Understanding Hospital Complexity in Public Bariatric Surgery: A 6-Year Population-Based Study in Chile

Understanding Hospital Complexity in Public Bariatric Surgery: A 6-Year Population-Based Study in Chile | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Understanding Hospital Complexity in Public Bariatric Surgery: A 6-Year Population-Based Study in Chile Nataly Droguett Droguett, Manuel Vasquez Muñoz, Vezna Sabando Franulic, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7951443/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Obesity represents a growing public health challenge in Latin America, with Chile reporting among the highest regional prevalence rates. Bariatric surgery is a cost-effective intervention for obesity; however, its implementation within public healthcare systems remains underexplored. Objective: To characterize the clinical and demographic profile of bariatric surgery patients in the Chilean public system and to assess the impact of obesity-related comorbidities on hospital complexity using Diagnosis-Related Group (DRG). Methods: A retrospective cross-sectional study analyzed 4,541 bariatric procedures performed between 2019 and 2024 in 72 public hospitals. Cases were identified using ICD-9-CM and ICD-10 codes and stratified by DRG complexity (≤ 1.25 vs. >1.25). Bivariate and multivariate logistic regression models examined associations between patient characteristics and higher DRG complexity. Results: Patients were predominantly female (86.5%) and aged 35–55 years (60.5%). The most frequent comorbidities were hypertension (33.2%) and hepatic steatosis (29.1%). DRG complexity exceeded 1.25 in 26.3% of cases. Independent predictors of higher complexity included age ≥ 35, female sex, hypertension (OR: 1.25), and prolonged medication use (OR: 5.05). In contrast, type 2 diabetes and impaired glucose tolerance were associated with lower complexity. Residence outside the Metropolitan Region also significantly increased complexity (OR: 1.78). Conclusions: Sociodemographic and clinical variables are significantly associated with hospital complexity in bariatric surgery. Incorporating DRG data into policy and planning can improve equity, optimize care pathways, and strengthen resource distribution in public health systems. Bariatric Surgery Obesity Comorbidity Health Resources Utilization Introduction Obesity has emerged as a global public health challenge, with rising prevalence rates placing Chile among the countries with the highest burden in Latin America [ 1 , 2 ]. This chronic condition not only impairs quality of life but is also strongly associated with a wide range of serious medical problems, including type 2 diabetes, hypertension, and hepatic diseases, which collectively increase morbidity and mortality rates [ 3 ]. In this context, Metabolic and Bariatric Surgery (MBS) has proven to be a highly effective therapeutic intervention for individuals with different types of obesity who have not responded to conventional treatments, resulting in significant weight reduction and substantial improvement or remission of obesity-related conditions. [ 3 , 4 ]. In addition to its established role in the treatment of obesity, bariatric surgery has increasingly been indicated in a broader range of clinical contexts. These include patients with refractory type 2 diabetes mellitus, severe obstructive sleep apnea, and as part of preoperative optimization in candidates for solid organ transplantation. Furthermore, growing evidence supports its use in patients with advanced osteoarthritis or other degenerative musculoskeletal conditions, in whom significant weight reduction is required to enable or improve the outcomes of orthopedic and joint replacement procedures, such as total hip or knee arthroplasty. International guidelines and recent systematic reviews particularly emphasize bariatric surgery for obesity-related obstructive sleep apnea when there is intolerance or poor adherence to continuous positive airway pressure (CPAP), showing meaningful improvements in metabolic control, respiratory function, and postoperative morbidity [ 5 , 6 ]. The presence of obesity-related diseases in patients eligible for MBS plays a critical role in determining both the choice of surgical approach and the complexity of postoperative management and long-term outcomes. International literature highlights that conditions such as type 2 diabetes, hypertension, dyslipidemia, and obstructive sleep apnea are highly prevalent in this population and may increase perioperative risks, prolong hospital stays, and necessitate more intensive multidisciplinary care [ 4 , 5 ]. Moreover, optimizing the management of these associated problems is essential to maximize the metabolic and cardiovascular benefits of surgical intervention [ 4 ]. Like any major surgical procedure, bariatric surgery is not free from complications. Perioperative and postoperative risks have significantly decreased due to advances in laparoscopic techniques, surgical experience, and preventive strategies. The most common complications include staple line leaks, bleeding, infections, nutritional deficiencies, and gastrointestinal disorders such as gastroesophageal reflux. In the long term, the main risks involve micronutrient deficiencies, severe reflux, incisional hernias, and, to a lesser extent, inadequate weight loss or the need for revision surgery. Reported mortality is extremely low (0–1%), confirming the procedure’s safety when performed in specialized centers with proper multidisciplinary follow-up [ 7 ]. In the Chilean public health system, MBS is financed and regulated through Diagnosis Related Groups (DRGs), a mechanism that enhances hospital management while allowing for detailed epidemiological and economic analyses of surgical procedures [ 2 ]. Understanding how specific associated medical problems impact hospital resource use and care complexity is vital for strategic planning and optimization of bariatric services. Therefore, the objective of this study is to describe the conditions such as abnormal glucose tolerance tests, hypertension, hepatic steatosis, hypothyroidism, long-term pharmacologic therapy, type 2 diabetes, and cholelithiasis on DRG complexity and length of hospital stay in patients undergoing MBS in Chilean public hospitals between 2019 and 2024. This analysis aims to improve resource allocation, clinical complexity management, and ultimately, the quality of care delivered within the national public healthcare system. Materials and Methods This study employed a cross-sectional design to analyze national-level data on bariatric surgeries performed within Chile’s public healthcare system from January 2019 to December 2024. Data were extracted from publicly available administrative databases maintained by the public insurance (Fondo Nacional de Salud), encompassing hospital discharges and outpatient major surgical procedures reported by 72 public institutions operating under a Diagnosis-Related Group (DRG) payment scheme. Eligible cases were identified using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) procedural codes associated with bariatric surgery: 44.31 (proximal gastric bypass), 44.38 (laparoscopic gastroenterostomy), 44.39 (other gastroenterostomy), 43.82 (laparoscopic vertical sleeve gastrectomy), and 43.89 (other or open partial gastrectomy). Only records with a primary diagnosis of obesity, defined by ICD-10 codes E65, E66, E66.2, E66.8, or E66.9, were included in the analysis. The analysis focused on three domains: (1) sociodemographic characteristics (sex, age, insurance status (public, private or other), and patient region of residence; (2) obesity-related comorbidities identified via ICD-10 codes, including impaired glucose tolerance (R73.0), hepatic steatosis (K76.0), hypothyroidism (E03.9), long-term pharmacologic therapy (Z92.2), hypertension (I10), type 2 diabetes mellitus (E11.9), and cholelithiasis (K80.2); and (3) indicators of hospital complexity, operationalized as Diagnosis-Related Group (DRG) weight, a standardized value that reflects the relative clinical complexity and resource consumption of hospitalized patients, and length of stay (LOS), both reported as means, medians, and standard deviations. Descriptive statistics were used to summarize the