A prospective time-series quality improvement trial of a standardized analgesia protocol to reduce postoperative pain among neurosurgery patients

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OBJECTIVE

The inclusion of the pain management domain in the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey now ties patients' perceptions of pain and analgesia to financial reimbursement for inpatient stays. Therefore, the authors wanted to determine if a quality improvement initiative centered on a standardized analgesia protocol could significantly reduce postoperative pain among neurosurgery patients.

METHODS

The authors implemented a 10-month, prospective, interrupted time-series trial of a quality improvement initiative. The intervention consisted of a multimodal, interdepartmental, standardized analgesia protocol with process improvements from preadmission to discharge. All neurosurgical-floor patients participated in the quality improvement intervention, with data collected on a systematically randomly sampled subset of 96 patients for detailed analysis. Patient-reported numeric rating scale pain on the first postoperative day (POD) served as the primary outcome.

RESULTS

Implementation of the analgesia protocol resulted in improved preoperative and postoperative documentation of pain (p < 0.001) and improved use of multimodal analgesia, including use of NSAIDs (p < 0.009) and gabapentin (p < 0.027). This intervention also correlated with a 32% reduction in reported pain on the 1st POD for all neurosurgical patients (mean pain scale scores 4.31 vs 2.94; p = 0.000) and a 43% reduction among spinal surgery patients (mean pain scale scores 5.45 vs 3.10; p = 0.036). After controlling for covariates, implementation of the protocol was a significant predictor of lowered postoperative pain (p = 0.05) on the 1st POD. This reduction in pain correlated with protocol compliance (p = 0.028), and a significant decrease in the monthly number of naloxone doses suggests improved safety (mean dose ± SD 1.5 ± 1.0 vs 0.33 ± 0.5; p = 0.04). Furthermore, a significant and persistent reduction in the pain management component of the HCAHPS scores suggests a durability of results extending beyond the life of the study (72.1% vs 82.0%; p = 0.033).

CONCLUSIONS

The implementation of a standardized analgesia protocol can significantly reduce postoperative pain among neurosurgical patients while increasing safety. Given the current climate of patient-centered outcomes, this study has broad implications for the continuum of care model proposed in the Affordable Care Act.

Clinical trial registration no.: NCT01693588 (clincaltrials.gov)

ABBREVIATIONSBMI = body mass index; EHR = electronic health record; HCAHPS = Hospital Consumer Assessment of Healthcare Providers and Systems; NRS = numeric rating scale; OME = oral morphine equivalent; PDSA = Plan-Do-Study-Act; POD = postoperative day; PROMIS = Patient Reported Outcomes Measurement Information System.

Abstract

OBJECTIVE

The inclusion of the pain management domain in the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey now ties patients' perceptions of pain and analgesia to financial reimbursement for inpatient stays. Therefore, the authors wanted to determine if a quality improvement initiative centered on a standardized analgesia protocol could significantly reduce postoperative pain among neurosurgery patients.

METHODS

The authors implemented a 10-month, prospective, interrupted time-series trial of a quality improvement initiative. The intervention consisted of a multimodal, interdepartmental, standardized analgesia protocol with process improvements from preadmission to discharge. All neurosurgical-floor patients participated in the quality improvement intervention, with data collected on a systematically randomly sampled subset of 96 patients for detailed analysis. Patient-reported numeric rating scale pain on the first postoperative day (POD) served as the primary outcome.

RESULTS

Implementation of the analgesia protocol resulted in improved preoperative and postoperative documentation of pain (p < 0.001) and improved use of multimodal analgesia, including use of NSAIDs (p < 0.009) and gabapentin (p < 0.027). This intervention also correlated with a 32% reduction in reported pain on the 1st POD for all neurosurgical patients (mean pain scale scores 4.31 vs 2.94; p = 0.000) and a 43% reduction among spinal surgery patients (mean pain scale scores 5.45 vs 3.10; p = 0.036). After controlling for covariates, implementation of the protocol was a significant predictor of lowered postoperative pain (p = 0.05) on the 1st POD. This reduction in pain correlated with protocol compliance (p = 0.028), and a significant decrease in the monthly number of naloxone doses suggests improved safety (mean dose ± SD 1.5 ± 1.0 vs 0.33 ± 0.5; p = 0.04). Furthermore, a significant and persistent reduction in the pain management component of the HCAHPS scores suggests a durability of results extending beyond the life of the study (72.1% vs 82.0%; p = 0.033).

CONCLUSIONS

The implementation of a standardized analgesia protocol can significantly reduce postoperative pain among neurosurgical patients while increasing safety. Given the current climate of patient-centered outcomes, this study has broad implications for the continuum of care model proposed in the Affordable Care Act.

Clinical trial registration no.: NCT01693588 (clincaltrials.gov)

Uncontrolled postoperative pain is associated with an increased risk for pulmonary and cardiovascular complications, is the most common cause for delayed discharge and unexpected readmissions after ambulatory surgery, and is responsible for prolonged convalescence after surgery.3,20,25,39,42,44 Additionally, high levels of postoperative pain are associated with an increased risk of chronic pain.25,42

Recently, patients' perceptions of postoperative pain and analgesia have become critical components of health care evaluations, and these evaluations are increasingly being tied to reimbursements. This is evident in the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey.14 The HCAHPS survey directly questions a patient's need for analgesics while admitted, how often their pain was “well controlled,” and how often the hospital staff did “everything they could to help with pain.”14 Prior studies have demonstrated that a patient's HCAHPS domain of pain and analgesia satisfaction is highly correlated with their global satisfaction with a hospitalization.19

After discovering that the pain domain HCAHPS scores for our department were consistently below the national median, we implemented a quality improvement trial to address postoperative pain. While several examples of analgesia protocols were present in the literature, none used an interdepartmental approach, focused on all phases of care, or used quality improvement methodologies. Therefore, using a conceptual health model of pain, we developed a multimodal, interdepartmental, standardized analgesia protocol that followed neurosurgical patients from preadmission to discharge. Our primary outcome goal was a significant reduction in patients' average postoperative pain score on the 10-point numeric rating scale (NRS). Secondary goals were to determine that a standardized protocol could be safely implemented and to determine which factors predicted postoperative pain in neurosurgical patients. We hypothesized that by using quality improvement methodologies, a standardized analgesia protocol could be developed and implemented by a multidisciplinary team and could increase patient satisfaction in the domain of pain treatment and analgesia during hospitalization for neurosurgical surgery.

