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Variation in perioperative opioid use after total joint arthroplasty
∗Corresponding author: Nicholas R. Pagani. npagani@tuftsmedicalcenter.org
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Received: ,
Accepted: ,
This article was originally published by Reed Elsevier India Pvt. Ltd. and was migrated to Scientific Scholar after the change of Publisher.
Abstract
Abstract
We studied variation in perioperative opioid use after total joint arthroplasty with respect to patient and procedure characteristics in order to inform initiatives to optimize pain relief.
We recorded perioperative opioid consumption for a cohort of total joint arthroplasty patients to identify factors underlying variation in perioperative opioid use.
Younger patient age, tobacco use, greater symptoms of depression, private insurance, and knee arthroplasty were associated with increased opioid consumption.
Awareness of the patient characteristics associated with increased perioperative opioid use can help inform implementation of targeted strategies for safe, optimal pain relief and satisfaction.
Keywords
Total joint arthroplasty
Pain
Opioid
Total knee arthroplasty
Total hip arthroplasty
1 Introduction
The United States is in the midst of an iatrogenic and advocatogenic epidemic of prescription opioid addiction and death that has also led to a resurgence in heroin use.1,2 Physicians were advised to use more and stronger opioids for pain relief, prescriptions for opioid analgesics rose,3,4 and now prescription opioids account for over 75% of drug overdose deaths5 and are largely responsible for the rising mortality rate of middle-aged white Americans.6 Opioids are the cornerstone of acute postoperative pain management after total joint arthroplasty (TJA), projected to surpass 4 million procedures annually by 2030.7
Initiatives to optimize value in orthopaedic surgery center, in part, on recovery from hip or knee arthroplasty. One important aspect of recovery from surgery is the tension between two major public health and policy concerns: 1) providing adequate pain relief and 2) ensuring patients and their social circle are exposed to addictive opioid medications as safely as possible.8,9 Recently, the American Academy of Orthopaedic Surgeons released an Information Statement to decrease opioid use, misuse, and abuse in the United States.10 Elective arthroplasty creates relatively uniform nociception, but notably variable pain intensity and opioid use. Efforts to reduce such variation have focused primarily on the technical aspects of care (e.g. epidural analgesia, periarticular multimodal analgesia, minimally invasive surgical approaches, etc.)11–18 rather than on identification of mindset and circumstances that place patients at risk for increased pain intensity and perioperative opioid use.19 Interventions to limit stress and distress and optimize coping strategies might do as much or more to improve pain relief and limit the use of opioids than biomedical interventions.
We studied variation in perioperative opioid use after total hip and total knee arthroplasty with respect to patient and procedure characteristics.
2 Methods
After institutional review board approval and informed consent were obtained, we enrolled 111 patients between March 2015 and May 2015 in this prospective observational study at a large urban academic center in the United States. The surgical schedule was reviewed daily to identify patients who underwent primary unilateral total hip (THA) or knee (TKA) arthroplasty for osteoarthritis. Exclusion criteria were inability to speak English or provide informed consent. To achieve a more homogeneous sample, we also decided a priori to consider only patients who were not taking opioids on a daily basis before surgery (opioid naïve).20 All of the patients approached agreed to participate in the study.
Surgery was performed by 1 of 5 fellowship-trained arthroplasty surgeons. A standard posterolateral (Moore or Southern) approach was used for all THAs, and a standard medial parapatellar approach for all TKAs. All patients received a peri-capsular injection at the time of surgery.
The outcome of interest was the total opioid consumption on the first postoperative day (POD). Opioid data were obtained from nursing records and converted to oral morphine equivalents (OMEs).13,21 An a priori decision was made to assess POD 1 variation in opioid use given that our arthroplasty patients are rarely discharged on that day––in our sample, no patients were discharged on POD 1.
On the first POD, research staff not involved in clinical care asked all patients to complete a sociodemographic survey (e.g. age, sex, race/ethnicity, income, insurance status), the Newest Vital Sign (NVS) health literacy test,22 the Patient Health Questionnaire-2 (PHQ-2) depression instrument,23 and the Pain Catastrophizing Scale (PCS).24 Participants were also asked about tobacco use, pain intensity and satisfaction with pain control (11-point numeric rating scales).
