Direct impact of COVID-19 by estimating disability-adjusted life years at national level in France in 2020

Background: The World Health Organization declared a pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), on March 11, 2020. The standardized approach of disability-adjusted life years (DALYs) allows for quantifying the combined impact of morbidity and mortality of diseases and injuries. The main objective of this study was to estimate the direct impact of COVID-19 in France in 2020, using DALYs to combine the population health impact of infection fatalities, acute symptomatic infections and their post-acute consequences, in 28 days (baseline) up to 140 days, following the initial infection. Methods: National mortality, COVID-19 screening, and hospital admission data were used to calculate DALYs based on the European Burden of Disease Network consensus disease model. Scenario analyses were performed by varying the number of symptomatic cases and duration of symptoms up to a maximum of 140 days, defining COVID-19 deaths using the underlying, and associated, cause of death. Results: In 2020, the estimated DALYs due to COVID-19 in France were 990 710 (1472 per 100 000), with 99% of burden due to mortality (982 531 years of life lost, YLL) and 1% due to morbidity (8179 years lived with disability, YLD), following the initial infection. The contribution of YLD reached 375%, assuming the duration of 140 days of post-acute consequences of COVID-19. Post-acute consequences contributed to 49% of the total morbidity burden. The contribution of YLD due to acute symptomatic infections among people younger than 70 years was higher (67%) than among people aged 70 years and above (33%). YLL among people aged 70 years and above, contributed to 74% of the total YLL. Conclusions: COVID-19 had a substantial impact on population health in France in 2020. The majority of population health loss was due to mortality. Men had higher population health loss due to COVID-19 than women. Post-acute consequences of COVID-19 had a large contribution to the YLD component of the disease burden, even when we assume the shortest duration of 28 days, long COVID burden is large. Further research is recommended to assess the impact of health inequalities associated with these estimates

Development of Two Morbidity Indices in the French National Health Data System (SNDS) - Application to Case-Identification and to Prospective Payment Models