Methods

Our institution is an 852-bed, academic tertiary referral center with approximately 4000 neurosurgical discharges annually. To assess the efficacy of our quality improvement initiative, a prospective interrupted time-series trial was conducted. The study consisted of a 4-month preintervention surveillance period (October 2012 through January 2013) followed by a 6-month postintervention phase (February through July 2013). Systematic random sampling was used to identify every 10th postoperative neurosurgical patient admitted preintervention and every 17th patient postintervention. Exclusion criteria were age younger than 18 years, nonoperative patients, use of methadone within the last 6 months, pregnancy, or inability to communicate their pain level in English. Ninety-six of 160 patients screened were enrolled in the study, a recruitment rate of 60%, with a 100% completion rate of enrolled patients. The reasons for screening failure were refusal to participate in the study (n = 28), discharge prior to the study coordinator arriving (n = 19), inability to provide informed consent (n = 5), use of methadone (n = 4), lack of English proficiency (n = 2), and other reasons (n = 6). The study was approved by the University of Florida institutional review board. It is registered with the ClinicalTrials. gov database (http://clinicaltrials.gov), and its registration no. is NCT01693588.

Intervention

An interdepartmental committee composed of neurosurgery, anesthesiology, acute pain service, nursing, and pharmacy personnel was formed. This committee developed an initial driver diagram16 and aggregated best practices from other institutions and the current literature. Interviews of residents, fellows, and nurses revealed specific barriers to pain control such as the following: 1) poor communication between anesthesiology and neurosurgery teams regarding postoperative analgesia, 2) variation of analgesia prescribing among neurosurgical faculty, 3) resident fears of obscuring the neurological examination with excessive opioids, 4) inconsistent notification of residents by nurses for uncontrolled postoperative pain, and 5) delayed responses of physicians to requests for analgesia escalation by nursing staff.

Therefore, an “analgesia bundle” was designed to address all points of a patient's hospitalization (Table 1). Appendix A presents a more detailed intervention protocol. The bundle included preoperative process improvements, intraoperative analgesia standardization, improved recognition of postoperative pain, and a standardized postoperative analgesia protocol (Appendix B) and analgesia escalation protocol (Appendix C). Using our electronic health record (EHR) system, we developed an automated daily list of all patients with at least 1 pain score equal to or greater than 7 on the NRS within the prior 24 hours. This information was then distributed to neurosurgery and nursing staff in the form of a run chart. The pain control committee used this data to guide multiple Plan-Do-Study-Act (PDSA) cycles.15

TABLE 1.

Intervention performed during the analgesia initiative

1Preop improvements
  1.1Increased documentation of preop pain using NRS
  1.2Improved documentation of preop anxiety & depression
  1.3Improved documentation of preop analgesic usage
  1.4Scripting of expected pain counseling & inclusion in preop visit
2Intraop
  2.1Preop dosing of spinal surgery patients w/ gabapentin
  2.2Improved use of multimodal analgesia (acetaminophen, NSAIDs, ketamine, gabapentin)
  2.3Standardization of analgesia use among neuroanesthesiologists
3Postop pain recognition
  3.1Online training of nurses on pain recognition
  3.2Set goal of “6-must be fixed.” In all patients w/ pain level >6, action must be taken
  3.3Nursing staff were informed to first maximize all PRN medications prior to notifying residents & fellows for uncontrolled pain
  3.4Automatically import last 24-hr pain scores into the daily rounding notes for neurosurgery
4Postop pain control
  4.1Developed a standardized analgesia protocol for neurosurgery patients based on surgery type
  4.2Inclusion of the analgesia protocol into the standard order set for postop neurosurgery patients
  4.3Developed a safe analgesia escalation protocol
  4.4Developed a trigger for consulting Acute Pain Services
  4.5Develop a pain note for neurosurgery that aided in calculation of preop OMEs
  4.6Education of residents and fellows on pain management

PRN = as needed.

Data Collection

Analgesics use was categorized as follows: acetaminophen, antiepileptics/antidepressants adjuvant agents (gabapentin, pregabalin), anxiolytics (e.g., benzodiazepines), NSAIDs, and opioids. Daily oral morphine equivalents (OMEs) were totaled using our pharmacy's equal analgesic conversion algorithm. To control for preexisting pain, anxiety, and depression, all subjects received 5 question batteries from the Patient Reported Outcomes Measurement Information System (PROMIS). The PROMIS batteries were Pain Behavior Bank, Physical Function Bank, Anxiety Bank, Depression Bank, and Sleep Disturbance Bank. PROMIS uses computer-adaptive testing and item-response theory to minimize responder burden and improve accuracy, which was necessary in patients with extreme pain.1,4,5,7,10,13,21,36,37 The question selection was by maximum posterior weighted information and stopping conditions were a minimum of 4 and a maximum of 8 responses per battery. PROMIS batteries were scored using a graded response model and reported t-scores were based on a large national sample.

The main process measure was compliance with the entire analgesia protocol. Other process measures included analgesics use on postoperative Days 1 and 3 (POD1, POD3), use of patient-controlled analgesia, and documentation of pre- and postoperative pain scores. A postoperative survey adapted from the Brief Pain Survey and the Short-Form McGill Pain Questionnaire18,28,29,41,45,46 assessed time to administration of pain medication, perception of physicians' and nurses' sympathy, and perceptions of analgesia regimen effectiveness (Appendix D).

Pain was assessed every 4 hours using the 10-point NRS. These scores were aggregated for a POD1 and POD3 score and functioned as the primary outcome. A successful reduction was defined as a statistically significant 1.06-point decrease in the average NRS on POD1. Secondary outcome measures were the POD3 scores and HCAHPS pain management domain. Length of stay and naloxone use data were documented as a countermeasure.

Education

Physicians underwent 3 hours of live training on the protocol. Intervention refinements from PDSA cycles were implemented via email. The initiative was disseminated to nurses via quality teams and an online mandatory training module with a posttest. All nurses completed the training and achieved an acceptable posttest score of at least 80%. Education of hospital administration and Quality Department staff was performed via regular updates through the hospital's Medical Executive Pain Committee. Educational presentations are available upon request from the first author.

Statistical Analysis

Based on pain and psychometric literature, a minimum clinically important difference of half the standard deviation of the preintervention POD1 pain scores (1.06) was determined a priori.1,2 Sample size was based on a mean change in the NRS of 1.0 (SD 1.5; α error 5%; 90% power). Baseline characteristics were compared with repeated 2-tailed independent sample t-tests if continuous and a chi-square test if ratios. Data are reported as mean ± SD. A univariate linear regression model (SPSS V22.0.0; IBM Corp.) was created to determine factors' association with postoperative pain. Treatment group (pre- or postintervention) was our primary predictor, and candidate variables included surgery type, age, sex, body mass index (BMI), history of depression, history of anxiety, each of the 5 PROMIS batteries, and preoperative medication use (acetaminophen, antiepileptics/antidepressants, anxiolytics, NSAIDs, and opioids, including OMEs) as covariates. The Hosmer-Lemeshow test was used to assess model fit. A p value < 0.05 was considered significant. A multivariate regression with a stepwise elimination routine was used to determine best predictors of POD1 pain with rational exceptions. The statistical criterion for entry into and staying in the model was p ≤ 0.3. The model for POD3 pain was identical but included POD1 pain as a candidate variable. Finally, a repeated measure, mixed linear model was developed with POD1 and POD3 as the outputs and the same covariates.

