Abstract
Background
Patient satisfaction surveys play an increasingly important role in United States healthcare policy and serve as a marker of provided physician services. In attempts to improve the patient’s clinical experience, focus is often placed on components of the healthcare system such as provider interaction and other experiential factors. Patient factors are often written off as “non-modifiable”; however, by identifying and understanding these risk factors for dissatisfaction, another area for improvement and intervention becomes available.
Questions/purposes
(1) Do patients in the orthopaedic clinic with a preexisting diagnosis of depression report lower satisfaction scores than those without a preexisting diagnosis of depression? (2) What other non-modifiable patient factors influence patient-reported satisfaction?
Methods
We reviewed Press Ganey Survey scores, which assess patient experiential satisfaction with a single clinical encounter, from 3044 clinic visits (2527 patients) in adult reconstructive, sports, and general orthopaedic clinics at a single academic medical center between November 2010 and May 2017, during which time approximately 19,000 encounters occurred. Multiple patient factors including patient age, gender, race, health insurance status, number of previous clinic visits with their physician, BMI, and a diagnosis of depression were recorded. Patient satisfaction was operationalized as a binary outcome as satisfied or less satisfied, and a multiple logistic regression analysis was used to estimate the odds of being satisfied.
Results
After adjusting for all other covariates in the model, we found that patients with a diagnosis of depression were less likely to be satisfied than patients without this diagnosis (odds ratio 0.749 [95% confidence interval, 0.600-0.940]; p = 0.01). Medicare-insured patients were more likely to be satisfied than non-Medicare patients (OR 1.257 [95% CI, 1.020-1.549]; p = 0.03), patients in the sports medicine clinic were more likely to be satisfied than those seen in the general orthopaedic clinic (OR 1.397 [95% CI, 1.096-1.775]; p = 0.007), and established patients were more likely to be satisfied than new patients (OR 0.763 [95% CI, 0.646-0.902]; p = 0.002).
Conclusions
Given the association of depression with lower satisfaction with a single visit at the orthopaedic clinic, providers should screen for depression and address the issue during the outpatient encounter. The impact of such comprehensive care or subsequent treatment of depression on improving patient-reported satisfaction offers areas of future study.
Level of Evidence
Level III, therapeutic study.
Introduction
Patient satisfaction is an essential part of a successful patient-physician interaction. Interpersonal relations with doctors and nursing staff, substantial time spent with the healthcare provider during the visit, expressed empathy, and delineation of clear expectations have been demonstrated to substantially influence patient satisfaction [4, 11, 12, 17, 22]. In the past decade, patient surveys have been used by payers and hospital groups to assess subjective patient satisfaction as a marker of physician services provided [3, 9, 14].
Patient-reported satisfaction surveys do not, however, always accurately reflect physician performance or overall quality of experience [7, 9, 13]. Considered non-modifiable, patient factors such as age, gender, race, employment status, type of health insurance, new or established visit, facilities, and distance from the clinic have been studied in various fields of medicine [1, 2, 4, 16, 18, 21, 22, 24, 26]. After orthopaedic surgery, depression specifically has been correlated with lower reported satisfaction scores [5, 15, 23, 25] and, similarly, self-reported “psychological distress” in the outpatient orthopaedic setting [1]. The Press Ganey survey (PGS) is a useful tool in this setting because it provides a global reflection of satisfaction with a single clinic visit, including clinical care, staff interactions, facilities, and other factors. In identifying these groups of patients who are dissatisfied with their experience, there is an opportunity for a later root cause analysis to identify modifications of the clinic interaction to accommodate these “non-modifiable” traits.
Therefore, we asked: (1) Do patients in the orthopaedic clinic with a preexisting diagnosis of depression report lower satisfaction scores than those without a preexisting diagnosis of depression? (2) What other non-modifiable patient factors influence patient-reported satisfaction?
