1. Predictors of Acute Care Transfers from Inpatient Rehabilitation
Angela Horton, MD, MPH

2. Presentation Outline Background regarding hospital readmissions
Acute care transfers
Study aims and hypothesis
Study design and methods
Statistical analysis and findings
Study limitations
Conclusion

3. 30 Day Hospital Readmission
Patient discharged from acute or post acute care facility and readmitted to the hospital within 30 days
Medicare estimates that avoidable readmissions cost 12 billion dollars annually1
1 in 5 Medicare and Medicaid beneficiaries are readmitted to hospital with 30 days2
The Patient Protection and Affordable Care Act has programs and policies to reduce hospital readmission3
Reduce reimbursement for hospitals with excessive readmission
Creating bundle payments for certain admission diagnoses

4. Post Acute Care (PAC)
In 2011, 43% of Medicare beneficiaries were discharged from acute care to the post acute care setting4
Skilled Nursing Facility/Nursing Home
Long Term Acute Care Facilities
Inpatient Rehabilitation Facilities
Home Health Services

5. Inpatient Rehabilitation
Intensive rehabilitation program
Supervision by rehabilitation physician
Requires medical stability
Requires patient participate in 3 hours of therapy daily for 2 disciplines
Limited access to consult services, radiology and laboratory services

6. Acute Care Transfer
Occurs when a patient admitted to post acute care facility is transferred secondary to changes in medical status which requires higher level of care.
Differs from inpt hospital readmission as pt are actually dc to community and return to hospital verse never leaving hospital setting.
Some excepts are when pts are admitted and

7. Readmissions/ACT in Post Acute Care
Overall readmission rate is 11.8%4
Lower Functional Independence Measure (FIM) scores have higher readmission rate5
In 50% of readmitted patients the diagnosis on readmission is unchanged from the index diagnosis5
Admission diagnoses of CHF, PNA and MI have higher readmission rate6

8. ACT from Inpatient Rehabilitation
Research is emerging regarding ACT and Inpatient Rehabilitation
Currently literature states ACT rate of % 4-5
Recent studies explore potential risk factors for ACT
*Time and date of admission
*Functional Independence Measure Score
Comorbidity Tiers
Demographics
*Poly-pharmacy
*Acute Hospital Length of Stay
Asteriixis indicates risk factors in other studies that have shown increase risk or odds of ACT that are statitiscally significant.

9. ACT and Inpatient Rehabilitation
Motor FIM Score
Length of Stay
Roberts, S. PM&R. Jan 2014
Morandi, A. JAMDA. Oct 2013

10. Study Aims
Aim 1
To determine the incidence of acute care transfers from Vanderbilt Stallworth Rehabilitation Hospital
Aim 2
To determine if the following are risk factors for acute care transfers
Functional Independence Measure
Length of acute care hospital stay
Malnutrition

11. Hypotheses
Patients with lower FIM scores will have a greater odds of ACT.
Longer length of stay at the acute care hospital will be associated with a greater odds of ACT
Patients with malnutrition (using pre-albumin as a surrogate) will be associated with greater odds of ACT.
Clarify, by duration of icu admission, bc some people go to icu

12. Study Design and Setting
Retrospective cohort study
1706 admissions at VSRH in 2010
Vanderbilt Stallworth Rehabilitation Hospital
80 bed inpatient rehabilitation facility
Joint Venture between HealthSouth Corporation and Vanderbilt University Medical Center

13. Inclusion/Exclusion Criteria
Inclusion Criteria
Admitted to VSRH in 2010 from acute care hospital
Exclusion Criteria
Patients < 18 years old
Patient admitted from home, SNF, IRF or ALF to VSRH
Only 1st admission was included
Patients admitted by physician who seldom practice at VSRH (admitted <10 patients)

14. Study Population 1706 Admissions 1519 Patients 1487 Patients 1438
187 excluded: repeat patients
1519
Patients
32 excluded: pediatric patients
1487
Patients
49 excluded: PAC/Home patient admission
1438
Patients
6 excluded: admitted by low yield MD
1432
Patients

15. Outcome Variable Acute care transfers
Binary outcome
Does the patient have an acute care transfers from VSRH ? “yes/no”
Initial transfer of patient from Inpatient Rehabilitation to Acute Care Facility
Thinking about considering time to event analysis

16. Exposure variables Functional Independence Measure Score (FIM Score)
Acute Care Length of Stay
Malnutrition

17. FIM Score Disability Measure used in inpatient rehabilitation
18 indicator scale with 13 motor tasks and 5 cognition tasks
Scored from 1 - 7
Score of 1 indicates complete dependence with a task
Score 7 indicates independence
Lowest score 18 and maximum score of 126
Performed on all patients by trained therapist within 48 hours of admission and discharge to IRF
0 = means activity does not occur.

