IRPPS Working Papers. The regional distribution of in-hospital fatality among Acute Myocardial Infarction events in Italy

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1 IRPPS Woking Papes Istituto di Riceche sulla Popolazione e le Politiche Sociali - CNR ISSN The egional distibution of in-hospital fatality among Acute Myocadial Infaction events in Italy Anna Gigli, Silvia Fancisci, Giuseppe Gesano, Pieto Folino-Gallo What is IRPPS? IRPPS is an Intedisciplinay Reseach Institute that conducts studies on demogaphic and migation issues, welfae systems and social policies, on policies egading science, technology and highe education, on the elations between science and society, as well as on the ceation of, access to and dissemination of knowledge and infomation technology. IRPPS WPs n. 9 (2005)

2 The egional distibution of in-hospital fatality among Acute Miocadial Infaction events in Italy Anna Gigli, Silvia Fancisci, Giuseppe Gesano, Pieto Folino-Gallo Abstact Aim of this pape is to investigate into the diffeences in the fist teatment of Acute Myocadial Infaction (AMI) among Italian egional health cae systems, by focusing on the egional distibution of in-hospital deaths. Stating fom the theoetical cae pathway (fom the onset of the illness to hospitalization and ecovey o possible death), the inhospital deaths in each egion ae decomposed into the contibutions of the attack ate, hospitalization and in-hospital fatality. The discepancies in egional behaviou ae investigated, in the aim to assess whethe they can be attibuted to diffeent pefomances among Italian egions. The study is based on two data souces: hospital dischages, based on Diagnosis Related Goups (DRG) and povided by the Ministy of Health; death and population data by egions of esidence, povided by the National Institute of Statistics. keywods: Acute Myocadial Infaction, Fatality ates, Attack ates, Hospitalization ates. Citazione consigliata: Gigli, Anna, Fancisci, Silvia, Gesano, Giuseppe, Folino-Gallo, Pieto. The egional distibution of in-hospital fatality among Acute Miocadial Infaction events in Italy. IRPPS Woking Papes, n. 9, Anna Gigli è icecatice pesso l Istituto di Riceche sulla Popolazione e le Politiche Sociali ( anna.gigli@ipps.cn.it). Silvia Fancisci è icecatice pessi l Istituto Supeioe di Sanità ( silvia.fancisci@iss.it). Giuseppe Gesano è associato pesso l Istituto di Riceche sulla Popolazione e le Politiche Sociali ( giuseppe.gesano@ipps.cn.it). Istituto di Riceche sulla Popolazione e le Politiche Sociali - CNR Via Palesto, Roma Istituto di Riceche sulla Popolazione e le Politiche Sociali 2005

3 1. Intoduction Among the coonay heat diseases, Acute Myocadial Infaction (AMI, ICD9: 410) is chaacteized by high fatality level associated with a fast couse of the disease. Consequently timeliness and appopiateness of the fist teatment ae fundamental fo a positive ecovey of the hospitalized patients. In Italy, Acute Myocadial Infaction is among the main causes of death in the esident population aged 45 and ove (ISTAT, 2002, 2004). Many evidences have demonstated that in Italy isk factos associated with the diffusion and seveity of AMI have a geogaphical connotation: Giampaoli and Vannuzzo (1999), Celentano et al. (1999), Giampaoli, Panico et al. (2001). On the othe hand the quality of fist cae teatments povided by the Italian National Health System should be homogeneously distibuted. Aim of this pape is to investigate into the possible diffeences among Italian egional health cae systems in the fist teatment of AMI, stating fom a theoetical cae pathway: fom the onset of the illness to hospitalization and ecovey o possible death (in o out of hospital). In paticula we investigate the geogaphical distibution of in-hospital fatality ate (defined as the atio between the numbe of AMI fatal cases occued in hospital and the total numbe of AMI hospitalizations) tying to assess whethe the obseved discepancies can be attibuted to diffeent egional pefomances. The study is based on two data souces: hospital dischages, based on Diagnosis Related Goups (DRG) and povided by the Ministy of Health; death and population data by egions of esidence, povided by the National Institute of Statistics. The pape is stuctued as follows: section 2 illustates the data main featues and defines the indicatos which will be used thoughout the pape; section 3 pesents the methods implemented to investigate the egional diffeences in the in-hospital fatality ate and to attibute the deviations of the in-hospital deaths fom the Italian aveage to diffeent components of the cae pathway (mobidity, hospitalization, fatality); section 4 illustates the main esults of the decomposition method; and finally section 5 is devoted to the discussion and futhe developments. 2. Mateials Diagam 1 descibes the pathway fom infaction to hospitalization to ecovey o death. It constitutes the fame of the decomposition method poposed in this pape. Diagam 1: Acute Myocadial Infaction pathway Population At-isk population P i =attack ate Infaction I h = hospitalization ate Hospitalization H f = in-hospital fatality ate Non-hospitalized death D 1-h Hospitalized death F Hospital dischage alive C The National Institute of Statistics povides the numbe of deaths due to myocadial infaction occued in Italy duing the yeas 1999 and 2000 and the coesponding Italian population at Januay 1 st Deaths and population data ae statified by sex, egion (egion of death and egion of esidence) and age goup. The age goups consideed fo the analysis ae: 45-64, 65-74, 3

