MAST Trial: Multi-modal Analgesic Strategies in Trauma
Phase: PHASE4
Conditions: Nonspecific Pain Post Traumatic Injury
Sponsor: The University of Texas Health Science Center, Houston

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
MAST Trial: Multi-modal Analgesic Strategies in Trauma 
 
NCT03472469 
 
Version Date: 03/02/2018 
 
 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
Protocol Title: 
MAST Trial: Multi-modal Analgesic Strategies in Trauma 
 
Principal Investigator: 
John A. Harvin, MD, FACS 
Assistant Professor of Surgery 
Faculty, Center for Translational Injury Research (CeTIR) 
 
Co-Investigators: 
Lillian S. Kao, MD, MS 
Professor of Surgery 
 
Charles E. Wade, PhD 
Professor of Surgery 
Director, CeTIR 
 
Study Coordinator: 
Jeanette Podbielski, R.N. 
Research Project Manager 
 
Population: 
Adult trauma patients admitted to the Trauma Service at Memorial 
Hermann Hospital-Texas Medical Center (MHH-TMC) 
 
Number of Sites: 
Single center, MHH-TMC 
 
Study Duration: 
One year 
 
Subject Duration: 
Time while hospitalized 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
Table of Contents 
General Information ........................................................................................................................ 3 
Background Information ................................................................................................................. 3 
Objectives ....................................................................................................................................... 4 
Study Design ................................................................................................................................... 5 
Study Population ............................................................................................................................. 7 
Study Procedures ............................................................................................................................ 7 
Statistics .......................................................................................................................................... 8 
Ethics............................................................................................................................................... 9 
Data Handling and Record Keeping ............................................................................................... 9 
Quality Control and Assurance ....................................................................................................... 9 
Publication Plan ............................................................................................................................ 10 
References ..................................................................................................................................... 10 
Supplement One: Data .................................................................................................................. 12 
 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
General Information 
 
The optimal strategy for providing effective and safe pain management after traumatic 
injury remains unknown. Although opioids have been a mainstay for pain management for 
decades, they have been increasingly recognized to be related to increased adverse events, 
increased costs and resource utilization, long-term dependence or addiction, and death. While 
opioid-minimizing, multi-modal analgesic strategies are promising, there is no high-quality 
evidence to guide their use or implementation. The proposed project is a randomized 
comparative effectiveness study of current pain management strategies in acutely injured trauma 
patients. A parallel group, randomized trial of two different multi-modal, opioid minimizing 
analgesic strategies will be performed and analyzed using Bayesian statistics. 
 
 
Background Information 
 
Opioid prescribing 
practices after traumatic 
injuries and surgeries are a 
significant driver of the 
current opioid epidemic. 
Over the last two decades, 
75% of patients seeking 
treatment for heroin 
addiction were introduced to 
opioids via prescription 
drugs.[1] 
In particular, 
surgeons have a high rate of 
opioid prescribing (36.5%), 
second only to pain 
medicine specialists.[2] The 
incidence of persistent 
opioid use in opioid-naïve 
patients after minor and 
major surgery is 6%, although rates can range as high as 24% in surgical sub-specialties such as 
orthopedics.[3, 4] Furthermore, the link between prescription opioids and transition to heroin 
has resulted in a significant rise in opioid-related deaths, which are now more common than 
deaths due to motor vehicle-related injuries (Figure 1).[5] 
Pain control after trauma must be timely and effective in order to allow patients earlier 
mobilization and improved functional status. Due to their injuries, 59% of trauma patients 
experience moderate to severe pain and, in 73% of patients, this pain interferes with activity 
during their acute hospitalization.[6] Pain control after traumatic injury must also be safe. 
Traditionally, pain regimens have relied on the administration of narcotics; however opioid- 
based analgesic strategies are associated with significant short- and long-term adverse 
consequences. In the short-term, opioid-related adverse events include respiratory failure, urinary 
Figure 1: Opioid and heroin-related deaths exceed those due 
to motor vehicle collisions (MVC). From the Centers for 
Disease Control and Prevention and Insurance Institute for 
Highway Safety 
1999 
2000 
2005 
2010 
2011 
2012 
2013 
2014 
2015 
All Opioid/Heroin 
Deaths 
All MVC Deaths 
 
