INTRODUCTION
Patient expectations for surgical recovery are informed by perceptions of the impact of surgery on health outcomes that matter to them.1 2
Patient expectations for postoperative HRQL may reflect the quality of shared decision-making between patients and surgeons.3 4 5
The purpose of this study was twofold. First was to determine preoperative expectations of postoperative HRQL among patients undergoing cancer surgery; and the second was to measure and compare experienced HRQL throughout postoperative recovery with patients’ preoperative expectations. We hypothesized that patient expectations of postoperative HRQL would be poorly aligned with experiences during recovery. If so, these data would underscore the importance of measuring patients’ recovery expectations and supporting shared decision-making to more effectively align these expectations with lived experiences following cancer surgery.
METHODS
Patient Recruitment
The study protocol was approved by the Human Research Committee Institutional Review Board. Eligible patients included adult (≥18 years) patients scheduled to undergo operations for breast, skin/soft-tissue (eg, wide local excision of melanoma and lymphadenectomy), head and neck (eg, thyroidectomy and parathyroidectomy), or abdominal tumors from a single academic cancer center (July 2017–July 2019). Patients were approached for enrollment following consultation with their surgeon, approximately 1 week before surgery. Consenting patients were instructed to download the Beiwe smartphone application, the user-facing component of a platform designed and previously used by our team for smartphone-based digital phenotyping research in surgical patients.6–8
At the time of enrollment, patients’ electronic health records were reviewed for the following demographics and disease characteristics: age, self-reported gender, self-reported race and ethnicity, body mass index (BMI, kg/m2 ), and cancer/treatment information (eg, neoadjuvant chemotherapy or radiation within 6 months of surgery, surgical pathology, and adjuvant treatment). During the 6-month study period, the electronic health records were periodically reviewed for perioperative details (eg, operative time, blood loss, postoperative morbidity, discharge disposition, and follow-up visits). All data were securely stored in Research Electronic Data Capture (REDCap).9
Measurement of Expected and Experienced HRQL
At the time of enrollment, patients were electronically sent a survey via the Beiwe smartphone application to assess expectations for postoperative HRQL during recovery. Given the lack of psychometrically validated instruments to assess patient expectations longitudinally during perioperative care,1 10–12 https://links.lww.com/AOSO/A26
In addition to the preoperative expectations survey, patients were also electronically sent the SF36 survey via the Beiwe application at enrollment and at 1, 3, and 6 months after surgery to assess experienced HRQL during recovery. The SF36 has been used to assess longitudinal HRQL, including among patients undergoing elective cancer operations, and is sensitive to changes in each of the 8 health domains following surgery.13
The primary endpoint in this study was to measure differences in trends of expected versus experienced HRQL among patients undergoing operations for cancer as measured by surveys delivered remotely through a smartphone platform.
Data Management and Statistical Analysis
All survey responses were encrypted and stored in compliance with the Health Insurance Portability and Accountability Act. Baseline patient demographics and clinical outcomes data were summarized using means and SDs for continuous measures, or frequencies for categorical data. To measure differences in characteristics among survey responders and nonresponders, bivariate analyses using two-sample Student t -tests, Wilcoxon tests, Chi-squared tests, and Fisher exact tests were performed. Completion rates for the preoperative expectations and postoperative SF36 surveys were determined using the American Association for Public Opinion Research Standard Definitions Report.14
To compare trends in expected versus experienced HRQL, correlation of 1- to 6-month observed differences in responses to the preoperative expectations and postoperative SF36 surveys were performed. Correlations were summarized using Spearman’s correlation coefficients for nonnormally distributed data, where correlations ≤±0.4 were considered poor, ±0.4 to 0.7 considered moderate, and ≥±0.8 considered strong.15 , 16
RESULTS
Study Population
Among 101 patients who consented to participate, 74 completed both the preoperative expectations and SF36 surveys (73% completion rate, Fig. 1 ). Among these patients, the mean age was 54 years (SD 14), 49 (66%) were female, and the most common operations were performed for breast (34%) and abdominal (31%) tumors. Additional demographics, disease factors, operative details, postoperative outcomes, and adjuvant treatment details are shown in Table 1 .
