Risk Factors for Nonelective Hospital Readmissions David M. Smith, MD, Barry P. Katz, PhD, Gertrude A. Huster, MHS, John F. Fitzgerald, MD, Douglas Ko Martin, MD, Jay A. Freedman, PhD
We p r e v i o u s l y r e p o r t e d a p r e d i c t i v e m o d e l t h a t i d e n t i f i e d po- t e n t i a l i y m o d i f i a b l e r i s k f a c t o r s for n o n e l e c t i v e r e s d m l s s i o n
t o a c o u n t y h o s p i t a l . T h e o b j e c t i v e s o f t h i s s t u d y w e r e to de- t e r m l n e i f t h o s e r i s k f a c t o r s w e r e g e n e r a l i z a b l e t o a d i f f erent p o p u l a t i o n . We f o u n d t h a t t h e p r e v i o u s l y r e p o r t e d r i sk fac- t o r s w e r e g e n e r a l i z a b l e , a n d o t h e r p o t e n t i a l l y m o d i f i a b l e r i sk
f a c t o r s w e r e i d e n t i f i e d in t h i s p o p u l a t i o n o f v e t e r a n s . How-
ever , fur ther r e s e a r c h i s n e e d e d t o e s t a b l i s h w h e t h e r or n o t t h e r i sk f a c t o r s c a n be m o d i f i e d a n d w h e t h e r or n o t m o d i f i c a - t i o n i m p r o v e s o u t c o m e s .
K E Y WORDS: p a t i e n t r e a d m i s s i o n ; p a t i e n t d i scharge ; hosp i - t a l i z a t i o n . J GEN INTERN MED 1 9 9 6 ; 1 1 : 7 6 2 - 7 6 4 .
or older; (5) had access to a telephone; and (6) were ex-
pected to live for more than 3 months.
We excluded 208 pat ients who were discharged be-
fore they could be recruited, 185 who declined to partici-
pate, 7 who enrolled in another study, and 6 women. This
left 662 pat ients (62% of eligible patients) for study, repre-
sent ing 14% of pat ients admit ted to the medical service.
The subsequen t annual readmiss ion rate for the s tudy
populat ion (N = 662) was 24% greater than the overall
mean (N = 4,245), indicating that a high-risk sample was
selected. The demographic character is t ics and subse-
quent annual readmiss ion rates for missed and noncon-
sent ing pat ients were similar to those for the participants.
A mong general medicine inpatients, 17% to 19% ex-
perience nonelective readmiss ions (those for urgent
or emergent reasons) within 90 days of discharge. 1-3 Cer-
ta in identified risk factors for readmiss ion are diagnostic
groups and difficult to modify2,4; other r isk factors are po-
tentially modifiable. 1 Our objective was to determine the
generalizability of the Smi th Index, a model previously de-
veloped and validated at a county hospital, 1,5 to pat ients
discharged from a Veterans Affairs Medical Center. We
also investigated whether other modifiable risk factors
could be identified.
METHODS
Setting and Patients
Data were collected during a trial to reduce nonelec-
tive readmiss ions among patients discharged from the
medical service of a Veterans Affairs Medical Center. 3 Eli-
gible pat ients (N = 1,068) (1) were discharged home be-
tween November 1, 1988, and October 31, 1990; (2) lived
within the pr imary service area; (3} were to receive pri-
mary care in the hospital 's clinics; (4) were aged 45 years
Received from The Richard L. Roudebush Veterans Affairs Medical Center (DMS, DKM, JAF), and the Divisions of General Internal Medicine (DMS, JFF, DKM, JAF) and Biostatistics (BPK, GAH) of the Department of Medicine, Indiana University School of Medicine, and The Regenstrief Institute for Health Care (DMS), Indianapolis.
Supported by Health Services and Research Development II-ISR&D) project IlR 87-137.1 from the Veterans Administration.
Address correspondence and reprint requests to Dr. Smith: Richard L. Roudebush VAMC, HSR&£) (11H), 1481 West Tenth St., Indianpolis, IN 46202.
