Search

Purpose: There are some methodological concerns regarding results from observational studies about the effectiveness of evidence-based (EB) drug therapy in secondary prevention after myocardial infarction. The present study used a nested case–control approach to address these major methodological limitations., Methods: A cohort of 6880 patients discharged from hospital after acute myocardial infarction (AMI) in 2006–2007 was enrolled and followed-up throughout 2009. Exposure was defined as adherence to each drug in terms of the proportion of days covered (cutoff ≥ 75%). Composite treatment groups, that is, groups with no EB therapy or therapy with one, two, three, or four EB drugs), were analyzed. Outcomes were overall mortality and reinfarction. Nested case–control studies were performed for both outcomes, matching four controls to every case (841 deaths, 778 reinfarctions) by gender, age, and individual follow-up. The association between exposure to EB drug therapy and outcomes was analyzed using conditional logistic regression, adjusting for revascularization procedures, comorbidities, duration of index admission, and use of the study drugs prior to admission., Results: Mortality and reinfarction risk decreased with the use of an increasing number of EB drugs. Combinations of two or more EB drugs were associated with a significant protective effect (p < 0.001) versus no EB drugs (mortality: 4 EB drugs: ORadj = 0.35; 95%CI: 0.21–0.59; reinfarction: 4 EB drugs: ORadj = 0.23; 95%CI: 0.15–0.37)., Conclusions: These findings of the beneficial effects of EB polytherapy on mortality and morbidity in a population-based setting using a nested case–control approach strengthen existing evidence from observational studies.