TABLE 1. -
Characteristics of Included Patients
N = 74
Demographics and disease factors
Age (y, mean, SD)
53.9 (13.9)
Female (n, %)
49 (66.2)
Race and ethnicity (n, %)
Non-Hispanic White
64 (86.5)
Non-Hispanic Black
2 (2.7)
Hispanic
2 (2.7)
Asian
1 (1.3)
Other
2 (2.7)
Unknown
3 (4.1)
BMI (kg/m2 , mean, SD)
27.8 (5.8)
Smartphone operating system (n, %)
iPhone
61 (82.4)
Android
13 (17.6)
Tumor primary site (n, %)
Breast
25 (33.8)
Head and neck
11 (14.9)
Abdominal
23 (31.1)
Skin/soft tissue
15 (20.3)
Neoadjuvant treatment (n, %)
Chemotherapy
16 (21.6)
Radiation
8 (10.8)
Operative details and postoperative outcomes
ASA classification* (mean, SD)
2.1 (0.5)
Operative time (min, mean, SD)
160.9 (133.1)
Blood loss* (mL, mean, SD)
120.2 (236.6)
Length of stay (d, mean, SD)
2.7 (3.1)
Discharge with home services (n, %)
27 (36.5)
Postoperative morbidity (n, %)
12 (16.2)
Readmission (n, %)
9 (12.2)
Return to operating room (n, %)
14 (18.9)
Adjuvant treatment (n, %)
Chemotherapy
12 (16.2)
Radiation
13 (17.6)
Immunotherapy
6 (8.1)
Number of follow-up visits with surgeon* (mean, SD)
2.2 (2.4)
Number of follow-up visits with any provider (mean, SD)
7.8 (6.0)
*ASA and number of follow-up visits recorded for 73/74 patients. Blood loss recorded for 62/74 patients.
ASA indicates American Society of Anesthesiology.
FIGURE 1.: Flow diagram showing recruitment and reasons for data exclusion among participating patients. Only surveys completed within one week of the scheduled date and with ≥75% completion were included.
There were no differences in baseline characteristics and disease factors comparing the 74 patients who completed the preoperative expectations and SF36 surveys versus noncompleters (Table 2 ). During the postoperative study period, there were 42 (42%) patients who completed the SF36 at 1 month after surgery; 33 (33%) patients at 3 months after surgery; and 24 (24%) patients at 6 months after surgery. The demographics, disease factors, operative details, and postoperative outcomes of patients at each time during the postoperative study period are summarized in Table 3 .
TABLE 2. -
Preoperative Survey Completers Versus Noncompleters
Completers (n = 74)
Noncompleters (n = 27)
P
Demographics and disease factors
Age (y, mean, SD)
53.9 (13.9)
48.9 (10.5)
0.092
Female (n, %)
49 (66.2)
18 (66.7)
0.966
Race and ethnicity (n, %)
Non-Hispanic White
64 (86.5)
23 (85.2)
0.937
Non-Hispanic Black
2 (2.7)
1 (3.7)
Hispanic
2 (2.7)
1 (3.7)
Asian
1 (1.3)
1 (3.7)
Other
2 (2.7)
0 (0.0)
Unknown
3 (4.1)
1 (3.7)
BMI (kg/m2 , mean, SD)
27.8 (5.8)
26.2 (5.5)
0.186
Smartphone operating system (n, %)
iPhone
61 (82.4)
22 (81.5)
0.771
Android
13 (17.6)
5 (18.5)
Tumor primary site (n, %)
Breast
25 (33.8)
9 (33.3)
0.930
Head and neck
11 (14.9)
3 (11.1)
Abdominal
23 (31.1)
10 (37.0)
Skin/soft tissue
15 (20.3)
5 (18.5)
Neoadjuvant treatment (n, %)
Chemotherapy
16 (21.6)
8 (29.6)
0.403
Radiation
8 (10.8)
4 (14.8)
0.729
Demographics, disease factors, operative details, and postoperative outcomes among completers versus noncompleters of preoperative surveys.
