Abstract
In order to study the impact of anesthesia opioid-related outcomes and acute and chronic post-surgical pain, we organized a multi-center study that comprehensively combined detailed perioperative data elements from multiple institutions. By combining pre- and post-operative patient reported outcomes with automatically extracted high resolution intra-operative data obtained through the Multicenter Perioperative Outcomes Group (MPOG), the authors sought to describe the impact of patient characteristics, pre-operative psychological factors, surgical procedure, anesthetic course, post-operative pain management, and post-discharge pain management on post-discharge pain profiles and opioid consumption patterns. This study is unique in that it utilized multi-center prospective data collection using a digital case report form integrated with the MPOG framework and database. Therefore, the study serves as a model for future studies using this innovative method. Full results will be reported in future papers; the purpose of this paper is to describe the methods of this study.
Introduction
Recent evidence suggests that surgery increases the risk of developing chronic opioid dependence.1, 2 Clarke et al. reported a 3.1% risk of prolonged opioid use (> 90 days after surgery) among 39,140 opioid-naïve patients who underwent surgery,2 while Brummett et al. reported 6%.3 There are currently no studies that have comprehensively combined detailed perioperative data with information about patient psychological factors, perioperative pain management strategies and pain profiles, and discharge opioid prescription patterns in order to study their summative impact on prolonged and excessive opioid use and the development of chronic pain in patients undergoing major surgery.
A multi-center study was organized to accomplish this by combining in-person perioperative patient observations with automatically extracted high resolution intra-operative data collected by the Multicenter Perioperative Outcomes Group (MPOG).4,5 The MPOG database allows extraction of detailed perioperative and administrative data from more than 10 million anesthetic cases performed at MPOG institutions This study is unique in that it will utilize multi-center prospective data collection using a digital case report form integrated with the MPOG framework and large clinical registry data mining. This study is also novel in that multiple retrospective studies have been published using MPOG data; however this is the first MPOG study to prospectively recruit patients and collect enhanced observational data. Future investigators may be interested in utilizing a similar study design. In order to address the growing interest in combining manually collected data with large clinical databases and to be able to refer to this complex methodology, we are reporting the comprehensive methodology as a standalone manuscript. Results will be reported in future papers; the purpose of this paper is to describe the methods of this study.
Methods
MPOG Enhanced Observational Study (EOS) Request for Proposals and Application Process
Proposals were solicited for the “Enhanced” Observational Study (EOS) process across member institutions to integrate the existing MPOG automated data collection infrastructure with a focused, prospective observational data collection component. The EOS study expected participating MPOG institutions to dedicate a two- to four-week period to shift existing research personnel and collect additional data elements that were not reliably extracted from the electronic medical record (EMR) or administrative systems. Initially one page letters of intent were submitted with the top nine invited to submit full research proposals by the MPOG executive board. Three proposals were selected for oral presentation and final scoring by the MPOG Perioperative Clinical Research Committee (PCRC). The winning proposal was ratified by the MPOG executive board in February, 2017. This report provides a detailed description of the methodology for the first EOS study, “Postoperative Pain Profiles, Analgesic Use, and Transition to Chronic Pain and Excessive and Prolonged Opioid Use Patterns.”
Organizing the Effort
Recruitment and Management of Participating Sites
All MPOG member institutions that were actively contributing data were invited (via email, via the MPOG website, and during the regular PCRC meetings) to participate in this EOS study. Participating institutions would have access to the type of data they would contribute, contingent on PCRC peer-review of their request. Authorship rules followed the precedents established for all MPOG research studies (data contribution, participation in PCRC peer-review, approval of the proposed project, and analytical/editorial duties) and International Committee of Medical Journal Editors (ICMJE) guidelines.
Study Protocol Development and Timeline
Weekly 1-hour conference calls were held with the EOS coordinating centers (University of Utah, University of Michigan, and University of Virginia) to develop the protocol for data collection and analysis. The protocol was refined during bi-monthly 30-minute conference calls with participating sites. Protocol development and refinement was performed in February of 2017. The protocol was finalized and approved by the MPOG PCRC on February 13, 2017. Study training was performed via a web conference.
Data Collection Timeline
Data collection time points and record completion is described in the results section and are shown in Figure 1.
Figure 1.
