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Research Article

Patient Factors and Perioperative Outcomes Affect Hospital Consumer Assessment of Healthcare Providers and Systems Survey Response Rates After Primary Total Hip Replacement

Mercier, Michael R. BA; Pathak, Neil MD; Adrados, Murillo MD; Galivanche, Anoop R. BS; Malpani, Rohil BS; Hilibrand, Ari S.; Rubin, Lee E. MD; Grauer, Jonathan N. MD

Author Information
JAAOS: Global Research and Reviews: April 2021 - Volume 5 - Issue 4 - e21.00052
doi: 10.5435/JAAOSGlobal-D-21-00052


In recent years, a growing emphasis has been placed on patients' perception of their health care.1-3 Although many hospitals have historically collected information on patient satisfaction for their own internal use, objectively and meaningfully comparing patients' perspective of care across hospitals has been difficult without a national standard for reporting this information.4 To address this, the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey was implemented as a national, standardized survey of patients' perception of hospital care.5 Factors that might affect such survey results are critical to interpreting such measures after high-volume procedures such as total hip arthroplasty (THA).

Since its initial conception in 2002, the HCAHPS survey was developed, tested, and eventually tied to the Annual Payment Update for Inpatient Prospective Payment System in 2008.6 Under this system, acute care facilities are required to gather and publish their HCAHPS results through the Centers for Medicare and Medicaid Services Hospital Compare Website or sustain up to a 2% reduction in their Annual Payment Update. Public reporting of these results creates new incentives for hospitals to improve the quality of care. As a further incentive, hospitals are financially rewarded for achievement and improvement through the Value-Based Purchasing program.7 The HCAHPS survey is administered to a random sample of adult patients across medical conditions between 48 hours and 6 weeks after discharge; the survey is not restricted to Medicare beneficiaries.

Despite its frequent use as a metric of “healthcare quality,” a number of studies have found that HCAHPS scores may not be a great measure of this. To that end, a study of 1,383 HCAHPS surveys provided by patients undergoing THA demonstrated that variables such as sex, length of stay, and body mass index (BMI) correlated with HCAHPS survey scores.8 In other words, factors other than the quality of care affected the HCAHPS results. Furthermore, a THA study found that HCAHPS did not correlate with change in EuroQol-5d (a standardized instrument for assessing generic health status) scores or Hip Disability and Osteoarthritis Outcome scores (a questionnaire that assesses patient-reported symptoms and functional limitations related to their hip arthroplasty).9

Yet, another overarching problem with the HCAHPS survey is its intrinsically low response rate. For example, in 2019, the Centers for Medicare and Medicaid Services reported a national HCAHPS response rate of 25%.10 Such a large percentage of nonresponders could skew the data if certain subgroups of the patient population are underrepresented.11 Such discrepancies in the response and nonresponse groups are referred to as nonresponse biases.

Nonresponse bias has been documented within an orthopaedic outpatient population in which age, sex, insurance type, and type of orthopedic subspecialist encountered were shown to influence the response rates to the Press-Ganey patient satisfaction survey.12,13 Furthermore, Malpani et al14 demonstrated that several patient characteristics and perioperative outcomes were associated with HCAHPS nonresponder bias after spine surgery. However, little is known regarding how the HCAHPS survey response rates may be affected by such variables for patients undergoing elective THA.

Thus, this study was performed to investigate the potential correlation of patient characteristics and perioperative variables with HCAHPS response rates after THA. Such data could be of help in interpreting HCAHPS responses and guiding future use and collection of such measures.


Patient Inclusion/Exclusion Criteria

All patients who underwent inpatient elective total THA at a single institution and received the HCAHPS questionnaire from February 2013 to May 2020 were selected for retrospective inclusion and analysis. Patients were identified using the Current Procedural Terminology codes for primary THA, which included 27,130 and 27,132.

