Infrastructure Initiatives SLU Approach To Data System Implementation

Infrastructure Initiatives SLU Approach To Data System Implementation Jack M Lionberger, MD. , Ph. D. 09/19/2016 OTTR Users Conference

Disclosure I have no financial relationships to disclose. I am employed solely by Saint Louis University, but I do take orders from my wife.

Data Plan – Global CLINICAL DATA Chemo EHR Lab Pharmacy Laboratory GMP, Inventory Legacy Data Source (Excel? Access? SQL? ) Clinical Data System Workflow Management CIBMTR Report BMT CTN Quality IRB Research CIBMTR Back. Download (x 1)

Types of Legacy Data, Or New Vistas Legacy Data Source (Excel? Access? SQL? ) Master List ALL BMT Patients CRID # OTLs Other Table Links: OTL Pharm Molecular Markers LLE in time No LLE NDDL Retrospective project (NDDL) Prospective project (LLE via Flow sheets) NDDL Cyto/FISH a. GVHD Prospective No LLE perhaps with In Progress, POC SSM Link Retro finis NDDL c. GVHD Cdiff CRInf Chimerisms GI HCT-CI In Progress, POC Retro/Pro Prospective In Progress, POC Retro finis In Progress, POC Retro/Pro Pending NDDL NDDL

Goals & Needs: Multiple Perspectives A Project like this has multiple stakeholders, multiple perspectives, multiple goals and needs. You get to satisfy them all! Academician “Need publishable data for my Center and my Career. I want the data as easy and perfect as possible. ” Quality Team (s) “Need data for policy development for compliance, certification, outcome and defined goals by Center” Sponsor (s) “Need the maximum value for system, implementation, and maintenance. Not a content expert, rely on advice for goal completion Registry “Need accurate data with minimum fuss and re-validation. Gotta get my forms done on time, the first time” Vendor (s) “Need to do this well, quickly and with highest value algorithm for the company and the client. Software Content expert, not an expert on your system per se. ” Sponsor Support IT, Clinic Administration: “Need clear implementation algorithm. Need plans for approach, initiation and maintaining with minimal interruption to workflows” Clinician (s) “Improve Quality, but please don’t slow my day down”

The Art of Compromise Making everyone unhappy with you, but nobody homicidal towards you.

Quality Improvement – Data System We have viewed the Data System Implementation as a step wise Quality Improvement Plan. Piece by piece Quality Improvement Multistep process to improve: Knowledge Documentation consistency Therapy accuracy Patient outcomes Steps: Retrospective Data Analysis Quality Improvement Intervention Prospective Evaluation A Retrospecti ve Data Collection B Intervene with Education and Tools C Collect Prospective Data D Real time Clinical Validation of Data E Report back to Group for QI

Our OTTR Timeline Concept of Data System: Hutch – Home Grown (Fractured); Vanderbilt - Vendor Review Vendors, Weigh Pros-Cons. Decided on OTTR Huh. Probably should have thought of that… Administration Approval, PO, Contract What Is Project Scope? Scope of Project: Number of Columns? What that means is, how many places does the OTTR data conversion have to worry about in the database. In its simplest conception, this is something like “WBC”. There might be several sources of WBC, and each have to be converted to a specific discrete (defined) type of information from the original source information. More complicated: Data that must be moved from a legacy data set (electronic, paper, etc) that must be converted into a unified data set, then converted to OTTR, then validated. This is very center specific. An example is your GVHD data.

Our OTTR Timeline Concept of Data System: Hutch – Home Grown (Fractured); Vanderbilt - Vendor Review Vendors, Weigh Pros-Cons. Decided on OTTR Administration Approval, PO, Contract Introduce the system and goals Kick-Off – Dec. 2015 Seek Early Wins: What are the tasks you can work on that will facilitate your stakeholder recognizing the value of the system? What is the timeline of goal completion for each stakeholder’s needs? What are the burning planks that must be resolved? Are these burning planks opportunities or deal breakers? What are your institution and system limitations? Do you know your system? “An EHR will not fix all of your problems, but implementing an EHR will identify all of your problems” Erron Swick Pharm D.

Burning Plank: Paper Burns!! Thank Goodness for those nice looking people in our Data Team!! Ouch! Yikes! Regulatory (FACT) The Way We have Always Been Clinical Data System Opinion: It is going to be harder and harder to comply with regulatory groups without a central and electronic data plan.

Data: Clinical Work Drives Outcome Legacy Formats Local Quality / Academic Registry You will likely want State of The Art transplant Approaches / Protocols / Data Collection. Especially as a Small to Medium sized Transplant Program. Lets use the protocols from the Best of the Best You must comply with Registry Data Collection and Reporting, even though these are sometimes dated. Not always the Same Fields CIBMTR: Data Back to Center

a. GVHD: Standardization Consensus State of the Art Ravulapati, Lionberger, et. al. BBMT; March 2016, (22), (3), Supp. , P: S 282–S 283

a. GVHD: Retro/Prospective & Validation Ravulapati, Lionberger, et. al. BBMT; March 2016, (22), (3), Supp. , P: S 282–S 283

a. GVHD Workflow APP: Mr. Suchand. Such has a new rx for GVHD (or a new Organ involved) APP: We started Prednisone on Mr. Suchand. Such for GVHD. Data is still pending. Weekly Clinical Mtg Data Team: “Treatment” matches our definition of a new GVHD case. I will “drop” a form for APP to fill out. One Pt, One NP, One Attending – One One Set Pt, One NP, Data One Attending – One Data Set APP 4 wks later APP finishes and files to Data Team: “New Treatment” and “new Organ system” matches our definition of new GVHD case. I will “drop” a form for APP to fill out. MD APP finishes and files to Data Team Adds Data to Excel Sheet MD At Data Meeting Used to Populate D 100, etc forms zzz zz 1 Month of Data Validate NP/MD Co-Validation Summa CIBMTR ry Summary Forms

