NUR-504CLCESRPAINMANAGEMENTARTICLE2.pdf

Journal of Clinical Anesthesia (2016) 34, 661–667

Original Contribution

A temporal analysis of opioid use, patient satisfaction, and pain scores in colorectal surgery patients☆,☆☆

Kamal Maheshwari MD, MPHa,⁎, Kenneth C. Cummings III MD, MSb, Ehab Farag MDb, Natalya Makarova MSc, Alparslan Turan MDa, Andrea Kurz MDa

aDepartment of General Anesthesiology, Department of Outcomes Research, Anesthesiology Institute, Cleveland Clinic, Cleveland, OH bDepartment of General Anesthesiology, Anesthesiology Institute, Cleveland Clinic, Cleveland, OH cDepartment of Outcomes Research, Cleveland Clinic, Cleveland, OH

Received 23 February 2015; revised 22 June 2016; accepted 5 July 2016

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Keywords: Acute pain; Colorectal surgery; Opioids; Patient satisfaction

Abstract Background: Recent health care policy changes promote objective measurements of patient satisfaction with care provided during hospitalization.Acute postsurgical pain is a significantmedical problemand strongly impacts patient experience and patient satisfaction. Multimodal analgesic pathways are used for acute pain management, but opioid medications remain amainstay of treatment.Opioid use is increasing in the outpatient setting, but opioid use trends in the inpatient postsurgical setting are not well known.We hypothesized that use of opioid medications has increased over time along with decrease in postoperative pain scores and increase in pain-related patient satisfaction. Methods: In this single-center study, we studied the trends and correlation in the average daily pain scores, opioid consumption, and patient satisfaction scores as measured by pain-related patient satisfaction questions in the Hospital Consumer Assessment of Healthcare Providers and System survey. Pain scores and opioid use data were obtained from electronic health records, vital signs monitoring, and medication databases. Adult patients who had nonemergent colorectal surgeries between January 2009 and December 2012 were included. Results:We found no significant trend in opioid use or pain-related patient satisfaction scores. There was an average annual increase of 0.3 (98.3% confidence interval, 0.2-0.4; Pb .001) in average daily pain score from 2.8 ± 1.5 to 3.8 ± 1.5. The univariable associations between time-weighted pain score, average daily opioid dose, and pain-related patient satisfaction score were all highly significant. Conclusion: In this retrospective cohort study, opioid use and pain-related patient satisfaction scores were stable over time. Pain-related patient satisfaction scores were negatively associated with both pain score and opioid dose. The associations we report should not be considered evidence of a causal relationship. © 2016 Elsevier Inc. All rights reserved.

☆ Support: departmental. ☆ Departmental attribution: Anesthesiology Institute, Cleveland Clinic, leveland, OH. ⁎ Corresponding author: 9500 Euclid Ave, E-30, Cleveland, OH 44195. E-mail address:[email protected] (K. Maheshwari).

ttp://dx.doi.org/10.1016/j.jclinane.2016.07.005 952-8180/© 2016 Elsevier Inc. All rights reserved.

1. Background

In the past decade, increased use of opioid medication has helped many patients with better management of acute post- surgical pain, but at the same time, problems associated with use of opioids like adverse reactions, tolerance, dependence,

662 K. Maheshwari et al.

and abuse are widespread. In outpatient setting, opioid use and overdose-related deaths have increased substantially from 1999 to 2008 [1,2]. On the other hand, uncontrolled acute postsurgical pain is still a significant problem not only from medical care and outcomes perspectives but also from the pa- tient satisfaction perspective [3].

Patient satisfaction as an outcome is gaining more attention after the Affordable Care Act of 2010, which focuses on increas- ing transparency and accountability in health care. The new law also promotes objective measurements of patient perspectives of health care so that both patients and payers can compare hospitals and make informed decisions. Patients' perception of pain control and the efforts by health care providers to help in their pain control are both important in determining patient satis- faction [4]. Anesthesiologists play an important role in periop- erative pain management and can influence patient satisfaction scores. Although a multimodal approach [3,5] is recommend- ed, opioids remain the mainstay of acute pain management.

