The reliability of hospital and pharmaceutical data to assess prevalent cases of chronic obstructive pulmonary disease

Inhaled Medications in Chronic Respiratory Diseases: Analysis of Real-Life Use in Puglia (Apulia), Italy

BACKGROUND

Chronic respiratory diseases (CRDs) are common diseases with a heterogeneous distribution worldwide. Due to their impact on disability, weight assistance and pharmaceutical spending, they represent an important global burden for national health systems. However, few studies have investigated the use and consumption of inhaled drugs in real life in patients with CRDs.

OBJECTIVE

This study aimed to investigate the real-life consumption of health care resources of main CRDs through an analysis of the administrative databases of the local health authority (ASL) in the Puglia region (Italy).

METHODS

The present study is an observational study that longitudinally reviewed the administrative and health databases associated with patients' consumption of health resources between 2017 and 2018.

RESULTS

The first important finding is a marked underestimation of the true incidence of CRDs despite the search for disease-specific exemption codes. Another important result is that the real-life consumption of inhaled drugs among these patients is well below the minimum acceptable values for adherence. The most commonly used inhaled drugs, for which at least one pack was withdrawn, were inhaled steroids (61.6%), followed by the ICS/LABA combination (43.7%) and LABAs (32.4%). However, less than one-third of patients (31%) withdrew at least three packages of ICS or ICS/LABA during the year, while the percentage was reduced to less than 15% for other combinations. Another alarming finding is that only 8.4% of patients taking CRDs drugs reported at least one spirometry during the study period.

CONCLUSIONS

The wide availability of computerized systems may be an important tool for increasing therapeutic adherence and optimizing the resources of health systems in the diagnosis, treatment and management of patients with CRDs.

High quality process of care increases one-year survival after acute myocardial infarction (AMI): A cohort study in Italy

Background

The relationship between guideline adherence and outcomes in patients with acute myocardial infarction (AMI) has been widely investigated considering the emergency, acute, post-acute phases separately, but the effectiveness of the whole care process is not known.

Aim

The study aim was to evaluate the effect of the multicomponent continuum of care on 1-year survival after AMI.

Methods

We conducted a cohort study selecting all incident cases of AMI from health information systems during 2011–2014 in the Lazio region. Patients’ clinical history was defined by retrieving previous hospitalizations and drugs prescriptions. For each subject the probability to reach the hospital and the conditional probabilities to survive to 30 days from admission and to 31–365 days post discharge were estimated through multivariate logistic models. The 1-year survival probability was calculated as the product of the three probabilities. Quality of care indicators were identified in terms of emergency timeliness (time between residence and the nearest hospital), hospital performance in treatment of acute phase (number/timeliness of PCI on STEMI) and drug therapy in post-acute phase (number of drugs among antiplatelet, β-blockers, ACE inhibitors/ARBs, statins). The 1-year survival Probability Ratio (PR) and its Bootstrap Confidence Intervals (BCI) between who were exposed to the highest level of quality of care (timeliness<10', hospitalization in high performance hospital, complete drug therapy) and who exposed to the worst (timeliness≥10', hospitalization in low performance hospital, suboptimal drug therapy) were calculated for a mean-severity patient and varying gender and age. PRs for patients with diabetes and COPD were also evaluated.

Results

We identified 38,517 incident cases of AMI. The out-of-hospital mortality was 27.6%. Among the people arrived in hospital, 42.9% had a hospitalization for STEMI with 11.1% of mortality in acute phase and 5.4% in post-acute phase. For a mean-severity patient the PR was 1.19 (BCI 1.14–1.24). The ratio did not change by gender, while it moved from 1.06 (BCI 1.05–1.08) for age<65 years to 1.62 (BCI 1.45–1.80) for age >85 years. For patients with diabetes and COPD a slight increase in PRs was also observed.

Conclusions

The 1-year survival probability post AMI depends strongly on the quality of the whole multicomponent continuum of care. Improving the performance in the different phases, taking into account the relationship among these, can lead to considerable saving of lives, in particular for the elderly and for subjects with chronic diseases.

Administrative databases and clinical governance: The case of COPD

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. However, COPD is still underdiagnosed, undertreated, and not sufficiently prevented. Health administrative databases provide a powerful way of studying COPD in the population.

