Perioperative Complications at Scale: A Multi-Center Analysis of 1.2 Million Surgical Inpatients and the Ethical Imperative for Risk Transparency

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Bloomstone, Benjamin Houseman, Bruce Kingsley, Rune Toms, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9397441/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Major inpatient surgery is associated with significant postoperative morbidity, yet large-scale contemporary data characterizing complication patterns remain limited. Understanding complication epidemiology is essential for individualized risk assessment and shared decision-making. This study aimed to validate prior findings of perioperative complication rates and characterize complication patterns by type, timing, surgical service, patient demographics, and the COVID-19 pandemic period. Methods We developed a tool in early 2019 to prospectively collect perioperative outcomes for patients undergoing major inpatient surgery across 35 different medical centers. We analyzed data from 1,214,539 surgical inpatients receiving care between October 2017 and December 2023. Complications were time stamped and identified using ICD-10 codes, and categorized as pulmonary, cardiac, renal, neurologic, hemorrhagic, or septic. Complication proportions were stratified by surgical service line, postoperative day, age, sex, and American Society of Anesthesiologists physical status. Results The overall complication rate was 7.6% (range 0.52%-23.72% by service line). Cardiac surgery (23.72%), ECMO (20.31%), and neurosurgery (19.89%) had the highest complication rates. The most frequent complications within 7 days per 1000 patients were: postoperative pulmonary complications (6.41), acute kidney injury (5.36), postsurgical sepsis (4.64), acute coronary syndrome (1.00), stroke (0.69), and cardiac arrest (0.63). Complications increased with age (0.67% ages 0–10 years to 15.65% ages 91–100) and were higher in males (9.20%) than females (6.46%). Post-pandemic complication rates (7.68%) declined below pre-pandemic levels (8.32%) and were highest during the emergency surgery only phase of the pandemic (10.53%). Complication rates ranged from a facility-level low of 0.96% to a high of 15.98%, while at the procedure level (CPT codes), certain low-volume interventions had 100% complication rates. Conclusions Complications following major inpatient surgery occur in up to 1 in 4 patients in high-risk surgical populations, and vary significantly by institution and procedure. Surgical facilities should utilize similar methodologies to define their own outcomes to drive perioperative quality improvement. Furthermore, patients have a fundamental right to know these data before consenting to surgery. Institutional complication rates should be made publicly available to facilitate shared decision-making and informed consent. Perioperative complications surgical morbidity risk assessment shared decision-making postoperative pulmonary complications acute kidney injury public reporting Figures Figure 1 Background Over 300 million major operations are performed worldwide each year, with approximately 14.4 million inpatient procedures performed in the United States according to the most recent Healthcare cost and Utilization Project (H-CUP) data.[ 1 , 2 ] Between 5% and 45% of surgical patients have postoperative complications that increase physical and psychosocial suffering, hospital length of stay, discharge level of care, healthcare costs, and decrease long-term survival.[ 3 , 4 , 5 , 6 ] Perioperative organ dysfunction represents a major contributor to adverse clinical outcomes, with acute kidney injury, ventilatory failure, and cardiovascular events among the most consequential complications.[ 7 , 8 ] Postsurgical complication rates vary among surgical service lines and among procedures within each service line.[ 9 ] Furthermore, older patients having non-cardiac surgery experience higher postoperative complication rates.[ 10 ] Despite knowing this data, surgeons and anesthesiologists rarely document individualized preoperative surgical risk assessment. Specifically, our previous multi-center study found that only 16.08% of surgeons and 4.76% of anesthesiologists documented preoperative risk predictions in patients who had poor outcomes, and only 1.3% included a named risk assessment tool. [ 11 ] According to the 2010 Salzburg statement on shared decision-making, patients have the right to be made aware of specific risks regarding their procedures, and physicians must provide accurate information about options, uncertainties, benefits, and harms of treatment. [ 12 , 13 ] The 1982 President's Commission for the Study of Ethical Problems in Medicine established that patients "must have all relevant information regarding their condition and alternative treatments, including possible benefits, risks, costs, other consequences, and significant uncertainties." Individualized risk assessments represent a National Quality Strategy surgical measure and are required by medical societies and regulatory bodies. [ 14 , 15 ] Additionally, patients may be more motivated to follow a preoptimization plan, including exercise, diet modification, alcohol and tobacco cessation, when coached and presented with an accurate and detailed risk assessment. [ 16 , 17 ] The primary purpose for collecting these data prospectively was to validate findings from smaller trials demonstrating that major inpatient surgery is associated with high postsurgical complication rates. Secondary objectives included characterizing complication types, timing, and associations with age, sex, and service lines. This study offers a more accurate picture of perioperative morbidity than self-reported event data, which lacks a denominator, thereby better informing perioperative shared decision-making and the development of evidence-based pathways to mitigate these complications. Methods We created a tool to prospectively collect administrative data from each clinician-patient interaction (encounter level billing data) that occurred within 35 different facilities for patients undergoing inpatient surgeries between October 1, 2017 and December 12, 2023. Facilities were located across seven states, including Florida, California, New Jersey, Texas, Georgia, Arkansas, and Arizona. Private health system affiliates made up 88%, while university-affiliated institutions represented a minority. Trauma center designations were present in 47%, with the majority holding Level II designations. The licensed bed capacity varied between 67 beds and 898 beds [median bed count was 238, with a mean of 263 beds.] Current Procedural Terminology (CPT) codes for specific surgical procedures were categorized into service lines including cardiac, thoracic, general, and neurosurgery, urology, gynecology, orthopedics, and others. Postsurgical morbidities were defined and categorized using the International Classification of Diseases, Tenth Revision (ICD-10) codes and sorted into pulmonary, cardiac, renal, neurologic, hemorrhagic, and septic complications. We utilized the Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators Technical Specifications Updates - Version v2018 and v2018.0.1 (ICD 10), June 2018 to quantify complications involving hemorrhage, respiratory failure, sepsis, pneumothorax, acute renal failure, wound dehiscence. Additional organ specific ICD-10 codes were applied for complications not included in the AHRQ Patient Safety Indicator categories including cardiac, neurologic, gastrointestinal, ocular, and other organ system