HOSPITAL READMISSIONS

J.ItVICES.
D,J 
'0 
lt""ia 
OFFICE OF INSPECTOR GENERAL 
AN 
OFFICE OF ANALYSIS  INSPECTIONS 
DECEMBER 1989  HOSPITAL READMISSIONS

RICHARD P. KUSSEROW 
INSPECTOR GENERAL 
OAI.12-88-01220  DECEMBER 1989
 Contr Inormtin 
Contrr  Prjec 
BOTEC Analysis Corpration  David Hsia, J.  , M.  , M. 
JF 
36  Street  Health Care Branch

Cambridge, MA 02138  Offce of Inpetor General 
330 Independence Ave., SW 
Contr 
Washigton, D.C. 20201

HHS-100-88-0019  EX 
SUMY

BACKGROUN 
Th inpection examies the caus and frequencies of multiple readmiions of Medicare 
beneficiaries, and the implication thi has on the management of the prospetive payment 
system. The readmiion of a patient may indicate premature dicharge, scheduled re
hospitaliation, natural recurrence of the diseas, or may have no relationship to the origial 
cause of hospitalition. The per revew organitions (PROs) monitor hospital 
readmiions to identif premature disharges. 
FIINGS 
ocr beus 
Over one-hal of readmions  of the natural recurrence of the disease 
(medicaly related readmiions). Approxiately, one-third of readmiions do not 
admiion (unrelated readmiions). 
medically relate to the intial  Nearly one-sixh of 
readmiions are planned at the time of the prevous discharge (planned 
readmisions). A prevous premature disharge causes only 1.0 percent of 
readmisions. 
PRO scrutiny of readmisions identifes no more clical incidents than random 
cas 
selection of  for revew. The Health Care Financing Admtration (HCFA) 
estimates that readmiion revew annually cot $45-55 miion. 
Readmisions do not signcantly difer from other hospitalitions in the rate of 
unnecary admiions, por quality care, or premature disharge. 
Hemoglobinopathies have signifcatly higher rates of readmision, both necsary and 
unnecary. The latter compri 46.7 percent of hemoglobinopathy bils and cost 
$47.2 millon annualy. 
RECOMMNDATIONS 
The HCFA should re-ealuate the effectivenes of PRO surveilance of readmissions 
versus surveilance of random admisions. 
The HCFA should study the effectivenes of PRO utiliztion review of 
hemoglobinopathies. 
The HCFA should determine whether primary and sendary prevention of acute 
exacerbations of hemoglobinopathies would consume les Medicare resource than 
repeated hospitaliztions. 
beuse 
The HCF A did not concur with these recmmendations  they would require statutory 
propo 
change. We continue to believe that HCFA should  legilative changes and take 
admitrative actions in order to implement our recmmendations.  ...................................................................................................................  ............................................................................ ..................................   .................................. ....
. . . ..  ...   ... . . ..  ..  ....    ....    ....    ...   ....    ....    ....    ....    ....    ....    ....    ....   ...   ...   ....    .....    .....    .....    ......    .....    ....     .....    ......     ......     ......      ......     ......     ........      .......      ........   .   .......      .......        ........       ......... .      ........     ....   ...   ...   ... .
CONT 
SUMY. 
EXECUT 
..00........... 
CONTNT  II.. ... ... 00....0.... D......  0.0...0 eo. 
INODUCTON. .  ....000 ..00..00... 
.0000..

Background. . . . . . . 
....0....0.

Methodology. . . 
FIINGS 
..............0

Sample 
Beneficiaries  . II IIII II . 
Disharges 
Hospital characteritics 
Readmiions. . . . . . . 
Reasons for readmiion 
.........8041 
Transferee hospitals 
Number of transferee hospitals 
Diseas causing multiple admiions  ......41... 
Clical review. 

.41.......  e.......  e......

RECOMMNDATIONS  0 0" De 00 
Appendix A-l: Medicare dicharges in FY 1985 .. . 
......e.. ........................... 0........

Appendix A-2: Samplig frame 
18........  o...e.........

Appendix A-3: Sample design  ........... D..".. 
01 
.........41.........11.......... 

Appendix A-4: Beneficiary demography. . . . . . 
Appendix B-1: Discharges by patient demography. ........e.e......... .......

Appendix B-2: Disharges by hospital demography 
Appendix C-l: Readmisions by patient demography. 
Appendix C-2: Readmiions by hospital demography 
Appendix C-3: Interval between rehospitaltions 
Appendix D-l: Reasons for readmision 
..............0..

Appendix D-2: Reasons for readmision by patient demography  . . . ..  ..  ...   ...   ...   ...   ....    ....    ....    ....    ......      ......      .......       ........        ........        ........        ........        .........         ..........          ..........          ..........          ..........
. . . . . . . ..  ...   ...   ...   ...   ...   ...   ...   ....    ....    .....     .......       .......       ........        ........        ........        ........        ........        ........        ........        ........        ........        ........        ........        ........        ........        ........        ........        .......       .......       .......       .......       .......       .......       .......       ......      .....     .....     .....     .....
Appendix D-3: Reasons for readmiion by hospital demography 
l: Readmiions to diferent hospitals by patient demography 
Appendix E-
Appendix E-2: Readmions to dierent hospitals by hospital demography 
Appendix  B-3:  Distance to diferent hospital 
Appendix F-l: Number of diferent hospitals viited in frequency order by patient 
demography 
Appendix F-2: Frequency order by be siz . 
Appendix F-3: Frequency order by hospital demography 
Appendix G-l: Diseases causing multiple disharges 
Appendix G-2: Major diagnostic categories causing multiple discharges 
Appendix G-3: Diseas by readmiion reasn. . . . . . . . . 
Appendi G-4: Diseases by number of disharges 
Appendi H-l: Clical revew 
Appendi H-2: Clical review comparin. . . 
Appendix H-3: Diseases by clical revew 
Appendix 1-1: HCFA comments  ., 