 
 
 
18 
16 
14 
12 
10 
8 
6 
4 
2 
0 
Deaths per 100,000 People in the United States by Year 
Deaths per 100,000 People 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
retention, ileus, and constipation.[7] In the long-term, opioid addiction and opioid-related deaths 
may result. In addition, adequacy of pain control as measured by pain scores is increasingly 
being used as a patient-centered outcome and evidence suggests that there is a lack of equity in 
pain management based on socioeconomic status, race, age, and gender.[8-10] While multi- 
modal analgesia is a promising strategy to reduce opioid use, it is unknown if this is the most 
efficient and cost-effective strategy for post-trauma pain control. 
 
Preliminary Data 
 
Multi-modal analgesic regimens have sought to minimize reliance on opioids for pain 
control by utilizing combinations of medications from different drug classes including non- 
steroidal anti-inflammatory drugs (NSAIDs), gabapentinoids, weak mu agonists, and central 
prostaglandin inhibitors. In 2013, our trauma service introduced a multi-modal analgesic 
regimen. Traumatically injured patients were immediately started on scheduled pain medications 
from each of the different drug classes. While this idea of a multi-modal strategy decreased mean 
opioid use in morphine milligram equivalents (MME) per patient per day (Table 1), there was 
and continues to be significant heterogeneity in the actual regimens prescribed by surgeons. 
 
Trauma Service Line Use of Pain Medications per Fiscal Year of Various Classes of Pain Medication 
FY 13 
FY 14 
FY 15 
FY 16 
FY 17 
Morphine milligram equivalents 
(oral opioids only) 
1,936,955 
1,566,248 
1,155,619 
948,088 
850,678 
Morphine milligram 
equivalents/patient day (oral 
opioids only) 
63 
49 
38 
29 
28 
NSAID mg/patient day 
92 
160 
181 
186 
271 
Gabapentinoids mg/patient 
day 
146 
293 
464 
550 
665 
Tramadol mg/patient day 
43 
121 
168 
159 
162 
Acetaminophen mg/patient 
day 
684 
1,048 
1,455 
2,144 
2,438 
Table 1: Implementation of a multi-modal analgesic strategy has resulted in halving of the 
use of oral opioids accompanied by a concomitant increase in the use of acetaminophen, 
NSAIDs, gabapentinoids, and tramadol. 
 
 
Objectives 
 
Aim 1: 
To perform a parallel group, randomized controlled trial comparing two 
multimodal pain strategies on clinical outcomes, patient-reported outcomes, and 
resource utilization 
Aim 2: 
To better understand the effect of the different multi-modal strategies by 
evaluating heterogeneity of treatment effect by performing hypothesis-testing and 
hypothesis-generating subgroup analyses to identify characteristics associated 
with the need for one strategy over the other 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
10/31/13    2/8/14 
5/19/14     8/27/14     12/5/14     3/15/15  6/23/15    10/1/15 
1/9/16 
Institutional Review Board Submission 
Data Collection Instrument Creation 
Patient Recruitment 
Protocol Publication 
Data Analysis 
Manuscript Preparation 
RO1 Grant Preparation and Submission 
Study Design 
 
This pragmatic, single-blind, randomized trial will be conducted at the Red Duke Trauma 
Institute at MHH-TMC. 
 