18. 9

19. FIM Score
Excellent internal consistency (Cronbach's alpha = 0.93 admission; 0.95 discharge as relates to general rehabilitation10
Excellent test-retest reliability (ICC = 0.98 for total FIM, 0.95 and 0.89 for motor FIM and cognitive FIM, respectively)11
Excellent overall consistency (median interrater reliability = 0.95) between raters across patients with different diagnosis and levels of impairment12
Add reference 10
Remember ICC is intraclass correlation

20. Malnutrition Pre-albumin
a serum protein synthesized by the liver with half-life of two days13
Normal value is 18.0 to 45.0 mg/dL
Ordered on day of admission
11. Refernce -- Prealbumin: A Marker for Nutritional Evaluation
FREDERICK K. BECK, M.D., and THOMAS C. ROSENTHAL, M.D., State University of New York at Buffalo, Buffalo, New York
Clin Nutr. 2012 Jun;31(3): doi: /j.clnu Epub 2011 Nov 26.
Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality.
Predicting clinical instability of older patients in post-acute care units: A nationwide cohort study.
Lee WJ, Chou MY, Peng LN, Liang CK, Liu LK, Liu CL, Chen LK, Wu YH; VAIC Study Group
2, Clinical Chem. Prealbumin Serum Concentrations as a Useful Tool in the Assessment of Malnutrition in Hospitalized Patients
Gianluigi Devoto1, 
Fabrizio Gallo2, 
Concetta Marchello1, 
Omar Racchi2,a,
Roberta Garbarini2, 
Stefano Bonassi3, 
Giorgio Albalustri1 and 
Enrico Haupt2
Surrogate Nutrition Markers, Malnutrition, and Adequacy of Nutrition Support
David S. Seres, MD, CNSP
Departments of Medicine and Surgery, Beth Israel Medical 
Am Fam Physician. 2002 Apr 15;65(8):
Malnutrition as assessed by nutritional risk index is associated with worse outcome in patients admitted with acute decompensated heart failure: an ACAP-HF data analysis.
Aziz EF, Javed F, Pratap B, Musat D, Nader A, Pulimi S, Alivar CL, Herzog E, Kukin ML. 9remember slide fromthis study.

21. Covariates Age Gender Race Insurance Marital Status Comorbidity
Medicare Comorbidity Tier
Attending Specialty
Internal Medicine
PMR
Pulm
Rehabilitation Impairment Categories

22. Comorbidity Tier
Developed by CMS for inpatient rehabilitation reimbursement
3 tiers
Tier 1 (B) high reimbursement
Tier 2 (C)
Tier 3 (D)
No Tier (A) low reimbursement
Tier assignments are based on comorbid/coexisting conditions
Explain of tier patient is CVA on mechanical ventilation Tier 1
Tier 3 CVA with controlled HTN
CVA – no risk factors

23. Rehabilitation Impairment Categories (RIC)
Primary diagnosis for rehabilitation
21 RICs
01 Stroke
02 Traumatic brain injury
03 Nontraumatic brain injury
04 Traumatic spinal cord
05 Nontraumatic spinal cord
06 Neurological
07 Fracture of Lower Extremity
08 Replacement of Lower Extremity
09 Other orthopedic
10 Amputation, lower extremity
11 Amputation
12 Osteoarthritis 13 Rheumatoid, other arthritis 14 Cardiac 15 Pulmonary 16 Pain Syndrome 17 Trauma w/o CNS damage 18 Trauma w CNS damage 19 Guillain Barre 20 Miscellaneous 21 Burn

24. Human Subject Consideration
IRB Approval
Exempt from Committee or expedited review
Obtained under the exemption category that covers research involving studying data, documents or diagnostic specimens that have been already been collected
Vulnerable populations were excluded