762
Assessments
Within 3 days of discharge, research nurses obtained
informed consent and administered a quest ionnaire com-
posed of the Duke Older Americans Resources and Ser-
vices (OARS) instrument , including assessment of 24 un-
met medical, nursing, and social support needs with 0 =
no unmet needs6; the Short Portable Mental Sta tus Exam-
ination, 10 items, 10 = no impairmentT; the Interpersonal
Support Evaluation List (ISEL}, 40 items, 40 = perceived
good supportS; interviewer-rated functional s ta tus (5-point
scale, 1 = no impairment, 5 = total impairment}; the Mich-
igan Alcoholism Screening Test (MAST)9; and patient satis-
faction, 4 items on a 5-point scale, maximum satisfaction =
20. Additional information included sociodemographic
data, last laboratory test results, number of medications,
number of emergency depar tment visits in the past 6
months, and whether the current admission was elective
or nonelective. Research nurses had 95% concordance
with obtaining survey data. Health resource utilization
was obtained by interview 12 months after enrollment.
Response Variable
We confirmed elective and nonelective VA and non-
VA hospital admiss ions by having two investigators re-
view the records. Elective admiss ions were those in which
a delay in the intended inpat ient stay presented no imme-
diate r isk to the patient. The two investigators agreed on
the urgency of the admiss ions in 93% of the cases. If they
disagreed, a third investigator decided the urgency.
Statistical Analysis
To assess the performance of the Smith Index, we
computed diser iminant scores from the original five risk
variables: 1 number of emergency depar tment visits in pre-
vious 6 months, blood urea nitrogen (BUN) level, arterial
]GIM Volume 11, December 1996 763
PO2, whi te b lood cell c o u n t (WBC) of a t l ea s t 1 2 , 0 0 0 / m m 3
a n d h e m o g l o b i n less t h a n 12 g /dL . Of these , all b u t n u m -
b e r of e m e r g e n c y d e p a r t m e n t v is i t s in t he p rev ious 6
m o n t h s a re po ten t ia l ly modi f iab le pr ior to d i scharge . Y =
1.517 + 0 .444XI + 0.038X2 + 1.018X3 + 1.131X4 +
0.827X~. Here X~ = n u m b e r of e m e r g e n c y d e p a r t m e n t vis-
i ts in t he p r ev ious 6 m o n t h s ; X2 = BUN (or m e a n of 16.45
ff miss ing) ; Xa = 1 ff a r te r ia l P O 2 < 88 Inln Hg, = 0 o ther -
wise; X4 = 1 i f W B C >- 1 2 , 0 0 0 / r a m 3, = 0 o therwise ; X s =
1 ff h e m o g l o b i n < 12 g / d l (for males) , 0 ff o therwise . Pa-
t i en t s w i t h d i s c r i m i n a n t s co re s above 0 .2040 were pre-
d ic ted to be r eadmi t t ed .
We ident i f ied n e w r i sk fac tors u s i n g logistic regres -
sion. Initially, b ivar ia te c o m p a r i s o n s of va r i ab les f rom pa-
t i en t s no t r e a d m i t t e d to t hose r e a d m i t t e d were done by
S t u d e n t ' s t t e s t s or ×2 ana lyses . Var iab les were r e t a ined ff
s igni f icant a t p < .20. S tepwise , forward a n d b a c k w a r d lo-
gist ic r eg re s s ion was done. Pe r fo rmance w a s a s s e s s e d by
eva lua t ing t h e a r e a u n d e r t he r ece ive r -ope ra t ing cu rve
(ROC). B o o t s t r a p p i n g (10) was u s e d to s i m u l a t e t he per-
f o r m a n c e in a n e w p o p u l a t i o n a n d ca l cu la t e a n a d j u s t e d
a r e a u n d e r t he ROC.
