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This paper examines the decision-making processes of physicians and intelligent agents within the healthcare sector, particularly focusing on their characteristics, architectures, and approaches. We provide a theoretical insight into the evolving role of artificial intelligence (AI) in healthcare, emphasizing its potential to address various healthcare challenges. Defining features of intelligent agents are explored, including their perceptual abilities and behavioral properties, alongside their architectural frameworks, ranging from reflex-based to general learning agents, and contrasted with the rational decision-making structure employed by physicians. Through data collection, hypothesis generation, testing, and reflection, physicians exhibit a nuanced approach informed by adaptability and contextual understanding. A comparative analysis between intelligent agents and physicians reveals both similarities and disparities, particularly in adaptability and contextual comprehension. While intelligent agents offer promise in enhancing clinical decisions, challenges with types of dataset biases pose significant hurdles. Informing and educating physicians about AI concepts can build trust and transparency in intelligent programs. Such efforts aim to leverage the strengths of both human and AI toward improving healthcare delivery and outcomes.
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BACKGROUND: The cost-to-charge ratio reflects the markup of hospital services. A lower cost-to-charge ratio indicates lower costs and/or greater charges. This study examines factors associated with cost-to-charge ratio trends to determine whether decreasing cost-to-charge ratio is associated with worse surgical outcomes. METHODS: The Florida Agency for Healthcare Administration Inpatient database (2018-2020) was queried for common surgical procedures and linked to the Distressed Communities Index, RAND Corporation Hospital data, Center for Medicare Services Cost Reports, and American Hospital Association data. Only hospitals with monotonically increasing or decreasing cost-to-charge ratio were included in the study. Univariable analysis compared these hospitals. Using patient-level data, interpretable machine learning predicted cost-to-charge ratio trend while identifying influential factors. RESULTS: The cohort had 67 hospitals (27 increasing cost-to-charge ratio and 40 decreasing cost-to-charge ratio) with 35,661 surgeries. Decreasing cost-to-charge ratio hospitals were more often proprietarily owned (78% vs 33%, P = .01) and had greater mean total charges ($134,349 ± $114,510 vs $77,185 ± $82,027, P < .01) with marginally greater mean estimated costs ($14,863 ± $12,343 vs $14,458 ± $15,440, P < .01). Patients from decreasing cost-to-charge ratio hospitals had greater rates of most comorbidities (P < .05) but no difference in mortality or overall complications. Machine-learning models revealed charges rather than clinical factors as most influential in cost-to-charge ratio trend prediction. CONCLUSIONS: Decreasing cost-to-charge ratio hospitals charge vastly more despite minimally greater estimated costs and no difference in outcomes. Although differences in case-mix existed, charges were the predominant differentiators. Patient clinical factors had far less of an impact.
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OBJECTIVE: We sought to determine the premium associated with a career in academic surgery, as measured by compensation normalized to the work relative value unit (wRVU). BACKGROUND: An academic surgical career, embodying innovation and mentorship, offers intrinsic rewards, but is not well monetized. We know compensation for academic surgeons is less than their non-academic counterparts, but the value of clinical effort, as normalized to the wRVU, between academic and non-academic surgeons has not been well characterized. Thus, we analyzed the variations in the valuation of academic and non-academic surgical work from 2010 to 2022. METHODS: We utilized Medical Group Management Association Provider Compensation data from 2010, 2014, 2018, and 2022 to compare academic and non-academic surgeons. We analyzed raw total cash compensation (TCC), wRVU, TCC per wRVU (TCC/wRVU), and TCC to collections (TCCtColl). We calculated collections per wRVU (Coll/wRVU). We adjusted TCC and TCCtColl for inflation using the Consumer Price Index. Linear modeling for trend analysis was performed. RESULTS: Compared to non-academic, academic surgeons had lower TCC (2010: $500,415.0±23,666 vs. $631,515.5±23,948.2, -21%; 2022: $564,789.8±23,993.9 vs. $628,247.4±15,753.2, -10%), despite higher wRVUs (2022: 9,109.4±474.9 vs. 8,062.7±252.7) and higher Coll/wRVU (2022: 76.68±8.15 vs. 71.80±6.10). Trend analysis indicated TCC will converge in 2038 at an estimated $660,931. CONCLUSIONS: In 2022, academic surgeons had more clinical activity and superior organizational revenue capture, despite less total and normalized clinical compensation. Based on TCC/wRVUs, academia charges a premium of 16% over non-academic surgery. However, trend analysis suggests that TCC will converge within the next twenty years.