data, with frequencies and percentages for categorical variables and central tendency measures for continuous variables. Bivariate analyses were conducted using chi-square tests for categorical associations. Multivariate logistic regression models were developed to identify independent predictors of higher DRG weight (> 1.25). All analyses were conducted using validated statistical software R Studio, with a two-tailed significance threshold set at p < 0.05. Given the use of fully anonymized, publicly accessible data, the study was exempt from formal ethics review. However, the study protocol was submitted for institutional oversight and approved by the Scientific Ethics Committee of Universidad Mayor, Chile. Results A total of 4,541 patients who underwent bariatric surgery in Chilean public hospitals between 2019 and 2024 were included in the analysis. The majority of patients were female (86.5%) and Chilean nationals (99.1%). The most represented age group was 35 to 55 years (60.5%), followed by younger adults aged 14 to 34 years (30.3%). Approximately two-thirds of the surgeries (65.0%) were performed in the Metropolitan Region. Short hospital stays (≤ 2 days) were observed in 73.2% of the cases, indicating a trend toward enhanced recovery protocols or minimally invasive techniques. Most discharges were to home (99.8%), during the study period, only one in-hospital death was reported in 2019, involving a 49-year-old woman with a diagnosis-related group (DRG) complexity of 3.6 (mortality 0,0%). The predominant primary diagnosis was other obesity (E66.8), representing other types of obesity (68.4%). A GRD-weight of ≤ 1.25 was observed in 73.7% of cases, suggesting a moderate resource use level. Severity levels associated with GRD were predominantly classified as mild (Level 1: 72.5%), while mortality risk was similarly concentrated in Level 1 (64.1%). In terms of insurance coverage, most patients were enrolled in public insurance FONASA categories B (44.1%) and D (24.0%). Table 1 Patient Demographic and Clinical Characteristics Category Frequency Percentage (%) Age (years) 14–34 1374 30.3% 35–55 2748 60.5% 56–76 419 9.2% Sex Male 611 13.5% Female 3930 86.5% Nationality Chilean 4501 99.1% Foreigner 40 0.9% Region Metropolitan 2953 65.0% Other 1588 35.0% Length of Stay (days) ≤ 2 3322 73.2% ≥ 3 1219 26.8% Primary Diagnosis E65 5 0.1% E66.0 626 13.8% E66.2 3 0.1% E66.8 3108 68.4% E66.9 799 17.6% Discharge Type Home 4534 99.8% Deceased 1 0.0% Home Hospitalization 6 0.1% GRD Weight ≤ 1.25 3347 73.7% > 1.25 1194 26.3% Severity Level 0 78 1.7% 1 3293 72.5% 2 1121 24.7% 3 49 1.1% Mortality Risk 0 78 1.7% 1 2913 64.1% 2 1507 33.2% 3 43 0.9% Insurance Type Public (FONASA A) 467 10.3% Public (FONASA B) 2002 44.1% Public (FONASA C) 603 13.3% Public (FONASA D) 1092 24.0% Other 10 0.2% Private 367 8.1% Admission Year 2019 1295 28.5% 2020 604 13.3% 2021 374 8.2% 2022 650 14.3% 2023 742 16.3% 2024 876 19.3% Glucose Tolerance Abnormality No 3822 84.2% Yes 719 15.8% Hypertension No 3034 66.8% Yes 1507 33.2% Hepatic Steatosis No 3220 70.9% Yes 1321 29.1% Hypothyroidism No 3874 85.3% Yes 667 14.7% Long-term Medication Use No 3723 82.0% Yes 818 18.0% Type 2 Diabetes No 3754 82.7% Yes 787 17.3% Gallstones No 4146 91.3% Yes 395 8.7% Primary Procedure 43.82 1046 23.0% 43.89 1018 22.4% 44.31 241 5.3% 44.38 2138 47.1% 44.39 98 2.2% Small Intestine Anastomosis No 4057 89.3% Yes 484 10.7% Laparoscopic Cholecystectomy No 4150 91.4% Yes 391 8.6% A bivariate analysis was conducted to examine associations between patient characteristics and hospital complexity, as defined by the GRD weight category (≤ 1.25 vs > 1.25). Female sex was significantly associated with higher GRD weight (p = 0.005), and younger patients aged 14–34 years were more likely to be in the lower GRD category (p < 0.001). Significant associations were also observed for region of residence, where patients from the Metropolitan Region were more frequently represented in the lower GRD weight category (p < 0.001), and for type of health insurance, particularly among those in FONASA B and D. Moreover, several obesity-related medical problems, including impaired glucose tolerance, hypertension, hepatic steatosis, hypothyroidism, and long-term medication use, showed statistically significant associations with higher GRD weight (all p 1.25 (N = 1194) p-value Sex Male 479 132 0.005 Female 2868 1062 Age 14–34 1118 256 < .001 35–55 1951 797 56–76 278 141 Nationality Chilean 3313 1188 0.103 Foreigner 34 6 Insurance Public (FONASA A) 311 156 < .001 Public (FONASA B) 1485 517 Public (FONASA C) 434 169 Public (FONASA D) 818 274 Other 7 3 Private 292 75 Region Metropolitan 2236 717 < .001 Other 1111 477 Length of Stay ≤ 2 days 2455 867 0.622 ≥ 3 days 892 327 Glucose Tolerance Abnormality No 2772 1050 < .001 Yes 575 144 Hypertension No 2328 706 1.25. The model revealed that several patient-related variables were statistically significant predictors of elevated complexity. Patients aged 35–55 years (OR: 1.72; 95% CI: 1.42–2.08; p < 0.001) and those aged 56–76 years (OR: 2.02; 95% CI: 1.49–2.73; p < 0.001) showed progressively higher odds of being assigned to a higher DRG category, compared to the reference group (aged 14–34 years). Female sex was also associated with higher complexity (OR: 1.40; 95% CI: 1.10–1.79; p < 0.001). Among the obesity-related conditions, impaired glucose tolerance (OR: 0.56; 95% CI: 0.44–0.71; p < 0.001) and type 2 diabetes (OR: 0.49; 95% CI: 0.39–0.62; p < 0.001) were negatively associated with higher DRG weight. In contrast, the presence of hypertension (OR: 1.25; 95% CI: 1.05–1.51; p < 0.001) and long-term pharmacologic therapy (OR: 5.05; 95% CI: 4.17–6.11; p < 0.001) were strong predictors of increased hospital complexity. Patients residing outside the Metropolitan Region had significantly higher odds of being categorized under greater complexity (OR: 1.78; 95% CI: 1.51–2.11; p < 0.001), suggesting potential disparities in case severity or access pathways across regions. Length of hospital stay greater than two days was not significantly associated with higher DRG weight (OR: 1.15; 95% CI: 0.96–1.38; p = 0.124). Table 3 Multivariate Logistic Regression Results Variable OR (95% CI) p-value Interpretation Age 35–55 1.72 (1.42–2.08) < 0.001 ↑ complexity Age 56–76 2.02 (1.49–2.73) < 0.001 ↑ complexity Female Sex 1.40 (1.10–1.79) < 0.001 ↑ complexity Impaired Glucose Tolerance 0.56 (0.44–0.71) < 0.001 ↓ complexity Hypertension 1.25 (1.05–1.51) < 0.001 ↑ complexity Type 2 Diabetes 0.49 (0.39–0.62) < 0.001 ↓ complexity Long-term Medication Use 5.05 (4.17–6.11) < 0.001 ↑ complexity Other Region 1.78 (1.51–2.11) 2 Days 1.15 (0.96–1.38) 0.124 NS Discussion This study offers a comprehensive characterization of patients undergoing bariatric surgery within Chile’s public healthcare system between 2019 and 2024, emphasizing the demographic profile, distribution of obesity-related medical problems, and their relationship with hospital complexity. The findings provide critical insights into surgical burden, health system planning, and potential disparities in access and outcomes. Consistent with global trends, women constituted most surgical candidates (86.5%), aligning with evidence that suggests higher rates of health-seeking behavior and acceptance of surgical treatment for obesity among females [ 8 ]. Additionally, most patients were between 35 and 55 years of age, a demographic that represents the most economically active segment of the population, underscoring the potential societal and economic benefits of timely intervention. The predominance of procedures performed in the Metropolitan Region (65.0%) reflects ongoing geographic disparities in access to metabolic and bariatric surgery (MBS), an issue previously highlighted in Latin American healthcare systems. This centralization likely arises not only from workforce and infrastructure limitations in peripheral regions but also from disparities in the composition and availability of multidisciplinary teams particularly endocrinologists, nutritionists, psychologists, and specialized surgeons essential for the comprehensive management of bariatric patients. The concentration of specialists and high-complexity facilities in major urban centers underscores the need for strategic resource