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					  INTERPRETATION OF THE
ACUTE CARE HOSPITALIZATION
         REPORTS
Objectives
• Describe how the Acute Care Hospitalization outcome
  measure is calculated
• Explain the differences between all of the reports
  related to OASIS outcome data
• Explain how to interpret the HHQI report
• Describe how to use these reports to guide your
  agency’s QI program
Data & Measurement
• Based on OASIS data submitted by Medicare-certified home
  health agencies
• Required for all Medicare/Medicaid patients
• Calculated on completed Episodes of Care
• Acute care hospitalization measure is a Utilization Outcome
  measure
• All patients have the potential for acute care hospitalization,
  EXCEPT:
     – Patients who die at home
     – Patients who are assessed at SOC as non-responsive (M0570 & M0580)
OBQI Outcome Rates
Include all Patient Care Episodes that began and ended
within the 12-month report period
– Episodes start with an admission to home health care or
  resumption of home health care after an inpatient facility stay

– Episodes end with a discharge from home health care,
  including discharge due to death, or admission to inpatient
  facility for 24 hours or more

– A patient may have multiple episodes within a 12-month period
Data & Measurement
 Rate is calculated as the % patients who have achieved
  that specific outcome during their home care stay, out of
  all eligible patients
 Episode of care must start and end within the specified

  12-month period
 OASIS items used M0100- timepoint 6, 7, 8, 9

 M0855 – type of inpatient facility: 1 - hospital
Outcome Data Source
    Comparison
    Data Sources/Reports
   OBQI Outcome Reports from CASPER
     • Risk-Adjusted Outcome Report
     • Descriptive Outcome Report
     • Patient-Level Tally Outcome and Tally Case Mix Reports
     • Case Mix Analysis Summary Report
Available for Home Health Agencies, State Agencies,



    Quality Improvement Organizations and CMS
Data Sources/Reports
   Reports are updated in the CASPER System on the
    Monday following the second Saturday of each month
   Data is approximately 2 ½ months old when posted
   Updates include late OASIS submissions and/or
    corrections for previous months
Data Sources/Reports
Risk-adjustment:
• Helps to level playing field for providers with higher risk or
  more frail patients
• Allows valid comparisons between individual agencies, states,
  and national rates
• Uses predicted rates to adjust actual rates
Data Sources/Reports
Risk-adjustment Determination
• Agency Prior Rate
  • Performance from 12 months prior, adjusted for differences in your patient’s
    population over time
  • Comparing current performance to this rate means comparing against how you
    would have performed 12 months ago, if your patient’s case mix was similar to
    what it is today

• National Reference
  • Predicted rate for each agency based on that agency’s case mix
  • Comparing current performance to this rate means comparing against how risk
    model predicts you should perform based on your patient’s case mix factors
Data Sources/Reports
OBQI Reports
• Agency rate is NOT risk-adjusted
• Adjusted prior & national reference rates are risk-adjusted
• Does include late oasis submissions and /or corrections
IPRO Agency Trend Reports
• Agency rate IS risk-adjusted
• Same data is currently used by CMS for 8th SOW progress measurement
   • Acute Care Hospitalization
   • Oral Medications
   • Second Quality Measure (CIPG agencies)
Data Sources/Reports
Home Health Compare
(http://www.medicare.gov/HHCompare/Home.asp)
• Agency rate IS risk-adjusted
• National average is not risk-adjusted
• Updated quarterly (March, June, September, December)
• Does not include late OASIS submissions and/or corrections

Home Health STAR Website
• Publicly reported data and OBQI report data trends
• National percentiles

Vendor Data
• Various sources and report formats
• Benchmarking rates
Home Health Compare Report
Percentage of patients who get better at walking or moving around

Why is this important?

Most people value being able to take care of themselves. . . .

THIS IS THE AVERAGE FOR
ALL THE HOME HEALTH                 34%
AGENCIES IN THE PHASE I
STATES (UNITED STATES)

THIS IS THE AVERAGE FOR
ALL HOME HEALTH                  33%
AGENCIES IN THE STATE
OF XXXXX

ABC HOME HEALTH AGENCY    Not Available-The number of patients is too small to report. Call
                          the agency to discuss this quality measure.

XYZ HOME HEALTH AGENCY
                                       40%


                          0%        20%          40%            60%          80%        100%
* Improvement in Pain Interfering with Activity and Improvement in Status of Surgical Wounds are not risk-adjusted for HH STAR
  or QIO evaluation data.
HHQI National Campaign
   Monthly Reports
Monthly Reports
 Monthly individualized agency-specific reports will be
  forwarded by IPRO starting the end of March
 State and national benchmarking rates

    •   Agency National Percentile Ranking
    •   National 20th Percentile Rate
    •   National 10th Percentile Rate
    •   Agency Statewide Percentile Ranking
    •   Statewide 20th Percentile Rate
    •   Statewide 10th Percentile Rate
Monthly Reports
 Monthly individualized agency-specific reports
 Case mix characteristics of hospitalized patients

 Actual versus risk-adjusted agency rates

 Number of monthly hospitalizations out of total

  transfers / discharges
 Percentage of hospital admissions by:

     • Urgency of Hospitalization (M0890)
     • Reason for Hospitalization (M0895)
     • Day of Week (M0906)
What Reports To Use?
Reports
   OBQI Reports
     – Risk-adjusted Outcome Report
     – Descriptive Outcome Report
     – Case-mix Profile Report
     – Patient Tally Reports
     – Case Mix Analysis Summary Report
 Home Health Compare
 Home Health STAR Web site

 IPRO Agency Trend Report

 Home Health Quality Improvement (HHQI) Campaign
  Report
 Vendor Reports
Predictive Modeling
   Definition
– “A practice that utilizes the sophistication of statistical
  models and the wealth of information available in the
  home care industry to predict potential patient
  outcomes.”

Source: Twiss, A., Lang, C., Long, B. (2006). Predictive modeling: a set of
  tools used to stratify a population according to its risk of nearly any
  outcome. Remington Report, 14 (4), 7-12
Predictive Modeling
 Predicts the probability of future events from
  past occurrences
 Uses variable factors that may influence future

  behavior or outcome
 Builds on the risk adjustment methodology

– Accounts for the differences in the two samples so they can be
  compared legitimately despite the differences in the two
  samples
    Predictive Modeling
   Application to home health care
     – Identify patients who may benefit from a specific
       intervention(s) before the occurrence of adverse
       outcomes
     – In the past, intuition or clinician experience occurred
     – Now, there is patient related data available to develop
       a patient picture
Predictive Modeling
 Reports
   – Patient Tally Report
   – Case Mix Analysis Summary Report
   – HHQI Campaign Report
 Plan interventions for the patients who will most
  benefit
 Better use of agency resources

 Improved patient outcomes
QUESTIONS

        &

            ANSWERS

				
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posted:12/12/2011
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