ASA indicates American Society of Anesthesiology; BMI, body mass index.
TABLE 3. -
Characteristics of Survey Completers During the Study Period
Preoperative (n=74)
Postoperative
Month 1(n=42)
Month 3(n=33)
Month 6(n=24)
Demographics and disease factors
Age (y, mean, SD)
53.9 (13.9)
53.6 (11.8)
58.0 (9.4)
59.7 (9.7)
Female (n, %)
49 (66.2)
30 (71.4)
23 (69.7)
16 (66.7)
Race and ethnicity (n, %)
Non-Hispanic White
64 (86.5)
41 (97.6)
33 (100.0)
23 (95.8)
Non-Hispanic Black
2 (2.7)
0 (0.0)
0 (0.0)
0 (0.0)
Hispanic
2 (2.7)
0 (0.0)
0 (0.0)
0 (0.0)
Asian
1 (1.3)
0 (0.0)
0 (0.0)
0 (0.0)
Other
2 (2.7)
0 (0.0)
0 (0.0)
0 (0.0)
Unknown
3 (4.1)
1 (2.4)
0 (0.0)
1 (4.2)
BMI (kg/m2 , mean, SD)
27.8 (5.8)
26.6 (5.6)
27.0 (5.5)
26.0 (5.9)
Smartphone operating system (n, %)
iPhone
61 (82.4)
42 (100)
32 (97.0)
23 (95.8)
Android
13 (17.6)
0 (0.0)
1 (3.0)
1 (4.2)
Tumor primary site (n, %)
Breast
25 (33.8)
18 (42.9)
13 (39.4)
9 (37.5)
Head and neck
11 (14.9)
6 (14.3)
5 (15.1)
6 (25.0)
Abdominal
23 (31.1)
12 (28.6)
9 (27.3)
6 (25.0)
Skin/soft tissue
15 (20.3)
6 (14.3)
6 (18.2)
3 (12.5)
Neoadjuvant treatment (n, %)
Chemotherapy
16 (21.6)
9 (21.4)
6 (18.2)
6 (25.0)
Radiation
8 (10.8)
3 (7.1)
3 (9.1)
3 (12.5)
Operative details and postoperative outcomes
ASA classification* (mean, SD)
2.1 (0.5)
2.0 (0.5)
2.1 (0.4)
2.1 (0.5)
Operative time (min, mean, SD)
160.9 (133.1)
157.3 (141.6)
160.1 (134.9)
177.7 (147.1)
Blood loss* (mL, mean, SD)
120.2 (236.6)
109.6 (248.9)
119.8 (276.8)
137.6 (307.6)
Length of stay (d, mean, SD)
2.7 (3.1)
3.0 (3.1)
3.2 (3.3)
3.2 (2.9)
Discharge with home services (n, %)
27 (36.5)
18 (42.9)
16 (48.5)
14 (58.3)
Postoperative morbidity (n, %)
12 (16.2)
6 (14.3)
5 (15.1)
6 (25.0)
Readmission (n, %)
9 (12.2)
4 (9.5)
2 (6.1)
3 (12.5)
Return to operating room (n, %)
14 (18.9)
9 (21.4)
7 (21.2)
5 (20.8)
Follow-up visits: surgeon* (mean, SD)
2.2 (2.4)
2.2 (2.8)
2.3 (2.9)
2.9 (3.2)
Follow-up visits: any provider (mean, SD)
7.8 (6.0)
9.1 (6.4)
8.0 (5.3)
8.7 (5.5)
*ASA and number of follow-up visits recorded for 73/74 participants preoperatively and 41/42 responders at postoperative month 1; blood loss for 62/74 participants preoperatively, 37/42 participants at postoperative month 1, 29/33 participants at postoperative month 3, and 21/24 participants at postoperative month 6.