4 75+ and 45+ yeas, being the numbe of myocadial infactions occuing in young women and men below age 45 negligible. The Ministy of Health supplies the numbe of hospital dischages (eithe dead o alive) with myocadial infaction diagnosis, which ae collected fo administative puposes by the hospitals though individual dischage cads and then sent to the Ministy of Health. These data ae based on Diagnosis Related Goups (DRG), a pospective payment system fo hospital cae. Patients hospitalized fo myocadial infaction can be assigned to thee diffeent DRGs: DRG 121 (AMI without cadiovascula complication, dischaged alive); DRG 122 (AMI with cadiovascula complication, dischaged alive); DRG 123 (AMI dischaged dead). Besides infomation on the DRG, the dischage cad contains vaiables at individual level concening demogaphic aspects (age, sex, esidence and maital status of the patient) and clinical aspects (length of hospital stay, diagnosis, theapy and vital status). Hospital dischages subdivided into dead and alive patients with myocadial infaction diagnosis efe to the yeas 1999 and 2000 and ae statified by sex, egion of hospitalization and age goup (the same age goups as fo deaths and population data). Hospital dischages ae collected fo administative puposes, and pesent some limitations when used in epidemiological studies. To this egad we make the following assumptions: a) due to the oganization of the hospital dischage database, the same event could be counted moe than once (multiple dischages). In ode to coect fo this bias, dischages of one day of length wee excluded fom the analysis; b) follow-up infomation is not included in ou data, theefoe we count deaths afte hospitalization as new cases; c) data on population efe to population esident in the egion, whilst data on hospitalizations and deaths efe to the population pesent in the egion; being AMI an acute illness we suppose that inteegional migation is negligible; d) in-hospital deaths collected by the Ministy of Health ae a subset of the total deaths collected by ISTAT, i.e. the epoting delay is negligible; e) thee ae no egional diffeences in the data collection and ecoding; f) silent events, intended as non-diagnosed non-sevee infactions, ae not elevant fo the evaluation of the quality and the timeliness of medical cae assistance, theefoe ae ignoed in ou analysis. The following indicatos ae paticulaly elevant to ou study: the population motality ate m is defined as the atio of the total deaths by infaction ove the elevant population; the attack ate i, is the atio between the infaction cases (obtained as the sum of the hospitalized cases dischaged alive and the total deaths) and the elevant population; the hospitalization ate h is the atio between the numbe of hospitalized cases and the infaction cases; the in-hospital fatality ate f descibes the motality among the hospitalized infaction cases, i.e. the atio between the deaths by infaction and the hospitalized cases. They can be computed as: m D P i C D P I P h C F C D I H f F F (1) C F H whee P is the elevant population (hee the Italian esidents aged 45+); D=F+D 1-h is the total numbe of deaths by infaction, which includes the deaths inside the hospitals (F), and those outside (D 1-h ); H is the numbe of hospitalizations by AMI. The numbe of infaction events I occued in a population in a time peiod is estimated as the sum of the total numbe of deaths by infaction D and the numbe of hospital dischages (alive) by infaction C. Table 1 povides the absolute figues and the age distibution of in-hospital deaths by infaction, deived fom the DRG system and total deaths by infaction, povided by the National Institute of Statistics. 4