La mesure pronostique de l’état de santé constitue un enjeu important dans de nombreux domaines liés aux soins, à la recherche ou à la décision publique en santé. Une approche commune à ces différents domaines est de synthétiser l’information disponible sur la morbidité d’une population sous la forme d’indices, appelés parfois scores, en faisant appel à des méthodes de modélisation prédictive. La disponibilité croissante de données médico-administratives et l’essor de leur utilisation à des fins de recherche ou d’aide à la décision ont souligné l’importance de ce type de mesures pronostiques. En France, les données du SNDS et en particulier la « cartographie des pathologies et des dépenses » développée par l’Assurance Maladie, permettent la mesure de la morbidité, un suivi individuel longitudinal sur plusieurs années et l’étude de différents résultats de santé. Nous proposons deux indices de morbidité élaborés en appliquant des méthodes de modélisation prédictive aux données médico-administratives françaises et nous illustrons leur apport par deux études d’application.Les deux indices proposés sont élaborés et validés en appliquant un cadre méthodologique commun à une population nationale de personnes âgées de 65 ans ou plus. L’indice MRMI (Mortality-Related Morbidity Index) est prédictif de la mortalité à deux ans et l’indice ERMI (Expenditure-Related Morbidity Index) est prédictif des dépenses de soins remboursées sur deux ans et reflète l’intensité du recours au système de santé. Leur performance prédictive est supérieure aux indices comparables les plus communément utilisés, indices de Charlson et mesures d’Elixhauser.Dans une première étude d’application, nous étudions le risque de réhospitalisation pour les patients atteints d’insuffisance cardiaque (IC), en utilisant des méthodes adaptées à la prise en compte du risque compétitif de décès. Nous distinguons la stabilité de l’IC de la sévérité globale de l’état de santé, mesurée à travers les deux indices proposés. Ces deux informations, disponibles à l’admission d’un séjour pour IC, permettent de segmenter la population en groupes de risque avec un écart de 40% d’incidence cumulée de réhospitalisation pour IC au bout d’un an de suivi.Pour la deuxième étude d’application, nous comparons différents modèles prédictifs afin de quantifier l’apport des indices de morbidité dans la prédiction des dépenses individuelles. Nous étudions trois périmètres de dépenses : totales, hospitalières et ambulatoires, parmi deux populations différentes : l’ensemble des personnes âgées de 65 ans ou plus et les personnes âgées de 65 ans ou plus et atteintes d’IC. Nous illustrons les enjeux de la définition de paiements populationnels prospectifs de type capitation, en comparant les dépenses observées aux dépenses prédites par ces modèles à l’échelle des départements métropolitains. La sévérité de l’état de santé, mesurée à travers les deux indices proposés, est le déterminant le plus important de la performance prédictive des dépenses, aussi bien au niveau individuel que départemental.Les indices MRMI et ERMI sont des outils performants pour prendre en compte la sévérité de l’état de santé dans les travaux basés sur des données du SNDS et de manière adaptée au résultat étudié. Ils peuvent servir de variables de stratification ou d’ajustement, ou être inclus parmi d’autres variables dans des modèles prédictifs.The accurate characterization of health-state severity has been a central concern in most health-related research or policy fields. A common approach to take into account health-state severity is the use of summary measures, usually referred to as indices or scores, based on predictive modeling methods. With the increasing availability of routinely collected standardized data in medico-administrative databases, such summary measures are more widely used for research purposes or to inform policy making. The French national health data system (SNDS) is particularly adapted to predictive modeling as it allows morbidity measurement, longitudinal follow-up and the study of health-related outcomes. We propose two morbidity indices developed using SNDS data and illustrate their utilization in two application studies.We developed and validated two outcome-specific morbidity indices in a nationwide population of people aged 65 years or older: the Mortality-Related Morbidity Index (MRMI) predictive of 2-year mortality and the Expenditure-Related Morbidity Index (ERMI) predictive of healthcare expenditure over 2 years and reflecting the intensity of healthcare utilization. The MRMI and ERMI indices have better overall performance and better calibration than comparable Charlson indices.As an application of the morbidity indices to case-identification, we studied the risk of readmission in heart failure (HF) patients. To analyze readmission predictors, we distinguished HF severity from overall morbidity measured through the MRMI and ERMI indices and took into account the competing mortality risk. Risk-groups defined upon HF severity and overall morbidity, available at admission, have a 40% separation in HF readmission incidence and specific patterns of risk over the 1-year follow-up period.As an application to payment models, we compared the performance of the MRMI and ERMI indices, among other predictors, for expenditure prediction. Models were applied to prediction of overall, inpatient and outpatient individual expenditure, for people aged 65 or older and for HF patients aged 65 or older. To illustrate the use of predictive models for prospective resource allocation, we compared predicted with observed mean individual expenditure at the area of residence level. Health-state severity measured through the MRMI and ERMI was the most important predictor, both at the individual and area of residence level.The MRMI and ERMI indices are performant tools for outcome-specific severity adjustment in studies using SNDS data. They can be used as stratification or adjustment variables, or among other predictors in predictive models

« Élaboration de deux indices de morbidité dans le Système National des Données de Santé (SNDS) - Application à l'identification de populations à risque et à la définition de modèles de paiement prospectif des soins »