General Plan: Validation In OTTR Data Event Occurs Clinical Mtg Coordinator NP Record Data Milestone Passes Clinician MD CIBMTR QIP Academics NP/MD Co-Validation

Types of Legacy Data, Or New Vistas Legacy Data Source (Excel? Access? SQL? ) Master List ALL BMT Patients CRID # OTLs Other Table Links: OTL Pharm Molecular Markers LLE in time No LLE NDDL Retrospective project (NDDL) Prospective project (LLE via Flow sheets) NDDL Cyto/FISH a. GVHD Prospective No LLE perhaps with In Progress, POC SSM Link Retro finis NDDL c. GVHD Cdiff CRInf Chimerisms GI HCT-CI In Progress, POC Retro/Pro Prospective In Progress, POC Retro finis In Progress, POC Retro/Pro Pending NDDL NDDL

Our OTTR Timeline Concept of Data System: Hutch – Home Grown (Fractured); Vanderbilt - Vendor Review Vendors, Weigh Pros-Cons. Decided on OTTR Kick Off December 2015 Use OTTR Project Management as basis for local Project Management Administration Approval, PO, Contract Introduce the system and goals Weekly Meetings: Go-Live: • • Overall Strategy Interface Data Conversion Hardware Regular Reports: • • Sub-meetings Training Staff Management Timeline Optimization Management Resources Who is trained When How do they visualize their goals

Our Data System Go-Live Carbon Based Virtues and Liabilities Silicon Based Virtues and Liabilities People don’t like to change workflows We had interviewed our workforce and discussed Project regularly. Orchestrated Global Mtgs Training for the Post Go-Live is difficult without seeing the final product (Chicken and the Egg) Establish concept of integrated workflows (conduits of communication) Vendor training team is diligent and thoughtful Not all stakeholders understand the point of the Data Program Management. Not all workflows are solid Continued communication is absolutely central, and establishing specific milestone Post Go-Live. You must be the visionary with thick skin. Concept Based Virtues and Liabilities

Our Data System Go-Live Carbon Based Virtues and Liabilities Silicon Based Virtues and Liabilities Concept Based Virtues and Liabilities A combined University and Hospital system have overlapping IT departments with varied Jurisdictions Centralized and regular meetings facilitate identifying responsible parties to engage in process, even if it does not ward off all problems Review of IT stakeholder’s goals may indicate in your case that you need more personnel support Honest and open conversations with your IT Team (s) will facilitate this clarity earlier in the process. IT Teams seem to appreciate engagement with the new processes

Our Data System Go-Live Carbon Based Virtues and Liabilities Silicon Based Virtues and Liabilities Concept Based Virtues and Liabilities No one vendor does all things, so you must manage several entities. We chose this Vendor because of the history at SLU of using the vendors successfully, and using HL-7. Our local system has grown organically with “work arounds” in electronic and in paper formats. Data is central to Transplant, as shown in recent publications (Marmor et. al. ) and outcomes. The process of Data System Implementation supports the goal of improved outcomes Politics may cause short term blocks to productivity Yeah, your on your own there.

Data System: Roll Out Week Data Review Conditioning Transplant x x x x x x x x x x x x IDM/Organ Fxn Arrival Transplant TOC Conditioning Scheduling Data Review Social Work Arrival Limited to Post Transplant Patients Financial TOC Backfilled and Cross-walked for both hospitals. Historical Up to 7/27/16 Referral - Listed Scheduling SLUH/Glennon Data in Data System Social Work Prospective = manage ‘p “Go-live Financial backfill as x = part of “Golive Referral - Listed Pre Transplant Patients - Overview

Data System: Roll Out Week SLUH/Glennon Data in Data System Backfilled and Cross-walked for both hospitals. Historical Up to 7/27/16 Limited to Post Transplant Patients Milestone: Are all pre transplant patients in? Milestone: 8/12/16: Did all new pts get in? Milestone: 8/19/16: Are all pre transplant patients in? Milestone: Weekly report/review thereafter. During Pre Transplant Mtg Weekly Check: Is data flowing to down stream algorithm functions? Financial Arrival Social Work TOC Scheduling

Post Go-Live: Success & Milestones We see this process as being completed in about 12 months. The reason it takes time is because each workflow must be carefully extracted from our personnel, redesigned to be fully functional and then carefully placed into the data system and then fully validated. That is the process not of putting in a data system. That is the process of building a solid program.

Good Luck I will leave you with a profound sentiment from Linda Laub, RN: “You don’t suddenly lose your expertise in your job just because a data system is being implemented. You were an expert last week, you are still an expert” That is a great mantra for your folks who are nervous. Thanks Linda, Marita, Shyla, Doug, Todd, Kathleen, Michelle and the Whole Vendor Team!!!! You are very good at your job, and we appreciate your work!