what to expect when migrating: a walk through a clinical data migration (2017)

Clinical Data Migration: Functional & Technical ConsiderationsA SSM Integrated Health Technologies Case Study

Confidential © 2017 Galen Healthcare Solutions

You have been automatically muted. Please use the Q&A panel to submit questions during the presentation


Roles & Organizations

SSM Case Study Overview

Migration Decisions

Functional Considerations

Technical Considerations

Considerations Relating to SSM

Panelist Questions

TODAY’S AGENDA



Taylor MawyerManaging ConsultantGalen Healthcare Solutions

Moderators:Justin CampbellVP, StrategyGalen Healthcare Solutions

Sandy WinkelmannProject ManagerSSM Integrated Health Technologies

Julie ChampagneStrategistGalen Healthcare Solutions

Kavon KaboliSenior ConsultantGalen Healthcare Solutions

Clinical Data Migration: Functional & Technical ConsiderationsA SSM Integrated Health Technologies Case Study

About Galen


Galen’s Vendor Expertise

Galen Roles: • Legacy System Data Extract and

Evaluation• Clinical Data Mapping• Configuration• Testing and Validation• Data Import and Issue Resolution

• GE Centricity and MEDITECH to Epic EHR Transition

⁃ Legacy Systems⁃ MEDITECH 6.0 Inpatient EHR 6.07⁃ MEDITECH/LSS Ambulatory EHR 6.08⁃ GE Centricity Ambulatory EMR 9.8

⁃ Target System: Epic 2014⁃ CCD Extract & Import

⁃ Allergies⁃ Medications⁃ Problems

Key Metrics

Immunizations270K Allergies360KMedications650K Problems600K

139K PatientsMigrated

200+ Providers

Migrated

SSM Integrated Health Technologies


SSM Case Study Overview

Our panelists will share:• An overview of the role they played in SSM’s data

migration• What challenges they faced as it related to the

SSM EHR data migration• Lessons learned from the EHR data migration


SSM Case Study: Sandy’s Role• Facilitated discussions with physicians, hospital administration

and clinic leaders regarding data elements for migration and amount of data to migrate.

• Coordinated IT technical plans with System IT leaders and local IT staff.

• Completed data mappings and coordinated System IT resources for data loads.

• Completed necessary paperwork and project request forms (internal change control process).

• Validated data loads, CCDs, and data reconciliation process.


SSM Case Study: Challenges

• Agreement on data elements – weighing the “cost” of the element versus the “benefit”

• Gaining necessary approvals and agreement from multiple stakeholders

• Timing of data migration versus abstraction activities versus actual “Go Live” date


SSM Case Study: Lessons Learned• Migrated data reduced the amount of time spent abstracting for not only clinic visits but also

patients who were currently in-house at the time of “Go Live.” This was an unexpected benefit.

• Ensure that the MPI and visit loads are complete, up-to-date, and clean.• Begin the data migration process early! Some activities took longer than anticipated• Get agreement on elements to migrate versus abstract as well as the approach for

migration (CCD, HL7).• Physician champions:

• Experts for data elements and data mapping• Strong working knowledge of the reconciliation process in the new EHR• Champion the data migration effort with other providers and physicians

• Have operational and IT subject matter experts available for data mapping. Experts need to be proficient with “old” EHR and have a good working knowledge of “new” EHR

• Ensure that the data migration and abstraction strategies work hand in hand.


SSM Case Study: Mapping• Mapping counts for Allergy

Reactions are lower in GE Centricity than for MEDITECH due to the large number of free text Allergy Reactions documented in this legacy system that do not have discrete matches in Epic

• Mapping counts for Medication Dose Units and Route appear lower due to how the data needed to be extracted from GE Centricity


Why?• Sometimes adding a large amount of data • Very difficult to change once data has been loaded • Way the data is stored in the source system does not always play nice with

how the target system accepts it• Way the source system records medication refills may be different from how

the target system records them• Often need to think long term and about the global context in the organization• Mapping highly utilized medication in source system to rarely used medication

in target system may not be a good idea

Amount of Migration Decisions


Migration vs Abstraction

SSM Case Study: Migration

Considerations:• Access to source clinical data?• Accuracy, validity, and cleanliness of clinical data?• Cost effectiveness of approach (business vs. clinical decision)?


