The present study is intended to be an analytical first step in measuring the quality of hospital care in an area of Italy by using a set of indicators that reflect the adherence to current evidence-based processes of care. The application of JCAHO/CMS quality indicators has provided valuable insight into their feasibility, ease of use, and availability of required data. This experience indicates that these quality indicators can be implemented in this context, and they showed to be easy to use.
The results of this study show that quality of hospital care is extremely variable according to indicators and to conditions and is often inadequate. Composite scores indicate that patients may not receive the recommended care in many cases and that there is wide room for improvement. Actually, one could expect a wide-ranging adherence rates at the baseline measurement, since this tendency has already been reported in earlier works on the topic. Indeed, in a study reporting time-series data over eight quarters from 2002 through 2004 in the U.S. hospitals, a wide variation in adherence to quality indicators was reported at the baseline measurement, whereas a significant compliance improvement for 15 of the 18 indicators was recorded over time 
This baseline measurement, according to its observational nature, allowed us to perform a real-world assessment of patterns of care, before any quality improvement initiative had been undertaken, and showed a very challenging scenario that deserves careful interpretation. Indeed, only few measures (use of aspirin and ACEI or ARB for AMI, ACEI or ARB for HF, appropriate thromboembolism prophylaxis and appropriate hair removal for surgical patients) almost approached optimal adherence, whereas, at the other extreme, rates regarding adherence to smoking-cessation counseling in AMI and HF patients, discharge instructions in HF patients, and influenza and pneumococcal vaccination in pneumonia patients were noticeably intangible. For all other measures a wide variation in uptake was registered, regardless of the condition taken into account. This variability has already been reported by Jha et al. 
in American hospitals, where for five indicators related to AMI half of the hospitals scored over 90%, whereas the level of performance for the other measures was much lower and variable.
A number of studies have identified potential barriers and factors for the adoption of best-practice guidelines. Reasons underlying this wide variation in adherence to quality indicators can be different and can be related to individual, organizational, and environmental factors 
. It has been suggested that variation in compliance to recommended processes of care may reflect differences in training, guideline familiarity, and implementation of tools and systems to ensure that recommended care is provided and documented 
. Indeed, another factor affecting the adherence to quality indicators may be the impaired perception about connection of evidence-based processes of care to improved outcomes 
. Two surveys conducted by some of us among Italian physicians documented that, despite a general agreement towards the need to integrate clinical practice and the best available evidence, they not frequently used results of economic evaluations, RCTs and meta-analyses to make decisions in the clinical practice 
. These results are quite consistent with those of another investigation regarding Italian general practitioners' perceptions of Evidence Based Medicine and its influence on headache patient management 
. However, it is difficult to translate evidence into clinical continuing educational programs and, therefore, raising awareness of how to use tools to critically appraise and apply the evidence to their patients are strongly needed 
. Furthermore, a number of studies showed that hospitals’ characteristics such as type, size, availability of given technologies and services, and geographic factors can play a role in the uptake of evidence-based processes of care 
, along with the capability in fitting and customization of existing guidelines to local contexts 
. In these settings many of these barriers may have had a role, but it is possible to tentatively try to suggest reasons for lack of adherence to some of the measured indicators. The pattern of performance observed seems to confirm previous research that showed how quality performance may vary more by functional roles in the hospital, such as treatment and diagnosis vs counseling and prevention, than by a particular disease being treated 
. This is in agreement with the findings of this study, where preventive indicators were those that can receive the largest improvements. This is of concern, since some of these indicators relates to effective practices, such as, for instance, patient education for the treatment of HF 
; moreover, from a hospital management perspective, interest in performance is related to both clinical (i.e. prescriptions and/or treatment procedures) and preventive (i.e. discharge HF education, vaccination practices and/or counseling on known risk factors) care.