METHODS

This retrospective study used administrative data, collected during 2011 and 2012, retrieved from 3 Italian local health authorities (LHAs).

RESULTS

The analysis through administrative databases allowed firstly to identify patients with COPD receiving services by the 3 LHAs: The estimated average is ~3% of the population aged ≥40 years. Furthermore, it was also possible to stratify patients by investigating the health consumption in hospitalization for COPD and use of respiratory drugs. In all 3 LHA patients with moderate COPD were the majority of the population with COPD. Finally, it was possible to distinguish patients who made an appropriate use of SABA (76% of the total), patients who had a potentially inappropriate use (20%), and those with an overuse of SABA (4%).

CONCLUSION

The use of SABA consumption patterns can be a reliable proxy variable to detect subgroups who may necessitate therapy revision. Health administrative databases seem beneficial for planning health care interventions, including the COPD field. They are robust information systems subjected to regular data quality controls remaining the prevalent data source, reliable because of the amount of data and the population coverage, especially in countries with a National Health Service System.

Combining information from a clinical data warehouse and a pharmaceutical database to generate a framework to detect comorbidities in electronic health records

Background

Medical coding is used for a variety of activities, from observational studies to hospital billing. However, comorbidities tend to be under-reported by medical coders. The aim of this study was to develop an algorithm to detect comorbidities in electronic health records (EHR) by using a clinical data warehouse (CDW) and a knowledge database.

Methods

We enriched the Theriaque pharmaceutical database with the French national Comorbidities List to identify drugs associated with at least one major comorbid condition and diagnoses associated with a drug indication. Then, we compared the drug indications in the Theriaque database with the ICD-10 billing codes in EHR to detect potentially missing comorbidities based on drug prescriptions. Finally, we improved comorbidity detection by matching drug prescriptions and laboratory test results. We tested the obtained algorithm by using two retrospective datasets extracted from the Rennes University Hospital (RUH) CDW. The first dataset included all adult patients hospitalized in the ear, nose, throat (ENT) surgical ward between October and December 2014 (ENT dataset). The second included all adult patients hospitalized at RUH between January and February 2015 (general dataset). We reviewed medical records to find written evidence of the suggested comorbidities in current or past stays.

Results

Among the 22,132 Common Units of Dispensation (CUD) codes present in the Theriaque database, 19,970 drugs (90.2%) were associated with one or several ICD-10 diagnoses, based on their indication, and 11,162 (50.4%) with at least one of the 4878 comorbidities from the comorbidity list. Among the 122 patients of the ENT dataset, 75.4% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the algorithm were confirmed in 44.6% of the cases. Among the 4312 patients of the general dataset, 68.4% had at least one drug prescription without corresponding ICD-10 code. The comorbidity diagnoses suggested by the algorithm were confirmed in 20.3% of reviewed cases.

Conclusions

This simple algorithm based on combining accessible and immediately reusable data from knowledge databases, drug prescriptions and laboratory test results can detect comorbidities.

Electronic supplementary material

The online version of this article (10.1186/s12911-018-0586-x) contains supplementary material, which is available to authorized users.

Protocol for validating cardiovascular and cerebrovascular ICD-9-CM codes in healthcare administrative databases: the Umbria Data Value Project

INTRODUCTION

Administrative healthcare databases can provide a comprehensive assessment of the burden of diseases in terms of major outcomes, such as mortality, hospital readmissions and use of healthcare resources, thus providing answers to a wide spectrum of research questions. However, a crucial issue is the reliability of information gathered. Aim of this protocol is to validate International Classification of Diseases, 9th Revision-Clinical Modification (ICD-9-CM) codes for major cardiovascular diseases, including acute myocardial infarction (AMI), heart failure (HF), atrial fibrillation (AF) and stroke.