The accurate characterization of health-state severity has been a central concern in most health-related research or policy fields. A common approach to take into account health-state severity is the use of summary measures, usually referred to as indices or scores, based on predictive modeling methods. With the increasing availability of routinely collected standardized data in medico-administrative databases, such summary measures are more widely used for research purposes or to inform policy making. The French national health data system (SNDS) is particularly adapted to predictive modeling as it allows morbidity measurement, longitudinal follow-up and the study of health-related outcomes. We propose two morbidity indices developed using SNDS data and illustrate their utilization in two application studies.We developed and validated two outcome-specific morbidity indices in a nationwide population of people aged 65 years or older: the Mortality-Related Morbidity Index (MRMI) predictive of 2-year mortality and the Expenditure-Related Morbidity Index (ERMI) predictive of healthcare expenditure over 2 years and reflecting the intensity of healthcare utilization. The MRMI and ERMI indices have better overall performance and better calibration than comparable Charlson indices.As an application of the morbidity indices to case-identification, we studied the risk of readmission in heart failure (HF) patients. To analyze readmission predictors, we distinguished HF severity from overall morbidity measured through the MRMI and ERMI indices and took into account the competing mortality risk. Risk-groups defined upon HF severity and overall morbidity, available at admission, have a 40% separation in HF readmission incidence and specific patterns of risk over the 1-year follow-up period.As an application to payment models, we compared the performance of the MRMI and ERMI indices, among other predictors, for expenditure prediction. Models were applied to prediction of overall, inpatient and outpatient individual expenditure, for people aged 65 or older and for HF patients aged 65 or older. To illustrate the use of predictive models for prospective resource allocation, we compared predicted with observed mean individual expenditure at the area of residence level. Health-state severity measured through the MRMI and ERMI was the most important predictor, both at the individual and area of residence level.The MRMI and ERMI indices are performant tools for outcome-specific severity adjustment in studies using SNDS data. They can be used as stratification or adjustment variables, or among other predictors in predictive models.La mesure pronostique de l’état de santé constitue un enjeu important dans de nombreux domaines liés aux soins, à la recherche ou à la décision publique en santé. Une approche commune à ces différents domaines est de synthétiser l’information disponible sur la morbidité d’une population sous la forme d’indices, appelés parfois scores, en faisant appel à des méthodes de modélisation prédictive. La disponibilité croissante de données médico-administratives et l’essor de leur utilisation à des fins de recherche ou d’aide à la décision ont souligné l’importance de ce type de mesures pronostiques. En France, les données du SNDS et en particulier la « cartographie des pathologies et des dépenses » développée par l’Assurance Maladie, permettent la mesure de la morbidité, un suivi individuel longitudinal sur plusieurs années et l’étude de différents résultats de santé. Nous proposons deux indices de morbidité élaborés en appliquant des méthodes de modélisation prédictive aux données médico-administratives françaises et nous illustrons leur apport par deux études d’application.Les deux indices proposés sont élaborés et validés en appliquant un cadre méthodologique commun à une population nationale de personnes âgées de 65 ans ou plus. L’indice MRMI (Mortality-Related Morbidity Index) est prédictif de la mortalité à deux ans et l’indice ERMI (Expenditure-Related Morbidity Index) est prédictif des dépenses de soins remboursées sur deux ans et reflète l’intensité du recours au système de santé. Leur performance prédictive est supérieure aux indices comparables les plus communément utilisés, indices de Charlson et mesures d’Elixhauser.Dans une première étude d’application, nous étudions le risque de réhospitalisation pour les patients atteints d’insuffisance cardiaque (IC), en utilisant des méthodes adaptées à la prise en compte du risque compétitif de décès. Nous distinguons la stabilité de l’IC de la sévérité globale de l’état de santé, mesurée à travers les deux indices proposés. Ces deux informations, disponibles à l’admission d’un séjour pour IC, permettent de segmenter la population en groupes de risque avec un écart de 40% d’incidence cumulée de réhospitalisation pour IC au bout d’un an de suivi.Pour la deuxième étude d’application, nous comparons différents modèles prédictifs afin de quantifier l’apport des indices de morbidité dans la prédiction des dépenses individuelles. Nous étudions trois périmètres de dépenses : totales, hospitalières et ambulatoires, parmi deux populations différentes : l’ensemble des personnes âgées de 65 ans ou plus et les personnes âgées de 65 ans ou plus et atteintes d’IC. Nous illustrons les enjeux de la définition de paiements populationnels prospectifs de type capitation, en comparant les dépenses observées aux dépenses prédites par ces modèles à l’échelle des départements métropolitains. La sévérité de l’état de santé, mesurée à travers les deux indices proposés, est le déterminant le plus important de la performance prédictive des dépenses, aussi bien au niveau individuel que départemental.Les indices MRMI et ERMI sont des outils performants pour prendre en compte la sévérité de l’état de santé dans les travaux basés sur des données du SNDS et de manière adaptée au résultat étudié. Ils peuvent servir de variables de stratification ou d’ajustement, ou être inclus parmi d’autres variables dans des modèles prédictifs

Cervical and breast cancer screening participation for women with chronic conditions in France: results from a national health survey

