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Background: the Italian National Prevention Plan (PNP) posed the standard to be achieved by Regions for the prevention of obesity in childhood and adolescence. The PNP also set up a monitoring system to assess the impact of implemented policies., Objectives: to develop a conceptual model to facilitate interpretation of variation in outcome indicators., Methods: after a systematic review, the DPSEEA («Driving forces», «Pressures», «State», «Exposure», «Effect», «Actions») was identified as the more appropriate framework to assess the results of preventive policies. Factors for each component of the framework were identified and indicators that allow measuring the changing of each of these factors were defined., Results: the included «driving forces» were related to the profit-led food industry, to the nutrition environment at school, and to household-level factors. Among the «pressures», parenting behaviours, food provided by school canteens, sociocultural factors, social context, physical activity (PA), opportunities at school or after-school were included. In the State, the high consumption of processed food, the large quantities of high-calorie food easy available, the consumption of carbonated and sugar-sweetened beverages, the reduced social function of mealtimes in families, the early cessation of breastfeeding, the reduction of outdoors activity, active transportation, and PA at school for children were identified. The «exposure» factors were the reduced opportunities of doing PA and the over-consumption of calories that influence the «effect», described as the prevalence of children and adolescents affected by obesity., Conclusions: through the DPSEEA, a conceptual model was set up; it allows to place in the causal chain the «actions» and the mechanisms through which these actions should impact on the «exposure» (PA and over-consumption of calories), making the rationale of process and impact indicators explicit.

Background: Demographic changes and chronicity are posing new challenges to health care systems. Our study aimed to examine how effectively the three different types of proactive primary care models adopted by three different regional health care systems in Italy were improving the quality of diabetes management by general practitioners., Methods: A coordinated Italian nationwide project to compare systematically the new proactive organizational models implemented at regional and local level (the MEDINA Project) involved several regions and their local health units (LHUs). A quasi-experimental study was conducted on a large dataset obtained by processing administrative databases. A combined indicator was developed to assess the quality of care delivered by primary care physicians, based on adherence to recommendations concerning patient monitoring and treatment., Result: The study concerned 602 Italian general practitioners (GPs), 174 of them female, who were caring for a total of 753,366 patients (47,575 of them diabetic). Analyzing a total score, representing global adherence to a quality management of patients with diabetes, confirmed that GPs who had adopted the new model of care for their diabetic patients obtained better results than those who had not, so the new policy was generally effective., Conclusion: Our study showed that introducing new, proactive primary care models could sustain efforts made around the world to guarantee good-quality chronic disease management in the primary care setting., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: In Italy, there currently is a lack of reliable and consistent data on home palliative care provided to people near death., Objectives: Monitoring the activities of the Italian Home Palliative Care Services, according to the 2014 national data collection program entitled "Observatory of Best Practices in Palliative Care" and providing process/outcome measures on a subsample (Best Practice Panel), on regulatory standards and on complete/reliable activity data., Design: A data collection web portal using two voluntary internet-based questionnaires in order to retrospectively identify the main care activity data provided within the year 2013 by Home care units. In the Best Practice Panel and International best practices, eligibility and quality measures refer to the national standards of the NL 38/2010. Setting/Subject: Home Palliative Care Services (HPCSs) that provided care from January to December 2013., Results: 118 Home care units were monitored, globally accounting for 40,955 assisted patients within the year 2013 (38,384 cancer patients); 56 (47.5% of 118) were admitted in the Best Practice Panel. Non-cancer (5%) and pediatric (0.4%) patients represented negligible percentages of frail care patients, and a majority of patients died at home (respectively nearly 75% and 80% of cancer and non-cancer patients)., Conclusion: The study demonstrated the feasibility of the collection of certified data from Home care services through a web-based system. Only 80% of the facilities met the requirements provided by the Italian NL 38/2010. Moreover, the extension of the palliative care services provided to frail non-cancer and pediatric patients, affected by complex and advanced chronic conditions, is still inadequate in Italy.