Patients and Methods
Participants
We retrospectively reviewed patient satisfaction scores from 3044 clinic visits (2527 patients) to the adult reconstructive surgery, sports medicine, or general orthopaedic clinics in the orthopaedic department of a single academic medical center between November 2010 and May 2017. During this time period, the cumulative outpatient volume was approximately 19,000 encounters. All clinic visits with patients aged 18 years and older who completed a survey after a clinic appointment were included in the study. After obtaining patient responses to the PGS, we extracted the following information from the patients’ medical records to create a cross-sectional study: age, comorbidities, self-reported gender, race, religion, marital status, type of health insurance provider, BMI, ZIP code, provider, and type of orthopaedic clinic visited. A Charlson comorbidity index score [8] was calculated for each patient. ZIP code was used to approximate the distance the patient travelled to the clinic. Clinic visit notes were analyzed for documentation that the provider recommended weight modification as a form of treatment and/or as a requirement before surgical intervention. Information on provider gender and race was also assigned (not self-reported) and included in the analysis. Depression was considered present if it was documented either in the progress note for a given encounter or in the patient’s electronic medical record as a preexisting condition in the patient’s medical history. This study was reviewed and approved by the institutional review board at the University of Texas Southwestern Medical Center.
Outcome Variables
The Medical Practice PGS is a survey tool used to report patient satisfaction with a one-time clinical encounter. It consists of 24 questions divided into six subdomains: access (five questions), progress through the visit (two questions), nurse or assistant (two questions), care provider (10 questions), personal issues (four questions), and special services and parking (one question). To focus on overall patient satisfaction with the clinic visit, we measured the primary outcome of patient satisfaction using all six domains and thus all 24 items comprising the PGS. We followed the scoring protocol of the PGS. Each of the 24 items was measured on a five-point scale (very poor [1], poor [2], fair [3], good [4], and very good [5]). On the PGS, participants rated services using a 1-5 scale and then, according to the PGS scoring protocol, respondents’ ratings were linearly transformed (converted) to very poor (0), poor (25), fair (50), good (75), and very good (100). Domain scores were calculated as the mean of the items for a given domain, and the six domain scores were averaged to produce a total mean satisfaction score ranging from 0 to 100. Higher total scores indicated greater overall patient satisfaction with the clinic visit.
Because we observed a frequency distribution of approximately 36% on the care provider survey on which patients indicated they were completely satisfied (PGS score = 100), for the analysis, patient satisfaction was operationalized as a binary outcome. Our selection of a cutoff for the binary operationalization of the outcome variable of patient satisfaction was empirically driven according to the distribution of satisfaction scores. The central thesis of our study was about the relationship between depression status and patient satisfaction. Thus, a receiver operating characteristic curve (based on the Youden index) helped guide our selection of a cutoff, and we determined that a total PGS score with a cutoff less than 87% best discriminated depression status. The 87% cutoff corresponded to approximately the 25th percentile in the distribution of satisfaction scores. This threshold was chosen a priori and is similar to the threshold used by Abtahi et al. [2].
Patients were categorized as “less satisfied” if their total PGS score was less than 87%. Patients with a total PGS score of at least 87% were categorized as “satisfied.” We modeled the probability of the patient being “satisfied.” We also retained the continuous metric properties of the Press Ganey patient satisfaction scale, which was used in a post hoc sensitivity analysis.
Potential Covariates
An initial pool of 15 characteristic variables were selected as potential covariates of patient satisfaction for analysis. These variables were selected based on the results of previously published findings [2-4, 16, 18, 21, 22, 24, 26]. The pool of potential covariates, which was selected a priori, included patient age (years), patient gender (man or woman), gender of the care provider (man or woman), patient race (white or non-white), race of the care provider (white or non-white), patient marital status (married or not married), patient depression status (yes or no) as determined by prior documentation in the patient’s electronic medical record without specification of treatment status, patient BMI (< 30 kg/m2, 30-34.9 kg/m2, 35-39.9 kg/m2, or ≥ 40 kg/m2, with < 30 kg/m2 as the reference group), modification of weight as a form of treatment (yes or no), modification of weight as a requirement for surgery (yes or no), patient health insurance status (Medicare or non-Medicare), patient Charlson comorbidity index score, patient distance to clinic (miles), patient’s first visit to clinic (yes or no), and type of orthopaedic clinic setting (adult reconstruction and hip, sports medicine, or general orthopaedic, with general orthopaedic as the reference group). For the analysis, BMI was rescaled as a multinomial variable (as indicated above), which was an a priori clinical decision and consistent with the guidelines of the Centers for Disease Control and Prevention weight status classification.