complications (supplementary data). Age, sex, American Society of Anesthesiologists physical status (ASA-PS) classification, and the postoperative day when a complication was reported were abstracted from the database. The proportion of postsurgical complications was defined as the total number of complications divided by the total surgical inpatient population, further stratified by service line, procedure type, and postoperative day. While complications were captured for each patient’s entire stay, we report findings from the first seven days of hospitalization as this time frame captures the majority of complications. COVID-19 pandemic periods were defined as: pre-COVID-19 (October 1, 2017 - March 31, 2020), early COVID-19 surge (April 1, 2020 - June 1, 2020), early post-COVID-19 (June 2, 2020 - November 10, 2021), and post-COVID-19 (November 11, 2021 - March 31, 2023). This work received IRB exemption (D4 determination). Results The study included 1,214,539 surgical inpatients, of whom 92,311 experienced complications, yielding an overall complication proportion of 7.6% (range 0.52% − 23.72%). Study population characteristics are summarized in Table 1 . Table 1 Study Population Characteristics Characteristic Value Study Period October 1, 2017 - December 23, 2023 Number of Centers 35 Total Surgical Inpatients 1,214,539 Patients with Complications 92,311 Overall Complication Rate 7.6% (range 0.52% − 23.72%) Complication rates varied substantially by surgical service line (Table 2 ). Cardiac surgery demonstrated the highest rate (23.72%), followed by extracorporeal membrane oxygenation (ECMO) procedures (20.31%), neurosurgery (19.89%), thoracic surgery (19.08%), vascular surgery (11.59%), general surgery (10.39%), orthopedic surgery (8.86%), urology (7.82%), gynecology (2.16%), and ophthalmology (0.52%). Table 2 Complication Rates by Surgical Service Line and Complication Type Surgical Service Line Complication Rate (%) Cardiac Surgery 23.72 ECMO 20.31 Neurosurgery 19.89 Thoracic Surgery 19.08 Vascular Surgery 11.59 General Surgery 10.39 Orthopedic Surgery 8.86 Urology 7.82 Gynecology 2.16 Ophthalmology 0.52 Complication Type (within 7 days) Rate per 1000 Patients Postoperative Pulmonary Complications 6.41 Acute Kidney Injury 5.36 Postsurgical Sepsis 4.64 Acute Coronary Syndrome 1.00 Stroke and New Neurologic Deficit 0.69 Cardiac Arrest 0.63 The most frequent major complications within 7 days of surgery per 1000 patients were: postoperative pulmonary complications (6.41), acute kidney injury (5.36), postsurgical sepsis (4.64), acute coronary syndromes (1.00), stroke and or new neurologic deficit (0.69), and cardiac arrest (0.63) (Table 2 ). Complications occurred more frequently in males (9.20%) than females (6.46%) and increased progressively with age (Table 3 ). Complication rates varied across American Society of Anesthesiologist Physical Status (ASA-PS) classifications for both elective and emergency procedures. Elective cases had complication rates of 2% for ASA-PS 1, 19% for ASA-PS 2, 56% for ASA-PS 3, and 29% for ASA-PS 4. Emergency cases had rates of 4% for ASA-PS 1E, 19% for ASA-PS 2E, 43% for ASA-PS 3E, and 39% for ASA-PS 4E. Complication rates did not follow a strict linear pattern across ascending ASA-PS classifications in either emergency or non-emergency groups. (Table 3 ) Table 3 Complication Rates by Patient Demographics Age Group (years) Complication Rate (%) 0–10 0.67 11–20 2.48 21–30 3.63 31–40 4.95 41–50 7.43 51–60 8.83 61–70 8.51 71–80 8.65 81–90 11.81 91–100 15.65 Sex Complication Rate (%) Male 9.20 Female 6.46 ASA Physical Status Complication Rate (%) ASA PS 1 2 ASA PS 1E 4* ASA PS 2 19 ASA PS 2E 19* ASA PS 3 56 ASA PS 3E 43 ASA PS 4 29 ASA PS 4E 39 *Impacted by small sample size Complications were highest (10.56%) during the emergency surgery only phase of the Covid-19 pandemic. Post-pandemic complication rates (7.68%) declined below pre-pandemic levels (8.32%). Annual complication rates and COVID-19 pandemic period analyses are presented in Table 4 . A 17-fold variation in facility-level complication rates was observed (Fig. 1). There was a dramatic escalation of complication risk among low-volume procedures. Specifically, 10 distinct cardiac procedures (specialized valve reconstructions, thoracic aortic procedures, and complex hybrid cardiac operations) with fewer than 5–10 cases performed were associated with 100% complication rates. (Fig. 1) Discussion Our comprehensive multi-center analysis involving millions of patients highlights the significant morbidity burden associated with major surgical procedures. This study confirms that complications following major inpatient surgeries occur in up to 25% of surgical inpatients having high-risk surgical interventions. This validates the findings of multiple smaller studies [ 3 , 4 , 5 ]. Furthermore, our overall 7.6% complication rate aligns with that published by Chen et al. in their survey of 113 US Department of Veterans Affairs hospitals, which sampled over 500,000 operations. This substantial external correlation provides further support and validation for both our methodology and our findings. [ 18 ] Our finding that pulmonary complications, acute kidney injury, and sepsis occur more frequently than cardiac or neurologic events has important implications for perioperative risk modification, risk communication, shared decision making, and planning. While cardiac events have traditionally dominated preoperative risk discussions, these data suggest that pulmonary and renal complications warrant equal attention in shared decision-making conversations and preprocedural optimization. Given the lack of an ICD-10 code for myocardial injury following non-cardiac surgery (MINS), we were unable to quantify MINS in this population. This potentially skews our findings. Recent evidence demonstrates that adverse events occur in more than one-third of surgical inpatients, with nearly half classified as major and most potentially preventable. [ 19 ] The progressive increase in complication rates with advancing age—from 0.67% in pediatric patients to 15.65% in nonagenarians—reinforces the importance of age-specific risk assessment. The higher complication rate in males (9.20% vs 6.46%) represents another demographic difference that warrants further study, and should play a key role during individualized risk discussions and shared decision-making. Complication rates across the American Society of Anesthesiologists Physical Status (ASA-PS) classification system did not follow the expected linear pattern. The disproportionately high rate among ASA-PS 3 elective cases (56%) relative to ASA-PS 4 elective cases (29%) may reflect surgical selection bias, whereby the highest-acuity patients are offered intervention only under the most favorable conditions. Similarly, the lower complication rate in ASA-PS 3E versus ASA-PS 3 elective cases (43% vs. 56%) challenges the assumption that emergency designation uniformly confers additional risk. The marked difference between ASA-PS 1 and ASA-PS 2 elective cases (2% vs. 19%) further suggests that even minor increments in comorbidity burden may carry substantial perioperative impact. These findings must be interpreted in the context of well-documented inter-provider variability in ASA-PS assignment. Sanford et al. demonstrated a lack of interrater reliability across 70 anesthesia providers using standardized clinical vignettes, with no correlation between ASA-PS scoring and years of practice or provider type.