INODUCfON

Backgund 
us 
health servce 
Medical research has long establihed that diferent subst populations 
unequaly.1 For example, Health Cae Financing Admitration (HCFA) fies of short-stay 
mion 
hospital bil show that 83.9 percent of its 31.1  beneficiaries did not enter a hospital 
at all durig calendar year (CY 1985. Medicae therefore spent $44.5 bilon on 
hospitalitions that benefit only the remaig one-sixh of beneficiaries. Adding Medicare 
Part B costs to the hospitaltion exnditures implies that thi inpatient subpopulation 
consumed approxiately three-fourths of Medicare s $70.5 bilon annual budget. (Figure 1). 
Not hospitalized 
Hospitalized 
iciaries 
Benef  Expendi tures 
utiltion 
Figure 1: Medicare servce 
The 17.1 percent of beneficiaries admtted one or more times durig the year is considered 
the "hospitalition percentage."2 Thes 5.3 mion inpatients accrue a total of 8.3 milion 
disharges, a "hospitalition rate" of 26.6 percent (or an average of 1.57 discharges per 
inpatient). 
The hospitalitions do not distribute equally among the inpatient subpopulation. 
relatively small fraction of inpatients constitute a disproportionate share of discharges. 
Three-quarters of the inpatient subpopulation (or 11.4 percent of the beneficiary population) 
enter a hospital only once durig the year. The 1.1 percent of inpatients with six or more 
annual discharges accunt for 5.1 percent of all hospitaliations, the 12.4 
percent of 
inpatients with three or more discharges comprie 30.4 percent of hospitaliations, and the 
33.2 percent of inpatients with two or more disharges make up 57.1 percent of 
hospitalizations. (Figure 2). 
Hollowy JJ, Thoma JW, & Shapiro 1. ainical and soo-emogphic rik factors for redmiion of Medicare beneficiaries. 
Health Care Financing Revew, Fall 1988; 10: 27-36. 
2 Haley RW, Culber DH, Whte JW, Morgn WM, & Emori TO. Nationwide nOlmia infection rate. Am J Epidemiol, Feb. 
1985; 121 (2): 159-67 at 162.
 iciaries  Discharges 
Benef 
Figure 2: Anual diharges 
per patient 
Th inpection studies the epidemiology of "readmiions." It defies a readmiion as a 
single inpatient enterig a hospital more than once in a single year. Readmiions occur for 
four pricipal reasons. 
precing 
Prevous premature disharge: Medical intabilty at the time of the 
readmiion (e.g., inappropriate discharge of a 
discharge caused the  stil septic 
los). 
inpatient to lit the hospital's fiancial 
Planned readmiion: The standard treatment entails discharge of the inpatient and 
later readmion for further therapy (e.g., repeated cycles of chemotherapy for 
lymphatic cancer). 
Medically related readmiion: The natural hitory of the diseas involves multiple 
hospitaliztions despite proper treatment and stabilty at prevous discharge (e. 
recurence of sickle criis or of acute exacerbation of chronic obst  ctive pulmonary 
disease). 
Th 
Unrelated readmision: The admiions ocur at random.  inpatient just 
happened to "hit" twce in a particular year (e.g., hospitaliztion for pneumonia 
followed by admiion for an unrelated hip fracture). 
These categories vary in their implications for Medicare costs and their amenabilty 
external control. 
Pr 
pr disc1uuge. Under the prospetive payment system (PPS) the hospital 
receives a pre-etablihed payment for each disharge, bas upon its diagnosis related group 
(DRG). Because the hospital gain when the inpatient consumes les than the expcted 
amount of resource, it has a fiancial incentive to disharge the inpatient as son 
feasible. Disharge may ocur before medically indicated or the patient attains a stable 
condition. , A premature discharge may als caus a subsequent readmiion with another 
hospitalition payment. A prevous Offce of Inpetor General (OIG) inspetion (OAI-05
88-00740) establihes the general rate of premature disharge to be about 0.8 percent among  00 
all Medicare hospitalitions. However, thes 50  premature disharges annually cost 
Medicare $150 millon. 
The HCFA relies pricipally upon the  to detect premature 
per revew organitions (PROs) 
discharges. Among other thigs, the intial PRO "scpe of work" required them to review all 
ocrrg 
related re-admisions" to PPS hospitals  withi 7 days of disharge from that  same 
hospital for possible premature discharge. Subsuent scpe of work exended 7 day 
readmision period for PRO revew to 15 days and then to 31 days followig the initial 
discharge. 
Intially each PRO decided for itslf what made readmisions "related" Some PROs only 
send 
revewed readmiions biled as the same DRG. Other PROs related  stays from the 
same major diagnostic category (MC), clusters of DRGs pertainng to a single organ system. 
Stil other PROs compared disas coes using the International Qasifcation of Disease -
Ninth Revion (ICD-9-CM. Th flexbilty contributed to the high inter-PRO variation in 
rates of readmiion revew and rates of readmision due to a precing premature discharge. 
Accrdingly, ' the third PRO "scpe of work"  readmissions 
added a revew of 25 percent of  al 
within 31 days for premature discharge, regardles of whether the PRO deemed them related. 
For all related readmiions, the HCFA directed the PROs to review the hospital recrds for 
asing 
both the initial and subseuent stays in  premature dicharge. 
The PROs als lit their inquires to readmiions to the same hospital. A readmission 
withi the designated time fra  , but to a diferent intitution, doe not fall under the 
PROs' scpe of work for premature disharge surveilance. 
Pl 
A readmision may ocur beaus at the time of the initial discharge 
re  fit 
the attending physician plans to readmit the patient. For example, the  hospitalization 
may identif the nee for an eventual coronary arery bypas, but medical considerations 
procing 
dictate outpatient cardiac rehabiltation before  with the operation. At the time of 
wi 
the first disharge, the attending physician notes that the patient  return for surgery in a 
few weeks. The two stays have a relationship, but not beaus of inadequate care during the 
initial hospitalition. 
The prospetive payment sytem permts such "split admiions" where medically indicated 
even though some simlarly situated inpatients recive all pertin nt servce durig the course 
profesional judgment to 
of a single stay. Theoretically, the attending physician exercises 
maxally  The additional DRG payment to the hospital could playa 
benefit the patient 
role in the selection of a split admision, but no objective method exits for identifyng such 
ocurrence. 
Other planned readmisions involve little physician disretion. Certain cancer protocls call 
for multiple cycles of chemotherapy or radiotherapy at scientifcally set intervals. Thus, the 
, intial admision for diagnosis and workup,
tyical diseas pattern entail an extensive
followed by numerous, brief readmiions for treatment over a prolonged period. The need 
for multiple readmisions exts from the' time of the intial diagnosis.  Di 
rela 
Other readmiions derie from the natural hitory of the 
re 
patient' s underlyig disas. Some conditions, lie chronic obstructive pulmonary disease or 
sickle criis, tend normaly to recur. Their chronic nature means that the physician cannot 
predict when the acute exacerbations wil ocur, but knows for certai that they will require 
readmiion in the near future. 
Unfortunately, health servce resarch has develope relatively little data about the pattern 
dias. 
of servce required by paricular chronic  Th inpetion quantifes the diseases 
that most commonly caus multiple admiions. Inurers that elect to pay for succful 
disas 
preventive measures for  causing frequent readmiions could accrue considerable 
savigs. 
Unr 
re  Finaly, multiple hospitaltions may bear no relationship to each 
other. The unlucky patient may suffer a series of indepecndaen t incidents, each requiring 
admiion. The beneficiary recives proper cae in each  and presumably return to 
baselie health status. Utiltion revew can exert relatively little control over unrelated 
readmiions. 
Number 
Benef iciaries

200 
Discharges 
100 
11 12 
13 14+ 
Figure 3: Sample' by annual disharges per inpatient 
Methodlogy 
The OIG cumulates quarterly a 0.2 percent sample of all PPS bil for short-term care. For 
CY 1985, it includes 19,84 disharges for 12 744 inpatients. To study readmiions, the 
samplig frame excludes 8 518 inpatients admitted only once durig the year. From the 
remaing 4 226 beneficiaries having multiple admiions, the design employed simple random 
without replacement. The OIG requested medical records 
sampling to selected 261  in 
for all discharges for each sampled inpatient. With follow-up, it ultimately obtained 847 or 
97.5 percent of the 869 medical recrds.  The Offce of Inpetor General contracted with the Health Data Intitute of Lexigton, MA 
for physician review of the medcal recrds. Among other criteria, the revewers used 
judgmental technques to identif premature diharges and planned readmiions. 
proc 
methodology parallels the  and standards employed in local per revew and by the 
PROs. The revewers had board certifcation, per revew exrience, and current clinical 
care responsibilties. Exrt consultation was avaiable for spealty care isues, and physician 
scrutin  proc 
panels for difcult cas. An OIG medical offcer  the overall review  for 
consistency and bias; and clasifed the remaing disharges as being either disease related or 
unrelated The OIG contracted with BOTEC Analysis of Cabridge, MA to analyz the 
resultant data and prepare thi report 
FIINGS 
Saple 
The sample closely miors the sampling frame in its distribution by number of annual 
disharges per beneficiar (Chi-square 766.5, 13 df, po:O.OO1). Most beneficiaries have three 
discharges or les, but a few beneficiaries have a large number of incidents and one person 
had 21 hospitalitions. The 7.0 percent of inpatients who exrience six or more 
disharges compri 21.0 percent of the disharges. Depite being lited to inpatients with 
multiple discharges, the sample could obtain onl one medical recrd for a few inpatients. 
(Appendix A-3). (Figue 3). 
Table I: Beneficiary demography 
Beneficiaries  Disharges  95% confdence interval 
Age (years) 74.  75.  Varance not available 
Se (% male)  40.4  46.  -0.027 to -0. 
Length of stay  Not applicable 
Cas mi index  1101  Not applicable 
Mortality (%)  6.4  -0.016 to -0.005 
Beneficies 
, the last year for which the HCFA publihed comprehensive data, Medicare enrollees 
In 1982
averaged 1.4 years younger than Medicare inpatient disharges. Lack of publihed variances 
precludes calculation of a confidence interva  but the large siz of the population 
undoubtedly makes this diference signficant. Older beneficiaries therefore enter the 
hospital at a higher rate than younger beneficiaries confrmg that older persons consume 
more health care servce. Empircally, health status deteriorates with advancing age, 
requirng more frequent hospitalition. Conversly, advers selection should ocur as the  disas 
more frail elderly succumb to their  leavig a cohort of older, but healthier, survvors. 
(Appendix A-4). (Table I). 
The 26.1 milion Medicare beneficiaries included 10.5 millon males (40.4 percent), a 
2 percent males among disharges (95% CI - 027 
signcantly lower proportion than the 46.
026).3 The inpatient population including more males than the beneficiary population 
to -0.
contradicts the traditional fidig that females consume health servce at a higher rate than 
males (despite havig superior health status). However, males in the general population 
have a lower proportion of inurance coverage than females, so male beneficiaries' higher 
rate of hospitalition may only reflect their improved inurance coverage upon acquiring 
Medcare eligibilty. 
Beneficiares do not have average lengths of stay or reimbursment in the same sense as do 
inpatients. Dividig total hospita days or cots by the number of beneficiaries, intead of 
inpatients, necarily decreas the averages. Unsurpriingly, the general population, aged 
65 and older, has a signcantly lower mortality rate (95% CI -0.016 to -0.005) than the 
(sicker) subpopulation of Medicare inpatients. 
Table IT: Disharge demography 
Admiions  Readmiions  95% confdence interval 
Age (year)  73.  71.  1.8 to 3.4 
Sex (% male)  46.  48.4  -0.06 to 0. 
Length of stay  1.3 to -0. 
Cas mix index  1.1101  1.180  -0.3 to 0. 
Mortality (%)  6.4  6.4  -0.02 to 0. 
7050  847 
Diarges 
compri a 
The National DRG Validation Study  represntative sample of all PPS discharges 
in 1985, the same sampling frame as thi sample of readmiions. The inpatients in this 
sample averaged a signifcant 2.6 years older than this inpetion s sample of inpatients with 
Th 
multiple discharges (95% CI 1.8 to 3.4).  fiding suggests that younger inpatients re
enter the hospital more frequently than older inpatients. While older beneficiaries generally 
have wors health, among the subpopulation of the sick, younger inpatients consume more 
servce. 
(Appendix B-1). (Table ll. 
3 US Depament of Health and Hum Sece Heath Ca F"mancig Admiistrtion, Offce of Resrch and Demonstrations. 
Heath Ca F"macig Prom Statistics - Medca and Medcad Data Bok, 198. Batiore, MD: US Goerment Printing Offce, 
Septembe 1987 (HCFA Pub. No. 03247). P. 43. 
198 
4 U.S. Department of Commerc Buru of the Census Statistica Abtrct of the United States  Washington, DC: U. 
Governent Priting Offce l08th Ed., 1987. Table 140.  Admiions do not difer signcantly from readmions in the proportion of males, case mix 
index or mortality rate. The former simarty in the distn"bution of admiions and 
readmiions suggests that male and female inpatients have simar health status, unlike the 
population of enrollee. Alternately, thi non-signcance may reflect the smaller siz of the 
samples. The single disharge sample als has a signcantly shorter average length of stay 
3). Th 
than the readmiion sample (95% CI -1.3 to -0. fiding probably reflects 
beneficiaries with multiple anual disharges being sicker than other Medicare inpatients 
despite their relative youth. 
charriti 
Hospita 
siz 
Readmiions ocur to smal (95% CI OJ)08 to 0.063) and medium  hospitals (95% CI 
030 to 0.09) in signcatly higher proportions than to large hospitals. The former 
disas, 
presumably serve a population havig routine chronic  whereas large hospitals attract 
more acute inpatients on a one time basis that better conform to the short term model of 
diseas. Urban-rual location has no effect, whereas nonteaching (95% CI 0.112 to 0.177) 
and for-profit hospitals (95% CI 0.313 to 0.361) have disproportionate shares of the 
readmiion sample. Unsurriingly, the readmiions sample als includes signcantly higher 
proportions of tranfers from other hospitals and admions for therapy. (Appendix B-2). 
Large hospitals recive a signcantly higher proportion of true readmiions (95% CI 
to - 14). Loation, teachig status, and profit control do not exercis an effect. The true 
readmiions subsample largely accunts for the overall higher proportions of tranfers from 
other hospitals and admiions for therapy. (Appendix C-2). 
Table il: Intial admiion demography

