Risk of Injury-Related Readmission Varies by Initial Presenting-Hospital Type Among Children at High Risk for Physical Abuse.

OBJECTIVES: Children experiencing physical abuse may initially present to hospitals with underappreciated minor injuries, only to experience more severe injuries in the future. The objectives of this study were to 1) describe young children presenting with high-risk diagnoses for physical abuse, 2) characterize the hospitals to which they initially presented, and 3) evaluate associations of initial presenting-hospital type with subsequent admission for injury. METHODS: Patients aged younger than 6 years from the 2009-2014 Florida Agency for Healthcare Administration database with high-risk diagnoses (codes previously associated with >70% risk of child physical abuse) were included. Patients were categorized by the hospital type to which they initially presented: community hospital, adult/combined trauma center, or pediatric trauma center. Primary outcome was subsequent injury-related hospital admission within 1 year. Association of initial presenting-hospital type with outcome was evaluated with multivariable logistic regression, adjusting for demographics, socioeconomic status, preexisting comorbidities, and injury severity. RESULTS: A total of 8626 high-risk children met inclusion criteria. Sixty-eight percent of high-risk children initially presented to community hospitals. At 1 year, 3% of high-risk children had experienced subsequent injury-related admission. On multivariable analysis, initial presentation to a community hospital was associated with higher risk of subsequent injury-related admission (odds ratio, 4.03 vs level 1/pediatric trauma center; 95% confidence interval, 1.83-8.86). Initial presentation to a level 2 adult or combined adult/pediatric trauma center was also associated with higher risk for subsequent injury-related admission (odds ratio, 3.19; 95% confidence interval, 1.40-7.27). CONCLUSIONS: Most children at high risk for physical abuse initially present to community hospitals, not dedicated trauma centers. Children initially evaluated in high-level pediatric trauma centers had lower risk of subsequent injury-related admission. This unexplained variability suggests stronger collaboration is needed between community hospitals and regional pediatric trauma centers at the time of initial presentation to recognize and protect vulnerable children.

Exploring the paradigm of robotic surgery and its contribution to the growth of surgical volume.

Background: Robotic surgery is an appealing option for both surgeons and patients. The question around the introduction of new surgical technology, such as robotics, with the potential link to increased procedure-specific volume has not been addressed. We hypothesize that hospital adoption of robotic technology increases the total volume of specific procedures as compared to nonrobotic hospitals. Methods: The 2010-2020 Florida Agency for Health Care Administration Inpatient database was queried for open, laparoscopic, and robotic colectomy, lobectomy, gastric bypass, and antireflux procedures. International Classification of Diseases, 9th and 10th Revisions, codes were used. Difference in difference method was used to evaluate the impact of robotics on total procedure-specific volume of robotic hospitals versus nonrobotic hospitals before and after adopting robotic technology. Incident rate ratios from the difference in difference analysis determined the significance of adding robotics. Patient demographics were evaluated using χ2 test. Results: A total of 291,826 procedures were performed at 217 hospitals, 151 with robotic capabilities. Robotic hospitals experienced a 37% increase in surgical volume due to robotic technology (incident rate ratio 1.37, P < .05), which was consistent for each surgery except antireflux procedures (incident rate ratio 0.95). Robotic procedures had significantly higher charges for medical/surgical supplies; however, the mean length of stay for robotic procedures was significantly shorter than that of laparoscopic and open cases. Conclusion: Hospital adoption of robotic technology significantly increases surgical volume for select procedures. Hospitals should consider the benefits of introducing robotic technology which leads to higher volume and decreased length of stay, benefitting both hospital systems and patients.

The International Classification of Disease Critical Care Severity Score demonstrates that pediatric burden of injury is similar to that of adults: Validation using the National Trauma Databank☆.