[ 23 ] Tollinche et al. similarly found very little inter-rater reliability when comparing ASA-PS assignments for the same patient across two different providers, with even same-provider reliability proving only moderate. This degree of classification inconsistency introduces misclassification bias that is difficult to quantify and may distort the complication rates that we observed. [ 25 ] However, many risk assessment tools including the American College of Surgeons National Surgical Quality Improvement Project (ACS-NSQIP) Surgical Risk Calculator has found the ASA-PS a robust contributor to risk. Our multicenter, procedure-level analysis of perioperative complication rates reveals a complex risk landscape that cannot be adequately characterized by institutional volume or aggregate complication rates alone. The high complication rates in certain cardiac procedures is likely due to small sample sizes, complex procedures that include the highest-risk patients, and potential gaps in institutional experience and preparedness for rare cardiac interventions. The 17-fold variation in facility-level complication rates and the dramatic escalation of complication risks among low-volume procedures (including 100% complication rates for multiple rare cardiac interventions) collectively demonstrate that procedural complexity, institutional experience, and case-mix composition are the primary determinants of perioperative safety. These findings carry significant implications for healthcare policies, surgical quality improvement, and patient safety initiatives. Specifically, they support the development of procedure-specific quality standards, minimum volume thresholds for complex cardiac interventions, and risk-adjusted benchmarking frameworks that can drive meaningful, targeted improvements across the full spectrum of perioperative care. Ultimately, addressing this variability through systematic quality improvement has the potential to significantly reduce preventable complications, improve patient outcomes, and optimize the allocation of specialized cardiac surgical resources across the healthcare system. The Critical Gap Between Complication Rates and Risk Documentation This study and our previous work on risk documentation reveal a significant disconnect between surgical morbidity and current risk communication practices. Despite complication rates approaching 1 in 4 patients for high-risk procedures, our prior work demonstrates that only 16.08% of surgeons and 4.76% of anesthesiologists documented individualized risk assessments in patients who subsequently experienced poor outcomes.[ 12 ] Even more striking, only 1.3% of these patients had risks determined by a validated risk assessment tool, such as the ACS NSQIP Surgical Risk Calculator. This gap represents a fundamental deficiency in the informed consent process, and perhaps a missed opportunity for organ specific preoperative optimization. Surgeons routinely discuss components of informed consent with patients before high-risk surgery. However, they may not be aware of the specific risks of a particular surgery, their own complication rates or those of the system of care they work in. They may fail to fully inform patients of these risks. Some surgeons do not fully explore the patient’s uncertainty, understanding, or preferences. [ 20 ] A systematic review of preoperative risk discussion found high levels of intra-surgeon variation in what risk information is provided to patients. [ 20 ] Additionally, less than 50% of patients who consented for common procedures demonstrated an adequate understanding of the procedures they consented to receive. [ 21 , 22 ] Ideally, patients should receive information regarding procedural volume, facility-specific resources, and whether dedicated perioperative care teams exist. Patients need to know the rates of complications and the types of complications. When clinicians fail to provide individualized risk information and presume what a patient wants, needs, or prefers, a "preference misdiagnosis" may lead to interventions that a fully informed patient might not want. [ 15 ] The Case for Public Reporting of Complication Data Given the magnitude of perioperative morbidity documented in this study, patients should have access to institutional and procedure-specific complication data before consenting to surgery. Public reporting of outcome data is intended to drive quality improvement, demonstrate transparency, facilitate patient choice, and allow identification of poor performance.[ 25 ] Nearly 90% of patients desire to review an individualized risk report before surgical consent, and high-risk patients are three times more likely to underestimate their risk of any complications, serious complications, and length of stay compared to low-risk patients.[ 26 ] While concerns exist regarding public reporting, including risk aversion, gaming, and data misinterpretation, the advantages of reporting outcomes outweigh the disadvantages.[ 25 , 27 , 24 ] Patient surveys indicate that 72% believe they should be made aware of surgeon-specific outcome data. The majority recognize the utility of such data to inform treatments and surgeon choice. [ 29 ] All perioperative physicians, including surgeons, have a duty to develop information systems that allow performance to be evaluated accurately and communicated transparently. Ultimately, what a patient really wants to know is the individual experience and competency of their operating surgeon or anesthesiologist, not numbers quoted from the peer reviewed literature. Limitations This study has important limitations inherent to retrospective administrative database analyses. Our identification of complications relied on ICD-10 coding which may underestimate true rates. MINS was not captured at all due to lack of a specific ICD-10 coding. Facility specific data in this study were not risk adjusted, limiting our ability to make detailed comparisons. Nor were we able to determine severity of complications or morbidity and mortality associated with complications. Finally, this work presents complications that occurred within 7 days of surgery, whilst some patients developed complications later during their hospitalization. Conclusions This large, multicenter analysis demonstrates that perioperative complications following major inpatient surgery occur in up to 1 in 4 patients in high-risk surgical populations. Postoperative pulmonary complications, acute kidney injury, and sepsis occur more frequently than cardiac or neurologic events. Complication rates increase with age and male sex. Despite these substantial and well-established risks, documentation of individualized risk assessment and shared decision-making remain alarmingly rare in clinical practice. This represents a failure to meet the ethical obligations of informed consent. Patients have a fundamental right to know these complication data—both their individualized risk and institutional outcomes—before consenting to surgery. Without documented individualized risk assessment, the quality of informed consent must be questioned, because the prediction and sharing of risk provides the foundation for perioperative decision-making and individualized physiologic optimization. We urge medical societies and medical colleges, facilities, and health systems to support the collection of morbidity data, and to make these rates publicly available. Transparency in surgical outcomes is not merely a quality improvement initiative, It is an ethical imperative that respects patient autonomy and enables truly informed shared decision-making. The type of data presented here should be accessible to every patient facing major surgery. Declarations Ethics approval and consent to participate: This work received IRB exemption (D4 determination). Consent for publication: Data are completely de-identified. No individual personal data is reported. Availability of data and materials: The datasets used and analyzed during the current study may be available from the corresponding author. Competing interests: The authors declare that they have no competing interests. Funding: This project was funded internally by Envision Healthcare Authors' contributions: JAB-conception, design, author, data acquisition, interpretation. BTH-editor, author. BK-editor, author. LR-editor, author. GM-editor, author. RT-editor. RN-editor. TH-editor, SS-statistical analysis, author. RS- statistical analysis, editor. BI-data curation. NG-data curation. HG- data curation. BJS- editor, author. All authors have read and approved the final manuscript. References Weiser TG, Regenbogen SE, Thompson KD, Haynes AB, Lipsitz SR, Berry WR, Gawande AA. An estimation of the global volume of surgery: a modelling strategy based on available data. Lancet. 