Multiple Imputation for Missing Values
Missing values for the PGS items and patient variables, which occurred in no more than approximately 10% of the sample, were imputed. Missing values (with an assumed arbitrary missing pattern) for the classification variables and continuous variables were imputed via 500 burn-in iterations (samples) using fully conditional specification along with the discriminant method (for the classification variables) and the predictive mean matching method (for continuous variables), using the PROC MI procedures in SAS software, version 9.4 (Cary, NC, USA) [28].
Statistical Analysis
Demographic and clinical characteristics of the sample of 3044 orthopaedic patient clinic visits are described using the sample mean and standard deviation for continuous variables and the frequency and percentage for categorical variables. A multiple logistic regression analysis with penalized maximum likelihood estimation along with Firth’s bias correction was implemented to estimate the odds (or probability) of the patient being satisfied, based on the set of regressors. Adjusted odds ratios and 95% confidence intervals are reported. As a sensitivity analysis, while retaining the continuous metric properties of the Press Ganey patient satisfaction scale, we also estimated patient satisfaction from the same set of regressors in the context of a multiple linear regression model. Statistical analyses were performed using SAS software, version 9.4 (SAS Institute, Inc., Cary, NC, USA). The level of significance was set at α = 0.05 (two-tailed).
Participant Characteristics
The 7-year data collection period encompassed approximately 19,000 encounters. Approximately 16% of visits (3044) returned a completed survey. Of these, 2527 individual patients (40% of all patients) were men and 72% were non-Hispanic white. The mean age of the patients was 60 years ± 16 years. The mean BMI was 29 kg/m2 ± 7 kg/m2, with 63% of the patients having a BMI less than 30 kg/m2. Approximately 38% of the patients had Medicare insurance, commuted a mean of 37 miles ± 116 miles to the clinic, and 43% were first-time (new) patients to the clinic. The mean total PGS satisfaction score was 91% ± 13%, with 73% of patients being satisfied (PGS score ≥ 87%) (Table 1). Depression as a comorbidity was noted in 14% of the patients’ medical records (Table 2).
Table 1.
Demographic and clinical characteristics of the overall sample
Table 2.
Demographic and clinical characteristics by depression status
Results
Association of Depression with Satisfaction
After adjusting for all other covariates (variables) in the model, we found that patients with depression were less likely to be satisfied with the clinic visit than patients without depression (OR 0.75 [95% CI, 0.60-0.94]; p = 0.01).
Association of Non-modifiable Factors with Satisfaction
After adjusting for all other covariates (variables) in the model, we found the odds that a patient would be satisfied were lower for new patients than for established patients (OR 0.76 [95% CI, 0.64-0.90]; p = 0.001) (Table 3). However, the odds of being satisfied were greater for Medicare-insured patients than for non-Medicare-insured patients (OR 1.25 [95% CI, 1.020-1.54]; p = 0.03). Patients who were seen at the sports medicine clinic were more likely to be satisfied than those seen in the general orthopaedic clinic (OR 1.39 [95% CI, 1.09-1.77]; p = 0.006). However, there was no difference in satisfaction between patients seen in the adult reconstruction or hip clinic and those seen in the general orthopaedic clinic (OR 0.94 [95% CI, 0.71-1.24]; p = 0.67). Finally, patients who were seen by a male care provider were more likely to be satisfied with the clinic visit than those who were seen by a female care provider (OR 1.28 [95% CI, 1.02-1.61]; p = 0.03). No other important covariates of patient satisfaction emerged from the logistic regression analysis (Fig. 1).