Process Timeline
Organizing Institutional Review Board Approval
The University of Utah is one of three Trial Innovation Centers (TIC) in the United States funded by the National Institutes of Health (NIH).6 Part of the $25 million funding is allocated to the Institutional Review Board (IRB) at the University of Utah, which served as a single IRB (SIRB) for this study.7 Smart IRB members have arrangements in place to use single center (in this case the University of Utah) IRB approved documents. The IRB process was initiated at the University of Utah in late February 2017. Approval at all sites was finalized in August 2017. The University of Utah SIRB and individual institutions’ IRBs approved using a waiver of documentation of informed consent or full consent.
Study Design
Outcomes
The primary outcomes of this study are opioid consumption and pain at three months after surgery. Secondary outcomes include opioid consumption and pain at one-month after surgery and intra-operative opioid and non-opioid analgesic administration. Regression models of primary and secondary outcomes are planned to assess associations between outcomes and basic MPOG pre-operative and intra-operative data and EOS special purpose pre-operative, post-operative and post-discharge data. The outcomes were defined during protocol development, i.e., prior to data collection and prior to any data analysis, in keeping with best practices outlined by Eisenach et al.8
Inclusion and Exclusion Criteria
Patients are included if they received general or regional anesthesia for total hip or knee replacement, spine surgery, open thoracic procedures, mastectomy, or abdominal surgery (including laparoscopic surgery).3, 9–12 Exclusion criteria include minor surgery requiring only monitored anesthesia care or local anesthesia, cardiac surgery, and intracranial and other surgeries with the potential for prolonged cognitive dysfunction. Patients are excluded from participation if they were enrolled in an independent randomized clinical trial (RCT), which does not allow co-enrollment in an observational study or which involved blinded drugs or interventions that are relevant to this MPOG EOS study.
Sample size planning
No formal sample size planning was performed due to lack of known effect size of operative factors on the outcomes of interest. Therefore, an additional outcome of interest in this study is the effect size of perioperative data on the primary and secondary outcomes to enable powering of future studies. Enrollment of 150 patients per participating institution per week in each of the two weeks of in-hospital data collection is expected. We estimate that if ten institutions participated, the total size of the convenience sample would be 3,000 patients.
Patient Enrollment
Eligible patients are identified using the surgical schedule and enrolled during the patients’ pre-operative preparation for surgery in the pre-operative waiting area / surgical admissions suites. A list of 415 Current Procedural Terminology (CPT) codes is used by study personnel to prescreen for eligibility. Enhanced observational data are collected from patient surveys and manually retrieved from the electronic medical record as described below.
EOS Data
Pre-operatively, information is collected on physical characteristics and demographics, home opioid and non-opioid analgesic medications and brief, validated questionnaires: Pain intensity using the Brief Pain Inventory severity questions for pain at the site of surgery and overall body pain;12 2011 Fibromyalgia Survey Criteria assesses for comorbid central nervous system symptoms using the Symptom Severity Index and widespread pain using the Michigan Body Map;13,14 Patient Reported Outcome Measurement System (PROMIS) Physical Function short form 4a,15 PROMIS Anxiety short form 4a,15 PROMIS Depression short form 4a,15 PROMIS Sleep Disturbance short form 5a,15 catastrophizing (Thoughts about Symptoms), and Expectations of Surgery. Questionnaires are administered on paper and in-person to participants.
At one-month and three-months post-operatively, enrolled patients are asked in brief phone interviews about opioid and non-opioid analgesic medication, pain at the site of surgery, overall body pain, symptom severity index, Michigan Body Map, PROMIS Physical function short form 4a, PROMIS Anxiety short form 4a, PROMIS Depression short form 4a, PROMIS sleep disturbance short form 5a, and catastrophizing. Interview duration is estimated to be 10 minutes based on previous studies utilizing a similar questionnaire set.3, 16
Additionally, questions are asked to determine satisfaction with surgery and adverse events. Questionnaires are provided in Supplemental Appendix 1. Table 1 shows the type of data collected pre-operatively, post-operatively, and in the phone interviews. Answers to survey questions are recorded by the data collectors into a web-based survey form developed by the MPOG consortium or onto a paper form and later transcribed into the web-based survey form.
Table 1.