BACKGROUND/PURPOSE: Resource-based severity of injury (SOI) measures, such as the International Classification of Disease (ICD) Critical Care Severity Score (ICASS), may characterize traumatic burden better than standard mortality-based measures. The purpose of this study was to validate the ICASS in a representative national-level trauma cohort and compare SOI measures between children and adults. METHODS: The National Trauma Databank was used to derive (2008-12) and validate (2013-15) ICASS and ICD Injury Severity Scores (ICISS, standard mortality-based SOI measure). SOI metrics and outcomes were compared between pediatric, adult, and elderly age groups. Logistic regression modeling evaluated predictors of critical care resource utilization. RESULTS: Derivation and validation cohorts consisted of 3.90 and 1.97 million patients, respectively. ICASS strongly predicted actual critical care utilization (OR 1.04, 95% CI 1.04-1.04, p<0.0001). Mean ICASS was 24.4 for children and 33.0 for adults (ratio 0.74), indicating predicted critical care utilization in children was three-quarters that of adults. In contrast, predicted pediatric mortality was less than half that of adults. CONCLUSIONS: Mortality-based SOI measures underestimate pediatric burden of injury. This study validates ICASS and demonstrates that pediatric resource-based SOI is more similar to that of adults. ICASS is easily calculated without a trauma registry and complements mortality-based measures. Level of evidence III, retrospective comparative study.

Does adoption of new technology increase surgical volume? The robotic inguinal hernia repair model.

Robotic Inguinal Hernia repair has been associated with higher costs but shorter length of stay. Robotic surgery is an appealing option for patients undergoing elective hernia surgery however given the high startup, maintenance and operating costs, the adoption of robotic technology may not guarantee increased profitability. Our hypothesis is that the introduction of robotic technology increases the overall surgical volume of inguinal hernia repairs within a hospital as compared to non-robotic hospitals. The 2010-2018 Florida Agency for Health Care Administration Ambulatory Patient data were queried for Open, Laparoscopic and Robotic inguinal hernia repairs using ICD9, ICD10 and CPT codes. Using a difference in difference (DID) technique, we determined the difference of the total hernia volume of robotic hospitals pre- and post-adoption of robotic technology. In addition, selected hospitals which were early adopters of robotic technology were compared to with their surrounding non-robotic competitor hospitals. Incident Rate Ratios-IRR, from the difference in difference analysis determined the significance of robotic technology. Hospital and patient demographic data were evaluated, and chi square test were used to determine statistical significance. p < 0.05 was considered significant. There were a total of 258,785 inguinal hernia repairs (5774 Robotic, 88,265 Laparoscopic and 164,746 Open) performed at 398 hospitals, 94 of which had robotic capabilities. Of all the procedure types, around 90% were primary inguinal hernia repairs. The majority of patients in this cohort were white non-Hispanic or Latino males (85%, 84%, 92%), age group 51-70 (46%), holding commercial health insurance (43%) and belonged to the lowest Charlson comorbidity index level (82%). Facility types designation for almost all robotic hospitals was hospital (99%), whereas 65% of non-robotic hospitals were ambulatory surgery centers and all other hospitals. Robotic hospitals experienced a 9.5% increase in total volume of inguinal hernia repairs after introduction of robotic technology (Incident Rate Ratios-IRR 1.095, p value < 0.0001). A significant increase in total hernia volume was observed for the early adopter hospitals with the IRR(s) ranging 1.20-2.51 (all p values < 0.0001), implying that adoption of robotic technology can in fact lead to very significant increase in total hernia volume for a hospital. The introduction of robotic technology leads to an increase in the overall volume of inguinal hernia repairs performed at a given hospital. To further evaluate the impact of robotic technology and significance of this methodology, additional work is underway using additional procedures and data from other states.

Elements of the care environment influence coronary artery bypass surgery readmission.

BACKGROUND: Coronary artery bypass grafting 30-day unplanned readmission is a focus for the CMS Hospital Readmissions Reduction Program. Awareness of the critical elements of the care delivery environment, including hospital infrastructure and patient clinical profiles that predispose toward readmission, is essential to proactively decrease readmissions. METHODS: The Healthcare Cost and Utilization Project-State Inpatient Database, American Hospital Association Annual Health Survey Database, and Healthcare Information Management Systems Society data sets were merged to create a single data set of patient- and hospital-level data from 8 states. Isolated coronary artery bypass grafting procedures were queried for all-cause 30-day readmission, and backwards stepwise logistic regression was performed. Readmission rate was then used to categorize hospitals into quartiles, and analysis focused on the hospitals with the lowest (Q1) and highest (Q4) readmission rates. Univariate analysis was performed comparing Q1 and Q4 hospitals. RESULTS: A total of 150,215 patients underwent isolated coronary artery bypass grafting with 23,244 (15.5%) readmitted patients among 903 hospitals. Model area under the curve was 0.709 (95% confidence interval, 0.702-0.716), with the top 3 readmission determinants related to discharge disposition. Compared to Q1, Q4 patients more often were female, were > 70 years of age, and had Medicare as a primary payor (P < .001). Low readmission rate hospitals were characterized by higher costs; not-for-profit status; having Joint Commission accreditation; and higher total admissions, operative volume, hospital/ICU beds, full-time physicians, nurses, and ancillary personnel (P < .001). CONCLUSION: Readmission after coronary artery bypass grafting is strongly influenced by discharge disposition. However, hospital factors such as scale, personnel, and ownership structure are significant contributors to readmission. Focus beyond patient factors to include the entire continuum of care is required to enhance outcomes, of which readmission is one surrogate measure.