Intial  Subsequent  95% confidence 
admiion  readmiions  interval 
Age (years) 72.  70.  7 to 4. 
Se (% male)  47.  48.  -0. 1 to 0. 
Length of stay 
1.8 to 0.4 
Cas mix index  1.1333  2018  03 to 0. 
Mortality (%)  -0. 13 to -0. 
259  588 
Readmiuions 
The sample of beneficiaries admitted to the hospital was divided into two part. The first 
send 
one consisted of those inpatients admitted only once durig the year, whie the 
send 
consisted of those with multiple readmiions. The  group averaged 2.5 years younger 
than the first, indicating that multiple readmiions ocur more often among younger 
Il. 
inpatients. (Appendix C-l). (Table  ' , '
' /  ()
,.-------,\/"" (.'.. - .-.. ./.-. .-..-. ............ ... . ,/.. ........... ........ ('j  . .
100 
Age (years) 
- Percent male

J' ,  -e 
LOS X 10 days 
C:tI X 10 
1\..  (7 
A .  :tortali ty (percent)
J' 
)(------7(------7( 
t-
\.,1 '  "1o
Figure 4: Readmiions sequence 
The subsamples of intial admiions and true readmiions do not difer in sex distribution or 
length of stay. Although males enter the hospital at a higher rate than the beneficiary 
intial stay they re-enter at comparable rates and remai for comparable
population, afer the 
term. By defition, the intial admiion subsample has no mortality. The samplig frame 
havig multiple admiions' and who therefore all survived 
consists exclusively of inpatients 
their intial hospital stays.

Days 
1. 0 
1.1  1. 2  13+ 
Admissions  sequence 
Figure 5: Days outside the hospital 
by sequence of admiion, average age declines steadily with 
Orderig the readmiion sample  confg 
increasing progresion of readmiions  the prevous hypthesis that among 
inpatients, younger beneficiares have worse health. However, length of stay and case-mix 
index decreas with admiion seuence, suggesting their maladies to be les serious than 
size 
average or to be follow-up treatment of the establihed disease. The small subsample 
lits 
conclusions about gender distribution or mortality. (Figure 4).  The sequence of readmiions als permts calculation of the average interval between 
bemes 
readmiions. The time outside the hospital  shorter and shorter as the chronically 
Th 
il beneficiary re-enters intitutions with increasing frequency.  trend may reflect either 
the porer  merely that the individual spending little 
physiological condition of the invalid or 
time at home has more opportunities for hospitalition. (Appendix C-3). (Figure 5). 
re.admiuion
Reans for 
beus 
readmions ocur  , with 
This study fids that most  of the natural history of diseases
54.7 percent of the sample being medically related readmiions. Nex most commonly, 32. 
precg iles. 
percent of readmiions do not relate to the  Only 11.0 percent of 
beus 
readmisions ocur  a prevous hospitalition triggers a standard pattern of 
readmiions for follow-up cae, signcantly les than the 15.7 percent planned procures 
identifed by the National DRG Validation Study (95% CI - 072 to -0.001). The 1.0 
precng  doe not differ 
percent of readmiions due to an imediately  premature dicharge 
signcantly from the 0.8 percent for all admiions (95% CI -0.005 to 0.010). Conversely, 75 
premature result in a subsequent readmiion 
percent of the eight disharges identifed as 
and all withi 15 days. (Appendix D-l). (Figure 6). 
II 
Prema ture discha rge 
Planned 
Rela ted

Unrela ted 
Figure 6: Reasons for readmiion 
Th 
distribution suggests that third part payors exercis relatively little influence over the 
frequency and timg of readmiions. The majority wil ocur beuse of the inpatient' 
health status and standardiz medical responses, rather than beaus of disretionary action. 
Random surveilance for premature disharges will identif true positives in only 1.0 percent 
of revew. 
Reason for readmiion subsamples do not dier in gender distribution, length of stay, or 
mortality. Readmiions following a prevous premature disharge and unrelated readmissions 
have signifcantly higher average ages, both fidings probably reflecting the more frail health 
planned readmisions have significantly higher 
status of very elderly inpatients. In addition,  average case mi index whie medically related readmiions have signcantly lower case mix 
index A  readmiions for high intensity, cardiac servce accunts for the 
high proportion of 
caus 
former trend, whie cancer follow-up  the latter. (Appendix D-2). 
The low frequency of readmions sendary to a precing premature disharge largely 
precludes hospital demographic trends. Unsurriingly, such readmiions all ocur withi 15 
days of the intial disharge, signcantly soner than average (95% CI 0.1 to 0.8). Large 
hospitals (95% CI 0.1 to 0.3) and urban hospita (95% CI 0.1 to 0.2) have a 
planed readmiions, no doubt due to the diversity of therapeutic 
disproportionate share of 
servce  , urban medical centers. By defition, planned readmiions come 
available at large
for planned procures, largely on an elective basis, and maiy via admiion orders from the 
nee 
attendig physician. Simarly, therapy  caus signcatly more medically related 
readmiions (95% CI 0.1 to 0.1), whie unrelated readmiions nee more diagnostic workups 
(95% CI 0.1 to 0.2). (Appendix D-3). 
Number of discharges

.:10  10- 50- 100-1000  1000+ 
Distance (miles) 
Figure 7: Distance to diferent hospital