Data Collection
| Timepoint | |||||
|---|---|---|---|---|---|
| Screening | Pre-Operative | Post-Operative | One-Month | Three-Month | |
| Age | Self-Report | Self-Report | |||
| Gender | Self-Report | Self-Report | |||
| Height | EMR | Self-Report | |||
| Weight | EMR | Self-Report | |||
| ASA Physical Status | EMR | ||||
| Baseline Opioid Assessment | Self-Report | ||||
| Demographics | Self-Report | ||||
| Ethnicity | Self-Report | ||||
| Race | Self-Report | ||||
| Relationship Status | Self-Report | ||||
| Education | Self-Report | ||||
| Occupational Status | Self-Report | ||||
| Pain at Site of Surgery | Self-Report | Self-Report | Self-Report | ||
| Overall Body Pain | Self-Report | Self-Report | Self-Report | ||
| Symptom Severity Index | Self-Report | ||||
| Michigan Body Map | Self-Report | ||||
| PROMIS Physical Function Short Form | Self-Report | Self-Report | Self-Report | ||
| PROMIS Anxiety Short Form | Self-Report | Self-Report | Self-Report | ||
| PROMIS Depression Short Form | Self-Report | Self-Report | Self-Report | ||
| PROMIS Sleep Short Form | Self-Report | Self-Report | Self-Report | ||
| Thoughts About Symptoms | Self-Report | Self-Report | Self-Report | ||
| Expectations of Surgery | Self-Report | ||||
| Discharge location | EMR | ||||
| Intubation at discharge | EMR | ||||
| Length of stay in PACU | EMR | ||||
| POD0 opioid administration | EMR | ||||
| POD0 anesthesia course | EMR | ||||
| POD0 Pain Score | Self-Report | ||||
| POD1 opioid administration | EMR | ||||
| POD1 anesthesia course | EMR | ||||
| POD1 Pain Score | Self-Report | ||||
| Post-Operative Outcomes | EMR | ||||
| Reintubation | EMR | ||||
| Supplemental Oxygen | EMR | ||||
| New NIV Requirement | EMR | ||||
| Myocardial Injury | EMR | ||||
| Hospital Length of Stay | EMR | ||||
| ICU Length of Stay | EMR | ||||
| Discharge Medications | EMR | ||||
| Post-Operative Opioid/Non-Opioid Use | Self-Report | Self-Report | |||
ASA: American Society of Anesthesiologists; PROMIS: Patient Reported Outcome Measurement System; EMR: Electronic Medical Record; PACU: Post-Anesthesia Care Unit; POD: Post-Operative Day; NIV: Non-Invasive Ventilation; ICU: Intensive Care Unit
Chart Review Data
The following items are collected via chart review: time until readiness for discharge from the PACU, post-operative Intensive Care Unit (ICU) length of stay, hospital length of stay, post-operative day 0 (POD0) and post-operative day 1 (POD1) pain scores, in-hospital opioid and non-opioid analgesic medications, reintubation, oxygen dependence, new non-invasive ventilation requirements, length of hospital stay, and post-operative myocardial injury (MI). Descriptions of these variables are provided in the Supplemental Appendix 1.
MPOG Data
The following variables will be extracted from the MPOG database for each enrolled patient: American Society of Anesthesiologists (ASA) score, admission diagnosis, comorbidities, type of anesthesia, intra-operative anesthetic technique including all drugs administered, in-hospital mortality, International Statistical Classification of Diseases and Related Health Problems (ICD) 10 diagnoses at discharge, and surgical procedure text type. MPOG variables extracted are described in Supplemental Appendix 2. Patient demographics are collected in-person, pre-operatively.
Research Coordinator Effort
Prior to study initiation a web conference is held to train all study personnel on study procedures. This study requires 2-3 Health Insurance Portability and Accountability Act (HIPAA) and Collaborative Institutional Training Initiative (CITI) trained, IRB approved research personnel (basic training was provided by coordinating centers to ensure consistency of data collection) with EMR familiarity at each institution, available for a continuous two-week period (in-hospital), and then one-week for the one-month and one-week for the three-month phone survey (total four weeks commitment).
Development of the Paper and Digital Case Report Form (CRF)
The paper CRF (Supplemental Appendix 1) for this study, modelled after a previous study performed by Brummett et al.,3, 16 was refined and finalized following pilot cases. The paper CRF was converted into an electronic case report form (eCRF) and implemented (Bootstrap, https://getbootstrap.com/docs/3.3/) as a web application built using ASP.NET framework (https://www.asp.net/) and SQL Server database. The web application is hosted on one of the MPOG servers at the University of Michigan. The application integrates with the MPOG central identity server Health Information Exchange (HIE) HIEBus for authentication. The EOS Web Application generated a Study ID, unique to the specific enrolled patient that was used to link the enhanced observational data with the highly granular electronically generated intra-operative MPOG data of each case without compromising patient de-identification. The eCRF infrastructure also allowed central real-time tracking of patient enrollment across all participating institutions.
