Help with Mortality reviews!!
Our department has started reviewing all mortalities for query opportunities and as a task force approach are deciding expected or unexpected on the mortality. We use our ROM scoring and all 3's and 4's we deem as expected and then review for quality of care or other issues and refer them to the appropriate teams for action.
My question is....opinions, please....should we only look at diagnosis codes that are present on admission or all coded diagnosis? Some on our task force want to look at the principle diagnosis and procedure only and don't want to take into consideration any issues other than that. What is your opinion?
Thanks!
April Floyd, RN, CCDS
Anderson RMC
601-553-6299
My question is....opinions, please....should we only look at diagnosis codes that are present on admission or all coded diagnosis? Some on our task force want to look at the principle diagnosis and procedure only and don't want to take into consideration any issues other than that. What is your opinion?
Thanks!
April Floyd, RN, CCDS
Anderson RMC
601-553-6299
Comments
Dorie Douthit, RHIT,CCS
Incidentally, all encounters factor into the numerator/denominator factor that will be used to give your facility an 'overall' Observed/Expected Ration for Mortality. It is wise to focus on Expired Cases, but bear in mind that each and every patient admitted factors into the overall risk-adjusted outcomes for Mortality Reporting.
Hope this helps a bit?
Paul Evans, RHIA, CCS, CCS-P, CCDS
Manager, Regional Clinical Documentation & Coding Integrity
633 Folsom St., 7th Floor, Office 7-044
San Francisco, CA 94107
Cell: 415.637.9002
Fax: 415.600.1325
Ofc: 415.600.3739
evanspx@sutterhealth.org
I'd be happy to delve into our process further if you have any more questions:)
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
We've recently been looking at expired cases.
We also looked closely at the mortality model available to us
(University Healthsystems Consortium) & were able to identify some
frequently occurring dx that OFTEN affect mortality. We've applied that
analysis by specifically focusing concurrent reviews and queries to
increase capture. Analyzing a case against the applicable UHC mortality
model can be a time consuming process, thus not feasible to do for every
case concurrently.
This analysis and concurrent review focus is an approach we're pursuing
toward Paul's point that ALL cases affect the Observed/Expected ratio.
In a similar manner, there are certain things that often affect the APR
DRGs (acute renal failure for example) and focusing on ACCURATE
CONSISTENT capture of those diagnosis will help the O/E ratio.
One additional point, for the UHC mortality model, only POA (Y) dx's
are eligible to affect their mortality models.
It helps to understand what information one has available, and against
which one benchmarks.
Don
The APR/DRG system is complicated.
I concur that 'acute organ failures' will often cause the ROM score to rise; it is important to ensure that major dysfunctions and conditions, such as PNA, AMI, Stroke, peritonitis, acute renal/respiratory failure, to name a few, are coded for each case.
You may want to ensure the coding (HIM) staff employ BOTH MS-DRG and APR-DRG methodology as they review and code cases.
DEFINTION Below:
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 600 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 600 hospitals nationally.
Paul Evans, RHIA, CCS, CCS-P, CCDS
Manager, Regional Clinical Documentation & Coding Integrity
633 Folsom St., 7th Floor, Office 7-044
San Francisco, CA 94107
Cell: 415.637.9002
Fax: 415.600.1325
Ofc: 415.600.3739
evanspx@sutterhealth.org
Thanks, guys!
April