a study of nursing facility transitions who leaves who stays n.
Skip this Video
Loading SlideShow in 5 Seconds..
A Study of Nursing Facility Transitions: Who Leaves? Who Stays? PowerPoint Presentation
Download Presentation
A Study of Nursing Facility Transitions: Who Leaves? Who Stays?

Loading in 2 Seconds...

play fullscreen
1 / 22

A Study of Nursing Facility Transitions: Who Leaves? Who Stays? - PowerPoint PPT Presentation

  • Uploaded on

A Study of Nursing Facility Transitions: Who Leaves? Who Stays?. Presentation to Olmstead Advisory Committee November 5, 2009 Kathryn E. Thomas, Ph.D. Kathleen H. Wilber, Ph.D. University of Southern California Davis School of Gerontology. Outline.

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
Download Presentation

PowerPoint Slideshow about 'A Study of Nursing Facility Transitions: Who Leaves? Who Stays?' - dolf

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
a study of nursing facility transitions who leaves who stays

A Study of Nursing Facility Transitions: Who Leaves? Who Stays?

Presentation to Olmstead Advisory Committee

November 5, 2009

Kathryn E. Thomas, Ph.D.

Kathleen H. Wilber, Ph.D.

University of Southern California

Davis School of Gerontology

  • A Fresh Look at Nursing Home Transition
    • Minimum Data Set, Episodes of Care
    • Transition outcomes vs. discharge outcomes
  • Goal of Study #1: Identify characteristics associated with successful community discharge
  • Goal of Study #2: Identify barriers to transition among residents with a community living preference
  • Implications
a fresh look nursing facility transition
A Fresh Look:Nursing Facility Transition
  • 40% of people 65+ likely to spend some time in a nursing home.
  • Targeting candidates is a critical component of NF transition programs.
  • Transition as “Conversion Diversion” - Getting individuals out before they convert to long-stay
  • Focus on “Transition Outcomes” instead of traditional “Discharge Outcomes”
a new approach episodes of care
A New Approach: Episodes of Care
  • MDS: A wealth of data, generally underutilized in NF Transition efforts
    • 10+ million records/year
    • Combination of short & long-stay residents
    • Difficult to extract meaningful data
  • Transition Outcomes vs. Discharge Outcomes
    • Transition outcomes require broader perspective.
    • Need to track person across settings.
episode of care
Episode of Care

Episode End Date

Discharge date and Discharge Status taken from Discharge Tracking Form

Episode Start Date

All variables taken from full Admissions Assessment.

Based on the work of Fisher et al., Medical Care, 41(12) 2003.

study 1 successful transitions

NF placement

90+ days

Study #1: Successful Transitions
  • Unit of Analysis: Episode of care
  • Sample: MDS from SCAN/Medicare (n = 4635)
  • What did we do? We compared…
  • Community Discharge w/in90 days


  • Community discharge = home w/ home health, home w/o home health or board & care/assisted living
who was in the sample
Who was in the sample?
  • Who we included: MDS records for SCAN and Medicare individuals who entered a NF in Los Angeles, Orange, Riverside, or San Bernardino between 1/1/01 and 12/31/03.
  • Who we excluded: Episode length < 14 days, those who died, residents discharged to the hospital w/in 90 days, MR/DD, persistent vegetative state
what did we look at
What did we look at?
  • Predisposing
    • Age, gender, marital status, race & education
  • Need
    • Cognitive functioning, depression, comorbidities, social engagement, behavior, ADLs, incontinence, recent fracture, recent fall, admitted-from location
  • Enabling
    • Generic: Living situation before admission, legal responsibility, payment source, type of insurance
    • Transition-Specific: Community living preference, presence of support person positive toward discharge, discharge prediction timeframe, receipt of community living skills training
study 1 questions
Study 1: Questions
  • We were interested in individual characteristics associated with successful transition to the community
    • Which transition-specific variables affect transition?
    • Does SCAN membership affect transition?
results what supports transition
Results: What Supports Transition?
  • Preference (Q1a) increases the likelihood of transition by 28%
  • Presence of support person (Q1b) increases the likelihood of transition by 250%
  • Discharge prediction (Q1c): Those predicted to stay 30+ days are 43% - 84% less likely to transition than those predicted to stay < thirty days
  • Community living skills training (P1ar) increases the likelihood of transition by 42%
  • SCAN membership increases the likelihood of transition by 50%
study 2 barriers to transition
Study #2: Barriers to Transition
  • Subsample: Only residents who expressed/indicated preference to return to the community (n = 2935)
  • Question: Who gets stuck in the NF and why?
Supports Transition