decentralization and regional capacity-building policies to ensure equitable access to metabolic surgery across the national territory. Hospital complexity, as measured by DRG weight, was generally low, with 73.7% of patients categorized at ≤ 1.25, in effect, the mode corresponded to GRD weight 1.25. This aligns with the short postoperative length of stay observed (≤ 2 days in 73.2%) and the high proportion of patients discharged home (99.8%), reinforcing the minimally invasive nature of current surgical techniques and the efficiency of perioperative care pathways [ 9 ]. In the multivariate analysis advanced age, female sex, hypertension, and particularly long-term medication use were significantly associated with higher DRG weight. These findings suggest that preoperative medical burden plays a critical role in determining hospital resource utilization and should be carefully factored into surgical risk stratification and resource allocation models. Interestingly, impaired glucose tolerance and type 2 diabetes were inversely associated with higher DRG weight. This counterintuitive result may reflect optimized perioperative metabolic management protocols for patients with known diabetes, or it may indicate earlier surgical referral before advanced complications arise. Similar findings have been reported by Zhang et al. (2018), who noted improved systemic and local inflammatory responses post-MBS in diabetic patients [ 10 ]. Another notable finding was the increased complexity among patients residing outside the Metropolitan Region, even after adjusting clinical variables. This suggests the potential influence of delayed access to surgical care, referral bottlenecks, or differences in preoperative optimization across regions—factors that merit further investigation to address systemic inequities [ 11 ]. Contrary to expectations, postoperative length of stay > 2 days was not a statistically significant predictor of higher DRG weight, reinforcing the notion that clinical burden and comorbidity profile, rather than hospital stay alone, are the main drivers of complexity classification. This study has some limitations that warrant consideration. First, the analysis was based on retrospective administrative data collected through the Chilean DRG system, which, although robust for epidemiological and economic analysis, lacks granularity in clinical details such as BMI, surgical technique specifics, perioperative complications, or long-term metabolic outcomes. This limitation may constrain the depth of inferences regarding individual patient trajectories and clinical efficacy. Second, comorbidity identification was reliant on ICD-10 coding in discharge records, which may be subject to underreporting or misclassification bias, especially for conditions that are subclinical or not prioritized in documentation. Consequently, some relevant clinical predictors may have been underestimated. Third, the study was restricted to the public healthcare sector, excluding private institutions that may serve a demographically or clinically distinct population. Thus, the generalizability of findings to the entire Chilean population undergoing bariatric surgery is limited. Fourth, although DRG weight is a validated proxy for hospital resource use, it does not fully capture dimensions of surgical complexity such as operative time, intraoperative complications, or postoperative rehabilitation needs. These factors may be clinically relevant but remain unobserved in our dataset. Finally, while the study spans a 6-year period, it does not incorporate granular temporal trends or the impact of major systemic events, such as the COVID-19 pandemic, which could have influenced surgical access, case selection, or outcomes during specific years Conclusions This study provides a population-level analysis of bariatric surgery in Chile's public healthcare system, offering novel insights into the demographic profile, comorbidity burden, and hospital complexity of surgical candidates between 2019 and 2024. Advanced age, female sex, hypertension, and long-term medication use emerged as key independent predictors of increased hospital complexity. Conversely, type 2 diabetes and impaired glucose tolerance were unexpectedly associated with lower DRG weight, potentially reflecting optimized care pathways or early surgical referral. The findings underscore the need for equitable geographic access, nuanced preoperative risk stratification, and integration of DRG metrics into surgical planning and policy evaluation. These insights can inform the design of targeted interventions and efficient resource allocation strategies to enhance the quality and equity of bariatric care in Latin American health systems. Declarations Author Contribution ND and MV contributed to the conception, design, and writing of the manuscript. Both authors contributed equally to this work.VS participated as a data analyst and contributed to data processing and statistical analysis.JH,JC,GC contributed as specialists in their respective areas, providing clinical expertise, data interpretation, and critical review of the manuscript. All authors read and approved the final version of the manuscript. Acknowledgement The authors would like to thank Universidad Mayor (Santiago, Chile) for its institutional support and for providing the computational infrastructure and data management resources that made this study possible. We also acknowledge the collaboration of the university’s research office for guidance throughout the project development and manuscript preparation Data Availability The datasets and analyses generated during the current study are securely stored on the servers of Universidad Mayor (Santiago, Chile). Data can be made available by the corresponding author upon reasonable request and with permission from Universidad Mayor References Sapunar J, Escalona A, Araya AV, Aylwin CG, Bastías MJ, Boza C, et al. Rol de la cirugía bariátrica/metabólica en el manejo de la diabetes mellitus 2. Consenso SOCHED/SCCBM. Rev Med Chile. 2018;146(10):1175–86. Paredes Fernández D, Muñoz Claro R, Lamoza Kohan P. Healthcare payment mechanism: Execution results of bundled payment program for bariatric surgery diagnosis in its first year of implementation in Chile. Medwave. 2024;24(1):e2762. Aravena C, Morales C, Rojas P. Prevalencia y consecuencias de la obesidad en adultos en Chile: revisión y análisis de datos nacionales. Rev Chil Nutr. 2018;45(3):235–41. Grando AP, Galiassi GER. Bariatric surgery and its global impact on quality of life. Int J Health Sci. 2023;7(3):61–7. Eisenberg D, Shikora SA, Aarts E et al. Surgery for Obesity and Related Diseases. 2022;18:1345–56. Guidelines IFSO - ASMBS 2022. 10.1016/j.soard.2022.03.008 Ponce J, Faria SL, Goodpaster K, et al. Cirugía bariátrica. Rev Med Clin Las Condes. 2012;23(2):128–44. 10.1016/j.rmclc.2011.10.004 . Lamoshi A, Chernoguz A, Harmon CM, Helmrath M. Complications of bariatric surgery in adolescents. Semin Pediatr Surg. 2020;29(1):150888. 10.1016/j.sempedsurg.2020.150888 . Epub 2020 Jan 20. PMID: 32238287. Risstad H, Søvik TT, Hewitt S, Kristinsson JA, Fagerland MW, Bernklev T, Mala T. Changes in health-related quality of life after gastric bypass in patients with and without obesity-related disease. Obes Surg. 2015;25(1):63–73. https://doi.org/10.1007/s11695-015-1637-y . Devadas M, Ku DJ. Conversional weight loss surgery: an Australian experience of converting laparoscopic adjustable gastric bands to laparoscopic sleeve gastrectomy. Obes Surg. 2018;28(5):1236–41. https://doi.org/10.1007/s11695-017-3007-6 . Zhang C, Zhang J, Liu Z, Zhou Z. More than an anti-diabetic bariatric surgery, metabolic surgery alleviates systemic and local inflammation in obesity. Obes Surg. 2018;28(10):3173–82. https://doi.org/10.1007/s11695-018-3376-1 . Lecaros BJ, Cruzat-Mandich C, Díaz-Castrillón F, Moore IC. Significados y vivencias en pacientes adultos sometidos a cirugía bariátrica. Rev Chil Nutr. 2015;42(2):143–8. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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11:48:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":724639,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7951443/v1/ae5a40e2-acc2-4a95-8435-0be07e7c9606.