Background: A major shift in the gender of the medical-doctor workforce is now underway, and all over the world it is expected that an average 65% of the medical workforce will be women by 2030. In addition, an aging population means that chronic diseases, such as diabetes, are becoming more prevalent and the demand for care is rising. There is growing evidence of female physicians performing better than male physicians.AimOur study aimed to investigate whether any differences in diabetes process indicators are associated with gender, and/or the interaction between gender and different organizational models.Design and settingA population-based cross-sectional analysis was conducted on a large data set obtained by processing the public health administration databases of seven Italian local health units (LHUs). The seven LHUs, distributed all over the Italian peninsula in seven different regions, took part in a national project called MEDINA, with the focus on chronic disease management in primary care (PC)., Methods: A total score was calculated for the average performance in the previously listed five indicators, representing global adherence to a quality management of patients with diabetes. A multilevel analysis was applied to see how LHUs affected the outcome. A quantile regression model was also fitted., Results: Our study included 2287 Italian general practitioners (586 of them female) caring for a total of 2 646 059 patients. Analyzing the performance scores confirmed that female general practitioners obtained better results than males. The differences between males and females were stronger on the 25th and 75th percentiles of the score than on the median values. The interaction between gender and LHU was not significant., Conclusion: Our study evidenced that female physicians perform better than males in providing PC for diabetes independently by the different organizational models. Further research to understand the reasons for these gender differences is needed.

Background: A recent comprehensive report on healthcare quality in Italy published by the Organization of Economic Co-operation and Development (OECD) recommended that regular monitoring of quality of primary care by means of compliance with standards of care for chronic diseases is performed. A previous ecological study demonstrated that compliance with standards of care could be reliably estimated on regional level using administrative databases. This study compares estimates based on administrative data with estimates based on GP records for the same persons, to understand whether ecological fallacy played a role in the results of the previous study., Methods: We compared estimates of compliance with diagnostic and therapeutic standards of care for type 2 diabetes (T2DM), hypertension and ischaemic heart disease (IHD) from administrative data (IAD) with estimates from medical records (MR) for the same persons registered with 24 GP's in 2012. Data were linked at an individual level., Results: 32,688 persons entered the study, 12,673 having at least one of the three diseases according to at least one data source. Patients not detected by IAD were many, for all three conditions: adding MR increased the number of cases of T2DM, hypertension, and IHD by +40%, +42%, and +104%, respectively. IAD had imperfect sensitivity in detecting population compliance with therapies (adding MR increased the estimate, from +11.5% for statins to +14.7% for antithrombotics), and, more substantially, with diagnostic recommendations (adding MR increased the estimate, from +23.7% in glycated hemoglobin tests, to +50.5% in electrocardiogram). Patients not detected by IAD were less compliant with respect to those that IAD correctly identified (from -4.8 percentage points in proportion of IHD patients compliant with a yearly glycated hemoglobin test, to -40.1 points in the proportion of T2DM patients compliant with the same recommendation). IAD overestimated indicators of compliance with therapeutic standards (significant differences ranged from 3.3. to 3.6 percentage points) and underestimated indicators of compliance with diagnostic standards (significant differences ranged from -2.3 to -14.1 percentage points)., Conclusion: IAD overestimated the percentage of patients compliant with therapeutic standards by less than 6 percentage points, and underestimated the percentage of patients compliant with diagnostic standards by a maximum of 14 percentage points. Therefore, both discussions at local level between GP's and local health unit managers and discussions at central level between national and regional policy makers can be informed by indicators of compliance estimated by IAD, which, based on those results, have the ability of signalling critical or excellent clusters. However, this study found that estimates are partly flawed, because a high number of patients with chronic diseases are not detected by IAD, patients detected are not representative of the whole population of patients, and some categories of diagnostic tests are markedly underrecorded in IAD (up to 50% in the case of electrocardiograms). Those results call to caution when interpreting IAD estimates. Audits based on medical records, on the local level, and an interpretation taking into account information external to IAD, on the central level, are needed to assess a more comprehensive compliance with standards.