ASA indicates American Society of Anesthesiology; BMI, body mass index.
Expected and Experienced HRQL
Figure 2 shows the results of the expectations and SF36 surveys summarizing patients’ expected and experienced HRQL, respectively, in each of the 8 SF36 health domains. Across all health domains, patients seemed to expect that their HRQL would worsen compared with their preoperative baseline at 1 week postoperatively and then improve steadily during recovery toward minimal disability by the end of the 6-month study period. Comparing preoperative expected versus experienced HRQL as measured by the results of the SF36 at months 1, 3, and 6 postoperatively, there was poor correlation of 1- to 6-month trends in 6 of the 8 health domains (eg, general health domain: correlation coefficient −0.15, 95% confidence interval [CI] [−0.48 to 0.18], P = 0.369, Table 4 ). There was moderate correlation in trends of expected and experienced HRQL only in the physical functioning (correlation coefficient 0.50, 95% CI [0.22–0.78], P < 0.001) and physical role limitations domains (correlation coefficient 0.41, 95% CI [0.05–0.77], P = 0.024). The results of the sensitivity analysis to assess for bias due to missing data (eg, nonresponders to the postoperative SF36 surveys) are shown in Table 5 . There were no significant differences in observed versus predicted HRQL at 1, 3, and 6 months postoperatively (eg, 6-month observed vs predicted general health domain scores: 61.3, 95% CI [52.2–70.3] vs 61.4, 95% CI [55.6–67.3]).
TABLE 4. -
Correlation of Trends in Expected Versus Experienced HRQL Spearman correlation coefficients for 1- to 6-month differences in expected versus experienced HRQL by health domain.
Health Domain
Correlation Coefficient [95% CI]
P
General health
−0.15 [−0.48 to 0.18]
0.369
Bodily pain
0.27 [−0.04 to 0.57]
0.089
Physical functioning
0.50 [0.22 to 0.78]
<0.001
Emotional role limitations
0.17 [−0.21 to 0.55]
0.367
Physical role limitations
0.41 [0.05 to 0.77]
0.024
Social functioning
0.19 [−0.11 to 0.50]
0.216
Vitality
0.21 [−0.16 to 0.57]
0.277
Mental health
0.35 [−0.01 to 0.70]
0.055
Cell values reflect observed and predicted (ie, results from linear mixed model) mean domain scores and 95% CIs.
TABLE 5. -
Observed and predicted HRQL as measured by the SF36 preoperatively and at postoperative months 1, 3, and 6
Health Domain
Preoperative
Postoperative Month 1
Postoperative Month 3
Postoperative Month 6
Observed
Predicted
Observed
Predicted
Observed
Predicted
Observed
Predicted
Vitality
51.6 [45.9–57.4]
51.6 [45.9–57.3]
52.0 [45.2–58.9]
50.8 [44.4–57.3]
58.3 [49.6–67.0]
54.0 [46.4–61.6]
64.0 [55.8–72.1]
58.8 [52.5–65.0]
Social functioning
78.2 [72.6–83.8]
78.2 [72.6–83.8]
78.6 [70.6–86.5]
78.5 [70.9–86.2]
84.1 [76.3–91.9]
81.2 [73.6–88.7]
94.3 [90.8–97.7]
94.1 [90.9–97.3]
Emotional role limitations
59.8 [48.9–70.7]
59.3 [48.4–70.2]
70.6 [57.6–83.7]
65.5 [53.4–77.5]
79.3 [65.4–93.2]
68.6 [56.3–81.0]
81.9 [65.9–98.0]
79.1 [66.0–92.2]
Physical role limitations
64.2 [54.6–73.7]
64.2 [54.7–73.7]
47.6 [33.5–61.8]
47.0 [33.6–60.4]
60.6 [43.9–77.3]
60.7 [45.3–76.1]
63.5 [44.4–82.7]
67.0 [51.6–82.4]
Bodily pain
78.4 [72.2–84.7]
78.4 [72.3–84.6]
69.7 [61.9–77.5]
69.2 [61.6–76.7]
77.2 [71.0–83.5]
76.3 [70.7–82.0]
84.4 [78.9–89.9]
84.5 [79.8–89.2]
Mental health
69.8 [64.8–74.7]
69.8 [64.9–74.7]
73.0 [67.0–78.9]
75.9 [70.7–81.1]
76.1 [69.7–82.5]
75.8 [70.3–81.2]
81.3 [75.9–86.8]
80.8 [76.7–84.9]
Physical functioning
81.4 [75.8–86.9]
81.4 [75.8–86.9]
71.9 [64.1–79.7]
68.2 [60.5–75.9]
78.5 [70.7–86.3]
76.8 [69.9–83.6]
87.5 [79.9–95.0]
84.9 [79.5–90.3]
General health
63.5 [58.2–68.8]
63.5 [58.2–68.8]
59.8 [52.7–66.9]
59.6 [53.2–66.0]
59.2 [51.4–66.9]
62.1 [55.8–68.3]
61.3 [52.2–70.3]
61.4 [55.6–67.3]
FIGURE 2.: Trends in expected versus experienced postoperative HRQL. Observed results from the preoperative expectations (dashed line) and postoperative SF36 surveys (solid line) with 95% CIs provided at each postoperative time point (ie, 1, 3, and 6 months) for the 8 SF36 health domains.