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding Hospital Complexity in Public Bariatric Surgery: A 6-Year Population-Based Study in Chile","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObesity has emerged as a global public health challenge, with rising prevalence rates placing Chile among the countries with the highest burden in Latin America [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This chronic condition not only impairs quality of life but is also strongly associated with a wide range of serious medical problems, including type 2 diabetes, hypertension, and hepatic diseases, which collectively increase morbidity and mortality rates [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In this context, Metabolic and Bariatric Surgery (MBS) has proven to be a highly effective therapeutic intervention for individuals with different types of obesity who have not responded to conventional treatments, resulting in significant weight reduction and substantial improvement or remission of obesity-related conditions. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn addition to its established role in the treatment of obesity, bariatric surgery has increasingly been indicated in a broader range of clinical contexts. These include patients with refractory type 2 diabetes mellitus, severe obstructive sleep apnea, and as part of preoperative optimization in candidates for solid organ transplantation. Furthermore, growing evidence supports its use in patients with advanced osteoarthritis or other degenerative musculoskeletal conditions, in whom significant weight reduction is required to enable or improve the outcomes of orthopedic and joint replacement procedures, such as total hip or knee arthroplasty. International guidelines and recent systematic reviews particularly emphasize bariatric surgery for obesity-related obstructive sleep apnea when there is intolerance or poor adherence to continuous positive airway pressure (CPAP), showing meaningful improvements in metabolic control, respiratory function, and postoperative morbidity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe presence of obesity-related diseases in patients eligible for MBS plays a critical role in determining both the choice of surgical approach and the complexity of postoperative management and long-term outcomes. International literature highlights that conditions such as type 2 diabetes, hypertension, dyslipidemia, and obstructive sleep apnea are highly prevalent in this population and may increase perioperative risks, prolong hospital stays, and necessitate more intensive multidisciplinary care [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, optimizing the management of these associated problems is essential to maximize the metabolic and cardiovascular benefits of surgical intervention [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Like any major surgical procedure, bariatric surgery is not free from complications. Perioperative and postoperative risks have significantly decreased due to advances in laparoscopic techniques, surgical experience, and preventive strategies. The most common complications include staple line leaks, bleeding, infections, nutritional deficiencies, and gastrointestinal disorders such as gastroesophageal reflux. In the long term, the main risks involve micronutrient deficiencies, severe reflux, incisional hernias, and, to a lesser extent, inadequate weight loss or the need for revision surgery. Reported mortality is extremely low (0\u0026ndash;1%), confirming the procedure\u0026rsquo;s safety when performed in specialized centers with proper multidisciplinary follow-up [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the Chilean public health system, MBS is financed and regulated through Diagnosis Related Groups (DRGs), a mechanism that enhances hospital management while allowing for detailed epidemiological and economic analyses of surgical procedures [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Understanding how specific associated medical problems impact hospital resource use and care complexity is vital for strategic planning and optimization of bariatric services. Therefore, the objective of this study is to describe the conditions such as abnormal glucose tolerance tests, hypertension, hepatic steatosis, hypothyroidism, long-term pharmacologic therapy, type 2 diabetes, and cholelithiasis on DRG complexity and length of hospital stay in patients undergoing MBS in Chilean public hospitals between 2019 and 2024. This analysis aims to improve resource allocation, clinical complexity management, and ultimately, the quality of care delivered within the national public healthcare system.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis study employed a cross-sectional design to analyze national-level data on bariatric surgeries performed within Chile\u0026rsquo;s public healthcare system from January 2019 to December 2024. Data were extracted from publicly available administrative databases maintained by the public insurance (Fondo Nacional de Salud), encompassing hospital discharges and outpatient major surgical procedures reported by 72 public institutions operating under a Diagnosis-Related Group (DRG) payment scheme.\u003c/p\u003e\u003cp\u003eEligible cases were identified using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) procedural codes associated with bariatric surgery: 44.31 (proximal gastric bypass), 44.38 (laparoscopic gastroenterostomy), 44.39 (other gastroenterostomy), 43.82 (laparoscopic vertical sleeve gastrectomy), and 43.89 (other or open partial gastrectomy). Only records with a primary diagnosis of obesity, defined by ICD-10 codes E65, E66, E66.2, E66.8, or E66.9, were included in the analysis.\u003c/p\u003e\u003cp\u003eThe analysis focused on three domains: (1) sociodemographic characteristics (sex, age, insurance status (public, private or other), and patient region of residence; (2) obesity-related comorbidities identified via ICD-10 codes, including impaired glucose tolerance (R73.0), hepatic steatosis (K76.0), hypothyroidism (E03.9), long-term pharmacologic therapy (Z92.2), hypertension (I10), type 2 diabetes mellitus (E11.9), and cholelithiasis (K80.2); and (3) indicators of hospital complexity, operationalized as Diagnosis-Related Group (DRG) weight, a standardized value that reflects the relative clinical complexity and resource consumption of hospitalized patients, and length of stay (LOS), both reported as means, medians, and standard deviations.\u003c/p\u003e\u003cp\u003eDescriptive statistics were used to summarize the data, with frequencies and percentages for categorical variables and central tendency measures for continuous variables. Bivariate analyses were conducted using chi-square tests for categorical associations. Multivariate logistic regression models were developed to identify independent predictors of higher DRG weight (\u0026gt;\u0026thinsp;1.25). All analyses were conducted using validated statistical software R Studio, with a two-tailed significance threshold set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003cp\u003eGiven the use of fully anonymized, publicly accessible data, the study was exempt from formal ethics review. However, the study protocol was submitted for institutional oversight and approved by the Scientific Ethics Committee of Universidad Mayor, Chile.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 4,541 patients who underwent bariatric surgery in Chilean public hospitals between 2019 and 2024 were included in the analysis. The majority of patients were female (86.5%) and Chilean nationals (99.1%). The most represented age group was 35 to 55 years (60.5%), followed by younger adults aged 14 to 34 years (30.3%). Approximately two-thirds of the surgeries (65.0%) were performed in the Metropolitan Region. Short hospital stays (\u0026le;\u0026thinsp;2 days) were observed in 73.2% of the cases, indicating a trend toward enhanced recovery protocols or minimally invasive techniques. Most discharges were to home (99.8%), during the study period, only one in-hospital death was reported in 2019, involving a 49-year-old woman with a diagnosis-related group (DRG) complexity of 3.6 (mortality 0,0%). The predominant primary diagnosis was other obesity (E66.8), representing other types of obesity (68.4%). A GRD-weight of \u0026le;\u0026thinsp;1.25 was observed in 73.7% of cases, suggesting a moderate resource use level. Severity levels associated with GRD were predominantly classified as mild (Level 1: 72.5%), while mortality risk was similarly concentrated in Level 1 (64.1%). In terms of insurance coverage, most patients were enrolled in public insurance FONASA categories B (44.1%) and D (24.0%).