Recent fracture

SCAN (44%)

Support person (269%)

Community living skills training (133%)

Barriers to Transition

ADL limitation

Bowel incontinence

Medicaid (- 43%)

Discharge prediction > 30 days (-36% to -76%)

  • Characteristics & Barriers
  • MDS
  • Targeting Strategies
  • Transition Interventions
characteristics barriers
Characteristics & Barriers
  • Key Issues
    • Support person most important factor
    • More research needed on discharge prediction and community living skills training variables.
  • Insurance
    • Medicaid a consistent barrier, SCAN positive
    • SCAN members are less likely to become long-stay
    • Reconsider S/HMO models?
mds 3 0
MDS 3.0
  • Q1a, Q1b and Q1c removed
    • Replaced by general question about goals and desire to talk to someone about community transition
    • Based on this research, it is unfortunate that ‘Presence of a Support Person’ and ‘Predicted Discharge’ were removed
  • Transition question is still at the end of the assessment and only on full assessments, not quarterly.
mds 3 0 cont
MDS 3.0 (Cont)
  • New Return to Community CAT
    • Triggers could be informed by results of this study.
  • CAT may shift responsibility for transition from NF to agencies. Potential to overwhelm.
    • Results could be used to help prioritize list from CAT
    • CNFTS can also be used by transition advocates/agencies
modernizing the mds process
Modernizing the MDS Process
  • NF personnel vs transition advocates/consumers
    • NF Administrators – occupancy
    • Nursing staff – light care need patients are easier
  • Mandatory referral processes based on CAT will circumvent some of these issues
  • Consumer Involvement
    • Resident/family should be informed about how community CAT triggers are filled out
    • Should be able to talk with ombudsman/advocate if they disagree with assessment.
    • Should be given opportunity to opt into community living training.
targeting strategies
Targeting Strategies
  • Discharge prediction & accrued length of stay
    • Compare predicted vs actual and assign likelihood level
    • Protocol in place to check in with resident/family when approaching predicted discharge
    • Reactive, but easy and could be used with all ages
  • Preference & discharge prediction
    • Pref & pred < 30 – minimal assistance needed
    • Pref & pred 30-90 or uncertain – midlevel assistance
    • Pref & pred > 90 – intensive assistance level.
    • Not recommended for 85+
targeting strategies cont
Targeting Strategies (Cont)
  • Discharge Probability Score
    • Use study results to create discharge probability score
    • Assign individuals to different transition assistance level based on probability score.
    • Ultimately CAT could automatically calculate probability score
tiered transition interventions
Tiered Transition Interventions
  • Minimal Assistance (residents w/ high likelihood of transition)
    • Review predicted discharge estimate with resident/family
    • Let them know transition assistance available if they get off track for discharge.
    • Offered basic information about HCBS and option to participate in community living skills training for resident and/or family
tiered transition cont
Tiered Transition (Cont)
  • Mid-Level Assistance
    • All of the above plus additional community living preference & feasibility assessment
    • Could use CNHTS around day 30 for efficiency
  • Intensive Assistance (residents w/ low likelihood of transition)
    • All of the above plus dedicated transition counselor
thank you

Thank you

Comments? Questions?