The NVS is a validated 6-item instrument to assess health literacy and numeracy.22,25 It is based on a nutrition label from an ice cream container. The use of an ice cream label is justified by the correlation between poor comprehension of food labels and low health literacy and numeracy skills.26 The overall test score ranges from 0 to 6, with higher scores indicating greater health literacy (Appendix 1).27
The PHQ-2 is an abbreviated version of the PHQ-9 depression instrument.23 It inquires about the frequency of depressed mood and anhedonia over the past 2 weeks. Higher scores represent greater symptoms of depression (Appendix 2).
The PCS measures ineffective coping strategies in response to pain.24 It consists of 13 items evaluated on a 5-point Likert scale from 0 to 4. Higher scores indicate greater pain catastrophizing (Appendix 3).
We reviewed surgeon, anesthesia, and nursing operative reports to collect data on the American Society of Anesthesiologists (ASA) score, body mass index (BMI), anesthesia type (spinal/general), femoral nerve block, use of ketorolac (Toradol), and operative time (time from incision to closure).
2.1 Statistical analysis
An a priori power analysis indicated that a minimum sample size of 111 patients would provide 90% statistical power (α = 0.05) to detect a moderate effect size (f2 = 0.18) in a linear regression model with 7 predictors and postoperative opioid consumption as the dependent variable.
To evaluate the association between each explanatory variable and postoperative opioid consumption, we performed bivariate analyses using Pearson correlation coefficients for continuous variables, independent samples T-tests for dichotomous variables, and analysis of variance for categorical variables.
To minimize confounding, variables with P < 0.05 in bivariate analysis were inserted into multivariable linear regression analysis to determine factors independently associated with variation in postoperative opioid use. All covariates were entered into the model simultaneously, without further selection. Results were presented in OMEs as regression coefficients (β) with 95% confidence intervals (CIs). To better understand the percentage of variation in opioid use explained by each of these variables and by the model as a whole, we also reported the partial R2 and the total R.2 Statistical significance was set at P < 0.05.
2.2 Patient characteristics (Table 1)
The 111 patients comprising our study population included 58 (52%) women and 53 men with a mean (SD) age of 66 (8.8) years. Most patients were white (91%), non-smokers (91%), and had an ASA score of 2 (76%). The mean (SD) BMI was 29 (5.2) kg/m2. Fifty-six percent of patients underwent THA, and 44% underwent TKA. Surgery was more commonly performed under spinal anesthesia (72%), and lasted an average (SD) of 83 (26) minutes. Regional anesthesia (femoral nerve block) was performed in 33% of patients and Toradol was used in 82% of patients.
3 Results
Postoperative opioid consumption ranged from 0 to 153 mg OMEs (mean ± SD, 34 ± 29), with patients taking more opioids reporting greater pain intensity (r = 0.44) and less satisfaction with pain relief (r = −0.42). The strength of these associations was moderate (Table 2).
| Parameter | Value |
| Age* (years) | 66 ± 8.8 |
| Female† | 58 (52) |
| White race/ethnicity† | 101 (91) |
| Insurance status† | |
| Medicare | 57 (51) |
| Private | 54 (49) |
| Income* (USD) | 64,366 ± 21,917 |
| Tobacco use† | 9 (8.1) |
| SSRI use† | 15 (14) |
| Benzodiazepine use† | 17 (15) |
| BMI* | 29 ± 5.2 |
| NVS Health Literacy* | 3.5 ± 2.0 |
| PHQ-2 Depression* | 1.1 ± 1.6 |
| Pain Catastrophizing Scale* | 8.6 ± 8.0 |
| Procedure type† | |
| THA | 63 (57) |
| TKA | 48 (43) |
| Anesthesia type† | |
| Spinal | 80 (72) |
| General | 31 (28) |
| ASA score† | |
| 2 | 84 (76) |
| 3 | 26 (24) |
| Procedure type† | |
| THA | 63 (57) |
| TKA | 48 (43) |
| Surgeon† | |
| A | 15 (14) |
| B | 56 (51) |
| C | 20 (18) |
| D | 19 (17) |
| E | 1 (0.90) |
| Operative time* (minutes) | 83 ± 26 |
