Stochastic simulation of clinical pathways from raw health databases

International audienceThis paper presents a method to automatically create stochastic simulation models of clinical pathways from raw databases. We introduce an automatic procedure to convert a process model, discovered with process mining, into an actionable simulation model. The concept of state charts is used and enriched to incorporate the distinctive features of healthcare processes into the model. The clinical pathway model is used to simulate new patients' sequence of events. The resulting model is validated by comparing key performances indicators with historical data. Finally, we use the model to perform an automatically setup sensitivity analysis. The whole process is automated and can be used with any input data

Discovery of patient pathways from a national hospital database using process mining and integer linear programming

International audienceThe analysis of patient pathways from event log is gaining importance in the field of medical information. It provides deep insights about the care process and the ways to improve it. This paper combines optimization and process mining. A new Integer Linear Programming model is proposed to discover the care process at a macroscopic scale from a large-size database. When dealing with health-care data, the main challenge to overcome is the considerable variability of patients' behaviors. An original size constraint and an aggregation method are used to create simple but significant process models. The results of a case study on heart failures confirm the ability of the approach to reveal the process information behind the data

Automatic and Explainable Labeling of Medical Event Logs with Autoencoding

International audienceProcess mining is a suitable method for knowledge extraction from patient pathways. Structured in event logs, medical events are complex, often described using various medical codes. An efficient labeling of these events before applying process mining analysis is challenging. This paper presents an innovative methodology to handle the complexity of events in medical event logs. Based on autoencoding, accurate labels are created by clustering similar events in latent space. Moreover, the explanation of created labels is provided by the decoding of its corresponding events. Tested on synthetic events, the method is able to find hidden clusters on sparse binary data, as well as accurately explain created labels. A case study on real healthcare data is performed. Results confirm the suitability of the method to extract knowledge from complex event logs representing patient pathways

Optimal Process Mining of Timed Event Logs

International audienceThe problem of determining the optimal process model of an event log of traces of events with temporal information is presented. A formal description of the event log and relevant complexity measures are detailed. Then the process model and its replayability score that measures model fitness with respect to the event log are defined. Two process models are formulated, taking into account temporal information. The first, called grid process model, is reminiscent of Petri net unfolding and is a graph with multiple layers of labeled nodes and arcs connecting lower to upper layer nodes. Our second model is an extension of the first. Denoted the time grid process model, it associates a time interval to each arc. Subsequently, a Tabu search algorithm is constructed to determine the optimal process model that maximizes the replayability score subject to the constraints of the maximal number of nodes and arcs. Numerical experiments are conducted to assess the performance of the proposed Tabu search algorithm. Lastly, a healthcare case study was conducted to demonstrate the applicability of our approach for clinical pathway modeling. Special attention was paid on readability, so that final users could beneficially use the process mining results

An optimization-based process mining approach for explainable classification of timed event logs

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Long-term hospital resource utilization and associated costs of care for patients initiating nivolumab in advanced non-small cell lung cancer in France

International audienceObjectives: In advanced cancers, healthcare resource utilization (HCRU) and costs usually increase until death. However, few studies have measured HCRU over time in patients treated with immunotherapies. The objective was to describe the evolution of HCRU and costs over four years for patients with advanced non-small cell lung cancer (aNSCLC) initiating nivolumab.Materials and methods: Based on the French hospital reimbursement database, all aNSCLC patients initiating nivolumab in the 2nd line or later in 2015 or 2016 were followed until 2019. HCRU (including hospitalizations and hospital visits) and costs (payer perspective) were described annually after nivolumab initiation. Trends in HCRU were analyzed with the Mann-Kendall test. As most patients did not reach the four-year follow-up, cost-analysis was performed without adjustment throughout, without adjustment in uncensored cases only or with adjustment using for all patients using the Bang&Tsiatis method.Results: 10,452 patients initiating nivolumab were evaluated. The percentage of patients hospitalized or with hospital visits decreased (p < .001) over the four-year follow-up with the exception of consultations. The number of hospital visits per patient decreased from 23.3 in Y1 to 13.2 in Y4 without adjustment and 18.3 with adjustment (p < .001). The overall hospitalization duration per patient (days) decreased from 36.0 (Y1) to 14.9 (Y4-unadjusted) and 20.5 (Y4-adjusted) (p < .001). Annual per capita costs also decreased. The method without adjustment provided the lowest cost over time (€44,404 (Y1), €32,206 (Y2); €28,552 (Y3); €18,841(Y4)) while the Bang&Tsiatis method presented the highest cost (€45,002 (Y1), €36,330 (Y2); €35,080 (Y3); €28,931 (Y4)).Conclusion: HCRU and costs for NSCLC patients treated with nivolumab decreased over time. Cost estimates are dependent on the statistical method used to take into account uncertainty, but costs decreased over time whatever the method used

Nivolumab treatment in advanced non-small cell lung cancer: real-world long-term outcomes within overall and special populations (the UNIVOC study)