It should also be noted that, at least partly, recommended processes of care were actually supplied but were not detailed in medical records. Thus, the low adherence rates to some evidence-based measures may underestimate the real uptake, mainly, for appropriate timing and selection of prophylactic antibiotics in surgical patients. Moreover, adherence to blood cultures (BCs) indicators was also inconsistent, which may reflect physicians’ awareness that BCs may have a limited utility in community-acquired pneumonia (CAP) patients. A systematic review of cohort studies showed that true-positive values of BCs obtained at hospital admission from patient admitted for CAP ranged from 0% to 14% of cases 
The present study was designed to provide information on process indicators and not on patient outcomes. Although all of the performance indicators measured were derived from the JCAHO and the CMS set of indicators and reflect the healthcare quality current evidence and practice guidelines, variable associations between performance measures and outcomes have been reported by several studies. Indeed, Wang et al. found that hospitals with better performance on both AMI and HF measures had lower risk-adjusted mortality compared with hospitals adherent to neither or either alone 
, whereas Ingraham et al. found only partial association between adherence to SCIP indicators and risk-adjusted outcomes related to morbidity and mortality following surgery 
In-hospital mortality rates can be regarded as a measure of association of hospital adherence to guidelines and patient outcomes. In this study, the overall mortality rate was 4%, whereas with respect to the principal diagnosis of admission, mortality rates ranged from 2.6% to 6.5%. These rates were steadily lower than those published in the Age.Na.S’s study 
, since condition-specific mortality rates were 7.5% for AMI, 7.1% for HF, and 8.6 for PN. It is plausible that these differences in mortality may be due to the fact that the Age.Na.S study 
refers to condition-specific mortality, while results of the present study concerned the in-hospital mortality of patients admitted with one of the four principal diagnosis selected. As regard the association between adherence to indicators and in-hospital mortality the only for which it was plausible to make this assessment were AMI and HF indicators. Indeed, for PN and SCIP the procedures identified by the indicators could, at most, affect the long-term mortality and could hardly be related to in-hospital mortality. Therefore, it was possible to model only the mortality for AMI as the outcome variable and a significant association has been found with a lowest adherence to AMI indicators (OR
0.97; 95% CI
0.032) (data not shown). Although this was not an aim of this study, it may be suggested that effectiveness of process indicators should be more thoroughly investigated in the real world.
Most of the previous studies were conducted on large numbers of hospitals and therefore were based on aggregated data. Instead, the results in this study were derived from a smaller number of patients, but detailed information was gathered from each of them. This was a strength of this study and allowed us to indicate subjective characteristics that could predict adherence to performance indicators. Indeed, the results from the multivariate analyses showed that age significantly predicted the adherence to quality indicators for AMI, HF, and SCIP, since older patients were less likely to receive the recommended processes of care. The findings are consistent with those reported by some authors who found out that patients aged ≥75 were independently associated with a lower level of care and worse outcomes 
. None of the other socio-demographic characteristics appear to influence the behavior of health professionals in the application of indicators. Further research is needed, involving larger datasets, that will identify eventual other subject or hospital characteristics that are related to the appropriateness of the process of care.
Some potential limitations of the present study need to be acknowledged. First, comparisons across countries should be made cautiously, since it has to do with the appraisal of different healthcare systems. Second, a main shortcoming may arise from the lack of follow up and it was not possible to appraise any relationship with indicators and outcomes over time. However, it was not an objective of the present study that was, instead, to detect an estimate of adherence to selected process of care indicators as a measure of quality of care provided in-hospital setting. Finally, it should be noted that the results depend not only on the quality of care provided, but also on patient characteristics that may be outside the direct control of a hospital 
. Therefore, it is not possible to report any change over time. Indeed, data abstraction was sharply critical in many cases, since it was not possible to retrieve the necessary data from medical records or the medical files were not available at all. Thus, it is arguable that availability and quality of data may have contributed to lower estimates of the adherence rates. Third, despite the importance of the patients educational level in the adherence to the treatments they undergo 
, this information was not present in the medical record and, therefore, the study does not provide guidance in this regard. Finally, although the reviewers collected the data not blinded to the outcome of interest, the use of explicit and objective indicators that relies entirely on the presence or absence of specific information entails that there is no influence of reviewers on the quality of abstracted data.
The wide variation and in some instances the very low adherence to quality indicators suggests that there is still substantial work that lies ahead on the way to improve hospital performance. Efforts should focus more on domains of healthcare than on specific conditions, and particularly on improvement in preventive care. Moreover, resources should be devoted to expand comprehensiveness and quality of data in medical records and to identify specific subgroup of the population that need a special attention in delivering care.