Table 3.
Odds ratios from the multiple logistic regression analysis for predictors of patient satisfaction
Fig. 1.
This forest plot of predicted odds from the multiple logistic regression analysis shows the adjusted odds of the patient being satisfied (total PGS score of at least 87%) with the clinic visit, based on the pool of predictors. An estimated odds ratio greater than 1 indicated a greater predicted odds of patient satisfaction. n = 3044 clinic visits.
Sensitivity Analysis for Satisfaction and Depression and Non-modifiable Factors
The basic results (not fully reported) of the multiple linear regression model were, in part, in line with those from the primary logistic regression model. The multiple linear regression, while adjusting for all other variables in the model, revealed a negative linear relationship between patient satisfaction and depression status (yes versus no) (b̂ = -1.42; 95% CI, -2.70 to -0.13; p = 0.03) as well as between patient satisfaction and new and established patient status (b̂ = -1.52; 95% CI: -2.44 to -0.59; p = 0.001). Patient satisfaction was lower for depressed patients and for new patients than for non-depressed and established patients. The multiple linear regression analysis, while adjusting for all other variables in the model, also revealed a positive linear relationship between patient satisfaction and Medicare-insured versus non-Medicare-insured patients (b̂ = 1.04; 95% CI, -0.11 to 2.18; p = 0.08). Patient satisfaction was greater for Medicare patients than for non-Medicare patients. No other important regressors of patient satisfaction emerged in the multiple linear regression (sensitivity) analysis.
Discussion
The patient-physician relationship is crucial to clinical practice and many factors may influence patient satisfaction. Payors and hospital systems are increasingly using patient surveys to assess patient satisfaction as a marker of services provided; however, these surveys do not always accurately reflect physician performance [3, 7, 9, 13, 14, 19]. Intrinsic patient factors, independent from the quality of provider interaction, influence these patient-reported outcome scores, and depression specifically has been demonstrated to correlate with lower satisfaction scores after orthopaedic surgery [5, 15, 23, 25]. To better understand how depression and other non-modifiable risk factors might influence patient satisfaction in the outpatient orthopaedic setting, we sought to identify their association through using patient satisfaction surveys. The PGS is one of the largest surveys designed to measure and analyze the outpatient clinic visit [20]. We found that a diagnosis of depression was associated with lower patient satisfaction with the orthopaedic clinic visit, as determined by the PGS score. In our study population, 14.5% of patients had a diagnosis of depression documented in their electronic medical record at the time of the clinic visit. These patients were more likely to report that they were less satisfied with their clinic visit, scoring less than 87% on the PGS. This expands the relationship between postoperative depression and dissatisfaction previously demonstrated in orthopaedic hand, spine, and arthroplasty studies into the outpatient orthopaedic clinic [5, 15, 23, 25].
Limitations
Although statistical power was provided by a large sample size, there are limitations to this study. There are limitations to the PGS itself, including a potential low response rate and nonresponse bias, although the survey continues to be widely used. For this dataset and our study sample, we only had data on patients who completed the survey; thus, information on non-responders is lacking, which raises concern of selection bias. In a previous study, Tyser et al. [27] found the response rate to the PGS was particularly poor and patients who responded tended to differ demographically from those who did not respond. The reader should interpret our results in the context of this potential limitation of the PGS. Further, the PGS is a process metric; it is designed to measure satisfaction with the process of healthcare delivery in the outpatient setting, and does not necessarily reflect the quality of care, outcomes, or adherence to standards of care. Additionally, although depression has been shown to be correlated with less satisfaction after orthopaedic surgery, satisfaction in this setting is multifactorial and includes patient expectations, pain, and function [6, 23]. Although a diagnosis of depression in the present study was associated with less satisfaction, as assessed by the PGS, one should interpret these results in the context of how satisfaction and depression status were measured in this study. Specifically, depression was considered present if it was documented either in the records or in the patient’s electronic medical record as a preexisting condition. This may have been self-reported and was not cross-referenced with an actual provider diagnosis or treatment status. In theory, a patient could be erroneously classified as having depression based on outdated records, user error in entering the patient’s history, or in the absence of sufficient clinical diagnostic criteria. Furthermore, patients may or may not have been actively treated for depression, which would bring important clinical information to bear on the results. Provider knowledge of a patient’s depression might subtly change how care was delivered, and thus how patients perceived their care. Furthermore, the demographics of this patient subset—predominantly older, white, female patients without Medicare insurance—may not necessarily reflect patients in other clinical settings. However, by accounting for these and other covariates in our model, we were able to statistically adjust for the effect of these factors as confounders in the depression subset and thus isolate depression as an independent and substantial factor affecting patient satisfaction with the orthopaedic clinic visit.