Background: Improving quality and effectiveness of health care is one of the priorities of health policies. Hospital or physician volume represents a measurable variable with a relevant impact on effectiveness of health care. A recent Italian law, the "spending review", calls for the definition of "qualitative, structural, technological and quantitative standards of hospital care". There is a need for an accurate evaluation of the available scientific evidence in order to identify these standards, including the volume of care above or below which the public and private hospitals may be accredited (or not) to provide specific health care interventions. Since 2009, the National Outcomes Programme evaluates outcomes of care of the Italian hospitals; nowadays it represents an official tool to assess the National Health System (NHS). In addition to outcome indicators, the last edition of the Programme (2013) includes a set of volume indicators for the conditions with available evidence of an association between volume and outcome. The assessment of factors, such as volume, that may affect the outcomes of care is one of its objectives., Objectives: To identify clinical conditions or interventions for which an association between volume and outcome has been investigated. To identify clinical conditions or interventions for which an association between volume and outcome has been proved. To analyse the distribution of Italian health providers by volume of activity. To measure the association between volume of care and outcomes of the health providers of the Italian NHS., Methods: Systematic review. An overview of systematic reviews and Health Technology Assessment (HTA) reports performed searching electronic databases (PubMed, EMBASE, Cochrane Library), websites of HTA Agencies, National Guideline Clearinghouse up to February 2012. Studies were evaluated for inclusion by two researchers independently; the quality assessment of included reviews was performed using the AMSTAR checklist. For each health condition and for each outcome considered, total number of studies, participants, high volume cut-off values (range, average and median) have been reported, where presented. Number of studies (and participants) with statistically significant positive association and metanalysis performed were also reported, if available. Analysis of the distribution of Italian hospitals by volume of activity and the association between volume of activity and outcomes. Outcomes National Programme 2011 The analyses were performed using the Hospital Information System and the National Tax Register pertaining the year 2011. For each condition, the number of hospitals by volume of activity was calculated. Hospitals with a volume of activity lower than 3-5 cases/year for the condition under study were excluded from the analysis. For conditions with more than 1,500 cases per year and frequency of outcome ≥ 3%, the association between volume of care and outcome was analysed. For these conditions, risk-adjusted outcomes were estimated according to the selection criteria and the statistical methodology of the National Outcome Programme., Results: The systematic reviews identified were 107, of which 47, evaluating 38 clinical areas, were included. Many outcomes were assessed according to the clinical condition/procedure considered. The main outcome common to all clinical condition/procedures was intrahospital/30-day mortality. Health topics were classified in the following groups according to this outcome: Positive association: a statistically significant positive association was demonstrated in the majority of studies/participants and/or a pooled measure (metanalysis) with positive results was reported. Lack of association: no association was demonstrated in the majority of studies/participants and/or no metanalysis with positive results was reported. No sufficient evidence of association: both results of single studies and metanalysis do not allow to draw firm conclusions on the association between volume and outcome. Evidence of a positive association between volumes and intrahospital/ 30-day mortality was demonstrated for 26 clinical areas: AIDS, abdominal aortic aneurysm (ruptured and unruptured), coronary angioplasty, myocardial infarction, knee arthroplasty, coronary artery bypass, cancer surgery (breast, lung, colon, colon rectum, kidney, liver, stomach, bladder, oesophagus, pancreas, prostate); cholecystectomy, brain aneurysm, carotid endarterectomy, hip fracture, lower extremity bypass surgery, subarachnoid haemorrhage, neonatal intensive care, paediatric heart surgery. For 2 clinical conditions (hip arthroplasty and rectal cancer surgery) no association has been reported. Due to a lack of evidence, it was not possible to draw firm conclusion for 10 clinical areas (appendectomy, colectomy, aortofemoral bypass, testicle cancer surgery, cardiac catheterization, trauma, hysterectomy, inguinal hernia, paediatric oncology). The relationship between volume of clinician and outcomes has been assessed only through the literature review; to date, it is not possible to analyse this association for Italian health providers hospitals, since information on the clinician/surgeon on the hospital discharge chart is missing. The literature found a positive association for: AIDS, coronary angioplasty, unruptured abdominal aortic aneurysm, hip arthroplasty, coronary artery bypass, cancer surgery (colon, stomach, bladder, breast, oesophagus), lower extremity bypass surgery. The analysis of the distribution of Italian hospitals per volume of activity concerned the 26 conditions for which the systematic review has shown a positive association between volume of activity and intrahospital/30-day mortality. For the following conditions it was possible to conduct the analysis of the association between volume and outcome of treatment using national data: unruptured abdominal aortic aneurysm, coronary angioplasty, knee arthroplasty, coronary artery bypass, cancer surgery (colon, pancreas, lung, prostate, stomach, bladder), laparoscopic cholecystectomy, endarterectomy, hip fracture and acute myocardial infarction. For them, the association between volume and outcome of care has been observed. The shape of the relationship is variable among different conditions, with heterogeneous "slope" of the curves. DISCUSSION For many conditions, the systematic review of the literature has shown a strong evidence of association between higher volumes and better outcomes. Due to the difficulty to test such an association in randomized controlled studies, the studies included in the reviews were mainly observational studies: however, the quality of the available evidence can be considered good both for the consistency of the results between the studies and for the strength of the association. Where national data had sufficient statistical power, this association has been observed by the empirical analysis conducted on the health providers of the NHS in 2011. Analysing national data, potential confounders, including age and the presence of comorbidities in the admission under study and in the admissions of the two previous years, have been considered. The systematic review of the literature does not permit to identify predefined volume thresholds. The analysis of national data shows a strong improvement in outcomes in the first part of the curve (from very low volumes to higher volumes) for the majority of the studied conditions. In some cases the improvement in outcomes remains gradual or constant with the increasing volume of care, in other the analysis could allow the identification of threshold values beyond which the outcome does not improve further. However, a good knowledge of the relationship between effectiveness of treatments and their costs, the geographical distribution and the accessibility to health care services are necessary to choose the minimum volumes of care, under which specific health procedures in the NHS should not be provided. Some potential biases due to the use of information systems data should also be taken into account. In particular, it is necessary to consider possible selection bias due to the different way of coding among hospitals that could lead to a different selection of cases for some conditions (e.g. acute myocardial infarction), less likely to occur in the selection of cases for oncologic, orthopaedic, vascular, abdominal, and cardiac surgery. Regarding the definition of the exposure (volume of care), a possible bias could result from misclassification of health providers with high volume of activity. In fact, performing the intervention in different departments/units of the same hospital would result in an overestimation of the volume of care measured for hospital rather than for department/unit. A similar bias could occur if the main determinant of the outcome of treatment was the case load of each surgeon: the results of the analysis may be biased when the same procedure was carried out by different operators in the same hospital/unit. In any case, the observed association between volumes of care and outcome is very strong, and it is unlikely to be attributable to biases of the study design. However, the foreseen bias is likely to be non-differential, and, therefore, it would eventually lead to an underestimation of the true association between volume of care and outcome. Health systems operate, by definition, in a context of limited resources, especially when societies and governments choose to reduce the amount of resources to allocate to the health system. In such conditions, the rationalisation of the organization of health services based on the volume of care may make resources available to improve the effectiveness of interventions. The identification and certification of services and provider with high volume of activity can help to reduce differences in the access to no effective procedures.