Results
Twelve institutions participated in this study: University of Utah, University of Michigan, University of Virginia (coordinating centers), Cleveland Clinic, Columbia University Medical Center, Oregon Health Sciences University, University Medical Center Utrecht (The Netherlands), Vanderbilt University Medical Center, University of Vermont, University of Washington, Washington University in St. Louis, and Yale University.
Information from surveying the participating sites regarding their actual use of time and resources is reported in summary form in Supplemental Table 1. Sites devoted ½ - 3 hours total per enrolled participant.
Discussion
The present study is uniquely positioned within the MPOG methods of data collection to dissect the current opioid crisis in a multimodal manner, utilizing not only electronic records but combining them with a longitudinal, prospective, and observational approach. The study is very different in its study design from past multicenter observational studies in acute pain management such as the PAIN-OUT study,17 with a shorter length of subject enrolloment at each participating center, longer subject postoperative follow-up, and use of the MPOG network and electronic perioperative data capture. The information gleaned from this first MPOG EOS study may serve as a framework and may prompt the development of similar investigations to answer different perioperative questions.
The present MPOG EOS study utilizes an a priori peer-reviewed protocol, collecting a large amount of highly granular data with no extramural funding. This effort offers insight into the potential for similar studies. First, the “crowdfunded” Enhanced Observation MPOG Study is novel in anesthesiology. MPOG has been operational as a database and research consortium since 2008. Multiple retrospective studies have been published using MPOG data, yet this is the first MPOG study to prospectively recruit patients and collect enhanced observational data. Since there is no extramural support, those institutions who participate are highly motivated to be involved. However, many institutions may find the EOS procedures to be too onerous, especially without funding. As such, funding or a less ambitious study design may make it easier for some institutions to participate.
An important factor in this study is the collaborative effort of participating institutions. Through this collaboration, the study covered a large variety of surgical case distributions, pain management approaches and recruited patients from various surgical patient populations covering a large range of socioeconomic, regional, educational, and occupational backgrounds. This will be reported in future manuscripts detailing the results of the data collected in this study.
This study requires a significant amount of human resources to accomplish. The EOS planning team had five core members who dedicated a substantial amount of unfunded time and effort, a consideration for future studies. The planned timeline of this project was overly optimistic and the project initiation took longer than anticipated. The pragmatic, accelerated approach, while good at keeping up the momentum, did result in a number of moved milestone dates, which may have complicated resource planning at some sites. For future enhanced observational MPOG studies, this working group recommends that EOS proposals be based on pilot studies with IRB approval in place and pretested, timed data collection.
There are additional considerations for future EOS studies. The lack of extramural funding, small resource expectation, and short start-up period limits the ability of the coordinating centers to enforce a strict protocol, have a minimum standard/training/experience level of data collectors or require a minimum number of participants to be enrolled. Future studies would benefit from funding to allow for improved pretesting of pilot data collection case report forms, and protocols, and a larger sample size.
This study intended to utilize the University of Utah’s TIC funded Smart IRB. While many of the participating institutions are Smart IRB institutions and could participate in the SIRB, only three institutions are. Since the process was new at the University of Utah and hardly in place at many of the other participating sites, use of the Smart IRB is inefficient. Many of the institutions have policies in place to use single IRBs only if required by the sponsor, e.g., by the National Institutes of Health (NIH). Many sites would like to customize enrollment and follow-up for what works best at their institution (e.g. pre-operative clinic enrollment, use of electronic media/smart phones rather than phones and number of attempts for contact, and incentives for study completion). This was not possible with the Smart IRB. Also, contrary to expectations, the SIRB process is more complicated than the conventional approach of using the local institutions’ IRB due to adherence to state laws such as requiring written HIPAA authorization.
Finally, some sites have delays in their routine MPOG clinical data upload that slow linkage of study data records. This working group recommends that sites with the desire to participate in EOS studies commit to timely clinical data uploads.
Conclusions
This manuscript describes the methods of the first MPOG EOS study. To the authors’ knowledge, this is the first crowdsourced multi-center study to comprehensively combined detailed perioperative data elements from multiple institutions. Future publications from this group will more comprehensively present the aims and hypotheses studied here and the MPOG EOS results.
