Applying sequence clustering techniques to explore practice-based ambulatory care pathways in insurance claims data

Vogt, Verena; Scholz, Stefan; Sundmacher, Leonie

doi:10.1093/eurpub/ckx169

Cited by 20 publications

(25 citation statements)

References 21 publications

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“…8,10,28,29 Third, these previous studies only focused on the analytic performances of the ensuing clusters, not on the clinical interpretation of the outputs. Le Meur et al, 30 Vogt et al, 31 and Roux et al 32 used methods similar to ours in various therapeutic areas, allowing for the scale-up of the modeling beyond a 1,000 patients while keeping the time dimension. In our study, we further developed algorithms to enable the analysis of > 10,000 patients while keeping all the information of their treatment sequences.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning–Based Analysis of Treatment Sequences Typology in Advanced Non–Small-Cell Lung Cancer Long-Term Survivors Treated With Nivolumab

Chouaïd

Grumberg

Batisse³

et al. 2022

JCO Clinical Cancer Informatics

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PURPOSE Immune checkpoint inhibitors substantially changed advanced non–small-cell lung cancer (aNSCLC) management and can lead to long-term survival. The aims of this study were (1) to use a machine learning method to establish a typology of treatment sequences on patients with aNSCLC who were alive 2 years after initiating a treatment with anti–programmed death-ligand 1 monoclonal antibody nivolumab and (2) to describe the patients' characteristics according to the typology of treatment sequences. MATERIALS AND METHODS This retrospective observational study was based on data from the comprehensive French hospital discharge database for all patients with lung cancer with at least one line of platinum-based chemotherapy, starting nivolumab between January 1, 2015, and December 31, 2016, and alive 2 years after nivolumab treatment initiation. Patients were followed until December 31, 2018. A typology of most common treatment sequences was established using hierarchical clustering with time sequence analysis. RESULTS Two thousand two hundred twelve study patients were, on average, 63.0 years old, 69.9% of them were men, and 61.9% had a nonsquamous cell carcinoma. During the 2 years after nivolumab treatment initiation, clusters of patients with four basic types of treatment sequences were identified: (1) almost continuous nivolumab treatment (44% of patients); (2) nivolumab most of the time followed by a treatment-free interval or a chemotherapy (15% of patients); and a short or medium nivolumab treatment, followed by (3) a long systemic treatment-free interval (17% of patients) or (4) a long chemotherapy (23% of patients). CONCLUSION This machine learning approach enabled the identification of a typology of four representative treatment sequences observed in long-term survival. It was noted that most long-term survivors were treated with nivolumab for well over 1 year.

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Section: Discussionmentioning

confidence: 99%

Machine Learning–Based Analysis of Treatment Sequences Typology in Advanced Non–Small-Cell Lung Cancer Long-Term Survivors Treated With Nivolumab

Chouaïd

Grumberg

Batisse³

et al. 2022

JCO Clinical Cancer Informatics

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“…This is the first SSA on insurance claims data that includes different kinds of simultaneous or overlapping care events, namely physician visits and medication, in a single analysis. Previous studies have focused on the frequency or volume of health service utilization alone, or on different care events in separate analysis 7,10–12. Our combined approach enables to exploit the potential of the SSA method to capture the treatment of large patient population in a holistic manner over a considerable period.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have focused on the frequency or volume of health service utilization alone, or on different care events in separate analysis. 7,[10][11][12] Our combined approach enables to exploit the potential of the SSA method to capture the treatment of large patient population in a holistic manner over a considerable period. The method is however limited to a rather small number of care events per type (due to the growing number of resulting states).…”

Section: Strengths and Limitationsmentioning

confidence: 99%

“…In addition, factors that impact on care and correlations between patterns and health-relevant outcomes are investigated 2–5. Data mining methods such as pattern mining, clustering, and classification methods are used to identify and investigate patient pathways, hereby exploiting the increasing availability of comprehensive data 3,5–7. Recently, first efforts have been made to apply a class of sequence clustering methods rooted in sociology and referred to as “State Sequence Analysis” (SSA),8,9 on health data to identify, visualize, and investigate empirical patient pathways and care utilization patterns 7,10–12…”