Opioid medication usage can lead to better pain control, improved pain scores, and better patient satisfaction metrics. This study, therefore, aimed to test the hypothesis that inpatient opioid use has increased over time among colorectal surgery patients and is associated with decreased pain scores and improved patient satisfaction as measured by pain- related patient satisfaction score in Hospital Consumer Assess- ment of Healthcare Providers and System (HCAHPS) survey.

2. Methods

2.1. Data collection

From the Cleveland Clinic Perioperative Health Documen- tation System and hospital electronic medical record, we ob- tained data for adult patients who had nonemergent colorectal surgeries at theClevelandClinic between January 2009 andDecem- ber 2012. We only included patients that completed the HCAHPS questionnaire. Patients who stayed less than 24 hours in the hospital were excluded. Pain scores are reported in themedical record using a numerical rating scale from 0 to 10 (0 = no pain and 10 = worst pain). Postoperative pain scores are recorded with vital signs at the time of nursing assessment. Oral and parenteral opioid utilization was assessed by using pharmacy data on amount of opioid actually administered to the patient. Opioids were converted to morphine equivalents by using the standard conversion chart.

2.2. HCAHPS survey

The HCAHPS survey is developed by the Agency for Healthcare Research and Quality and the Centers for Medicare and Medicaid Services to provide a standardized and publicly reported tool that allows objective and meaningful compari- sons of hospitals on important quality of care issues [6,7]. The survey is administered to patients after hospital discharge via various valid methods like standard mail, speech-enabled/ interactive voice response, and Web/e-mail.

The pain-related patient satisfaction score was calculated as the percentage of “top-box” responses (“always” response) among nonmissing answers (“always,” usually,” “sometimes,” or “never”) to 2 following pain-related HCAHPS questions: (1) During this hospital stay, how often was your pain well con- trolled? (2) During this hospital stay, how often did the hospital staff do everything they could to help you with your pain? Spe- cifically, if both answers were “always,” a patient will have 100% of “top-box” responses on pain-related HCAHPS ques- tions. If 1 answer was “always,” a patient will have 50% of “top-box” responses on pain-related HCAHPS questions. If none of the answers were “always,” a patient will have 0% of “top-box” responses on pain-related HCAHPS questions. If the answer to a question is missing, the percentage of “top-box” responses is identified based on remaining question only. Thus, possible values for the primary outcome percentage of “top- box” responses on pain-related HCAHPS questions are 0%, 50%, and 100%. Postoperative pain score was defined as the time-weighted pain score per patient (before discharge) [8]. Time-weighted average pain score for a patient is the sum of the pain scores multiplied by the proportion of the time a patient experienced that pain out of total considered time.

2.3. Primary analysis

There were 3 primary outcomes: (1) postoperative daily opi- oid dose: we used log-transformed postoperative daily opioid dose for modeling purposes; (2) postoperative pain scores; and (3) pain-related patient satisfaction score. To analyze the trend in postoperative daily opioid dose and pain score, we built two separate linear regression models to assess the association be- tween year of surgery and the 2 outcome variables. We used log-transformed daily opioid dose as an outcome to meet the model assumption of normality. Because the percentage of “top- box” responses on pain-related HCAHPS questions, pain-related patient satisfaction score only had 3 possible outcomes (0%, 50%, or 100%), the association between year of surgery and the pain-related patient satisfaction scorewas evaluated using a propor- tional odds model. All models were adjusted for the prespecified demographic, baseline andperioperativevariables listed inTable 1. The predictor variable of interest, year of surgery, was treated as a continuous variable because we assumed that there was a trend in the primary outcomes. Bonferroni correction was used to adjust for multiple comparisons. Thus, 98.3% confidence intervals (CIs) were reported, and significance criterion was Pb .017 (ie, .05/3).

In addition, we separately plotted the three outcome vari- ables on the aggregate level (average across patients) over time for information purposes.