5 Table 1: Age distibution of deaths by AMI in Italy by sex and age. Yeas Males Females age in-hospital (%) total (%) in-hospital (%) total (%) deaths deaths deaths deaths (13) 4675 (23) 174 (4) 991 (7) (27) 6212 (31) 665 (16) 2739 (19) (60) 9366 (46) 3372 (80) (74) (100) (100) 4211 (100) (100) Diffeent indicatos povide diffeent insights into the phenomenon: in the yeas evey 10,000 males of age 45 and ove (hee indicated as 45+) thee wee about 54 AMI events, of which 40 wee hospitalized, 4 died in hospital and 13 out of hospital; in the same peiod evey 10,000 women thee wee about 25 AMI events, of which 17 wee hospitalized, 3 died in hospital and 7 out of hospital. Tables 2 and 3 descibe in moe details the elevant egional ates, which ae standadized by age. Table 2: Age-adjusted attack (i) and motality (m) ates x 10,000 by sex and Italian egions. Yea ; age 45+ Males Females Italian egions i m i m Piemonte & Val d'aosta Lombadia Tentino Alto Adige Veneto Fiuli Venezia Giulia Liguia Emilia Romagna Toscana Umbia Mache Lazio Abuzzo Molise Campania Puglia Basilicata Calabia Sicilia Sadegna ITALIA

6 Table 3: Age-adjusted hospitalization (h) and in-hospital fatality (f) ates x 100 by sex and Italian egions. Yeas ; age 45+ Males Females Italian egions h f h f Piemonte & Val d'aosta Lombadia Tentino Alto Adige Veneto Fiuli Venezia Giulia Liguia Emilia Romagna Toscana Umbia Mache Lazio Abuzzo Molise Campania Puglia Basilicata Calabia Sicilia Sadegna ITALIA Looking at the egional distibution of these indicatos some inteesting featues ae appaent: among people of age 45+ (Table 2), as well as among people of age 75+ (Fig. 1 and 2) thee ae egional diffeences in motality and attack ates but no specific egional tends; on the othe hand the egional distibution of in-hospital fatality ates among people of age 45+ (Table 3) anges fom 5% in Sicilia to 12% in Tentino Alto Adige, Veneto, Liguia, Emilia Romagna and Lazio, among men; and fom 6% in Basilicata to 23% in Liguia, among women, evealing a South- Noth gadient. This patten equies futhe investigation. Fig. 1: Attack ate x 10,000 in Italian egions. Yeas ; age 75+ Males a (1) a (5) a (9) 84 a (5) Females 29.1 a 32.5 (2) 25.8 a 29.1 (6) 22.5 a 25.8 (6) 19.2 a 22.5 (6) 6

7 Fig. 2: Motality ate x 10,000 in Italian egions. Yeas ; age 75+ Males 75.8 a 86.2 (1) 65.3 a 75.8 (2) 54.9 a 65.3 (10) 44.4 a 54.9 (7) Females a (1) a (4) a (6) 8.53 a (9) 3. Methods We use hee a statistical method, the Statistical Pocess Contol (SPC), which was poposed in the 1930's by the physicist Walte A. Shewhat (1931), and much moe ecently adapted to healthcae evaluation. In Shewhat appoach vaiation is categoized accoding to the action needed to educe it: common-cause vaiation, which is intinsic to the pocess, and special-cause vaiation, which is the esult of factos extinsic to the pocess. To disciminate between the two souces of vaiation a simple gaphical method -the contol chat- is developed: the mean of the pocess is plotted togethe with the uppe and lowe contol limits; if the coesponding data point lies within the limits it is accepted, but if it falls outside the contol limits, a special-cause vaiation is suggested and futhe investigation is equied. The value poposed by Shewhat fo the contol limits is +/- 3, whee is a vaiability measue - an empiical adaptation of the lage sample Nomal appoximation. We assume that i) the efeence in-hospital fatality ate is the Italian one; ii) the egional inhospital deaths ae binomial outcomes with pobability f of ealization in H hospitalizations. Then fo each egion is: f 1 H f Figues 3a and 3b illustate the situation fo males and females, whee the vetical bas epesent the +/- 3 contol limits. We obseve that some Nothen and Cental egions (Tentino Alto Adige, Veneto, Liguia, Emilia Romagna and Lazio and also Lombadia fo men) ae above the uppe contol limit, while some Southen egions (Sicilia, Calabia, Campania and Puglia and also Basilicata fo women) ae below the lowe contol limit. 7

