Medical record linkage in health information systems by approximate string matching and clustering

BACKGROUND: Multiplication of data sources within heterogeneous healthcare information systems always results in redundant information, split among multiple databases. Our objective is to detect exact and approximate duplicates within identity records, in order to attain a better quality of information and to permit cross-linkage among stand-alone and clustered databases. Furthermore, we need to assist human decision making, by computing a value reflecting identity proximity. METHODS: The proposed method is in three steps. The first step is to standardise and to index elementary identity fields, using blocking variables, in order to speed up information analysis. The second is to match similar pair records, relying on a global similarity value taken from the Porter-Jaro-Winkler algorithm. And the third is to create clusters of coherent related records, using graph drawing, agglomerative clustering methods and partitioning methods. RESULTS: The batch analysis of 300,000 "supposedly" distinct identities isolates 240,000 true unique records, 24,000 duplicates (clusters composed of 2 records) and 3,000 clusters whose size is greater than or equal to 3 records. CONCLUSION: Duplicate-free databases, used in conjunction with relevant indexes and similarity values, allow immediate (i.e.: real-time) proximity detection when inserting a new identity

A Spatio-temporal model for cancer incidence data with zero-inflation

In this work we consider a joint space-time model for cancer incidence, using data on prostate cancer collected between 1988 and 2005 in a specific area of France. Our aim is to take into account possible non linear effects of some covariates and zero-inflation due to data aggregation for Poisson regression. We assume that counts of cancer cases follow zero-inflated Poisson distribution, where the probability of zero inflation is a monotonic function of the mean. The purpose of our analysis is to check whether the French prostate screening programme, which begins in 1994, results in a spatial or a spatial-temporal change of the pattern of the disease

Resources allocation in healthcare for cancer: a case study using generalised additive mixed models

Abstract. Our aim is to develop a method for helping resources re-allocation in healthcare linked to cancer, in order to replan the allocation of providers. Ageing of the population has a considerable impact on the use of health resources because aged people require more specialised medical care due notably to cancer. We propose a method useful to monitor changes of cancer incidence in space and time taking into account two age categories, according to healthcar general organisation. We use generalised additive mixed models with a Poisson response, according to the methodology presented in Wood, Generalised additive models: an introduction with R. Chapman and Hall/CRC, 2006. Besides one-dimensional smooth functions accounting for non-linear effects of covariates, the space-time interaction can be modelled using scale invariant smoothers. Incidence data collected by a general cancer registry between 1992 and 2007 in a specific area of France is studied. Our best model exhibits a strong increase of the incidence of cancer along time and an obvious spatial pattern for people more than 70 years with a higher incidence in the central band of the region. This is a strong argument for re-allocating resources for old people cancer care in this sub-region

A Bayesian analysis of relative cancer survival with geoadditive models

In this paper, we develop a so-called relative survival analysis that is used to model the excess risk of a certain sub-population relative to the natural mortality risk which is present in the whole population. Such models are typically used in population-based studies that aim at identifying prognostic factors for disease-specific mortality, with data on specific causes of death not being available. This paper combines relative survival with Bayesian geoadditive regression allowing for a flexible semiparametric analysis. Our work has been motivated by continuous-time spatially referenced survival data on breast cancer where causes of death are not known. A detailed analysis of these data is given. The usefulness of the approach is further illustrated by means of a simulated data set

Multilocus sequence typing of clinical Borreliella afzelii strains: population structure and differential ability to disseminate in humans

Abstract Background Lyme borreliosis in humans results in a range of clinical manifestations, thought to be partly due to differences in the pathogenicity of the infecting strain. This study compared European human clinical strains of Borreliella afzelii (previously named Borrelia afzelii) using multilocus sequence typing (MLST) to determine their spatial distribution across Europe and to establish whether there are associations between B. afzelii genotypes and specific clinical manifestations of Lyme borreliosis. For this purpose, typing was performed on 63 strains, and data on a further 245 strains were accessed from the literature. Results All 308 strains were categorized into 149 sequence types (STs), 27 of which are described here for the first time. Phylogenetic and goeBURST analyses showed short evolutionary distances between strains. Although the main STs differed among the countries with the largest number of strains of interest (Germany, the Netherlands, France and Slovenia), the B. afzelii clinical strains were less genetically structured than those previously observed in the European tick population. Two STs were found significantly more frequently in strains associated with clinical manifestations involving erythema migrans, whereas another ST was found significantly more frequently in strains associated with disseminated manifestations, especially neuroborreliosis. Conclusions The MLST profiles showed low genetic differentiation between B. afzelii strains isolated from patients with Lyme borreliosis in Europe. Also, clinical data analysis suggests the existence of lineages with differential dissemination properties in humans

Long-term cognitive outcome of Alzheimer’s disease and dementia with Lewy bodies: dual disease is worse

Abstract Background Longitudinal studies of dementia with Lewy bodies (DLB) are rare. Clinically, DLB is usually considered to worsen into Alzheimer’s disease (AD). The aim of our study was to compare the rate of the cognitive decline in DLB, AD, and the association of the two diseases (AD + DLB). Methods Using the Regional Network for Diagnostic Aid and Management of Patients with Cognitive Impairment database, which includes all the patients seen at all memory clinics (medical consultation and day hospitals) in four French regions, and beta regression, we compared the longitudinal the Mini-Mental State Examination scores of 1159 patients with AD (n = 1000), DLB (n = 131) and AD + DLB (association of the two) (n = 28) during follow-up of at least 4 years. Results The mean follow-up of the patients was 5.88 years. Using beta regression without propensity scores, the comparison of the decline of patients with AD and patients with DLB did not show a significant difference, but the decline of patients with AD + DLB was worse than that of either patients with DLB (P = 0.006) or patients with AD (P < 0.001). Using beta regression weighted by a propensity score, comparison of patients with AD and patients with DLB showed a faster decline for patients with DLB (P < 0.001). The comparison of the decline of patients with AD + DLB with that of patients with DLB (P < 0.001) and patients with AD (P < 0.001) showed that the decline was clearly worse in the patients with dual disease. Conclusions Whatever the analysis, the rate of decline is faster in patients with AD + DLB dual disease. The identification of such patients is important to enable clinicians to optimise treatment and care and to better inform and help patients and caregivers