2.4. Secondary analysis

The association between the three primary outcome vari- ables was assessed using Spearman correlation. As a post hoc analysis, we summarized the demographics, medical

Table 1 Demographics, medical history, and perioperative parameters for the cohort of patients (n = 943 patients with pain-related patient satisfaction scores)

Variable Year 2009 (n = 227)

Year 2010 (n = 265)

Year 2011 (n = 218)

Year 2012 (n = 233)

P ⁎ Total HCAHPS patients (n = 943)

Total not HCAHPS patients (n = 4123)

Demographics Age (y) 54 ± 17 54 ± 16 53 ± 16 54 ± 16 .85 54 ± 16 53 ± 17 Female (%) 56 50 52 53 .65 53 51 White (%) 94 95 95 94 .81 95 87 Body mass index a (kg/m2) 26 [22, 31] 27 [23, 30] 25 [22, 29] 26 [23, 30] .06 26 [23, 30] 26 [23, 30] Graduated from high school b (%)

97 97 97 97 .97 97 NA †

Graduated from college b (%)

36 40 33 40 .42 37 NA †

Median household income c (K$)

49,2 [41,8, 62,1]

49,4 [42,3, 61,9]

51,0 [43,3, 65,2]

49,7 [43,0, 61,4]

.50 49,7 [42,6, 62,5]

48,9 [41,7, 64,1]

ASA physical status .05 I (%) 1 2 1 0 1 1 II (%) 56 48 46 41 48 46 III (%) 41 45 50 55 48 46 IV (%) 2 5 3 3 3 6

Medical history Diabetes (%) 11 10 11 11 .99 10 13 Hypertension (%) 32 33 32 36 .66 33 36 Coronary artery disease (%) 7 9 8 8 .88 8 11 Congestive heart failure (%) 4 4 4 4 .97 4 5 Chronic pain (%) 1 2 1 6 b.001 2 3 Preoperative narcotic use (%)

39 37 39 35 .82 37 43

Perioperative parameters Use of regional anesthesia (%)

7 7 9 7 .84 7 7

Duration of surgery (min) 244 [189, 337]

244 [194, 330]

253 [191, 326]

240 [192, 319]

.98 248 [191, 326]

252 [192, 326]

Intraoperative opioid dose ‡ (mg)

27 ± 13 31 ± 14 32 ± 14 28 ± 12 .004 30 ± 13 32 ± 15

Length of hospital stay (d) 7 [5, 9] 7 [5, 9] 7 [5, 9] 6 [6, 8] .38 6 [5, 9] 7 [5, 10] Primary surgical procedures Small to large bowel (%) 26 18 22 30 .18 24 19 Anal anastomosis (%) 19 26 22 20 22 18 Sigmoidectomy (%) 12 12 9 12 11 12 Lg-to-lg bowel anastom (%) 11 5 6 10 8 7 Right hemicolectomy (%) 10 7 9 6 8 9 Part lg bowel excis (%) 6 8 10 5 7 9 Lg bowel exteriorization (%) 3 3 4 1 3 3 Colostomy nos (%) 3 5 4 7 5 5 Left hemicolectomy (%) 2 3 3 3 2 2 Suture lg bowel lacerat (%) 2 2 3 1 2 2 Cecectomy (%) 1 3 2 3 2 2 Sm bowel-rect stump anas (%) 1 4 2 1 2 2

Data are presented as percentage of patients, mean ± SD, or median [Q1, Q3], respectively. Number of missing: a = 15, b = 14, c = 7, d = 3, e = 2.

⁎ P values were derived from Pearson χ2 test, ANOVA, and Kruskal-Wallis test, as appropriate; test if at least 1 measure is different comparing 4 years. † Information was not collected. ‡ Intraoperative and post-anesthesia care unit (PACU) opioid dose has been converted to morphine (intravenous) equivalent dose. List of opioids includes

alfentanil, codeine, fentanyl, hydrocodone, hydromorphone, meperidine, methadone, morphine, oxycodone, propoxyphene, remifentanil, tramadol, oxymor- phone, buprenorphine, nalbuphine, and tapentadol.

663Opioid use and patient satisfaction

664 K. Maheshwari et al.

history, and relevant perioperative characteristics for the pa- tients who refused to participate in the HCAHPS survey. We also estimated associations listed for the primary and second- ary analyses except analyses related to the pain-related patient satisfaction scores.