Background: From 2006 to 2007 Lazio and Tuscany, two Italian regions, released data about hospital performance and implemented strategic programmes aimed at improving the quality of hospital care. Furthermore, different pay-for-performance systems were introduced: the hospital's performance determined the DRG (Diagnosis-Related Group) reimbursement rate for Lazio providers while in Tuscany the chief executive officer's compensation was linked to the hospital's performance. The authors evaluated the impact of the Lazio and Tuscany programmes on quality of healthcare for orthopaedic patients compared with other Italian regions., Methods: The proportion of older patients admitted with hip fractures who had surgery within 48 h and the median waiting time for surgical treatment of fractures of the tibia or fibula were estimated separately for Lazio, Tuscany and other Italian regions for two periods: 2006-2007 and 2008-2009. Risk-adjusted proportions were obtained using the direct standardisation method and a multivariate logistic regression was performed taking into account age, gender and comorbidity status., Results: The proportion of hip operations performed within 48 h was increased by 34% for Lazio (p<0.001) and 46% for Tuscany (p<0.001) and reduced by 3% in other Italian regions (p<0.001). To assess for possible adverse consequences, such as increased waiting times for other orthopaedic procedures, the authors monitored time to surgery for tibia or fibula fractures. There were no significant differences in the median time to surgery for tibia or fibula fractures between the two periods., Conclusions: The Lazio and Tuscany programmes appeared to have a positive impact on quality of care for older patients admitted with hip fracture without having a negative impact on other orthopaedic interventions. The results highlight the need for continuous quality improvement by repeating the evaluation process and by combining the performance system with a management strategy.

Objectives: To compare the risk-adjustment model empirically derived from the 'Italian CABG Outcome Project' with that of the additive and logistic EuroSCORE in terms of accuracy, predictive power and ability to rank hospital performances., Methods: The Italian CABG model, the logistic and additive EuroSCORE were applied to the Italian CABG population; the observed deaths/expected deaths (O/E) ratios, as obtained by the three models, were computed for each Italian cardiac surgery centre and for six classes of risk-stratified patients. The performance of the three models in predicting the 30-day mortality was formally assessed for calibration (Hosmer-Lemeshow test) and discrimination (ROC area). According to the three models, risk-adjusted mortality rates (RAMR = O/E x Italian CABG population mortality rate) were estimated for each centre; possible differences were detected in the identification of hospitals with mortality rates higher and lower than average., Results: The Italian CABG model uses fewer variables than the EuroSCORE system (14 vs 17) and exhibits the best performance in terms of discrimination and calibration. Contrary to the other tested models, the logistic EuroSCORE shows a significant Hosmer-Lemeshow test (chi(H-L)(2)=19.30, p<0.0001), indicating unsatisfactory calibration, and a clear predicted death overestimation in each of the considered risk classes (O/E = 0.4). When a proper recalibration procedure is applied, the logistic EuroSCORE performance parameters achieve acceptable levels. The Italian CABG model identified seven centres as having higher than average mortality, while the EuroSCORE identified the same seven centres plus one other. The Italian CABG model identified eight centres with lower than average mortality, five of which were identified by the additive EuroSCORE and four of which were identified by the logistic EuroSCORE. The additive EuroSCORE identified four more and the logistic EuroSCORE three more low mortality centres., Conclusions: Although this analysis reveals a satisfactory concordance between results from the three models, a detailed comparison shows that the Italian CABG model uses fewer variables and performs better than the others. Nevertheless, when properly recalibrated, the EuroSCORE model can be exported to the Italian population and used to rank hospital performance and evaluate preoperative risk of patients undergoing open-heart surgery.