Results

Prior to the intervention, no standardized analgesia strategy existed for neurosurgical patients; rather, each physician followed personal preference. Accordingly, analgesics were not included in the standard postoperative order sets. Informal interviews revealed that residents were often hesitant to adequately treat patients' pain for fear of obscuring the neurological examination. In the 8 quarters preceding the initiative, HCAHPS survey results showed that only 72.1% ± 6.4% of neurosurgical-floor patients felt they were “always helped with their pain” and only 56.6% ± 6.9% felt their “pain was always controlled.” Both of these numbers place us below the national median when compared with other neurosurgery programs. Therefore, we implemented a quality improvement intervention to address postoperative pain control.

The cornerstone of the intervention was a standardized analgesia protocol based on the World Health Organization analgesic ladder. Postoperative analgesia regimens were created for supratentorial craniotomy, suboccipital craniotomy, spine surgery without fusion, and spine surgery with fusion (Appendix B). Next, a rational analgesia escalation algorithm was developed by Pharmacy and Acute Pain Service (Appendix C). These protocols were approved by the neurosurgery faculty and incorporated into the electronic postoperative order sets. Other interventions, as detailed in Table 1 and Appendix A, were implemented on or about February 1, 2013. The Pain Control Committee met monthly to review the project, and PDSA cycles were implemented as necessary.

When comparing the pre- and postintervention sample populations (n = 48 each), no difference was found between them in age, sex, type of surgery (cranial vs spinal), or BMI (Table 2). PROMIS computer adaptive testing surveys were used to control for premorbid pain, physical dysfunction, anxiety, and depression. No differences in preoperative pain behaviors (p = 0.075), pain-related interference in daily life (p = 0.567), or pain-related physical dysfunction (p = 0.198) were noted. Although no difference existed between the two groups regarding a medical history of depression (p = 0.238) or anxiety (p = 0.809), after the intervention, patients reported a slightly higher preadmission depression inventory score (46.3 ± 11.1 vs 53.5 ± 11.7; p = 0.003) and anxiety scale score (49.8 ± 10.9 vs 56.8 ± 10.5; p = 0.002) on the PROMIS batteries. Therefore, these were controlled for in the final analysis. No difference existed between the percentage of patients using opioids (p = 0.212), acetaminophen (p = 0.657), benzodiazepines (p = 0.412), NSAIDs (p = 0.386), or gabapentin (p = 0.355) before or after the intervention. However, among the patients who did use opioids, the preintervention group tended to use a high, 24-hour OME (mean 94.8 ± 48.9 mg/day vs 48.9 ± 48.9 mg/day; p = 0.007). Again, this was controlled for in the final analysis.

TABLE 2.

Preoperative patients' characteristics*

CharacteristicPreinterventionPostinterventionp Value
Time
  October 2012 through January 201348
  February 2013 through August 201348
Sex0.067
  M29 (60.4)20 (41.7)
  F19 (39.6)28 (58.3)
Mean age, yrs56.2 ± 16.755.9 ± 16.20.926
Mean BMI, kg/m228.4 ± 7.129.1 ± 7.60.662
Surgery1.00
  Craniotomy18 (37.5)17 (35.4)
  Spine30 (62.5)31 (64.6)
Mental health
  History of depression9 (18.8)15 (31.3)0.238
  History of anxiety10 (20.8)12 (25)0.809
Preop analgesia use
  Opioids23 (47.9)16 (33.3)0.212
  Mean 24-hr OME, mg/day94.8 ± 48.948.9 ± 48.90.007
  Acetaminophen16 (33.3)13 (27.1)0.657
  Anxiolytics (e.g., benzodiazepines)10 (20.8)6 (12.5)0.412
  NSAIDs5 (10.4)9 (18.8)0.386
  Antiepileptics/antidepressants (gabapentin, pregabalin)4 (8.3)7 (14.6)0.355
PROMIS, mean score
  Pain Behavior Scale56.0 ± 10.459.2 ± 5.80.075
  Pain Interference Scale60.2 ± 12.161.5 ± 9.60.567
  Physical Dysfunction Scale34.4 ± 8.336.7 ± 8.40.198
  Sleep Scale55.2 ± 10.559.6 ± 10.30.049
  Depression Scale46.3 ± 11.153.5 ± 11.70.003
  Anxiety Scale49.8 ± 10.956.8 ± 10.50.002

Data are given as number (%) of patients unless otherwise indicated, and mean values are presented ± SD.

Implementation of the Pain Control Protocol

Institution of a pain management initiative correlated with increased documentation of preexisting pain and recognition of postoperative pain. Documentation of preoperative pain in the medical record increased from 12.5% to 47.9% (p = 0.000) (Table 3), and documentation of pain in the daily postoperative rounding notes increased from 8.3% to 100% following the intervention (p = 0.000).

TABLE 3.

Process improvement measures*

MeasurePreinterventionPostinterventionp Value
Pain documented in HPI6 (12.5)23 (47.9)0.000
Pain documented in daily note4 (8.3)48 (100)0.000
POD1, no. of patients4848
Acetaminophen27 (56.3)36 (75)0.055
Benzodiazepine5 (10.4)10 (20.8)0.170
NSAID4 (8.3)15 (31.3)0.009
Baclofen9 (18.8)5 (10.4)0.386
Gabapentin6 (12.5)16 (33.3)0.027
PCA use18 (37.5)14 (29.2)0.390
Mean OME, mg/day, ± SD55.7 ± 100.663.2 ± 58.50.655
Compliance w/protocol0 (0)17 (35.4)0.000
POD3, no. of patients1922
Acetaminophen4 (21.1)11 (50.0)0.050
Benzodiazepine4 (21.1)8 (36.4)0.466
NSAID1 (5.3)4 (18.2)0.393
Muscle relaxant8 (42.1)3 (13.6)0.133
Gabapentin3 (15.8)9 (40.9)0.176
PCA use02 (0.9)0.490
Mean OME ± SD72.29 ± 70.739.17 ± 36.50.062

HPI = history of presenting illness; PCA = patient-controlled analgesia.

Data given as number (%) unless otherwise indicated.

Significant changes in peri- and intraoperative analgesia were driven by a consensus discussion by the neuroanesthesia faculty. The approach focused on consistent use of multimodal analgesia and attention to continuation of preexisting therapy with long-acting opiates. Patients receiving some form of multimodal pain therapy beyond the intraoperative administration of intermediate-acting narcotics increased from 81% to 92% (p = 0.23) across all neurosurgeries. The use of gabapentin and acetaminophen increased from 6% to 25% and 67% to 88%, respectively (p = 0.025 for gabapentin and p = 0.029 for acetaminophen). Gabapentin use increased particularly in spine surgery patients. The proportion of patients who received long-acting opiates perioperatively increased from 40% to 67% (p = 0.014). Although not statistically significant, there was an increase from 25% to 46% (p = 0.055) in the percentage of patients prescribed at least 1 adjunctive analgesic after the rollout of the initiative.