Association of Depression with Satisfaction
In our outpatient orthopaedic clinic, patients with a preexisting diagnosis of depression reported lower satisfaction scores than those without. Our findings are similar to those reported by Abtahi et al. [1], who evaluated patient-reported “psychologic distress” at a single spine clinic visit, reporting a substantial association between psychologic distress and decreased patient satisfaction. However, these self-reported depressive symptoms may vary day-to-day and change with the severity of orthopaedic pain and disease. As such, it seems a preexisting diagnosis of depression serves as a more consistent variable when predicting dissatisfaction overall, rather than during a given clinic visit.
Clinical depression is characterized by a depressed mood and lack of interest or pleasure in activities [3]. This mood alteration may unfavorably affect interpersonal interactions, including those essential to the clinic visit, which have been shown to be a critical component of patient satisfaction. Furthermore, depression was demonstrated to be associated with increased non-compliance with medical therapy for non-psychiatric-related disease [10].
In a group of patients treated surgically for lumbar stenosis, depression scores were measured both preoperatively and postoperatively [25]. Depression was associated with less improvement in symptoms and worse pain and functional scores, but those who had recovered from depression had outcomes that were similar to those of the control group. Although this could be more reflective of a transient mood disorder related to spinal pathology-induced pain, it also suggests the treatment of depression could improve compliance and patient satisfaction with the clinic visit. One potential intervention is routine screening of depression using standard clinic intake forms. If a patient screens positive, a frank but empathetic conversation on the impact of depression on satisfaction and pain would be warranted, and a proper referral should be made to a provider who could treat their depression, such as a primary care provider.
Association of Non-modifiable Factors with Satisfaction
We found that patients were more likely to be satisfied if they were established patients, Medicare-insured, visiting the sports medicine clinic, or seeing male providers. Consistent with the findings of previous studies, our study demonstrated that race, gender, insurance status, and previous visits to the provider are non-modifiable patient factors that affect patient satisfaction with the orthopaedic clinic visit [1, 15, 13, 17, 29]. Non-white patients, female patients, non-Medicare insured patients, and patients seeing their provider for the first time were less satisfied with the orthopaedic clinic visit. Acknowledging these risk factors of patient dissatisfaction offers an opportunity for the orthopaedic provider to enhance other components of the interaction that have been shown to increase satisfaction, such as time spent with the healthcare provider during the visit, expressed empathy, and delineation of clear expectations [4, 11, 12, 17, 22].
Conclusions
Patients with a diagnosis of depression are more likely to report dissatisfaction with their clinical experience in a single orthopaedic outpatient visit. Race, gender, insurance status, and previous visits to the provider are non-modifiable patient factors that potentially affect patient satisfaction with the orthopaedic clinic visit. This knowledge may be used to better understand the drivers of patient satisfaction in an outpatient visit. Providers can and should screen for depression in their clinic visits on intake to identify a high-risk population. After identifying depression, providers could address the patient’s diagnosis empathetically and offer them a referral to a treating physician such as a primary care provider. Surgeons might ensure that depression is adequately treated before elective surgery. Additionally, knowledge before the clinical encounter that other non-modifiable risk factors could decrease satisfaction may help the provider focus their efforts on other factors known to increase satisfaction. The efficacy of these possible interventions is a relevant area of future research.