2.5. Sample size considerations

With 943 patients and an overall .05 significance level, we have more than 90% power to detect a correlation of 0.12 or greater between the outcome and the predictor assuming a null correlation of zero. SAS software version 9.3 (SAS Institute, Cary, NC) was used for all analyses.

3. Results

We included 943 adult patients who had nonemergent colo- rectal surgery at the Cleveland Clinic between January 2009 and December 2012 and completed HCAHPS survey. All pa- tients received general anesthesia, with 69 (7%) also having additional regional anesthesia. Table 1 summarizes the demo- graphics, medical history, and relevant perioperative charac- teristics for the cohort of patients.

3.1. Primary outcomes

The only significant association between year of surgery and primary outcome was detected in postoperative pain score with an estimated average annual increase of 0.3 (98.3% CI, 0.2-0.4; Pb .001; significance criterion was Pb .017) unit. However, no significant trend was found in postoperative opioid consumption (P= .68) and pain-related patient satisfac- tion score (P= .93). The estimated ratio of medians of opioid consumption was 0.98 (98.3% CI, 0.88-1.08) for 1-year increase (Table 2). The odds ratio of obtaining a higher pain- related patient satisfaction score next year comparing with current year was 1.01 (98.3% CI, 0.87-1.17) (Table 2). Figs. 1, 2, and 3, respectively, presented the three primary outcomes on the aggregate level (averaging across all patients). Common surgical procedures included in the study are listed in Table 4.

3.2. Secondary outcomes

The univariate associations between time-weighted pain score, average daily opioid dose, and pain-related patient satisfaction were all significant (Table 3). The corresponding Spearman correlation was 0.18 (98.75% CI, 0.10-0.26; Pb .001) between pain score and opioid dose, −0.20 (98.75% CI, −0.28 to −0.12; Pb .001) between pain score and pain-related patient satisfaction score, and −0.15 (98.75% CI, −0.23 to −0.07; Pb .001) between opioid dose and pain-related patient satisfaction score. In other words,

pain-related patient satisfaction score was negatively associat- ed with both pain score and opioid dose.

There were 4123 patients eligible for the study but did not participate in the HCAHPS survey. These patients were less likely to be female and white, had a bit lower income, had more extensive medical history, received more opioids intra- operatively, and appeared to stay slightly longer in the hospital (Table 1). The trends of postoperative opioid use and pain scores in patients who did not participate in the HCAHPS sur- vey reported in Table 2 an association between opioid use and pain is reported in Table 3.

4. Discussion

In this retrospective cohort study, opioid use and pain- related patient satisfaction score did not increase in colorectal surgery inpatients. These results were contrary to our hypoth- esis and could be explained by multiple factors. First, pain in- tensity and opioid administration during the hospital admission are relatively similar for particular surgical proce- dures over time. Second, the need for opioids in an acute pain setting is almost always present, and new medications or strat- egies for pain management are not widely available. Third, we only used the pain management domain of HCAHPS scores for our calculation and did not calculate or study the composite HCAHPS scores, which may show a different trend. Fourth, the response rate of HCAHPS surveys was low (20% in this patient population) compared with an approximately 30% response rate reported elsewhere [9]. If more patients were in- cluded, our results might be different. Finally, we only studied one patient population (colorectal surgery), and the trends of primary outcomes may be different in other patient popula- tions.We did find that the average daily pain score significant- ly increased over the study period, but this may not be a clinically significant difference. This could also be due to the Hawthorne effect, as more emphasis is given to pain assess- ment and health care providers are asking and recording pain scores more frequently.

We used numeric rating scale for pain assessment, which is a valid unidimensional scale that is commonly used in clinical practice because they are easy to administer and change in pain intensity over time can be easily assessed. However, pain as- sessment is subjective and fraught with many challenges in various clinical settings. In measurement of acute pain, pain severity both at rest and during motion is important and is a function of physical discomfort and postoperative complica- tions, respectively [10]. But in our database, we had pain scores recorded without any additional information.