Background: Hierarchical modelling represents a statistical method used to analyze nested data, as those concerning patients afferent to different hospitals. Aim of this paper is to build a hierarchical regression model using data from the "Italian CABG outcome study" in order to evaluate the amount of differences in adjusted mortality rates attributable to differences between centres., Methods: The study population consists of all adult patients undergoing an isolated CABG between 2002-2004 in the 64 participating cardiac surgery centres.A risk adjustment model was developed using a classical single-level regression. In the multilevel approach, the variable "clinical-centre" was employed as a group-level identifier. The intraclass correlation coefficient was used to estimate the proportion of variability in mortality between groups. Group-level residuals were adopted to evaluate the effect of clinical centre on mortality and to compare hospitals performance. Spearman correlation coefficient of ranks (rho) was used to compare results from classical and hierarchical model., Results: The study population was made of 34,310 subjects (mortality rate = 2.61%; range 0.33-7.63). The multilevel model estimated that 10.1% of total variability in mortality was explained by differences between centres. The analysis of group-level residuals highlighted 3 centres (VS 8 in the classical methodology) with estimated mortality rates lower than the mean and 11 centres (VS 7) with rates significantly higher. Results from the two methodologies were comparable (rho = 0.99)., Conclusion: Despite known individual risk-factors were accounted for in the single-level model, the high variability explained by the variable "clinical-centre" states its importance in predicting 30-day mortality after CABG.

Objective: In countries with universal health coverage, socioeconomic status is not expected to influence access to effective treatment and its prognosis. We tested whether socioeconomic status affects the rates of elective total hip replacement and whether it plays a role in early and late outcomes., Design: Multicity population-based longitudinal study., Setting and Participants: From Hospital Registries of four Italian cities (Rome, Milan, Turin, and Bologna), we identified 6140 residents aged 65+ years undergoing elective total hip replacement in 1997-2000., Main Outcome Measures: An area-based (census block) income index was used for each individual. Poisson regression yielded rate ratios (RR) of population occurrence by income level. Logistic regression estimated odds ratios (OR) of selected outcomes within 90 days. Cox proportional hazard models evaluated effects of income on rates of revision of total hip replacement and mortality up to 31 December 2004. Analyses were adjusted for age, gender, city of residence, and coexisting medical conditions., Results: Low-income people were less likely than high-income counterparts to undergo total hip replacement [RR = 0.87, 95% confidence interval (CI) 0.81-0.95]; the effect was stronger among those aged 75+ years (RR = 0.76, 95% CI = 0.66-0.86). Low income was associated with higher risk of acute adverse medical events (P trend = 0.05) and of general infections and decubitus ulcer (P trend = 0.02) within 90 days. The effects were even higher among those aged 75+ years. No effects were found either for orthopaedic complications within 90 days or for revision and mortality., Conclusions: Total hip replacement is underutilized among elderly deprived individuals. Disadvantaged patients seem more vulnerable to acute adverse medical events after surgery. The evidence of unmet need and poor prognosis of low social class people has important implications for health care policy.

Objective: The increasing demand for comparative evaluation of outcomes requires the development and diffusion of epidemiologic research, the ability to correctly formulate hypotheses, to conduct analyses and to interpret the results. The purpose of this paper is to provide a detailed but easy-reading review of epidemiologic methods to compare healthcare outcomes, particularly risk-adjustment methods., Methods: The paper is divided into three parts. Part I describes confounding in observational studies, the ways confounding is identified and controlled (propensity adjustment and risk adjustment), and the methods for constructing the severity measures in risk-adjustment procedures., Conclusions: It is becoming increasingly important for policy makers and planners to identify which factors may improve or worsen the effectiveness of treatments and services and to compare the performances of providers. Politicians, managers, epidemiologists, and clinicians should make their decisions based on the validity and precision of study results, by using the best scientific knowledge available. The statistical methods described in this review cannot measure 'reality' as it 'truly' is, but can produce 'images' of it, defining limits and uncertainties in terms of validity and precision. Studies that use credible risk-adjustment strategies are more likely to yield reliable and applicable findings.

