Xiao Xiang, PhD; Wendy Yi Xu, PhD, MS; and Randi E. Foraker, PhD, MA
With an increasing emphasis on curbing costs while improving healthcare, patient satisfaction has become an essential quality indicator. Patient satisfaction measures are an important component of the Affordable Care Act’s financial incentives for hospitals to provide better quality of care.1
In the Donabedian framework for examining health service and quality, healthcare quality comprises the dimensions of structure, process, and outcomes.2
Fortunately, the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey provides an opportunity to capture the patient experience with a variety of quality categories, including environment, communication, pain control, responsiveness, and care continuity in hospitals, allowing us to further explore the role of patient satisfaction in distinct quality aspects.3
The HCAHPS measures were built into financial incentives. In 2012, CMS began withholding 1% of reimbursements from hospitals as part of its value-based purchasing (VBP) program. Hospitals are able to earn the payment back by realizing high patient satisfaction scores and care quality standards. Tying patient satisfaction to hospital reimbursements remains controversial, as more satisfied patients do not necessarily receive better medical care or experience superior health outcomes. Moreover, there is a controversy over the efficacy and reliability of patient satisfaction metrics. There is a concern that unnecessary costs may increase in the pursuit of higher scores on these metrics, because doctors may turn to discretional services when their payments are associated with patient satisfaction.4
The controversies urged researchers to examine the association between patient satisfaction and healthcare quality in distinct classes of diseases. Stroke is a class of life-threatening cerebrovascular disease that caused 129,000 deaths and cost $20.2 billion in 2010 in the United States.5
If boosting patient satisfaction can improve stroke care quality without significantly increasing the cost, patients and hospitals will benefit.
So far, empirical studies have studied the association between patient satisfaction and healthcare cost and quality in various diseases. Evidence suggests that hospitals with higher patient satisfaction scores have lower readmission rates for acute myocardial infarction, heart failure, and pneumonia,6
and patient satisfaction has also been shown to improve guideline adherence and mortality in acute myocardial infarction.7
For surgical care, higher patient satisfaction saw shorter inpatient stays and lower readmission and mortality rates.8
However, higher patient satisfaction was also associated with higher inpatient costs and postdischarge mortality rates on the individual patient level.4
Moreover, most existing studies have assumed all satisfaction categories to have a similar effect as global satisfaction on care quality. It is well documented that higher global patient satisfaction was associated with better care qualities, yet how the specific aspects of patient satisfaction relate to other structure and process quality measures is still unknown.
Therefore, we explored the relationship between patient satisfaction and cost, clinical performance, and health outcomes in stroke care at the hospital level. We examined the following research questions: first, whether global satisfaction was associated with better stroke care quality; second, whether the components of satisfaction were independently associated with stroke care performance and outcomes; and finally, we assessed whether improving patient satisfaction resulted in higher stroke care cost and what satisfaction categories accounted for the differences in costs.
We obtained hospital-level patient satisfaction measures from the 2015 HCAHPS patient survey database.9
The average inpatient charges for hospitalized patients who had a stroke came from the 2013 CMS Medicare Provider Cost and Payment Data inpatient file. Outcome measures were selected from the CMS Hospital Compare database, including risk-adjusted 30-day mortality rates and risk-adjusted 30-day unplanned readmission rates. This database was updated between 2014 and 2015 at the time of the study. The clinical performance measures for timely and effective stroke care also came from Hospital Compare database (eAppendix Table 1
[eAppendices available at www.ajmc.com
We further augmented our data with hospital characteristics from the fiscal year 2016 Inpatient Prospective Payment System final rule file.11
We obtained the US Census geographic region from the 2014 Area Health Resource File.12
Hospital-level mortality and unplanned readmission rates were already adjusted by patient demographic characteristics and CMS condition categories (eAppendix Table 1). Thus, these risk-standardized measures allowed us to compare hospitals with different patient demographics and health status distribution.13,14
Cost of acute stroke care.
Cost was defined as the cost of care for patients who have had a stroke without major comorbidity. Specifically, we estimated cost by multiplying the charges for Diagnosis-Related Group (DRG) 066 by hospital-specific Cost-to-Charge Ratios (CCRs). We used the CCRs from the fiscal year 2016 file for cost in 2013 because of the 3-year lag period in cost data collection.