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003ePatient Demographic and Clinical Characteristics\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCategory\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFrequency\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePercentage (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u0026ndash;34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1374\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u0026ndash;55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2748\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e60.5%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e56\u0026ndash;76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e419\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.2%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSex\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e611\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.5%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3930\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e86.5%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNationality\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChilean\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4501\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e99.1%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eForeigner\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.9%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRegion\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetropolitan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2953\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e65.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOther\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1588\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e35.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLength of Stay (days)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3322\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e73.2%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1219\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e26.8%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary Diagnosis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" 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char=\".\"\u003e\n\u003cp\u003e68.4%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE66.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e799\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17.6%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDischarge Type\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHome\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4534\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e99.8%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDeceased\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHome Hospitalization\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.1%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGRD Weight\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;1.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3347\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e73.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;1.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1194\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e26.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSeverity Level\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3293\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e72.5%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1121\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.1%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMortality Risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2913\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e64.1%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1507\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33.2%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.9%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsurance Type\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePublic (FONASA A)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e467\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePublic (FONASA B)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e44.1%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePublic (FONASA C)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e603\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePublic (FONASA D)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1092\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e24.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOther\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.2%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrivate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e367\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.1%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAdmission Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2019\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1295\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e28.5%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e604\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e13.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e374\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.2%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e650\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2023\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e742\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2024\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e876\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGlucose Tolerance Abnormality\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3822\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e84.2%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e719\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15.8%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3034\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e66.8%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1507\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33.2%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHepatic Steatosis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3220\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e70.9%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1321\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e29.1%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypothyroidism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3874\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e85.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e667\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLong-term Medication Use\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3723\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e82.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e818\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eType 2 Diabetes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3754\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e82.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e787\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGallstones\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4146\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e91.