Study Arms: Treatment Strategies 
 
Treatment Strategy #1 
Treatment Strategy #2 
First 48 hours 
Thereafter 
Admission and thereafter 
Central Prostaglandin Inhibitor 
Acetaminophen 1g 
IV/PO q6 hours 
Acetaminophen 1g 
PO q6 hours 
Acetaminophen 1g PO q6 
hours 
NSAID COX Inhibitor 
Ketorolac 30mg IV 
once 
Celebrex 200mg PO 
q12 hours 
Naproxen 500mg PO 
q12 hours 
Ketorolac 30mg IV once 
Naproxen 500mg PO q12 
hours 
Weak Mu Opioid Agonist 
Tramadol 100mg PO 
q6 hours 
Tramadol 100mg PO 
q6 hours 
None 
Gabapentinoid 
Pregabalin 100mg PO 
q8 hours 
Gabapentin 300mg 
PO q8 hours 
Gabapentin 300mg PO q8 
hours 
Local anesthetics 
Lidocaine patch q12 
hours 
Lidocaine patch q12 
hours 
Lidocaine patch q12 hours 
PRN medications 
Opioids 
Regional anesthesia 
Opioids 
Regional anesthesia 
Tramadol 
Opioids 
Regional anesthesia 
Dosing, dose adjustments, and contra-indications used are available at: https://med.uth.edu/surgery/acute-trauma- 
pain-multimodal-therapy/ 
 
Setting 
This study will be conducted at the Texas Trauma Institute at Memorial Hermann 
Hospital-Texas Medical Center (MHH-TMC). It is one of two Level 1 trauma centers in the 
Houston metropolitan area, an area in which over 6 million people reside, and is the busiest 
trauma center in the country, with approximately 2,000 admissions to the adult Trauma Service 
per year. 
 
Time Period 
IRB submission for the study will occur in December 2017. Enrollment of eligible 
patient will begin in April 2018 and continue for 12 months. 
 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
Outcomes 
The primary outcome of the study is opioid use per day until discharge or 30 days post 
admission (whichever is sooner), calculated by tallying the MME of all opioids received and 
dividing by the number of days hospitalized. This outcome captures the effectiveness of the 
combined non-opioid medications in not only achieving pain control but also in reducing opioid 
administration. 
 
The secondary outcomes of the study include: 
 Pain scores until discharge or 30 days post 
admission (whichever is sooner): an average 
will be calculated of the average daily numeric 
rating scale of pain (0=no pain, 10=worst 
pain). 
o Pain scores are currently recorded by 
nursing staff at standard intervals based 
upon the patient’s level of care. 
o The numeric rating scale of pain is already 
assessed by nurses multiple times per day 
at hospitals across the United States, 
including Memorial Hermann Hospital- 
Texas Medical Center, and will not require 
additional training or man power to collect. 
 Discharge from the hospital with an opioid 
prescription 
 Incidence of opioid-related complications, 
such as ileus, aspiration, unplanned intubation, 
unplanned admission to an intensive care unit, 
and use of an opioid-reversal agent. 
o Until discharge or 30 days post admission (whichever is sooner) 
o Measures of safety 
o Some of these complications are already recorded by the Trauma Quality 
Improvement Project (TQIP) and the hospital as a core measure. 
 Costs: overall and pharmacy costs 
 Lengths of stay: ventilator-/hospital-/ICU-free days 
 Measures of function that may be limited by pain, such as percent of predicted daily 
incentive spirometry volumes (which is based on ideal body weight) and failure to 
work with physical therapy due to pain (until discharge or 30 days post admission 
[whichever is sooner]) 
 
Study Population 
 
Screening 
All adult patients (≥16 years) arriving to the trauma center and admitted to the trauma 
service will be screened for eligibility in the study. Clinical research staff are available on a 24/7 
basis to conduct screening and collect data on those patients meeting inclusion criteria. Research 
Opioid 
Conversion 
Factor 
Oral Opioids 
Codeine (mg) 
0.15 
Tramadol (mg) 
0.1 
Hydrocodone (mg) 
1 
Oxycodone (mg) 
1.5 
Methadone 
1-20 mg/day 
4 
21-40 mg/day 
8 
41-60 mg/day 
10 
≥61-80mg/day 
12 
Morphine (mg) 
1 
Hydromorphone (mg) 
4 
Transdermal Opioids 
Fentanyl (mcg/hr) 
2.4 
Intravenous Opioids 
Morphine (mg) 
3 
Hydromorphone (mg) 
15 
Fentanyl (mcg) 
0.2 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
staff will inform the physicians of randomization allocation and drug regimen/dosages. All 
patient care aspects other than the randomization to multimodal treatment strategy will follow 
the MHH-TMC policies and guidelines. 
 