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BACKGROUND: Patients with low socioeconomic status (SES) are disadvantaged in terms of access to health care. A novel metric for SES is the Distressed Communities Index (DCI). This study evaluates the effect of DCI on hospital choice and distance traveled for surgery. METHODS: A Florida database was queried for patients with symptomatic cholelithiasis or chronic cholecystitis who underwent an outpatient cholecystectomy between 2016 and 2019. Patients' DCI was compared with hospital ratings, comorbidities, Charlson Comorbidity Index, and distance traveled for surgery. Stepwise logistic regression was used to determine which factors most influenced distance traveled for surgery. RESULTS: There were 54,649 cases-81 open, 52,488 laparoscopic, and 2,080 robotic. There was no difference between surgical approach and patient's DCI group (p = 0.12). Rural patients traveled the farthest for surgery (avg 21.29 miles); urban patients traveled the least (avg 5.84 miles). Patients from distressed areas more often had surgery at one- or two-star hospitals than prosperous patients (61% vs 36.3%). Regression indicated distressed or at-risk areas predicted further travel for rural/small-town patients, while higher hospital ratings predicted further travel for suburban/urban patients. DISCUSSION: Compared to prosperous areas, patients from distressed areas have surgery at lower-rated hospitals, travel further if they live in rural/small-town areas, but travel less if they live in suburban areas. We postulate that farther travel in rural areas may be explained by a lack of health care resources in poor, rural areas, while traveling less in suburban areas may be explained by personal lack of resources for patients with low SES.
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Objective: This review introduces interpretable predictive machine learning approaches, natural language processing, image recognition, and reinforcement learning methodologies to familiarize end users. Background: As machine learning, artificial intelligence, and generative artificial intelligence become increasingly utilized in clinical medicine, it is imperative that end users understand the underlying methodologies. Methods: This review describes publicly available datasets that can be used with interpretable predictive approaches, natural language processing, image recognition, and reinforcement learning models, outlines result interpretation, and provides references for in-depth information about each analytical framework. Results: This review introduces interpretable predictive machine learning models, natural language processing, image recognition, and reinforcement learning methodologies. Conclusions: Interpretable predictive machine learning models, natural language processing, image recognition, and reinforcement learning are core machine learning methodologies that underlie many of the artificial intelligence methodologies that will drive the future of clinical medicine and surgery. End users must be well versed in the strengths and weaknesses of these tools as they are applied to patient care now and in the future.
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In evidence-based medicine, systematic review continues to carry the highest weight in terms of quality and reliability, synthesizing robust information from previously published cohort studies to provide a comprehensive overview of a topic. Meta-analysis provides further depth by allowing for comparative analysis between the studied intervention and the control group, providing the most up-to-date evidence on their characteristics and efficacy. We discuss the principles and methodology of meta-analysis, and its applicability to the field of surgical research. The clinical question is defined using PICO framework (Problem, Intervention, Comparison, Outcome). Then a systematic article search is performed across multiple medical databases using relevant search terms, which are then filtered out based on appropriate screening tools. Pertinent data from the selected articles are collected and undergo critical appraisal by at least two independent reviewers. Additional statistical tests may be performed to identify the presence of any significant bias. The data are then synthesized to perform comparative analysis between the intervention and comparison groups. In this article, we discuss specifically the usage of R software (R Foundation for Statistical Computing, Vienna, Austria) for data analysis and visualization. Meta-analysis results of the pooled data are presented using forest plots. Concerns for potential bias may be addressed through the creation of funnel plots. Meta-analysis is a powerful tool to provide highly reliable medical evidence. It may be readily performed by independent researchers with minimal need for funding or institutional approval. The ability to conduct such studies is an asset to budding medical scholars.