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e395\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary Procedure\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.82\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1046\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23.0%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1018\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e22.4%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44.31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e241\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2138\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e47.1%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.2%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmall Intestine Anastomosis\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4057\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e89.3%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e484\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.7%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLaparoscopic Cholecystectomy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4150\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e91.4%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e391\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8.6%\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eA bivariate analysis was conducted to examine associations between patient characteristics and hospital complexity, as defined by the GRD weight category (\u0026le;\u0026thinsp;1.25 vs\u0026thinsp;\u0026gt;\u0026thinsp;1.25). Female sex was significantly associated with higher GRD weight (p\u0026thinsp;=\u0026thinsp;0.005), and younger patients aged 14\u0026ndash;34 years were more likely to be in the lower GRD category (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Significant associations were also observed for region of residence, where patients from the Metropolitan Region were more frequently represented in the lower GRD weight category (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and for type of health insurance, particularly among those in FONASA B and D. Moreover, several obesity-related medical problems, including impaired glucose tolerance, hypertension, hepatic steatosis, hypothyroidism, and long-term medication use, showed statistically significant associations with higher GRD weight (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). No significant associations were found for diabetes type 2, length of stay, or presence of gallstones.\u003c/p\u003e\n\u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBivariate Analysis by GRD Weight Category\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCategory\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;1.25 (N\u0026thinsp;=\u0026thinsp;3347)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;1.25 (N\u0026thinsp;=\u0026thinsp;1194)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSex\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e479\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e132\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2868\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1062\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14\u0026ndash;34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1118\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e256\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u0026ndash;55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1951\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e797\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e56\u0026ndash;76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e278\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e141\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNationality\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChilean\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3313\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1188\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.103\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eForeigner\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsurance\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePublic (FONASA A)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e311\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e156\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePublic (FONASA B)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1485\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e517\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePublic (FONASA C)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e434\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e169\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePublic (FONASA D)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e818\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e274\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOther\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrivate\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e292\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRegion\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetropolitan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2236\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e717\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOther\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1111\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e477\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLength of Stay\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;2 days\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2455\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e867\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.622\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;3 days\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e892\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e327\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGlucose Tolerance Abnormality\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2772\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1050\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e575\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e144\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2328\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e706\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eA multivariate logistic regression model was constructed to identify factors associated with increased hospital complexity, defined by DRG weight\u0026thinsp;\u0026gt;\u0026thinsp;1.25. The model revealed that several patient-related variables were statistically significant predictors of elevated complexity.\u003c/p\u003e\n\u003cp\u003ePatients aged 35\u0026ndash;55 years (OR: 1.72; 95% CI: 1.42\u0026ndash;2.08; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and those aged 56\u0026ndash;76 years (OR: 2.02; 95% CI: 1.49\u0026ndash;2.73; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) showed progressively higher odds of being assigned to a higher DRG category, compared to the reference group (aged 14\u0026ndash;34 years). Female sex was also associated with higher complexity (OR: 1.40; 95% CI: 1.10\u0026ndash;1.79; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cp\u003eAmong the obesity-related conditions, impaired glucose tolerance (OR: 0.56; 95% CI: 0.44\u0026ndash;0.71; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and type 2 diabetes (OR: 0.49; 95% CI: 0.39\u0026ndash;0.62; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were negatively associated with higher DRG weight. In contrast, the presence of hypertension (OR: 1.25; 95% CI: 1.05\u0026ndash;1.51; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and long-term pharmacologic therapy (OR: 5.05; 95% CI: 4.17\u0026ndash;6.11; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were strong predictors of increased hospital complexity.\u003c/p\u003e\n\u003cp\u003ePatients residing outside the Metropolitan Region had significantly higher odds of being categorized under greater complexity (OR: 1.78; 95% CI: 1.51\u0026ndash;2.11; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting potential disparities in case severity or access pathways across regions. Length of hospital stay greater than two days was not significantly associated with higher DRG weight (OR: 1.15; 95% CI: 0.96\u0026ndash;1.38; p\u0026thinsp;=\u0026thinsp;0.124).