Patients younger than 18 years of age, patients who died during their hospital stay, and patients undergoing revision or partial hip arthroplasty, or THA for hip fracture, were excluded from the study. HCAHPS responses resulting from any patient readmission encounters were not separately assessed. Use of all patient data for this research project was approved by our institution's Institutional Review Board.

Data Elements

Patient demographic data, in addition to preoperative and 30-day postoperative outcome data, are recorded systematically by our institution's National Surgical Quality Improvement Program team for all THA patients. This team consists of trained clinical reviewers that follow patients for 30 days after surgery to characterize patient characteristics and procedures, as well as to document the incidence of postoperative complications, readmissions, and additional surgeries.15

Demographic variables included patient age, sex, height and weight (used to calculate BMI), American Society of Anesthesia (ASA) class, functional status (before surgery), and race. ASA class data were used as a composite marker for patient comorbidity, as is often done in orthopedics literature.16,17

Postoperative adverse events were similarly tabulated and were categorized as major or minor. Major adverse events included deep infection, sepsis and septic shock, ventilator use more than 48 hours, unplanned intubation, acute renal failure, deep vein thrombosis, pulmonary embolism, cardiac arrest, myocardial infarction, and stroke. Minor adverse events included superficial infection, wound dehiscence, pneumonia, urinary tract infection, and renal insufficiency. Any adverse event was defined as the occurrence of either a major or minor adverse event.

In addition to the aforementioned postoperative events, several other variables were collected. Readmission within 30 days was assessed. Discharge disposition from index hospitalization was categorized as home or other. Prolonged hospital length of stay was assessed if greater than 3 days.

All patients who had a THA performed at our institution were mailed an HCAHPS survey within 2 days of discharge for completion and return. All returned HCAHPS surveys were accounted for when calculating survey return rate, regardless of whether the survey was completed in its entirety. In addition, the surgeon of record was noted to assess if there was bias to rate of survey return by surgeon.

Statistical Analysis

After tabulating returned HCAHPS surveys, patient demographics and perioperative outcomes were compared between patients who returned the HCAHPS survey and those who did not. Categorical demographic variables were compared with chi-squared or Fisher exact tests. Continuous demographic variables such as age and BMI were compared using the Student t-test. Major and minor postoperative adverse events, readmission, prolonged length of stay, and HCAHPS survey response rates between surgeons were also compared using chi-squared tests.

Binary logistic regressions were performed to assess the independent effects of demographic variables on patients' likelihood of returning the HCAHPS survey. The first regression included the following patient demographic factors: age, race, sex, BMI, and ASA class. The second regression included the following postoperative factors: any, major, and minor adverse events occurrence, readmission, hospital discharge destination, and prolonged hospital stay. Covariates controlled for in the second regression included all variables studied in the first regression.

Statistical significance for all analyses was set at α = 0.05, and 95% confidence intervals (CI) were reported. Statistical analysis was performed with IBM SPSS Statistics, version 26 (IBM).


Patient Demographics

Of 3,310 THA patients analyzed, 1,049 (31.69%) returned HCAHPS surveys (Figure 1). Patients who returned the survey varied by attending surgeon, with the highest response rate being 44% for surgeon 1 and 17% for surgeon 8 (P < 0.001) (Figure 2).

Figure 1
Figure 1:
Pie chart depicting the HCAHPS response rate after total hip arthroplasty. Of 3,310 primary total hip arthroplasties included in the study, 1,049 patients returned the HCAHPS survey, yielding a response rate of 31.69%. HCAHPS = Hospital Consumer Assessment of Healthcare Providers and Systems
Figure 2
Figure 2:
Chart showing the HCAHPS survey response rate by treating surgeon. All surgeons performing 60 or more total hip arthroplasty procedures were anonymized by code and arranged by descending case volume. HCAHPS survey response rate varied considerably depending on the surgeon (range: 17% to 44%, P < 0.001). HCAHPS = Hospital Consumer Assessment of Healthcare Providers and Systems

On univariate chi-squared analysis, patients who did not return the survey were more likely to be younger (mean of 63.32 years compared with 66.91 years, P < 0.001), be more male (45.64% versus 39.75%, P = 0.001), have slightly higher BMIs (mean of 30.27 compared with 29.45, P < 0.001), have higher ASA class scores (43.92% of patients with an ASA score of three compared with 33.65%, P < 0.001), be slightly less functionally independent (97.35% functionally independent compared with 99.05%, P = 0.002), or be non-Caucasian (76.65% Caucasian compared with 91.42% Caucasian, P < 0.001). These findings are summarized in Table 1.