DISCUSSION
In this study, we used smartphone-based surveys to measure and compare the expected and experienced postoperative HRQL among 74 patients undergoing cancer surgery. Across 8 health domains, patients expected HRQL to worsen 1 week after surgery and improve toward minimal disability at 6 months postoperatively. There was poor correlation in trends of expected versus experienced HRQL in all health domains except in constructs related to physical health (eg, physical functioning and physical role limitations), where there was moderate correlation. Patients generally expected better HRQL than what they experienced postoperatively.
Patient Expected Versus Experienced HRQL
Previous research evaluating patient expectations for surgical recovery has focused on associations with postoperative patient satisfaction, disease-specific outcomes, and longitudinal HRQL.17 13 18 13
We observed poor correlation between trends in expected versus experienced HRQL in nearly all health domains, where patients generally expected better HRQL than what they experienced. There are several potential explanations for these findings. Each warrants discussion as misalignment between expectations and experiences place patients at risk for worse satisfaction with treatment, poorer relationships with providers and health systems, and adverse health outcomes.17
First, patients’ recovery expectations represent perceptions of the impact of surgery on postoperative HRQL as informed, in part, by surgeons. Therefore, discordance between expectations and lived experiences may reflect the quality of shared decision-making. Elwyn et al3
Second, it is possible that surgeons communicate more effectively about pathophysiology and operative treatments than the effects of surgery on postoperative HRQL. A substantial body of the prior literature has demonstrated that while surgeons are active in counseling patients, we rarely empathize with patients and infrequently explore or advise them on the potential psychosocial impact of surgical treatment options.19 , 20 4 , 5 , 18 , 21–23
The lack of nuanced data describing the impact of surgery on postoperative psychosocial HRQL underscores the ongoing unmet need to develop and collect longitudinal, patient-centered recovery metrics following cancer surgery. The current implementation of patient-reported outcome measures has prioritized the patient perspective throughout preoperative and postoperative care.2
Measuring Expectations
An important consideration when contextualizing the lack of agreement between trends in expected versus experienced HRQL relates to the method of measuring patient expectations. While postoperative HRQL was assessed using the SF36—an instrument that has been extensively psychometrically evaluated—preoperative expectations of postoperative HRQL were measured using a survey designed for the purposes of this study. This was due to the lack of an available, psychometrically tested instrument during the study period. In a systematic review of 60 studies on patient expectations for surgical recovery, Waljee et al17 1 24
Limitations
The findings of this study must be interpreted in the context of the following important limitations. First, this was a relatively small and heterogenous patient population including those undergoing surgery for breast, skin/soft tissue, head and neck, and abdominal tumors. As such, we were unable to perform additional sensitivity analysis to explore the lack of concordance between expected and experienced HRQL (eg, by type of cancer surgery, postoperative complication, length of stay, or adjuvant treatment). The study population demography was also relatively ethnically homogenous (86.5% non-Hispanic white patients), which may limit the generalizability of our findings. Future work must strive to include more diverse patient populations. The wide ownership and usage of smartphones across social