Related Experiment Video
Updated: Jan 24, 2026

Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering
Published on: November 22, 2019
Comparison of perioperative bariatric complications using 2 large databases: does the data add up?
Benjamin Clapp1, Carl D Devemark1, Robert Jones1
1Department of Surgery, Texas Tech Health Sciences Center Paul Foster School of Medicine, El Paso, Texas.
Comparing bariatric surgery databases reveals significant differences in complication rates. Administrative data, like the Texas Inpatient PUDF, show higher complication risks than clinical registries, such as MBSAQIP.
Area of Science:
- Bariatric Surgery Outcomes
- Health Informatics
- Quality Improvement
Background:
- The Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) database captures prospective short-term outcomes.
- The Texas Inpatient Public Use Data File (PUDF) is an administrative database using hospital discharge data.
Purpose of the Study:
- To assess the reliability between different databases for common bariatric surgery complications.
Main Methods:
- Compared data from the Texas Inpatient PUDF and MBSAQIP for sleeve gastrectomy and gastric bypass in 2015.
- Queried International Classification of Diseases 9 Clinical Modification and Current Procedural Terminology codes for bariatric procedures.
- Examined identical postoperative complications across both databases.
Main Results:
- MBSAQIP included 137,291 patients; PUDF included 9,474 patients.
- The PUDF showed higher odds ratios for acute renal failure, cardiac arrest, myocardial infarction, pneumonia, progressive renal failure, and sepsis.
Conclusions:
- Significant disparities exist in reported perioperative complication rates based on the database used.
- Relying solely on administrative databases for quality assessment in bariatric surgery may be misleading.
- Accurate data interpretation is crucial for surgeon evaluation and financial implications.
More Related Videos
07:59Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
Published on: June 9, 2023
07:41Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Related Concept Videos
The Sense of Self: Reflected Self-Appraisal and Social Comparison
Hemodialysis II: Procedure and Complications
Diabetes: Symptoms, Diagnosis, and Complications
Pneumonia III: Complications and Assessment
Multiple Comparison Tests
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Asthma-III: Symptoms and Complications
Classification of Asthma