Table 1 - Demographics of Patients Undergoing Primary Total Hip Replacement Organized by the Status of Hospital Consumer Assessment of Healthcare Providers and Systems Survey Return
Survey Status Survey Not Returned Survey Returned Univariate P
N = 3,310 (100%) N = 2,261 (68.31%) N = 1,049 (31.69%)
Age: mean (SD) 63.32 (12.73) 66.91 (10.74) <0.001
 18-34 56 (2.48%) 10 (0.95%)
 35-54 500 (22.11%) 110 (10.49%)
 55-74 1,289 (57.01%) 691 (65.87%)
 ≥75 416 (18.40%) 238 (22.69%)
Sex 0.001
 Male 1,032 (45.64%) 417 (39.75%)
 Female 1,229 (54.36%) 632 (60.25%)
BMI: mean (SD) 30.27 (6.45) 29.45 (5.97) <0.001
 <25 476 (21.05%) 261 (24.88%)
 25-30 726 (32.11%) 347 (33.08%)
 30-35 602 (26.63%) 256 (24.40%)
 >35 450 (19.90%) 179 (17.06%)
ASA <0.001
 1 80 (3.54%) 59 (5.62%)
 2 1,150 (50.86%) 627 (59.77%)
 3 993 (43.92%) 353 (33.65%)
 4+ 38 (1.68%) 10 (0.95%)
Functional status (before surgery) 0.002
 Independent 2,201 (97.35%) 1,039 (99.05%)
 Partially/totally dependent 60 (2.65%) 10 (0.95%)
Race <0.001
 Caucasian 1,733 (76.65%) 959 (91.42%)
 Black/African American 397 (17.56%) 34 (3.24%)
 Asian 6 (0.27%) 56 (5.34%)
ASA = American Society of Anesthesiologists classification, BMI = body mass index
Bolding indicates statistical significance at P < 0.05.

Perioperative Outcomes

Univariate analysis was then done with univariate chi-squared tests to assess for perioperative variables associated with not returning the survey (Table 2). Patients who did not return the survey were more likely to experience any adverse event (5.00% compared with 2.38%, P < 0.001) and a major adverse event (2.48% compared with 0.76%, P = 0.001). For individual adverse events, those who did not return the survey were more likely to have experienced a deep infection (0.57% compared with 0.10%, P = 0.048), pulmonary embolism (0.57% compared with 0.00%, P = 0.014), a superficial infection (1.42% compared with 0.57%, P = 0.034), and pneumonia (0.57% compared with 0.10%, P = 0.048).