International audienceObjective : To describe long-term outcomes of patients treated with nivolumab for advanced non-small cell lung cancer (aNSCLC) in everyday clinical practice in France, with a focus on patients aged ⩾80 years, patients with renal impairment and patients with brain metastases.Methods : The study included all patients with aNSCLC recorded in the French national hospital database, starting nivolumab in 2015–2016 and followed until December 2018. Patients were stratified by age, the presence of renal impairment and brain metastasis, as documented in the hospital discharge summaries. Information was retrieved on demographics, comorbidities and treatment history at baseline. Time to discontinuation of nivolumab treatment and overall survival were estimated using Kaplan–Meier survival analysis.Results : Overall, 10,452 patients were included, of whom 514 were octogenarians, 479 had renal impairment and 1800 had brain metastases at baseline. Median duration of nivolumab treatment was 2.8 months in the overall population and in both the octogenarian and renally impaired subgroups, and 2.3 months in patients with brain metastases. Median overall survival in these patient groups was 11.7 months (95% confidence interval: 11.3–12.2), 11.7 months (11.3–12.1), 11.7 months (11.3–12.2) and 9.9 months (9.0–10.9) respectively. Three-year overall survival rates were 19.1% (18.1–20.2) in the overall population, 16.5% (11.6–23.4) in octogenarians, 15.9% (11.8–21.4) in patients with renal impairment and 21.7% (19.4–24.2) in those with brain metastases.Conclusion : This large nationwide retrospective real-life cohort provided narrow estimates of long-term overall survival, which reached 19% at 3 years, consistent with data from phase III trials of nivolumab. Survival rates were comparable in the three special populations of interest and the overall population

Hospital costs impact of post ischemic stroke dysphagia: Database analyses of hospital discharges in France and Switzerland

INTRODUCTION: Oropharyngeal dysphagia is frequent in hospitalized post-stroke patients and is associated with increased mortality and comorbidities. The aim of our analysis was to evaluate the impact of dysphagia on Length of Hospital Stay (LOS) and costs. The hospital perspective was used to assess costs. METHODS: Hospital discharge databases comparing hospital stays for ischemic stroke associated with dysphagia vs stroke without dysphagia in France and Switzerland were analyzed. The French Medical Information System Program (PMSI) database analysis focused on 62'297 stays for stroke in the public sector. 6'037 hospital stays for stroke were analyzed from the Swiss OFS (Office fédéral de la statistique: Statistique des coûts par cas 2012) database. Diagnosis codes and listing of procedures were used to identify dysphagia in stroke patients. RESULTS: Patients with post-stroke dysphagia accounted for 8.4% of stroke hospital stays in Switzerland, which is consistent with recently reported prevalence of dysphagia at hospital discharge (Arnold et al, 2016). The French database analysis identified 4.2% stays with post-stroke dysphagia. We hypothesize that the difference between the Swiss and French datasets may be explained by the limitations of an analysis based on diagnosis and procedure coding. Patients with post-stroke dysphagia stayed longer at hospitals (LOS of 23.7 vs. 11.8 days in France and LOS of 14.9 vs. 8.9 days in Switzerland) compared with patients without post-stroke dysphagia. Post-stroke dysphagia was associated with about €3'000 and CHF14'000 cost increase in France and Switzerland respectively. DISCUSSION: In this study post-stroke dysphagia was associated with increased LOS and higher hospital costs. It is difficult to isolate the impact of dysphagia in patients with multiple symptoms and disabilities impacting rehabilitation and recovery. After adjusting for confounding factors by matching stays according to age, sex and stroke complications, post-stroke dysphagia association with increased LOS and higher hospital costs was found to be independent of sensory or motor complications. CONCLUSION: Post-stroke dysphagia is associated with increased length of hospital stay and higher hospital costs

Outcome following nivolumab treatment in patients with advanced non-small cell lung cancer and comorbid interstitial lung disease in a real-world setting

International audienceBackground: Up to 10% of patients with advanced non-small cell lung cancer (aNSCLC) have pre-existing interstitial lung disease (ILD). These patients are usually excluded from immunotherapy clinical trials. Consequently, knowledge on outcomes following nivolumab treatment in these patients remains limited. The primary objective of this study was to evaluate survival outcome following nivolumab treatment in ILD patients with pre-treated aNSCLC in the real-world setting. Patients and methods: The study included all patients with aNSCLC recorded in the French hospital database, starting nivolumab in 2015–2016. Patients were stratified by pre-existing ILD and three subgroups were studied [auto-immune or granulomatous (AI/G) ILD, other known causes ILD and idiopathic ILD]. Time to discontinuation of nivolumab treatment [time to treatment duration (TTD)] and overall survival (OS) were estimated using Kaplan–Meier survival analysis. Results: Of 10,452 aNSCLC patients initiating nivolumab, 148 (1.4%) had pre-existing ILD. Mean age at nivolumab initiation was 64.6 ± 9.4 years in ILD and 63.8 ± 9.6 years in non-ILD. Compared to non-ILD, patients in the ILD group were more frequently men ( p < 0.05) and had more comorbidities ( p < 0.001). There was no significant difference between ILD and non-ILD groups for median TTD (2.5 versus 2.8 months; p = 0.6) or median OS (9.6 versus 11.9 months; p = 0.1). Median OS in AI/G ILD ( n = 14), other known causes ILD ( n = 75), and idiopathic ILD ( n = 59) were 8.6, 10.7, and 9.6 months, respectively. Conclusion: In this large cohort of aNSCLC patients with ILD, outcomes are similar to those obtained in the non-ILD population. Immunotherapy could be beneficial for these patients