8 research outputs found

    Individuals tell a fascinating story: using unsupervised text mining methods to cluster policyholders based on their medical history

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    Background and objective: Classifying people according to their health profile is crucial in order to propose appropriate treatment. However, the medical diagnosis is sometimes not available. This is for example the case in health insurance, making the proposal of custom prevention plans difficult. When this is the case, an unsupervised clustering method is needed. This article aims to compare three different methods by adapting some text mining methods to the field of health insurance. Also, a new clustering stability measure is proposed in order to compare the stability of the tested processes. Methods : Nonnegative Matrix Factorization, the word2vec method, and marginalized Stacked Denoising Autoencoders are used and compared in order to create a high-quality input for a clustering method. A self-organizing map is then used to obtain the final clustering. A real health insurance database is used in order to test the methods. Results: the marginalized Stacked Denoising Autoencoder outperforms the other methods both in stability and result quality with our data. Conclusions: The use of text mining methods offers several possibilities to understand the context of any medical act. On a medical database, the process could reveal unexpected correlation between treatment, and thus, pathology. Moreover, this kind of method could exploit the refund dates contained in the data, but the tested method using temporality, word2vec, still needs to be improved since the results, even if satisfying, are not as better as the one offered by other methods

    La psychiatrie : un risque important en assurance santé ?

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    The French Social Security has highlighted psychiatric diseases as a major risk. However, French private health insurance companies do not consider psychiatric care as an important topic. In this article is presented a study (based on four real health insurance databases) of the cost of a policyholder benefiting from a psychiatric follow-up care. It aims to provide a better understanding of this risk in an insurance context. It is shown that such a policyholder costs twice as much as an average policyholder, notably due to important expenses in hospitalization. Policyholders aged from 15 to 30 years, as well as the ones over 70 years old are the most concerned by this risk.La psychiatrie a été identifiée par la Sécurité Sociale comme un enjeu majeur. Pourtant, celle-ci n'est pas identifiée comme un risque important par les organismes d'assurance santé complémentaire, si bien qu'aucune étude n'a été publiée en France sur sa prise en charge en dehors de l'Assurance Maladie. Cet article présente le résultat de travaux réalisés à partir de quatre bases de données regroupant les prestations versées par des complémentaires santé. L'objectif de cette analyse consiste à mieux comprendre ce risque et évaluer son coût pour les complémentaires santé. Cette étude permet de conclure qu'un assuré identifié comme étant suivi par un psychiatre présente un coût médical à la charge de l'assureur deux fois supérieur à celui d'un assuré moyen, notamment à cause de fortes dépenses en hospitalisation non psychiatrique. Les personnes ayant entre 15 et 30 ans et les séniors sont les plus concernés par ce risque

    COVID-19 outcomes in patients with inflammatory rheumatic and musculoskeletal diseases treated with rituximab: a cohort study

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    International audienceBackground: Various observations have suggested that the course of COVID-19 might be less favourable in patients with inflammatory rheumatic and musculoskeletal diseases receiving rituximab compared with those not receiving rituximab. We aimed to investigate whether treatment with rituximab is associated with severe COVID-19 outcomes in patients with inflammatory rheumatic and musculoskeletal diseases.Methods: In this cohort study, we analysed data from the French RMD COVID-19 cohort, which included patients aged 18 years or older with inflammatory rheumatic and musculoskeletal diseases and highly suspected or confirmed COVID-19. The primary endpoint was the severity of COVID-19 in patients treated with rituximab (rituximab group) compared with patients who did not receive rituximab (no rituximab group). Severe disease was defined as that requiring admission to an intensive care unit or leading to death. Secondary objectives were to analyse deaths and duration of hospital stay. The inverse probability of treatment weighting propensity score method was used to adjust for potential confounding factors (age, sex, arterial hypertension, diabetes, smoking status, body-mass index, interstitial lung disease, cardiovascular diseases, cancer, corticosteroid use, chronic renal failure, and the underlying disease [rheumatoid arthritis vs others]). Odds ratios and hazard ratios and their 95% CIs were calculated as effect size, by dividing the two population mean differences by their SD. This study is registered with ClinicalTrials.gov, NCT04353609.Findings: Between April 15, 2020, and Nov 20, 2020, data were collected for 1090 patients (mean age 55·2 years [SD 16·4]); 734 (67%) were female and 356 (33%) were male. Of the 1090 patients, 137 (13%) developed severe COVID-19 and 89 (8%) died. After adjusting for potential confounding factors, severe disease was observed more frequently (effect size 3·26, 95% CI 1·66-6·40, p=0·0006) and the duration of hospital stay was markedly longer (0·62, 0·46-0·85, p=0·0024) in the 63 patients in the rituximab group than in the 1027 patients in the no rituximab group. 13 (21%) of 63 patients in the rituximab group died compared with 76 (7%) of 1027 patients in the no rituximab group, but the adjusted risk of death was not significantly increased in the rituximab group (effect size 1·32, 95% CI 0·55-3·19, p=0·53).Interpretation: Rituximab therapy is associated with more severe COVID-19. Rituximab will have to be prescribed with particular caution in patients with inflammatory rheumatic and musculoskeletal diseases

