores as markers of healthcare quality.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Study Sample
The study population and methods have been described previously (36). Participants were part of Prospective Registry Evaluating Myocardial Infarction: Events and Recovery (PREMIER), a multicenter prospective study of patients hospitalized for AMI between January 1, 2003 and June 28, 2004. Institutional Research Board approval was obtained at each participating institution. All patients were admitted to one of 19 US hospitals and screened for possible inclusion in this study. Eligibility criteria included age ≥18 years, either increased troponin or creatine phosphokinase-2 (CPK-MB; patients with elevated cardiac enzymes as a complication of elective coronary revascularization were not eligible), and supporting evidence suggestive of an AMI (e.g., prolonged ischemic signs/symptoms, electrocardiographic ST changes) and having presented at the enrolling institution or having been transferred within the first 24 hours of onset of symptom. Incarcerated patients were not eligible. To participate in the study, all patients had to sign an informed consent, approved by each institution's review board. A total of 3953 patients met eligibility criteria and 2498 (63.2%) patients were enrolled. Although some statistically significant differences were detected between the enrolled and nonenrolled patients, the absolute differences were small (36).

The sample for the present study consists of the 1847 (74.0%) patients who had complete baseline psychosocial data and 30-day treatment satisfaction scores. Of the 2235 patients with complete psychosocial data, 388 were then excluded from the study sample because they were missing a 30-day treatment satisfaction score: 107 refused, 29 did not complete the treatment satisfaction questions, 38 died, and 214 were lost to follow-up.

Predischarge Data Collection
Although the data collection methods have been previously described (33), several variables warrant mention.

Social Support
Social support was assessed during the predischarge face-to-face interview by using the Enhancing Recovery in Coronary Heart Disease (ENRICHD) Social Support Instrument (ESSI) (37), a scale with documented validity (30,38–40). Responses to each of six questions about how often social support was available ranged from 1 (none of the time) to 5 (all of the time). These items, along with marital status (married = 4, not married = 2), were added to form a summary scale with a possible range from 8 (minimum level of social support) to 34 (maximum level of social support). The ESSI demonstrated strong internal consistency in our cohort (Cronbach's {alpha} = 0.87). We also reestablished in our population the construct validity of the ESSI by comparing the mean scores between two groups: a) married and nonmarried participants and b) participants living alone versus those not living alone. Being married automatically confers +2 to the social support score; thus, this item was excluded for validation purposes, leaving the score as the sum of the other six ESSI items. The analysis was stratified by a dichotomous classification of low versus high social support to determine if there was any additional quantitative construct association over and above an initial screening classification for low social support (37). Among those patients screening negative for low social support, being married and living alone were associated with 0.6 point greater and 1.0 point lower mean social support scores, respectively. Results were similar for those screening positive for low social support. These findings indicate that the ESSI social support measure has additional construct validity beyond a low versus high social support classification.

Dispositional Optimism
Dispositional optimism was assessed using the Life Orientation Test-Revised (LOT-R) (41). The LOT-R is an 8-item self-report measure that assesses generalized expectancies for positive and negative outcomes. Scores range between 1 and 24. Cronbach's {alpha} was 0.74 in our cohort.

Depression Severity
Depression severity was assessed using the 9-item version of the Patient Health Questionnaire (PHQ-9), which has been shown to be 88% sensitive and specific for major depressive disorder (42). The PHQ-9 has a range from 0 to 27 with higher scores indicating more severe depression. Patients were classified according to their severity of depression scores as follows: 0 to 4 (no clinical depression), 5 to 9 (mild depression), 10 to 14 (moderate depression), 15 to 19 (moderately severe depression), and ≥20 (severe depression) (42). Participants with no depression comprised the referent category and dummy variables were created for the other depression categories.

