**5. Discussions and conclusions**

Italian regional devolution on health care has led each Region to develop its own PMS. Although national reforms have pushed the adoption of managerial tools, the study points out that still few Regions have developed PMS capable to measure all the topical dimensions of the OECD framework (Efficiency, Responsiveness, Equity and Health improvement/outcome). In particular dimensions less controlled are: responsiveness and equity. Besides another weakness of the Italian regional PMSs is that often policy makers and regional managers use a plethora of tools in order to control the performance of health service and health system organizations. This highlights that in most cases regional policy level lacks of strategic tools capable of summing up the overall performance in an easy, integrated and systematic way.

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Similarities concerning the dimensions covered by all PMSs seem to be dictated by path dependency or national pressure on financial deficit. Indeed past choices, such as the DRG financing system, have had an enduring influence on narrowing the range of viable alternatives in fact health informative systems are mainly oriented to hospital services (as Friuli Venezia Giulia and Bolzano complained in table 2). Moreover national pressure on financial deficit have shaped lots of regional PMSs so that these PMSs are focused on the efficiency and financial performance dimension paying less attention to the other ones.

Pioneer Regions in the development of PMS or area indicators are those that declared to have adopted a specific framework or those that have specialized regional study centres (often linked to University) that have spurred Regions to look beyond traditional measures (ie. Piedmont with the equity research group or Tuscany with the MeS lab).

Another interesting result pointed out by the study is the role played by the rewarding systems. The rewarding system is often integrated with PMS even if they do not completely overlap. A different situation regards Regions that are not used to measure performance in a systematic and coordinated way. Here, the rewarding system is the means by which Regions, such as Basilicata, introduce comprehensive PMSs. To this extent rewarding system can be seen as the driver of innovation.

Scholars suggest benchmarking as another driver of change. Although most Regions acknowledge that benchmarking processes may help spreading innovation and improvements there are still few Regions that adopt benchmarking within regional boundaries (Lombardy and Tuscany), sometimes because they are small Region (like Bolzano or Umbria), sometimes because they don't want to enable negative competition (like Apulia). Most Regions declare to be open to compare their performance across regional health authorities or teaching hospitals but there are quite different visions on how this comparison should be done. From one side there is the vision related to the fear of loosing autonomy (like Regions that want to share only the criteria on how to assess performance), on the opposite side there is the vision that consider performance benchmarking as a powerful tool in order to support regional decisions and strategies (like Regions that ask for public evidence in order to overcome unacceptable differences).

This paper has provided with a first picture of the similarities and differences of the Regional PMSs seeking to identify the factors that may have influenced the PMS design.

These hypotheses on factors that affect PMSs design, should be tested throughout other studies above all with the new scenario that has been emerging on the performance control: from one hand a group of Regions decided to start a network in which they compare and evaluate the performance of health services throughout the help of a benchmarking agency; from the other hand on April 2010 the Ministry of Health published on the website its national performance evaluation system (Nuti et al forthcoming b).

#### **6. References**


Similarities concerning the dimensions covered by all PMSs seem to be dictated by path dependency or national pressure on financial deficit. Indeed past choices, such as the DRG financing system, have had an enduring influence on narrowing the range of viable alternatives in fact health informative systems are mainly oriented to hospital services (as Friuli Venezia Giulia and Bolzano complained in table 2). Moreover national pressure on financial deficit have shaped lots of regional PMSs so that these PMSs are focused on the

Pioneer Regions in the development of PMS or area indicators are those that declared to have adopted a specific framework or those that have specialized regional study centres (often linked to University) that have spurred Regions to look beyond traditional measures

Another interesting result pointed out by the study is the role played by the rewarding systems. The rewarding system is often integrated with PMS even if they do not completely overlap. A different situation regards Regions that are not used to measure performance in a systematic and coordinated way. Here, the rewarding system is the means by which Regions, such as Basilicata, introduce comprehensive PMSs. To this extent rewarding

Scholars suggest benchmarking as another driver of change. Although most Regions acknowledge that benchmarking processes may help spreading innovation and improvements there are still few Regions that adopt benchmarking within regional boundaries (Lombardy and Tuscany), sometimes because they are small Region (like Bolzano or Umbria), sometimes because they don't want to enable negative competition (like Apulia). Most Regions declare to be open to compare their performance across regional health authorities or teaching hospitals but there are quite different visions on how this comparison should be done. From one side there is the vision related to the fear of loosing autonomy (like Regions that want to share only the criteria on how to assess performance), on the opposite side there is the vision that consider performance benchmarking as a powerful tool in order to support regional decisions and strategies (like Regions that ask for

This paper has provided with a first picture of the similarities and differences of the Regional PMSs seeking to identify the factors that may have influenced the PMS design. These hypotheses on factors that affect PMSs design, should be tested throughout other studies above all with the new scenario that has been emerging on the performance control: from one hand a group of Regions decided to start a network in which they compare and evaluate the performance of health services throughout the help of a benchmarking agency; from the other hand on April 2010 the Ministry of Health published on the website its

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supplemento al n.20


**Part 3** 

**General Issues** 


**Part 3** 

**General Issues** 

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**18** 

*Japan* 

**Causal Inference in** 

*Kinki University School of Medicine,* 

No. of

patients Deaths

*Division of Biostatistics, Clinical Research Center,* 

Yasutaka Chiba

**Randomized Trials with Noncompliance** 

In human clinical trials, ethical considerations for study subjects override the scientific requirements of trial design. Noncompliance with an intervention or study procedure for

The Coronary Drug Project (CDP) trial (CDP Research Group, 1980) was a typical example of trials with noncompliance. The CDP trial was a large, double-blinded, randomized trial testing the effect of the cholesterol-lowering drug, clofibrate, on mortality. Patients were randomly assigned to the clofibrate or placebo groups and were followed for at least 5 years, documenting clinic visits and examinations. During each 4-month follow-up visit, the physician assessed compliance by counting or estimating the number of capsules returned by the patients. In the protocol, good compliers were defined as patients taking more than 80% of the prescribed treatment. Table 1 summarizes the incidence of death during the 5-year follow-up period, based on the treatment assigned and compliance status. Patients

status

Less than 80% 357 88

Less than 80% 882 249

who left the trial before the end of the 5-year follow-up period were excluded.

patients Deaths Compliance

interpret the result as being that the placebo had the effect of decreasing death.

Clofibrate 1065 194 More than 80% 708 106

Placebo 2695 523 More than 80% 1813 274

Table 1. The compliance status and incidence of death during a 5-year follow-up period in

In the clofibrate group, 708 patients were considered good compliers; 106 died during the follow-up period. There were 357 patients considered poor compliers; 88 died. Comparing the compliance status of the proportion of patients that died yields 106/708 – 88/357 = –9.68%. From this result, clofibrate seems to have been beneficial. However, when we make the same comparison for the placebo group, it yields 274/1813 – 249/882 = –13.12%. Surprisingly, we obtain the result that the placebo was more beneficial than clofibrate. However, nobody would

ethical reasons is thus inevitable in practice (Piantadosi, 1997).

**1. Introduction** 

Group No. of

the CDP trial.

Totals 3760 717