The increasing demand for comparative evaluation of outcomes requires the development and diffusion of epidemiologic research, the ability to correctly conduct analyses and to interpret results. When healthcare outcomes are used for comparing quality of care across providers, failure to use methods of risk adjustment to account for any variation in patient populations can lead to misinterpretation of the findings. The purpose of this paper is to provide a detailed but easy-reading review of different risk adjustment methodologies to compare health care outcomes. The paper is divided in two parts. Introduction describes the difference between experimental and observational studies, the role of confounding in observational studies and the ways confounding is identified and controlled (propensity adjustment and risk adjustment), Specific part on risk adjustment describes: (1) the methods for constructing the severity measures; (2) the methods that use the severity measures to obtain "adjusted" outcome measures for valid comparison between groups (stratified analysis, indirect and direct standardization); (3) identification and management of effect modification; (4) the methods to gain the precision of the estimates; (5) the risk adjustment methods used with multiple comparisons and (6) introduction to other models (multi-level models) used for risk adjustment. For policy makers and planners, epidemiologists and clinicians it is important to understand which factors can improve or worsen the effectiveness of treatments and services and to compare the performances of hospitals and healthcare providers. Decisions should be based on the validity and precision of study results, by using the best scientific knowledge available. The statistical methods described in this review cannot measure reality as it truly is, but can produce images of it, defining limits and uncertainties in terms of validity and precision. Since any risk-adjustment model used for comparative evaluation of outcomes must be time- and population-specific, only the studies that use credible risk adjustment strategies are more likely to yield reliable findings.

Background: The major fault with existing reimbursement systems lies in their failure to discriminate for the effectiveness of stay, both when paying per day and when paying per episode of treatment., Objectives: We sought to define an average length of effective stay and recovery trends by impairment category, to design a prospective payment system that takes into account costs and expected recovery trends, and to compare the calculated reimbursement with the predicted costs estimated in a previous study (Saitto C, Marino C, Fusco D, et al. A new prospective payment system for inpatient rehabilitation. Part I: predicting resource consumption. Med Care. 2005;43:844-855)., Research Design: We considered all rehabilitation admissions from 5 Italian inpatient facilities during a 12-month period for which total cost of care had already been estimated and daily cost predicted through regression model. We ascertained recovery trends by impairment category through repeated MDS-PAC schedules and factorial analysis of functional status. We defined effective stay and daily resource consumption by impairment category and used these parameters to calculate reimbursement for the admission. We compared our reimbursement with predicted cost through regression analysis and evaluated the goodness of fit through residual analysis., Results: We calculated reimbursement for 2079 admissions. The r(2) values for the reimbursement to cost correlation ranged from 0.54 in the whole population to 0.56 for "multiple trauma" to 0.85 for "other medical disorders." The best fit was found in the central quintiles of the cost and severity distributions., Conclusion: For each impairment category, we determined the number of days of effective hospital stay and the trends of functional gain. We demonstrated, at least within the Italian health care system, the feasibility of a reimbursement system that matches costs with functional recovery. By linking reimbursement to effective stay adjusted for trends of functional gain, we suggest it is possible to avoid both needless cuts and extensions of hospital admissions.

Background: The measures of clinical status used to predict costs must pay the most attention possible to medical conditions and clinical complexity. Length of stay (LOS), which has been used as a proxy for resource consumption, is not a direct measure of costs. Classification and regression trees, which are used in defining iso-resource groups, can be affected by overfitting and are based on a priori choices of the splitting attributes. Finally, current approaches are mainly concerned in estimating average group costs and do not attempt to estimate individual case costs., Objectives: We sought to define comprehensive measures of clinical status and detailed measures of resource consumption. We also sought to predict individual inpatient rehabilitation costs through multiple regression models., Research Design: A prospective analysis was conducted of all rehabilitation cases admitted to 5 Italian inpatient facilities during a period of 12 months. All admissions underwent repeated Minimum Data Set-Post Acute Care (MDS-PAC) schedules to collect information on clinical status and treatment provided. We used factorial analysis to yield continuous variables representing clinical characteristics, and we priced treatments to obtain cost of stay. We used linear regression models to predict cost of stay and validated the model-based cost predictions by data-splitting., Results: We collected 9720 MDS-PAC schedules from 2702 hospital admissions. The multivariate regression models fitted costs reasonably well with r(2) values of at least 0.34. On cross-validation, the ability of the regression models to predict cost was confirmed., Conclusion: We were able to estimate actual rehabilitation costs and define reliable regression models to predict costs from individual patient characteristics. Our approach identifies the contribution of any single patient characteristic to rehabilitation cost and tests the assumptions of the analysis.