Defining the relative contribution of health care environmental components to patient outcomes in the model of 30-day readmission after coronary artery bypass graft (CABG).

BACKGROUND: Patient outcomes following health care interventions may be dependent on a variety of factors: patient, surgeon, hospital, information technology, and temporal, cultural, and socioeconomic factors, among others. In this study, we characterize the relative contribution of each of these factors using a model of 30-day readmission following coronary artery bypass graft. METHODS: The Healthcare Cost and Utilization Project, the American Hospital Association Annual Health Survey Databases, the Healthcare Information and Management Systems Society, and the Distressed Communities Index from 2010 to 2013 were linked for Florida, Iowa, Massachusetts, Maryland, New York, and Washington. Logistic regression, random forest, decision tree, gradient boosting, k-nearest-neighbors classification, and XGBoost tree models were implemented. Modeling results were compared on the basis of predictive accuracy, sensitivity, specificity, and area under the curve. Decision tree performed best and was selected for further analysis. A gradient-boosted model was used to quantify factor contribution. RESULTS: The model had 45,352 patients, 54,096 admissions, and a 16.2% 30-day readmission rate after coronary artery bypass graft. The top 10 predictors were disposition at discharge, number of chronic conditions, total procedures, median household income, adults without high school diplomas, primary payer method, Agency for Healthcare Research and Quality comorbidity: renal failure, patient location (urban-rural), admission type, and age categories. The top 3 socioeconomic predictors were estimated state median household income, adults without high school diplomas, and patient location (urban versus rural designation). The relative contribution of patient/temporal, socioeconomic, hospital information technology, and hospital factors to readmission is 83.45%, 5.71%, 6.34%, and 4.31%, respectively. CONCLUSION: In this model, the contribution of socioeconomic factors is substantive but lags significantly behind patient/temporal factors. With ever increasing availability of data, identification of contributors to patient outcomes within the overall health care macroenvironment will allow prioritization of interventions.

The future surgical training paradigm: Virtual reality and machine learning in surgical education.

Surgical training has undergone substantial change in the last few decades. As technology and patient complexity continues to increase, demands for novel approaches to ensure competency have arisen. Virtual reality systems augmented with machine learning represents one such approach. The ability to offer on-demand training, integrate checklists, and provide personalized, surgeon-specific feedback is paving the way to a new era of surgical training. Machine learning algorithms that improve over time as they acquire more data will continue to refine the education they provide. Further, fully immersive simulated environments coupled with machine learning analytics provide real-world training opportunities in a safe atmosphere away from the potential to harm patients. Careful implementation of these technologies has the potential to increase access and improve quality of surgical training and patient care and are poised to change the landscape of current surgical training. Herein, we describe the current state of virtual reality coupled with machine learning for surgical training, future directions, and existing limitations of this technology.

Discharge timing: Does targeting an ideal length of stay for patients undergoing colectomy impact readmissions and costs of care?