25. Statistical Analysis Stata for data analysis R version 3.0.2
Descriptive Statistics
Bivariate Analysis
Multivariate Logistic Regression
R version 3.0.2
Multivariate Logistic Regression with Multiple imputation
P value of less than 0.05 is considered statistically significant
Enlisted by colleuges in Biostats to assist with logistic regression with multiple imputation.
Consider using FIM, LOS and Malnutrition as continuous variables then would use t test.
Could do time to event analysis

26. Missing Data Pre-albumin missing 30% of values Multiple Imputation
Method of analyzing data with missing values
Replaces each missing value with a set of plausible predictions multiple time
Imputation Model includes:
Variables potentially related to the imputed variable
Variables potentially related to the missingness of the imputed variable
All covariates were used in model
Missing 420 prealbumin

27. Univariate Analysis and Incidence of ACT
Characteristic
N=1432
Age -- Years
Median
66.8
Mean 64
Interquartile range
Gender
Male
49% (699)
Female
51% (733)
Race
Caucasian
85%(1217)
African American
13% (186)
Other
2% (29)
Insurance
Medicare
64% (915)
Commercial
30% (426)
6% (91)
Marital Status
Married
49% (706)
Incidence of ACT
14.7% (210)
Source: UDS data for Vanderbilt Stallworth Patients discharged from Jan 1, 2010 to December 31, 2010.

28. Bivariate Statistics: Exposure Variables
Non-ACT
N = 1222
ACT
N=210
P Value (<0.05)
Functional Impairment Measure Score
59 (Mean)
61(mean)
0.146
IQR 48 – 69
IQR
Acute Hospital Length of Stay
8 days
10 days
<0.001
IQR 5 – 13 days
IQR 6.25 – days
Malnutrition (Pre-albumin)1* 16
IQR 12 – 23 17
0.97
Mention that Acute Care Length of Stay statistically signficant
Source: UDS data for Vanderbilt Stallworth Patients discharged from Jan 1, 2010 to December 31, 2010.
*Source: Vanderbilt Medical Center Electronic Medical Record
1Missing data for pre-albumin in 420 patients. N for Non-ACT is 802; N for ACT is 210.

29. Bivariate Statistics: Covariates
Non-ACT
N = 1222
ACT
N=210
P Value (<0.05)
Age
66.8
67.3
0.498
Race
- White
85% (1034)
87% (183)
0.416
- Black
13% (161)
12% (25)
- Other
2% (27)
1% (2)
Marital Status
50% (606)
48% (100)
0.681
Insurance
- Medicare
64% (786)
61% (129)
0.275
- Commercial
29% (355)
34% (71)
7% (81)
5% (10)
Rehab Impairment
< 0.001
- RIC 8 (LE replacement)
7% (90)
1% (3)
- RIC 1 (CVA)
12% (152)
15% (31)
- RIC 6 (Neuro Condition)
31% (373)
40% (83)
- RIC 9 (Orthopedic)
10% (126)
5% (10)
- RIC 17 ( Multi Trauma w/o CNS)
10% (125)
11% (23)
- Other RIC
29% (356)
29% (60)
Age, Race, Martial Status and Insurance is very similiar
Source: UDS data for Vanderbilt Stallworth Patients discharged from Jan 1, 2010 to December 31, 2010.
*Source: Vanderbilt Medical Center Electronic Medical Record

30. Bivariate Statistics: Covariates
Non-ACT
N = 1222
ACT
N=210
P Value (<0.05)
Attending
0.006
- Internal Medicine
35% (432)
44% (92)
- PMR
57% (701)
46% (96)
- Pulmonary
7% (89)
10% (22)
Comorbidity Tier
0.192
- Tier A (No comorbidities)
51% (629)
50%(105)
- Tier B (High Reimburse)
9% (108)
13% (28)
- Tier C (Med Reimburse)
10% (118)
8% (16)
- Tier D (Low Reimburse)
30% (367)
29% (61)
Significant with Attending group
Cormorbidity group
Source: UDS data for Vanderbilt Stallworth Patients discharged from Jan 1, 2010 to December 31, 2010.
*Source: Vanderbilt Medical Center Electronic Medical Record