We used pain-related questions from HCAHPS survey to assess pain-related patient satisfaction. Measuring and ad- dressing patient satisfaction are also crucial for Value-Based Purchasing (VBP) programs [6,11]. In the VBP program, up to 1.5% of the total Medicare and Medicaid reimbursement is determined by performance on the quality measures. The

Table 2 Association between 3 primary outcomes and year of surgery (n = 943 patients with HCAHPS scores)

Outcomes Year 2009 (n = 227)

Year 2010 (n = 265)

Year 2011 (n = 218)

Year 2012 (n = 233)

Estimate (98.3% CI)

P ⁎

Pain score 2.8 ± 1.5 3.2 ± 1.4 3.6 ± 1.6 3.8 ± 1.5 0.3 (0.2-0.4) § b.001 Daily opioid dose ‖ (morphine iv mg) 3.7 [1.2, 11.1] 3.6 [1.5, 9.0] 4.0 [1.5, 9.5] 3.9 [1.5, 8.2] 0.98 (0.88-1.08) † .68 Pain-related (HCAHPS) patient satisfaction: % of “always” responses ¶

1.01 (0.87-1.17) ‡ .93

0% (n) 18 19 17 16 50% (n) 20 22 22 25 100% (n) 62 59 62 59 Pain “always” controlled during admission a (%)

63% 60% 63% 62%

Staff “always” did everything they could to relieve pain b (%)

81% 80% 83% 82%

Patients who refused to participate in HCAHPS survey (n = 4123)

Pain score 3.0 ± 1.7 3.4 ± 1.8 3.4 ± 1.8 3.7 ± 1.9 0.15 (0.12-0.19) § b.001 Daily opioid dose ‖ 5.2 [1.7, 20.2] 4.8 [1.6, 17.8] 4.2 [1.3, 10.8] 5.0 [1.6, 12.2] 0.91 (0.88-0.93) † b.001

To analyze the trend over the years for pain score and postoperative opioid dose, we built 2 separate regression models. We used log-transformed daily opioid dose as an outcome to meet the model assumption of normality.P value on pain score assessed if there was a significant trend in pain score over the years.P value on daily opioid dose assessed if ratio of medians was different from one. The association between year of surgery and the HCAHPS score was evaluated using a proportional odds model. All models were adjusted for the prespecified potential confounders listed in Table 1. Data are presented as number of patients, percentage of patients, mean ± SD, or median [Q1, Q3], respectively. Number of missing: a = 3, b = 2.

⁎ Significance criterion was Pb .017. † Ratio of medians (98.3% CI). ‡ Odds ratio (98.3% CI). § Slope (rate) (98.3% CI). ‖ Opioid dose has been converted to morphine (intravenous) equivalent dose (mg) per day. List of opioids includes alfentanil, codeine, fentanyl, hydrocodone,

hydromorphone, meperidine, methadone, morphine, oxycodone, propoxyphene, remifentanil, tramadol, oxymorphone, buprenorphine, nalbuphine, and tapentadol. ¶ Percentage of “always” response was calculated based on nonmissing answers (“always,” “usually,” “sometimes,” or “never”) to 2 pain-related HCAHPS

questions: (1) During this hospital stay, how often was your pain well controlled? (2) During this hospital stay, how often did the hospital staff do everything they could to help you with your pain? If both of the patient's answers were “always,” a patient will have 100%; if 1 of the patient's answers was “always,” a patient will have 50%; if none of the patient's answers was “always,” a patient will have 0%.

Fig. 1 Trend in average daily pain score across patients from 2009 to 2012 (n = 943). Data were presented as mean ± 1.96* standard error, which descriptively showed 95% CIs.

ig. 2 Trend in postoperative opioid use (morphine IV equivalent per ay) across patients from 2009 to 2012 (n = 943). Data were presented

665Opioid use and patient satisfaction

F d

as mean ± 1.96* standard error, which descriptively showed 95% CIs.

Fig. 3 Trend in pain-related patient satisfaction (from HCAHPS) score across patients from 2009 to 2012 (n = 943). Data were presented as percentage of “always” responses and were calculated based on nonmissing answers to 2 pain-related HCAHPS questions. The results for 2 HCAHPS pain-related questions were presented as mean ± 1.96* standard error, which descriptively showed 95% CIs.