2008;372(9633):139–44. 10.1016/S0140-6736(08)60878-8 . Epub 2008 Jun 24. PMID: 18582931. 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Chou E, Abboudi H, Shamim Khan M, Dasgupta P, Ahmed K. Should surgical outcomes be published? J R Soc Med. 2015;108(4):127–35. PMID: 25899023; PMCID: PMC4406890. John IJ, Choo H, Pettengell CJ, Riga CV, Martin GFJ, Bicknell CD. Patient Views on Surgeon-specific Outcome Reporting in Vascular Surgery: Novel Validated Patient Questionnaire Study. Ann Surg. 2021;274(6):e1030-e1037. 10.1097/SLA.0000000000003730 . PMID: 31851006. Burger I, Schill K, Goodman S. Disclosure of individual surgeon's performance rates during informed consent: ethical and epistemological considerations. Ann Surg. 2007;245(4):507–13. 10.1097/01.sla.0000242713.82125.d1 . PMID: 17414595; PMCID: PMC1877054. Table 4 Table 4 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table4.docx SupplementalMaterialICD10CodesandCodeSets.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 07 May, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 15 Apr, 2026 Submission checks completed at journal 15 Apr, 2026 First submitted to journal 12 Apr, 2026 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9397441","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628179542,"identity":"c377836c-b01a-471c-b931-e3c73fc480e3","order_by":0,"name":"Joshua A. 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Kingsley","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Bruce","middleName":"","lastName":"Kingsley","suffix":""},{"id":628179545,"identity":"4c238360-5882-427f-87e8-6e72052cc66f","order_by":3,"name":"Rune Toms","email":"","orcid":"","institution":"Nicklaus Children's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Rune","middleName":"","lastName":"Toms","suffix":""},{"id":628179546,"identity":"a94e1a84-e2eb-4db2-aac1-69d1b8b7d140","order_by":4,"name":"Gerald Maccioli","email":"","orcid":"","institution":"ForesightVenturesAI","correspondingAuthor":false,"prefix":"","firstName":"Gerald","middleName":"","lastName":"Maccioli","suffix":""},{"id":628179547,"identity":"0563d462-5da9-458e-95f1-2c4246c788d9","order_by":5,"name":"Rafael Noriega","email":"","orcid":"","institution":"Envision Healthcare","correspondingAuthor":false,"prefix":"","firstName":"Rafael","middleName":"","lastName":"Noriega","suffix":""},{"id":628179548,"identity":"ba9b1c16-0dc8-4ca2-9f3b-30f63af989df","order_by":6,"name":"Tania Haddad","email":"","orcid":"","institution":"Circle the City","correspondingAuthor":false,"prefix":"","firstName":"Tania","middleName":"","lastName":"Haddad","suffix":""},{"id":628179549,"identity":"cc98e47f-db7a-4f3f-ade6-43cf2251c15c","order_by":7,"name":"Boyoung In","email":"","orcid":"","institution":"Amazon Logistics","correspondingAuthor":false,"prefix":"","firstName":"Boyoung","middleName":"","lastName":"In","suffix":""},{"id":628179550,"identity":"e7c7b22b-707b-46ad-ab95-0ab4131024ae","order_by":8,"name":"Nihar Garlapati","email":"","orcid":"","institution":"Amazon Logistics","correspondingAuthor":false,"prefix":"","firstName":"Nihar","middleName":"","lastName":"Garlapati","suffix":""},{"id":628179551,"identity":"79ff3bfb-31f7-4b01-9334-78b677b3ece8","order_by":9,"name":"Nishant Gupta","email":"","orcid":"","institution":"ChenMed","correspondingAuthor":false,"prefix":"","firstName":"Nishant","middleName":"","lastName":"Gupta","suffix":""},{"id":628179552,"identity":"0dd8a9c1-192c-4650-9cc8-0b1ac2bc7b94","order_by":10,"name":"Rupa Sabbineni","email":"","orcid":"","institution":"Envision Healthcare","correspondingAuthor":false,"prefix":"","firstName":"Rupa","middleName":"","lastName":"Sabbineni","suffix":""},{"id":628179553,"identity":"66f28bd4-8fb0-4c39-bbdc-e939894e9429","order_by":11,"name":"Sara Sigler","email":"","orcid":"","institution":"Envision Healthcare","correspondingAuthor":false,"prefix":"","firstName":"Sara","middleName":"","lastName":"Sigler","suffix":""},{"id":628179554,"identity":"55eb9469-7194-4b6e-8b81-ed6252a273c7","order_by":12,"name":"Leopoldo Rodriguez","email":"","orcid":"","institution":"Medical University of South Carolina","correspondingAuthor":false,"prefix":"","firstName":"Leopoldo","middleName":"","lastName":"Rodriguez","suffix":""},{"id":628179555,"identity":"430a99c5-81c5-46bc-b7d3-68fca0b0bc5e","order_by":13,"name":"BobbieJean Sweitzer","email":"","orcid":"","institution":"Vanderbilt University Medical Center","correspondingAuthor":false,"prefix":"","firstName":"BobbieJean","middleName":"","lastName":"Sweitzer","suffix":""}],"badges":[],"createdAt":"2026-04-13 01:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9397441/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9397441/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108383325,"identity":"50ea22f8-1dec-4db8-8de0-79cd3b95e30b","added_by":"auto","created_at":"2026-05-04 05:45:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":581109,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9397441/v1/e39537c4f4596fd938241649.png"},{"id":108804096,"identity":"2253116c-c9f3-41e6-9007-1b1867a88089","added_by":"auto","created_at":"2026-05-08 15:15:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":656103,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9397441/v1/8ba0d641-7497-4687-a20a-ae378c6043e5.pdf"},{"id":108383327,"identity":"f6294b6d-4cbb-4ffe-a1a0-adc60c7789cc","added_by":"auto","created_at":"2026-05-04 05:45:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14291,"visible":true,"origin":"","legend":"","description":"","filename":"Table4.docx","url":"https://assets-eu.researchsquare.com/files/rs-9397441/v1/4253b772898204058368e7c7.docx"},{"id":108383326,"identity":"6789db75-10c4-4dbc-aec8-647ad6db0232","added_by":"auto","created_at":"2026-05-04 05:45:33","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":25204,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalMaterialICD10CodesandCodeSets.docx","url":"https://assets-eu.researchsquare.com/files/rs-9397441/v1/5d336633b9676a5d59984197.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Perioperative Complications at Scale: A Multi-Center Analysis of 1.2 Million Surgical Inpatients and the Ethical Imperative for Risk Transparency","fulltext":[{"header":"Background","content":"\u003cp\u003eOver 300\u0026nbsp;million major operations are performed worldwide each year, with approximately 14.4\u0026nbsp;million inpatient procedures performed in the United States according to the most recent Healthcare cost and Utilization Project (H-CUP) data.