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Multicenter Perioperative Outcomes Group (MPOG) and Anesthesiology Performance

Improvement and Reporting Exchange (ASPIRE) Protocol

Project Summary

The Multicenter Perioperative Outcomes Group (MPOG) is a consortium of anesthesiology departments

of academic medical centers with electronic perioperative information systems. The purpose of MPOG is

MPOG was developed so that institutions across the globe can join together to pool their electronic

perioperative data into a common research database. These limited datasets (only date-of-service will

be uploaded into the repository) are used for clinical outcomes and quality assurance research purposes

by the members of participating institutions. The database will also include administrative information

and outcomes data. The MPOG Coordinating Center, housed at the University of Michigan, receives and

merges the limited dataset into one centralized data repository.

This protocol describes University of Michigan’s role as a performance site and Coordinating Center for

MPOG. As a performance site, the University of Michigan uploads a limited dataset from our anesthesia

electronic information systems to the MPOG Coordinating Center repository (HUM00024166). MPOG

has a Perioperative Clinical Research Committee (PCRC) which is comprised of members of institutions

into a MPOG database. There are no patient identifiers stored in the MPOG central repository and no

members of the research team will ever have access to identifiers. Automated database extraction

process is performed on secure UMHS servers. The only PHI element collected will be date-of-service.

Background

The traditional prospective, randomized controlled trial (RCT) is a mainstay of medical research.

However, although RCTs are regarding as the gold standard of medical research, there are many clinical

conundrums that cannot be effectively addressed by a prospective RCT. Observational studies are often

the only option for research into

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- Infrequent adverse events associated with a medication

- Emergency operations challenging conventional consent and randomization systems

For these and many other clinical questions, the only practical research structure is a large observational

dataset based upon existing information system data elements. By combining point-of-care clinical

information systems with clinical registries, financial data, laboratory information systems, radiology

information systems, administrative datasets, and scheduling datasets, one can address previously

unanswerable clinical questions. Though causality cannot be concluded, these hypothesis generating

studies are crucial to the advancement of clinical science.

Specifically, the field of perioperative medicine has witnessed a major improvement in safety over the

last few decades. As a result, many of the morbidity endpoints (death, myocardial infarction, pulmonary

complications, nerve injury) previously followed are now occurring with a frequency far too low (< 1%)

for prospective enrollment in controlled trials. However, the importance of these morbidity endpoints

profile for certain patients, leading to major changes in the perioperative use of these drugs.

Objective

To identify the perioperative adverse events, and changes in resource utilization associated with

variation in perioperative management. Create quality measures focusing on quality improvement and

as a result will include quality focused research.

Specific Aims

conditions, and operations

observational and quality research

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knowledgebase. He has previously used retrospective analysis of clinical documentation databases to

publish studies in leading peer-reviewed anesthesiology journals. In addition, he has served as a

Dr. Shah is an assistant professor in the Department of Anesthesiology with expertise in medical

informatics and quality. He is the Director of Informatics and Systems Integration for the Department of

Anesthesiology and the University of Michigan Health System. He has served as a systems designer,

database architect both in industry and at academic institution for over 10 years. He brings a technical

and medical background that will help to integrate the software and analytic system.

Inclusion/Exclusion Criteria

As a participating site, all adult and pediatric patients undergoing perioperative services at the Michigan

Medicine are included. There are no exclusion criteria.

Methodology1

The perioperative clinical information system, several UMHS surgical outcome databases, laboratory

After anesthetic case data are extracted from the source system, data are integrated with other data

sources including institutional research repositories, case data that may also be available from outcome

registries (such as an extract of data captured by that site as part of participation in the National Surgical

Quality Improvement Project [NSQIP] or Society of Thoracic Surgeons General Thoracic Surgery

Database [STS-GTSD]), and other clinical, laboratory, or administrative systems. Data are matched at the

participating site based on locally held unique identifiers (such as Medical Record Number or Social

Security Number). The unique identifiers are removed before transmission to the Coordinating Center.