666 K. Maheshwari et al.

VBP score incorporates clinical process of care (70%) and HCAHPS scores (30%). Multiple patient factors affect the re- sponses to these surveys and how patients rate their experiences. One study found that women have a less positive experience compared with men especially in the area of communication about medicines, discharge information, and cleanliness [12]. HCAHPS scores can also vary considerably by patient health status and race/ethnicity and moderately by patient age and ed- ucation status [13]. There is also a regional geographic effect on these satisfaction scores [13-15]. These facts point toward cautious interpretation of the HCAHPS survey results when comparing hospitals with different patient populations.

Table 3 Summary of 4 secondary outcomes (n = 943 patients with pain-related patient satisfaction scores–fromHCAHPS score)

Outcomes Spearman correlation (98.75% CI)

P ⁎

Association between pain score and opioid dose

0.18 (0.10, 0.26) b.001

Association between pain score and pain-related patient satisfaction score

−0.20 (−0.28 to−0.12) b.001

Association between opioid dose and pain-related patient satisfaction score

−0.15 (−0.23 to−0.07) b.001

Patients who did not participate in HCAHPS survey (n = 4123)

Spearman correlation (98.75% CI)

Association between pain score and opioid dose

0.19 (0.15-0.23) b.001

⁎ Significance criterion was Pb .0125.

The limitations of currently available patient-reported out- comes used in this study, namely, HCAHPS and pain scores, should be kept in mind before drawing final conclusions. For example, the Centers for Medicare and Medicaid Services Web site does not recommend the use of HCAHPS scores for intrahospital comparisons but to compare hospitals. Geo- graphical variations, different patient populations, and treat- ment settings can all affect HCAHPS scores. Also, as with any retrospective statistical analysis, our ability to adjust for potential confounding is limited to available data. Consequent- ly, the associations we report should not be considered evi- dence of a causal relationship.

In conclusion, in this single-center study, for adult patients who had nonemergent colorectal surgeries at the Cleveland Clinic between January 2009 and December 2012, we found that the pain-related patient satisfaction score and opioid con- sumption were unchanged. There was a slight annual increase

Table 4 Tenmost common surgical procedures (92% of total) for colorectal patients with HCAHPS scores (total n = 943 patients)

ICD-9 procedure code ICD-9 procedure names n %

45.93 Small-to-large bowel 226 24% 45.95 Anal anastomosis 206 22% 45.76 Sigmoidectomy 105 11% 45.94 Lg-to-lg bowel anastom 76 8% 45.73 Right hemicolectomy 74 8% 45.79 Part lg bowel excis 68 7% 46.10 Colostomy nos 43 5% 46.03 Lg bowel exteriorization 26 3% 45.75 Left hemicolectomy 23 2% 45.72 Cecectomy 22 2%

667Opioid use and patient satisfaction

in average daily pain score. Patient satisfaction scores were negatively associated with both pain score and opioid dose. Further research is needed to devise methods to accurately measure acute pain and improve pain control, and to study the impact of acute pain management on patient satisfaction.

Appendix 1. Opioid conversion chart

Drug

Route

Units

Equivalent dose

Morphine

IV

mg

10

Morphine

Oral

mg

30

Fentanyl

IV

mg

0.1

Fentanyl

IV

μg

100

Fentanyl

Patch

mg

0.1

Fentanyl

Patch

μg

100

Fentanyl

Epidural PCA

mg

0.1

Fentanyl

Oral

mg

0.229

Fentanyl

Oral

μg

229

Alfentanil

IV

mg

0.67

Meperidine

IV

mg

75

Meperidine

Oral

mg

333

Demerol

IV

mg

75

Oxycodone

Oral

mg

20

Percocet

Oral

mg

20

Percocet 5/325

Oral

tabs

6

Darvocet

Oral

tabs

1

Propoxyphene

Oral

tabs

1

Oxycontin

Oral

mg

20

Hydrocodone

Oral

mg

30

Vicodin 5/500

Oral

tabs

6

Vicodin 7.5/500

Oral

tabs

4

Tramadol

Oral

mg

150

Hydromorphone

IV

mg

1.5

Hydromorphone

Oral

mg

7

Dilaudid

IV

mg

1.5

Dilaudid

Oral

mg

7

Remifentanil

IV

mg

0.1

Sufentanil

IV

mg

0.01

Methadone

Oral

mg

20

Codeine

Oral

mg

200

IV = intravenous.