8 Fig. 3a: Regional distibution of in-hospital fatality (%). Yeas ; age 45+; Males egional in-hospital fatality Italian in-hospital fatality Piemonte & Val d'aosta Lombadia Tentino Alto Adige Veneto Fiuli Venezia Giulia Liguia Emilia Romagna Toscana Umbia Mache Lazio Abuzzo Molise Campania Puglia Basilicata Calabia Sicilia Sadegna Fig. 3b: Regional distibution of in-hospital fatality (%). Yeas ; age 45+; Females egional in-hospital fatality Italian in-hospital fatality Piemonte & Val d'aosta Lombadia Tentino Alto Adige Veneto Fiuli Venezia Giulia Liguia Emilia Romagna Toscana Umbia Mache Lazio Abuzzo Molise Campania Puglia Basilicata Calabia Sicilia Sadegna 8

9 This geogaphical tend could be elated to egional discepancies in the pocess of the disease occuence (fom isk factos exposue to in-hospital death). The pocess appoach illustated in Diagam 1 allows us to decompose the in-hospital deaths F into the poduct of thee conditional pobabilities: Infaction population PHospitaliz ation Infaction PInhospital. death hospitaliz ation F P P (2) By using the definitions (1) we apply (2) to egion and obtain a decomposition of the inhospital deaths F fo each Italian egion: F P i h f. In ode to obtain the standadized numbe of deaths by infaction in the hospitals of egion F, we substitute the egional ates with the coesponding aveage Italian ates: F P i h f. Thus, we ae able to compae the egional pefomances in tems of the deviation of the inhospital deaths in egion fom the coesponding standadized value: By setting F i F P h f i h f. (3) i i i h h h f f f (3) becomes: F i i h h f f i h f F P. (4) Afte developing the inne poducts, the deviation of the egional in-hospital deaths fom the coesponding standadized value decomposes into a seies of single and mixed contibutions, as shown in Table 4, wheeby single contibution means the contibution of a single egional gap in a specific ate (i.e. hospitalization ate) while the othe two ates (i.e. attack ate and in-hospital fatality ate) ae supposed equal to the Italian aveage; mixed contibution means the contibution of two o thee egional ates at the same time. 9

10 Table 4: Components of the egional deviations fom standadized in-hospital fatality Attack i h f Single Hospitalization In-hospital Fatality i h i h f f Attack & Hospitalization i h f Mixed Attack & In-hospital Fatality Hospitalization & In-hospital Fatality Attack & Hospitalization & In-hospital Fatality i h f i f h i h f Let us define F (h) F the deviation (due to hospitalization (DDH)) of the in-hospital deaths fom the standadized countepat, when the egional attack and in-hospital fatality ates ae supposed equal to the Italian ates. Equation (4) becomes: ( F F ) h) i f ( h h) ( i f h) P i f ( h ) ( P h. (5) We can similaly poceed fo the othe two: deviation due to in-hospital fatality (DDF) F. as F F ( f ) and deviation due to attack (DDI) as F (i) 4. Results Fig. 4a and fig 4b illustate, sepaately fo men and women, how the diffeence between obseved and expected in-hospital deaths in egion decomposes into the contibutions due to attack, hospitalization and in-hospital fatality ates (hee expected is used with the same meaning as standadized). The thee bas epesent the % contibution of each deviation, obtained as: F F i 100 % DDI F F F h 100 % DDH F F F f 100 % DDF F The numbes nea the egion names epesent the total diffeence as obtained in (4). The % contibutions can eithe be positive, if the egional ate is highe than the standadized one, o negative, vice vesa. When the thee contibutions have the same sign the effects add up, and einfoce each othe. When thei signs ae diffeent the effects may cancel out, and the combined contibution becomes moe difficult to evaluate. 10