Table 2 - Adverse Event Outcomes After Primary Total Hip Replacement Organized by the Status of Hospital Consumer Assessment of Healthcare Providers and Systems Survey Return
Survey Status Survey Not Returned Survey Returned Univariate P
N = 3,310 (100%) N = 2,261 (68.31%) N = 1,049 (31.69%)
All adverse events 113 (5.00%) 25 (2.38%) <0.001
Major adverse events 56 (2.48%) 8 (0.76%) 0.001
 Deep infection 13 (0.57%) 1 (0.10%) 0.048
 Sepsis/septic shock 16 (0.71%) 3 (0.29%) 0.135
 Ventilator >48 hrs 1 (0.04%) 0 (0.00%) 0.496
 Unplanned intubation 3 (0.13%) 0 (0.00%) 0.238
 Acute renal failure 0 (0.00%) 0 (0.00%)
 Deep vein thrombosis 12 (0.53%) 4 (0.38%) 0.564
 Pulmonary embolism 13 (0.57%) 0 (0.00%) 0.014
 Cardiac arrest 0 (0.00%) 0 (0.00%)
 MI 5 (0.22%) 1 (0.10%) 0.429
 Stroke 3 (0.13%) 0 (0.00%) 0.238
Minor adverse events 65 (2.87%) 19 (1.81%) 0.070
 Superficial infection 32 (1.42%) 6 (0.57%) 0.034
 Wound disruption 1 (0.04%) 1 (0.10%) 0.578
 Pneumonia 13 (0.57%) 1 (0.10%) 0.048
 Urinary tract infection 19 (0.84%) 10 (0.95%) 0.746
 Progressive renal insufficiency 1 (0.04%) 1 (0.10%) 0.578
Readmissions 174 (7.70%) 36 (3.43%) <0.001
Discharge disposition 898 (39.72%) 297 (28.31%) <0.001
 Home 1,363 (60.28%) 752 (71.69%)
 Other 898 (39.72%) 297 (28.31%)
Long hospital length of stay (> 3 d) 268 (11.85%) 62 (5.91%) <0.001
Bolding indicates statistical significance at P < 0.05.
MI = myocardial infarction.

For other postoperative adverse events, those who did not return the survey were more likely to have had readmission (7.70% compared with 3.43%, P < 0.001), been discharged to a place other than home (39.72% compared with 28.31%, P < 0.001), or experience a hospital length of stay greater than 3 days (11.85% compared with 5.91%, P < 0.001).

Multivariate Analysis of Patient Factors Associated with Hospital Consumer Assessment of Healthcare Providers and Systems Survey Nonresponse

A multivariate regression model containing age, sex, BMI, ASA classification, preoperative functional status, and race was constructed to determine the odds of not returning the HCAHPS survey. This approach allowed the quantification of nonresponse risk in the context of all other demographic and preoperative factors. These findings are summarized in Table 3, and statistically significant findings are shown in a forest plot (Figure 3).

Table 3 - Demographic Factors Associated With Not Returning the Hospital Consumer Assessment of Healthcare Providers and Systems Survey in Patients Undergoing Primary Total Hip Replacement
Type N = 3,830 (100%) Likelihood of Not Returning Survey
OR 95% CI P
 18-34 1.00
 35-54 0.93 0.45-1.93 0.853
 55-74 0.38 0.19-0.78 0.008
 75+ 0.35 0.17-0.71 0.004
 Female 1.00
 Male 1.17 1.00-1.37 0.050
 <25 1.00
 25-30 1.10 0.89-1.36 0.367
 30-35 1.09 0.87-1.36 0.449
 >35 0.97 0.76-1.25 0.834
 1 1.00
 2 1.51 1.04-2.20 0.029
 3 2.27 1.54-3.35 <0.001
 4+ 3.13 1.41-6.98 0.005
Functional status (before surgery)
 Independent 1.00
 Partially/totally dependent 2.69 1.35-5.36 0.005
 Caucasian 1.00
 Black or African American 3.40 2.53-4.57 <0.001
ASA = American Society of Anesthesiologists classification, BMI = body mass index, CI = confidence interval, OR = odds ratio
Factors in model: all factors in Table 1.
Bolding indicates statistical significance at P < 0.05.

Figure 3
Figure 3:
Forest plot depicting the notable variables from the multivariate regression on both demographic and postoperative factors highlighting the HCAHPS nonresponder bias after total hip arthroplasty. HCAHPS = Hospital Consumer Assessment of Healthcare Providers and Systems