| POD 1 pain intensity* | 4.2 ± 1.9 |
| POD 1 satisfaction with pain relief* | 8.4 ± 2.0 |
| POD 1 opioid use* (morphine equivalents) | 34 ± 29 |
| POD 1 a.m.-PAC Mobility* | 12 ± 3.0 |
| Parameter | POD 1 Opioid Use*, mean ± SD | P |
| Sex | ||
| Female | 28 ± 21 | 0.019 |
| Male | 41 ± 35 | |
| Race/ethnicity | ||
| White | 34 ± 30 | 0.78 |
| Non-white | 37 ± 22 | |
| Insurance status | ||
| Medicare | 25 ± 25 | <0.001 |
| Private | 44 ± 30 | |
| Tobacco use | ||
| No | 32 ± 26 | 0.001 |
| Yes | 62 ± 50 | |
| SSRI use | ||
| No | 33 ± 27 | 0.33 |
| Yes | 41 ± 38 | |
| Benzodiazepine use | ||
| No | 33 ± 27 | 0.34 |
| Yes | 40 ± 41 | |
| ASA score | ||
| 2 | 36 ± 29 | 0.17 |
| 3 | 27 ± 29 | |
| Procedure type | ||
| THA | 29 ± 41 | 0.044 |
| TKA | 40 ± 27 | |
| Anesthesia type | ||
| Spinal | 34 ± 27 | 0.90 |
| General | 34 ± 35 | |
| Surgeon† | ||
| A | 38 ± 29 | 0.11 |
| B | 28 ± 23 | |
| C | 43 ± 33 | |
| D | 43 ± 37 | |
| Parameter | Correlation (r) with POD 1 Opioid Use | P |
| Age (years) | −0.46 | <0.001 |
| BMI | 0.13 | 0.19 |
| Income | −0.082 | 0.40 |
| NVS Health Literacy | −0.037 | 0.70 |
| PHQ-2 Depression | 0.30 | 0.001 |
| Pain Catastrophizing Scale | 0.18 | 0.043 |
| Operative time (minutes) | 0.11 | 0.25 |
| POD 1 pain intensity | 0.44 | <0.001 |
| POD 1 satisfaction with pain relief | −0.18 | 0.058 |
| POD 1 a.m.-PAC Mobility | −0.078 | 0.42 |
Sources of patient-to-patient variation in postoperative opioid use included procedure type and patient characteristics such as age (Fig. 1), emotional health (Fig. 2), tobacco use, and insurance status. Total knee arthroplasty was associated with increased postoperative opioid use (16-mg OME increase compared to THA; P < 0.001), as were younger patient age (1.2-mg OME decrease per 1-year increase; P < 0.001), tobacco use (16-mg OME increase compared to no tobacco use; P = 0.038), greater symptoms of depression (5.1-mg OME increase per 1-unit increase in PHQ-2 score; P = 0.001), and private insurance (7.3-mg OME increase compared to Medicare; P = 0.003). Patient age alone accounted for 9% (partial R2 = 0.090) of the observed variation in opioid use, while procedure type explained 7.4% of the variation, symptoms of depression 5.4%, insurance status 4.7%, and tobacco use 2.3%. Taken together, patient characteristics and procedure type accounted for 48% (R2 = 0.48) of the observed variation in opioid consumption, while 52% of the variation remained unexplained (Table 3).


| Predictor | Estimate (Coefficient) | 95% CI | Partial R2 | P | R2 | |
| Lower | Upper | |||||
| Age, per 1-year increase | −1.2 | −1.8 | −0.65 | 0.096 | <0.001 | 0.46 |
| Male sex (vs. female sex) | 7.6 | −0.86 | 16 | 0.016 | 0.078 | |
| Private insurance (vs. Medicare) | 7.3 | 2.4 | 12 | 0.046 | 0.004 | |
| TKA (vs. THA) | 16 | 7.0 | 24 | 0.068 | 0.001 | |
| Tobacco use | 14 | −1.5 | 30 | 0.017 | 0.076 | |
| PHQ-2 Depression, per 1-unit increase | 5.5 | 2.5 | 8.5 | 0.068 | <0.001 | |
| Pain Catastrophizing Scale, per 1-unit increase | 0.32 | −0.26 | 0.90 | 0.0064 | 0.26 | |
4 Discussion
The increasing prescription of opioids for analgesia over the last 20 years led to a corresponding increase in addiction and overdose death.3,28,29 Promotion of the idea that doctors undertreat pain and that opioids are relatively safe and effective pain relievers created in part the current opioid crisis in the United States and Canada and left healthcare professionals with a climate in which limiting opioid use risks the impression of undertreating pain. Physicians might overprescribe opioids in an attempt to improve patient satisfaction scores and avoid financial penalties.30,31 Most of the world provides adequate pain relief with minimal opioids. There is growing national interest in minimizing perioperative exposure to these potentially addictive drugs after discretionary surgery. In this context, we aimed to explore patient-level variation in perioperative opioid consumption after elective TJA, and to characterize factors that contribute to this variation.