METHODS AND ANALYSIS

Data from the centralised administrative database of the entire Umbria Region (910 000 residents, located in Central Italy) will be considered. Patients with a first hospital discharge for AMI, HF, AF or stroke, between 2012 and 2014, will be identified in the administrative database using the following groups of ICD-9-CM codes located in primary position: (1) 410.x for AMI; (2) 427.31 for AF; (3) 428 for HF; (4) 433.x1, 434 (excluding 434.x0), 436 for ischaemic stroke, 430 and 431 for haemorrhagic stroke (subarachnoid haemorrhage and intracerebral haemorrhage). A random sample of cases, and of non-cases, will be selected, and the corresponding medical charts retrieved and reviewed for validation by pairs of trained, independent reviewers. For each condition considered, case adjudication of disease will be based on symptoms, laboratory and diagnostic tests, as available in medical charts. Divergences will be resolved by consensus. Sensitivity and specificity with 95% CIs will be calculated.

ETHICS AND DISSEMINATION

Research protocol has been granted approval by the Regional Ethics Committee. Study results will be disseminated widely through peer-reviewed publications and presentations at national and international conferences.

Can healthcare utilization data reliably capture cases of chronic respiratory diseases? a cross-sectional investigation in Italy

BACKGROUND

Healthcare utilization data are increasingly used for chronic disease surveillance. Nevertheless, no standard criteria for estimating prevalence of high-impact diseases, such as chronic obstructive pulmonary disease (COPD) and asthma, are available. In this study an algorithm for recognizing COPD/asthma cases from HCU data is developed and implemented in the HCU databases of the Italian Lombardy Region (about 10 million residents). The impact of diagnostic misclassification for reliably estimating prevalence was also assessed.

METHODS

Disease-specificdrug codes, hospital discharges together with co-payment exemptions when available, and a combination of them according with patient's age, were used to create the proposed algorithm. Identified cases were considered for prevalence estimation. An external validation study was also performed in order to evaluate systematic uncertainty of prevalence estimates.

RESULTS

Raw prevalence of COPD and asthma in 2010 was 3.6 and 3.3% respectively. According to external validation, sensitivity values were 53% for COPD and 39% for asthma. Adjusted prevalence estimates were respectively 6.8 and 8.5% for COPD (among person aged 40 years or older) and asthma (among person aged 40 years or younger).

CONCLUSIONS

COPD and asthma prevalence may be estimated from HCU data, albeit with high systematic uncertainty. Validation is recommended in this setting.

Validation of chronic obstructive pulmonary disease (COPD) diagnoses in healthcare databases: a systematic review protocol

INTRODUCTION

Healthcare databases are useful sources to investigate the epidemiology of chronic obstructive pulmonary disease (COPD), to assess longitudinal outcomes in patients with COPD, and to develop disease management strategies. However, in order to constitute a reliable source for research, healthcare databases need to be validated. The aim of this protocol is to perform the first systematic review of studies reporting the validation of codes related to COPD diagnoses in healthcare databases.

METHODS AND ANALYSIS

MEDLINE, EMBASE, Web of Science and the Cochrane Library databases will be searched using appropriate search strategies. Studies that evaluated the validity of COPD codes (such as the International Classification of Diseases 9th Revision and 10th Revision system; the Real codes system or the International Classification of Primary Care) in healthcare databases will be included. Inclusion criteria will be: (1) the presence of a reference standard case definition for COPD; (2) the presence of at least one test measure (eg, sensitivity, positive predictive values, etc); and (3) the use of a healthcare database (including administrative claims databases, electronic healthcare databases or COPD registries) as a data source. Pairs of reviewers will independently abstract data using standardised forms and will assess quality using a checklist based on the Standards for Reporting of Diagnostic accuracy (STARD) criteria. This systematic review protocol has been produced in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P) 2015 statement.

ETHICS AND DISSEMINATION

Ethics approval is not required. Results of this study will be submitted to a peer-reviewed journal for publication. The results from this systematic review will be used for outcome research on COPD and will serve as a guide to identify appropriate case definitions of COPD, and reference standards, for researchers involved in validating healthcare databases.

TRIAL REGISTRATION NUMBER

CRD42015029204.

Validity of ICD-9-CM codes for breast, lung and colorectal cancers in three Italian administrative healthcare databases: a diagnostic accuracy study protocol

INTRODUCTION

Administrative healthcare databases are useful tools to study healthcare outcomes and to monitor the health status of a population. Patients with cancer can be identified through disease-specific codes, prescriptions and physician claims, but prior validation is required to achieve an accurate case definition. The objective of this protocol is to assess the accuracy of International Classification of Diseases Ninth Revision-Clinical Modification (ICD-9-CM) codes for breast, lung and colorectal cancers in identifying patients diagnosed with the relative disease in three Italian administrative databases.