11 In Nothen and Cental egions thee is an excess of obseved in-hospital deaths compaed to the expected values, while in Southen egions the obseved in-hospital deaths ae fewe than the expected ones; the only exception being Piemonte & Valle d Aosta, which behave like the Southen egions. A close look to the egions, which wee found out of statistical pocess contol, as highlighted in Fig.3a and 3b, eveals some common pattens and some exceptions. In paticula in most of the Nothen egions of inteest (Tentino Alto Adige, Veneto, Liguia, Emilia Romagna) the excess of obseved in-hospital deaths is a combination of excess due to attack ate, hospitalization and in-hospital fatality: moe people ae ill, moe people go to hospital, moe people die in hospital (and also outside). In Lombadia (males) and Lazio (both sexes) the excess of inhospital deaths is due to an excess of in-hospital fatality only, while the othe two components give a null o negative contibution: in spite of a lowe numbe of people who become ill, and a lowe numbe who ae hospitalized, moe people die in hospital (and also outside). In most of the Southen egions of inteest (Puglia and Calabia both sexes, Basilicata and Sicilia females) thee is an oveall lack of obseved in-hospital deaths, which is a combination of a lack due to attack ate, hospitalization and in-hospital fatality: less people become ill, less people ae hospitalized, less people die in hospital (and also outside). Exceptions ae Campania and Sicilia (males), whee the lack of obseved in-hospital deaths is a combination of negative contibutions due to fatality and hospitalization and positive contibution due to attack ate: although moe people become ill and die, less people ae hospitalized and die in hospital. Fig. 4a: Decomposition of diffeence between obseved and expected in-hospital deaths. Yeas ; age 45+; Males % Piemonte & Val d'aosta --13 Lombadia +4 Tentino Alto Adige +37 Veneto +22 Fiuli Venezia Giulia - Liguia +35 Emilia Romagna +34 Toscana +4 Umbia +7 Mache +7 Lazio +25 Abuzzo +7 Molise --31 Campania --34 Puglia --53 Basilicata --54 Calabia --34 Sicilia --51 Sadegna in-hospital fatality hospitalization attack 11

12 Fig. 4b: Decomposition of diffeence between obseved and expected in-hospital deaths. Yeas ; age 45+; Females % Piemonte & Val d'aosta --14 Lombadia +3 Tentino Alto Adige +56 Veneto +26 Fiuli Venezia Giulia +18 Liguia +33 Emilia Romagna +34 Toscana +9 Umbia +10 Mache +10 Lazio +16 Abuzzo --4 Molise --30 Campania --41 Puglia --51 Basilicata --79 Calabia --43 Sicilia --62 Sadegna --22 in-hospital fatality hospitalization attack 5. Discussion Seveal epidemiological studies have been conducted in the wold involving patients with AMI: the lagest and most elevant being the MONICA (Monitoing Tends and Deteminants in Cadiovascula Disease) Poject: data wee poduced fom acoss the wold with the scope of assessing the contibution of incidence, case fatality, tends in isk factos and advancement in coonay cae towads the decline of motality, which has been appaent since the late 70's. (Tunstall-Pedoe et al., 1999). Othe lage studies include OASIS (Yusuf et al., 1998), the ENACT study (Fox et al., 2000), and the GRACE egisty (Fox, 2000). Moe ecently an attempt to define monitoing indicatos and standadized methods fo futue data collection in the Euopean Union has been established by the EUROCISS poject (2003). In Italy most epidemiological studies aim at investigating the causes and educing the isk factos elated to cadiovascula diseases: see, fo example, Giampaoli and Vannuzzo (1999), Giampaoli, Panico et al. (2001); othe woks use the findings of the MONICA poject to estimate the incidence and pevalence of majo coonay events, including IMA: Feaio et al. (2001), Giampaoli, Palmiei et al. (2001). A poject aimed at establishing a national suveillance system fo acute coonay and ceebovascula events was initiated at the end of the 90's and the fist esults wee available in the Italian Atlas of Cadiovascula Diseases: Giampaoli and Vannuzzo (2003), Giampaoli, Vannuzzo, et al. (2004); the Atlas contains estimates of fatal and nonfatal coonay events in 7 aeas of the county, suveying about 4.5 million people fo the yeas 1998 and Ou contibution is aimed at poviding a tool fo the evaluation of possible egional diffeences in Italy in the quality of cae fo AMI patients, by using infomation on in-hospital fatality. We found a South-Noth tend in the in-hospital fatality ates and tied to identify those egions out of contol in tems of the Statistical Pocess Contol (SPC) - a method that has eceived inceasing inteest in the healthcae community and is used to help impove clinical and 12

