№ lp_2_1_26808
Note: Primary Institution
Co-Authors: Please consider defining co-authors at time of presentation. Further info: Preparing Your MPOG Manuscript Requirements: ICMJE requirements for co-authorship
Statistician(s): Please note, if statisticians are seeking access to case-level data to execute the proposed analysis, they must have a primary appointment (i.e. non-adjunct/affiliate faculty appointment) at the active MPOG site for which the IRB is obtained.
Type of Study: << Exploratory / Retrospective Observational / Prospective Trial >>
Data Source(s): << MPOG Database / Surgical Registry (e.g. STS, NSQIP) / Other (describe) >>
IRB Number/Status: <> / <>☐ IRB is specific to this project ☐ IRB specifies that dataset is a limited dataset (i.e., not de-identified)☐ PI is listed on the study IRB
Hypotheses / Aims: Please be sure to describe how you plan to define your cohort, exposure, and outcome Tip: review Tips & Tricks Modules on the MPOG website: “MPOG Research Process Overview” “Developing a Research Proposal” Please be sure to describe your cohort, exposure (if applicable), and outcome.
Number of Patients/Participants: Please list the cohort sample size estimated using MPOG DataDirect
Resources (Brief summary of resources for data collection, personnel, financial): STOP Before investing the substantial time to develop the rest of this proposal, please submit the Cover Sheet to the MPOG Coordinating Center via the ‘Research Consultation Form,’ as detailed in Step 3 of the MPOG website --> Research --> “Research Proposal Process”. Submission of the Cover Sheet enables the MPOG Central Research Team to provide early feedback on your project idea, in its formative stages, in order to: ensure feasibility; identify potential collaborators across MPOG who are developing similar projects; position your project for maximal chance of successful publication in a high-impact journal. Please note, successful completion of an MPOG project typically requires an integrated team-based scientific approach with: Clinical subject matter expertise (usually with a primary medical qualification and perioperative clinical practice insight), and Statistical methods expertise (usually with doctoral level training and experience in public health science, e.g. biostatistics, epidemiology) Please consider seeking collaboration from those with complementary expertise to ensure these skills are reflected in your study team. The remainder of this template includes all the sections necessary to complete your PCRC proposal. Please include all the following sections as applicable to your project. The MPOG Central Research team is committed to your success!
Introduction (target 300-500 words; limit 750 words) Tip: consider writing the Introduction and Methods, exactly as intended for submission to target journal (links to Instructions for Authors can be found here: Anesthesiology, BJA, JAMA, A&A). The introduction should cover: What is the significance of the clinical problem being addressed? What current gaps exist in understanding this problem? How will this project address this gap and advance clinical care and/or research knowledge? What is the primary (and secondary if applicable) aim(s) / hypothes(es)? [hypotheses should be predictive] Note: Occasionally, PCRC proposals may have 2-3 aims, although each proposal is intended to correspond to one manuscript. For proposals with 2-3 aims, please clearly identify which outcomes / exposures / covariates / statistical analyses / power analyses correspond to each aim. For proposals exceeding the scope of 2-3 aims, please consider developing separate PCRC proposals, or discussing with the MPOG Coordinating Center.
Methods Tip: review Tips & Tricks Module on the MPOG website: “Developing a Research Question Answerable with MPOG Data”
Study Design Please include: Type of study (e.g. exploratory, retrospective, prospective, etc.) IRB approval/pending approval statement
Reporting Guidelines: Please review the EQUATOR Network and determine the appropriate guidelines for reporting your proposal and that your proposal is in accordance with the checklist. Common examples include: Observational studies using routinely collected EHR data (i.e., MPOG data) - RECORD extension of the STROBE guidelines Clinical prediction or diagnostic models - TRIPOD guidelines Systematic reviews and meta-analysis - PRISMA guidelines Quality Improvement Studies - SQUIRE guidelines
Study Population Tip: review Tips & Tricks Module on the MPOG website: “Using DataDirect for Self-Serve Data Access” Text to include: Date range Participating institutions (or selection criteria for institutions) Please state whether non-US institutions should be included in study, versus US institutions only NOTE: EHR Data from international sites may be different from US Sites (e.g., CPT Codes may not be available). Including both US and International Sites may add a layer of complexity to the analysis.
Study population Inclusion criteria – Which cases/patients are included in the dataset that you will receive (e.g., certain timeframes, procedures, ages). Some notes: Start dates earlier than Jan 1st, 2015 have less consistent data quality compared to more recent dates. End dates later than 3 months before the current date may have lower rates of data completeness. Consider using a pre-defined starting population, such as “Intraoperative Research Standard” or “Outcome Research Standard”; see MPOG DataDirect for details.
Exclusion/Screening criteria – Those criteria your team will want to use to exclude/screen cases from the dataset you receive, as part of your analysis processes. For example, if you list “Ou: Demonstration of Inclusions vs. Exclusions, and Initial Dataset received from MPOG Central vs. Final Analytic Dataset that study team creates
Covariates Tip: Review the Tips & Tricks Module on the MPOG website, “Transforming Raw Data into Clinical Inferences: Phenotypes” Text to describe the relevant, specific covariates to the study and their derived parameters. To promote generalizability and comparison to other studies, please consider using MPOG Phenotyp
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