31. ACT Logistic Regression MI: FIM
Variable
Coef SE
Odds Ratio
95% C.I.
P Value (<0.05)
Total FIM
(per 10 units)
0.07
0.05
1.07
(0.98, 1.18)
0.135
Prealbumin
(per 5 units)
-0.08
0.06
0.92
(0.82, 1.03)
0.158
Age (per 10 years)
0.15
1.16
(1.03, 1.31)
0.016
Gender
- Female
0.27
0.16
1.30
(0.95, 1.79)
0.100
Marital Status
- Married
-0.02
0.98
(0.71, 1.35)
0.906
Insurance (Medicare)
- Commercial
0.54
0.22
1.72
(1.12, 2.63)
0.037
- Other
0.14
0.40
1.15
(0.52, 2.52)
1 unit increase in FIM score is not clinically meaningful, however 10 unit increase in FIM is clinically usually. For every 10 units increase in Total FIM score there is a 7% increase in odds of ACT with 95% CI of 0.98 and This was not statistically significant with p value of

32. Acute Care Length of Stay
Acute LOS was non-linear data, thus ANOVA anaylsis was done from the multiple regression and this has been adjusted by the covariates. This a graphically way to represent acute length of stay.
X axis represents LOS in day
Y axis represents to odds of ACT.
As the length of stay increases the odd ratio for ACTincreases and up to about 10 days and then the odd ratio stays about 2.5
The longer the LOS in acute care hospital the increased odds of ACT. This increasebegins to level off around 10 days.

33. ACT Logistic Regression: Prealbumin
Variable
Coef SE
Odds Ratio
95% C.I.
P Value (<0.05)
Total FIM
(per 10 units)
0.07
0.05
1.07
(0.98, 1.18)
0.135
Prealbumin
(per 5 units)
-0.08
0.06
0.92
(0.82, 1.03)
0.158
Age (per 10 years)
0.15
1.16
(1.03, 1.31)
0.016
Gender
- Female
0.27
0.16
1.30
(0.95, 1.79)
0.100
Marital Status
- Married
-0.02
0.98
(0.71, 1.35)
0.906
Insurance (Medicare)
- Commercial
0.54
0.22
1.72
(1.12, 2.63)
0.037
- Other
0.14
0.40
1.15
(0.52, 2.52)
As the prealbumin increases by 5 units the odds of ACT decreases by 8% with a 95% CI of 0.82, 1.03)The p valve of This finding was also not statistically significant. Previous studies looking at prealbumin and mortality and

34. ACT Logistic Regression: Covariates
Variable
Coef SE
Odds Ratio
95% C.I.
P Value (<0.05)
Comorbidity Tier (A)
- Tier B
- Tier C
- Tier D
0.25
-0.29
-0.12
0.27
0.30
0.18
1.28
0.75
0.89
(0.78,2.15)
(0.42, 1.36)
(0.62, 1.27)
0.417
RIC (Replace LE)
- CVA RIC 1
- Neuro RIC 6
- Orthopedic RIC 9
- Multi Trauma RIC 17
- Other RIC
1.75
1.47
0.82
1.59
1.48
0.64
0.68
0.65
0.62
5.77
4.36
2.28
4.91
4.39
(1.66, 20.08)
(1.25, 15.18)
(0.6, 8.66)
(1.38, 17.41)
(1.3, 14.82)
0.040
Age (per 10 years)
0.15
0.06
1.16
(1.03, 1.31)
0.016
Gender
- Female
0.16
1.30
(0.95, 1.79)
0.100
Marital Status
- Married
-0.02
0.98
(0.71, 1.35)
0.906
Insurance (Medicare)
 0.037
- Commercial
0.54
0.22
1.72
(1.12, 2.63)
- Other
0.14
0.40
1.15
(0.52, 2.52)
When using lower extremity replacement as the reference group ( Recent study in Jama last month showed LE with lowest readmission rate (5.8%). There is an 5.77 increased odds of ACT, 4.36 increased odds in Neuro condition groups, Orthopedic 2.28 odds, Multi Trauma Group 4.91 increase odds of Act when compared to LE replacement RIC
Age 10 year increments found to be clinically meaningful. For every 10 year increase in age there is a 16% increase in odds of ACT.

35. Summary of Findings Incidence of ACT was 14.7%
Patients with prolonged acute care hospitalization have increased odds of ACT
Patients with RIC diagnoses of CVA, Neurologic Conditions, Multiple Trauma without CNS damage and Other Orthopedic have increased odds of ACT when compared to lower extremity replacement patients
Older patients have increased odds of ACT.