Inclusion of the standardized analgesia protocol in the neurosurgery postoperative order set also had significant effects on prescriber habits. Monthly compliance with all aspects of the analgesia protocol increased from 0% to 35.4% postintervention, with a maximal compliance of 80% noted in the 3rd postintervention month (Fig. 1A). It must be noted that if a patient failed on any single measure, they were not counted as compliant. Despite this partial compliance with the total protocol, physicians were much more likely to use at least 2 or more classes of analgesia after the protocol implementation. Postintervention, the use of NSAIDs increased from 8.3% to 31.3% (p = 0.009) and use of gabapentin increased from 12.5% to 33.3% (p = 0.027). While not statistically significant, acetaminophen use also trended upward (56.3% vs 75%; p = 0.055). Preintervention, no patient was prescribed intravenous acetaminophen, which was commonly used after-ward. Interestingly, there was no significant change in the mean 24-hour OME after the intervention (55.7 ± 100.6 mg/day vs 63.2 ± 58.5 mg/day; p = 0.655), nor was there an increase in the use of patient-controlled analgesics (37.5% vs 29.2%; p = 0.390).

FIG. 1.
FIG. 1.

Protocol process and outcome measures. A: Protocol compliance and POD1 pain scores. B: Aggregate NRS pain scores for all surgeries and specifically for craniotomies and spinal surgeries. ***p < 0.0001. C: Monthly postoperative NRS pain scores pre- and postintervention for craniotomies and spinal surgeries. D: Weekly aggregate pain scores for all patients admitted to the neurosurgery, orthopedic, or general surgery services. E: HCAHPS scores: pain management summary scores by quarter. F: T-chart showing the number of days between consecutive naloxone doses. A T-chart is a specialized control chart used for monitoring rare adverse events. Each point on the x-axis is a sequential administration of naloxone to a floor patient with times since previous administration represented on the y-axis.

Although the time between patients' requests for analgesia and administration of the medication among floor patients was brief preintervention, this showed no significant changes postintervention. The percentage of patients who felt that less than 5 minutes had elapsed between requesting medication and its administration remained constant (52.2% vs 48.8%; chi-square, p = 0.712). Additionally, the percentage of patients who felt the longest time for analgesic delivery was less than 10 minutes (67.4% vs 58.2%; chi-square, p = 0.782) remained unchanged.

It appears that gains made in this study were due to improved pain control rather than changes in patients' perceptions of medical staff. Patients' perception of caregiver sympathy was assessed through postoperative surveys. However, the percentage of patients who either “strongly agree” or “agree” with the statement “My doctor is always sympathetic to my pain” (91.7% vs 91.7%; p = 1.00) did not change. Similarly, no change was seen when asking about nursing sympathy (93.8% vs 91.6%; p = 0.452).

Postoperative Pain Decreased Following Implementation of the Pain Control Protocol

In general, implementation of the analgesia protocol correlated with reduced pain on POD1. A univariate linear regression of 16 candidate variables demonstrated that increasing age (p = 0.016), having a cranial surgery as opposed to spinal surgery (p = 0.000), and being admitted to the hospital after the analgesia protocol (p = 0.004) (Table 4) were most predictive of a lower aggregate POD1 pain score. Controlling for all other variables, patients reported a 31.8% reduction in POD1 pain on the 10-point NRS scale after implementation of the protocol (p < 0.0001) (Table 4, Fig. 1B). Patients recovering from spine surgery had the largest improvement, with a 43.1% drop in NRS pain scores (5.45 vs 3.10; p < 0.036). Patients recovering from cranial surgery only had a 20.9% reduction but most likely suffered a floor effect, since their baseline pain scores were roughly half that of spinal surgery patients both before and after the intervention (2.78 vs 5.45) (Table 4).

TABLE 4.

Outcome measures*

MeasurePreinterventionPostinterventionp Value
POD1, no. of patients4848
  Aggregate pain score4.31 (3.7–4.9)2.94 (2.04–3.85)0.000
  Cranial surgery patients' scores2.78 (1.79–3.77)2.20(1.08–3.32)0.21
  Spinal surgery patients' scores5.45 (4.64–6.25)3.10 (2.37–3.83)0.036
POD3, no. of patients1820
  Aggregate pain score3.22 (1.972–4.465)2.39 (1.382, 3.391)0.058
  Cranial surgery patients' scores1.54 (−0.991 to 4.076)1.39 (−0.300 to 3.080)0.402
  Spinal surgery patients' scores4.89 (3.838–5.949)3.38 (2.451–4.314)0.043
How much relief has your pain treatments or medication provided? (0%–100%)74.3 (66.7–81.93)66.3 (58.30–74.22)0.663
  Mean length of stay, days (CI)2.98 (2.21–3.75)2.87 (2.10–3.65)0.851
  Naloxone doses/mo, ± SD1.5 ± 1.00.33 ± 0.50.039
  Median days btwn naloxone doses1264

Data given as mean pain score (95% CI) unless otherwise indicated.

Modifiers of postoperative pain included age. For each additional year of age, patients reported 0.03 fewer points on the average POD1 NRS. Factors having no effect included BMI, sex, any of the PROMIS indices, and history of depression, anxiety, or preoperative OME. Similarly, the greatest predictor of lower POD3 pain was having a cranial procedure (p = 0.018). Otherwise, the greatest predictors of lower POD3 pain were a low POD1 NRS pain score (p = 0.0033), a lower BMI (p = 0.032), and a lower PROMIS depression inventory (p = 0.006). All other variables showed no significant influence (Table 4).

A repeated measure, mixed linear model was developed with POD1 and POD3 pain scores as the outputs; covariates included type of surgery, age, pain intervention group, preoperative OME, BMI, and PROMIS depression inventory. Patients' pain did not change significantly between POD1 and POD3 (p = 0.787); this most likely resulted from the discharge of patients with adequate analgesia. When including both POD1 and POD3 pain scores in the model, having cranial surgery (p = 0.001) and being in the postintervention group (p = 0.046) were significant predictors of decreased postoperative pain.

The observed decline in monthly aggregate POD1 NRS pain scores appears to begin with implementation of the analgesia protocol (time = 0) (Fig. 1A and C). Furthermore, the monthly aggregate POD1 showed a strong negative correlation with protocol compliance in cranial patients (−0.441; n = 10; p = 0.202), spinal surgery patients (−0.515; n = 10; p = 0.128), and all surgical patients (−0.686; n = 10; p = 0.028) (Fig. 1A and C). The possibility exists that these results could have been due to secular trends (e.g., hospitalwide improvements in pain management) concurrent with this initiative. Therefore, 307,945 NRS pain scores were collected from all postoperative neurosurgery (n = 140,035), general surgery (n = 77,789), and orthopedic surgery patients (n = 90,121). Neurosurgery pain scores were compared with general surgery and orthopedic pain scores by week. After controlling for age (p < 0.0001) and BMI (p < 0.0001), a univariate linear regression revealed a significant department and time interaction, with the neurosurgery NRS pain scores being significantly lower than scores for other services after the start of the intervention (p < 0.0001) (Fig. 1D).