References

[1] Centers for Disease C. Prevention: vital signs: overdoses of prescription opioid pain relievers—United States, 1999-2008. MMWRMorb Mortal Wkly Rep 2011;60:1487-92.

[2] Manchikanti L, Singh A. Therapeutic opioids: a ten-year perspective on the complexities and complications of the escalating use, abuse, and non- medical use of opioids. Pain Physician 2008;11:S63-88.

[3] Benhamou D, Berti M, Brodner G, De Andres J, Draisci G, Moreno- Azcoita M, et al. Postoperative analgesic THerapy observational survey (PATHOS): a practice pattern study in 7 central/southern European countries. Pain 2008;136:134-41.

[4] Hanna MN, Gonzalez-Fernandez M, Barrett AD, Williams KA, Prono- vost P. Does patient perception of pain control affect patient satisfaction across surgical units in a tertiary teaching hospital? Am J Med Qual 2012;27:411-6.

[5] Practice guidelines for acute pain management in the perioperative set- ting: an updated report by the American Society of Anesthesiologists Task Force on Acute Pain ManagementAnesthesiology 2012;116: 248-73.

[6] Hospitalcompare: the official U.S. Government site for Medicare. Pa- tients' survey; 2013.

[7] Goldstein E, Farquhar M, Crofton C, Darby C, Garfinkel S. Measuring hospital care from the patients' perspective: an overview of the CAHPS hospital survey development process. Health Serv Res 2005; 40:1977-95.

[8] Turan A, Atim A, Dalton JE, Keeyapaj W, Chu W, Bernstein E, et al. Preoperative angiotensin-converting enzyme inhibitor use is not associat- ed with increased postoperative pain and opioid use. Clin J Pain 2013;29: 1050-6.

[9] Siddiqui ZK, Wu AW, Kurbanova N, Qayyum R. Comparison of hospital consumer assessment of healthcare providers and systems patient satisfaction scores for specialty hospitals and general medical hospitals: confounding effect of survey response rate. J Hosp Med 2014;9:590-3.

[10] Breivik H, Borchgrevink PC, Allen SM, Rosseland LA, Romundstad L, Hals EK, et al. Assessment of pain. Br J Anaesth 2008;101:17-24.

[11] CMS: the official website for theMedicare hospital value-based purchas- ing program; 2015.

[12] Elliott MN, Lehrman WG, Beckett MK, Goldstein E, Hambarsoomian K, Giordano LA. Gender differences in patients' perceptions of inpatient care. Health Serv Res 2012;47:1482-501.

[13] Elliott MN, Lehrman WG, Goldstein E, Hambarsoomian K, Beckett MK, Giordano LA. Do hospitals rank differently on HCAHPS for differ- ent patient subgroups? Med Care Res Rev 2010;67:56-73.

[14] Elliott MN, Zaslavsky AM, Goldstein E, Lehrman W, Hambarsoomians K, Beckett MK, et al. Effects of survey mode, patient mix, and nonre- sponse on CAHPS hospital survey scores. Health Serv Res 2009;44: 501-18.

[15] Tighe PJ, Fillingim RB, Hurley RW. Geospatial analysis of hospital con- sumer assessment of healthcare providers and systems pain management experience scores in U.S. hospitals. Pain 2014;155:1016-26.

  • A temporal analysis of opioid use, patient satisfaction, and pain scores in colorectal surgery’patients
    • 1. Background
    • 2. Methods
      • 2.1. Data collection
      • 2.2. HCAHPS survey
      • 2.3. Primary analysis
      • 2.4. Secondary analysis
      • 2.5. Sample size considerations
    • 3. Results
      • 3.1. Primary outcomes
      • 3.2. Secondary outcomes
    • 4. Discussion
    • Appendix 1. Opioid conversion chart
    • References