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The Italian case: methods and case-studies
Authors:
Silvia Francisci (ISS)
Anna Gigli (IRPPS-CNR)
Maura Mezzetti (Università di Roma Tor Vergata)
Francesco Giusti (Tuscany Cancer Registry)
Stefano Guzzinati (Veneto Cancer Registry)
Overview
Description of the situation in Italy
Aims and challenges
Methods for costs estimation
Data sources: needed Vs available
Two case-studies
Open issues
Background
Prevalent cases (in 2008): 1.8 mln
Total health expenditure (2008): €112 bln (7.1% of GDP)
Expenditure dedicated to cancer: €7.5 bln
(6.7% of health expenditure)
Growth trends both in terms of costs (more expensive treatments) and cases (population ageing, improving survival)
(Sources: ITAPREVAL, ISTAT, WHO)
Rationale
Develop a methodology suitable to the Italian context to:
• estimate present and future cancer costs
• evaluate different scenarios (screening, etc.)
• plan resources to be allocated to oncology
Major challenges• Create a dataset by merging information from
different sources
• Adapt existing methods and develop new ones
Methods Cancer survivors at current time T are assumed to be
distributed according to three disease phases: initial 0, continuing 1, terminal 2.
The following steps are required to derive the cancer burden profile, according to disease phases:
• Estimate and decompose observed survivors by phases
• Estimate and decompose unobserved survivors by phases
• Estimate the distribution of costs by phases
• Combine survivors (prevalent cases) and costs by phases
Decomposition of prevalent cases
Initial phase
Continuing phase
Terminal phase
NobsT,0
NobsT,1
+ NuT,1
+ LT,1
NobsT,2
+ NuT,2
+ LT,2
Lost to follow-up
Before registration
NT =
Observed prevalent cases
Markov process
Initial → Continuing → Terminal
Transition probabilities are estimated for the last year of available data (T-K) and then used to update Nobs from (T-K) to T.
Markov process
Initial 0 → Cont 1 → Term 2
Transition probabilities 0 1 2 0 − p
01 p
02
1 − p11
p12
2 − − −
p01
(t)= Prob(yt= 1 | y
t-1= 0)
Nobst,0
is estimated from an ad-hoc incidence function
Nobst,1
= Nobst-1,0
x p01
(t) + Nobst-1,1
x p11
(t)
Nobst,2
= Nobst-1,0
x p02
(t) + Nobst-1,1
x p12
(t)
These equations are reiterated from T- K to the current time T
Unobserved prevalent cases: estimation
Patients diagnosed before the registry activity and still alive at the current time t, are not directly observed and are estimated using the completeness index R, specific by tumour site, age, sex and length of CR (all these variables are included in vector x):
where Rx= completeness index but
Nux = Nu
1, x + Nu
2, x => decomposition?
1
1
x
obsx
ux R
N=N
Unobserved prevalent cases: decomposition strategy
• Hp 1: Nu1
and Nu2 same proportion as Nobs
1
and Nobs2
of the first available diagnosis
cohort unobserved have same survival as first observed cohort =>
need to isolate cohort
• Hp 2: Nu1
and Nu2 same proportion as cured
and non-cured cases (estimated from survival) proportion of cured estimated from more recent cases =>
overestimate of intermediate patients
Unobserved prevalent cases: decomposition strategy
• Hp 3: Nu1
and Nu2 same proportion as Nobs
1
and Nobs2 wrt age at prevalence
Nu made of older patients diagnosed when they were younger
(i.e. better prognosis) => overestimation of terminal patients
• Hp 4: Nu1
and Nu2 same proportion as Nobs
1
and Nobs2
wrt age at diagnosis Nu made of patients diagnosed in the past (i.e. worse
therapies) => underestimation of terminal patients
Which is the preferable hypothesis?
Lost of follow up
• Survival and distribution into disease phases of cases lost to follow-up is needed in order to adjust the observed prevalent cases
• Assume they survive and decompose like observed cases (homogeneously with respect to age, sex,…)
LT,1=LT X {NobsT,1/(Nobs
T,1+NobsT,2)}
LT,2=LT X {NobsT,2/(Nobs
T,1+NobsT,2)}
Cost estimate and decomposition
Initial Phase
Continuing Phase
Terminal Phase
CT,0
CT,1
CT,2
CT =
• The cost profile is a vector, with three components, according to the disease phases.