Once extracted from the local electronic health record (EHR), perioperative data are mapped to MPOG-

developed standardized, semantically interoperable concepts before submission to the central

repository. MPOG embraces standardized definitions where available, such as the use of ICD-10

requires a clinically trained site representative to review and attest to data accuracy before each data

transmission to the central repository. At the Coordinating Center, the MPOG Director reviews the initial

data upload (including the Data Diagnostics information) before it is integrated into the main MPOG

database. Participating MPOG sites perform a manual review of a random sample of cases recorded

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within the local database before transmission to the centralized database, because some errors may

escape detection when assessed at an aggregate level.

In rare situations, research investigators using the centralized or performance site database may

observe a rare clinical event that requires additional data extraction. Every case in the centralized

repository and at each performance site will have a distinct patient system number (that is randomly

generated) that is NOT a patient identifier. This system number is NOT related to or derived from any

PHI (ie, name, reg num, DOB, etc). The centralized MPOG repository has no way of using this random

system number to link to any patient identifiers. If a rare clinical event that requires additional data

extraction is observed, this non-PHI system number will be provided to a performance site. Technical

staff at the performance site can access their own source databases in an attempt to link the system

number to PHI. This linkage exists in the source clinical information system, not in any research database

proposed by this project. If they choose to, the performance site may use this system number to extract

and provide additional de-identified clinical data to the Coordinating Center investigators. No patient

contact will occur. All additional data extracted would be from existing clinical and administrative data

sources.

Removal of Identifiers and Data Transmission

A limited data set is first created locally by removing selected PHI via a customized “scrubbing” tool

(leaving only dates and extremes of age) and then transmitted to a centralized MPOG database. The

scrubbing tool additionally removes common names that may be entered in the free text. Several

dictionaries are preloaded into the scrubbing application including the most common first and last

transferring case-level data to the MPOG Coordinating Center become available. Data are transferred

available for use within research and quality improvement projects. As specific to the needs of a project,

data are subject to focused examination to ensure appropriate values are included.

Data Use

All research projects using MPOG data sets must obtain project-specific IRB approval. Additionally, a

detailed proposal must be presented through the monthly MPOG Perioperative Research Committee

and other interested research faculty. The committee critically reviews and amends the proposal, and

subsequently votes to accept, require revisions, or reject the proposal. Before accessing data, research

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project proposals are prospectively registered and tracked on the MPOG website which remains

accessible to members.

Figure 1 provides an overview of the flow of information through the MPOG consortium, outlining the

process of data acquisition at the point of care, importing of data into local and central data registries,

and finally, curation of data for research and quality improvement measures.

Statistical Design

A variety of statistical techniques often used for large dataset research will be used. Each approved

research question may use distinct techniques, so it is beyond the scope of this document to

prospectively delineate a complete statistical plan. Logistic regression modeling (GEE and standard),

propensity score matching, cox proportional hazard modeling, and basic univariate comparisons are a

few of the many techniques that will be used. Descriptive and inferential statistical techniques will be

Privacy Risk (Rarely likelihood of risk)

Theoretically, since patient data is being extracted, there exists a non-zero privacy risk. However, since

the data extraction process is automated and the data structures involved separate patient identifiers

from the data being extracted, the likelihood is extremely rare. Patient identifiers (DOB, Name, MRN,

Insurance account numbers, SSN) are NOT stored or transmitted at any point during the data extraction

or transmittal process.

Data Security and Privacy

All data extraction processes are automated to eliminate the possibility of human error. No research

personnel are required to 'match' or review identifiers. All database work is performed on UMHS-MCIT

approved and secured servers, with multiple password security layers for access, that are physically

located in the UMHS computing environment and maintained by MCIT security standards. No patient

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Only the database mining automated processes will have visibility to the patient identifier and not the

statistical team, manuscript authors, or any members of Coordinating Center. All identifiers will be

An internal perioperative clinical information system number for each operation that is completely

unrelated to the patient medical record number or name remains in the data extract. This system

number cannot be used to ascertain any PHI regarding the patient unless the perioperative clinical

system database is accessed by a database specialist. In rare cases, additional info about a patient may

be requested. In that case, a separate IRB application will be submitted to link the internal system

number to the perioperative clinical information system.

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References