    Severity of COVID-19 and survival in patients with rheumatic and inflammatory diseases: data from the French RMD COVID-19 cohort of 694 patients

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    International audienceObjectives: There is little known about the impact of SARS-CoV-2 on patients with inflammatory rheumatic and musculoskeletal diseases (iRMD). We examined epidemiological characteristics associated with severe disease, then with death. We also compared mortality between patients hospitalised for COVID-19 with and without iRMD.Methods: Individuals with suspected iRMD-COVID-19 were included in this French cohort. Logistic regression models adjusted for age and sex were used to estimate adjusted ORs and 95% CIs of severe COVID-19. The most significant clinically relevant factors were analysed by multivariable penalised logistic regression models, using a forward selection method. The death rate of hospitalised patients with iRMD-COVID-19 (moderate-severe) was compared with a subset of patients with non-iRMD-COVID-19 from a French hospital matched for age, sex, and comorbidities.Results: Of 694 adults, 438 (63%) developed mild (not hospitalised), 169 (24%) moderate (hospitalised out of the intensive care unit (ICU) and 87 (13%) severe (patients in ICU/deceased) disease. In multivariable imputed analyses, the variables associated with severe infection were age (OR=1.08, 95% CI: 1.05-1.10), female gender (OR=0.45, 95% CI: 0.25-0.80), body mass index (OR=1.07, 95% CI: 1.02-1.12), hypertension (OR=1.86, 95% CI: 1.01-3.42), and use of corticosteroids (OR=1.97, 95% CI: 1.09-3.54), mycophenolate mofetil (OR=6.6, 95% CI: 1.47-29.62) and rituximab (OR=4.21, 95% CI: 1.61-10.98). Fifty-eight patients died (8% (total) and 23% (hospitalised)). Compared with 175 matched hospitalised patients with non-iRMD-COVID-19, the OR of mortality associated with hospitalised patients with iRMD-COVID-19 was 1.45 (95% CI: 0.87-2.42) (n=175 each group).Conclusions: In the French RMD COVID-19 cohort, as already identified in the general population, older age, male gender, obesity, and hypertension were found to be associated with severe COVID-19. Patients with iRMD on corticosteroids, but not methotrexate, or tumour necrosis factor alpha and interleukin-6 inhibitors, should be considered as more likely to develop severe COVID-19. Unlike common comorbidities such as obesity, and cardiovascular or lung diseases, the risk of death is not significantly increased in patients with iRMD

    Severity of COVID-19 and survival in patients with rheumatic and inflammatory diseases: data from the French RMD COVID-19 cohort of 694 patients