Acknowledgements
We thank Adina Stewart BA for her assistance with grammar and gathering of logistical forms.
Footnotes
Each author certifies that neither he or she, nor any member of his or her immediate family, has funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article.
All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research® editors and board members are on file with the publication and can be viewed on request.
Each author certifies that his or her institution waived approval for the human protocol for this investigation and that all investigations were conducted in conformity with ethical principles of research.
This work was performed at the University of Texas Southwestern Medical School, Dallas, TX, USA.
References
- 1.Abtahi AM, Brodke DS, Lawrence BD, Zhang C, Spiker WR. Association between patient-reported measures of psychological distress and patient satisfaction scores after spine surgery. J Bone Joint Surg Am. 2015;97:824-828. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Abtahi AM, Presson AP, Zhang C, Saltzman CL, Tyser AR. Association between orthopaedic outpatient satisfaction and non-modifiable patient factors. J Bone Joint Surg Am . 2015;97:1041-1048. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Batbaatar E, Dorjdagva J, Luvsannyam A, Savino MM, Amneta P. Determinants of patient satisfaction: a systematic review. Perspect Public Health. 2017;137:89-101. [DOI] [PubMed] [Google Scholar]
- 4.Bourdreaux ED, Ary RD, Mandry CV, McCabe B. Determinants of patient satisfaction in a large municipal ED: the role of demographic variables, visit characteristics, and patient perceptions. Am J Emerg Med. 2000;18:394-400. [DOI] [PubMed] [Google Scholar]
- 5.Brander V, Gondek S, Martin E, Stulberg SD. The John Insall Award: pain and depression influence outcome 5 years after knee replacement surgery. Clin Orthop Relat Res . 2007;464:21-26. [DOI] [PubMed] [Google Scholar]
- 6.Bullens PH, van Loon CJ, de Waal Malefijt MC, Laan RF, Veth RP. Patient satisfaction after total knee arthroplasty: a comparison between subjective and objective outcome assessments. J Arthroplasty 2001;16:740–747. [DOI] [PubMed] [Google Scholar]
- 7.Chang JT, Hays RD, Shekelle PG, MacLean CH, Solomon DH, Reuben DB, Roth CP, Kamberg CJ, Adams J, Young RT, Wenger NS. Patients' global ratings of their health care are not associated with the technical quality of their care. Ann Intern Med. 2006;144:665-672. [DOI] [PubMed] [Google Scholar]
- 8.Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitidinal studies: development and validation. J Chronic Dis . 1987;40:373-383. [DOI] [PubMed] [Google Scholar]
- 9.Chughatai M, Patel NK, Gwan CU, Khlopas A, Bonutti PM, Delanois RE, Mont MA. Do Press Ganey scores correlate with total knee arthroplasty-specific outcome questionnaires in postsurgical patients? J Arthroplasty . 2017;32:S109-S112. [DOI] [PubMed] [Google Scholar]
- 10.DiMatteo MR, Lepper HS, Croghan TW. Depression is a risk factor for noncompliance with medical treatment: meta-analysis of the effects of anxiety and depression on patient adherence. Arch Intern Med . 2000;160:2101-2107. [DOI] [PubMed] [Google Scholar]
- 11.Etier BE, Orr SP, Antonetti J, Thomas SB, Theiss SM. Factors impacting Press Ganey patient satisfaction scores in orthopedic surgery spine clinic. Spine J . 2016;16:1285-1289. [DOI] [PubMed] [Google Scholar]