Supplementary Material
ACKNOWLEDGMENTS
The authors would like to acknowledge the following people whose hard work on this project made it be possible: Michael Avidan, MD (Washington University), Marcia Birk, RN (University of Virginia), Max Breidenstein, BS (University of Vermont), Lisa Flint, BS (University of Washington), Alex Friend, MS (University of Vermont), Sherry McKinnon, BS (Washington University), Jordan Oberhaus, BS (Washington University), Nicole Pescatore, MPH (University of Michigan), Laura Sissons-Ross (Oregon Health & Science University), Troy Wildes, MD (Washington University), Robli Kennedy (University of Utah), Yuri Kida, MS, CRCC (University of Utah), Jaqueline van Dijk, MSc (UMC Utrecht), Julia White, RN, BS, CRCC (University of Utah), Amber Bledsoe, MD (University of Utah), Ken Johnson, MD (University of Utah), Scott Junkins, MD (University of Utah), Amy Shanks, PhD (University of Michigan), Josh Zimmerman, MD (University of Utah).
Financial Disclosures:
Dr. Brummett reports other from Recro Pharma Inc, other from Heron Therapeutics, grants from NIH-DHHS-US-17-PAF02680 (R01 DA042859-05): oPioids: Prevention of Iatrogenic Opioid Dependence after Surgery, grants from NIH-DHHS-US-16-PAF06270 (R01 HD088712-05) Peripheral and Central Nervous System Correlates of Persistent Post-Hysterectomy Pain, grants from NIH0DHHS-US-16 PAF 07628 (R01 NR017096-05) Resilience Skills Self- Management for Chronic Pain, grants from NIH-DHHS-US (K23 DA038718-04) Chronic Pain through Individualized Opioid Cessation, grants from MDHHS (Sub K Michigan OPEN), grants from NIH-DHHS (P50 AR070600-05 CORT), grants from NIDA (Centralized Pain Opioid Non-Responsiveness R01 DA038261-05), grants from UM Michigan Genomics Initiative, during the conduct of the study; In addition, Dr. Brummett has a patent Peripheral Perineural Dexmedetomidine (no royalties) Application number 12/791,506; Issue Date 4/2/13; licensed.
Financial Disclosures:
Dr. Edwards reports grants from Grunenthal and Semnur outside the submitted work.
Glossary of Terms
- ASA
American Society of Anesthesiologists
- CITI
Collaborative Institutional Training Initiative
- CPT
Current Procedural Terminology
- CRF
Case Report Form
- ECRF
Electronic Case Report Form
- EMR
Electronic Medical Record
- EOS
Enhanced Observational Study
- HIE
Health Information Exchange
- HIPAA
Health Insurance Portability And Accountability Act
- ICD
International Statistical Classification Of Diseases And Related Health Problems
- ICMJE
International Committee Of Medical Journal Editors
- ICU
Intensive Care Unit
- IRB
Institutional Review Board
- LOI
Letter Of Intent
- MAC
Monitored Anesthesia Care
- MPOG
Multicenter Perioperative Outcomes Group
- MT
Myocardial Injury
- NIH
National Institutes Of Health
- PAIN OUT
Improvement In Postoperative PAIN Outomes
- PCRC
Perioperative Clinical Research Committee
- POD0
Post-Operative Day 0
- POD1
Post-Operative Day 1
- PROMIS
Patient Reported Outcome Measurement System
- RCT
Randomized Clinical Trial
- SIRB
Single Institutional Review Board
- SQL
Structured Query Language
- TIC
Trial Innovation Centers
Footnotes
Conflicts of Interest:
Drs. Stuart, Kuck, Naik, Saager, Domino, Pace, Posner, Alpert, Kheterpal, Brummet, Durieux, and Mr. Sinha have no conflicts of interest.
Clinical trial number and registry URL: This study is not subject to ClinicalTrials.gov review as the study is not a clinical trial and does not involve an intervention or investigational use of a device or drug.
Conflicts of Interest:
Drs. Aziz, Cummings, Edwards, Gaudet, Kurz, Paganelli, Rijsdijk, Schonberger, Thomas, Wanderer, Rose, van Klei, and Ms. Corradini, Mrs. Vaughn, Ms. Lamers, and Mr. Mincer have no conflicts of interest.
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