International audienceBackgroundComorbidity at the time of diagnosis is an independent prognostic factor for survival among women suffering from cervical or breast cancer. Although cancer screening practices have proven their efficacy for mortality reduction, little is known about adherence to screening recommendations for women suffering from chronic conditions. We investigated the association between eleven chronic conditions and adherence to cervical and breast cancer screening recommendations in France.MethodUsing data from a cross-sectional national health survey conducted in 2008, we analyzed screening participation taking into account self-reported: inflammatory systemic disease, cancer, cardiovascular disease, chronic respiratory disease, depression, diabetes, dyslipidemia, hypertension, obesity, osteoarthritis and thyroid disorders. We first computed age-standardized screening rates among women who reported each condition. We then estimated the effect of having reported each condition on adherence to screening recommendations in logistic regression models, with adjustment for sociodemographic characteristics, socioeconomic position, health behaviours, healthcare access and healthcare use. Finally, we investigated the association between chronic conditions and opportunistic versus organized breast cancer screening using multinomial logistic regression.ResultsThe analyses were conducted among 4226 women for cervical cancer screening and 2056 women for breast cancer screening. Most conditions studied were not associated with screening participation. Adherence to cervical cancer screening recommendations was higher for cancer survivors (OR = 1.73 [0.98–3.05]) and lower for obese women (OR = 0.73 [0.57–0.93]), when accounting for our complete range of screening determinants. Women reporting chronic respiratory disease or diabetes participated less in cervical cancer screening, except when adjusting for socioeconomic characteristics. Adherence to breast cancer screening recommendations was lower for obese women and women reporting diabetes, even after accounting for our complete range of screening determinants (OR = 0.71 [0.52–0.96] and OR = 0.55 [0.36–0.83] respectively). The lower breast cancer screening participation for obese women was more pronounced for opportunistic than for organized screening.ConclusionWe identified conditions associated with participation in cervical and breast cancer screening, even when accounting for major determinants of cancer screening. Obese women participated less in cervical cancer screening. Obese women and women with diabetes participated less in mammographic screening and organized breast cancer screening seemed to insufficiently address barriers to participation

Late-onset pseudoepitheliomatous hyperplasia developing within a red ink tattoo

The popularity of tattoos has increased dramatically worldwide particularly in the last three decades, giving rise to the frequent occurrence of a wide spectrum of secondary cutaneous and systemic complications. Pseudoepitheliomatous hyperplasia (PEH) is a benign irregular hyperplasia of the epidermis occurring in response to various stimuli, that clinically and histopathologically resembles cutaneous neoplasms such as squamous cell carcinoma and keratoacanthoma. In an attempt to improve the awareness of the possible occurrence of PEH in tattoos and of its diagnostic and therapeutic aspects, we present herein the case of a 30-year-old woman with histologically confirmed PEH related to a red-ink tattoo. She revealed two important features: the longest interval reported so far between tattooing and onset of PEH (two years) and the lack of the otherwise very common lichenoid tissue reaction to red ink. In view of the serious toxicological potential of tattoo inks, implementation of updated and standardized regulations worldwide regarding their use in the tattooing process is now urgently warranted and continuous efforts should be undertaken in order to enhance the awareness among tattoo artists and the public with regard to the possible serious health risks associated with the use of tattoo ink pigments

Are breast cancer patients with suboptimal adherence to cardiovascular treatment more likely to discontinue adjuvant endocrine therapy? Competing risk survival analysis in a nationwide cohort of postmenopausal women

Abstract Background High rates of discontinuation undermine the effectiveness of adjuvant endocrine therapy (AET) among hormone-receptive breast cancer patients. Patient prognosis also relies on the successful management of cardiovascular risk, which affects a high proportion of postmenopausal women. As with AET, adherence with cardiovascular drugs is suboptimal. We examined whether patient adherence with cardiovascular drugs was associated with the rate of AET discontinuation in a French nationwide claims database linked with hospitalisation data. Methods We identified postmenopausal women starting AET between 01/01/2016 and 31/12/2020 and taking at least two drugs for the primary prevention of cardiovascular disease (antihypertensive drugs, lipid-lowering drugs and platelet aggregation inhibitors) before AET initiation. Adherence was assessed for each drug class by computing the proportion of days covered. Women were categorised as fully adherent, partially adherent or fully non-adherent with their cardiovascular drug regimen based on whether they adhered with all, part or none of their drugs. AET discontinuation was defined as a 90-day gap in AET availability. Time to AET discontinuation according to levels of cardiovascular drug adherence was estimated using cumulative incidence curves, accounting for the competing risks of death and cancer recurrence. Multivariate cause-specific Cox regressions and Fine-and-Gray regressions were used to assess the relative hazards of AET discontinuation. Results In total, 32,075 women fit the inclusion criteria. Women who were fully adherent with their cardiovascular drugs had the lowest cumulative incidence of AET discontinuation at any point over the 5-year follow-up period. At 5 years, 40.2% of fully non-adherent women had discontinued AET compared with 33.5% of partially adherent women and 28.8% of fully adherent women. Both partial adherence and full non-adherence with cardiovascular drugs were predictors of AET discontinuation in the two models (cause-specific hazard ratios 1.16 [95% CI 1.10–1.22] and 1.49 [95% CI 1.39–1.58]; subdistribution hazard ratios 1.15 [95% CI 1.10–1.21] and 1.47 [95% CI 1.38–1.57]). Conclusion Clinicians should be aware that patients who do not adhere with their entire cardiovascular drug regimen are also more likely to discontinue AET. This stresses the importance of integrated care, as suboptimal adherence with both treatment components poses a threat to achieving ideal patient outcomes