Finally, during the intervention and after its completion, the HCAHPS pain domain responses for this patient population were also assessed as an externally measured and nationally standardized method of assessing inpatient analgesia. However, it must be noted that HCAHPS scores were collected quarterly from 50 randomly selected, anonymous patients and did not correlate directly with the study population. The normalized national percentage of patients that either “agree” or “strongly agree” with their pain management increased from 64.3% preintervention to 72.8% postintervention (t-test, p = 0.007). This resulted in departmental scores at or near the national median and coincided with the implementation of the analgesia initiative (Fig. 1E). Furthermore, this trend has continued well after the close of the study, suggesting persistent institutional change. Additionally, the percentage of patients who were always “helped with their pain” increased significantly from 72.1% to 82.0% postintervention (p = 0.033). While there was no statistical change in the percentage of patients reporting their pain was “always controlled,” this HCAHPS question was trending in a favorable direction (56.5% vs 63.2%; p = 0.14).

As a countermeasure, the number of naloxone doses was tracked. This medication is only given in this population for treatment of altered mental status believed to be associated with opioid overdose. Given its low frequency, this indicator was documented among all postoperative neurosurgical-floor patients during the study period. Following implementation of the pain protocol, the rate of naloxone dose administration fell from 1.5 doses per month to 0.33 doses per month (p = 0.04) (Table 4). Additionally, the median number of days between naloxone doses increased from 12 to 64 after the intervention (Fig. 1F).

Lessons From Implementation

Significant resistance to implementation was encountered from neurosurgery residents. Although all neurosurgery faculties had approved the protocol, many residents were unsure if repercussions would exist if a faculty member's previous preferences were ignored. Reinforcing the Just Culture Model combatted this misconception.9 This paradigm does not punish a practitioner for a patient harm event if this practitioner was following a best practices protocol; rather, it coaches the individual if errors were made and alters the protocol to improve safety if needed. Second, the few instances of overmedication were closely scrutinized. Because of this increased emphasis, it was assumed that these events were occurring with increased frequency, although the inverse was true as demonstrated in our findings (Table 4, Fig. 1E). One failure of this initiative was an EHR note that guided residents through calculating a patient's OME and suggested logical escalations according to the protocol. Despite several revisions, this note remained too cumbersome to gain widespread adoption among the residents. Finally, our EHR did not clearly show nurses which analgesia tiered patients were receiving, thus preventing them from suggesting dose escalations. Improvements to the electronic medical record order displays were a frequent focus of the PDSA cycles.

Discussion

In this study we demonstrated that a literature-based, standardized analgesia protocol could be implemented among postoperative patients despite a wide range of faculty opinions regarding analgesia. This protocol resulted in improved documentation, improved response to postoperative pain, and improved use of multimodal analgesia. Furthermore, it correlated with a 32% reduction in aggregate pain scores among all patients on POD1, and this effect was most significant among spinal surgery patients, who had a 43% reduction in postoperative pain. This observed decline correlated with an increase in protocol compliance and a significant decrease in the number of administered naloxone doses. Furthermore, HCAHPS scores recorded since the completion of the formal initiative suggest durability beyond the life of the study.

These findings are consistent with and extend those from previous reports. Uncontrolled postoperative pain is both prevalent and undertreated, with 20% to 30% of all surgical patients experiencing moderate to severe postoperative pain.8,30 A review of inpatient neurosurgical patients at another institution found that 18% of patients complained of excruciating pain, while 37% of patients complained of severe pain.33 Similar to this study, published work shows that among neurosurgery patients, factors that predict postoperative pain include type of surgery,17,26 premorbid pain,26 and depression.

This study supports improved analgesia among patients with multimodal therapy. Prior neurosurgical literature demonstrates that narcotics have been the predominant method of pain management after craniotomy.23,33,38,40 Unfortunately, because of their effects on mental status, these agents are typically used sparingly. However, a Cochrane Review showed that combining acetaminophen with codeine provides increased pain control and extends the duration of analgesia.43 Given the disadvantages of opioids and the relative advantages of nonopioid agents, it is surprising that very few studies of neurosurgery patients have promoted the use of multimodal analgesia.

In a meta-analysis of 17 lumbar surgery studies, patients receiving NSAIDs in addition to opioids had lower pain scores and consumed fewer opioids than the group receiving opioids alone, with no difference in the incidence of adverse effects.24 In 1 small, randomized controlled trial, craniotomy patients receiving both cyclooxygenase-2 inhibitors and narcotics had significantly lower pain, decreased length of stay, and decreased narcotics use compared with narcotics use alone.34

The implementation of an analgesia protocol is not new. In patients with end-stage renal disease, implementation of the WHO analgesia ladder decreased mean pain scores by 6 points on a 10-point scale.2 A multimodal analgesia regimen implemented among total hip arthroplasty patients found reduced postoperative pain in a 4-day postoperative period.27 Finally, 2 randomized controlled trials showed that a single-agent protocol of more than 300 mg of oral gabapentin prior to lumbar discectomy reduced postoperative pain and decreased fentanyl use.31,32 In contrast to the current study, these studies only addressed a single class of agents and lacked modern quality improvement methodologies.

One published quality improvement intervention compared patient-controlled analgesia to an oral, multimodal analgesia protocol that included NSAIDs and acetaminophen in spinal surgery patients.35 Similar to the current study, these authors found that patients used significantly fewer opioids, had less pain, and fewer side effects associated with opioids; however, this study only used historical controls.35 Other examples of multimodality pain management protocols in nonsurgical patients have shown decreased use of inappropriate pain medications,6 standardized care, decreased length of time to extubation, decreased hospital length of stay, decreased cost, and decreased nursing time.11,12 Whereas other studies have altered the analgesia agents used to treat postoperative pain, this was the first study, to our knowledge, to address patient pain pre-, intra, and postoperatively. Furthermore, to our knowledge, this is the first report that used the combined efforts of surgery, anesthesia, nursing, pharmacy, and quality improvement methodologies.

Several potential limitations resulting from this study's time-series design must be acknowledged. First, nurses collected pain scores and were aware of the initiative; this could have potentially influenced patient-reporting practices, resulting in response bias. However, self-reported, anonymous patient questionnaires showed similar trends in magnitude and temporal correlation with the nurse-collected data. Next, the recruitment of patients with lower pain scores in the postintervention group could have resulted in allocation bias. Therefore, systematic random sampling was used to limit convenience sampling, and a recruitment rate of 60% is similar to published analgesia literature. Furthermore, we used PROMIS computer adaptive testing to ease responder burden and lessen responder fatigue, making it more likely to capture this population. Contamination bias was curtailed by limiting initiative implementation to a 1-week period among all departments. This study design also is susceptible to secular trends, but a comparison of neurosurgery pain scores to those of orthopedic and general surgery patients during the same time period mitigates this concern. Finally, improved analgesia could have resulted from the Hawthorne effect or improvements in performance because clinicians were aware of the study goals. Unfortunately, a balanced, incomplete block design was not feasible in this study. However, the HCAHPS scores (Fig. 1E) demonstrate persistent improvements in pain management nearly 2 years after the end of the formal study, which lasted only 6 months. If the results were only from the influence of being observed, this effect would have returned to baseline at the close of the study.