30-Day Assessment of Treatment Satisfaction
Patient satisfaction with treatment was determined using the Treatment Satisfaction scale of the Seattle Angina Questionnaire (SAQ) (43) that was administered during the 30-day follow-up phone interview. This scale is comprised of four questions asking patients to evaluate the current treatment of their chest pain, chest tightness, or angina; scores range between 0 and 100, with the higher scores indicating greater satisfaction. In support of its validity and reliability, the Treatment Satisfaction scale of the SAQ has been found to be highly correlated with the American Board of Internal Medicine's Patient Satisfaction Questionnaire (44) and the mean scores did not change after 3 months of observing patients with stable coronary artery disease (intraclass correlation coefficient = 0.81) (43). The SAQ Treatment Satisfaction scale has also been demonstrated to be sensitive to improvements in the structures of healthcare delivery (45).

Treatment satisfaction was analyzed as a continuous variable in the primary analyses. In addition, we used two alternate ways of assessing outcome. First, we defined high satisfaction as having a perfect score of 100 (n = 924, or 50% of the study participants). Second, given that there is no standard way to classify treatment satisfaction (46), we used the strategy of Beinart and colleagues (47) and created "high treatment satisfaction" as the primary outcome, defined as having a score in the upper three quartiles (range 83.3–100.0). The reference group was considered as having "low satisfaction." These decisions were made before examining associations with patient factors.

Statistical Methods
Predictors of treatment satisfaction were evaluated using bivariate and multivariable regression models. Because treatment satisfaction scores demonstrated a substantial ceiling effect (left-skewed with a mode at 100 comprising 50% of the responses), a censored normal model was used, which assumes that observed satisfaction scores are censored versions of latent (unobserved) values that may exceed the scale of the instrument (48). Analyses were also replicated using standard linear models (i.e., assuming normality of responses), and the results were very comparable. Censored-model results are presented here. Multivariable models were constructed to estimate the incremental prognostic value of psychosocial variables after adjusting for patient demographic and clinical factors. An initial model was constructed including patients' socioeconomic status, medical history, clinical presentation, and treatment variables (Table 1). Social support, optimism, and depression variables were then added simultaneously, given that the correlation between each of these psychosocial variables was low (r = 0.2–0.3). All continuous variables were allowed to be entered nonlinearly using restricted cubic splines. For variables for which the nonlinear component was nonsignificant (p > .2), we allowed those to be fit linearly for easier interpretation of the effects; results for these variables are reported as change in treatment satisfaction per 1 SD increase in the underlying variable. Pseudo-R2 (49) values for the initial and final models were calculated to compare the proportion of variation explained by each model. Furthermore, the presence of interactions between each of the psychosocial variables and age, sex, and race was tested by including interaction terms in the final multivariable model. We also included interaction terms for each of the psychosocial variables with each other (e.g., depression x social support) to determine if the effect of any of the psychosocial variables on treatment satisfaction was modified by other psychosocial variables.


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  		TABLE 1. Study Population Characteristics

 

In the secondary analyses of dichotomized treatment satisfaction, model-based, relative risks of high satisfaction were estimated using modified Poisson regression models (50). Rather than standard logistic regression, this approach was used because treatment satisfaction "events" (i.e., scores of 100 or scores in the upper three quartiles) were not rare, in which case odds ratios are poor estimates of relative risk.

Unless otherwise noted, p < .05 denotes statistical significance. SAS version 9.1 (SAS Institute, Cary, NC) and R version 2.3.0 (51) were used to perform all analyses.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 NOTES
 REFERENCES
 
Patient Characteristics
Table 1 presents the descriptive characteristics of the study population. The mean ± SD age of the 1847 study participants was 60.6 ± 12.7 years. The majority of the study participants were white (77.6%) and male (68.8%), and noncardiac comorbidities were common, including diabetes (26.6%), chronic obstructive pulmonary disease (11.9%), and chronic renal failure (8.0%). Approximately 20% of this sample had had a previous myocardial infarction. Mean ± SD values for social support and dispositional optimism scores were 29.7 ± 5.4 and 15.9 ± 3.7, respectively. Approximately 46% of the study participants showed some depression at baseline, with 2.3% experiencing severe depression.

Treatment Satisfaction
The mean treatment satisfaction score in the present study was 90.7 (median = 100, range = 16.7–100, interquartile range (IQR) = 81.3–100). Half (n = 924, 50.0%) of the patients reported maximum treatment satisfaction scores of 100. The mean ± SD scores for patients in the three highest and the lowest treatment satisfaction quartiles were 97.0 ± 4.7 and 72.0 ± 12.1, respectively.