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Between 5% and 45% of surgical patients have postoperative complications that increase physical and psychosocial suffering, hospital length of stay, discharge level of care, healthcare costs, and decrease long-term survival.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Perioperative organ dysfunction represents a major contributor to adverse clinical outcomes, with acute kidney injury, ventilatory failure, and cardiovascular events among the most consequential complications.[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e \u003cp\u003ePostsurgical complication rates vary among surgical service lines and among procedures within each service line.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] Furthermore, older patients having non-cardiac surgery experience higher postoperative complication rates.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] Despite knowing this data, surgeons and anesthesiologists rarely document individualized preoperative surgical risk assessment. Specifically, our previous multi-center study found that only 16.08% of surgeons and 4.76% of anesthesiologists documented preoperative risk predictions in patients who had poor outcomes, and only 1.3% included a named risk assessment tool. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAccording to the 2010 Salzburg statement on shared decision-making, patients have the right to be made aware of specific risks regarding their procedures, and physicians must provide accurate information about options, uncertainties, benefits, and harms of treatment. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] The 1982 President's Commission for the Study of Ethical Problems in Medicine established that patients \"must have all relevant information regarding their condition and alternative treatments, including possible benefits, risks, costs, other consequences, and significant uncertainties.\" Individualized risk assessments represent a National Quality Strategy surgical measure and are required by medical societies and regulatory bodies. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] Additionally, patients may be more motivated to follow a preoptimization plan, including exercise, diet modification, alcohol and tobacco cessation, when coached and presented with an accurate and detailed risk assessment. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe primary purpose for collecting these data prospectively was to validate findings from smaller trials demonstrating that major inpatient surgery is associated with high postsurgical complication rates. Secondary objectives included characterizing complication types, timing, and associations with age, sex, and service lines. This study offers a more accurate picture of perioperative morbidity than self-reported event data, which lacks a denominator, thereby better informing perioperative shared decision-making and the development of evidence-based pathways to mitigate these complications.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe created a tool to prospectively collect administrative data from each clinician-patient interaction (encounter level billing data) that occurred within 35 different facilities for patients undergoing inpatient surgeries between October 1, 2017 and December 12, 2023. Facilities were located across seven states, including Florida, California, New Jersey, Texas, Georgia, Arkansas, and Arizona. Private health system affiliates made up 88%, while university-affiliated institutions represented a minority. Trauma center designations were present in 47%, with the majority holding Level II designations. The licensed bed capacity varied between 67 beds and 898 beds [median bed count was 238, with a mean of 263 beds.]\u003c/p\u003e \u003cp\u003eCurrent Procedural Terminology (CPT) codes for specific surgical procedures were categorized into service lines including cardiac, thoracic, general, and neurosurgery, urology, gynecology, orthopedics, and others.\u003c/p\u003e \u003cp\u003ePostsurgical morbidities were defined and categorized using the International Classification of Diseases, Tenth Revision (ICD-10) codes and sorted into pulmonary, cardiac, renal, neurologic, hemorrhagic, and septic complications. We utilized the Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators Technical Specifications Updates - Version v2018 and v2018.0.1 (ICD 10), June 2018 to quantify complications involving hemorrhage, respiratory failure, sepsis, pneumothorax, acute renal failure, wound dehiscence.\u003c/p\u003e \u003cp\u003eAdditional organ specific ICD-10 codes were applied for complications not included in the AHRQ Patient Safety Indicator categories including cardiac, neurologic, gastrointestinal, ocular, and other organ system complications (supplementary data). Age, sex, American Society of Anesthesiologists physical status (ASA-PS) classification, and the postoperative day when a complication was reported were abstracted from the database.\u003c/p\u003e \u003cp\u003eThe proportion of postsurgical complications was defined as the total number of complications divided by the total surgical inpatient population, further stratified by service line, procedure type, and postoperative day. While complications were captured for each patient\u0026rsquo;s entire stay, we report findings from the first seven days of hospitalization as this time frame captures the majority of complications. COVID-19 pandemic periods were defined as: pre-COVID-19 (October 1, 2017 - March 31, 2020), early COVID-19 surge (April 1, 2020 - June 1, 2020), early post-COVID-19 (June 2, 2020 - November 10, 2021), and post-COVID-19 (November 11, 2021 - March 31, 2023). This work received IRB exemption (D4 determination).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study included 1,214,539 surgical inpatients, of whom 92,311 experienced complications, yielding an overall complication proportion of 7.6% (range 0.52% \u0026minus;\u0026thinsp;23.72%). Study population characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStudy Population Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy Period\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOctober 1, 2017 - December 23, 2023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Centers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Surgical Inpatients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,214,539\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients with Complications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92,311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall Complication Rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.6% (range 0.52% \u0026minus;\u0026thinsp;23.72%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eComplication rates varied substantially by surgical service line (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Cardiac surgery demonstrated the highest rate (23.72%), followed by extracorporeal membrane oxygenation (ECMO) procedures (20.31%), neurosurgery (19.89%), thoracic surgery (19.08%), vascular surgery (11.59%), general surgery (10.39%), orthopedic surgery (8.86%), urology (7.82%), gynecology (2.16%), and ophthalmology (0.52%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComplication Rates by Surgical Service Line and Complication Type\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgical Service Line\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplication Rate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac Surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECMO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeurosurgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic Surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular Surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral Surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrthopedic Surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGynecology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOphthalmology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplication Type (within 7 days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRate per 1000 Patients\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative Pulmonary Complications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute Kidney Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostsurgical Sepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute Coronary Syndrome\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke and New Neurologic Deficit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac Arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe most frequent major complications within 7 days of surgery per 1000 patients were: postoperative pulmonary complications (6.41), acute kidney injury (5.36), postsurgical sepsis (4.64), acute coronary syndromes (1.00), stroke and or new neurologic deficit (0.69), and cardiac arrest (0.63) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eComplications occurred more frequently in males (9.20%) than females (6.46%) and increased progressively with age (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Complication rates varied across American Society of Anesthesiologist Physical Status (ASA-PS) classifications for both elective and emergency procedures. Elective cases had complication rates of 2% for ASA-PS 1, 19% for ASA-PS 2, 56% for ASA-PS 3, and 29% for ASA-PS 4. Emergency cases had rates of 4% for ASA-PS 1E, 19% for ASA-PS 2E, 43% for ASA-PS 3E, and 39% for ASA-PS 4E. Complication rates did not follow a strict linear pattern across ascending ASA-PS classifications in either emergency or non-emergency groups. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComplication Rates by Patient Demographics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Group (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplication Rate (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e61\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e71\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e81\u0026ndash;90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e91\u0026ndash;100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eComplication Rate (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eASA Physical Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eComplication Rate (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA PS 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA PS 1E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA PS 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA PS 2E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA PS 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA PS 3E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA PS 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA PS 4E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cem\u003e*Impacted by small sample size\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eComplications were highest (10.56%) during the emergency surgery only phase of the Covid-19 pandemic. Post-pandemic complication rates (7.68%) declined below pre-pandemic levels (8.32%). Annual complication rates and COVID-19 pandemic period analyses are presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eA 17-fold variation in facility-level complication rates was observed (Fig.\u0026nbsp;1). There was a dramatic escalation of complication risk among low-volume procedures. Specifically, 10 distinct cardiac procedures (specialized valve reconstructions, thoracic aortic procedures, and complex hybrid cardiac operations) with fewer than 5\u0026ndash;10 cases performed were associated with 100% complication rates. (Fig.\u0026nbsp;1)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur comprehensive multi-center analysis involving millions of patients highlights the significant morbidity burden associated with major surgical procedures. This study confirms that complications following major inpatient surgeries occur in up to 25% of surgical inpatients having high-risk surgical interventions. This validates the findings of multiple smaller studies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Furthermore, our overall 7.6% complication rate aligns with that published by Chen et al. in their survey of 113 US Department of Veterans Affairs hospitals, which sampled over 500,000 operations. This substantial external correlation provides further support and validation for both our methodology and our findings. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eOur finding that pulmonary complications, acute kidney injury, and sepsis occur more frequently than cardiac or neurologic events has important implications for perioperative risk modification, risk communication, shared decision making, and planning. While cardiac events have traditionally dominated preoperative risk discussions, these data suggest that pulmonary and renal complications warrant equal attention in shared decision-making conversations and preprocedural optimization. Given the lack of an ICD-10 code for myocardial injury following non-cardiac surgery (MINS), we were unable to quantify MINS in this population. This potentially skews our findings. Recent evidence demonstrates that adverse events occur in more than one-third of surgical inpatients, with nearly half classified as major and most potentially preventable. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe progressive increase in complication rates with advancing age\u0026mdash;from 0.67% in pediatric patients to 15.65% in nonagenarians\u0026mdash;reinforces the importance of age-specific risk assessment. The higher complication rate in males (9.20% vs 6.46%) represents another demographic difference that warrants further study, and should play a key role during individualized risk discussions and shared decision-making.\u003c/p\u003e \u003cp\u003eComplication rates across the American Society of Anesthesiologists Physical Status (ASA-PS) classification system did not follow the expected linear pattern. The disproportionately high rate among ASA-PS 3 elective cases (56%) relative to ASA-PS 4 elective cases (29%) may reflect surgical selection bias, whereby the highest-acuity patients are offered intervention only under the most favorable conditions. Similarly, the lower complication rate in ASA-PS 3E versus ASA-PS 3 elective cases (43% vs. 56%) challenges the assumption that emergency designation uniformly confers additional risk. The marked difference between ASA-PS 1 and ASA-PS 2 elective cases (2% vs. 19%) further suggests that even minor increments in comorbidity burden may carry substantial perioperative impact.\u003c/p\u003e \u003cp\u003eThese findings must be interpreted in the context of well-documented inter-provider variability in ASA-PS assignment. Sanford et al. demonstrated a lack of interrater reliability across 70 anesthesia providers using standardized clinical vignettes, with no correlation between ASA-PS scoring and years of practice or provider type.