Our analysis should be interpreted cautiously in light of its shortcomings. First, this study was performed at a single large urban academic hospital serving predominantly white patients in the Northeastern United States, and the results may not generalize to other practice settings. Second, because of the limited number of surgeons in the study, we were unable to determine physician characteristics (e.g. technical skill, interpersonal communication skills) influencing perioperative opioid consumption. Third, the fact that postoperative pain management was not standardized is both a strength and a weakness. The variations among surgeons allowed us to study technical variations in daily practice, but it would be better to compare to standardized approaches. Finally, we only considered opioid naïve patients in order to minimize bias associated with heterogeneity of preoperative opioid tolerance. That said, our findings may not apply to patients taking opioids daily or patients on suboxone or methadone for opioid addiction.
We documented substantial variation in perioperative opioid consumption in spite of relatively uniform procedures, all for osteoarthritis, and all in opioid naïve patients. This variation, which was substantiated in a recent randomized trial of 84 patients undergoing THA,13 suggests ample opportunity for improvement in pain relief after discretionary surgery. Consistent with two studies in orthopaedic inpatients,21,32 we found that patients who used more opioids postoperatively reported greater pain intensity and less satisfaction with pain control. As payment models focus on value and reimbursement becomes increasingly tied to patient experience,33 factors other than pain medication merit greater attention for optimal comfort after discretionary surgery.
Patient factors (age, symptoms of depression, tobacco use, and insurance status) accounted for most of the variation in perioperative opioid use. Age was the strongest driver, with younger patients taking more opioids: a finding that is consistent with a recent study in 519 TKA and THA patients in Michigan.19 There may be nociceptive and psychosocial differences attributed to age.34,35 The observed higher perioperative exposure to opioids in younger patients may partly explain why they are at risk for continued opioid use 3 months after major elective surgery.20 Greater symptoms of depression (anhedonia and depressed mood) were predictive of increased opioid use, which may be a result of less resilience and adaptiveness. This finding is consistent with previous orthopaedic research noting the difficulty in achieving adequate pain control in patients with psychological distress.21,32,36,37 Given increasing evidence that patients with symptoms of depression are at higher risk for opioid misuse and dependence,38–40 efforts to address stress, distress, and ineffective coping strategies prior to elective surgery merit greater attention. Mindful of the growing emphasis placed on value by payers and policymakers, we believe that routinely screening for symptoms of depression preoperatively and postponing elective joint arthroplasty to address these symptoms might enhance outcomes and decrease opioid use.20,41 We also observed that tobacco use was linked to higher perioperative opioid use. This aligns with a study in patients undergoing coronary artery bypass surgery that showed a 33% greater opioid use in smokers than nonsmokers within 48 h of surgery.42 There is evidence that abrupt discontinuation of nicotine in hospitalized nicotine-dependent patients increases the perception of pain and the use of opioid analgesics.42,43 On the basis of our findings and because tobacco use is also associated with increased postoperative morbidity and mortality,44 smokers should be encouraged to quit before undergoing elective TJA.
Opioid consumption by patients after TKA was greater than after THA, but no other procedural characteristics that we evaluated (e.g. anesthesia type, operative time) influenced variation in the use of these drugs. Given the notion that patients value non-technical skills (e.g. empathy, respect, professionalism) as much or more than technical ability, it is also possible that surgeons’ “soft” skills influence opioid use. Bozic and colleagues45 recently identified physician manner (e.g. the surgeon spends adequate time answering questions, communicates clearly, and values patient opinion) as the most important consideration for 251 patients seeking a surgeon for elective joint arthroplasty, even more so than surgeon reputation or quality of care (e.g. surgical outcomes). In sum, our results indicate that patient-related factors may explain more of the variation in opioid use after hip and knee arthroplasty than technical factors.
In a population of opioid naïve patients undergoing elective TJA, we observed wide variation in perioperative opioid use that was most strongly associated with patient age and potentially modifiable factors such as emotional health and tobacco use. Awareness of these associations might aid in preoperative counseling and education, and can help inform implementation of targeted strategies for safe, optimal pain relief and satisfaction.
Ethical review committee statement
The Institutional Review Board approved this study.
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