Trafere hopita

Theoretically, inpatients move from small, rural hospitals to large, urban intitutions because 
their diseases require the latter s more sophiticated diagnostic and therapeutic facilties. 
Partitioning the readmision sample into readmisions to the same hospital versus 
readmiions to a diferent hospital permits verication of this clasical hypthesis. Under 
this servce regionaltion model, newly diagnose inpatients may return to their local 
hospitals for rehabiltation or treatment clos to their familes and support networks 
obscuring any regional referral pattern.  Readmiions to the same versus diferent hospital do not difer in gender distribution 
length of stay, or mortality. Patients readmitted to diferent hospitals are signcantly 
younger than patients readmitted to the same hospital (95% CI 1.83 to 6. 16). Possibly 
younger inpatients warrant more aggesive diagnosis and treatment, or older inpatients 
prefer not to travel to distant centers for defitive servce. As exted from both referral 
pattern and servce available, readmions to hospital diferent from the disharging 
hospital have a signcantly higher average cas mi index (95% CI -0.37 to -0.10) and enter 
larger intitutions (95% CI 96.7 to 11.3). (Appendix E-l). 
Th 
Readmiions to diferent intitutions do not difer in hospital characteritics.  finding 
than a refutation of the regionalition 
may capture a litation in the analysis, rather 
hypthesis. IT inpatients transfer to an urban center and subseuently re-enter the local 
hospital, the readmiions wi demographicay cancel each other out. (Appendix E-2). 
Th litation would not apply to measurig the ditance to the new hospital It would 
merely result in two trips of the requisite length. Over a fih of trips ocur withi the same 
city, nearly one-thid total les than 10 miles, and two-thids les than 50 mies. These 
relatively short distance could reflect either effective regionalition of servce or inpatient 
preference about accptable travel times. Patients travelig long distance for readmission 
are generally represent beneficiaries who nee hospitalition whie vacationing in the South 
during the witer, rather than the seerely il seekig relief at national medical centers. 
(Appendix E-3). (Figue 7). 
Hospi tal #1

Hospi tal #2

Hospi tal #3

Hospi tal #4 
Patients  Discharges 
Figure 8: Hospital frequency order 
trfer 
Number of  hospita 
To avoid the problem of admiions to diferent hospital canceling out each other 
demographic contrasts, an alternative analysis notes that no patient enters more than four 
different hospitals. Each hospital is ranked by the number of times it disharged this patient. 
The hospital with the most disharges bemes #1, conceptually the local hospital nearest 
the patient. The hospital with the second most discharges for the patient bemes #2, etc. 
The latter hospitals with fewer discharges should include the referral centers not identifed by 
the simpler "different hospital" analysis. (Figure 8).  frequency order, the average age drops and percent of males 
As hospitals increas in 
ca mi 
increas. Except for hospital #4, mortality and  index als increas. Length of stay 
shows no trend, whie by defition the average number of disharges per hospital decreases. 
(Appendix F-l). 
As origialy expted the higher frequency orders disproportionately include large, urban 
includes more for-profit hospitals. This 
and teachig hospitals. Interestigly, thi group als 
fiding  exptation that referral centers consist primariy of nonprofit 
contradicts the 
intitutions. (Appendix F-2). 
admk
causing multiple 

Examination of the ICD- CM coes for each inpatient's seuence of diharges reveals that 
a single chronic disas usualy accunts for most of each persn s hospitaltions. Grouping 
thes underlyig pathologies by spealty or organ system: Cardiology, pulonology, and 
disas 
gastroenterology accunt for 54.9 percent of  whether measured by number of 
inpatients or discharges. Only in general hematology doe the proportion of discharges 
exce 
signcantly  the proportion of inpatients, indicating a high rate of readmiions (95% 
CI -0.06 to -0.01). Upon disection of the underlyig ICD- CM coes, hemoglobinopathies 
conf 
Th 
accunt for thi discrepancy.  fiding  the clical impresion that such patients 
repeatedly present in criis. (Appendix G-l). (Figure 9). 
Cardiology 
Pulmonology 
Gastroenterology 
Other 
Patients  Discharges 
Figure 9: Diseas causing related readmiions 
Hemoglobinopathies group to DRG 395, red bloo cell disrders. Although thes bils 
constitute only 0.8 percent of diharges and 0.5 percent of reimbursement, the average 
payment of $2,063 in Fiscal Year (FY 198 sum to over $101 million. Some primary (e. 
sendary preventive measures (e.g., hydration 
genetic screenig, famiy counseling) and 
activity restriction) can reduce the nee for hospitalition. Medicare support of such 
activities could have a very high cost-benefit ratio, despite their being outside its traditional 
mision. A  7 percent of unnecary admisions hemoglobinopathy for 
reduction in the 46.
2 milion annually in hospitalition expns. 
could save $47.
Agegated as major diagnostic categories, the readmiion sample s proportions do not 
generally difer from the distribution of all disharges. However, readmiions include a 
signcantly higher fraction of respiratory disas (95% CI 0.01 to 0.05), principally chronic  Th 
obstructive pulmonary disas, pneumonia, and lung cancer.  finding als conform to 
the natural hitory of thes disas, being characteri by repeated hospitalition for acute 
exacerbations of the chronic, progresive, underlyig pathology. (Appendix G-2). 
Reasons for readmion (e.  , medically related readmiion) do not particularly cluster by 
diseases (e.g., cancer). Gastrointestinal disas compri half of rehospitalitions secndary 
to a precing  Planed readmiions include more cardiology and 
premature disharge. 
cas. 
gastroenterology  Unplaned, (but) medically related readmiions have a high 
disas, 
proportion of respiratory  pricipally chronic obstructive pulmonary disase. As 
disas 
expted, unelated readmions show no paricular  trends. (Appendi G-3). 
Based on the average number of times the patient enters the hospital anually by disease; 
cancer, hematology (hemoglobinopathies), pschiatry, congestive heart failure, and chronic 
obstructive pulmonary dias have particularly high averages. Thes trends also conform to 
disas. 
their natural hitory as chronic  In addition, myocardial inarctions constitute so high 
a share of readmiions that,they retain clical importance despite their relatively low 
frequency of readmisions per patient. (Appendix G-4). 
Rate (percent) 
c= 
Readmissions 
National DRG Study

10 . 
Hnneeded admissions  Poor quality care  Premature discharqe

comparn 
Figure 10: Clical revew 
Clca reew

Contractor physicians categori 162 medical recrds as documenting unnecary admision 
l). Thes 
por quality care, or prem'1ture discharge. (Appendix H- rates do not signifcantly 
difer from the random selection of disharges of the National DRG Validation Study. This 
finding suggests that PRO revew of readmiions identifes no more clical incidents than a 
proc. 
random  (Appendix H-2). (Figure 10). 
By contract, the PROs designated discharges for review in several speific ways during their 
send "scope of work" (approxiately 1987-88).  Random review: A 3.0 percent sample of all disharges (12.8 percent of all PRO 
revew). 
Readmiions revew: Al re-entries toc thae  same hospital ocurrng within 14 days of 
the index disharge (22.6 percent of " selected" for PRO revew). The HCFA 
has subsequently increas the revew period to 30 days. 
Other: Various selection algorithm such as outliers, designated DRGs, etc. (the 
remaing 64.
6 percent). 
clical 
Since the readmiions revew ditinguishes  incidents no better than random review, it 
unecary 
contnbutes nothing to PRO deterrence of  readmisions or medically appropriate 
communty. Disntinuing it would elimate 36.9 percent of PRO 
behavior by the clical 
send 
revew (each readmiion entai revew of both the fit and  disharge). The HCF 
estimates that readmiion revew annually cot $45-55 mion. 
Unnecary readmiions ocur most commonly in ophthalmology, hematology, and lung 
cancer. Improved PRO utiltion revew has deceas the incidence of unnecary lens 
procures subseuent to the date of thi samplig frame. Hemoglobinopathies' amenabilty 
to preventive measures and their high rate of unnecary hospitalitions make them a high 
yield target for further study.

por 
General neurology and hematologica oncology have the highest rates of  quality care. 
recnt 
Scentifc developments have rapidly advance both speialties in  years. Premature 
disharge ensues most frequently followig sepsis, gastrointestinal bleeing, and trauma 
although the small number of events detracts from the statistical reliabilty of these rates. 
(Appendix H-3). 
REMMATIONS

The HCF A should re-ealuate the effectivenes of PRO surveilance of readmissions 
versus sureilance of random admisions. 
utilition revew of 
The HCFA should study the effectivenes of PRO 
hemoglobinopathies. 
The HCF A should determe whether primary and sendary prevention of acute 
exacerbations of hemoglobinopathies would consume les Medicare resource than 
repeated hospitalitions. 
beaus 
The HCFA did not concur with thes recmmendations  they would require statutory 
change. We continue to believe that HCFA should propose legilative changes and take 
admintrative actions in order to implement our recmmendations.  Appendix A-I: Medca dishaes in FY 198 
Medicare beneficies

28 mion 
Aged
Disbled  2.9 mion 
PPS disharges 
8. mion 
Number 
pet)
(Hospitaliztion rate) (26.
PPS beneficiares diharged 
mion
Number  S.3 pet)
(17. 
(Hospitation perctage) 
Appendix A-2: Samplig frme 
Annual dishaes  Beneficiaries  Tota dis 
Numbe (perct)  Numbe (pert) 
per beneficiry 
8,s18  (66.8)  8,s18  (42.9) 
S,2 
2,64S  (20.  (26. 
913  (7.  2,739  (13.8) 
374  (2.9)  496  (7.s) 
IS6  (1.2)  780  (3. 
(O.s)  (0.2) 
(0.21)  189  (0.01) 
(O.IS)  IS2.  (0.00) 
(o.S)  (0.00) 
(o.S)  (0.00) 
(0.3)  (0.00) 
(0.2)  24- (0.001) 
(0.3)  (0.00) 
14+  (0.01)  (0.001) 
Total  12,744  (100.  19,8  (100.) 
Appendix A-3: Saple design 
Disharges per  Rea ested  OBbetaienefdi ci  Dises 
beneficiary  Beneficiries  Disharges 
112  111 
198 
196  180 
14+