Performance measures of stroke care.
According to a previous classification of stroke care performance measure, we constructed 3 performance domains, including acute treatment, inpatient management performance, and secondary prevention performance.15
We generated the domain performance scores (range = 0-100) by averaging the scores of measures that belonged to the same domain (eAppendix Table 1). We used 6 items from a CMS measurement of timely and effective stroke care to indicate clinical performance of stroke care (eAppendix Table 1).16
“Intravenous thrombolytic therapy” and “patients with atrial fibrillation receiving anticoagulation therapy” were dropped from analysis because of an excessive missing rate (>50%).
The data from the HCAHPS survey provided us with standardized measures of patient satisfaction with hospital care for all patients at the hospital level and were adjusted for patient-mix and survey mode.3
CMS classified the HCAHPS survey questions into 2 global items, 2 individual items, and 7 composite measures of patient satisfaction.9
Patient satisfaction categories in our analyses were selected from this preexisting classification.
The global items were an overall rating of the hospital and the patient’s likelihood of recommending the hospital to friends and family. Because these 2 global measures were highly correlated, we only used the recommendation measure for analyses. The patient satisfaction score is the percentage of patients with the highest possible rating on the metric. We averaged the scores in the same category, and then divided these scores into quartiles (eAppendix Table 1).
Multiple hospital characteristics were included as covariates in the analyses. Hospitals’ geographic characteristics included whether they were located in an urban or rural setting and their census region locations (northeast, midwest, west, or south). Teaching status was determined by whether a hospital received a teaching hospital payment adjustment from CMS. Hospital ownership was classified as public, for-profit private, nonprofit private, or other. We classified hospitals as small, medium, or large according to the number of beds, teaching status, and region, following the definition used by the Healthcare Cost and Utilization Project.17
Disproportionate share hospitals (DSH) were defined by CMS as the sum of the percentage of Medicare and Medicaid days that were attributed to low-income patients who were Supplementary Security Income eligible. We also determined from these data whether or not a hospital participated in a stroke care registry.
We first described the distribution of hospital characteristics in those that reported stroke outcome measures or cost information. Categorical data were presented as counts with percentages and continuous variables were presented as medians with interquartile ranges.
We estimated coefficients (β) and 95% CIs for the association between patient satisfaction and cost, 30-day mortality rate, 30-day readmission rate, and stroke care performance for all hospitals reporting stroke outcome data, using multiple linear regression models. The regression model for cost was performed on hospitals that reported cost information for DRG 066. We applied a log transformation to the cost data. Thus, the β coefficients yielded a percentage difference in cost compared with the reference group. The percentage change of the cost was calculated as (еβ
− 1) × 100%.
Regression models were adjusted for hospital size, ownership, teaching status, region, rural location, DSH percent, and stroke registry status. For models regarding stroke outcomes, we added stroke performance measures to the adjustment set to examine whether patient satisfaction measures were independently associated with stroke outcomes. To make the results more generalizable to all strokes, even those accompanied by complications and comorbidities, we did a sensitivity analysis combining all stroke DRGs (65 and 66). All statistical analyses were performed using SAS version 9.4 (SAS Institute; Cary, North Carolina).
We identified 2530 hospitals that reported 30-day mortality rates and 30-day readmission rates for stroke and 1422 hospitals that reported an average cost for stroke without major comorbidities and conditions in fiscal year 2013.
describes the characteristics of selected hospitals. In hospitals that reported stroke outcomes, 15.1% were publicly owned, 17.1% were located in the northwestern region, 22.2% were small, and 22.2% were located in a rural area. The median 30-day mortality and readmission rate was 14.7 and 12.7 per 100 patients, respectively (interquartile ranges, 2.1 and 1.4, respectively). The median scores for acute treatment, inpatient management, and secondary prevention were 99.0, 98.5, and 97.6 (interquartile ranges, 2.0, 3.5, and 5.1).