• Each component is derived by averaging the cost of cancer patients observed in a given phase of the disease.
• The average is specific by x = (cancer site, age, stage,...)
Estimate total current cost
The total current cost for a specific cancer is derived by multiplying prevalent cases by corresponding cost wrt disease phase:
Total CT,x
= NobsT,0,x
x CT,0,x
+
(NobsT,1,x
+ NUT,1,x
+ LT,1,x
) x CT,1,x
+
(NobsT,2,x
+ NUT,2,j
+ LT,2,x
) x CT,2,x
and then summing up by x CT, total
Data needed
Two different sources need to be combined and used:
Cancer Registries• Incidence and
follow-up data• Surveillance source• Demographic and
clinical information
Regional Health System • Hospital Discharge
Cards (HDC/SDO)• Administrative
source• Clinical and cost
information (based on DRG system)
Data Available: the Italian Cancer Registries
No homogeneous life span: 30 registries from 1976 to 2010
Source: AIRTUM
19 mln residents in CR's areas (34% population)
Data Available: the Italian Cancer Registries
No sample design
North 50%Centre 25%
South 18%
Source: AIRTUM
Data Available: Hospital Discharge Card
• Within the NHS every hospital must fill the HDCs, that will be centrally collected at regional level
• HDC contains demographic, clinical and cost related information for each individual hospital admission and discharge
• HDCs allow to identify each single patient disease history from first diagnosis to possible recovery or death.
Regionalization
• National Ministry of Health supervises and sets the minimum reimbursement price
• Regional independent public health systems (21). Each of them provides care to residents and sets the final reimbursement to be given to hospitals
Two case-studies
• Two cancer registries (Padua and Florence and Prato) have been analyzed
• Major data issues (availability and completeness of information, record linkage) will be presented for colorectal cancer patients in Veneto and Tuscany
Data descriptionCancer Registries:
Padua and Florence-Prato (high quality data)
Cancer site:
Colorectal cases (ICD-X C18-21)
Information collected:
site, morphology, stage, date of diagnosis, date of last follow up, vital status
Padua Local Health Unit: 380,000 inhabitants
Florence and Prato provinces: 1,200,000 inhabitants
Hospital discharges
Ordinary and day hospital (DH) discharges with information about date of discharge, diagnosis, procedures, DRG code
In Veneto CR 95% of colorectal incident cases in 1990-2005 have at least 1 hospital discharge with a diagnosis of tumour
Record linkage (RL)Deterministic RL of incident cases with Hospital
discharges by unique identified number
Padua:
- RL of 609 colorectal incident cases in 2000-2001 with 7,6 million of regional hospital discharges (H) for 2000-2006 period
5,195 records for 607 incident cases
Florence-Prato:
11,121 records for 2,115 colorectal incident cases in 2000-2001
APPROPRIATE DISCHARGES:
Every discharge is classified according a list of ICD9-CM codes about
disease and injuries (for example 153=malignant neoplasm of colon, 154=malignant neoplasm of rectum, rectosigmoid junction and anus, V58.1 chemotherapy)
procedures (for example 45.23 colonoscopy, 99.25 injection or infusion of cancer chemotherapeutic substance, 45.73 Open and other right hemicolectomy)
Padua: 74% of total discharges linked (3,828 records) is appropriate
Florence-Prato: 69% (7,715 records) is appropriate
Major NON-APPROPRIATE Discharges
Diseases Of The Circulatory System – Padua 23%, Florence-Prato 22%
Diseases Of The Digestive System – Padua 13%, Florence-Prato 15%
Other neoplasm different than colorectal – Padua 10%, Florence-Prato 12%
Distribution of subjects by phase of care
