Purpose: The rapid development of technological tools to record data allows storage of enormous datasets, often termed “big data”. In the USA, three large databases have been developed to store data regarding surgical outcomes: the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) and the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP). We aimed to evaluate the clinical impact of studies found in these databases concerning outcomes of bariatric surgery. Methods: We performed a systematic review using the Meta-analysis of Observational Studies in Epidemiology guidelines. Research carried out using the PubMed database identified 362 papers. All outcomes related to bariatric surgery were analysed. Results: Fifty-four studies, published between 2005 and February 2017, were included. These articles were divided into (1) outcomes related to surgical techniques (12 articles), (2) morbidity and mortality (12), (3) 30-day hospital readmission (10), (4) outcomes related to specific diseases (11), (5) training (2) and (6) socio-economic and ethnic observations in bariatric surgery (7). Forty-two papers were based on data from ACS-NSQIP, nine on data from NIS and three on data from MBSAQIP. Conclusions: This review provides an overview of surgical management and outcomes of bariatric surgery in the USA. Large databases offer useful complementary information that could be considered external validation when strong evidence-based medicine data are lacking. They also allow us to evaluate infrequent situations for which randomized control trials are not feasible and add specific information that can complement the quality of surgical knowledge.
Outcomes after bariatric surgery according to large databases. A systematic review / Balla, Andrea; Batista Rodríguez, Gabriela; Corradetti, Santiago; Balagué, Carmen; Fernández-Ananín, Sonia; Targarona, Eduard M.. - In: LANGENBECK'S ARCHIVES OF SURGERY. - ISSN 1435-2443. - STAMPA. - 402:6(2017), pp. 885-899. [10.1007/s00423-017-1613-6]
Outcomes after bariatric surgery according to large databases. A systematic review
Balla, Andrea
Primo
;
2017
Abstract
Purpose: The rapid development of technological tools to record data allows storage of enormous datasets, often termed “big data”. In the USA, three large databases have been developed to store data regarding surgical outcomes: the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), the Healthcare Cost and Utilization Project (HCUP) National Inpatient Sample (NIS) and the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP). We aimed to evaluate the clinical impact of studies found in these databases concerning outcomes of bariatric surgery. Methods: We performed a systematic review using the Meta-analysis of Observational Studies in Epidemiology guidelines. Research carried out using the PubMed database identified 362 papers. All outcomes related to bariatric surgery were analysed. Results: Fifty-four studies, published between 2005 and February 2017, were included. These articles were divided into (1) outcomes related to surgical techniques (12 articles), (2) morbidity and mortality (12), (3) 30-day hospital readmission (10), (4) outcomes related to specific diseases (11), (5) training (2) and (6) socio-economic and ethnic observations in bariatric surgery (7). Forty-two papers were based on data from ACS-NSQIP, nine on data from NIS and three on data from MBSAQIP. Conclusions: This review provides an overview of surgical management and outcomes of bariatric surgery in the USA. Large databases offer useful complementary information that could be considered external validation when strong evidence-based medicine data are lacking. They also allow us to evaluate infrequent situations for which randomized control trials are not feasible and add specific information that can complement the quality of surgical knowledge.File | Dimensione | Formato | |
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