Objectives: The Italian project MATRICE aimed to assess how well cases of type 2 diabetes (T2DM), hypertension, ischaemic heart disease (IHD) and heart failure (HF) and their levels of severity can be automatically extracted from the Health Search/CSD Longitudinal Patient Database (HSD). From the medical records of the general practitioners (GP) who volunteered to participate, cases were extracted by algorithms based on diagnosis codes, keywords, drug prescriptions and results of diagnostic tests. A random sample of identified cases was validated by interviewing their GPs., Setting: HSD is a database of primary care medical records. A panel of 12 GPs participated in this validation study., Participants: 300 patients were sampled for each disease, except for HF, where 243 patients were assessed., Outcome Measures: The positive predictive value (PPV) was assessed for the presence/absence of each condition against the GP's response to the questionnaire, and Cohen's κ was calculated for agreement on the severity level., Results: The PPV was 100% (99% to 100%) for T2DM and hypertension, 98% (96% to 100%) for IHD and 55% (49% to 61%) for HF. Cohen's kappa for agreement on the severity level was 0.70 for T2DM and 0.69 for hypertension and IHD., Conclusions: This study shows that individuals with T2DM, hypertension or IHD can be validly identified in HSD by automated identification algorithms. Automatic queries for levels of severity of the same diseases compare well with the corresponding clinical definitions, but some misclassification occurs. For HF, further research is needed to refine the current algorithm., Competing Interests: MJS is an employee of a pharmaceutical company. Genomedics is a private company owned by IC. RG, FL, GR and MS have conducted pharmacoepidemiological studies funded by pharmaceutical companies., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Interest in chronic conditions reflects their role as the first cause of death and disability in developed countries; improving the management of these conditions is a priority for health care services. The aim of this study was to establish which sociodemographic factors influence adherence to standards of care for chronic heart failure (CHF). A generalized multilevel structural equation model was developed and applied to a sample of patients with CHF obtained from administrative data flows in six Italian regions to ascertain any associations between adherence to standards of care for CHF and sociodemographic variables. Indicators of compliance were adherence to beta-blocker therapy (BB-A) and Angiotensin Convertin Enzime inhibitor/Angiotensin Receptor Blocker therapy (ACE-A), and creatinine and electrolyte testing (CNK-T). All indicators were computed over a one-year follow-up. Among a cohort of 24,997 patients, the BB-A rate was 40.4%, the ACE-A rate 61.1%, and the CNK-T rate 57.0%. Factors found associated with adherence were gender, age, and citizenship. Our study shows an inadequate adherence to standards of care for CHF, particularly associated with certain sociodemographic characteristics. This suggests the need to improve the role of primary care in managing this chronic condition. The measures considered only apply to patients with a reduced Left Ventricular Ejection Fraction, hence a limitation of this analysis is the lack of information on left ventricular ejection.

Introduction: We see increased use of existing observational data in order to achieve fast and transparent production of empirical evidence in health care research. Multiple databases are often used to increase power, to assess rare exposures or outcomes, or to study diverse populations. For privacy and sociological reasons, original data on individual subjects can't be shared, requiring a distributed network approach where data processing is performed prior to data sharing., Case Descriptions and Variation Among Sites: We created a conceptual framework distinguishing three steps in local data processing: (1) data reorganization into a data structure common across the network; (2) derivation of study variables not present in original data; and (3) application of study design to transform longitudinal data into aggregated data sets for statistical analysis. We applied this framework to four case studies to identify similarities and differences in the United States and Europe: Exploring and Understanding Adverse Drug Reactions by Integrative Mining of Clinical Records and Biomedical Knowledge (EU-ADR), Observational Medical Outcomes Partnership (OMOP), the Food and Drug Administration's (FDA's) Mini-Sentinel, and the Italian network-the Integration of Content Management Information on the Territory of Patients with Complex Diseases or with Chronic Conditions (MATRICE)., Findings: National networks (OMOP, Mini-Sentinel, MATRICE) all adopted shared procedures for local data reorganization. The multinational EU-ADR network needed locally defined procedures to reorganize its heterogeneous data into a common structure. Derivation of new data elements was centrally defined in all networks but the procedure was not shared in EU-ADR. Application of study design was a common and shared procedure in all the case studies. Computer procedures were embodied in different programming languages, including SAS, R, SQL, Java, and C++., Conclusion: Using our conceptual framework we found several areas that would benefit from research to identify optimal standards for production of empirical knowledge from existing databases.an opportunity to advance evidence-based care management. In addition, formalized CM outcomes assessment methodologies will enable us to compare CM effectiveness across health delivery settings.

Background: An aging population means that chronic illnesses, such as diabetes, are becoming more prevalent and demands for care are rising. Members of primary care teams should organize and coordinate patient care with a view to improving quality of care and impartial adherence to evidence-based practices for all patients. The aims of the present study were: to ascertain the prevalence of diabetes in an Italian population, stratified by age, gender and citizenship; and to identify the rate of compliance with recommended guidelines for monitoring diabetes, to see whether disparities exist in the quality of diabetes patient management., Methods: A population-based analysis was performed on a dataset obtained by processing public health administration databases. The presence of diabetes and compliance with standards of care were estimated using appropriate algorithms. A multilevel logistic regression analysis was applied to assess factors affecting compliance with standards of care., Results: 1,948,622 Italians aged 16+ were included in the study. In this population, 105,987 subjects were identified as having diabetes on January 1st, 2009. The prevalence of diabetes was 5.43% (95% CI 5.33-5.54) overall, 5.87% (95% CI 5.82-5.92) among males, and 5.05% (95% CI 5.00-5.09) among females. HbA1c levels had been tested in 60.50% of our diabetic subjects, LDL cholesterol levels in 57.50%, and creatinine levels in 63.27%, but only 44.19% of the diabetic individuals had undergone a comprehensive assessment during one year of care. Statistical differences in diabetes care management emerged relating to gender, age, diagnostic latency period, comorbidity and citizenship., Conclusions: Process management indicators need to be used not only for the overall assessment of health care processes, but also to monitor disparities in the provision of health care.

