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RVU - what are they?
- CPT - "Current Procedure Terminology" - codes hospitals can use to bill insurance for imaging procedures
- RVU defined - way to assign a value ($) for each service so what a hospital charges is uniform accross the united states
- "Relative Value Units"
- Defined by CMS (Medicare) as the reimbursement $ for a given procedure
- Flexibility in how radiology groups define the RVUs
- Recommended by the AMA (RUC) - lead by a radiologist Zeke Silva
- Defined differently between private and public payors?
- CPT to RVU Codes mapping? how is it done?
- Canada (David)
- does not have the concept of an RVU?
- Have diagnostic codes
- All fee based (every province has their own flavor of it)
- 80/20 - 80% is the same, 20% variance
- Do map to CPT codes, but for secondary use
- Moving forward, highly dynamic
- Three territories, 10 provinces. Each jurisdiction is managed independently for healthcare
- Codes/procedures standardized by each province
- OHIP = Ontario Health Insurance Plan (universal healthcasre)
- Grand Caymans published their reimbursements
- LOINC to CPT Mapping
- https://www.ahra.org/
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How does billing work in the NHS and how does it compare to Canada?
- Candaa has some similartiies?
- NHS moving to snomed
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PACS Migrations Guidance
- https://siim.org/news/615974/DICOM-Supplement-223-is-Incorporated-into-the-DICOM-Standard.htm
- What are the root causes of migration problems?
- Variety/Range of goals
- "DataBrokers" - create longitudinal records + make it de-identified
- Don't know much about DICOM data so run into problems (e.g. SCO tomos dont work with viewer)
- "Clinical World"
- Hospital Acquisition - want to normalize patient information
- Study/Series Descriptions (for hanging protocols)
- Patient matching
- Prior/Relevant Prior
- Hospital Acquisition - want to normalize patient information
- MGH Migration from one pacs to another (example)
- DICOM data is dirty - unique identifiers not always unique - what do you do?
- Not always easy rules
- Need Process/Tools/etc
- DICOM data is dirty - unique identifiers not always unique - what do you do?
- "DataBrokers" - create longitudinal records + make it de-identified
- Expectation Management
- Start With "Migrate ALL files"
- some are too hard to migrate?
- End with "Migration of some files"
- "data liquidity" ?
- Start With "Migrate ALL files"
- Mike Toland from University of Maryalnd had a talk at SIIM 2022 on ILM (data retention)
- Legal department wanted to get rid of as much data as they legally could
- Clinical people wanted to keep as much as possible
- 99.9% of studies > 10y won't ever be looked at it, but for that .1% case, it can hugely useful
- performance/capacity
- Hardware speced just for clinical workloads
- Architecture - stores updates in DB only
- Aviram / DICOMatics *
- Variety/Range of goals
- Does cloud fix it all?
- Some things are easier - storage, speed, scale
- Summary
- Scoping is critical!
- Data cleanup is key!