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Managing Cost and Outcome of Post Hospital Care. Reg Warren PhD, Rick Glanz and Amy Leibensberger The National Predictive Modeling Summit September 13, 2007. The dilemma for post hospital care?. MCO’s spent $7.9B on SNF and Home Health in 2005 (MedPac 2007 ) - PowerPoint PPT Presentation
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Managing Cost and Outcome of Managing Cost and Outcome of Post Hospital CarePost Hospital Care
Reg Warren PhD,Rick Glanz and Amy Leibensberger
The National Predictive Modeling SummitSeptember 13, 2007
The dilemma for post hospital care?The dilemma for post hospital care?
MCO’s spent $7.9B on SNF and Home Health in 2005 (MedPac 2007)
1/3 of hospitalized seniors will receive post acute care
1/3 of those will not go to the most appropriate setting
Misalignment of incentives: per diem High degree of practice variation Over-utilization unnecessarily exposes members
to institutional risks
Managing Cost and Outcome of Managing Cost and Outcome of Post Hospital CarePost Hospital Care
Diagnosis vs Function The Predictive Model
Regression Severity adjustment
Application Real-time decision support Retrospective comparison
Influence on cost and outcome
People get postacute care because they are frail and Care Dependent:
Function Driven
People go to the Hospital because they are Sick:
Disease Driven Treat the Illness
Restore the Ability
Acu
teP
osta
cute
Key PredictorKey Predictor
Functional MeasurementFunctional Measurement
EatingGroomingBathingDressing Upper BodyDressing Lower BodyToiletingBladder ManagementBowel ManagementBed, Chair, WC TransferToilet TransferTub/Shower TransferWalk/WCStairs
• Expression• Comprehension• Social Interaction• Problem Solving• Memory
Functional Independence Measure - FIM (18-126)
Function Burden of Care Function Burden of Care
Functional needs Drives >90% of skilled utilization Admit function- predict outcome Discharge setting : 5 points FIM equate
to one hour caregiver burden/day
Calibrate the ContinuumCalibrate the Continuum
Home
Post-acute
Other
HH
SNF
20% of SNF patients would get the same result at home
SNF LOS can be reduced by 40% without impacting functional result
HH Cost can remain stable even with increased referrals
Most Acute Rehab cases would get the same result in SNF
Acute DischargesSr. Population
Managing Cost and Outcome of Managing Cost and Outcome of Post Hospital CarePost Hospital Care
Diagnosis vs Function The Predictive Model
Regression Severity adjustment
Application Real-time decision support Retrospective comparison
Influence on cost and outcome
• Leader in post-acute outcome measurement since 1995
• Manage over 900,000 Senior lives in SNF, Acute Discharge, Acute Rehab, Home Health
• Database of 250,000+ post-acute cases• Over 30,000 new records added each year
• California, Colorado, Washington, Maryland, District of Columbia, Virginia, Arizona, Pennsylvania and Tennessee
• Kaiser Permanente, PacifiCare, Health Net, Group Health Coop, and AmeriGroup
• MHS Participant
Improvement in Function in SNF: Improvement in Function in SNF: PredictablePredictable
ADMFIM
120100806040200
DIS
FIM
140
120
100
80
60
40
20
0
Correlations
1.000 .818**. .000
500 500.818** 1.000.000 .500 500
Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N
ADMFIM
DISFIM
ADMFIM DISFIM
Correlation is significant at the 0.01 level(2-tailed).
**.
80 yr old female with CHF, cellulitis, UTI
and prior stroke
Discharge Site and Functional LevelDischarge Site and Functional Level(FIM 18-126)(FIM 18-126)
Discharge Site Considerations FIM Score
Home AloneOP Therapy/Home Safety >108
Home with AssistOP (Outpatient) Therapy >90
Home w/Assist or ALFHome Health Services >80
Home, SNF, Custodial, B&C w/24-hour Assistance <79
Diagnosis, medical complexity or other social, caregiver or medical issues may influence the functional level at which the patient is discharged.
ADMFIM
120100806040200
EPIS
OD
E
120
100
80
60
40
20
0
Length of SNF Stay: Length of SNF Stay: Less Predictable Less Predictable
Correlations
1.000 -.265**. .000
500 500-.265** 1.000.000 .500 500
Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N
ADMFIM
EPISODE
ADMFIM EPISODE
Correlation is significant at the 0.01 level (2-tailed).**.
Medical Complexity ScaleMedical Complexity Scale
Level 0: No systemic disease other than primary diagnosis
Level 1: Pre-morbid, inactive and/or irrelevant Level 2: Active, relevant. Not limiting function Level 3: Active, relevant. Limiting function Level 4: Active, relevant. Severely limiting function Level 5: Moribund/Terminal
Relevant ConditionsRelevant Conditions
Restricted Weight BearingRestricted Weight Bearing Pressure Wound: II, III or IVPressure Wound: II, III or IV Vascular (non-pressure) woundVascular (non-pressure) wound IVIV Vent Vent
Hospital: not currently dependent Hospital: not currently dependent Currently DependentCurrently Dependent
Severe ObesitySevere Obesity HemodialysisHemodialysis
Regression: Length of Skilled StayRegression: Length of Skilled StayIndependent
VariableCoefficient Patient’s
Actual Value
Result
Random Error(constant)
24.45
Admission FIM -.234 65 -15.21
Age .034 82 2.78
Days Post Onset
.565 4 2.26
Condition(IV/Obese)
13.1
Predicted Episode LOS =
27.38
X
X
=
=
=
+
+
+
X =
=+
82 y/o femaleUTIAcute: 6 days
(9.24)
(12.02)
(14.28)
How powerful is the model?How powerful is the model?