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] Tollinche et al. similarly found very little inter-rater reliability when comparing ASA-PS assignments for the same patient across two different providers, with even same-provider reliability proving only moderate. This degree of classification inconsistency introduces misclassification bias that is difficult to quantify and may distort the complication rates that we observed. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] However, many risk assessment tools including the American College of Surgeons National Surgical Quality Improvement Project (ACS-NSQIP) Surgical Risk Calculator has found the ASA-PS a robust contributor to risk.\u003c/p\u003e \u003cp\u003eOur multicenter, procedure-level analysis of perioperative complication rates reveals a complex risk landscape that cannot be adequately characterized by institutional volume or aggregate complication rates alone. The high complication rates in certain cardiac procedures is likely due to small sample sizes, complex procedures that include the highest-risk patients, and potential gaps in institutional experience and preparedness for rare cardiac interventions. The 17-fold variation in facility-level complication rates and the dramatic escalation of complication risks among low-volume procedures (including 100% complication rates for multiple rare cardiac interventions) collectively demonstrate that procedural complexity, institutional experience, and case-mix composition are the primary determinants of perioperative safety.\u003c/p\u003e \u003cp\u003eThese findings carry significant implications for healthcare policies, surgical quality improvement, and patient safety initiatives. Specifically, they support the development of procedure-specific quality standards, minimum volume thresholds for complex cardiac interventions, and risk-adjusted benchmarking frameworks that can drive meaningful, targeted improvements across the full spectrum of perioperative care. Ultimately, addressing this variability through systematic quality improvement has the potential to significantly reduce preventable complications, improve patient outcomes, and optimize the allocation of specialized cardiac surgical resources across the healthcare system.\u003c/p\u003e\n\u003ch3\u003eThe Critical Gap Between Complication Rates and Risk Documentation\u003c/h3\u003e\n\u003cp\u003eThis study and our previous work on risk documentation reveal a significant disconnect between surgical morbidity and current risk communication practices. Despite complication rates approaching 1 in 4 patients for high-risk procedures, our prior work demonstrates that only 16.08% of surgeons and 4.76% of anesthesiologists documented individualized risk assessments in patients who subsequently experienced poor outcomes.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Even more striking, only 1.3% of these patients had risks determined by a validated risk assessment tool, such as the ACS NSQIP Surgical Risk Calculator.\u003c/p\u003e \u003cp\u003e This gap represents a fundamental deficiency in the informed consent process, and perhaps a missed opportunity for organ specific preoperative optimization. Surgeons routinely discuss components of informed consent with patients before high-risk surgery. However, they may not be aware of the specific risks of a particular surgery, their own complication rates or those of the system of care they work in. They may fail to fully inform patients of these risks. Some surgeons do not fully explore the patient\u0026rsquo;s uncertainty, understanding, or preferences. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] A systematic review of preoperative risk discussion found high levels of intra-surgeon variation in what risk information is provided to patients. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] Additionally, less than 50% of patients who consented for common procedures demonstrated an adequate understanding of the procedures they consented to receive. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] Ideally, patients should receive information regarding procedural volume, facility-specific resources, and whether dedicated perioperative care teams exist. Patients need to know the rates of complications and the types of complications. When clinicians fail to provide individualized risk information and presume what a patient wants, needs, or prefers, a \"preference misdiagnosis\" may lead to interventions that a fully informed patient might not want. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e\n\u003ch3\u003eThe Case for Public Reporting of Complication Data\u003c/h3\u003e\n\u003cp\u003eGiven the magnitude of perioperative morbidity documented in this study, patients should have access to institutional and procedure-specific complication data before consenting to surgery. Public reporting of outcome data is intended to drive quality improvement, demonstrate transparency, facilitate patient choice, and allow identification of poor performance.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] Nearly 90% of patients desire to review an individualized risk report before surgical consent, and high-risk patients are three times more likely to underestimate their risk of any complications, serious complications, and length of stay compared to low-risk patients.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eWhile concerns exist regarding public reporting, including risk aversion, gaming, and data misinterpretation, the advantages of reporting outcomes outweigh the disadvantages.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] Patient surveys indicate that 72% believe they should be made aware of surgeon-specific outcome data. The majority recognize the utility of such data to inform treatments and surgeon choice. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] All perioperative physicians, including surgeons, have a duty to develop information systems that allow performance to be evaluated accurately and communicated transparently. Ultimately, what a patient really wants to know is the individual experience and competency of their operating surgeon or anesthesiologist, not numbers quoted from the peer reviewed literature.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThis study has important limitations inherent to retrospective administrative database analyses. Our identification of complications relied on ICD-10 coding which may underestimate true rates. MINS was not captured at all due to lack of a specific ICD-10 coding.\u003c/p\u003e \u003cp\u003eFacility specific data in this study were not risk adjusted, limiting our ability to make detailed comparisons. Nor were we able to determine severity of complications or morbidity and mortality associated with complications. Finally, this work presents complications that occurred within 7 days of surgery, whilst some patients developed complications later during their hospitalization.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis large, multicenter analysis demonstrates that perioperative complications following major inpatient surgery occur in up to 1 in 4 patients in high-risk surgical populations. Postoperative pulmonary complications, acute kidney injury, and sepsis occur more frequently than cardiac or neurologic events. Complication rates increase with age and male sex.