Table 2 presents the unadjusted (bivariate) and adjusted (multivariable) results. A linear fit was adequate for all continuous variables except social support and hematocrit. Wald {chi}2 and p values are provided for these variables. In both bivariate and multivariable analyses, mean treatment satisfaction at 30 days posthospitalization for AMI increased with increasing age (adjusted ß = 3.25; 95% CI 1.77, 4.73) and was lower for females as compared with males (adjusted ß = –4.24; 95% CI –6.93, –1.54). In contrast to the bivariate findings, education was significantly associated with treatment satisfaction in the multivariable analysis, with treatment satisfaction declining with more years of education (adjusted ß = –4.40; 95% CI –7.38, –1.42). Race, marital status, and health insurance status were significantly associated with treatment satisfaction in bivariate but not multivariable analyses. In addition, treatment satisfaction was lower in participants who had a previous coronary artery bypass graft surgery (CABG) (adjusted ß = –6.53; 95% CI –10.25, –2.80) or stroke/transient ischemic attack (TIA) (adjusted ß = –4.25; 95% CI –8.29, –0.22). Each of the psychosocial variables was associated with treatment satisfaction in the bivariate analysis and remained significant after adjusting for the additional socioeconomic status, medical history, clinical presentation, and treatment variables, although the effect sizes were slightly attenuated. As shown in Figure 1, higher social support scores were associated nonlinearly with higher treatment satisfaction scores in both bivariate and multivariable analyses (adjusted Wald {chi}2 = 35.02, p < .001). As indicated by the more marked increase in mean treatment satisfaction score, there is a seemingly stronger relationship between treatment satisfaction and social support in persons scoring >25 points on the ESSI. Dispositional optimism was also associated (linearly) with treatment satisfaction. Dispositional optimism scores increased as treatment satisfaction scores increased (ß = 1.42; 95% CI 0.24, 2.60). Furthermore, participants with mild (ß = –3.10; 95% CI –5.77, –0.44), moderate (ß = –4.77; 95% CI –8.16, –1.38), moderately severe (ß = –8.49; 95% CI –13.47, –3.52), and severe (ß = –11.65; 95% CI –18.77, –4.73) depression had significantly worse treatment satisfaction as compared with those participants with no depression (p < .001 for trend). The R2 for the initial model was 0.072 before adding the psychosocial variables to the model and 0.119 afterward. In addition, there was no substantial effect modification by age, sex, or race, nor was the association between any of the three psychosocial variables and treatment satisfaction significantly modified by the effect of each other (p < .15 for all interactions). For example, the association between the reduced levels of social support and lower treatment satisfaction remained regardless of depression severity (p = .18 for the interaction). Each of the psychosocial variables remained significantly associated with treatment satisfaction in the two sensitivity analyses of dichotomized treatment satisfaction (data not shown).


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  		TABLE 2. Bivariate and Multivariable Risk Models of the Association Between Psychosocial Factors and Treatment Satisfaction

 

Figure 11
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  		Figure 1. Unadjusted and adjusted predicted treatment satisfaction scores according to social support instrument scores.

 

To explore the potential impact of follow-up bias, we repeated the dichotomous-outcome twice, assigning first "low satisfaction" and then "high satisfaction" to patients who had incomplete 1-month follow-up. Effect sizes for all three psychosocial variables were nearly identical to the primary results in each of these sensitivity analyses, and statistical significance was maintained, except for the association with dispositional optimism when missing satisfaction scores were imputed as "high satisfaction" (p = .17). Thus, although there may be unmeasurable bias in treatment satisfaction among patients who were not followed up, the association between psychosocial factors and treatment satisfaction did not appear to be affected appreciably.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
NOTES
 REFERENCES
 
To our knowledge, this is the first study to demonstrate that psychosocial status before hospital discharge is associated with the patient's satisfaction of care received after hospitalization for AMI. Even after controlling for many potentially confounding factors, social support, dispositional optimism, and depression severity were independently associated with 30-day treatment satisfaction. These findings suggest that patient-related characteristics, above and beyond many other sociodemographic and clinically related factors, may be important indicators of who is likely to be more or less satisfied with treatment delivered after hospitalization for AMI.