Inclusion/Exclusion Criteria 
Patients will be excluded if they are a pediatric patient (<16 years), pregnant, or a 
prisoner. Additionally, patients placed in observation (i.e. not admitted to the hospital) will be 
excluded. While certain patients may have contraindications for select drug classes (e.g. NSAID 
contraindicated in acute kidney injury, tramadol contraindicated in patients with seizures, 
acetaminophen contraindicated in Child’s C cirrhosis), patients will not be excluded based on 
these individual drug contraindications. Randomization should balance these patients in both 
treatment strategies. 
If a patient meets inclusion criteria without any exclusion criteria, they will be 
randomized in the Emergency Department so that medications can be ordered and administered 
as quickly as possible. 
 
Study Procedures 
 
Randomization 
Allocation will occur through sequentially numbered, opaque envelopes kept in the 
research assistants’ office in the emergency department. Envelopes will be opened upon trauma 
resident writing admission orders in the Emergency Department An independent statistician will 
determine the randomization sequence and oversee the labeling of cards and envelopes. 
Randomization will be stratified by unit of admission (ICU, IMU, floor). 
 
Data Collection 
Data collection will occur by one of two methods: manual entry or automatic capture of 
data. Data points to be collected are detailed in Supplement One. 
Supplement One also indicates the manner by which data points will be collected – 
manually, from National Trauma Data Base registry, or automatic capture from the electronic 
medical record. 
 
Follow up 
No study-specific follow-up will be required. 
 
Statistics 
Sample Size 
The function of this preliminary study is to provide the most precise, unbiased estimate of 
treatment effect possible. The precision of this estimate is largely a function of sample size. As 
such our goal is to conduct the largest feasible study in a 12 month period upon which to base 
these estimates. We believe we will be able to enroll 75% of admissions to the trauma service, 
which would be approximately 1,506 patients in the 12 month period. 
% 
Enrollment 
Total 
Accrual 
50% 
1,004 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
The trauma center is one of the busiest in the United States. Of 
patients who come to the trauma center, the number of patients admitted 
to the adult trauma surgery service are: 1,974 (FY 2015), 2,022 (FY 
2016), and 2,026 (FY 2017). This equates to 167 patients admitted per 
month. 
The table to the right estimates total patient accrual in a 12 month period assuming 
multiple rates of enrollment. 
 
Data Analysis Plan 
We plan a Bayesian statistical approach for three reasons: 
 
1) At an early stage in the development and implementation of an intervention, 
investigators must decide whether to invest further time and resources on a specific 
approach given the data they have thus far observed. Fundamentally, this requires 
evaluation of the probability that the alternative hypothesis is true (i.e. the probability that 
an effect of some magnitude exists). Frequentist approaches to statistical reasoning do not 
directly estimate the probability of the alternative hypothesis, focusing instead on the 
rejection of the null; 
2) Bayesian approaches combine any salient prior information with the observed data to 
form a posterior distribution which then captures the current state of the evidence for the 
probability that an effect of some magnitude exists. This posterior distribution may then 
function as an empirically derived, informative prior that provides information in the 
evaluation of subsequent samples. This permits the analyses from the current project to 
inform the design and analysis of subsequent studies; 
3) the process of updating a prior with data provides a mechanism for continued 
monitoring of an established program for quality control purposes. 
 