Background: Improving quality and effectiveness of health care is one of the priorities of health policies. Hospital or physician volume of activity may be a measurable variable with a relevant impact on effectiveness of health care. There are several studies and systematic reviews evaluating the association between volume and outcome of health care. The aim of this review is to identify: areas, clinical conditions or interventions (prevention, diagnostic, therapeutic, surgical or clinical) for which an association between volume and outcome has been investigated; those for which an association between volume and outcome has been proved, Methods: Overview of systematic reviews and Health Technology Assessment reports; search of MEDLINE, EMBASE, The Cochrane Library, Web sites of Health Technology Assessment, other HTA Agencies, National guideline Clearinghouse, National Health Care quality tools (1995-february 2005). For each studied area results are described separately for each review due to the heterogeneity of outcomes, volume thresholds and results reported. No metanalysis has been conducted. Completeness of reporting of the systematic reviews has been evaluated using the QUOROM statement. For each review we evaluated the number of studies included and the proportion of studies with statistically significant results (p < 0,05). As far as in-hospital mortality is concerned, the different areas have been classified in the following groups: Strong evidence ofpositive association: areas with > or =10 studies included in the reviews, and high prevalence (> or =50%) of positive studies (p <0. 05) in the majority of reviews. Weak evidence of association: areas with 5 to 9 studies included in the reviews and high prevalence (> or =50%) of positive studies (p <0.05) in the majority of reviews. Weak evidence of lack of association: areas with 5 to 9 studies included in the reviews and high prevalence (>50%) of not statistically significant studies (p >0.05) in the majority of reviews. No suficient evidence of association: areas with less than 5 studies included in the reviews. No evidence of association: areas with > or =10 studies included in the reviews, and high prevalence (>50%) of not statistically significant studies (p >0.05) in the majority of reviews. The same literature search was then applied to identify primary studies published in each considered area following the most recent systematic review published., Results and Discussion: We identified 21 systematic reviews and included 11 of them analysing 46 different areas. The majority of studies evaluate the effect of specific surgical procedures; the main outcomes considered are hospital mortality and 5 year survival for cancers. Considering in-hospital mortalilty as outcome, in 11 areas there is strong evidence ofassociation between volume of activity and outcome: abdominalaortic aneurysm (unruptured), percutaneous transluminal coronary angioplasty knee arthroplasty coronary artery bypass, surgery for oesophageal and pancreatic cancer, surgery for prostate cancer, colecistectomy, carotid endarterectomy, myocardial infarction, neonatal intensive care. It is never possible however to identify a unique volume threshold. For some of these areas, particularly coronary angioplasty and coronary artery bypass, there are many new studies published following the last systematic review; some specific aspects are being investigated such as the role of temporal changes in the association, the effect of different risk adjustment procedures and the separate role of physician or hospital volume. In some cases, for example knee arthroplasty in-hospital mortality could be an inadequate outcome on which judging the strength of association, in fact, the few studies evaluating other outcomes such as complications provide inconsistent results. For a range of areas the evidence of association is weak: AIDS, appendicectomy, cardiac catheterization, surgery for breast, lung, stomach cancer, hernia repair, hip fracture, hysterectomy and injuries. As far as AIDS is concerned, the few number of studies found is probably due to the lack of studies published after the introduction of effective therapies. All the included studies show an evidence of association between volume and in-hospital mortality. In no case we found weak evidence of lack of association while we identified three conditions for which the number of studies included in the reviews together with the prevalence of non significant studies do suggest lack of association; these are abdominal aortic aneurysm (ruptured), hip arthroplasty and surgery for colorectal cancer. In the case of hip arthroplasty as well, inhospital mortality could be an inadequate outcome, but only one old study found a positive association with risk of complications. Eventually there is a group of areas (n=22) for which there is not enough evidence to draw conclusions about the association between volume and outcome due to a small number of studies. In some cases, such as transplants, this could be due to the low rate of events; in this case all the few published studies show positive results. There are some limitations which should be taken into account in the interpretation of these results: despite the overall good completeness of reporting of the included reviews, the majority of studies included in the reviews themselves are cross-sectional studies representing a very weak study design to evaluate causality of the investigated association. Moreover the methodology of risk adjustment applied is heterogenous among studies and it is difficult to know the extent to which this can affect the observed results. It is eventually necessary to consider the possible occurrence of publication bias which could lead to an overestimation of the positive effect of volume on health care outcomes attributable to the lack of publication of negative studies., Conclusions: In some areas the evidence seems strong enough to guide health care organizational choices, although it is not possible to identify well defined volume thresholds. In other areas, particularly for non surgical conditions, where there is not enough evidence, it seems necessary to conduct proper epidemiological studies. Also the evaluation of effectiveness of using volume as an instrument of health policy requires further research. Taking into account the rapid and continuing process of technology development, the definition of standard and prerequisite volumes of care should be specific of each temporal period and health care system. It is therefore a dynamic process requiring a continuous review of the available evidence. In the area of evidence based public health, the limited available evidence should not impair the choice of actions based on limited evidence, but rather it should lead to the application of thefew available evidence on one side and to the planning of proper research in the areas of lack of evidence.