\u003c/p\u003e\n\u003ch3\u003e\u0026nbsp;\u003c/h3\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eMultivariate Logistic Regression Results\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVariable\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eInterpretation\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge 35\u0026ndash;55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.72 (1.42\u0026ndash;2.08)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026uarr; complexity\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAge 56\u0026ndash;76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.02 (1.49\u0026ndash;2.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026uarr; complexity\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale Sex\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.40 (1.10\u0026ndash;1.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026uarr; complexity\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eImpaired Glucose Tolerance\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.56 (0.44\u0026ndash;0.71)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026darr; complexity\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.25 (1.05\u0026ndash;1.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026uarr; complexity\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eType 2 Diabetes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.49 (0.39\u0026ndash;0.62)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026darr; complexity\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLong-term Medication Use\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5.05 (4.17\u0026ndash;6.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026uarr; complexity\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOther Region\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.78 (1.51\u0026ndash;2.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026uarr; complexity\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLength of Stay\u0026thinsp;\u0026gt;\u0026thinsp;2 Days\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.15 (0.96\u0026ndash;1.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.124\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNS\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study offers a comprehensive characterization of patients undergoing bariatric surgery within Chile\u0026rsquo;s public healthcare system between 2019 and 2024, emphasizing the demographic profile, distribution of obesity-related medical problems, and their relationship with hospital complexity. The findings provide critical insights into surgical burden, health system planning, and potential disparities in access and outcomes.\u003c/p\u003e\u003cp\u003eConsistent with global trends, women constituted most surgical candidates (86.5%), aligning with evidence that suggests higher rates of health-seeking behavior and acceptance of surgical treatment for obesity among females [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Additionally, most patients were between 35 and 55 years of age, a demographic that represents the most economically active segment of the population, underscoring the potential societal and economic benefits of timely intervention.\u003c/p\u003e\u003cp\u003eThe predominance of procedures performed in the Metropolitan Region (65.0%) reflects ongoing geographic disparities in access to metabolic and bariatric surgery (MBS), an issue previously highlighted in Latin American healthcare systems. This centralization likely arises not only from workforce and infrastructure limitations in peripheral regions but also from disparities in the composition and availability of multidisciplinary teams particularly endocrinologists, nutritionists, psychologists, and specialized surgeons essential for the comprehensive management of bariatric patients. The concentration of specialists and high-complexity facilities in major urban centers underscores the need for strategic resource decentralization and regional capacity-building policies to ensure equitable access to metabolic surgery across the national territory.\u003c/p\u003e\u003cp\u003eHospital complexity, as measured by DRG weight, was generally low, with 73.7% of patients categorized at \u0026le;\u0026thinsp;1.25, in effect, the mode corresponded to GRD weight 1.25. This aligns with the short postoperative length of stay observed (\u0026le;\u0026thinsp;2 days in 73.2%) and the high proportion of patients discharged home (99.8%), reinforcing the minimally invasive nature of current surgical techniques and the efficiency of perioperative care pathways [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the multivariate analysis advanced age, female sex, hypertension, and particularly long-term medication use were significantly associated with higher DRG weight. These findings suggest that preoperative medical burden plays a critical role in determining hospital resource utilization and should be carefully factored into surgical risk stratification and resource allocation models.\u003c/p\u003e\u003cp\u003eInterestingly, impaired glucose tolerance and type 2 diabetes were inversely associated with higher DRG weight. This counterintuitive result may reflect optimized perioperative metabolic management protocols for patients with known diabetes, or it may indicate earlier surgical referral before advanced complications arise. Similar findings have been reported by Zhang et al. (2018), who noted improved systemic and local inflammatory responses post-MBS in diabetic patients [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAnother notable finding was the increased complexity among patients residing outside the Metropolitan Region, even after adjusting clinical variables. This suggests the potential influence of delayed access to surgical care, referral bottlenecks, or differences in preoperative optimization across regions\u0026mdash;factors that merit further investigation to address systemic inequities [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eContrary to expectations, postoperative length of stay\u0026thinsp;\u0026gt;\u0026thinsp;2 days was not a statistically significant predictor of higher DRG weight, reinforcing the notion that clinical burden and comorbidity profile, rather than hospital stay alone, are the main drivers of complexity classification.\u003c/p\u003e\u003cp\u003eThis study has some limitations that warrant consideration. First, the analysis was based on retrospective administrative data collected through the Chilean DRG system, which, although robust for epidemiological and economic analysis, lacks granularity in clinical details such as BMI, surgical technique specifics, perioperative complications, or long-term metabolic outcomes. This limitation may constrain the depth of inferences regarding individual patient trajectories and clinical efficacy.\u003c/p\u003e\u003cp\u003eSecond, comorbidity identification was reliant on ICD-10 coding in discharge records, which may be subject to underreporting or misclassification bias, especially for conditions that are subclinical or not prioritized in documentation. Consequently, some relevant clinical predictors may have been underestimated.\u003c/p\u003e\u003cp\u003eThird, the study was restricted to the public healthcare sector, excluding private institutions that may serve a demographically or clinically distinct population. Thus, the generalizability of findings to the entire Chilean population undergoing bariatric surgery is limited.\u003c/p\u003e\u003cp\u003eFourth, although DRG weight is a validated proxy for hospital resource use, it does not fully capture dimensions of surgical complexity such as operative time, intraoperative complications, or postoperative rehabilitation needs. These factors may be clinically relevant but remain unobserved in our dataset.\u003c/p\u003e\u003cp\u003eFinally, while the study spans a 6-year period, it does not incorporate granular temporal trends or the impact of major systemic events, such as the COVID-19 pandemic, which could have influenced surgical access, case selection, or outcomes during specific years\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides a population-level analysis of bariatric surgery in Chile's public healthcare system, offering novel insights into the demographic profile, comorbidity burden, and hospital complexity of surgical candidates between 2019 and 2024. Advanced age, female sex, hypertension, and long-term medication use emerged as key independent predictors of increased hospital complexity. Conversely, type 2 diabetes and impaired glucose tolerance were unexpectedly associated with lower DRG weight, potentially reflecting optimized care pathways or early surgical referral.