Background: Italy has a population of 60 million and a universal coverage single-payer healthcare system, which mandates collection of healthcare administrative data in a uniform fashion throughout the country. On the other hand, organization of the health system takes place at the regional level, and local initiatives generate natural experiments. This is happening in particular in primary care, due to the need to face the growing burden of chronic diseases. Health services research can compare and evaluate local initiatives on the basis of the common healthcare administrative data.However reliability of such data in this context needs to be assessed, especially when comparing different regions of the country. In this paper we investigated the validity of healthcare administrative databases to compute indicators of compliance with standards of care for diabetes, ischaemic heart disease (IHD) and heart failure (HF)., Methods: We compared indicators estimated from healthcare administrative data collected by Local Health Authorities in five Italian regions with corresponding estimates from clinical data collected by General Practitioners (GPs). Four indicators of diagnostic follow-up (two for diabetes, one for IHD and one for HF) and four indicators of appropriate therapy (two each for IHD and HF) were considered., Results: Agreement between the two data sources was very good, except for indicators of laboratory diagnostic follow-up in one region and for the indicator of bioimaging diagnostic follow-up in all regions, where measurement with administrative data underestimated quality., Conclusion: According to evidence presented in this study, estimating compliance with standards of care for diabetes, ischaemic heart disease and heart failure from healthcare databases is likely to produce reliable results, even though completeness of data on diagnostic procedures should be assessed first. Performing studies comparing regions using such indicators as outcomes is a promising development with potential to improve quality governance in the Italian healthcare system.

Background: Our interest in chronic conditions is due to the fact that, worldwide, chronic diseases have overtaken infectious diseases as the leading cause of death and disability, so their management represents an important challenge for health systems. The aim of this study was to compare the performance of primary health care services in managing diabetes, congestive heart failure (CHF) and coronary heart disease (CHD), by age group., Methods: This population-based retrospective cohort study was conducted in Italy, enrolling 1,948,622 residents ≥ 16 years old. A multilevel regression model was applied to analyze compliance to care processes with explanatory variables at both patient and district level, using age group as an independent variable, and adjusting for sex, citizenship, disease duration, and Charlson index on the first level, and for District Health Unit on the second level., Results: The quality of chronic disease management showed an inverted U-shaped relationship with age. In particular, our findings indicate lower levels for young adults (16-44 year-olds), adults (45-64), and oldest old (+85) than for patients aged 65-74 in almost all quality indicators of CHD, CHF and diabetes management. Young adults (16-44 y), adults (45-64 y), the very old (75-84 y) and the oldest old (+85 y) patients with CHD, CHF and diabetes are less likely than 65-74 year-old patients to be monitored and treated using evidence-based therapies, with the exceptions of echocardiographic monitoring for CHF in young adult patients, and renal monitoring for CHF and diabetes in the very old., Conclusion: Our study shows that more effort is needed to ensure that primary health care systems are sensitive to chronic conditions in the young and in the very elderly.

Background: For chronic conditions, disparities can take effect cumulatively at various times as the disease progresses, even when care is provided. The aim of this study was to quantify the prevalence of diabetes, congestive heart failure (CHF) and coronary heart disease (CHD) in adults by citizenship, and to compare the performance of primary care services in managing these chronic conditions, again by citizenship., Methods: This is a population-based retrospective cohort study on 1,948,622 people aged 16 years or more residing in Italy. A multilevel regression model was applied to analyze adherence to care processes using explanatory variables at both patient and district level., Results: The age-adjusted prevalence of diabetes was found higher among immigrants from high migratory pressure countries (HMPC) than among Italians, while the age-adjusted prevalence of CHD and CHF was higher for Italians than for HMPC immigrants or those from highly-developed countries (HDC). Our results indicate lower levels in all quality management indicators for citizens from HMPC than for Italians, for all the chronic conditions considered. Patients from HDC did not differ from Italian in their adherence to disease management schemes., Conclusion: This study revealed a different prevalence of chronic diseases by citizenship, implying a different burden of primary care by citizenship. Our findings show that more effort is needed to guarantee migrant-sensitive primary health care.