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INTRODUCTION: Identifying contributors to lung transplant survival is vital in mitigating mortality. To enhance individualized mortality estimation and determine variable interaction, we employed a survival tree algorithm utilizing recipient and donor data. METHODS: United Network Organ Sharing data (2000-2021) were queried for single and double lung transplants in adult patients. Graft survival time <7 d was excluded. Sixty preoperative and immediate postoperative factors were evaluated with stepwise logistic regression on mortality; final model variables were included in survival tree modeling. Data were split into training and testing sets and additionally validated with 10-fold cross validation. Survival tree pruning and model selection was based on Akaike information criteria and log-likelihood values. Estimated survival probabilities and log-rank pairwise comparisons between subgroups were calculated. RESULTS: A total of 27,296 lung transplant patients (8175 single; 19,121 double lung) were included. Stepwise logistic regression yielded 47 significant variables associated with mortality. Survival tree modeling returned six significant factors: recipient age, length of stay from transplant to discharge, recipient ventilator duration post-transplant, double lung transplant, recipient reintubation post-transplant, and donor cytomegalovirus status. Eight subgroups consisting of combinations of these factors were identified with distinct Kaplan-Meier survival curves. CONCLUSIONS: Survival trees provide the ability to understand the effects and interactions of covariates on survival after lung transplantation. Individualized survival probability with this technique found that preoperative and postoperative factors influence survival after lung transplantation. Thus, preoperative patient counseling should acknowledge a degree of uncertainty given the influence of postoperative factors.
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Trasplante de Pulmón , Trasplante de Pulmón/mortalidad , Trasplante de Pulmón/estadística & datos numéricos , Humanos , Femenino , Persona de Mediana Edad , Masculino , Adulto , Estimación de Kaplan-Meier , Anciano , Estudios Retrospectivos , Algoritmos , Supervivencia de InjertoRESUMEN
INTRODUCTION: The number of patients with congenital disease living to adulthood continues to grow. Often undergoing surgical correction in infancy, they continue to require lifelong care. Their numbers are largely unknown. We sought to evaluate hospital admissions of adult patients with esophageal atresia with tracheoesophageal fistula (EA/TEF), congenital diaphragmatic hernia (CDH), and Hirschsprung disease (HD). METHODS: The Florida Agency for Healthcare Administration inpatient database was merged with the Distressed Communities Index and Centers for Medicare and Medicaid Services Hospital and Physician Compare datasets. The dataset was queried for adult patients (≥18 y, born after 1970) with EA/TEF, CDH, and HD in their problem list from 2010 to 2020. Patient demographics, hospitalization characteristics, and discharge information were obtained. RESULTS: In total, 1140 admissions were identified (266 EA/TEF, 135 CDH, 739 HD). Patients were mostly female (53%), had a mean age of 31.6 y, and often admitted to an adult internist in a general hospital under emergency. Principal diagnoses and procedures (when performed) varied with diagnosis and age at admission. EA patients were admitted with dysphagia and foregut symptoms and often underwent upper endoscopy with dilation. CDH patients were often admitted for diaphragmatic hernias and underwent adult diaphragm repair. Hirschsprung patients were often admitted for intestinal obstructive issues and frequently underwent colonoscopy but trended toward operative intervention with increasing age. CONCLUSIONS: Adults with congenital disease continue to require hospital admission and invasive procedures. As age increases, diagnoses and performed procedures for each diagnoses evolve. These data could guide the formulation of multispecialty disease-specific follow-up programs for these patients.