Additional file 1 of Are breast cancer patients with suboptimal adherence to cardiovascular treatment more likely to discontinue adjuvant endocrine therapy? Competing risk survival analysis in a nationwide cohort of postmenopausal women

Additional file 1: Tables S1. List of AET drugs with a dosing regimen of 2 pills per day. Table S2. List of health conditions considered for the comorbidity count included in multivariate models. Table S3. Population characteristics stratified by level of cardiovascular treatment adherence. Table S4. Unadjusted predictors of AET discontinuation using Cox and Fine-and-Gray regressions. Figures S1. Log-minus-log plots for each time-invariant predictor

Two morbidity indices developed in a nationwide population permitted performant outcome-specific severity adjustment

Objective: The objective of the study was to develop and validate two outcome-specific morbidity indices in a population-based setting: the Mortality-Related Morbidity Index (MRMI) predictive of all-cause mortality and the Expenditure-Related Morbidity Index (ERMI) predictive of health care expenditure. Study Design and Setting: A cohort including all beneficiaries of the main French health insurance scheme aged 65 years or older on December 31, 2013 (N = 7,672,111), was randomly split into a development population for index elaboration and a validation population for predictive performance assessment. Age, gender, and selected lists of conditions identified through standard algorithms available in the French health insurance database (SNDS) were used as predictors for 2-year mortality and 2-year health care expenditure in separate models. Overall performance and calibration of the MRMI and ERMI were measured and compared to various versions of the Charlson Comorbidity Index (CCI). Results: The MRMI included 16 conditions, was more discriminant than the age-adjusted CCI (c-statistic: 0.825 [95% confidence interval: 0.824–0.826] vs. 0.800 [0.799–0.801]), and better calibrated. The ERMI included 19 conditions, explained more variance than the cost-adapted CCI (21.8% vs. 13.0%), and was better calibrated. Conclusion: The proposed MRMI and ERMI indices are performant tools to account for health-state severity according to outcomes of interest

Underuse of primary healthcare in France during the COVID-19 epidemic in 2020 according to individual characteristics: a national observational study

International audienceBackground: The organization of healthcare systems changed significantly during the COVID-19 pandemic. The impact on the use of primary care during various key periods in 2020 has been little studied. Methods: Using individual data from the national health database, we compared the numbers of people with at least one consultation, deaths, the total number of consultations for the population of mainland France (64.3 million) and the mean number of consultations per person (differentiating between teleconsultations and consultations in person) between 2019 and 2020. We performed analyses by week, by lockdown period (March 17 to May 10, and October 30 to December 14 [less strict]), and for the entire year. Analyses were stratified for age, sex, deprivation index, epidemic level, and disease. Results: During the first lockdown, 26% of the population consulted a general practitioner (GP) at least once (-34% relative to 2019), 7.4% consulted a nurse (-28%), 1.6% a physiotherapist (-80%), and 5% a dentist (-95%). For specialists, consultations were down 82% for ophthalmologists and 37% for psychiatrists. The deficit was smaller for specialties making significant use of teleconsultations. During the second lockdown, the number of consultations was close to that in 2019, except for GPs (-7%), pediatricians (-8%), and nurses (+ 39%). Nurses had already seen a smaller increase in weekly consultations during the summer, following their authorization to perform COVID-19 screening tests. The decrease in the annual number of consultations was largest for dentists (-17%), physiotherapists (-14%), and many specialists (approximately 10%). The mean number of consultations per person was slightly lower for the various specialties, particularly for nurses (15.1 vs. 18.6). The decrease in the number of consultations was largest for children and adolescents (GPs:-10%, dentists:-13%). A smaller decrease was observed for patients with chronic diseases and with increasing age. There were 9% excess deaths, mostly in individuals over 60 years of age. Conclusions: There was a marked decrease in primary care consultations in France, especially during the first lockdown, despite strong teleconsultation activity, with differences according to age and healthcare profession. The impact of this decrease in care on morbidity and mortality merits further investigation