The following data analytic approach applies to evaluation Aims 1 and 2, though we 
present it only once to conserve space. Broadly, the data analytic strategy will use generalized 
linear multilevel modeling with level-two random effects to account for clustering of participants 
within site and, where applicable, observations within participants. Modeling will use R v. 3.4 
and Stan v. 1.10.[11, 12]. Initial analyses examining group differences for baseline variables will 
use cross-tabulation, ANOVA’s, and examination of correlations between baseline variables and 
specified outcomes. For the purposes of evaluating the comparability of groups, a posterior 
probability of > 95% will constitute evidence for statistically reliable differences. Baseline or 
demographic variables on which group differences are detected and which are correlated with 
outcomes meet the definition of confounders and will result in two sets of analyses: one in which 
the relevant variable is included as a covariate and one in which it is not.[13, 14] This will 
permit determination of the degree to which any group differences might confound conclusions 
regarding treatment. 
All analyses will be conducted on an intention-to-treat basis. Bayesian approaches will 
implement joint modeling of observed outcomes and the missing data which is robust to 
ignorable missingness (i.e., MCAR and MAR).[15] Sensitivity analyses will evaluate robustness 
of analytic conclusions to missing data. Non-ignorable missing data patterns will be addressed 
through pattern-mixture modeling methods.[16] Convergence of Bayesian analyses on the 
posterior distributions via Monte-Carlo Markov chain (MCMC) will be assessed via graphical 
60% 
1,204 
70% 
1,405 
75% 
1.506 
80% 
1.606 
90% 
1.807 
100% 
2,007 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
(Gelman-Rubin Plots) and quantitative (Gelman-Rubin Diagnostics and Effective Sample Size) 
evidence. Evaluation of posterior distributions will permit statements regarding the probability 
that effects of varying magnitudes exist, given the data. Specification of diffuse, neutral priors 
will reflect the initial uncertainty regarding effect sizes. For all generalized linear multilevel 
models, priors for regression coefficients will be specified as ~Normal (µ=0, σ2=10) on the 
identity or log-scale depending upon the model, level one error variances will be specified as 
~Half-T (df = 3, mean = 0, standard deviation = 100). Prior distribution for level two variances 
will use ~Half-T (df = 3, mean = 0, standard deviation = 10). Priors for the comparison of 
proportions will be specified as ~Beta (α=0.5, β=0.5). For all subgroup analyses using multilevel 
models the approach will follow that used in Tyson, et al.[17] 
 
Ethics 
 
Due to the acute clinical status of the trauma patient population (intubation, intoxication, 
severe pain), it is often not feasible to obtain truly informed consent from a patient or legally 
authorized representative (LAR) before pain medications are prescribed. Therefore, we will use 
delayed consent. The patient will be randomized and enrolled prior to consent. 
Once the patient is enrolled, a member of the trauma research team will make attempts to 
contact either the patient or LAR to obtain consent for this study. Consents will be obtained by 
trained research personnel Monday through Friday during the day. If a consent needs to be 
obtained on the weeknight or weekend, research personnel will be available. Once appropriate to 
approach the patient for consent, a study team member will explain the study, its implications for 
the patient, and give the patient written study information. Additionally, an educational pamphlet 
on safe opioid use will be given to the patient. 
If the subject consents to participation, they will sign the consent document. If the subject 
refuses, data collection will stop at time of refusal. 
Due to the high enrollment rate, the study team will attempt to inform and consent the 
patients/LARs for at least five days. If, after 5 days, the patient remains unable to self-consent 
and no LAR is available to consent, the consent will be waived and data included. Additionally, 
if the subject does not survive following the traumatic injury or is discharged from the hospital 
before the study team is able to obtain consent, their information will be included in the data 
analysis. 
 
Data Handling and Record Keeping 
 
If data is to be extracted by hand, it will be entered into a standardized case report form 
and entered into a RedCap™ database. Each subject will be assigned a study-specific number. 
Data will be collected until hospital discharge. 
All hard copy source documentation will be kept in a secured, locked cabinet in the 
research coordinator’s office. All study documents will be maintained in a secure location for 
two years following study completion. 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
Quality Control and Assurance 
 
Each item on the web forms will have validity checks performed to ensure that the data 
entered are accurate and that items are not skipped during entry by mistake. Bi-weekly audits of 
data will be performed by both clinical investigators and research assistants. 
 
Publication Plan 
Planned publications include the following: 
(1) Protocol paper detailing the proposed project; 
(2) Clinical results paper of randomized controlled study 
 