We evaluated the disease management of transient ischemic attack in patients admitted to Lazio hospitals from July 1997 to June 1998. We assessed the effects of patient characteristics including chronic comorbidities on the use of diagnostic procedures, endarterectomy, and on the risk of adverse cerebrovascular outcome or death. There were 2,608 patients in the study who were followed up over a 18- to 30-month period. Carotid surgery was performed on 1.15% of the subjects, total mortality was 34.7 per 1,000 person-years and adverse cerebrovascular outcome was observed in 38.1 per 1,000 person-years. Chronic comorbidities did affect the mortality rate and the rate of adverse outcome, but not the rate of endarterectomies. Carotid surgery was infrequently performed in study subjects. It seems that this potentially stroke-preventive treatment was not offered to suitable candidates in many instances., (Copyright 2004 S. Karger AG, Basel)

Objective: Monitoring health outcomes across hospitals has become a growing interest as a potential means to promote quality of care, but in Italy it is at the beginning stage. We aimed at comparing the performance of different cardiac surgery units and testing the utility of routinely collected data in this respect., Methods: From the Lazio region hospital information system (HIS), we selected a cohort of 1603 individuals (84% males; mean age 63 years, SD 8) residing in Rome (2,685,890 inhabitants), who underwent isolated coronary artery bypass surgery (CABG, ICD-9-CM code: 36.1) in the period 1996-97 in seven major cardiac surgery units in the city. They were identified as A, B, C (teaching), D and E (non-teaching) units. Information on vital status at 30 days after the CABG surgery was obtained through an automatic record linkage with the Municipal Registry of Rome. The association between cardiac surgery units and outcome was evaluated through logistic regression taking into account the following a priori risk factors in different models: gender, age, socio-economic status, type of ischaemic heart disease and comorbidities., Results: The overall mortality was 5.4% (range 2.1-11.4%). Statistically significant predictors of outcome included: age (OR=7.5 for age> or =70 vs. 35-49 years), acute myocardial infarction (OR=32.7 vs. acute-subacute forms/angina), chronic myocardial ischaemia (OR=4.2 vs. acute-subacute forms/angina), other heart diseases (OR=4.8), chronic renal disease (OR=16.0) and peripheral arterial disease (OR=2.9). Statistically significant variability in mortality was observed across hospitals; taking hospital A as reference, hospital D showed the highest risk (OR=5.7, 95% CI=1.9-17.3, in the fully adjusted model)., Conclusions: We suggest that a true variation in quality of care play a role in the observed differences across hospitals, although chance and inaccurately measured risk factors cannot be excluded. Despite some limitations, the HIS is a valid tool for screening cardiac surgery units with poor performance.

In 1991 the Lazio Region set up a surveillance system which collects individual data on each drug user attending Public Treatment Centres (PTCs). The analysis of surveillance system data allows not only to describe the characteristics of treatments but also to analyse determinants of treatment outcomes. In this study the outcome of treatment was evaluated in 5.646 drug users who attended public centres in 1992. The outcome was defined in two categories: positive (subjects who completed the therapeutic program, were referred to different service or were still in treatment) negative (subjects who refused or dropped out treatment, arrested or dead). Drug users usually receive more than one treatment in one year, 60% of them successfully completed. Methadone treatment shows the highest level of compliance while naltrexone the lowest. The negative outcome is highly associated with sex, type of treatment, length of treatment and outcome of previous treatment. Males are more likely to experience a negative outcome than females. Those offered naltrexone are more likely to refuse and drop out than those offered psychosocial treatment. Long term treatments are more successful than shorter ones. Furthermore, drop out is higher among those who have dropped out in the past. Although this observational study might not permit conclusions on the efficacy of each type of treatment, it allows an evaluation of the selection procedures at the treatment centres. Treatment centres for drug users in Lazio tend to select clients according to standard therapeutic treatment protocols instead of making treatments more accessible to drug users.