Total  261  869  259  847
 (y) 
((%%))
Beeficiar demogphy 
Appendix A-4: 
Age  Geder  LOS  Ca mi  Mortlity 
(yea)  (% ma)  (da)  index  (millon) 
Beneficiries  74.  40.  S.51  26.1 milion 
Disharges  7S.  46.  7.2  11012  9 miJion 
t95% confidence interaH  t -0.27 to  02)  016 to  OOS) 
Res 
Sourc U.S. Health Ca Fmancig Adtrtion Offce of  an DeDStrations Medca and Medicaid Data Bok 1986. Baltimore, 
MD: HCFA Pub. No. 03247, Septembe 198. Table 3.10.  Se  Di 
1. U.S. Depament of Heath &. Hum Servce Public Heath  Cete for  Contrl, Nationa Ceter for Heath Statistics. Vital 
Statistics of the United States 198, Vol. II - Mortty, Par A Hyatts MD: DHH Pub. No. (PHS) 881122 198. P. 312 
2 Delaney AM &. Hsia DC (E.). Nationa DRG Valdation Stud. Legt MA Heath Data Intitute Novembe 1987. 
Appendix B-1: Dishaes by patient demogphy 
Age  Geer  LOS  Ca mi  Mortlity 
(% mae)  (da)  index 
National DRG 
Validation Study  73.  46.  7.5  1.101  70S0 
Readmisions saple  71.  48.  8.3  1.80  847 
t95% confidence interv)  8 to 3.  06 to 0.1)  H.3 to  .3)  .3 to 0.  02 to 0.02)  (%)  (%) 
Appendix B-2: Dishaes by hospital demogphy 
Reaions 
Nationa DRG  (95% confdence 
inteIH 
Validation  Samole 
(6) 
-:100  Zl76  (18.  186  (21.  (0.00 to 0.
(9) 
100-299  (37.5)  372  (43.  (0.03 to 0.
30+ be  (44.  (33.  (-0.135 to-0.64) 
Urban  4374  (71.5)  586  (69.2)  (-0.055 to 0.(9) 
Rur  '176  (28.  '11  (30.8)  (-0.00 to 0.055) 
Teaching  1854  (31.)  148  (17.3)  (-0.177 to -0.112) 
Nonteaching  5195  (68.  (81.  (0.112 to 0.177) 
Profit  689  (9.  (42.6)  (0.313 to 0.31) 
Nonprofit  6361  (90.  (24.  (-0.31 to -0.313) 
Public  273  (31. 
Source

Physician  (51.7)  393  (46.  (-0.08 to -0.001(7))


Clinic  136  (1.  (1.  (-0.010 to 0.
HMO  (0.  (0.)  (-0.00 to 0.(01) 
Hospital  116  (1.)  (5.  (0.27 to 0.48) 
SNF  (0.  (0.  (-0.014 to -0.(01) 
ICF  (2.8)  (3.5)  (-0.00 to 0.019) 
2786  (40.4)  (42.0)  (-0.014 to 0.056) 
0() 
Unknow  (0.  (0.  (-0.00 to 0.
Cause

Workup  5569  (778)  598  (69.8)  (-0.102 to -0.042)

Therapy  179  (2.7)  107  (12.)  (0.86 to 0.113)

Planned  109  (17.  110  (12.8)  (-0.072 to -0.018)

Outpatient  146  (1.  (3.  (0.00 to 0.02)

failure

(8) 
Emergency  1433  (20.  (9.5)  (-0.139 to -0.
Urgent  3791  (52.)  554  (64.  (0.09 to 0.165) 
Elecive  168  (25.  212  (24.  (-0.04 to 0.02) 
Unknow  (1.0)  (0.)  (-0.019 to -0.00) 
Total  7050  (100.  847  (100. 
1. Disharge weighted  (%) 
Appendi C-l: Readmions by patient demogphy 
Age  Geder  LOS  Ca mi  Mortlity 
(years)  (% mae)  (da)  index 
Initial admiions  727  47.  7.8  1.333  259 
Subsuent admisions  70.  48.  8.5  2018  588 
(95% confidence interJ  (0.7 to 4.3J  (-G.l to O.  8 to 0.  (0.03 to O.2J  (-G.13 to -G.06J 
ssion  nce 
727  47.  7.8  1333  256 
728  482  145 
71.2  49.  2746 
70.  40.  1.781  11. 
69.  53.  1.091  18. 
68.  40.  5.5  939  15. 
66.3  40.  9337 
622  40.  782  10. 
51.4  51.5  8565 
Reason for redmi 
Preous prematur dishae  827  33.3  1.181 
Planned redmiion  71.4  57.  8.3  21403 
Related redmion  68.  50.  0582  11.2  321 
Unrelated redmiion  73.  43.  1.168  8.3  194 
Source 
Physicin offce  70.  49.2  2118 
Clinic  70.  222  13.  0586  11. 
Another hospita  68.  55.  887  23.3 
EInmteerrmgeednicayt er ocmare  facity  7699..   3469..   10.5  11..50284   11.9  252 
Unkow  74.  4110 
Cause 
Workup  70.3  48.2  1.22  10.  407 
Therpy  69.  40.  6.5  10. 
Planned redmision  71.  59.  1.891 
Outpatient failur  65.5  59.  10.5  1.0507 
1.3 
Emergency  69.  50.  25. 
Urgent  70.  49.  1.259  8.4  396 
Elective  71.2  45.  6.5  1.31  138  (%)  (%) 
2: Readmiions by hospita demogphy 
Appendix C-
Intial  Subsuent  (95% confdence 
inter) 
admissio  misi 
.c 100  (21.9)  129  (220)  0.61 to 0.60) 
100-29 be  152  (58.5)  (23.5)  (0.137 to 0.28) 
30+ be  (19.  239  (40.5)  (-0.279 to -0.140) 
Urb  175  (67.  411  (69.  (-0.08 to 0.46) 
Rur  (32.)  177  (30.  (-0.04 to 0.(8) 
Teachig  (15.8)  108  (18.  (-0.08 to 0.31) 
Nonteaching  219  (84.  (81.8)  (-0.031 to 0.08) 
Profit  114  (43.8)  251  (428)  (-0.061 to 0.08) 
Nonprofi  (25.  144  (24.5)  (-0.058 to 0.06) 
Public  (31.)  1?J  (32.7)  (-0.08 to 0.053) 
Source

Physician  133  (51.  (443)  (-0.00 to 0.141)

Clinic  (1.9)  (1.5)  (-0.015 to 0.23)

HMO  (0.)  (0.)

Hospital  (1.  (73)  (-0.08 to -0.02)

SNF  (03)  (0.)  (0.001 to 0.00)

ICF  (3.  (3.  (-0.03 to 0.02)

108  (41.5)  252  (42.9)  (-0.08 to 0.058) 
Unkow  (0.  (0.  (-0.007 to 0.00) 
Caus

Workup  191  (73.  407  (69.  (-0.02 to 0.113)

Therpy  (6.5)  (153)  (-0.136 to -0.039)

(8)

Planned  (15.8)  (11.  (-0.00 to 0.
Outpatient  (3.  (3.  (-0.027 to 0.02)

failure

Emergency  (10.)  (9.  (-0.031 to 0.055) 
Urgent  158  (61.2)  396  (673)  (-0.131 to 0.00) 
Elective  (28.5)  138  (23.5  (-0.014 to 0.113) 
Unknow  (0.)  (0.) 
Tota  259  (100.  588  (100. 
Appendix C-3: Intervl between rehospitaliztions

