Mariadonata Bellentani

Chronic disease prevalence from Italian administrative databases in the VALORE project: A validation through comparison of population estimates with general practice databases and national survey

BackgroundAdministrative 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.MethodsData 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.ResultsCrude 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.ConclusionThis 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.

Can italian healthcare administrative databases be used to compare regions with respect to compliance with standards of care for chronic diseases

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.

Data Extraction and Management in Networks of Observational Health Care Databases for Scientific Research: A Comparison of EU-ADR, OMOP, Mini-Sentinel and MATRICE Strategies

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.

Need and disparities in primary care management of patients with diabetes

BackgroundAn 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.MethodsA 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.Results1,948,622 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.ConclusionsProcess 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.

Automatic identification of type 2 diabetes, hypertension, ischaemic heart disease, heart failure and their levels of severity from Italian General Practitioners' electronic medical records: a validation study

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 GPs response to the questionnaire, and Cohens 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. Cohens 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.

Prevalence of Heart Failure and Adherence to Process Indicators: Which Socio-Demographic Determinants are Involved?

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.

Monitoring compliance with standards of care for chronic diseases using healthcare administrative databases in Italy: Strengths and limitations

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 GPs 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.