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.

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.