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    International audienceObjectives: There is little known about the impact of SARS-CoV-2 on patients with inflammatory rheumatic and musculoskeletal diseases (iRMD). We examined epidemiological characteristics associated with severe disease, then with death. We also compared mortality between patients hospitalised for COVID-19 with and without iRMD.Methods: Individuals with suspected iRMD-COVID-19 were included in this French cohort. Logistic regression models adjusted for age and sex were used to estimate adjusted ORs and 95% CIs of severe COVID-19. The most significant clinically relevant factors were analysed by multivariable penalised logistic regression models, using a forward selection method. The death rate of hospitalised patients with iRMD-COVID-19 (moderate-severe) was compared with a subset of patients with non-iRMD-COVID-19 from a French hospital matched for age, sex, and comorbidities.Results: Of 694 adults, 438 (63%) developed mild (not hospitalised), 169 (24%) moderate (hospitalised out of the intensive care unit (ICU) and 87 (13%) severe (patients in ICU/deceased) disease. In multivariable imputed analyses, the variables associated with severe infection were age (OR=1.08, 95% CI: 1.05-1.10), female gender (OR=0.45, 95% CI: 0.25-0.80), body mass index (OR=1.07, 95% CI: 1.02-1.12), hypertension (OR=1.86, 95% CI: 1.01-3.42), and use of corticosteroids (OR=1.97, 95% CI: 1.09-3.54), mycophenolate mofetil (OR=6.6, 95% CI: 1.47-29.62) and rituximab (OR=4.21, 95% CI: 1.61-10.98). Fifty-eight patients died (8% (total) and 23% (hospitalised)). Compared with 175 matched hospitalised patients with non-iRMD-COVID-19, the OR of mortality associated with hospitalised patients with iRMD-COVID-19 was 1.45 (95% CI: 0.87-2.42) (n=175 each group).Conclusions: In the French RMD COVID-19 cohort, as already identified in the general population, older age, male gender, obesity, and hypertension were found to be associated with severe COVID-19. Patients with iRMD on corticosteroids, but not methotrexate, or tumour necrosis factor alpha and interleukin-6 inhibitors, should be considered as more likely to develop severe COVID-19. Unlike common comorbidities such as obesity, and cardiovascular or lung diseases, the risk of death is not significantly increased in patients with iRMD

    Factors associated with COVID-19-related death in people with rheumatic diseases: results from the COVID-19 Global Rheumatology Alliance physician-reported registry

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    Objectives: To determine factors associated with COVID-19-related death in people with rheumatic diseases. Methods: Physician-reported registry of adults with rheumatic disease and confirmed or presumptive COVID-19 (from 24 March to 1 July 2020). The primary outcome was COVID-19-related death. Age, sex, smoking status, comorbidities, rheumatic disease diagnosis, disease activity and medications were included as covariates in multivariable logistic regression models. Analyses were further stratified according to rheumatic disease category. Results: Of 3729 patients (mean age 57 years, 68% female), 390 (10.5%) died. Independent factors associated with COVID-19-related death were age (66-75 years: OR 3.00, 95% CI 2.13 to 4.22; >75 years: 6.18, 4.47 to 8.53; both vs ≤65 years), male sex (1.46, 1.11 to 1.91), hypertension combined with cardiovascular disease (1.89, 1.31 to 2.73), chronic lung disease (1.68, 1.26 to 2.25) and prednisolone-equivalent dosage >10 mg/day (1.69, 1.18 to 2.41; vs no glucocorticoid intake). Moderate/high disease activity (vs remission/low disease activity) was associated with higher odds of death (1.87, 1.27 to 2.77). Rituximab (4.04, 2.32 to 7.03), sulfasalazine (3.60, 1.66 to 7.78), immunosuppressants (azathioprine, cyclophosphamide, ciclosporin, mycophenolate or tacrolimus: 2.22, 1.43 to 3.46) and not receiving any disease-modifying anti-rheumatic drug (DMARD) (2.11, 1.48 to 3.01) were associated with higher odds of death, compared with methotrexate monotherapy. Other synthetic/biological DMARDs were not associated with COVID-19-related death. Conclusion: Among people with rheumatic disease, COVID-19-related death was associated with known general factors (older age, male sex and specific comorbidities) and disease-specific factors (disease activity and specific medications). The association with moderate/high disease activity highlights the importance of adequate disease control with DMARDs, preferably without increasing glucocorticoid dosages. Caution may be required with rituximab, sulfasalazine and some immunosuppressants

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