RESULTS
Baseline Characteristics
C o m p a r e d wi th t he or iginal s a m p l e ) t he c u r r e n t
s a m p l e of v e t e r a n s h a d a s l ight ly h i g h e r none lec t ive read-
m i s s i o n ra te a t 90 days (20.1% vs 16.9%). The c u r r e n t
s a m p l e was older (65 vs 54 years) , m o r e l ikely to be m a l e
(100% vs 64%), a n d less l ikely to be Af r i can -Amer ican
(17% vs 59%). These cha rac t e r i s t i c s e s t ab l i shed t h a t o u r
c u r r e n t p o p u l a t i o n was dif ferent f rom the or iginal s a m p l e
a n d they were exposed to a di f ferent h e a l t h ca re sys tem.
Performance of the Smith Index in a Different Population
In t he p rev ious s t u d y ) t he sens i t iv i ty of t he m o d e l
w a s 55%, specif ici ty was 68%, a n d the posi t ive predic t ive
va lue (PPV) w a s 28%. In t he c u r r e n t s tudy , u s i n g the
s a m e r i sk fac tors a n d d i s c r i m i n a n t score, t he sens i t iv i ty
w a s 75%, the specif ici ty 50%, a n d the PPV 27.5%. Thus ,
t he va r i ab les in S m i t h Index pe r fo rmed very s imi lar ly in
th i s ve ry different popu la t ion , ind ica t ing t h a t t he r i sk fac-
tors m a y be appl icab le to th is d i f ferent popu la t ion . We
u s e d t h e s e s a m e va r i ab les in a logist ic r eg re s s ion model ,
a n d the a r e a u n d e r t he ROC w a s 0 .660.
Attempts to Improve the Model by Using Additional Variables
A tota l of 33 va r i ab le s were cons ide r ed for model ing ,
and 22 were e l iminated th rough bivariate compar i sons (p >
.2) or h a d s igni f icant m i s s i n g var iab les . The va r i ab le s
e l imina ted inc luded race, mar i t a l s ta tus , employment , ser-
v ice -connec ted disabil i ty, h e a l t h i n s u r a n c e , h e m o g l o b i n
be low 12 g /dL , WBC less t h a n 1 2 , 0 0 0 / m m 3, s e r u m crea t -
inine, a r te r ia l 02 less t h a n 80 m m Hg, s e r u m a lbumin ,
n u m b e r of medica t ions , d iagnoses of d iabe tes mel l i tus and
h e a r t d isease , base l ine a d m i s s i o n (elective vs nonelect ive) ,
phys ica l hea l t h ra t ing scale, act ivi t ies of daffy living, MAST
score, and pa t ien t satisfaction. The var iables inc luded in de-
veloping the mode l a re s h o w n in Table 1. The fmal m o d e l
{Table 2) u s e d 640 pa t i en t s or 97% of t hose enrol led. Of
t he s ix var iab les , two were in t he S m i t h Index: BUN a n d
WBC >- 1 2 , 0 0 0 / r a m 3. Also, of t he six var iab les , all b u t di-
agnos i s of h y p e r t e n s i o n a re po ten t ia l ly modi f iab le by ac-
t ions. After boo t s t r app ing , t he a r e a u n d e r t he ROC w a s
0 .690 wi th a 95% conf idence in te rva l of 0 .634 to 0 .746.
DISCUSSION
The r e su l t s d e m o n s t r a t e t h a t the S m i t h Index I h a d
s imi la r a c c u r a c y of p red ic t ion w h e n appl ied to pa t i en t s
wi th m a r k e d l y dif ferent d e m o g r a p h i c s a n d ca r ed for in a
di f ferent h e a l t h ca re sys tem. Val ida t ion of a mode l for
none lec t ive r e a d m i s s i o n s in a di f ferent p o p u l a t i o n a n d
h e a l t h ca re s y s t e m h a s no t p rev ious ly b e e n repor ted .
F o u r of t he va r i ab les (risk factors), e leva ted BUN, hypox-
emia , l eukocytos i s , a n d anemia , cou ld serve as indica-
t ions for i n t ense i n p a t i e n t e v a l u a t i o n s for poss ib le revers -
ible cond i t ions d u r i n g hospi ta l iza t ion .