Admisions  Days outside hospital 
5-6 
6-7 
7-8 
10-11 
11
12-13 
13 l: Reans (or redmiion 
Appendix D-
Numbe (percnt) 
Preous premature diharge  (1.) 
Planed redmiion  (11. 
Related redmiion  321  (54. 
Unrlated redmision  194  (33. 
Tota  588  (100.) 
Appendix D-2: Reans (or redmion by patient demogphy 
Pla 
Average  Preous prematur Related  Unrlated
dihae  redmiion  redmiion  redmion 
(95% en 
Age (years)  827 (4.4 to 2O.  71.4 (-1.7 to 4.  68.0 (-.0 to oO.  73.1 (0.8 to 5. 
Gender (% male)  33.3 (oO.6 to 0.3 J  59.7 (oO.02 to oO.  50.2 (oO.l to O.  428 (oO.l to 0.02J 
LOS (days) 7 (-8.2 to 26J  8.3 (-21 to 1.  4 (-1.3 to 1.)  0 (oO.8 to 1.8J 
Ca mix index  1.181 (oO.7 to O.5J  2140 (0.7 to 1.2J  1.0582 (oO.2 to oO.  1.166 (oO.2 to 0.3) 
Mortlity (%)  0 (oO.3 to O.  0 (oO.l to O.  11.2 (oO.02 to O.  2 (oO.l to 0.04)  Appendi D-3: Reans for redmion by hospita demogphy 
Number  Preous prematur Plaed  Related  Unrlated  Total 
(95% cn  dihae  redmiion  redmion  redmiion 
dOO  2 (-0.2 to 0.  7 (-0.2 to -0.  71 (-0.1 to 0.  49 (-0.1 to 0.  129 
100-299  2 (-0.4 to 0.3)  23 (-0.2 to 0.  114 (-0.1 to 0.  81 (-0.1 to 0. 
30+ be  2 (-0.5 to 0.3)  37 (0.1 to 0.3)  136 (-0.1 to 0.  64 (-0.2 to 0.  239 
Urb  3 (-0.6 to 0.  55 (0.1 to 0.  22 (-0.1 to 0.  124 (-0.1 to 0.  411 
Rur  3 (-0.2 to 0.  12 (-0.2 to -0.  92 (-0.1 to 0.  70 (-0.1 to 0.  177 
Teachig  0 (-0.5 to 0.  16 (-0.1 to 0.2)  68 (-0.1 to 0.  24 (-0.1 to 0.  108 
Nonteaching  6 (-0.1 to 0.5)  51 (-0.2 to 0.  253 (-0.1 to 0.  170 (-0.1 to 0. 
Profit  1 (-0.7 to 0.  34 (-0.1 to 0.  147 (-0.1 to 0.  69 (-0.2 to 0.  251 
Nonprofit  3 (-0.1 to 0.  17 (-0.1 to 0.  73 (-0.1 to 0.  51 (-0.1 to 0.  144 
Public  2 (-0.4 to 0.  16 (-0.2 to 0.  101 (-0.1 to 0.  74 (-0.1 to 0.  193 
Phyicin  4 (-0.2 to 0.  59 (0.3 to 0.  123 (-0.1 to 0.  74 (-0.1 to 0. 
Clnic  0 (-0.1 to 0.  0 (-0.1 to 0.  7 (-0.1 to 0.  3 (-0.1 to 0. 
Hospita  0 (-0.3 to 0.  7 (-0.1 to 0.  26 (-0.1 to 0.  10 (-0.1 to 0. 
ICF  0 (-0.2 to 0.  0 (-0.1 to 0.  10 (-0.1 to 0.  12 (-0.1 to 0. 
Emergency Room  2 (-0.5 to 0.3)  1 (-0.5 to 0.3)  155 (-0.1 to 0.  94 (-0.1 to 0.  252 
Unkow  0 (-0.1 to 0.  0 (-0.1 to 0.  0 (-0.1 to 0.  1 (-0.1 to 0. 
Workup  4 (-0.3 to 0.3)  0 (-0.8 to -0.  237 (-0.1 to 0.  166 (0.1 to 0. 
Therapy  1 (-0.3 to 0.3)  0 (-0.2 to -0.  69 (0.1 to 0.  20 (-0.1 to 0. 
Planned proure  1 (-0.2 to 0.3)  67 (0.8 to 1.)  1 (-0.2 to -0.  0 (-0.2 to -0. 
Outpatient faur  0 (-0.2 to 0.  0 (-0.1 to 0.  -14 (-0.1 to 0.  8 (-0.1 to 0. 
Url!encv 
Emergency  0 (-0.3 to 0.  2 (-0.1 to 0.  28 (-0.1 to 0.  24 (-0.1 to 0. 
Urgent  5 (-0.2 to 0.5)  5 (-0.7 to -0.5)  !4 (-0.1 to 0.  146 (0.1 to 0.  396 
Elective  1 (-0.4 to 0.3)  60 (0.5 to 0.8)  53 (-0.1 to -0.  24 (-0.2 to -0.  138 
mision 
5 (-0.1 to 0.  37 (-0.1 to 0.  109 (-0.2 to -0.  105 (0.1 to 0.  256 
1 (-0.4 to 0.3)  17 (-0.1 to 0.  74 (-0.1 to 0.  53 (-0.1 to 0.  145 
0 (-0.4 to 0.  10 (-0.1 to 0.  47 (-0.1 to 0.  20 (-0.1 to 0. 
0 (-0.2 to 0.  1 (-0.1 to 0.  26 (-0.1 to 0.  5 (-0.1 to 0. 
0 (-0.2 to 0.  1 (-0.1 to 0.  14 (-0.1 to 0.  5 (-0.1 to 0. 
0 (-0.2 to 0.  0 (-0.1 to 0.  12 (-0.1 to 0.  3 (-0.1 to 0. 
0 (-0.1 to 0.  0 (-0.1 to 0.  9 (-0.1 to 0.  1 (-0.1 to 0. 
0 (-0.1 to 0.  0 (-0.1 to 0.  6 (-0.1 to 0.  0 (-0.1 to 0. 
0 (-0.2 to 0.  1 (-0.1 to 0.  24 (-0.1 to 0.  2 (-0.1 to -0. 
Dav between redmissio 
0-15  6 (0.1 to 0.  44 (-0.1 to 0.  187 (-0.1 to 0.  117 (-0.1 to 0.  354 
16-30  0 (-0.4 to 0.  5 (-0.1 to 0.  51 (-0.1 to 0.  20 (-0.1 to 0. 
31-45  0 (-0.3 to 0.  5 (-0.1 to 0.  30 (-0.1 to 0.  15 (-0.1 to 0. 
0 (-0.2 to 0.  3 (-0.1 to 0.  18 (-0.1 to 0.  10 (-0.1 to 0. 
61 0 (-0.2 to 0.  1 (-0.1 to 0.  14 (-0.1 to 0.  11 (-0.1 to 0. 
91-120  0 (-0.2 to 0.  2 (-0.1 to 0.  7 (-0.1 to 0.  8 (-0.1 to 0. 
121+  0 (-0.2 to 0.  7 (-0.1 to 0.  14 (-0.1 to 0.  13 (-0.1 to 0. 
Total  321  194  588  Appedi E-1: Readmions to diferent hospita by patient demogph 
Same hospital  Diferet hospita  t9S% confidence interv) 
Age (yea)
 71.9  67.8  83 to 6.16)
Se (% male)  48.3  48.  t -0.09 to o.S) 
LOS (da)  8.3  t -1.4 to 1.3) 
Mortty (%)  1.93.2   t-O.OS to 0.003) 
Ca mi index  1.30  t-O.37 to -0.10) 
Appedi E-2: Readmiions to diferet hospita by hopita demogphy 
Same hosc tal  Differet hPosecirtta   t9S% coinnftdee)n  
Number  Percnt  Numbe 
Averge  291  345  96.7 to -11.3) 
-:100  155  (23.  (19.  t-O.03 to 0.11) 
10029  25S  (38.  (34.  t -0.04 to 0.12) 
30+ be  254  (38.3)  (46.  t-O.16 to 0.001) 
Urbn  451  (62.6)  135  (73.  t -0.13 to 0.2) 
Rur  212  (32.0)  (36.3)  t -0.02 to 0.13) 
Teaching  109  (16.  (21.2)  t -0.11 to 0.01) 
Non-teaching  554  (83.  145  (7S.  t-O.01 to 0.11) 
Profit  (44.  (39.  t-O.03 to 0.13) 
Non-profi  160  (24.  (26.  t-O.10 to  05) 
Governent  210  (31.7)  (34.2)  t -0.10 to 0.05) 
Total  663  (78.3)  184  (21.7) 
Appendix E-3: Distance to dierent hospita 
(pert) 
Number 
Sae city  (22) 
Same state, diferent city  118  (64.

-:10 mies  (8.

10-49 mies  (29.

50-99 mies  (17.)

100+ mies  (8.7)

Different state  (13.

-: 10 mies  (1.

(1.)

10-49 miles 
50-99 mies  (3.8) .

100.100 mies  (2.2) 
100+ miles  (4.