Initial phase (first 12 months after diagnosis)(date of discharge – date of diagnosis) < 1 year
Continuing (intermediate) phase
Final (terminal) phase (last year of life)(date of death – date of discharge) < 1 year
12/9%
37/35%1/1%
18/23%
13/15%
19/16%
1/1%
Complete path: Padua 44%Florence-Prato 47%
Padua/Florence-Prato
Distribution over time (2000-2006) of hospital expenditure (€) of colorectal cancer patients
diagnosed in years 2000-2001 for appropriate dischargesYear Discharges Expenditure
(€)N. of patients
in INITIAL phase
N. of patients in CONTINUING
phase
N. of patients in FINAL
phase
2000 721 2,721,737 231 36
2001 1438 4,836,668 349 49 118
2002 730 1,918,096 102 79 83
2003 397 867,395 75 622004 239 623,272 45 352005 187 464,572 42 272006 116 221,025 19 16Total 3828 11,652,765 682 309 377
Padua
Year Discharges Expenditure (€) N. of patients in INITIAL
phase
N. of patients in CONTINUING
phase
N. of patients in FINAL phase
2000 1862 10,022,688 776 236
2001 2729 14,684,233 970 137 368
2002 1339 6,341,692 272 265 249
2003 713 2,526,120 208 170
2004 486 1,750,252 130 108
2005 357 1,281,530 100 83
2006 229 817,016 64 54
Total 7715 37,423,531 2,001 921 1,268
Florence-Prato
Average patients expenditure (€), Padua
66% 84% 79% 73% 64% 59% 49%
% appropriate discharge by year
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
2000 2001 2002 2003 2004 2005 2006
€ Ordinary
DH
Average expenditure (€) by phase of care during the period 2000-’06 for the 2000-’01
incident cases
*every subject could contribute to more than one phase
Phase of care Discharges Subjects* Average expenditure
by subject (€)Initial (1 year since diagnosis) 1.939 488 13.107
Continuing 746 194 9.136
Final (1 year before death) 1.143 265 13.147
Total 3.828 947 12.305
Phase of care Discharges Subjects* Average expenditure by
subject (€)Initial (1 year since diagnosis) 3.722 1.546 12.847
Continuing 1.527 559 10.336Final (1 year before death) 2.466 977 12.062
Total 7.715 3.082 12.143
Padua
Florence-Prato
Average expenditure (€) by phase of care during the period 2000-2006 for the 2000-2001 incident cases by type
of discharge, Padua
*every subject could contribute to more than one phase
0
2.000
4.000
6.000
8.000
10.000
12.000
Initial Continuing Final
€ Ordinary
DH
Average expenditure (€) by stage at diagnosis (Dukes),
Padua
Distribution of subjects
13,323
17,314
22,652
25,64523,303
14,062
0
5,000
10,000
15,000
20,000
25,000
30,000
A B C1 C2 D missing
17% 20% 18% 8% 22% 14%
Average expenditure (€) by phase of care and age class,
Padua
0
5000
10000
15000
20000
25000
29-49 50-59 60-69 70-79 80-95
Initial
Continuing
Final
Average expenditure (€) by stage and age class,
Padua
05,000
10,00015,00020,00025,00030,00035,000
Loca
l
Regi
onal
/Dis
tant
Loca
l
Regi
on/D
ista
nt
Loca
l
Regi
onal
/Dis
tant
Loca
l
Regi
onal
/Dis
tant
Loca
l
Regi
onal
/Dis
tant
29-49 50-59 60-69 70-79 80-95
Average expenditure (€) by phase, age class and stage,
Padua
0
5000
10000
15000
20000
25000
30000
35000
40000
local reg/dist local reg/dist local reg/dist local reg/dist local reg/dist
<49 50- 60- 70- 80+
INITIAL CONTINUING FINAL
Average expenditure (€) by type of DRG and type of discharges, Padua
0
2,000
4,000
6,000
8,000
10,000
12,000
chemotherapy surgery medical not chemo
ordinary discharges Day Hospital
n.a.
n=282n=567
n=15
n=344
n=208
Average expenditure (€) by phase and vital status, Padua
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
INITIAL PHASE CONTINUING PHASE
FINAL PHASE
Alive
Deceased
Open issues
Projections: implementation, validation
Scenarios: screening, primary prevention, population ageing
Uncertainty: how to estimate
Data collection: how to improve
Integration of other data sources (e.g. drugs, out-of-hospital care)