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Atresia Esofágica , Hernias Diafragmáticas Congénitas , Enfermedad de Hirschsprung , Humanos , Femenino , Masculino , Adulto , Enfermedad de Hirschsprung/cirugía , Enfermedad de Hirschsprung/epidemiología , Hernias Diafragmáticas Congénitas/cirugía , Hernias Diafragmáticas Congénitas/epidemiología , Florida/epidemiología , Atresia Esofágica/cirugía , Adulto Joven , Fístula Traqueoesofágica/cirugía , Fístula Traqueoesofágica/epidemiología , Persona de Mediana Edad , Sobrevivientes/estadística & datos numéricos , Hospitalización/estadística & datos numéricos , Adolescente , Estudios Retrospectivos , Lactante , Bases de Datos Factuales/estadística & datos numéricosRESUMEN
BACKGROUND: The impact of different phases of COVID-19 infection on outcomes from acute calculous cholecystitis (ACC) is not well understood. Therefore, we examined outcomes of acute cholecystitis during the COVID-19 pandemic, comparing the effect of different treatment modalities and COVID-19 infection status. We hypothesized that patients with acute COVID-19 would have worse outcomes than COVID-negative patients, but there would be no difference between COVID-negative and COVID-recovered patients. METHODS: We used 2020-2023 National COVID Cohort Collaborative data to identify adults with ACC. Treatment (antibiotics-only, cholecystostomy tube, or cholecystectomy) and COVID-19 status (negative, active, or recovered) were collected. Treatment failure of nonoperative managements was noted. Adjusted analysis using a series of generalized linear models controlled for confounders (age, sex, body mass index, Charlson comorbidity index, severity at presentation, and year) to better assess differences in outcomes among treatment groups, as well as between COVID-19 groups. RESULTS: In total, 32,433 patients (skewed count) were included: 29,749 COVID-negative, 2112 COVID-active, and 572 (skewed count) COVID-recovered. COVID-active had higher rates of sepsis at presentation. COVID-negative more often underwent cholecystectomy. Unadjusted, COVID-active had higher 30-day mortality, 30-day complication, and longer length of stay than COVID-negative and COVID-recovered. Adjusted analysis revealed cholecystectomy carried lower odds of mortality for COVID-active and COVID-negative patients than antibiotics or cholecystostomy. COVID-recovered patients' mortality was unaffected by treatment modality. Treatment failure from antibiotics was more common for COVID-negative patients. CONCLUSION: Acute cholecystitis outcomes are affected by phase of COVID-19 infection and treatment modality. Cholecystectomy does not lead to worse outcomes for COVID-active and COVID-recovered patients than nonoperative treatments; thus, these patients can be considered for cholecystectomy if their physiology is not prohibitive.
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COVID-19 , Colecistectomía , Colecistitis Aguda , Colecistostomía , Humanos , COVID-19/complicaciones , COVID-19/terapia , COVID-19/epidemiología , COVID-19/mortalidad , Femenino , Masculino , Colecistitis Aguda/terapia , Persona de Mediana Edad , Anciano , Colecistostomía/métodos , Antibacterianos/uso terapéutico , Resultado del Tratamiento , SARS-CoV-2 , Adulto , Tiempo de Internación/estadística & datos numéricos , Estudios Retrospectivos , Anciano de 80 o más AñosRESUMEN
Background: The COVID-19 pandemic necessitated changes in processes of care, which significantly impacted surgical care. This study evaluated the impact of these changes on patient outcomes and costs for non-elective major lower extremity amputations (LEA). Methods: The 2019-2021 Florida Agency for Health Care Administration database was queried for adult patients who underwent non-elective major LEA. Per-patient inflation-adjusted costs were collected. Patient cohorts were established based on Florida COVID-19 mortality rates: COVID-heavy (CH) included nine months with the highest mortality, COVID-light (CL) included nine months with the lowest mortality, and pre-COVID (PC) included nine months before COVID (2019). Outcomes included in-hospital patient outcomes and hospitalization cost. Results: 6132 patients were included (1957 PC, 2104 CH, and 2071 CL). Compared to PC, there was increased patient acuity at presentation, but morbidity (31%), mortality (4%), and length of stay (median 12 [8-17] days) were unchanged during CH and CL. Additionally, costs significantly increased during the pandemic; median total cost rose 9%, room costs increased by 16%, ICU costs rose by 15%, and operating room costs rose by 15%. When COVID-positive patients were excluded, cost of care was still significantly higher during CH and CL. Conclusions: Despite maintaining pre-pandemic standards, as evidenced by unchanged outcomes, the pandemic led to increased costs for patients undergoing non-elective major LEA. This was likely due to increased patient acuity, resource strain, and supply chain shortages during the pandemic. Key message: While patient outcomes for non-elective major lower extremity amputations remained consistent during the COVID-19 pandemic, healthcare costs significantly increased, likely due to increased patient acuity and heightened pressures on resources and supply chains. These findings underscore the need for informed policy changes to mitigate the financial impact on patients and healthcare systems for future public health emergencies.