\u003c/p\u003e \u003cp\u003eDespite these substantial and well-established risks, documentation of individualized risk assessment and shared decision-making remain alarmingly rare in clinical practice. This represents a failure to meet the ethical obligations of informed consent. Patients have a fundamental right to know these complication data\u0026mdash;both their individualized risk and institutional outcomes\u0026mdash;before consenting to surgery. Without documented individualized risk assessment, the quality of informed consent must be questioned, because the prediction and sharing of risk provides the foundation for perioperative decision-making and individualized physiologic optimization.\u003c/p\u003e \u003cp\u003eWe urge medical societies and medical colleges, facilities, and health systems to support the collection of morbidity data, and to make these rates publicly available. Transparency in surgical outcomes is not merely a quality improvement initiative, It is an ethical imperative that respects patient autonomy and enables truly informed shared decision-making. The type of data presented here should be accessible to every patient facing major surgery.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e This work received IRB exemption (D4 determination).\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Data are completely de-identified. No individual personal data is reported.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e The datasets used and analyzed during the current study may be available from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This project was funded internally by Envision Healthcare\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e JAB-conception, design, author, data acquisition, interpretation. BTH-editor, author. BK-editor, author. LR-editor, author. GM-editor, author. RT-editor. RN-editor. TH-editor, SS-statistical analysis, author. RS- statistical analysis, editor. BI-data curation. NG-data curation. HG- data curation. BJS- editor, author. All authors have read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWeiser TG, Regenbogen SE, Thompson KD, Haynes AB, Lipsitz SR, Berry WR, Gawande AA. An estimation of the global volume of surgery: a modelling strategy based on available data. Lancet. 2008;372(9633):139\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(08)60878-8\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(08)60878-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2008 Jun 24. PMID: 18582931.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOverview of Operating Room Procedures During Inpatient Stays in U.S. Hospitals. 2018 AHRQ HCUP Data. 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PMID: 17414595; PMCID: PMC1877054.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table 4","content":"\u003cp\u003eTable 4 is available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"perioperative-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"peri","sideBox":"Learn more about [Perioperative Medicine](http://perioperativemedicinejournal.biomedcentral.com)","snPcode":"13741","submissionUrl":"https://submission.nature.com/new-submission/13741/3","title":"Perioperative Medicine","twitterHandle":"@EMSurgeryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Perioperative complications, surgical morbidity, risk assessment, shared decision-making, postoperative pulmonary complications, acute kidney injury, public reporting","lastPublishedDoi":"10.21203/rs.3.rs-9397441/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9397441/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMajor inpatient surgery is associated with significant postoperative morbidity, yet large-scale contemporary data characterizing complication patterns remain limited. Understanding complication epidemiology is essential for individualized risk assessment and shared decision-making. This study aimed to validate prior findings of perioperative complication rates and characterize complication patterns by type, timing, surgical service, patient demographics, and the COVID-19 pandemic period.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe developed a tool in early 2019 to prospectively collect perioperative outcomes for patients undergoing major inpatient surgery across 35 different medical centers. We analyzed data from 1,214,539 surgical inpatients receiving care between October 2017 and December 2023. Complications were time stamped and identified using ICD-10 codes, and categorized as pulmonary, cardiac, renal, neurologic, hemorrhagic, or septic. Complication proportions were stratified by surgical service line, postoperative day, age, sex, and American Society of Anesthesiologists physical status.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe overall complication rate was 7.6% (range 0.52%-23.72% by service line). Cardiac surgery (23.72%), ECMO (20.31%), and neurosurgery (19.89%) had the highest complication rates. The most frequent complications within 7 days per 1000 patients were: postoperative pulmonary complications (6.41), acute kidney injury (5.36), postsurgical sepsis (4.64), acute coronary syndrome (1.00), stroke (0.69), and cardiac arrest (0.63). Complications increased with age (0.67% ages 0\u0026ndash;10 years to 15.65% ages 91\u0026ndash;100) and were higher in males (9.20%) than females (6.46%). Post-pandemic complication rates (7.68%) declined below pre-pandemic levels (8.32%) and were highest during the emergency surgery only phase of the pandemic (10.53%). Complication rates ranged from a facility-level low of 0.96% to a high of 15.98%, while at the procedure level (CPT codes), certain low-volume interventions had 100% complication rates.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eComplications following major inpatient surgery occur in up to 1 in 4 patients in high-risk surgical populations, and vary significantly by institution and procedure. Surgical facilities should utilize similar methodologies to define their own outcomes to drive perioperative quality improvement. Furthermore, patients have a fundamental right to know these data before consenting to surgery. Institutional complication rates should be made publicly available to facilitate shared decision-making and informed consent.\u003c/p\u003e","manuscriptTitle":"Perioperative Complications at Scale: A Multi-Center Analysis of 1.2 Million Surgical Inpatients and the Ethical Imperative for Risk Transparency","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 05:45:29","doi":"10.21203/rs.3.rs-9397441/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-07T17:41:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293036738052370798376959691246884170388","date":"2026-04-23T06:58:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-20T15:40:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-15T10:07:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-15T10:07:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"Perioperative Medicine","date":"2026-04-13T01:16:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"perioperative-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"peri","sideBox":"Learn more about [Perioperative Medicine](http://perioperativemedicinejournal.biomedcentral.com)","snPcode":"13741","submissionUrl":"https://submission.nature.com/new-submission/13741/3","title":"Perioperative Medicine","twitterHandle":"@EMSurgeryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dcb36956-913e-4df1-9072-a25688e1ef9f","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-07T17:41:53+00:00","index":10,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T05:45:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 05:45:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9397441","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9397441","identity":"rs-9397441","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}