Higher levels of social support have been found to be associated with more positive outcomes among patients with AMI and other cardiac illnesses. Patients with AMI and high social support have been shown to have decreased morbidity and mortality as compared with those patients with lower levels of social support (30–35). Increased social support also has been found to be associated with better prognosis among older patients with heart failure (52). Our findings that a high level of social support is associated with another positive outcome—higher satisfaction with treatment—are supported by a study of noncardiac patients whose satisfaction with their medical care was better for those with high perceived social support (53). It is possible that the availability of social support may make the recovery period post-AMI less physically and mentally challenging. A supportive network to take on tasks, such as daily chores and/or to have associates available just to talk with, may decrease the patient's distress and ultimately translate into better treatment satisfaction.

Earlier studies of patients with cardiac illness have found that higher dispositional optimism is associated with better health outcomes (32,54,55). Our finding that increasing optimism was associated with increasingly higher treatment satisfaction was consistent with these studies. One study of patients recovering from coronary artery bypass surgery (54) found that the more optimistic patients used coping strategies, such as goal-setting, gathering information about their condition, and making the decision not to dwell on feelings of nervousness and sadness. Disengagement from their postoperative goals was more common among the less optimistic. Coping strategies, such as these, may help to explain why the patients with higher dispositional optimism in our study had higher satisfaction with their post-AMI care. Future studies are needed to determine whether the use of different coping strategies among more and less optimistic persons affects satisfaction with the treatment delivered after hospitalization for AMI.

We also found that another psychosocial factor, depression severity, was strongly associated with patient satisfaction after hospitalization for AMI. As compared with those nondepressed participants, participants with any form of depression, ranging from mild to severe, had significantly worse treatment satisfaction scores. Among the most severely depressed participants, the treatment satisfaction scores were nearly 12 points lower than those participants with no depression. Our results are congruent with other studies that have found depression to be associated with poor health outcomes in patients with AMI (20–28,56), other cardiac conditions such as congestive heart failure (57,58), and postcoronary artery bypass surgery (59). Furthermore, these results are consistent with several studies that have examined the relationship between depression and satisfaction in noncardiac patients (60–62). In subsequent analyses, we found that patients with depression scores below the median had significantly more comorbid conditions, worse clinical presentation, and were more likely to have had previous cardiac procedures. It is possible that the perception of the quality of their healthcare systems was diminished among these persons because they had chronic illnesses and procedures that did not resolve their cardiac problems.

We also found that several socioeconomic factors were associated with treatment satisfaction. Treatment satisfaction increased with increasing age. Other studies assessing patients' satisfaction with their health care also reported this association (63–65). Possible explanations for the increased satisfaction with age have previously been suggested, including more favorable treatment of older persons by healthcare workers due to maturational, generational, and historical factors (66); a greater likelihood for older persons to provide socially desirable responses (67); and a lesser likelihood for older persons to challenge physician authority (68). More years of education and female gender were associated with worse treatment satisfaction. Reportedly, more educated patients are less likely to be satisfied with their health care (69,70). Patients with more years of schooling may have heightened expectations regarding their treatment options and recovery (8,71). It is possible that poorer treatment satisfaction may result if these preconceived expectations are not met. The finding that the female gender was associated with worse treatment satisfaction scores as compared with the male gender contrasts the results of other studies assessing the relationship between gender and patient satisfaction that have found no association with gender (8). These studies, however, were not conducted in cardiac patients. Other studies have repeatedly shown that women have poorer recovery after cardiac procedures (72,73) and higher mortality rates after AMI as compared with men (74,75). In addition, having had prior coronary artery bypass surgery was the only clinical factor to be associated with lower treatment satisfaction after AMI. Because the prior surgery did not prevent a future heart attack, these patients may have felt particularly frustrated and, consequently, less satisfied. Importantly, psychosocial factors appear to have a greater predictive ability regarding patient satisfaction with treatment than do traditional sociodemographic and clinical factors.

