Evidence map›Paper›PMID 32030617›Full record

ArticleObesity surgery2020

Analysis of Trajectories of Care After Bariatric Surgery Using Data Mining Method and Health Administrative Information Systems.

Anaïs Charles-Nelson, Andrea Lazzati, Sandrine Katsahian

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Article in Obesity surgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Anaïs Charles-NelsonSorbonne Universités, UPMC Univ Paris 06, UMRS 1138, Centre de Recherche des Cordeliers, Paris, France. anais.charles.nelson@gmail.com.ORCID http://orcid.org/0000-0001-6437-7059
Andrea LazzatiUniversité Paris Descartes, Sorbonne Paris Cité, UMRS 1138, Centre de Recherche des Cordeliers, F75006, Paris, France.
Sandrine KatsahianINSERM, UMRS 1138, Centre de Recherche des Cordeliers, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextThe 30-day readmission rate after bariatric surgery is considered an important metric of the quality of hospital care. However, readmission rate beyond 30 days is rarely reported and does not provide any information about trajectories of care which would be of great interest for healthcare planning. The aim of this study was to analyze trajectories of care during the first year after bariatric surgery on a nationwide basis using data mining methods.

methodThis was a retrospective descriptive study on the trajectories of care within the first year after bariatric surgery. Data were extracted from a national administrative claims database (the PMSI database) and trajectories were defined as principal diagnosis of successive readmissions. Formal Concept Analysis was performed to find common concepts of trajectories of care.

resultsWe included for analysis 198,389 bariatric procedures performed on 196,323 patients. Twelve main concepts were selected. About one third of patients (32.4%) were readmitted in the first year after surgery. Most common trajectories were as follows: regular follow-up (14.9%), cholelithiasis (2.2%), abdominal pain (1.9%), and abdominal sepsis (1.3%). Important differences were found in trajectories among different bariatric procedures: 1.8% of gastric banding patients had pregnancy-related events (delivery or medical abortion), while we observed a readmission rate for abdominal sepsis in 2.7% and 5.1% of patients operated of gastric bypass and sleeve gastrectomy respectively.

conclusionAdministrative claim data can be analyzed through Formal Concept Analysis in order to classify trajectories of care. This approach permits to quantify expected postoperative complications and to identify unexpected events.

Indexed as

Bariatric SurgeryGastric BypassObesity, MorbidData MiningHumansPatient ReadmissionPostoperative ComplicationsRetrospective StudiesBariatric surgeryClaim dataData miningFormal Concept AnalysisTrajectory of care

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.