Aim of the project. costs/expenditure, output, productivity, health outcomes, 1 The main aim of this project is to provide a quantitative analysis on:

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2 Aim of the project 1 The main aim of this project is to provide a quantitative analysis on: costs/expenditure, output, productivity, health outcomes, of the Italian health care system based on patient level data by means of a microsimulation model using data collected by individual Italian GPs.

3 The Health Search database in figures patients in the DB; diagnoses/problems; lab tests and diagnostic tests; blood pressure measurements; drug prescriptions. 6 Data available from year 2000 in form of an unbalanced panel

4 Health Search DB: Quality of the data Accuracy: % of coded diagnoses, % of prescriptions linked to diagnoses Completeness: % of data on prevention (i.e. smoking, BMI, cholesterol, Blood Pressure) Frequency of recording: N recorded daily visits visits standardized by No. of total patients

5 Health Search DB: National representativeness - 1 The distribution of patients by age in HSD is very close to the distribution by age recorded by ISTAT (ONS)

6 Health Search DB: National representativeness - 2 Prevalence of chronic pathologies: HSD vs ISTAT (HIS)

7 Health Search DB: National representativeness - 3 DDD/1000 habitant die per each therapeutic group over total DDD/1000 habitant die: HEALTH SEARCH vs OsMed.

8 Prices and Tariffs 1 We have completed the raw information included in the HS dataset with the following data: Drug prices; Lab and diagnostic test tariffs (at regional level); Hospital DRG tariffs (at regional level); GP salary.

9 SiSSI - Italian Simulation Model of Health Expenditure Building up the model 1 Phase 1 - Static model Static analysis of outcomes, output, costs and utilization in the NHS; Total costs (by region, patient, GP, pathology, etc.); Benchmarking across regions, GPs, patients, etc.; Analysis of alternative health policies ("what if"). 2 Phase 2 - Dynamic model Analysis of chronic diseases and the effect that medical treatments have on them; Analysis of health expenditure in the medium-long run; Analysis of financial sustainability of the system.

10 The expected results of the model 1 As all our information are at patient level and over time, we can construct: Price and Quantity Indices; Cost of Treatment Indices; Health Outcomes Indices; Cost-Effectiveness Indices ( health/ inputs) Treatment effect (on treated) indices. 2 All these measures can be produced by good and services, groups of patients, GPs, gender, age, region, disease,...and any possible combination of all characteristics we have in the dataset. 3 Unfortunately we cannot observe patients income and education. However we do have information regarding income exemption status.

11 SiSSI model: Preliminary results - 1 Structure of output

12 SiSSI model: Preliminary results - 2 Total cost of treatment (drugs and diagnostic tests), by gender

13 SiSSI model: Preliminary results - 3 Total cost of treatment (drugs and diagnostic tests), by gender with Confidence Intervals- 2008

14 SiSSI model: Preliminary results - 4 Total cost of treatment (drugs and diagnostic tests), by geographic area

15 SiSSI model: Preliminary results - 5 Total cost of treatment (drugs and diagnostic tests), by geographic area with Confidence Intervals- 2008

16 SiSSI model: Preliminary results - 6 Total cost of treatment (drugs and diagnostic tests), by year

17 SiSSI model: Preliminary results - 7 Total cost of treatment (drugs and diagnostic tests), by year with Confidence Intervals

18 SiSSI model: Preliminary results - 8 Average drug price and ddd price by quarter and year

19 SiSSI model: Preliminary results - 9 Average diagnostic test price by quarter and year

20 SiSSI model: Preliminary results - 10 Average drug prescriptions (ddd) by quarter and year

21 SiSSI model: Preliminary results - 11 Average diagnostic test prescriptions by quarter and year

22 SiSSI model: Preliminary results - 12 Price and Quantity Indices In order to compare over time drug and diagnostic test prescriptions and prices, we used several types of indices, such as Laspeyres price and quantity indices (fixed-base and fixed-weight): P0,t L = n p i,t i=1 p p i,0 i,0 q i,0 n i=1 p i,0 q i,0 Q0,t L = n q i,t i=1 q p i,0 i,0 q i,0 n i=1 p i,0 q i,0 Paasche price and quantity indices (fixed-base and variable-weight): P0,t P = n i=1 p i,t q i,t n p i,t q i,t i=1 p i,t /p i,0 Q0,t P = n i=1 p i,t q i,t n p i,t q i,t i=1 q i,t /q i,0 and Fisher price and quantity indices, the geometric mean of Laspeyres and Paasche indices. Furthermore, we used the following synthetic indices (a cost index and a quantity index): I C 0,t = n i=1 p i,t q i,t n i=1 p i,0 q i,t I Q 0,t = n i=1 q i,t n i=1 q i,0