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confidence: 99%

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Identifying and Investigating Ambulatory Care Sequences Before Invasive Coronary Angiography

et al. 2022

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Background: The concept of care pathways is widely used to provide efficient, timely, and evidence-based medical care. Recently, the investigation of actual empirical patient pathways has gained attention. We demonstrate the usability of State Sequence Analysis (SSA), a data mining approach based on sequence clustering techniques, on comprehensive insurance claims data from Germany to identify empirical ambulatory care sequences. We investigate patients with coronary artery disease before invasive coronary angiography (CA) and compare identified patterns with guideline recommendations. This patient group is of particular interest due to high and regionally varying CA rates.Methods: Events relevant for the care of coronary artery disease patients, namely physician consultations and medication prescriptions, are identified based on medical guidelines and combined to define states.State sequences are determined for 1.5 years before CA. Sequence similarity is defined for clustering, using optimal matching with theoryinformed substitution costs. We visualize clusters, present descriptive statistics, and apply logistic regression to investigate the association of cluster membership with subsequent undesired care events.Results: Five clusters are identified, the included patients differing with respect to morbidity, urbanity of residential area, and health care utilization. Clusters exhibit significant differences in the timing, structure, and extent of care before CA. When compared with guideline recommendations, 3 clusters show signs of care deficits.Conclusions: Our analyses demonstrate the potential of SSA for exploratory health care research. We show how SSA can be used on insurance claims data to identify, visualize, and investigate care patterns and their deviations from guideline recommendations.

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“…[ 9 ] NGOs can provide health promotion support by filling the gap of health systems in community and improve individual community health by healthy living. [ 10 ] National development requires a creative, real, and organized participation on the part of people. The public participation plays an important role in humanitarian services,[ 11 ] health improvement, and reduction in poverty and healthcare inequalities among communities.…”

Section: Introductionmentioning

confidence: 99%

Assessing the status and recognizing the performance of various nongovernmental organizations in providing health-oriented services as opportunities in promoting community health

Saber

Haghdoost

Eftekhar

et al. 2021

J Edu Health Promot

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BACKGROUND: nongovernmental organizations (NGOs( are the hidden system of promoting public health and the symbol and mediator of people's participation. The aim of the present research was to assess the status and recognize the performance of various NGOs in providing health-oriented services as opportunities in promoting community health. MATERIALS AND METHODS: The present study was a descriptive–analytical (cross-sectional) study, which was conducted on the position and function of all NGOs in Kerman from February 2014 to the end of January 2015. A researcher-made checklist was used to collect the data, which was designed based on the statutes of NGOs. The information was collected from a total of 150 NGOs. To analyze the data, in addition to descriptive statistical tests (frequency, percentage, mean, and standard deviation), other tests were also used (Chi-square test and Fisher's exact test). Moreover, all data analysis was done using SPSS (ver. 16). RESULTS: There was a significant relationship between the levels of prevention and field of activity and the objectives and methods of implementation of these objectives ( P < 0.001). There was a significant relationship between health prevention levels in the target community of the NGO and initial assets ( P = 0.02), licensing organization ( P < 0.001), management type in terms of the board of trustees or membership availability ( P < 0.001), relevance of members' major with organizational goals ( P = 0.02), and activeness or inactiveness of the organization ( P = 0.007). CONCLUSION: The results showed that there was a relationship between NGO's target population in terms of levels of prevention and the studied factors. The relationship between the services of these organizations and the levels of prevention is a very important and effective role in community health promotion.

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Applying sequence clustering techniques to explore practice-based ambulatory care pathways in insurance claims data

Abstract: Sequence clustering techniques can be used as an explorative tool to systematically extract, describe compare and analyze treatment sequences and associated characteristics.

Cited by 20 publications

References 21 publications

Machine Learning–Based Analysis of Treatment Sequences Typology in Advanced Non–Small-Cell Lung Cancer Long-Term Survivors Treated With Nivolumab

Machine Learning–Based Analysis of Treatment Sequences Typology in Advanced Non–Small-Cell Lung Cancer Long-Term Survivors Treated With Nivolumab

Identifying and Investigating Ambulatory Care Sequences Before Invasive Coronary Angiography

Assessing the status and recognizing the performance of various nongovernmental organizations in providing health-oriented services as opportunities in promoting community health

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