13 administative pocesses (Caey, 2003), to measue the vaiability of a pocess ove time (Shahian et al., 1996), to compae pefomances, such as motality ates, among diffeent hospitals (Mohammed et al., 2001). Futhemoe we tied to undestand the causes fo the diffeent egional pefomances by looking at the entie cae pathway fom infaction to death (in o out of hospital) o ecovey and poposed a method to attibute the in-hospital deaths to diffeent causes: attack, hospitalization o in-hospital fatality ates. Diffeent conditions influence the suvival and ecovey of an AMI patient: the seveity and suddenness of the event, whee and when the heat attack occus, the availability of assistance facilities neaby, the time lag between medical intevention and tanspotation to the hospital, and the pompt and coect outing at the hospital acceptance. Some of these factos have been estimated diectly (hospitalization and attack ate), othes have been neglected (seveity of the illness and pomptness of the intevention) because ou data did not contain the elevant infomation (fo example on isk factos). Theefoe in dawing conclusions one must be cautious about vaious confounding factos, fist of all the seveity of the disease. The use of DRG data in epidemiology has its advantages and disadvantages: administative data ae eadily available, inexpensive to acquie, compute eadable and typically encompass lage populations (Iezzoni, 1997); on the othe hand the DRG system can be pone to oppotunistic featues aimed to incease the eimbusement level of the hospital and this may cause incompleteness and inaccuacy of the data and misclassification of diagnoses (Mahonen et al., 2000). Beaing these limits in mind, we have attained some geneal conclusions: in those Nothen and Cental egions whee the obseved in-hospital fatality is out of the uppe contol limit, the decomposition suggests a moe fequent and sevee illness, geneally accompanied by a highe availability of hospitals. Exceptions ae Lombadia and Lazio, whee the combination of excess of in-hospital deaths and lack of infaction events and hospitalizations seems to suggest some inefficiencies in the hospital system. In most Southen egions whee the numbe of in-hospital deaths is out of the lowe contol limit, the decomposition confims a less fequent and less sevee illness. Exceptions ae Campania and Sicilia whee, in spite of highe incidence and motality ates, fewe people each the hospital and fewe die in hospital, thus suggesting a selection of cases: only the less sevee ones each the hospital and then ecove, the othes die befoe eaching the hospital. Fom the gende pespective the situation of the women is fa wose: the in-hospital fatality is moe than double that of the men. This esult is consistent with the findings of seveal studies: in geneal males and females have diffeent natual histoies egading AMI, the female's being a moe aggessive fom with a high motality ate: Pimenta et al. (2001), Tofle et al. (1987), Geenland et al. (1991). An inteesting development of this wok is the study of the coelation between in-hospital deaths and the distibution of emegency cae depatments, such as Coonay Cae Units (CCU) and fist cae ambulances. The moe eliable data egading CCU efe to a suvey caied out in the yea 2000 among the Italian hospitals (Fedeazione Italiana di Cadiologia, 2003) about the availability of emegency stuctues. Howeve the data efe to the availability of beds and not to thei effective use and would allow only a ough compaison: moe detailed infomation on thei actual use and thei geogaphical location (taking into account also the mophological diffeences in the teitoy) ae needed in ode to gathe a wide and bette pictue. Moeove, the availability of the geogaphical distibution of the main isk factos, as a poxy of the seveity of the disease, would allow us to bette identify the influence of the quality of cae on the outcome of the disease. Acknowledgements The authos would like to thank Simona Giampaoli fo a vey useful discussion about the Italian situation and Tom Mashall fo suggestions egading the Statistical Pocess Contol method. Silvia Buzzone of ISTAT and Lucia Lispi of the Ministy of Health kindly supplied the data. 13