23 SiSSI model: Preliminary results - 13 With the aim of approximating the impact of technological progress, we produced the following three indices: 1) A cost index with fixed-basket and fixed-quantities. I C1 0,t = n i=1 p i,t q i,0 n i=1 p i,0q i,0 2) A cost index with fixed-basket and variable-quantities. I C2 0,t = n i=1 p i,t q i,t n i=1 p i,0q i,0 3) A cost index with variable-basket and variable-quantities. I C3 0,t = n i=1 p i,t Q i,t n i=1 p i,0q i,0

24 SiSSI model: Preliminary results - 14 Cost indices for drugs and diagnostic tests and their subcategories INDICI DI COSTO Farmaci Farmaci: A* Farmaci: B* Farmaci: C* Farmaci: D* Farmaci: G* Farmaci: H* Farmaci: J* Farmaci: L* Farmaci: M* Farmaci: N* Farmaci: P* Farmaci: R* Farmaci: S* Farmaci: V* Farmaci: Statine (ATC=C10AA) Farmaci: Fans (ATC=M01A) Test Test: Nord-Occidente Test: Nord-Oriente Test: Centro Test: Sud Test: Isole Test: Ferritina Test: Colesterolo LDL Test: Creatinina Colesterolo Diabete *A: Tratto alimentare e metabolismo B: Sangue e organi eritropoietici C: Apparato cardiovascolare D: Farmaci dermatologici G: Apparato genito-urinario e ormoni sessuali H: Preparazioni ormonali sistemiche, esclusi ormoni sessuali e insulina J: Anti-infettivi per uso sistemico L: Antineoplastici e immunomodulatori M: Apparato muscolo-scheletrico N: Sistema nervoso P: Prodotti antiparassitari, insetticidi e repellenti R: Apparato respiratorio S: Organi sensori V: Vari

25 SiSSI model: Preliminary results - 15 Quantity indices for drugs and diagnostic tests and their subcategories INDICI DI QUANTITA Farmaci Farmaci: A* Farmaci: B* Farmaci: C* Farmaci: D* Farmaci: G* Farmaci: H* Farmaci: J* Farmaci: L* Farmaci: M* Farmaci: N* Farmaci: P* Farmaci: R* Farmaci: S* Farmaci: V* Farmaci: Statine (ATC=C10AA) Farmaci: Fans (ATC=M01A) Test Test: Nord-Occidente Test: Nord-Oriente Test: Centro Test: Sud Test: Isole Test: Ferritina Test: Colesterolo LDL Test: Creatinina *A: Tratto alimentare e metabolismo B: Sangue e organi eritropoietici C: Apparato cardiovascolare D: Farmaci dermatologici G: Apparato genito-urinario e ormoni sessuali H: Preparazioni ormonali sistemiche, esclusi ormoni sessuali e insulina J: Anti-infettivi per uso sistemico L: Antineoplastici e immunomodulatori M: Apparato muscolo-scheletrico N: Sistema nervoso P: Prodotti antiparassitari, insetticidi e repellenti R: Apparato respiratorio S: Organi sensori V: Vari

26 SiSSI model: Preliminary results - 16 Cost indices: Statins

27 SiSSI model: Preliminary results - 17 Cost indices: FANS

28 SiSSI model: Preliminary results - 18 Analysis by Disease: Hypercholesterolemia and Diabetes

29 SiSSI model: Preliminary results - 19 Total cost of treatment for patient with Hypercholesterolemia (including all comorbidities), by gender

30 SiSSI model: Preliminary results - 20 Total cost of treatment for patient with Hypercholesterolemia (including all comorbidities), by gender and cohort size

31 SiSSI model: Preliminary results - 21 Total cost of treatment for patient with Hypercholesterolemia (including all comorbidities), by cohort size and year

32 SiSSI model: Preliminary results - 22 Total cost of Hypercholesterolemia treatment, for pathology and comorbidities

33 SiSSI model: Preliminary results - 23 Total cost of Hypercholesterolemia treatment, for pathology and comorbidities with Confidence Intervals- 2008