References 
 
1. 
Cicero, T.J., et al., The changing face of heroin use in the United States: a retrospective 
analysis of the past 50 years. JAMA Psychiatry, 2014. 71(7): p. 821-6. 
2. 
Levy, B., et al., Trends in Opioid Analgesic-Prescribing Rates by Specialty, U.S., 2007- 
2012. Am J Prev Med, 2015. 49(3): p. 409-13. 
3. 
Brummett, C.M., et al., New Persistent Opioid Use After Minor and Major Surgical 
Procedures in US Adults. JAMA Surg, 2017. 152(6): p. e170504. 
4. 
Jiang, X., et al., Chronic Opioid Usage in Surgical Patients in a Large Academic Center. 
Ann Surg, 2017. 265(4): p. 722-727. 
5. 
Unick, G.J., et al., Intertwined epidemics: national demographic trends in 
hospitalizations for heroin- and opioid-related overdoses, 1993-2009. PLoS One, 2013. 
8(2): p. e54496. 
6. 
Archer, K.R., et al., Pain and satisfaction in hospitalized trauma patients: the importance 
of self-efficacy and psychological distress. J Trauma Acute Care Surg, 2012. 72(4): p. 
1068-77. 
7. 
Oderda, G.M., et al., Opioid-related adverse drug events in surgical hospitalizations: 
impact on costs and length of stay. Ann Pharmacother, 2007. 41(3): p. 400-6. 
8. 
Joynt, M., et al., The impact of neighborhood socioeconomic status and race on the 
prescribing of opioids in emergency departments throughout the United States. J Gen 
Intern Med, 2013. 28(12): p. 1604-10. 
9. 
Hwang, U., et al., The quality of emergency department pain care for older adult 
patients. J Am Geriatr Soc, 2010. 58(11): p. 2122-8. 
10. 
Hollingshead, N.A., et al., Impact of race and sex on pain management by medical 
trainees: a mixed methods pilot study of decision making and awareness of influence. 
Pain Med, 2015. 16(2): p. 280-90. 
11. 
Team, R.C., R: A Language and Environment for Statistical Computing. 2017, R 
Foundation for Statistical Computing: Vienna, Austria. 
12. 
Team., S.D., RStan: the R interface to Stan: Stan Development Team. 2017, Available 
from: http://mc-stan.org . 
13. 
Assmann, S.F., et al., Subgroup analysis and other (mis)uses of baseline data in clinical 
trials. Lancet, 2000. 355(9209): p. 1064-9. 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
14. 
Pocock, S.J., et al., Subgroup analysis, covariate adjustment and baseline comparisions 
in clinical trial reporting: Current practice and problems. Statistics in Medicine, 2002. 
21: p. 2917-2930. 
15. 
Best, N. and A.E.p.-. Thomas, Bayeisan Graphical Models and Software for GLMs, in 
Generalized Linear Models: A Bayesian Perspective, D. Dey, S.K. Ghosh, and B.K. 
Mallick, Editors. 2000, Marcel Dekker, Inc.: New York. 
16. 
Fitzmaurice, G.M. and N.M. Laird, Generalized linear mixture models for handling 
nonignorable dropouts in longitudinal studies. Biostatistics, 2000. 1: p. 141-156. 
17. 
Tyson, J.E., et al., Does aggressive phototherapy increase mortality while decreasing 
profound impairment among the smallest and sickest newborns? J Perinatol, 2012. 32(9): 
p. 677-84. 

IRB NUMBER: HSC-MS-18-0036 
IRB APPROVAL DATE: 03/02/2018 
 
Supplement One: Data 
 
Variable 
RedCap 
From Registry/NTDB 
Electronic Data 
Withdrawal 
Demographics 
 Age 
 Sex 
 Race 
 Prior opioid use 
Injury Information 
 Mechanism of injury 
 Specific injuries: 
- Total number ribs with a fracture 
(0-24) (two or more fractures in 
a single rib counts as 1) 
- Flail chest 
- Long bone fracture (radius, ulna, 
humerus, femur, tibia, fibula) 
- Vertebral body fracture 
- Laparotomy 
- Thoracotomy 
- Amputation 
- Any pelvis/acetabular fracture 
 AIS values 
 ISS 
Opioid Specific 
 Discharge opioid status 
 Regional anesthetic used 
 Daily morphine 
milligram equivalents 
 Pain scores 
Complications 
 Ileus 
 Cardiac arrest 
 Unplanned 
admission to ICU 
 Unplanned 
intubation 
Hospital Stay 
 Hospital length of 
stay 
 ICU length of stay 
 Ventilator days 
 Mortality