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We present a rare case of prolonged ileus caused by underlying Shigella infection after surgical hernia repair. Infectious disease is an uncommon cause of postoperative prolonged ileus in adults. Our 48-year-old male patient underwent bilateral open inguinal hernia repair and open umbilical hernia repair without complication at an academic institution, with same-day discharge. Eight days later, he presented to the emergency department with complaints of severe cramping abdominal pain, nausea, emesis, and watery diarrhea. Physical examination, computed tomography scan of the abdomen and pelvis, and abdominal X-ray were initially concerning for bowel obstruction. The patient was admitted to the general surgery service. Concern for ileus with underlying gastritis arose after a small bowel follow-through showed contrast eventually reaching the rectum. A subsequent gastrointestinal pathogens panel was positive for Shigella. The patient's symptoms resolved after appropriate antibiotic treatment. Shigellosis and other infectious diseases should be considered in the differential diagnosis of postoperative prolonged ileus.
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Pre-existing cirrhosis is associated with increased mortality in blunt liver injury. Despite widespread use of nonoperative management (NOM) for blunt liver injury, there is a relative paucity of data regarding how pre-existing cirrhosis impacts the success of NOM. Herein, we perform a retrospective cohort study using ACS TQIP 2017-2020 data to assess the relationship between cirrhosis and failure of NOM for adult patients with blunt liver injury. 37,176 patients were included (342 cirrhosis and 36,834 without cirrhosis). After propensity-score matching, patients with pre-existing cirrhosis had higher rates of failure of NOM (32.2 vs 14.1%, p < 0.01) and in-hospital mortality (36.3 vs 10.8%, p < 0.01) than patients without cirrhosis. Hesitancy to operate on patients with pre-existing cirrhosis and trauma, as well as significant underlying coagulopathy, may explain these findings.
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Cirrosis Hepática , Hígado , Insuficiencia del Tratamiento , Heridas no Penetrantes , Humanos , Heridas no Penetrantes/terapia , Heridas no Penetrantes/complicaciones , Heridas no Penetrantes/mortalidad , Estudios Retrospectivos , Masculino , Femenino , Persona de Mediana Edad , Cirrosis Hepática/complicaciones , Cirrosis Hepática/terapia , Hígado/lesiones , Adulto , Mortalidad Hospitalaria , Puntaje de Propensión , AncianoRESUMEN
BACKGROUND: Firearm-related death rates continue to rise in the US. As some states enact more permissive firearm laws, we sought to assess the relationship between a change to permitless open carry (PLOC) and subsequent firearm-related death rates, a currently understudied topic. STUDY DESIGN: Using state-level data from 2013 to 2021, we performed a linear panel analysis using a state fixed-effects model. We examined total firearm-related death, suicide, and homicide rates separately. If a significant association between OC law and death rate was found, we then performed a difference-in-difference (DID) analysis to assess for a causal relationship between changing to PLOC and increased death rate. For significant DID results, we performed confirmatory DID separating firearm and nonfirearm death rates. RESULTS: Nineteen states maintained a no OC or permit-required law, whereas 5 changed to permitless and 26 had a PLOC before 2013. The fixed-effects model indicated more permissive OC law that was associated with increased total firearm-related deaths and suicides. In DID, changing law to PLOC had a significant average treatment effect on the treated of 1.57 (95% CI 1.05 to 2.09) for total suicide rate but no significant average treatment effect for the total firearm-related death rate. Confirmatory DID results found a significant average treatment effect on the treated of 1.18 (95% CI 0.90 to 1.46) for firearm suicide rate. CONCLUSIONS: OC law is associated with total firearm-related death and suicide rates. Based on our DID results, changing to PLOC is indeed strongly associated with increased suicides by firearm.