By age, using the age group 18 to 34 years as the referent, there were decreased odds of nonresponse in patients aged 55 to 74 years (Odds Ratio [OR] = 0.38; 95% CI, 0.19 to 0.78; P = 0.008) and in patients aged 75 years and older (OR = 0.35; 95% CI, 0.17 to 0.71; P = 0.004). No association was seen between BMI or sex and nonresponse (P > 0.050 for all). By ASA, using the patient cohort with ASA classifications of 1 as the referent, increased odds of nonresponse were observed in patients with an ASA of 2 (OR = 1.51; 95% CI, 1.04 to 2.20; P = 0.029), ASA of 3 (OR = 2.27; 95% CI, 1.54 to 3.35; P < 0.001) and in patients with an ASA of four or greater (OR = 3.13; 95% CI, 1.41 to 6.98; P = 0.005). Patients with nonindependent preoperative functional statuses had increased odds of nonresponse compared with patients who had independent preoperative functional statuses (OR = 2.69; 95% CI, 1.35 to 5.36; P = 0.005). Black patients had increased odds of nonresponse compared with Caucasian patients (OR = 3.40; 95% CI, 2.53 to 4.57; P < 0.001).

Multivariate Analysis of Postoperative Factors Associated With Hospital Consumer Assessment of Healthcare Providers and Systems Survey Nonresponse

Multivariate regression models were then constructed to quantify the odds of nonresponse in patients who experienced postoperative adverse events, controlling for the aforementioned demographic variables. These findings are summarized in Table 4, and statistically significant findings are shown in a forest plot (Figure 3).

Table 4 - Postoperative Factors Independently Associated With Not Returning the Hospital Consumer Assessment of Healthcare Providers and Systems Survey in Patient Undergoing Primary Total Hip Replacement
Type Likelihood of Not Returning Survey
N = 3,830 (100%)
OR 95% CI P
Any adverse event 1.80 1.14-2.84 0.012
Major adverse event 2.88 1.34-6.19 0.007
Minor adverse event 1.26 0.74-2.16 0.399
Readmission 2.13 1.45-3.13 <0.001
Discharged place other than home 1.71 1.43-2.03 <0.001
Long hospital length of stay (> 3 d) 1.89 1.40-2.55 <0.001
CI = confidence interval, OR = odds ratio
Factors in model: all factors in Table 1.
Bolding indicates statistical significance at P < 0.05.

There were increased odds of nonresponse in patients who experienced any adverse event postoperatively (OR = 1.80; 95% CI, 1.14 to 2.84; P = 0.012), a major adverse event (OR = 2.88; 95% CI, 1.34 to 6.19; P = 0.007), and readmission to the hospital within 30 days (OR = 2.13; 95% CI, 1.45 to 3.13; P < 0.001). There were also increased odds of nonresponse in patients who were discharged to a place other than home (OR = 1.71; 95% CI, 1.43 to 2.03; P < 0.001) and in patients who experienced a prolonged hospital stay (OR = 1.89; 95% CI, 1.40 to 2.55; P < 0.001). No statistically significant difference was noted in odds of nonresponse in patients who experienced a minor adverse event (OR = 1.26; 95% CI, 0.74 to 2.16; P = 0.399).


The HCAHPS survey has historically been used as a tool by which patient satisfaction after hospitalization can be determined. Although the program has been in place since 2008, it is still not certain whether a compelling association between HCAHPS scores and health care quality exists.5,18

Although several investigations have been performed on the association of HCAHPS scores to a patient's clinical and demographic characteristics, few studies have assessed the nonresponse rate of HCAHPS surveys. This study focuses on the nonresponse rate (and thus potential nonresponse bias) because response patterns can affect average survey answers and survey conclusions. Studying the nonresponse rate of national healthcare surveys such as the HCAHPS is especially relevant because the actual HCAHPS responses have been shown to vary based on a variety of patient characteristics19,20 and thus factors associated with response could select for those more or less likely to provide positive feedback.

In assessing 3,310 patients undergoing THA from a single academic institution, this study showed that only 1,049 (31.69%) patients returned the survey. Further nonresponse rates were variable for different surgeons, patient of different demographics, and patients with different perioperative outcomes.