34 SiSSI model: Preliminary results - 24 Total cost of treatment for patient with Hypercholesterolemia (including all comorbidities), by geographic area

35 SiSSI model: Preliminary results - 25 Total cost of treatment for patient with Hypercholesterolemia (including all comorbidities), by geographic area - Average

36 SiSSI model: Preliminary results - 26 Total cost of treatment for patient with Hypercholesterolemia (including all comorbidities), by year

37 SiSSI model: Preliminary results - 27 Total cost of treatment for patient with Hypercholesterolemia (including all comorbidities), by year with Confidence Intervals

38 SiSSI model: Preliminary results - 28 Total cost of treatment for patient with Diabetes (including all comorbidities), by gender

39 SiSSI model: Preliminary results - 29 Total cost of treatment for patient with Diabetes (including all comorbidities), by gender and cohort size

40 SiSSI model: Preliminary results - 30 Total cost of treatment for patient with Diabetes (including all comorbidities), by cohort size and year

41 SiSSI model: Preliminary results - 31 Total cost of Diabetes treatment, for pathology and comorbidities

42 SiSSI model: Preliminary results - 32 Total cost of Diabetes treatment, for pathology and comorbidities with Confidence Intervals- 2008

43 SiSSI model: Preliminary results - 33 Total cost of treatment for patient with Diabetes (including all comorbidities), by geographic area

44 SiSSI model: Preliminary results - 34 Total cost of treatment for patient with Diabetes (including all comorbidities), by geographic area - Average

45 SiSSI model: Preliminary results - 35 Total cost of treatment for patient with Diabetes (including all comorbidities), by year

46 SiSSI model: Preliminary results - 36 Total cost of treatment for patient with Diabetes (including all comorbidities), by year with Confidence Intervals

47 SiSSI model: Preliminary results - 37 Delay in disease occurrences

48 SiSSI model: Preliminary results - 38 Number of patients by age and year - Arthrosis

49 SiSSI model: Preliminary results - 39 Number of patients by age and year - Arthritis

50 SiSSI model: Preliminary results - 40 Number of patients by age and year - Hypercholesterolemia

51 SiSSI model: Preliminary results - 41 Number of patients by age and year - Diabetes

52 SiSSI model: Preliminary results - 42 Distributional aspects of treatment costs Skewness is substantial Is the average so informative?

53 SiSSI model: Preliminary results - 43 Treatment cost by quantile and age - Arthrosis

54 SiSSI model: Preliminary results - 44 Treatment cost by quantile and age - Arthritis

55 SiSSI model: Preliminary results - 45 Treatment cost by quantile and age - Asthma

56 SiSSI model: Preliminary results - 46 Treatment cost by quantile and age - Hypercholesterolemia

57 SiSSI model: Preliminary results - 47 Treatment cost by quantile and age - Diabetes

58 SiSSI model: Preliminary results - 48 VERY, VERY PRELIMINARY RESULTS!!!!

59 SiSSI model: Preliminary results - 49 Drug treatment and diagnostic test costs by age, gender and region Regione Femmine Maschi Abruzzo Basilicata Calabria Campania Emilia-Romagna Friuli-Venezia Giulia Lazio Liguria Lombardia Marche Piemonte Puglia Sardegna Sicilia Toscana Trentino-Alto Adige Umbria Veneto

60 SiSSI model: Preliminary results - 50 Drug treatment and diagnostic test costs by gender and region

61 SiSSI model: Preliminary results - 51 Drug treatment and diagnostic test costs by age, gender and type of region Regione Femmine Maschi Piano di rientro Con piano di rientro Senza piano di rientro Piano di rientro (escluse Sardegna e Liguria) Con piano di rientro Senza piano di rientro

62 SiSSI model: Preliminary results - 52 An example of health outcome index: Trends of Total and LDL Cholesterol by year

63 SiSSI model: Preliminary results - 53 An example of health outcome index: Trends of LDL Cholesterol by geographic area

64 SiSSI model: Preliminary results - 54 An example of health outcome index: Distribution of LDL Cholesterol by year

65 Conclusions and future agenda 1 HS represents an important source of information for output and productivity analysis as it is based on GP and patient microdata. 2 The potential number of GPs enrolled in this project can be easily extended to more than 5.000! This will imply extending our sample to more than 14 millions of patients! 3 More important, the quality, richness and completeness of the information collected could be easily improved over time. 4 The agenda for the future: Include information on non-treated patients Construct weights for inference to the whole population