The greatest strengths of this study are its pragmatism and generalizability. All measures implemented are achievable in other institutions with very little capital outlay. To our knowledge, this is one of the first studies to use rigorous quality improvement methodology and a strong multidisciplinary approach to directly address an observed underperformance in the HCAHPS pain domain. This study suggests that among neurosurgery patients, a quality improvement initiative with interdepartmental cooperation and standardization of analgesia can decrease postoperative pain, promote multimodal analgesia therapy, and decrease adverse events associated with opioids in a large institution. Since immediate postoperative pain is one of the strongest predictors of developing chronic pain among outpatients, this study has broad implications for the continuum of care model proposed in the Affordable Care Act.22

Acknowledgments

This study received funding from the W. Martin Smith Interdisciplinary Patient Quality and Safety Awards Program.

References

  • 1

    Amtmann DCook KFJensen MPChen WHChoi SRevicki D: Development of a PROMIS item bank to measure pain interference. Pain 150:1731822010

  • 2

    Barakzoy ASMoss AH: Efficacy of the world health organization analgesic ladder to treat pain in end-stage renal disease. J Am Soc Nephrol 17:319832032006

  • 3

    Capdevila XBarthelet YBiboulet PRyckwaert YRubenovitch Jd'Athis F: Effects of perioperative analgesic technique on the surgical outcome and duration of rehabilitation after major knee surgery. Anesthesiology 91:8151999

  • 4

    Castel LDWilliams KABosworth HBEisen SVHahn EAIrwin DE: Content validity in the PROMIS social-health domain: a qualitative analysis of focus-group data. Qual Life Res 17:7377492008

  • 5

    Cella DYount SRothrock NGershon RCook KReeve B: The Patient-Reported Outcomes Measurement Information System (PROMIS): progress of an NIH Roadmap cooperative group during its first two years. Med Care 45:5 Suppl 1S3S112007

  • 6

    D'Arcy YJohann D: Using a medication protocol to improve pain management. Nurs Manage 39:35392008

  • 7

    DeWalt DARothrock NYount SStone AA: Evaluation of item candidates: the PROMIS qualitative item review. Med Care 45:5 Suppl 1S12S212007

  • 8

    Dolin SJCashman JNBland JM: Effectiveness of acute postoperative pain management: I. Evidence from published data. Br J Anaesth 89:4094232002

  • 9

    Fargen KMFriedman WA: The science of medical decision making: neurosurgery, errors, and personal cognitive strategies for improving quality of care. World Neurosurg 82:e21e292014

  • 10

    Fries JFBruce BCella D: The promise of PROMIS: using item response theory to improve assessment of patient-reported outcomes. Clin Exp Rheumatol 23:5 Suppl 39S53S572005

  • 11

    Furdon SAEastman MBenjamin KHorgan MJ: Outcome measures after standardized pain management strategies in postoperative patients in the neonatal intensive care unit. J Perinat Neonatal Nurs 12:58691998

  • 12

    Furdon SAPfeil VCSnow K: Operationalizing Donna Wong's principle of atraumatic care: pain management protocol in the NICU. Pediatr Nurs 24:3363421998

  • 13

    Gershon RCRothrock NHanrahan RBass MCella D: The use of PROMIS and assessment center to deliver patient-reported outcome measures in clinical research. J Appl Meas 11:3043142010

  • 14

    Giordano LAElliott MNGoldstein ELehrman WGSpencer PA: Development, implementation, and public reporting of the HCAHPS survey. Med Care Res Rev 67:27372010

  • 15

    Goldmann D: How can CLABSIs and cucumbers teach PDSA?. IHI Open School (http://www.ihi.org/education/IHIOpenSchool/resources/Pages/Activities/PDSACyclesFromCLABSIsToCucumbers.aspx

  • 16

    Goldmann D: How do you use a driver diagram?. IHI Open School (http://www.ihi.org/education/ihiopenschool/resources/Pages/Activities/GoldmannDriver.aspx

  • 17

    Gottschalk ABerkow LCStevens RDMirski MThompson REWhite ED: Prospective evaluation of pain and analgesic use following major elective intracranial surgery. J Neurosurg 106:2102162007

  • 18

    Grafton KVFoster NEWright CC: Test-retest reliability of the Short-Form McGill Pain Questionnaire: assessment of intraclass correlation coefficients and limits of agreement in patients with osteoarthritis. Clin J Pain 21:73822005

  • 19

    Gupta ADaigle SMojica JHurley RW: Patient perception of pain care in hospitals in the United States. J Pain Res 2:1571642009

  • 20

    Gust RPecher SGust AHoffmann VBöhrer HMartin E: Effect of patient-controlled analgesia on pulmonary complications after coronary artery bypass grafting. Crit Care Med 27:221822231999

  • 21

    Hung MClegg DOGreene TSaltzman CL: Evaluation of the PROMIS physical function item bank in orthopaedic patients. J Orthop Res 29:9479532011

  • 22

    Janssen KJKalkman CJGrobbee DEBonsel GJMoons KGVergouwe Y: The risk of severe postoperative pain: modification and validation of a clinical prediction rule. Anesth Analg 107:133013392008

  • 23

    Jeffrey HMCharlton PMellor DJMoss EVucevic M: Analgesia after intracranial surgery: a double-blind, prospective comparison of codeine and tramadol. Br J Anaesth 83:2452491999

  • 24

    Jirarattanaphochai KJung S: Nonsteroidal antiinflammatory drugs for postoperative pain management after lumbar spine surgery: a meta-analysis of randomized controlled trials. J Neurosurg Spine 9:22312008

  • 25

    Katz JJackson MKavanagh BPSandler AN: Acute pain after thoracic surgery predicts long-term post-thoracotomy pain. Clin J Pain 12:50551996

  • 26

    Klimek MUbben JFAmmann JBorner UKlein JVerbrugge SJ: Pain in neurosurgically treated patients: a prospective observational study. J Neurosurg 104:3503592006

  • 27

    Lee KJMin BWBae KCCho CHKwon DH: Efficacy of multimodal pain control protocol in the setting of total hip arthroplasty. Clin Orthop Surg 1:1551602009

  • 28

    McDonald DDWeiskopf CS: Adult patients' postoperative pain descriptions and responses to the Short-Form McGill Pain Questionnaire. Clin Nurs Res 10:4424522001