Wai te a n d coworke r s u s e d the S m i t h Index to p red ic t
all r e a d m i s s i o n s (elective a n d nonelect ive) 6 m o n t h s af ter
Table I . Variables Used in Developing a New Predictive Model
Not Readmitted Readmitted
(n = 529) (n = 133)
Mean Mean p Characteristic or % SD or % SD Value
Age, years 64.3 7.7 65.4 7.7 .175 Systolic blood
pressure <- 115 m m Hg, % 26.0 34.1 .062
WBC -> 12 ,000/ ram s, % 10.2 18.3 .010
BUN, m g / d L 19.1 9.2 22.7 11.8 .002 Emergency dept.
visits in prior 6 mo 1.6 2.1 2.0 1.5 .032
Diagnosis of chronic obstructive pulmonary disease 32.3 43.6 .014 hypertension 60.3 75.2 .001
Interviewer-rated functional s ta tus 3.7 0.7 4.1 0.7 < .001
Mental s ta tus 9.1 1.2 8.8 1.7 .094 Interpersonal Suppor t
Evaluat ion List 31.9 6.7 30.4 6.8 .021 Service Assessment
Scale, unme t needs 0.18 0.49 0.43 0.99 .006
764 S m i t h e t al., Pat ient R e a d m i s s i o n s JGIM
Table 2. Predictive Model for Nonelective Readmissions at 90 Days
95% Standard Odds Confidence
Variable ~ Error Ratio Interval
WBC - 1 2 , 0 0 0 / m m 3 0 .822 0 ,294 2 .28 1.28, 4 .05
D i a g n o s i s of
h y p e r t e n s i o n 0 .696 0 .243 2.01 1.25, 3 .22
In t e rv iewer - ra t ed func t iona l s t a t u s
(1 ca tegory change) 0 .545 0 .158 1.73 1.27, 1.36
Systol ic b lood p r e s s u r e ---
i 15 m m Hg 0.511 0 .226 1.67 1.07, 2 .60
Service A s s e s s m e n t Scale, u n m e t n e e d s
(1 need change) 0 .507 0,171 1.66 1.19, 2 .32
BUN, m g / d L change) 0 .024 0 .010 1.27 1.04, 1.55
d i s c h a r g e a n d f o u n d n o r e l a t i o n o f t h e S m i t h I n d e x to re -
a d m i s s i o n s , t l B e c a u s e e lect ive r e a d m i s s i o n s a r e m o r e fre-
q u e n t fo r h e a l t h i e r p a t i e n t s , w e w o u l d e x p e c t n o r e l a t i o n
b e t w e e n e lec t ive h o s p i t a l i z a t i o n s a n d r i s k f a c t o r s for b u r -
d e n of d i s e a s e , x2 Also , r i s k f a c t o r s for r e a d m i s s i o n v a r y
w i t h t h e l e n g t h o f f o l l ow-up . ~3 T h u s , r i s k f a c t o r s for r e a d -
m i s s i o n s a t 9 0 d a y s m a y n o t b e g e n e r a l i z a b l e to 6 m o n t h s .
T h e S m i t h I n d e x a n d t h e n e w m o d e l (Table 2) i den t i -
f ied v a r i a b l e s t h a t a r e p o t e n t i a l l y m o d i f i a b l e a n d m a y b e
ob jec t ive m e a s u r e s of d e c r e a s e d r e a d i n e s s for d i s c h a r g e .
T h e s e r i s k f a c t o r s m a y h a v e u t i l i ty in t h i s e r a o f c a s e
m a n a g e m e n t . H o w e v e r , f u r t h e r r e s e a r c h i s n e e d e d to e s -
t a b l i s h w h e t h e r o r n o t t h e r i s k f a c t o r s c a n b e m o d i f i e d
a n d w h e t h e r o r n o t m o d i f i c a t i o n i m p r o v e s o u t c o m e s .
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The authors thank Terry Adams, RN, Nancy Armstrong, RN, Bev- erly Musick, and Gayle Redmon for technical assistance and Morris Weinberger, PhD, and Lorrie A. Mamlin, MPH, for com- ments on drafts of this manuscript.