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Best Practice Updates for Weight Loss Surgery Data Collection
Author(s) -
Hutter Matthew M.,
Jones Daniel B.,
Riley Stancel M.,
Snow Roger L.,
Cella Robert J.,
Schneider Benjamin E.,
Clancy Kerri A.
Publication year - 2009
Publication title -
obesity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.438
H-Index - 199
eISSN - 1930-739X
pISSN - 1930-7381
DOI - 10.1038/oby.2008.568
Subject(s) - data collection , medicine , medline , best practice , accreditation , grading (engineering) , outlier , cochrane library , data quality , medical physics , missing data , computer science , medical education , operations management , surgery , randomized controlled trial , statistics , metric (unit) , civil engineering , mathematics , management , artificial intelligence , machine learning , political science , law , economics , engineering
To update evidence‐based best practice guidelines for collection of data on weight loss surgery (WLS). Systematic search of English‐language literature in MEDLINE and the Cochrane Library on WLS and data collection, registries, risk adjustment, accreditation, benchmarks, and administrative and outcomes databases published between April 2004 and May 2007. Use of key words to narrow the search for a selective review of abstracts, retrieval of full articles, and grading of evidence according to systems used in established evidence‐based models. During our search, we identified 212 papers; the 63 most relevant were reviewed in detail. Most data collection on WLS has relied on administrative data sets, single‐institution studies, and other sources that are not WLS specific. A six‐center, nationwide study involving data collection has been started by the longitudinal assessment of bariatric surgery, but results are not yet available. Two WLS‐specific, longitudinal, national data collection systems are about to be implemented. Key factors in patient safety include data collection for all weight loss procedures; prospective, risk‐adjusted, universal, benchmarked, longitudinal data collection systems; and use of WLS‐specific data points that track clinical effectiveness and complications following WLS. Data collection will need to include assessments of novel therapies and specific subgroups (e.g., adolescents, the elderly, and individuals who are at the greatest risk or have the most to gain from WLS). Quality indicators, including metrics on processes of care and determination of outliers, need to be established and monitored to advance patient safety and quality improvement.