Mortalities

fentona@bronsonhg.orgfentona@bronsonhg.org
in CDI Talk Archive
I review mortalities on a daily basis looking for missed opportunities that may affect SOI/ROM. In Premier data our E/O ratio for mortalities is high and has been all year. My understanding is they have their own risk adjustment model and it is not public knowledge. We have been successful in moving patients scores to 4/4 or at least closer to this but it has not affects our E/O ratio. Is anyone familiar with this or having the same issues? I would love any input or suggestions.
Thanks,
Amy

Amy Fenton RN, CDS
Bronson Healthcare Group
Kalamazoo, MI
269-341-8442

Comments

  • jschoonhovenjschoonhoven
    edited April 2016
    I think an easy concept for us to miss is that the mortality data is based on ALL patients not just the deceased ones.
    To truly move the E/O ratio, one has to document full severity of all the patients. That’s the only way to show that the number that actually die is small considering the very ill patients that are being treated.
    In other words, if your population of patients appears to be very healthy, less should be dying. If we capture through appropriate documentation how ill they actually are, then it is expected that more will pass away.

    Therein lies our reason for working...
    Janice

    Janice Schoonhoven RN, MSN, CCDS | Manager | Clinical Documentation Integrity
    PeaceHealth | 3333 Riverbend Dr. | Springfield, OR 97477
    office 541-222-5348 | fax 541-222-2427 | efax 541-335-2347



  • katysuegood@gmail.comkatysuegood@gmail.com
    edited April 2016
    I am not familiar with their methodology but keep in mind that it's ALL your patients that factor into the expected rate. Even if all your deaths were a 4/4 you still may have a high O:E if you are not accurately capturing the SOI/ROM of all your patients. Most 4/4's still survive hospitalization. This is yet another reason for all-payer review (if you are not already doing so).
    Additionally, I always think it's important to ensure there are no quality of care issues. Not suggesting that there are but it needs to be ruled out. Before we expanded our program our SOI/ROM was ridiculously high (approaching 2!!). Before we would blame that all on poor documentation/coding, the hospital did a thorough quality review to make sure there were no other issues... We still struggle because of some specific regional issues but we have cut our O:E in half with all payer review in addition to a post-coding mortality review process.

    Katy Good, RN, BSN, CCDS, CCS
    Clinical Documentation Program Coordinator
    AHIMA Approved ICD-10CM/PCS Trainer
    Flagstaff Medical Center
    Kathryn.Good@nahealth.com
    Cell: 928.814.9404


  • katysuegood@gmail.comkatysuegood@gmail.com
    edited April 2016
    Excuse my typos.

    That should say that our O:E was approaching 2 before our program was initiated.

    Sorry!

    Katy Good, RN, BSN, CCDS, CCS
    Clinical Documentation Program Coordinator
    AHIMA Approved ICD-10CM/PCS Trainer
    Flagstaff Medical Center
    Kathryn.Good@nahealth.com
    Cell: 928.814.9404


  • evanspx@sutterhealth.orgevanspx@sutterhealth.org
    edited April 2016
    I was asked to provide one definition for this metric.

    5. Acute Care Admission Mortality Ratio (Observed/Expected) (1 measure)

    Definition: Acute Care Admissions Mortality ratio is the APR-DRG risk-adjusted ratio of observed/expected deaths for acute inpatient admissions based on the MIDAS DataVision benchmark. Results are compared to the MIDAS “universe” standardized O/E mortality ratio (1.0). A ratio of 1.0 means that a hospital’s mortality is average in comparison to the national MIDAS Comparative Database (CDB) comprising more than 800 hospitals. Below 1.0 means that the mortality rate is lower than the average performance of the comparative group and above 1.0 means that the hospital’s mortality is higher than the average performance of the comparative group/database.
    Numerator: Observed deaths.
    Denominator: Expected deaths.
    Measurement Calculation: Numerator divided by denominator.
    Data Source: MIDAS DataVision Hospital APR-DRG Ranking Report.
    Benchmark Goal Source: MIDAS DataVision web application comparison population for the standardized mortality ratio benchmark of 1.0. This is based on the concurrent period MIDAS comparative database of approximately 100,000,000 encounters from more than 800 hospitals nationally.
    Threshold: 1.0
    Full Performance: 1.0


    Paul Evans, RHIA, CCDS, CCS, CCS-P
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