• Multiple ways to filter the data• Decide what data types will be converted• Immunizations, allergies, medications, results, problems,

documents, vitals, images• Not every data type may be present in the source system• If organization has no inbound results interface then there may

not be results to extract• Different ways to filter clinical data depending on need

• Clearly define what fields will be converted• Can help to display where fields render in the target system• All fields might not be available to convert

• Can depends on workflow

Scope of Conversion

Migration Data Elements


SSM Case Study: Migration Stats


Current Medications Only shows most recent occurrence of

medication Not necessarily last time it was prescribed

Medication History Each time medication was recorded will

convert separately Can clog up Past Medications

Current Medications vs. Medication History


• Easy way to signify that clinical data came from another system

• Way to add data that is not able to be mapped or able to be brought over discretely

• Free text comments in source system

Annotations


Map all providers Able to associate providers to meds prescribed, orders placed etc. Not always connected to most recent record

Use generic “conversion” provider At a quick glance allows users to see where item came from Conversion MD, HeartPro

Non-providers Administered by Recorded by Can use annotations as well

Providers


SSM Case Study: Mapping• Mapping counts for Allergy

Reactions are lower in GE Centricity than for MEDITECH due to the large number of free text Allergy Reactions documented in this legacy system that do not have discrete matches in Epic

• Mapping counts for Medication Dose Units and Route appear lower due to how the data needed to be extracted from GE Centricity


Problems Name ICD-9 Problem Code

Medications Name NDC Medication Code

Allergies Name Allergy Code

Galen Intelligent Mapper


Use counts to map most commonly used items What items to exclude (NKA, NKDA, No Known Medications etc.)Think critically about why values may be present

Data could have been entered incorrectlyAncillary mapping needs

Route of Administration Body Site Manufacturer Allergy Reaction

Mapping Considerations


The good Does not require time to map Allows users to build a patient’s chart history on the fly for ambiguous items

The bad Items are not functional within Touchworks Items do not participate in DUR (Drug Utilization Review) checking Items do not auto-cite into a note Cannot assess and charge for unverified problems Immunizations display under the Orders Component

Make sure users know the Verify and Add workflow

Unverified Items

Migration Validation Methodology

Chart Reconciliation


SSM Case Study: Validation


Non-Discrete Conversion Chart Summary of Data

• Less work• Won’t duplicate data• Not Reportable

Discrete Conversion – Stored Procedures Inserting data directly into the database

• Reportable• Users can use items in workflow• More work• Can duplicate data if users are already live on system

Types of Conversions


CCD – Continuity of Care Document Active problems, medications, and allergies Semi-discrete

• Epic will attempt to match items on import• Users will need to manually reconcile the remaining items

Imported via separate utility (Document Assimilator) Other data can be viewed via a report

Discrete Conversion – HL7 Messages Imported via Interface (Bridges for Epic)

• Reportable• Data is filed directly to the patient’s chart• Needs to be mapped

Types of Conversions (cont.)


Different options for matching Standard matching vs. Extended matching criteria

When would patient matching fail? Name misspelled Name change Info lacking in legacy system Patients don’t exist

Other Considerations Multi-org environment

• Use of Internal Organization number in Patient table• eMPI Enterprise Master Patient Index

Merged and Deactivated Patients

Patient Matching


Epic Matched by Identity ID and ID type Some interfaces can create patients Identity Duplicate Configuration (IDC)

• Weights• “Sounds Like”

Meditech MRN needed prior to clinical data import for matching

Patient Matching (cont.)


Ways to Access Data: Direct network access Access to legacy system

• Galen Securelink Linked server

• Copy of legacy system to test database of new system

Scanned Images Options:

• Direct network access• Removable device• FTP

Getting Access to the Data


Windows Server 2008 R2SQL Server 2008 R24 Server Class CPU cores8 GB RAM1 TB Free Disk SpaceVirtual or Physical

Conversion Server


Space needed in Works for discrete item conversion No easy way to estimate this:

• Test with % of patients and extrapolate Also take into account scanned images

Space needed in Scan warehouse for image conversion PDFs loaded into scan warehouse 900KB per Chart Summary

Space Needed for Conversion


Panel Questions

Q1 - Sandy: How did you decide on the # of years of data to migrate?

Q2 – Sandy: Knowing what you know now, would you have chose to migrate?

Q3 – Sandy: What was one of the unexpected benefits of data migration? Any downsides?


Sandy’s Key Insight

Message to audience: Assess data needs before you actually jump into the project


OUR PHILOSOPHY


Thank you for joining us today. To access the slides from today’s presentation, please visit:

http://wiki.galenhealthcare.com/Category:Webcasts

For additional assistance or to request information about our many services and products, please contact us through our website:

www.galenhealthcare.com

http://wiki.galenhealthcare.com/Category:Webcasts

http://www.galenhealthcare.com/

MUCH MORE THAN I.T.

GALENHEALTHCARE.COM