Tota  184  (100.
 1: Numbe of diferent hospita viited in fruency order by patient demogphy 
Appendix F-
mber of differt hOlDita oer oatient 
TotaVAverge 
Age (years) 
Fllt hospita
 728  720  67.2  327  71. 
Send hospita 71.  68.3  69. 
Th 
hospital  68.3  32.6  60. 
Fourh hospita 
Tota  72.  71.  67.  32.  71. 
Se (% mae) 
Fllt hospita 50.  41.  48.  100.  48.5 
Send hospital  44.2  40.  100.  45. 
Thir hospital  47.  100.  59. 
Fourth hospita  100.  100. 
Tota  50.  42.  46.  100.  48. 
LOS (days) 
Fllt hospita

Send hospital 9.3 
Th 
hospita  7.5  2.6 
Fourh hospita  10.  10. 
Total  8.8  2.4  8.3 
Mortlity (%) 
Fllt hospital
 2.2 
Send 
hospital 
Third hospita  23.5  18.2 
Fourh hospita 
Total  6.3 
Ca 
mix index 
Fllt hospital
 1.32  1.796  1.514  7116  11.3.339  
Send hospita  1.4051  1.34  662 
Thir hospita
 7133  1.5117 
Fourh hospita  7758  7758 
1.80 
Total  1.320  2613  2767 
Averge disharges per hospita 
Fllt hospita
 2.6  4.8  3.8 
Send hospita  1.2  2.2 
Third hospita 
Fourh hospita 
Avege  2.1  3.3  6.8  Appendi F-2: Freuency order by be siz 
Number  mbe of differnt hosDita oer  tient 
(percnt)  TotaVAverge 
Al patients  148  259 
Al disharges 
F1It hospita  452  183  689 
Send hospital 104  135 
Th 
hospita 
Fourh hospital 
Tota  452  847 
.:100 
F1It hospita (19.5)  (36.  (37.  (0.  171  (24. 
Send hospita (4.  (36.  (0.)  (10.4) 
Th 
hospita (5.  (0.)  (4. 
Four hospita  (0.)  (0.) 
Tota  (19.5)  (24.  (31.)  (0.  186  (22. 
10029 
F1It hospita  178  (39.  (39.  (31.)  (0.  265  (38.5) 
Send hospita  (35.  (40.  (100.  (39.3) 
Third hospita  (23.5)  (0.  (18. 
Fourth hospita  (0.  (0. 
Tota  178  (39.  110  (38.3)  (322)  (28.  322  (38. 
30+ 
FIrst hospita  186  (41.  (24.  (31.)  (100.  253  (36. 
Send hospita (59.  (24.  (0.  (50. 
Th 
hospita  (70.  (100.  (77.3) 
Fourh hospita  (100.  (100. 
Tota  186  (41.  106  (36.  (36.  (71.4)  339  (40.  Appedix F-3: Frequency order by hospita demogphy 
Numbe  mber of different hosDitals ocr oatient 
(perct)  Tota 
Urb 
F1It hospita  323  (71.5)  103  (56.3)  (55.  (100.)  (66. 
Send hospita (827)  (520)  (100.)  105  (77. 
Th 
hospital (88.  (100.)  (90. 
Four hospita  (100.)  (100.) 
Tota  323  (71.5)  189  (65.  (60.  (100.)  586  (69. 
Rur 
F1It hospita  129  (28.5)  (43.  (44.  (0.)  (33. 
Send hospita (17.3)  (480)  (0.)  (22. 
Th 
hospita  (11.  (0.)  (9. 
Fourh hospital  (0.  (0. 
Tota  129  (28.5)  (75.3)  (39.  (0.)  261  (30. 
Teachig 
First hospita (17.  (11.5)  (11.)  (100.)  116  (16. 
Send hospita (21.2)  (120)  (0.)  (18. 
Th 
hospita  (11.8)  (100.)  (31.8) 
Fourth hospita  (0.)  (0. 
Tota  (17.  (15.  (11.5)  (66.  148  (17.5) 
Non-teachig 
F1It hospita  371  (821)  162  (88.5)  (88.  (0.)  573  (83. 
Send hospital (78.8)  (88.  (100.)  110  (81.5) 
Th 
hospita  188.  (0.)  (68. 
Fourh hospita  (100.)  (100.) 
Tota  371  (821)  (85.  (88.5)  (33.3)  699  (825) 
For-profit 
F1It hospita  197  (43.  (41.)  (33.3)  (100.)  (43. 
Send hospita  (43.3)  (20.  (100.)  (41.5) 
Thir hospital  (41.2)  (100.  (54. 
Fourth hospita  (100.  (100. 
Tota  197  (43.  120  (41.8)  (31.)  (100.  365  (43. 
Non-profit 
F1It hospita  104  (23.  (24.  (40.  (0.)  166  (24. 
Send hospita  (29.  (320)  (0.)  (28. 
Thrd hospita  (23.5)  (0.)  (18. 
Fourh hospita  (0.  (0. 
Tota  104  (23.  (26.  (34.5)  (0.)  (24. 
Government 
F1It hospita  151  (33.4)  (35.  (26.  (0.)  227  (32. 
Send hospital  (26.  (48.  (0.)  (29. 
Third hospital  (35.3)  (0.)  (27.3) 
(0.)  (0.) 
Fourth hospita 
Total  151  (33.4)  (321)  (34.5)  (0.)  273  (322)  (%)  (%) 
Dis  disha 
Appendix G-l:  causing multiple 
ients  Dishal'es  (95% confidence 
interaH 
Nonspec metata  (0.  (1.  02 to 0.01) 
Fluids &: elecrolyes  (3.  (2.7)  02 to 0.02) 
Hematology 
Inection  (1.9)  (1.3)  01 to 0.02) 
Caoma  (3.  (2.7)  02 to 0.02) 
Other  (1.  (4.3)  06 to  01) 
Psychiatr 
Alcohol  (1.5  (1.5)  02 to 0.2) 
Drugs  (1.5  (1.3)  01 to 0.02) 
Other  (2.7)  (2.7)  02 to 0.02) 
Neurlog
Vas 
accdent  (4.2)  (4.3)  03 to 0.3) 
Caoma  (0.8)  (1.  02 to 0.01) 
Other  (1.2)  (0.  01 to 0.02) 
Ophthalmolog  (1.  (0.  01 to 0.2) 
Otolagolog  (0.  (0.  01 to 0.01) 
Cardiolog
Arhytmi  (3.5)  (3.3)  02 to 0.3)
Inion  (11.  (9.  02 to 0.(6) 
Heart faur  (7.  (10.  07 to 0.02) 
Ovthaer s  (0.  (0.  01 to 0.01) 
Peripheral  (1.  (1.4)  01 to 0.02) 
Pulmonology 
Lung caoma  (2.7)  (3.  03 to 0.02) 
Pneumoni  (6.  (6.  03 to 0.3) 
Chnic obstrction  (8.  (7.  03 to 0.4) 
Gastrnterolog
Caoma  (5.  (6.8)  OS  to 0.02) 
Bleeing  (2.7)  (2.4)  01 to 0.3) 
Other  (6.  (5.  02 to 0.4) 
Urolog 
Caoma  (5.  (3.  01 to 0.4) 
Other  (4.  (3.  02 to 0.3) 
Gyeclogica caoma  (2.)  (3.  03 to 0.02)
Bret carcoma
 (1.)  (1.)  02 to 0.01)
Orthopeics 
Back  (1.)  (1.4)  02 to 0.02) 
Hip  (2.7)  (2.2)  02 to 0.3) 
Knee  (0.  (0.5)  01 to 0.01) 
Traum  (2.7)  (2.6)  02 to 0.02) 
Total  259  (100.)  847  (100. 
dihaes 
Appendix G-2: Major dignostic categories causing multiple 
(percnt  Readmiions  Nationa DRG  (95% confdence

distribution)  saple  Validation Study  interH

Caiolog  (23.  (23.5)  03 to 0.03)

Pulmonology  (16.  (14.  (0.01 to 0.05)

Gastronterlogy  (14.  (15.3)  04 to 0.01)

Other  (45.  (47.  06 to 0.02) 
Total  (100.  (100.  Dis  ren 
3:  by redmiion 
Appendix 0-
Preous premature  Planned  Related  Unrlated  Total 
diharge  redmision  redmiion  redmiion 
metata 
Nonspefic 
Fluids & electrlyes 
Hematology 
Inecion 
Caoma 
Other 
Psychitr 
Alcohol 
Drugs 
Other 
Neurlog
Vasla 
accdent 
Caoma 
Other 
Ophthalmolog 
Otolarygolog 
CardiologyAria
Inrcon 
Hea faure 
Other 
vasul 
Periphera 
Pulmonolog 
Lug carcioma 
Pneumoni 
Chnic obstruction 
Gastronterology
Caoma 
Bleeing 
Other 
Urology 
Caoma 
Other 
caoma 
Gyeclogical 
Bret carcoma 
Orthopecs 
Back 
Hip 
Knee 
Traum 
Total  321  194  588  Dis 
dihages 
Appendix 0-4:  by numbe of 
Dishaes pe patient  Total 
metata 
Nonspefic 
Fluids & elecrolyes 
Hematology 
Inecion 
Caoma 
Other 
Psychiauy 
Alcohol 
Drugs 
Other 
Neurlogy
Vasla 
accdent 
Caoma 
Other 
Ophthaolog 
Otolarygolog 
Cardology
Arythm
Infon 
Hea failur 
Other 
vaul 
Periphera 
Pulmonolog
Lug caoma 
Pneumoni 
Chnic obstruction 
Gastronterlogy
Caoma 
Bleeg 
Other 
Urology 
Caoma 
Other

caoma

Gyeclogca 
Bret caoma 
Orthopecs

Back

Hip

Knee

Traum 
Tota  111  259 
1: Clical reew 
Appendix H-
Numbe  (Rte) 
Unnecry admiions  112  (13.