  • 29

    Melzack R: The short-form McGill Pain Questionnaire. Pain 30:1911971987

  • 30

    Michel MZSanders MK: Effectiveness of acute postoperative pain management. Br J Anaesth 91:4484492003

  • 31

    Pandey CKNavkar DVGiri PJRaza MBehari SSingh RB: Evaluation of the optimal preemptive dose of gabapentin for postoperative pain relief after lumbar diskectomy: a randomized, double-blind, placebo-controlled study. J Neurosurg Anesthesiol 17:65682005

  • 32

    Pandey CKSahay SGupta DAmbesh SPSingh RBRaza M: Preemptive gabapentin decreases postoperative pain after lumbar discoidectomy. Can J Anaesth 51:9869892004

  • 33

    Quiney NCooper RStoneham MWalters F: Pain after craniotomy. A time for reappraisal?. Br J Neurosurg 10:2952991996

  • 34

    Rahimi SYVender JRMacomson SDFrench ASmith JRAlleyne CH Jr: Postoperative pain management after craniotomy: evaluation and cost analysis. Neurosurgery 59:8528572006

  • 35

    Rajpal SGordon DBPellino TAStrayer ALBrost DTrost GR: Comparison of perioperative oral multimodal analgesia versus IV PCA for spine surgery. J Spinal Disord Tech 23:1391452010

  • 36

    Revicki DAChen WHHarnam NCook KFAmtmann DCallahan LF: Development and psychometric analysis of the PROMIS pain behavior item bank. Pain 146:1581692009

  • 37

    Revicki DAKawata AKHarnam NChen WHHays RDCella D: Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample. Qual Life Res 18:7837912009

  • 38

    Roberts G: A review of the efficacy and safety of opioid analgesics post-craniotomy. Nurs Crit Care 9:2772832004

  • 39

    Shea RABrooks JADayhoff NEKeck J: Pain intensity and postoperative pulmonary complications among the elderly after abdominal surgery. Heart Lung 31:4404492002

  • 40

    Stoneham MDCooper RQuiney NFWalters FJ: Pain following craniotomy: a preliminary study comparing PCA morphine with intramuscular codeine phosphate. Anaesthesia 51:117611781996

  • 41

    Strand LILjunggren AEBogen BAsk TJohnsen TB: The Short-Form McGill Pain Questionnaire as an outcome measure: test-retest reliability and responsiveness to change. Eur J Pain 12:9179252008

  • 42

    Tasmuth TKataja MBlomqvist Cvon Smitten KKalso E: Treatment-related factors predisposing to chronic pain in patients with breast cancer—a multivariate approach. Acta Oncol 36:6256301997

  • 43

    Toms LSheena DMoore RAMcQuay HJ: Single dose oral paracetamol (acetaminophen) with codeine for postoperative pain in adults. Cochrane Database Syst Rev 2009:CD0015472009

  • 44

    Tsui SLLaw SFok MLo JRHo EYang J: Postoperative analgesia reduces mortality and morbidity after esophagectomy. Am J Surg 173:4724781997

  • 45

    Voorhies RMJiang XThomas N: Predicting outcome in the surgical treatment of lumbar radiculopathy using the Pain Drawing Score, McGill Short Form Pain Questionnaire, and risk factors including psychosocial issues and axial joint pain. Spine J 7:5165242007

  • 46

    Wright KDAsmundson GJMcCreary DR: Factorial validity of the short-form McGill pain questionnaire (SF-MPQ). Eur J Pain 5:2792842001

Disclosures

The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Author Contributions

Conception and design: Titsworth, Guin, Bushwitz, Hurley, Seubert. Acquisition of data: Abram, Herman, West, Davis, Bushwitz, Seubert. Analysis and interpretation of data: Guin, Bushwitz, Seubert. Critically revising the article: Titsworth, Abram, Guin, Herman, Bushwitz, Hurley, Seubert. Reviewed submitted version of manuscript: all authors. Administrative/technical/material support: Davis.

Supplemental Information

Online-Only Content

Supplemental material is available with the online version of the article.

Previous Presentations

Portions of this work were presented in abstract form at the Annual Meeting of the Congress for Neurological Surgeons, Boston, Massachusetts, October 18–22, 2014.

If the inline PDF is not rendering correctly, you can download the PDF file here.

Article Information

INCLUDE WHEN CITING Published online March 11, 2016; DOI: 10.3171/2015.10.JNS15698.

Correspondence William Lee Titsworth, Department of Neurosurgery, University of Florida, Box 100265, Gainesville, FL 32610. email: wlt@ufl.edu.

© AANS, except where prohibited by US copyright law.

Headings

Figures

  • View in gallery

    Protocol process and outcome measures. A: Protocol compliance and POD1 pain scores. B: Aggregate NRS pain scores for all surgeries and specifically for craniotomies and spinal surgeries. ***p < 0.0001. C: Monthly postoperative NRS pain scores pre- and postintervention for craniotomies and spinal surgeries. D: Weekly aggregate pain scores for all patients admitted to the neurosurgery, orthopedic, or general surgery services. E: HCAHPS scores: pain management summary scores by quarter. F: T-chart showing the number of days between consecutive naloxone doses. A T-chart is a specialized control chart used for monitoring rare adverse events. Each point on the x-axis is a sequential administration of naloxone to a floor patient with times since previous administration represented on the y-axis.

References

1

Amtmann DCook KFJensen MPChen WHChoi SRevicki D: Development of a PROMIS item bank to measure pain interference. Pain 150:1731822010

2

Barakzoy ASMoss AH: Efficacy of the world health organization analgesic ladder to treat pain in end-stage renal disease. J Am Soc Nephrol 17:319832032006

3

Capdevila XBarthelet YBiboulet PRyckwaert YRubenovitch Jd'Athis F: Effects of perioperative analgesic technique on the surgical outcome and duration of rehabilitation after major knee surgery. Anesthesiology 91:8151999

4

Castel LDWilliams KABosworth HBEisen SVHahn EAIrwin DE: Content validity in the PROMIS social-health domain: a qualitative analysis of focus-group data. Qual Life Res 17:7377492008

5

Cella DYount SRothrock NGershon RCook KReeve B: The Patient-Reported Outcomes Measurement Information System (PROMIS): progress of an NIH Roadmap cooperative group during its first two years. Med Care 45:5 Suppl 1S3S112007

6

D'Arcy YJohann D: Using a medication protocol to improve pain management. Nurs Manage 39:35392008

7

DeWalt DARothrock NYount SStone AA: Evaluation of item candidates: the PROMIS qualitative item review. Med Care 45:5 Suppl 1S12S212007

8

Dolin SJCashman JNBland JM: Effectiveness of acute postoperative pain management: I. Evidence from published data. Br J Anaesth 89:4094232002

9

Fargen KMFriedman WA: The science of medical decision making: neurosurgery, errors, and personal cognitive strategies for improving quality of care. World Neurosurg 82:e21e292014