- 12.Hamilton DF, Lane JV, Gaston P, Patton JT, MacDonald D, Simpson AH, Howie CR. What determines patient satisfaction with surgery? A prospective cohort study of 4709 patients following total joint replacement. BMJ Open. 2013;3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Kohring JM, Pelt CE, Anderson MB, Peters CL, Gililland JM. Press Ganey outpatient medical practice survey scores do not correlate with patient-reported outcomes after primary joint arthroplasty. J Arthroplasty. 2018;33:2417-2422. [DOI] [PubMed] [Google Scholar]
- 14.Larson EB, Yao X. Clinical empathy as emotional labor in the patient-physician relationship. JAMA. 2005;293:1100-1106. [DOI] [PubMed] [Google Scholar]
- 15.Lozano Calderon SA, Paiva A, Ring D. Patient satisfaction after open carpal tunnel release correlates with depression. J Hand Surg Am. 2008;33:303-307. [DOI] [PubMed] [Google Scholar]
- 16.Martin L, Presson A, Zhang C, Ray D, Finlayson S, Glasgow R. Association between surgical patient satisfaction and non-modifiable factors. J Surg Res . 2017;214:247-253. [DOI] [PubMed] [Google Scholar]
- 17.Menedez ME, Chen NC, Mudgal CS, Jupiter JB, Ring D. Physician empathy as a driver of hand surgery patient satisfaction. J Hand Surg Am. 2015;40:1860-1865. [DOI] [PubMed] [Google Scholar]
- 18.Mira JJ, Tomas O, Virtudes-Perez M, Nebot C, Rodriguez-Marin J. Predictors of patient satisfaction in surgery. Surgery . 2009;145:546-541. [DOI] [PubMed] [Google Scholar]
- 19.Peskin T, Micklitsch C, Quirk M, Sims H, Primack W. Malpractice, patient satisfaction, and physician-patient communication. JAMA. 1995;274:22. [PubMed] [Google Scholar]
- 20.Press Ganey Associates Inc. About Press Ganey. Available at: http://www.pressganey.com/about. Accessed June 29, 2019.
- 21.Schmocker RK, Cherney Stafford LM, Siy AB, Leverson GE, Winslow ER. Understanding the determinants of patient satisfaction with surgical care using the CAHPS Surgical Care Survey (S-CAHPS). Surgery. 2015;158:1272-1233. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Schoenfelder T, Klewer J, Kugler J. Factors associated with patient satisfaction in surgery: the role of patient’s perceptions of received care, visit characteristics, and demographic variables. J Surg Res. 2010;164:53-59. [DOI] [PubMed] [Google Scholar]
- 23.Scott CE, Howie CR, MacDonald D, Biant LC. Predicting dissatisfaction following total knee replacement: a prospective study of 1217 patients. J Bone Joint Surg Br. 2010;92:1253-1258. [DOI] [PubMed] [Google Scholar]
- 24.Shaterian A, Gandy J, Lalezari S, Smith S, Paydar K. Patient race and provider predict patient satisfaction following post-mastectomy breast reconstruction. World J Plast Surg. 2016;5:114-123. [PMC free article] [PubMed] [Google Scholar]
- 25.Sinikallio S, Aalto T, Airaksinen O, Hemo A, Kroger H, Savolainen S, Turunen V, Vinamaki H. Depression is associated with poorer outcome of lumbar spinal stenosis surgery. Eur Spine J. 2007;16:905-912. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Sun BC, Adams J, Orav EJ, Rucker DW, Brennan TA, Burstin HR. Determinants of patient satisfaction and willingness to return with emergency care. Ann Emerg Med. 2000;35:426-434. [PubMed] [Google Scholar]
- 27.Tyser AR, Abtahi AM, McFadden M, Presson AP. Evidence of nonresponse bias in the Press-Ganey patient satisfaction survey. BMC Health Serv Res . 2016;16:350. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Van Buuren S. Multiple imputation of discrete and continuous data by fully conditional specification. Stat Methods Med Res. 2007;16:219-242. [DOI] [PubMed] [Google Scholar]
- 29.Vorhies JS, Weaver MJ, Bishop JA. Admission through the emergency department is an independent risk factor for lower satisfaction with physician performance among orthopaedic surgery patients: a multicenter study. J Am Acad Orthop Surg. 2016;24:735-742. [DOI] [PubMed] [Google Scholar]