determinants of health underscores the possibility of performing studies with similar methods in a more generalizable patient population. A second limitation is that preoperative and postoperative HRQL were assessed using the SF36 rather than disease-, treatment-, and cancer-specific HRQL instruments. We chose a generic health instrument as it applied to a heterogenous sample of patients regardless of differences in individual treatment plans. This minimized the burden associated with completing multiple surveys. Third, despite the relatively high completion rate of the preoperative surveys, there was loss to follow up when assessing experienced HRQL at 1, 3, and 6 months postoperatively. However, there were no significant differences in the characteristics of survey completers versus noncompleters at baseline, and the results of the sensitivity analysis comparing observed versus predicted postoperative HRQL demonstrated similar findings. While this suggests that there was minimal bias due to non-response to the postoperative SF36, there may be additional, unmeasured sources of bias in these trends of postoperative HRQL. Fourth, while we contextualized postoperative HRQL in terms of patients’ expectations, we did not assess surgeon expectations, which would allow us to comment on the effectiveness of shared decision-making. Subsequent studies will incorporate not only patient expectations for HRQL, but also the perspectives of surgeons and caregivers.
Last, there are several limitations of the survey to measure preoperative expectations of postoperative HRQL, which was designed for this study. The survey was not previously validated, although it did appear to have face validity when reviewed by experts in surgical oncology, psychometrics, and survey methodology. Furthermore, the survey captured expectations in terms of general HRQL, but did not collect information on oncologic expectations (eg, being cancer free). Patients may have answered the postoperative SF36 differently based on the oncologic outcome of their treatment. While this study’s results are significant for finding that preoperative expectations of postoperative HRQL correlated poorly with lived experiences, future studies can consider the underlying reasons for this finding, which may include misalignment of oncologic expectations.
CONCLUSION
Patients experienced HRQL outcomes following cancer surgery which were poorly correlated with preoperative expectations. Recognizing that patient expectations reflect, in part, the information provided by surgical care teams, the results of this study underscore the need to strive for greater concordance between expected and experienced postoperative HRQL. Failing to do so may result in poorer patient satisfaction, patient–provider relationships, and overall health outcomes. There is an opportunity for surgeons to contribute to the development and implementation of tools to capture expected HRQL outcomes among patients, and use these data to strengthen shared decision-making prior to surgery.
ACKNOWLEDGMENTS
N.P. and I.S. contributed equally as first authors. C.E.C. and A.B.H. contributed equally as senior authors.
N.P., I.S., and A.H. participated in research design, performance of the research, data analysis, contributed to new analytic tools, writing of the paper, critical review of the paper, and approval for submission. B.N. participated in data analysis, contributed to new analytic tools, critical review of the paper, and approval for submission. B.H., S.L., C.L., and C.C. participated in data analysis, contributed to new analytic tools, writing of the paper, critical review of the paper, and approval for submission. C.G., M.B., R.S. participated in data analysis, critical review of the paper, and approval for submission. J.-P.O. participated in research design, performance of the research, critical review of the paper, and approval for submission.
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