Some considerations should be kept in mind when interpreting the results of this study. It is possible that the type of hospital (e.g., large, university-based versus small, community-based) may have influenced the results. Although we adjusted for the enrollment site in all analyses, this study did not include smaller community and rural hospitals. We were unable to conduct 30-day assessments on 214 patients due to reasons other than death, refusal, or illness, and the psychosocial profile of these patients was poorer than those not missing follow-up data. Results of the sensitivity analysis indicated that follow-up bias was unlikely. Furthermore, we do not perceive our inability to include these patients as a threat to the generalizability of our findings; patients who did not respond to the 1-month follow-up survey would also be unlikely to respond to other efforts to quantify treatment satisfaction. Although our satisfaction measure included a question regarding satisfaction with the doctor's explanations, it is possible that this question was not sensitive enough to capture the nuances of satisfaction with various facets of the patient-provider relationship, such as perceived empathy, kindness, and time spent with the patient. Consequently, the relationship between the psychosocial factors and treatment satisfaction may be driven by their relationship to a particular aspect of treatment satisfaction. Future studies may consider assessing the role of psychosocial variables in various areas of satisfaction.

Although the treatment satisfaction scale used in this study quantifies current satisfaction with treatment by capturing patients' satisfaction with treatment 1 month after their AMI, we may have captured residual impressions from their hospital care. Moreover, because coronary artery disease is a longitudinal condition that requires continual care, capturing patients' satisfaction with the process of care posthospitalization (as is done in most surveys that use satisfaction as a marker of healthcare quality) is an advantage. We were able to show that psychosocial characteristics at the time of discharge, above and beyond many clinical factors, are associated with patient satisfaction with care post-AMI. Consequently, our findings provide the basis for future research exploring a causal relationship between psychosocial status and post-AMI treatment satisfaction.

Related to this latter point, there may be multiple factors, including patients' symptoms (e.g., chest pain), rehospitalization, cardiac procedures, change in comorbid conditions, life events, and interaction with the healthcare system, that may mediate the relationship between psychosocial status and 30-day treatment satisfaction. For example, a previous study conducted on patients experiencing an acute coronary syndrome indicated that both history of depression and current angina burden were associated with 7-month treatment satisfaction (47). Thus, the severity of depression after AMI may influence angina symptoms 1 month after AMI, which, in turn, acts as the mechanism through which the severity of depression influences treatment satisfaction. Furthermore, it is possible that changes in social support, optimism, and the severity of depression that occurred between the the time of discharge and the period of follow-up assessments may have affected patients' perceptions of their physical condition, thereby acting as mediators of the association between these variables and treatment satisfaction. For example, among patients with moderately severe depression, depression may persist and/or worsen between the two assessments. Their persistent and/or worsening depression may negatively affect the self-assessment of their physical functioning, ultimately translating into poorer treatment satisfaction. Consequently, the association between psychosocial variables and satisfaction, as found in our study, may not be directly causal. However, our findings indicate that psychosocial status is a risk marker for poor satisfaction at 1 month post-AMI.

In conclusion, our study provides important insight into who may be at risk for having poor satisfaction with posthospitalization treatment following AMI. Overall, our findings suggest that psychosocial characteristics are important factors to consider when assessing satisfaction with post-AMI treatment and they may be more influential than factors like medical history and type of treatment. Consequently, healthcare institutions should consider collecting and adjusting for psychosocial data before presenting patient satisfaction with treatment as a quality-of-care indicator. Future work is needed to better understand the mechanisms by which psychosocial variables influence patient satisfaction with treatment after myocardial infarction and other illnesses, and to evaluate whether psychosocial interventions after AMI can improve patient satisfaction.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
REFERENCES
 
Received for publication December 12, 2005; revision received October 4, 2006.

This project was supported by CV Therapeutics, Inc., Agency for Healthcare Research and Quality Grant R-01 HS11282-01, and National Institute on Aging Training Grant T32AG019134 (L.C.B.).

DOI:10.1097/PSY.0b013e31802f2785


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 

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