Poor quality  (4.

Pretur dihages  (1.
 2: Clica reew compan 
Appendi H-
(Rate)  Readmions  National DRG  (95% confidence
saple  Validation Study  intem) 
Unnecry cadmaiio n(s4 (13..   (10.)  (-0.01 to 0.4) 
Poor quatyd ishae  (5.5)  (-0.02 to 0.01) 
Prematur  (1.2)  (0.8)  (-0.01 to 0.01) 
Dis 
Appendi H-3:  by clica reew 
(Rte)  Unnec  Poor quality  Pdreituer  
admion 
Nonspec metata  (0.)  (0.)  (0. 
Auids &. eleclyes  (13.  (0.)  (0.) 
Hematology
Inecon  (9.  (0.)  (9.
Caoma  (13.  (18.  (0.) 
Other  (46.  (0.)  (0.) 
PsychitI 
Alcohol  (23.  (0.)  (0.) 
Drugs  (0.)  (0.)  (0.) 
Other  (26.  (8.  (0.) 
Neurlog
Vas 
accdent  (5.  (16.  (28)
Caoma  (11.)  (11.  (0.) 
Other  (125)  (37.5)  (0.) 
Ophthology  (83.3)  (0.)  (0.) 
Otolagology  (0.)  (0.  (0.) 
Cardiolog
Arythmi  (7.  (0.)  (0.)
Intion 
(8.5)  (1.2)  (1. 
Hea faur  (3.5  (5.8)  (1.2) 
Other  (0.)  (0.)  (0.) 
Peripheral  (16.  (8.3)  (0.) 
Pulonology 
Lung caoma  (30.  (0.)  (0.) 
Pneumoni  (1.)  (5.  (0.) 
Chrnic obstrction  19.5)  (1.6)  (0.) 
Gastronterlogy 
Cacioma  (224)  (6.  (1. 
Bleeing  (5.  (10.)  (5. 
Other  (14.3)  (4.8)  (24) 
Urology 
Caoma 
(16.  (6.5)  (3. 
Other  (9.  (3.  (3. 
Gyeclogical carcinoma  (18.5)  (3.  (0.) 
Bret carcioma  (0.)  (0.)  (0.) 
Orthopeics 
Back  (21.4)  (7.  (0.) 
Hip  (5.3)  (5.3)  (0.) 
Knee  (0.  (0.)  (0. 
Traum  (227)  (4.5)  (4.5) 
Tota  (13.  (4.  (1.2)  Appendi 1-1: HCFA comments 
Ca 
Adsttion 
of the Heath Ca Finin 
Drft Rert 
on the OIG  ''Hosita Redmssions. 
01 -12-88-01120 
Retion 
reuate th effeciven of Pe 
HCF shc:d  ver  Reiew Oranzation 
(:E) sweilan of redmion  sweillan of raam
admion. 
co  ca 
mt  with  eunrt icu  dintinue 
wceu d os willa(nQd onf  rieth d mion  ron. eFir,    law. Seaomn 19 52 of 
seta  Seion 
L. 99-509t h soiaB Sueeti tRye iliation Ac of 1986) 
ocinA c to  trhee    to reiew a
sc11a54:l e(ea )o o.ff r  edmion  su  with 31 days of th preiou
cle.  To  reiew wod reona  legislative
cowe  also beieve tchto ari osingn fiicna ,  in th reiew 
bsPalee rveize  cwoidth  vthiSo lcaytiee  r of pretu c:eass ur tcho iMnueecs ato
Paym 
(Pm).

awy 
5er-' "the nOI G  reiew a setleh o f al Pm redmion

duin  Yea 1f98r5  aom tfo u 1!t  redmion did no
signficay differ  hbitaization in thc ra:tee o"f 
pretu 
quity ca, or 
uin( dPeangef iie)s.  nFo rlir m rtedh ico,nl ,iitf hnpiec o marr. e inr ti dceonl uthd  thrta c::E  sreeieecwi oonf  oref dcomacio infnosr  
ca  redmion 
reiew. Haoer, the  fra OIG's reiew of  c:e.
wreithi o1 nye a of  oc  clealy  be awlied to the PR reiew of
with  af die,
whch  31 days of th preiou 
bieniedve   enins r eiewe wne  limte 
tohft  if OIG' an  yea, thto  p31e tdaaygs e toif c linca us 
th 
inide wod have be nu high.r e'!l elOsBer  peiod 
sale 
the sale fra, th mre th  rac: sale.

'l,  ca 
th prole "sein" 
we  ignre  emffece o f :Ed reeitewe ton 
ressions. 
eeaafflseyc   of :E  Whper iet tius  nho ops:iltabl ce :toe  s, it thise  renale
reiew on  oc if 
reion ca.a b wod  PR we no reiewin ealy
tht DDre 
Rection 
st 
th effecven 
HCF shc:d  of :E utization reiew of
he1lobinthes.  Page 2

Rens 
Wuthet d ani ghigr.h   wnituh th  of Ltht: IaLdLitotinon af.o Fr ilhr e, lbtoeho  eiiI.Gnt hpcersett s nfo oecvi den 
In adtion, FR  to 
shuavtes  , su 
dcleintcea   th  as heloointhes, if
inteified reiew on 
ha  tht 
physician reiew  is a prOlem with
admion. 
Rection 
shd dete whth  co  reacuur
HeCxFc  :tion  prim am  lepsre vMenteicona o f 
th rete of heloointhes wod 
hositaization. 
Rens 
co  retion. 
th  stte 
no  with  As cota 
We also do  coer  sc  in the report, 
Mth  eca mamtee. ,I nb yas dth  tieon,  in.u uthdX Mtioen cara  pnoo ationc, porinii mtIhe  
su 
preenirvee ev.  as gentic  am fasmuy es  have
litte 
'!e  al 
rert,  hydtion am actprevenvie ty reicton,  offer lini ttthee
clincasu crhe aes v.:t hoitaization  helobinthes 
for 
in the 
eldely.
Ge 
aJ 
este 
Wafer nb ei e:vme  tchto e IaG'r  grte ths tahvi na ocf t savi$r1 1t1h mt ilwioond i nret 
elimtion  ion. 
nmi
of :m reiew of 
HCF' s esilte for th co of the tny  otfh re iew is
aprothte-yr o$11 0 milion for th  thc otrct cycle.
Sainn   contct arre nioormnly  for  cey ea, the
di co of ealy 
reiew woud
approtey 
$35 to $45 milion. Wee satre n.o   how eIG
savir 
develop the  milion 
$111 
in 
poal 
In  savin wod 
be offset by even a slight
pa,  in thce anutme   le reiew, whch would be
nesary to  of froaanr  elimti :m reiew of ealy
redmions.  su
Page 3
 in 
nu 
'!er cod  also be an  ret  ine thxe  y  of 
CClai, 
whch wod  in  co-inteive PR 
actvity . 
unerta 
'! rert  urea 
is  in ma place.  ha difficuty 
we 
th sele seecon, th critebia efo r clasifyinf Wredmiss.si ons, the
sttica meth us, an th talest ea,n  th  '!e 
wan feor:t r  tales an
native mvfeisg buac.k   intin 
taalwes a n  referf,u ly  the te an
rey fotlalCleMs t thh dt aatar  arn leogic  usS Oci nth et t hrli  redieo nc.a A lnsoor,e much
dof1 th  ctrlii scsi)o ni,s  (ne.og .g  e to tahge , seth  or hisoeista. '!e
rEliuermtion do no flCM fra th fWi. 
Edtoial 
pa, 
di th  stte tht 
Page 3 - In  fir ful  lin 3  ocin the PR
reiew reate redmion to PP ho'Iit as inrr.w  ith 
of  fr  hoita.  is  '!e s7a dlaey s
wres ion ir tht  ion with 7  ws no tied to
all reatte o th sa rlhi o!:sita.  days; it 
'!e las se- se fu 
sc  in the  pagtt: reds as if in 
PR  'I  HC stiln mrra.te  reiew of soncy  reate the new 
admionof.  woprk, e 
cx  In th ne  of work, the
is also.  die 
reiew is a 25  raan sele of all redmions to
hoitas  with 
31 days of  fra a PP hosita. 
th 
rIne thio thn  fu  , lin 1,  is th sa err
th sa hoita.

to 
th fou ful  un '
In  " HCF doe

wh' tPhla sna riecdem ions,
no 
pet plan redmion  shoud have
proided in on sty .

Bulet 2 also stte in err tht the PR reiew wa limte

Page 14, 
to redmion to th sa hoita.