The overall response rate for HCAHPS identified in this study was on par with other published reports and the national average.10,21 With less than one-third of the patient population returning the survey, a potential for bias in those who returned the survey is evident. In fact, if a survey study were performed asking surgeons or other respondents about almost any topic, a response rate of less than one-third would certainly raise questions of nonresponse bias.

In addition, this study demonstrated a range of HCAHPS survey return rates by treating surgeon to range from 17% to 44%. Previous research has examined surgeon characteristics associated with high patient satisfaction survey scores, but not on survey return rate.22 More research is needed to determine ways in which surgeons can optimize survey return rates among their own patients.

For patient characteristics, a multivariate analysis found patients to be less likely to respond to the HCAHPS survey if they were younger, have a higher ASA classification, be partially or totally functionally dependent, and be Black or African American. Each of these findings is of potential impact on response findings.

That patients with a higher comorbidity burden (ASA) and who are more functionally disabled were less likely to complete the survey (independent of other demographic variables) are similar to previous findings for a spine surgery population.14 It is unclear why sicker patients are less likely to respond to patient satisfaction surveys. Future research may seek to determine whether the patient's nonresponse is because of a physical inability to complete and return the survey or an unwillingness to engage in postdischarge communication with the hospital.

The higher nonresponse rate for younger patients is in line with a previous study which studied an outpatient orthopaedics patient population receiving Press-Ganey satisfaction surveys.12 This may be related to previous research that has demonstrated that younger patients are more likely to respond to patient satisfaction surveys via Web-based delivery methods, whereas older patients are more likely to respond to mail-in methods.23 Thus, future efforts to optimize patient response rate may include expanding delivery methods of surveys with consideration to the target populations.

Patients identified as Black or African American were also markedly less likely to respond to the HCAHPS survey. This follows other survey nonresponse patterns, including the U.S. census, in which persons identifying as African American are significantly less likely to respond.24 Nonresponse bias based on demographic factors creates a situation where certain groups are underrepresented in the survey scores, potentially undermining the validity of survey conclusions.25

Furthermore, on a multivariate analysis controlling for patient factors, this study found that several perioperative adverse events correlated with nonresponse. These included any adverse event, major adverse event, readmission, discharge destination to a place other than home, and hospital length of stay greater than 3 days.

It is possible that patients who experience certain postoperative complications, and are potentially less satisfied with their hospital experience, may be less likely to be motivated to complete postdischarge paperwork such as the HCAHPS surveys. Thus, these patients many not be adequately represented in response studies.

Postoperative factors including readmission within 30 days, discharge to a place other than home, and longer hospital length of stay were all associated with survey nonresponse bias. For readmission and discharge to a place other than home, it is possible that not being in their own home mailing address disrupted their ability to properly receive and return the survey.

These factors were similarly implicated in the HCAHPS survey nonresponse among a single institution cohort of spine surgery patients.14 Thus, the HCAHPS response rates among these patients may benefit from using more comprehensive survey distribution strategies.

This study has several limitations. It is retrospective in nature, which introduces the possibility of unmeasured confounding variables. In addition, the particular reason why a patient chose to return or not return the survey is unknown, making it difficult to gain further insight into specific patient factors driving nonresponse. Finally, as the data analyzed stems from one institution, the results may not be entirely generalizable to the national THA patient population.

Nonetheless, this study comprehensively assesses determinants of nonresponse bias in THA patients completing the HCAHPS survey. The results of this study suggest that the HCAHPS survey results represent a markedly skewed sample of the true surgical population. These findings are especially relevant, given previous research that suggests a correlation between lower response rates and lower average patient satisfaction scores.26 Understanding the response rate and systemic biases that affect the response of the HCAHPS surveys is paramount in critically evaluating the utilization of the HCAHPS surveys as a legitimate measure of healthcare quality. These findings must be considered when drawing conclusions from the results of HCAHPS surveys, and academic studies surrounding them. This is also true regarding federal policy if hospital payment adjustments or physician professional fees are linked to HCAHPS survey responses or the results.


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Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Orthopaedic Surgeons.