INTRODUCTION: In colorectal surgery, enhanced recovery protocols reduce length-of-stay (LOS). Concerns remain about increased readmission rates. Using a predictive model targeting ideal LOS (iLOS), we evaluate the impact of discharge timing on readmission. METHODS: The HCUP-SID and AHA databases combined patient and hospital-level data from four states. Colectomy patients were stratified and propensity-matched based. We predicted iLOS using multivariate linear regression, created a discharge timing variable and used multivariate logistic regression to analyze 30-day and 90-day readmissions. RESULTS: Of 100,701 patients, 6903 (6.85%) were Lap-Left, 16,883 (16.77%) were Open-Left, 32,173 (31.95%) were Lap-Right, and 44,742 (44.43%) were Open-Right. Very early discharge (>4d before iLOS) and very late discharge (>4d after iLOS) were predictors of readmission in Lap- Left (p < 0.05) and Open-Right (p < 0.05). In Lap-Right, early discharge was a significant predictor of readmission (p < 0.01). CONCLUSION: Targeting using iLOS may optimize discharge timing after colectomy and avoid unplanned readmissions.

TEMPORARY REMOVAL: Battle of the sexes: The effect of surgeon gender on postoperative in-hospital mortality.

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Robotic Approach to Outpatient Inguinal Hernia Repair.

BACKGROUND: Robotics offers improved ergonomics, visualization, instrument articulation, and tremor filtration. Disadvantages include startup cost and system breakdown. Surgeon education notwithstanding, we hypothesize that robotic inguinal hernia repair carries minimal advantages over the laparoscopic or open approach. METHODS: The 2009-2015 Healthcare Cost and Utilization Project-State Ambulatory Surgery and Services and American Hospital Association Annual Health data sets from Florida were queried for open, laparoscopic, and robotic inguinal hernia repairs. Hospital and patient demographic, financial, and comorbidity data (26 total variables) were evaluated. Data are presented as mean ± SEM; p < 0.05 was considered significant. RESULTS: We identified 103,183 cases (63,375 open, 38,886 laparoscopic, and 922 robotic). Patient characteristics were the following: male, white, aged 51 to 70 years, nongovernmental and not-for-profit hospitals, grouped Charlson Comorbidity Category = 0, private insurance coverage, median income quartile 3 (4 = highest), and routine discharge disposition (all, p < 0.05). Total charges were: $18,261 ± $38 (open), $25,223 ± $60 (laparoscopic), and $45,830 ± $1,023 (robot) (p < 0.0001 robot vs open, robot vs laparoscopic, and laparoscopic vs open). Top factors associated with open procedures (area under the curve 0.785): hospital is investor owned for profit, self-pay, black, Latino, and Medicaid; with laparoscopic procedures (area under the curve 0.771): private insurance, median income quartile 4 (highest), median income quartile 3, median income quartile 2, and nongovernmental, not-for-profit hospitals; and with robotic procedures (area under the curve 0.936): Charlson Comorbidity Category = 2, Charlson Comorbidity Category = 1, median income quartile 3, median income quartile 2, and age. CONCLUSIONS: Robotic surgery has increased charges and is performed in sicker, higher-income patients. The open approach is more apt to be performed in black/Hispanic, self-pay patients, and for-profit hospitals. The role for robotic inguinal hernia repair is undefined.

The paradox of the robotic approach to inguinal hernia repair in the inpatient setting.

BACKGROUND: Robotics offers improved ergonomics, enhanced visualization, and increased dexterity. Disadvantages include startup, maintenance and instrument costs. Surgeon education notwithstanding, we hypothesized that robotic inguinal hernia repair carries minimal advantages over the open or laparoscopic approach in the inpatient setting. METHODS: The HCUP-SID and AHA datasets were queried for inguinal hernia repair codes. Hospital and patient demographic, financial and comorbidity data were evaluated. Data are presented as mean ±â€¯SEM. RESULTS: 36396 cases (27776 Open, 7104 Laparoscopic and 1516 Robotic) were identified. Total costs were: $13595 ±â€¯104 (Open), $13581 ±â€¯176 (Laparoscopic) and $18494 ±â€¯323 (Robotic). (p < 0.0001 Robotic vs Open, Robotic vs Laparoscopic) Robotic costs were 38% greater than that of the Open and Laparoscopic subsets (p < 0.001 Robotic vs. Open and Laparoscopic). The Open, Laparoscopic and Robotic subsets' length of stay were 4.2, 3.2 and 2.3 days, respectively. (p < 0.0001 among Open, Laparoscopic and Robotic). CONCLUSION: The Robotic approach to the inguinal hernia repair had the lowest length of stay, despite having the highest costs. The benefits of robotic surgery in inguinal hernia repair are unclear in the inpatient setting.