Patient Satisfaction and Health Outcomes
We found that the global satisfaction measure (“recommendation of hospital”) was related to 30-day outcomes. The 30-day mortality rate comparing the highest quartile to the lowest quartile of global satisfaction was significantly lower (β = 0.39 per 100 patients) (Table 2
). Similarly, the 30-day readmission rate was also lower in the highest quartile of global satisfaction compared with the lowest quartile (β = 0.34 per 100 patients) (Table 2). The Figure
(a and b) demonstrated a dose-dependent effect for 30-day readmission across quartiles of global satisfaction, with a negative association between satisfaction and 30-day mortality in the upper 3 quartiles.
Hospitals that ranked the highest in satisfaction with hospital environment had a higher 30-day readmission rate by 0.27 per 100 patients compared with the least satisfied quartile. However, 30-day mortality was not associated with satisfaction with hospital environment. The highest quartile of satisfaction with pain control was associated with lower 30-day mortality rate (β = –0.57 per 100 patients) (Table 2). In contrast, we observed an increase in 30-day mortality rate of 0.70 per 100 patients in the highest quartile of satisfaction with discharge information relative to the lowest quartile. However, readmission rates were lower in hospitals with the highest, versus the lowest, satisfaction with discharge information (β = –0.37 per 100 patients) (Table 2). The full regression results can be found in the eAppendix Table 2
Patient Satisfaction and Cost
The average cost in hospitals with the highest global satisfaction was $6785, 7.3% higher than the least satisfied hospitals ($6324) (Figure
[c]). There is a decreasing trend of cost within the first 3 quartiles of satisfaction, but with no statistical or clinical significance. After adjusting for hospital-level covariates, the cost in hospitals with highest global satisfaction was still 8% higher than the least satisfied hospitals. In addition, compared with hospitals in the least satisfied quartile of environment, the highest quartile had 7% higher costs. Meanwhile, satisfaction with communication, pain control, care transition, and discharge information was not associated with cost (Table 2).
In sensitivity analysis (eAppendix Table 3
), the hospitals with the highest global satisfaction cost 8% higher than the least satisfied hospitals, even after combining the cost of all patients who had a stroke (with and without major complications).
Patient Satisfaction and Stroke Care Performance
No association was found between global satisfaction and acute treatment, inpatient management, or secondary prevention performance. Hospitals in the highest quartile of discharge information satisfaction had 1.62 (P
<.001) and 1.82 (P
<.001) higher scores, on average, with regard to inpatient management and secondary prevention than hospitals in the lowest quartile (eAppendix Table 4
). Full regression results can be found in eAppendix Table 5
Understanding whether patient satisfaction with hospital care is consistent with healthcare quality is critical to current CMS reimbursement policies based on a VBP system.18
Our findings support the hypothesis that global patient satisfaction can represent the quality of care that hospitals provide. Specifically, we found that the risk-adjusted 30-day mortality rate and readmission rate among patients who have had a stroke decreased, with an increase in global patient satisfaction from the lowest to the highest quartile. Linking patient satisfaction to healthcare quality, our study results suggest that the global patient satisfaction measure is useful for assessing value-based care in the context of stroke.
Our investigation into each satisfaction dimension also challenged the conventional assumptions in existing studies that all satisfaction dimensions have similar effects on care quality. Previous studies found that improving the quality of care continuity, such as care transition, patient education, and discharge planning, was effective in containing unplanned readmission rates.16
We observed that patient satisfaction with discharge information was associated with a reduced readmission rate. Surprisingly, we also observed higher satisfaction with discharge information associated with higher 30-day mortality rates. A previous systematic review of various diseases showed that discharge planning did not help reduce the mortality rate,19
leading us to reconsider the role of discharge information in quality improvement.
The results of a recent study show that the hospital-level mortality rates were not associated with the readmission rates, proposing the hypothesis that the 30-day readmission rate and mortality rate are conveying different information about healthcare quality.17
It should be noted that the 30-day mortality rate was calculated from the moment of inpatient admission and was largely affected by in-hospital care, whereas 30-day readmission rates were calculated only after discharge. There was even an article that casted doubt on the validity of readmission rates, suggesting that it is more an accountability measure than a quality measure.18
Thus, patient experience measures that are found to be associated with readmission reduction do not necessarily also help to reduce mortality rate.