10

Fries JFBruce BCella D: The promise of PROMIS: using item response theory to improve assessment of patient-reported outcomes. Clin Exp Rheumatol 23:5 Suppl 39S53S572005

11

Furdon SAEastman MBenjamin KHorgan MJ: Outcome measures after standardized pain management strategies in postoperative patients in the neonatal intensive care unit. J Perinat Neonatal Nurs 12:58691998

12

Furdon SAPfeil VCSnow K: Operationalizing Donna Wong's principle of atraumatic care: pain management protocol in the NICU. Pediatr Nurs 24:3363421998

13

Gershon RCRothrock NHanrahan RBass MCella D: The use of PROMIS and assessment center to deliver patient-reported outcome measures in clinical research. J Appl Meas 11:3043142010

14

Giordano LAElliott MNGoldstein ELehrman WGSpencer PA: Development, implementation, and public reporting of the HCAHPS survey. Med Care Res Rev 67:27372010

15

Goldmann D: How can CLABSIs and cucumbers teach PDSA?. IHI Open School (http://www.ihi.org/education/IHIOpenSchool/resources/Pages/Activities/PDSACyclesFromCLABSIsToCucumbers.aspx

16

Goldmann D: How do you use a driver diagram?. IHI Open School (http://www.ihi.org/education/ihiopenschool/resources/Pages/Activities/GoldmannDriver.aspx

17

Gottschalk ABerkow LCStevens RDMirski MThompson REWhite ED: Prospective evaluation of pain and analgesic use following major elective intracranial surgery. J Neurosurg 106:2102162007

18

Grafton KVFoster NEWright CC: Test-retest reliability of the Short-Form McGill Pain Questionnaire: assessment of intraclass correlation coefficients and limits of agreement in patients with osteoarthritis. Clin J Pain 21:73822005

19

Gupta ADaigle SMojica JHurley RW: Patient perception of pain care in hospitals in the United States. J Pain Res 2:1571642009

20

Gust RPecher SGust AHoffmann VBöhrer HMartin E: Effect of patient-controlled analgesia on pulmonary complications after coronary artery bypass grafting. Crit Care Med 27:221822231999

21

Hung MClegg DOGreene TSaltzman CL: Evaluation of the PROMIS physical function item bank in orthopaedic patients. J Orthop Res 29:9479532011

22

Janssen KJKalkman CJGrobbee DEBonsel GJMoons KGVergouwe Y: The risk of severe postoperative pain: modification and validation of a clinical prediction rule. Anesth Analg 107:133013392008

23

Jeffrey HMCharlton PMellor DJMoss EVucevic M: Analgesia after intracranial surgery: a double-blind, prospective comparison of codeine and tramadol. Br J Anaesth 83:2452491999

24

Jirarattanaphochai KJung S: Nonsteroidal antiinflammatory drugs for postoperative pain management after lumbar spine surgery: a meta-analysis of randomized controlled trials. J Neurosurg Spine 9:22312008

25

Katz JJackson MKavanagh BPSandler AN: Acute pain after thoracic surgery predicts long-term post-thoracotomy pain. Clin J Pain 12:50551996

26

Klimek MUbben JFAmmann JBorner UKlein JVerbrugge SJ: Pain in neurosurgically treated patients: a prospective observational study. J Neurosurg 104:3503592006

27

Lee KJMin BWBae KCCho CHKwon DH: Efficacy of multimodal pain control protocol in the setting of total hip arthroplasty. Clin Orthop Surg 1:1551602009

28

McDonald DDWeiskopf CS: Adult patients' postoperative pain descriptions and responses to the Short-Form McGill Pain Questionnaire. Clin Nurs Res 10:4424522001

29

Melzack R: The short-form McGill Pain Questionnaire. Pain 30:1911971987

30

Michel MZSanders MK: Effectiveness of acute postoperative pain management. Br J Anaesth 91:4484492003

31

Pandey CKNavkar DVGiri PJRaza MBehari SSingh RB: Evaluation of the optimal preemptive dose of gabapentin for postoperative pain relief after lumbar diskectomy: a randomized, double-blind, placebo-controlled study. J Neurosurg Anesthesiol 17:65682005

32

Pandey CKSahay SGupta DAmbesh SPSingh RBRaza M: Preemptive gabapentin decreases postoperative pain after lumbar discoidectomy. Can J Anaesth 51:9869892004

33

Quiney NCooper RStoneham MWalters F: Pain after craniotomy. A time for reappraisal?. Br J Neurosurg 10:2952991996

34

Rahimi SYVender JRMacomson SDFrench ASmith JRAlleyne CH Jr: Postoperative pain management after craniotomy: evaluation and cost analysis. Neurosurgery 59:8528572006

35

Rajpal SGordon DBPellino TAStrayer ALBrost DTrost GR: Comparison of perioperative oral multimodal analgesia versus IV PCA for spine surgery. J Spinal Disord Tech 23:1391452010

36

Revicki DAChen WHHarnam NCook KFAmtmann DCallahan LF: Development and psychometric analysis of the PROMIS pain behavior item bank. Pain 146:1581692009

37

Revicki DAKawata AKHarnam NChen WHHays RDCella D: Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample. Qual Life Res 18:7837912009

38

Roberts G: A review of the efficacy and safety of opioid analgesics post-craniotomy. Nurs Crit Care 9:2772832004

39

Shea RABrooks JADayhoff NEKeck J: Pain intensity and postoperative pulmonary complications among the elderly after abdominal surgery. Heart Lung 31:4404492002

40

Stoneham MDCooper RQuiney NFWalters FJ: Pain following craniotomy: a preliminary study comparing PCA morphine with intramuscular codeine phosphate. Anaesthesia 51:117611781996

41

Strand LILjunggren AEBogen BAsk TJohnsen TB: The Short-Form McGill Pain Questionnaire as an outcome measure: test-retest reliability and responsiveness to change. Eur J Pain 12:9179252008

42

Tasmuth TKataja MBlomqvist Cvon Smitten KKalso E: Treatment-related factors predisposing to chronic pain in patients with breast cancer—a multivariate approach. Acta Oncol 36:6256301997

43

Toms LSheena DMoore RAMcQuay HJ: Single dose oral paracetamol (acetaminophen) with codeine for postoperative pain in adults. Cochrane Database Syst Rev 2009:CD0015472009

44

Tsui SLLaw SFok MLo JRHo EYang J: Postoperative analgesia reduces mortality and morbidity after esophagectomy. Am J Surg 173:4724781997

45

Voorhies RMJiang XThomas N: Predicting outcome in the surgical treatment of lumbar radiculopathy using the Pain Drawing Score, McGill Short Form Pain Questionnaire, and risk factors including psychosocial issues and axial joint pain. Spine J 7:5165242007

46

Wright KDAsmundson GJMcCreary DR: Factorial validity of the short-form McGill pain questionnaire (SF-MPQ). Eur J Pain 5:2792842001

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