36. Relationship to other studies
Lower FIM scores associated with increase risk readmission
Differs from our study, however this difference was not statistically significant
In other studies shows an increase incidence in 30 day readmissions and acute care transfers with increase LOS
Our study is consistent with this finding
Malnutrition
Shown to be statistically significant in studies related to hospital readmission
Although not significant, there was a decrease odds in ACT with increase in pre-albumin
FIM score had odd ratio of 16% as increase odds of ACT. Not stasitical significant and 95% CI erossed 1.

37. Why is this research clinically important?
With this background work and future studies, hopefully, ACTs from inpatient rehab will decrease
This will assist the clinician with
Identifying patients at risk
Older patients
RIC categories of CVA, Neurologic Conditions and Other Orthopedic
Prolonged acute care hospitalization
Increasing physician evaluation of these high risk patients
Encourage early sub-specialty or Medicine consultation
Encourage nutrition consultation and management

38. Study Limitations Single center study in urban academic setting
Missing data as relates to pre-albumin
No differentiation between planned and unplanned acute care transfers
Difference between our study results with FIM score and other studies
Analyze initial ACT, and not subsequent ACT
Retrospective
Coding data hard to validate

39. Final Conclusion
Acute care length of stay is a risk factor for ACT from inpatient rehabilitation
Additional research should be done to evaluate malnutrition and ACT
FIM score is likely a good predictor of ACT, however this study did not show a significant difference
Additional research is needed to evaluate other possible risk factor for ACT.

40. Acknowledgements Mentor Committee Vanderbilt Stallworth
Sunil Kripalani, MD, MSc, SFHM Susan Health, CEO of VSRH
Jack F. Schnelle, PhD Eric Woodard, RN
Walter Frontera, MD, PhD LaToya Mercado
MPH Program
William Cooper, MD, MPH
Marie Griffith, MD, MPH
Biostatistician
Jonathan Scott Schildcrout, PhD
Yuwei Zhu, MD, MS
Xan Hue, MPH, MS
Funding
Center for Clinical Quality and Implementation Research
Zan Hue
Uway Joo

41. Bibliography
1.Burton R, Lipson D. Health Policy Brief: Care Transitions,” Health Affairs, September 13, 2012
2.Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med. 2009;360:1418–28.
3. Vincent Mor, Orna Intrator, Zhanlian Feng, and David C. Grabowski. The Revolving Door Of Rehospitalization From Skilled Nursing Facilities. Health Aff January :157-64
4. MedPAC. Medicare Post Acute Care Reforms. Testimony. June 14, 2011.
5. MedPAC. Medicare Payment Advisory Commission’s March 2011 Report to Congress, June 2011 Data Book and December 16, 2011 Commissioners Meeting . Accessed 12/21/2013.
6. Ottenbacher KJ, Karmarkar A, Graham JE, et al. Thirty-Day Hospital Readmission Following Discharge From Postacute Rehabilitation in Fee-for-Service Medicare Patients. JAMA. 2014;311(6):
7. Ouslander JG1, et al. Frequency and diagnoses associated with 7- and 30-day readmission of skilled nursing facility patients to a nonteaching community hospital. J Am Med Dir Assoc Mar;12(3):

42. Bibliography
8. Ouslander , J et al. Potentially avoidable hospitalizations of nursing home residents: frequency, causes, and costs. J Am Geriatr Soc Apr;58(4): Uniform Data System for Medical Rehabilitation. Functional Independent Measure Dodds, T, Martin D, et al. A validation of the functional independence measure and its performance among rehabilitation inpatients. Arch Phys Med Rehabili (5): Hobart J. Lamping D., et al. Evidence based measurement: which disability scale for neurologic rehabilitation. Neurology ; Ottenbacher K, Hsu Y, et al The reliability of the functional indepoendence measure: a quantitative review. Arch Phys Med Rehabil :1226 – Beck FK, Rosenthal, T. Prealbumin: A Marker for Nutritional Evaluation. American Family Physician Apr 15;65(8):
14. FREDERICK K. BECK, M.D., and THOMAS C. ROSENTHAL, M.D., State University of New York at Buffalo, Buffalo, New York.

44. Sample Size and Power Calculation
Sample Size is 1222 patients in Non ACT and 210 ACT group
FIM score
Power for detecting a difference in the means in the ACT vs non-ACT group of 10 is 73%
Acute Care Length of Stay
Power for detecting a difference in the means of 1 day the in the ACT vs non-ACT group is 67%
Pre-albumin
Power for detecting a difference in the means of 5 units in the ACT vs non-ACT group is 98%