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Armas de Fuego , Suicidio , Heridas por Arma de Fuego , Humanos , Estados Unidos/epidemiología , HomicidioRESUMEN
The surgical robot is assumed to be a fixed, indirect cost. We hypothesized rising volume of robotic bariatric procedures would decrease cost per patient over time. Patients who underwent elective, initial gastric bypass (GB) or sleeve gastrectomy (SG) for morbid obesity were selected from Florida Agency for Health Care Administration database from 2017 to 2021. Inflation-adjusted cost per patient was collected. Cost-over-time ($/patient year) and change in cost-over-time were calculated for open, laparoscopic, and robotic cases. Linear regression on cost generated predictive parameters. Density plots utilizing area under the curve demonstrated cost overlap. Among 76 hospitals, 11,472 bypasses (223 open, 6885 laparoscopic, 4364 robotic) and 36,316 sleeves (26,596 laparoscopic, 9724 robotic) were included. Total cost for robotic was approximately 1.5-fold higher (p < 0.001) than laparoscopic for both procedures. For GB, laparoscopic had lower total ($15,520) and operative ($6497) average cost compared to open (total $17,779; operative $9273) and robotic (total $21,756; operative $10,896). For SG, laparoscopic total cost was significantly less than robotic ($10,691 vs. $16,393). Robotic GB cost-over-time increased until 2021, when there was a large decrease in cost (-$944, compared with 2020). Robotic SG total cost-over time fluctuated, but decreased significantly in 2021 (-$490 compared with 2020). While surgical costs rose significantly in 2020 for bariatric procedures, our study suggests a possible downward trend in robotic bariatric surgery as total and operative costs are decreasing at a higher rate than laparoscopic costs.
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Cirugía Bariátrica , Derivación Gástrica , Laparoscopía , Obesidad Mórbida , Procedimientos Quirúrgicos Robotizados , Robótica , Humanos , Procedimientos Quirúrgicos Robotizados/métodos , Estudios Retrospectivos , Cirugía Bariátrica/métodos , Derivación Gástrica/métodos , Obesidad Mórbida/cirugía , Costos y Análisis de Costo , Gastrectomía/métodos , Resultado del TratamientoRESUMEN
Robotic surgery may decrease surgeon stress compared to laparoscopic. To evaluate intraoperative surgeon stress, we measured salivary alpha-amylase and cortisol. We hypothesized robotic elicited lower increases in surgeon salivary amylase and cortisol than laparoscopic. Surgical faculty (n = 7) performing laparoscopic and robotic operations participated. Demographics: age, years in practice, time using laparoscopic vs robotic, comfort level and enthusiasm for each. Operative data included operative time, WRVU (surgical "effort"), resident year. Saliva was collected using passive drool collection system at beginning, middle and end of each case; amylase and cortisol measured using ELISA. Standard values were created using 7-minute exercise (HIIT), collecting saliva pre- and post-workout. Linear regression and Student's t test used for statistical analysis; p values < 0.05 were significant. Ninety-four cases (56 robotic, 38 laparoscopic) were collected (April-October 2022). Standardized change in amylase was 8.4 ± 4.5 (p < 0.001). Among operations, raw maximum amylase change in laparoscopic and robotic was 23.4 ± 11.5 and 22.2 ± 13.4; raw maximum cortisol change was 44.21 ± 46.57 and 53.21 ± 50.36, respectively. Values normalized to individual surgeon HIIT response, WRVU, and operative time, showing 40% decrease in amylase in robotic: 0.095 ± 0.12, vs laparoscopic: 0.164 ± 0.16 (p < 0.02). Normalized change in cortisol was: laparoscopic 0.30 ± 0.44, robotic 0.22 ± 0.4 (p = NS). On linear regression (p < 0.001), surgeons comfortable with complex laparoscopic cases had lower change in normalized amylase (p < 0.01); comfort with complex robotic was not significant. Robotic may be less physiologically stressful, eliciting less increase in salivary amylase than laparoscopic. Comfort with complex laparoscopic decreased stress in robotic, suggesting laparoscopic experience is valuable prior to robotic.