\u003c/p\u003e\u003cp\u003eThe findings underscore the need for equitable geographic access, nuanced preoperative risk stratification, and integration of DRG metrics into surgical planning and policy evaluation. These insights can inform the design of targeted interventions and efficient resource allocation strategies to enhance the quality and equity of bariatric care in Latin American health systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eND and MV contributed to the conception, design, and writing of the manuscript. Both authors contributed equally to this work.VS participated as a data analyst and contributed to data processing and statistical analysis.JH,JC,GC contributed as specialists in their respective areas, providing clinical expertise, data interpretation, and critical review of the manuscript. All authors read and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors would like to thank Universidad Mayor (Santiago, Chile) for its institutional support and for providing the computational infrastructure and data management resources that made this study possible. We also acknowledge the collaboration of the university\u0026rsquo;s research office for guidance throughout the project development and manuscript preparation\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets and analyses generated during the current study are securely stored on the servers of Universidad Mayor (Santiago, Chile). Data can be made available by the corresponding author upon reasonable request and with permission from Universidad Mayor\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSapunar J, Escalona A, Araya AV, Aylwin CG, Bast\u0026iacute;as MJ, Boza C, et al. Rol de la cirug\u0026iacute;a bari\u0026aacute;trica/metab\u0026oacute;lica en el manejo de la diabetes mellitus 2. Consenso SOCHED/SCCBM. Rev Med Chile. 2018;146(10):1175\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eParedes Fern\u0026aacute;ndez D, Mu\u0026ntilde;oz Claro R, Lamoza Kohan P. Healthcare payment mechanism: Execution results of bundled payment program for bariatric surgery diagnosis in its first year of implementation in Chile. Medwave. 2024;24(1):e2762.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAravena C, Morales C, Rojas P. Prevalencia y consecuencias de la obesidad en adultos en Chile: revisi\u0026oacute;n y an\u0026aacute;lisis de datos nacionales. Rev Chil Nutr. 2018;45(3):235\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGrando AP, Galiassi GER. Bariatric surgery and its global impact on quality of life. Int J Health Sci. 2023;7(3):61\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEisenberg D, Shikora SA, Aarts E et al. Surgery for Obesity and Related Diseases. 2022;18:1345\u0026ndash;56. Guidelines IFSO - ASMBS 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.soard.2022.03.008\u003c/span\u003e\u003cspan address=\"10.1016/j.soard.2022.03.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePonce J, Faria SL, Goodpaster K, et al. Cirug\u0026iacute;a bari\u0026aacute;trica. Rev Med Clin Las Condes. 2012;23(2):128\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.rmclc.2011.10.004\u003c/span\u003e\u003cspan address=\"10.1016/j.rmclc.2011.10.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLamoshi A, Chernoguz A, Harmon CM, Helmrath M. Complications of bariatric surgery in adolescents. Semin Pediatr Surg. 2020;29(1):150888. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.sempedsurg.2020.150888\u003c/span\u003e\u003cspan address=\"10.1016/j.sempedsurg.2020.150888\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2020 Jan 20. PMID: 32238287.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRisstad H, S\u0026oslash;vik TT, Hewitt S, Kristinsson JA, Fagerland MW, Bernklev T, Mala T. Changes in health-related quality of life after gastric bypass in patients with and without obesity-related disease. Obes Surg. 2015;25(1):63\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11695-015-1637-y\u003c/span\u003e\u003cspan address=\"10.1007/s11695-015-1637-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDevadas M, Ku DJ. Conversional weight loss surgery: an Australian experience of converting laparoscopic adjustable gastric bands to laparoscopic sleeve gastrectomy. Obes Surg. 2018;28(5):1236\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11695-017-3007-6\u003c/span\u003e\u003cspan address=\"10.1007/s11695-017-3007-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang C, Zhang J, Liu Z, Zhou Z. More than an anti-diabetic bariatric surgery, metabolic surgery alleviates systemic and local inflammation in obesity. Obes Surg. 2018;28(10):3173\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11695-018-3376-1\u003c/span\u003e\u003cspan address=\"10.1007/s11695-018-3376-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLecaros BJ, Cruzat-Mandich C, D\u0026iacute;az-Castrill\u0026oacute;n F, Moore IC. Significados y vivencias en pacientes adultos sometidos a cirug\u0026iacute;a bari\u0026aacute;trica. Rev Chil Nutr. 2015;42(2):143\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bariatric Surgery, Obesity, Comorbidity, Health Resources Utilization","lastPublishedDoi":"10.21203/rs.3.rs-7951443/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7951443/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e\u003cp\u003eObesity represents a growing public health challenge in Latin America, with Chile reporting among the highest regional prevalence rates. Bariatric surgery is a cost-effective intervention for obesity; however, its implementation within public healthcare systems remains underexplored.\u003c/p\u003e\u003ch2\u003eObjective:\u003c/h2\u003e\u003cp\u003eTo characterize the clinical and demographic profile of bariatric surgery patients in the Chilean public system and to assess the impact of obesity-related comorbidities on hospital complexity using Diagnosis-Related Group (DRG).\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eA retrospective cross-sectional study analyzed 4,541 bariatric procedures performed between 2019 and 2024 in 72 public hospitals. Cases were identified using ICD-9-CM and ICD-10 codes and stratified by DRG complexity (\u0026le;\u0026thinsp;1.25 vs. \u0026gt;1.25). Bivariate and multivariate logistic regression models examined associations between patient characteristics and higher DRG complexity.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003ePatients were predominantly female (86.5%) and aged 35\u0026ndash;55 years (60.5%). The most frequent comorbidities were hypertension (33.2%) and hepatic steatosis (29.1%). DRG complexity exceeded 1.25 in 26.3% of cases. Independent predictors of higher complexity included age\u0026thinsp;\u0026ge;\u0026thinsp;35, female sex, hypertension (OR: 1.25), and prolonged medication use (OR: 5.05). In contrast, type 2 diabetes and impaired glucose tolerance were associated with lower complexity. Residence outside the Metropolitan Region also significantly increased complexity (OR: 1.78).\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e\u003cp\u003eSociodemographic and clinical variables are significantly associated with hospital complexity in bariatric surgery. Incorporating DRG data into policy and planning can improve equity, optimize care pathways, and strengthen resource distribution in public health systems.\u003c/p\u003e","manuscriptTitle":"Understanding Hospital Complexity in Public Bariatric Surgery: A 6-Year Population-Based Study in Chile","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-22 02:25:12","doi":"10.21203/rs.3.rs-7951443/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a9c15418-6878-444b-a702-37f1420f4b37","owner":[],"postedDate":"November 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-24T04:40:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-22 02:25:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7951443","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7951443","identity":"rs-7951443","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}