It is possible that resource abundant hospitals have good quality and accountability and generally have better patient experience. However, hospitals that have to spend substantial efforts on improving patient education, discharge planning, and outpatient support may have higher patient satisfaction and lower readmission rates; however, such efforts could drive stroke mortality in the opposite direction. In our analysis, patient satisfaction with discharge information was linked to better inpatient management and secondary prophylaxis performance, while the increased performance was not associated with better health outcomes. Thus, the incentive to achieve premium patient experience may be unfair to hospitals that cannot spare enough resources to support all patient satisfaction–promoting activities.
VBP programs are primarily aimed at improving healthcare quality while reducing cost, yet we found that hospitals in the highest quartile of satisfaction provided care that costs 6.9% more than hospitals in the lowest quartile, suggesting that improving patient satisfaction does not help to mitigate inpatient costs. Hospitals that take a large number of patients who have suffered a stroke will spend substantially more money to achieve higher satisfaction. This is an interesting finding, because we observed that the cost rose faster than any improvements in outcomes. The observed improvements in mortality and readmission rates were 3.1% and 2.7%, respectively, which were similar in size to a previous study of patients with acute myocardial infarction, heart failure, and pneumonia.6
The results of a previous study showed that higher patient satisfaction was linked to higher intensity of inpatient care and drug prescriptions.4
Yet, these procedures and prescriptions were not necessarily beneficial to patients. This finding suggests that hospitals that invested more money to improve patient satisfaction generated a minimum or even a negative return in stroke care outcome.
Limitations and Strengths
There are several limitations to our study. First, as it is based on CMS data, our results may not be appropriate to generalize to all hospitals because the participating hospitals may be systematically different, in terms of hospital characteristics, compared with non-participating hospitals. Another limitation is the ecological design of our study. Our results can only explain the association at the hospital level, not at the patient level. Although we have adjusted for hospital size, teaching status, location, region, and disproportionate share, unobserved factors may still confound our results. For example, hospitals that discharge more patients to their home, rather than a skilled nursing facility, may have higher patient satisfaction and lower readmission rates. Nevertheless, lacking stroke severity information may not be a major confounder because the health outcome measures were risk adjusted in terms of case mix, hospital clustering effect, and comorbidities of patients.14
The risk adjustment may also explain the lack of variability of mortality and readmission rate among hospitals in our sample. Furthermore, our study cannot determine the direction of causality. HCAHPS surveys were conducted from 48 hours to 6 weeks after discharge. It could be possible that some patients reported low satisfaction because they experienced unfavorable health outcomes during the time after discharge. Finally, without an indicator of stroke severity, we can only provide the evidence of association, instead of causality, between patient satisfaction and stroke care cost.
Despite the limitations, our study also has some strengths. To extend our ability to extrapolate our conclusions to a broader definition of stroke cases, we conducted a sensitivity analysis. In those analyses, global patient satisfaction remained associated with an increased cost of care. In addition, we used both CCR and hospital charge to estimate cost. Specifically, we estimated cost by multiplying the charges for DRG 066 by hospital-specific cost-to-charge ratios. Although we do not have information of the real costs that were incurred, previous researchers have verified that using the CCR produces estimates closest to providers’ actual costs.20-22
There are many other ways to estimate cost, such as using the CMS payments or hospital charges; however, these methods are also subject to limitations. The CMS payments were the reimbursements to the hospitals after adjusting the costs by regional, hospital, and individual characteristics according to published policies.11
With hospital-level aggregated data, we were not able to disentangle policy adjustment and the real cost from the payments. The charges were the list prices marked by the hospitals, which were usually much higher than the real cost.23
Thus, standardizing charges by CCR was the best approximation of cost in this context.
Our study provided important knowledge on the relationship between patient satisfaction and healthcare quality in stroke care. Higher global patient satisfaction scores were associated with improved readmission and mortality rates while discharge information satisfaction domains produced mixed evidence. Our analysis also suggests that improving patient satisfaction will lead to higher stroke care costs and the associated improvements observed in stroke outcomes may not be cost-effective.