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Abstract Background Administrative databases are widely available and have been extensively used to provide estimates of chronic disease prevalence for the purpose of surveillance of both geographical and temporal trends. There are, however, other sources of data available, such as medical records from primary care and national surveys. In this paper we compare disease prevalence estimates obtained from these three different data sources. Methods Data from general practitioners (GP) and administrative transactions for health services were collected from five Italian regions (Veneto, Emilia Romagna, Tuscany, Marche and Sicily) belonging to all the three macroareas of the country (North, Center, South). Crude prevalence estimates were calculated by data source and region for diabetes, ischaemic heart disease, heart failure and chronic obstructive pulmonary disease (COPD). For diabetes and COPD, prevalence estimates were also obtained from a national health survey. When necessary, estimates were adjusted for completeness of data ascertainment. Results Crude prevalence estimates of diabetes in administrative databases (range: from 4.8% to 7.1%) were lower than corresponding GP (6.2%-8.5%) and survey-based estimates (5.1%-7.5%). Geographical trends were similar in the three sources and estimates based on treatment were the same, while estimates adjusted for completeness of ascertainment (6.1%-8.8%) were slightly higher. For ischaemic heart disease administrative and GP data sources were fairly consistent, with prevalence ranging from 3.7% to 4.7% and from 3.3% to 4.9%, respectively. In the case of heart failure administrative estimates were consistently higher than GPs’ estimates in all five regions, the highest difference being 1.4% vs 1.1%. For COPD the estimates from administrative data, ranging from 3.1% to 5.2%, fell into the confidence interval of the Survey estimates in four regions, but failed to detect the higher prevalence in the most Southern region (4.0% in administrative data vs 6.8% in survey data). The prevalence estimates for COPD from GP data were consistently higher than the corresponding estimates from the other two sources. Conclusion This study supports the use of data from Italian administrative databases to estimate geographic differences in population prevalence of ischaemic heart disease, treated diabetes, diabetes mellitus and heart failure. The algorithm for COPD used in this study requires further refinement.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

Objectives: the Italian National Prevention Plan (PNP) posed the standard to be achieved by Italian Regions for the implementation of cervical, breast, and colorectal cancer screening: to invite all of the target populations and to increase the screening uptake up to 50%, 60%, and 50%, respectively, the standard defined by the Essential Levels of Care (LEA). Moreover, for cervical cancer screening, it requires the implementation of HPV-DNA test and, for breast cancer screening, the PNP demands for the definition of diagnostic and follow up pathways for high familial risk women. The PNP also set up a monitoring system to assess the impact of implemented policies. A conceptual model has been defined to facilitate interpretation of variation in outcome indicators., Design: after a systematic review, the DPSEEA (Driving forces, Pressure, State, Exposure, Effect, Actions) was identified as the more appropriate framework to assess the results of preventive policies. Factors for each component of the model were identified and indicators that allow measuring the changing of each of these factors were defined., Results: among the "driving forces", the trust in the health care system and the social capital were included. The presence of opportunistic screening, the competing private clinical activity, the commitment of General Practitioners and "medical" leaders, the attitude to cooperation and to patients' involvement, and the level of agreement between the positions of scientific societies and the recommendations implemented in organized screening programmes were included in the "pressures". In "state", the availability of technological and human resources, the level of management skills and of accessibility were identified. The "exposure" was defined as the coverage of active invitation of the target population and the uptake of screening tests. The "exposure" factors influence the "effect", described as the impact on anticipation of cancer diagnosis, on disease incidence (for cervical and colorectal cancer) and prognosis. The changing in screening programs performance modifies the impact of invitation coverage and test uptake ("exposure")., Conclusions: through the DPSEEA framework, we set up a logical conceptual model, which includes implementable actions and the mechanisms through which these actions should impact on the "exposure" (invitation coverage and screening uptake) and on the screening performance (quality).

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.