14 Refeences Capewell S, MacIntye K, Stewat S, Chalme JWT, Boyd J, Finlayson A, Redpath A, Pell JP, McMuay JJV, 2001: Age, sex, and social tends in out-of-hospital cadiac deaths in Scotland : a etospective cohot study. The Lancet, 358, Caey RG, 2003: Impoving healthcae with contol chats. ASQ, Milwaukee. Celentano E, Palmiei L, Galasso R, Poce A, Panico S, Giampaoli S, 1999: Rischio cadiovascolae e classi sociali: confonto ta popolazioni femminili adulte abitanti aee uali e ubane. Gionale Italiano di Cadiologia, 29, EUROCISS poject, 2003, in euopa.eu.int/comm/health/ph_pojects/2000/monitoing/fp_monitoing_2000_fep_10_en.pdf Fedeazione Italiana di Cadiologia, 2003: Censimento delle stuttue cadiologiche in Italia, Italian Heat Jounal, 4, 3S-75S. Feaio M, Cesana G, Vanuzzo D, Pilotto L, Sega R, Chiodini P, Giampaoli S, 2001: Suveillance of ischaemic heat disease: esults fom the Italian MONICA populations. Intenational Jounal of Epidemiology, 30, S23-S29. Fox K, 2000: An intoduction to the Global Registy of Acute Coonay Events: GRACE. Euopean Heat Jounal, 2, F21-F24. Fox K, Cokkinos D, Deckes J, Keil U, Maggioni A, Steg G, 2000: The ENACT study: a pan- Euopean suvey of acute coonay syndomes. Euopean Netwok fo Acute Coonay Teatment. Euopean Heat Jounal, 21, Giampaoli S, Palmiei L, Capocaccia R, Pilotto L, Vanuzzo D, 2001: Estimating populationbased incidence and pevalence of majo coonay events. Intenational Jounal of Epidemiology, 30, S5-S10. Giampaoli S, Panico S, Palmiei L, Magini N, Feaio M, Pede S, Vannuzzo D, 2001: L identificazione degli individui ad elevato ischio coonaio nella popolazione italiana: indicazioni dall Ossevatoio Epidemiologico Cadiovascolae. Italian Heat Jounal, 2, Giampaoli S, Vanuzzo D, 1999: I fattoi di ischio cadiovascolae in Italia: una lettua in ifeimento al Piano Sanitaio Nazionale Gionale Italiano di Cadiologia, 29, Giampaoli S, Vannuzzo D (eds), 2003: Italian Atlas of Cadiovascula Diseases. Italian Heat Jounal, 4 (Suppl 4), 9S-121S. Giampaoli S, Vannuzzo D, Feaio M, Vanchei F, Cesana G, 2004: The National Registe of Coonay and Ceebovascula Events. Italian Heat Jounal, 5 (Suppl 3), 22S-37S. Geenland P, Reiche-Reiss H, Goldbout U, Beha S, 1991: In-hospital and 1-yea motality in 1,524 women afte myocadial infaction. Compaison with 4,315 men. Ciculation, 83,

15 Iezzoni LI, 1997: Assessing Qualità Using Administative Data. Annals of Intenal Medicine, 127, Istat, 2002: Cause di mote. Anno Annuai ISTAT, Roma. Istat, 2004: Cause di mote. Anno Annuai ISTAT, Roma. Mähonen M, Salomaa V, Keskimäki I, Moltchanov V, 2000: The feasibility of outine motality and mobidity egiste data linkage to study the occuence of acute coonay heat disease events in Finland. Euopean Jounal of Epidemiology, 16, Mohammed MA, Cheng KK, Rouse A, Mashall T, 2001: Bistol, Shipman, and clinical govenance: Shewhat's fogotten lessons. The Lancet, 357, Pimenta L, Bassan R, Potsch A, Soaes JF, Manes Albanesi Filho F, 2001: Is Female Sex an Independent Pedicto of In-Hospital Motality in Acute Myocadial Infaction? Achives of Bazilian Cadiology, 77, Shahian DM, Williamsom WA, Svensson LG, Restuccia JD, D'Agostino RS, 1996: Application of statistical quality contol to cadiac sugey. Annals of Thoacis Sugey; 62, Shewhat WA, 1931: Economic contol of quality of manufactued poduct. D. Van Nostand Company, Pinceton. (Repinted by ASQC Quality Pess, 1980). Toffle GH, Stone PH, Mulle JE, Willich SN, Davis VG, Poole K, et al. Effects of gende and ace on pognosis afte myocadial infaction: advese pognosis fo women, paticulaly black women. J Am Coll Cadiol. 1987; 9: Tunstall-Pedoe H, Kuulasmaa K, Mähonen M, Tolonen H, Ruokokoski E, Amouyel P, 1999: Contibution to tends in suvival and coonay y-event ates to changes in coonay heat disease motality: 10-yea esults fom 37 MONICA Poject populations. The Lancet, 353, Yusuf S, Flathe M, Pogue J, Hunt D, Vaigos J, Piegas L, Avezum A, Andeson J, Keltai M, Budaj A, Fox K, Ceemuzynski L, 1998: Vaiations between counties in invasive cadiac pocedues and outcomes in patients with suspected unstable angina o myocadial infaction without initial ST elevation. The Lancet, 352,