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Laparoscopía , Procedimientos Quirúrgicos Robotizados , Cirujanos , Humanos , Procedimientos Quirúrgicos Robotizados/métodos , Hidrocortisona/análisis , AmilasasRESUMEN
BACKGROUND: Previous studies on nonoperative management (NOM) of acute appendicitis (AA) indicated comparable outcomes to surgery, but the effect of COVID-19 infection on appendicitis outcomes remains unknown. Thus, we evaluate appendicitis outcomes during the COVID-19 pandemic to determine the effect of COVID-19 infection status and treatment modality. We hypothesized that active COVID-19 patients would have worse outcomes than COVID-negative patients, but that outcomes would not differ between recovered COVID-19 and COVID-negative patients. Moreover, we hypothesized that outcomes would not differ between nonoperative and operative management groups, regardless of COVID-19 status. METHODS: We queried the National COVID Cohort Collaborative from 2020 to 2023 to identify adults with AA who underwent operative or NOM. COVID-19 status was denoted as follows: COVID-negative, COVID-active, or COVID-recovered. Intention to treat was used for NOM. Propensity score-balanced analysis was performed to compare outcomes within COVID groups, as well as within treatment modalities. RESULTS: A total of 37,868 patients were included: 34,866 COVID-negative, 2,540 COVID-active, and 460 COVID-recovered. COVID-active and recovered less often underwent operative management. Unadjusted, there was no difference in mortality between COVID groups for operative management. There was no difference in rate of failure of NOM between COVID groups. Adjusted analysis indicated, compared with operative, NOM carried higher odds of mortality and readmission for COVID-negative and COVID-active patients. CONCLUSION: This study demonstrates higher odds of mortality among NOM of appendicitis and near equivalent outcomes for operative management regardless of COVID-19 status. We conclude that NOM of appendicitis is associated with worse outcomes for COVID-active and COVID-negative patients. In addition, we conclude that a positive COVID test or recent COVID-19 illness alone should not preclude a patient from appendectomy for AA. Surgeon clinical judgment of a patient's physiology and surgical risk should, of course, inform the decision to proceed to the operating room. LEVEL OF EVIDENCE: Therapeutic/Care Management; Level III.
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Apendicitis , COVID-19 , Adulto , Humanos , Apendicitis/diagnóstico , Apendicitis/cirugía , Resultado del Tratamiento , Pandemias , Estudios Retrospectivos , COVID-19/terapia , COVID-19/complicaciones , Apendicectomía , Enfermedad AgudaRESUMEN
MINI-ABSTRACT: The study introduces various methods of performing conventional ML and their implementation in surgical areas, and the need to move beyond these traditional approaches given the advent of big data. OBJECTIVE: Investigate current understanding and future directions of machine learning applications, such as risk stratification, clinical data analytics, and decision support, in surgical practice. SUMMARY BACKGROUND DATA: The advent of the electronic health record, near unlimited computing, and open-source computational packages have created an environment for applying artificial intelligence, machine learning, and predictive analytic techniques to healthcare. The "hype" phase has passed, and algorithmic approaches are being developed for surgery patients through all stages of care, involving preoperative, intraoperative, and postoperative components. Surgeons must understand and critically evaluate the strengths and weaknesses of these methodologies. METHODS: The current body of AI literature was reviewed, emphasizing on contemporary approaches important in the surgical realm. RESULTS AND CONCLUSIONS: The unrealized impacts of AI on clinical surgery and its subspecialties are immense. As this technology continues to pervade surgical literature and clinical applications, knowledge of its inner workings and shortcomings is paramount in determining its appropriate implementation.
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Inteligencia Artificial , Cirujanos , Humanos , Aprendizaje Automático , Atención a la Salud , Ciencia de los DatosRESUMEN
The modern surgical leader now requires many tools for successful leadership. One critical tool is developing an integrated strategic plan where team and culture are developed with a directed common mission. This mission or strategic plan must fit within certain constraints, such as the larger institutional goals and constrained resources. To help develop this strategic plan, the surgical leader has many resources to use. The most common strategic planning tool is the Strengths, Weaknesses, Opportunities, and Threats analysis. Here, both internal and external factors are evaluated. From here, the contribution will review the Political, Economic, Social, Technological, Legal, and Environmental analysis (ideal for external factors) and Mission, Objectives, Strategies and Tactics analysis (ideal for internal factors), along with the Blue Ocean Strategy, Scenario Planning, and Ansoff Matrix, all of which are excellent for future planning. Porter's Five Forces will review standard competing forces, whereas Six Sigma reviews measurable process development, and Balanced Scorecard provides the framework for measurable advancements. After the paper, the reader will better understand the various tools that can be used to develop an integrated strategic plan.