METHODS AND ANALYSIS

Data from the administrative databases of Umbria Region (910,000 residents), Local Health Unit 3 of Napoli (1,170,000 residents) and Friuli--Venezia Giulia Region (1,227,000 residents) will be considered. In each administrative database, patients with the first occurrence of diagnosis of breast, lung or colorectal cancer between 2012 and 2014 will be identified using the following groups of ICD-9-CM codes in primary position: (1) 233.0 and (2) 174.x for breast cancer; (3) 162.x for lung cancer; (4) 153.x for colon cancer and (5) 154.0-154.1 and 154.8 for rectal cancer. Only incident cases will be considered, that is, excluding cases that have the same diagnosis in the 5 years (2007-2011) before the period of interest. A random sample of cases and non-cases will be selected from each administrative database and the corresponding medical charts will be assessed for validation by pairs of trained, independent reviewers. Case ascertainment within the medical charts will be based on (1) the presence of a primary nodular lesion in the breast, lung or colon-rectum, documented with imaging or endoscopy and (2) a cytological or histological documentation of cancer from a primary or metastatic site. Sensitivity and specificity with 95% CIs will be calculated.

DISSEMINATION

Study results will be disseminated widely through peer-reviewed publications and presentations at national and international conferences.

How Reliable Are Current Data for Assessing the Actual Prevalence of Chronic Obstructive Pulmonary Disease?

Background

Estimating COPD occurrence is perceived by the scientific community as a matter of increasing interest because of the worldwide diffusion of the disease. We aimed to estimate COPD prevalence by using administrative databases from a city in central Italy for 2002–2006, improving both the sensitivity and the reliability of the estimate.

Methods

Multiple sources were used, integrating the hospital discharge register (HDR), clinical charts, spirometry and the cause-specific mortality register (CMR) in a longitudinal algorithm, to reduce underestimation of COPD prevalence. Prevalence was also estimated on the basis of COPD cases confirmed through spirometry, to correct misclassification. Estimating such prevalence relied on using coefficients of validation, derived as the positive predictive value (PPV) for being an actual COPD case from clinical and spirometric data at the Institute of Clinical Physiology of the National Research Council.

Results

We found that sensitivity of COPD prevalence increased by 37%. The highest estimate (4.43 per 100 residents) was observed in the 5-year period, using a 3-year longitudinal approach and combined data from three sources. We found that 17% of COPD cases were misclassified. The above estimate of COPD prevalence decreased (3.66 per 100 residents) when coefficients of validation were applied. The PPV was 80% for the HDR, 82% for clinical diagnoses and 91% for the CMR.

Conclusions

Adjusting the COPD prevalence for both underestimation and misclassification of the cases makes administrative data more reliable for epidemiological purposes.

Occurrence of inflammatory bowel disease in central Italy: a study based on health information systems

BACKGROUND

The burden of inflammatory bowel diseases, including Crohn's disease and ulcerative colitis, has never been estimated in Italy using administrative data sources. Our objective was to measure the occurrence of inflammatory bowel diseases in the Lazio region (Italy) using administrative data and to test the sensitivity of the Crohn's disease case-finding algorithm with respect to clinical diagnosis.

METHODS

We conducted a population-based cross-sectional study identifying prevalent and incident cases. We estimated occurrence rates of inflammatory bowel diseases using hospital discharges or activation of copayment exemptions. Sensitivity was calculated from 2358 subjects with clinical diagnosis of Crohn's disease.

RESULTS

Exemptions identified more than 20% of the cases. Prevalence rates (per 100,000) on December 31, 2009 for males and females were 177 and 144 for ulcerative colitis and 91 and 81 for Crohn's disease, respectively. The incidence rates during the years 2008-2009 were 14.5 and 12.2 for ulcerative colitis and 7.4 and 6.5 for Crohn's disease for males and females, respectively. The sensitivity of the administrative sources was 82.2%.

CONCLUSIONS

Health and population data sources allow the estimation of inflammatory bowel diseases occurrence. The age-specific peaks of diagnosis were consistent with those reported in other studies. Sensitivity may be affected by temporal changes in the quality of the data sources.

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

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.