emerging profiles of michigan long-term care users mary l. james, m.a. brant e. fries, ph.d....
TRANSCRIPT
Emerging Profiles of Michigan Long-Term Care Users
Mary L. James, M.A.Brant E. Fries, Ph.D.
University of Michigan
March 23, 2006
Agenda
Compare people who use nursing homes with people using home- and community-based services (HCBS)
Temporal trends Selected sub-populations Next steps
Notes
1999-2005 data from MDCH data warehouse
MDS (NH) and MDS-HC (HC) All people, not only Medicaid eligibles 2005 data from Jan-June Admission = all admissions in year Prevalence = assessment closest to
July 1st of that year
Number of Annual NH Admissions is Growing
0
10,000
20,000
30,000
40,000
50,000
60,000
NH HCBS
Number of NH Admissions is Growing – From Hospitals
0
10000
20000
30000
40000
50000
60000
NH HCBS
From Hospital
NH Admissions Increasingly Physically Dependent
0%
25%
50%
75%
100%
Dependent
Limited
Independ
NH HCBS
ADL Hierarchy
HC Admissions Increasingly Cognitively Dependent
0%
25%
50%
75%
100%
DependentLimitedIndepend
NH HCBS
CPS Scale
RUG-III Categories at Admission
0%
25%
50%
75%
100%
RehabExtensSpecialClinCompImpairCogBehaviorPhysical
NH HCBS
Q1A/Q1B – NH Prevalence
0% 25% 50% 75% 100%
Prefer communitySupport positive
Identifying LTC Sub-populations
SMI (any of 4)• verbally abusive, physically abusive, socially inappropriate• hallucinations, delusions• bipolar disease, schizophrenia• symptoms of depression
Short stay• Admission from hospital (NH)• Medicare (NH)• LOS < 90 days (both NH and HCBS)
Long stay: >1 year Age <45 years Note: subpopulations overlap somewhat
Selected Sub-Population Notes
Used 2004 (last year with full data, as some pops had low prevalence)
Some differences in NH and HC definitions (long- and short-stay)
SMI not really SMI
National Study: Some Diagnoses Decline with Age
0%
10%
20%
30%
40%
50%
60%
0-4 5-14 15-24
25-34
35-44
45-54
55-64
65+
Age Decade
ID/Seizures
ID/Seizures&Quad
Hemi- or Quadriplegia
National Study: Some Diagnoses Increase in Middle Age
0%
10%
20%
30%
40%
50%
60%
0-4 5-14 15-24
25-34
35-44
45-54
55-64
65+
Age Decade
ID/Seizures
ID/Seizures&Quad
Hemi- or Quadriplegia
Multiple Sclerosis
National Study: Some Diagnoses Increase in Old Age
0%
10%
20%
30%
40%
50%
60%
0-4 5-14 15-24
25-34
35-44
45-54
55-64
65+
Age Decade
ID/Seizures
ID/Seizures&Quad
Hemi- or Quadriplegia
Multiple Sclerosis
CVA with Hemiplegia
Alzheimer’s Disease
Cancer
Cardiac Conditions
Prevalence of Selected Subpopulations
0%
10%
20%
30%
40%
50%
60%
NH HCBS
ADL Special Pops
0%
25%
50%
75%
100%
DependentLimitedIndepend
NH HCBS
Cognition Special Pops
0%
25%
50%
75%
100%
DependentLimitedIndepend
NH HCBS
WHERE THEY CAME FROM - NH
0%
25%
50%
75%
100%
OtherHomeOther NHHospital
Q1a/Q2a by NH Subpopulations
0%
25%
50%
75%
100%
Q1aQ2a
NH HCBS
Prevalence of Conditions in HC Subpopulations
0%
25%
50%Head Trauma
Multiple Sclerosis
Alzheimer's
Dementia other thanAlzheimer's
Hemiplegia/Hemiparesis
Cancer (not including skincancer)
Falls
Prevalence of Conditions in HC Subpopulations
0%
25%
50%Head Trauma
Multiple Sclerosis
Alzheimer's
Dementia other thanAlzheimer's
Hemiplegia/Hemiparesis
Cancer (not including skincancer)
Falls
Prevalence of Conditions in HC Subpopulations
0%
25%
50%Head Trauma
Multiple Sclerosis
Alzheimer's
Dementia other thanAlzheimer's
Hemiplegia/Hemiparesis
Cancer (not including skincancer)
Falls
Prevalence of Conditions in HC Subpopulations
0%
25%
50%
Head Trauma
Multiple Sclerosis
Alzheimer's
Other Dementia
Hemiplegia/Hemiparesis
Cancer (not skin)
Falls
Results
Following slide shows output from preliminary analysis
Groups (boxes) with lighter color
more like Passages individuals Groups with darker colors
less like Passages individuals
A B CD
E
X
Results – “Focused Approach”
Groups “most like” Passages individuals:• < 65, in facility 60d-2yr, at most mildly
cognitively impaired (A, B, D)• < 65, in facility >2yr, with hemiplegia,
quadriplegia, or paraplegia (C)• 65+ age, in facility 60d-2yr, in lowest RUG-III
case-mix groups, cognitively intact (E)• Focused target is 1.5% of entire NF population
– 62.2% sensitivity– 98.5 specificity
Next Steps
Link new data with:• Medicaid identifiers• Death records• Length of stay information
Examine longitudinal outcomes Identify “boutique” populations
• What are your ideas to define these? Make data available to UoM LTC researchers Could we forge a common research agenda?