60%
38%
2%
SMTX Model Treatment Unknown
TherapyIntensity
DisabilityCo-morbidityDPODx (stroke)AgeCondition Grouper
EACH patient is case adjusted:
Impairment Group
Age
DPO
Adm FIM
Med Complex
Pt. #30: CVA ,75 yrs, DPO 12, Adm FIM 30, and Med Complex 4
Pt. # 1: UTI, 82 yrs, DPO 31, Adm FIM 57, and Med Complex 3
Query
LOS: 15 days DC FIM: 50
LOS: 11 days DC FIM: 81
Best Practice Calculation
LOS: 13 days DC FIM: 62.5
LOS: 21 days DC FIM: 50
LOS: 14 days DC FIM: 81
Actual Calculation
LOS: 18 days DC FIM: 62
SMTX National Comparison
(60% most efficient facilities)Actual Values
Pts #2-30
VARIANCELOS: 28%DC FIM: 1%
REGRESSION
Managing Cost and Outcome of Managing Cost and Outcome of Post Hospital CarePost Hospital Care
Diagnosis vs Function The Predictive Model
Regression Severity adjustment
Application Real-time decision support Retrospective comparison
Influence on cost and outcome
Expe
ctat
ions
High Practice VariationHigh Practice Variation
Actual Result
Ass
essm
ent
Treatment
Dis
char
ge
Plan
ning
Admission Discharge
Postacute Episode
Full
Rec
over
yN
o R
ecov
ery
Real-Time Decision Support
Reduced Practice VariationReduced Practice VariationA
sses
smen
t
Mos
t Lik
ely
Res
ult
Treatment
Expe
ctat
ions
Dis
char
ge
Plan
ning
Actual Result
Admission Discharge
Traditional Timeframe
Value Added
Postacute Episode
12
Retrospective ComparisonRetrospective ComparisonSeverity-Adjusted ComparisonSeverity-Adjusted Comparison
Case
s in
SM
TX
Reha
b St
art L
ag
Opt
imal
Reh
ab C
ycle
Acut
al R
ehab
Cyc
le
Reha
b Cy
cle
Varia
nce
Disc
harg
e La
g
Reha
b AL
OS
Expe
cted
Dis
char
ge F
IM
Actu
al D
isch
arge
FIM
FIM
Dis
char
ge V
aria
nce
% D
isch
arge
d to
Com
mun
ity
Ther
apy
Hrs
per D
ay
Jefferson Ave 45 1.4 7.9 10.2 28% 1.1 12.7 101.2 96.0 -5% 0.83 0.97
Mercy Court 67 1.3 11.7 12.1 3% 0.8 14.2 77.0 76.1 -1% 0.83 1.43St AllensGarden RidgeSan AngeloPacific CrestCareBrook
Total/Average
Efficiency Quality
Managing Cost and Outcome of Managing Cost and Outcome of Post Hospital CarePost Hospital Care
Diagnosis vs Function The Predictive Model
Regression Severity adjustment
Application Real-time decision support Retrospective comparison
Influence on cost and outcome
SNF LOS Variance Trend
-10
0
10
20
30
40
50
July
Aug
Sep Oct
Nov
Dec Ja
n
Feb
Mar
Apr
May
June July
Aug
Sep
t
Month
Perc
ent V
aria
nce/
Que
ry
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Ther
apy
Hour
s/Da
y
cycle dcFIM Hours/Day
Client Q3, 2006 Source: SMTX
73
96.7 93.2
105.8115.5
5060708090
100110120130140
SNF Admit SNF DC HH Admit HH DC Follow-up
Assessment
Tota
l FIM
Sco
reFunctional recovery Across Settings:
SNF thru HH to Follow-up*11-01 to 9-05
Source: SMTX
SNF: all dc homeHH: all admitted from SNFFollow –up: all records (N=1259)
Improving Acute DC PlacementImproving Acute DC Placement
49%
58% 58%61% 63%
60%
67%64%
57%
40%
34%37%
32%28% 30% 28% 30% 31%
11%8%
5% 7% 9% 10%5% 6%
12%
0%
10%
20%
30%
40%
50%
60%
70%
80%
J an(N=291)
Feb(N=264)
Mar(N=260)
April(N=247)
May(N=284)
Jun(N=321)
July(N=334)
Aug(N=317)
Sep(N=195)
Home Skilled Other
Influence on UtilizationInfluence on Utilization
Average Medicare PlanLOS: 22 daysSNF Admits/k: 50-65SNF Days/k: 900-1100PMPM: $33
Predictive Model ResultsLOS: 16 daysSNF admits/k: 40-50SNF days/k: 600- 800PMPM: $22.50
Reducing Practice Variation Using Reducing Practice Variation Using Predictive ModelsPredictive Models
11
SNF Days of Treatment SNF Days of Treatment
Patie
nt H
ealth
Impr
ovem
ent
(Fun
ction
al Im
prov
emen
t Mea
sure
men
t)
Pre-Implementation Post-Implementation
SNF Days of Treatment SNF Days of Treatment
Patie
nt H
ealth
Impr
ovem
ent
(Fun
ction
al Im
prov
emen
t Mea
sure
men
t)
Pre-Implementation Post-Implementation
$5,655 average cost per case
23 point average gain in Functional Improvement Measurement (“FIM”), an internationally recognized scale of disability
$4,485 average cost per case (20.7% decrease)
23 point average gain in FIM (unchanged)
One Year
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