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1.
JAMA Netw Open ; 2(4): e191313, 2019 04 05.
Article in English | MEDLINE | ID: mdl-31002316

ABSTRACT

Importance: The existing readmission quality metric does not meaningfully distinguish readmissions associated with surgical quality from those that are not associated with surgical quality and thus may not reflect the quality of surgical care. Objective: To compare a quality metric that classifies readmissions associated with surgical quality with the existing metric of any unplanned readmission in a surgical population. Design, Setting, and Participants: Cohort study using US nationwide administrative data collected on 4 high-volume surgical procedures performed at 103 Veterans Affairs hospitals from October 1, 2007, through September 30, 2014. Data analysis was conducted from October 1, 2017, to January 24, 2019. Main Outcomes and Measures: Hospital-level rates of unplanned readmission (existing metric) and surgical readmissions associated with surgical quality (new metric) in the 30 days following hospital discharge for an inpatient surgical procedure. Results: The study population included 109 258 patients who underwent surgery at 103 hospitals. Patients were majority male (94.1%) and white (78.2%) with a mean (SD) age of 64.0 (10.0) years at the time of surgery. After case-mix adjustment, 30-day surgical readmissions ranged from 4.6% (95% CI, 4.5%-4.8%) among knee arthroplasties to 11.1% (95% CI, 10.9%-11.3%) among colorectal resections. The new surgical readmission metric was significantly correlated with facility-level postdischarge complications for all procedures, with ρ coefficients ranging from 0.33 (95% CI, 0.13-0.51) for cholecystectomy to 0.52 (95% CI, 0.38-0.68) for colorectal resection. Correlations between postdischarge complications and the new surgical readmission metric were higher than correlations between complications and the existing readmission metric for all procedures examined (knee arthroplasty: 0.50 vs 0.48; hip replacement: 0.44 vs 0.18; colorectal resection: 0.52 vs 0.42; and cholecystectomy: 0.33 vs 0.10). When compared with using the existing readmission metric, using the new surgical readmission metric could change hip replacement-associated payment penalty determinations in 28.4% of hospitals and knee arthroplasty-associated penalties in 26.0% of hospitals. Conclusions and Relevance: In this study, surgical quality-associated readmissions were more correlated with postdischarge complications at a higher rate than were unplanned readmissions. Thus, a metric based on such readmissions may be a better measure of surgical care quality. This work provides an important step in the development of future value-based payments and promotes evidence-based quality metrics targeting the quality of surgical care.


Subject(s)
Hospitals/statistics & numerical data , Patient Readmission/statistics & numerical data , Quality of Health Care/statistics & numerical data , Surgical Procedures, Operative/statistics & numerical data , Aged , Arthroplasty, Replacement, Hip/adverse effects , Arthroplasty, Replacement, Hip/statistics & numerical data , Arthroplasty, Replacement, Knee/adverse effects , Arthroplasty, Replacement, Knee/statistics & numerical data , Benchmarking , Cohort Studies , Colorectal Surgery/adverse effects , Colorectal Surgery/statistics & numerical data , Female , Humans , Male , Middle Aged , Patient Discharge/statistics & numerical data , Postoperative Complications/epidemiology , Postoperative Complications/ethnology , Prospective Studies , United States/epidemiology , United States Department of Veterans Affairs
2.
Med Care ; 56(6): 460-469, 2018 06.
Article in English | MEDLINE | ID: mdl-29746348

ABSTRACT

INTRODUCTION: Homeless Veterans are vulnerable to poor care transitions, yet little research has examined their risk of readmission following inpatient surgery. This study investigates the predictors of surgical readmission among homeless relative to housed Veteran patients. METHODS: Inpatient general, vascular, and orthopedic surgeries occurring in the Veterans Health Administration from 2008 to 2014 were identified. Administrative International Classification of Diseases, Ninth Revision, Clinical Modification codes and Veterans Health Administration clinic stops were used to identify homeless patients. Bivariate analyses examined characteristics and predictors of readmission among homeless patients. Multivariate logistic models were used to estimate the association between homeless experience and housed patients with readmission following surgery. RESULTS: Our study included 232,373 surgeries: 43% orthopedic, 39% general, and 18% vascular with 5068 performed on homeless patients. Homeless individuals were younger (56 vs. 64 y, P<0.01), more likely to have a psychiatric comorbidities (51.3% vs. 19.4%, P<0.01) and less likely to have other medical comorbidities such as hypertension (57.1% vs. 70.8%, P<0.01). Homeless individuals were more likely to be readmitted [odds ratio (OR), 1.43; confidence interval (CI), 1.30-1.56; P<0.001]. Discharge destination other than community (OR, 0.57; CI, 0.44-0.74; P<0.001), recent alcohol abuse (OR, 1.45; CI, 1.15-1.84; P<0.01), and elevated American Society Anesthesiologists classification (OR, 1.86; CI, 1.30-2.68; P<0.01) were significant risk factors associated with readmissions within the homeless cohort. CONCLUSIONS: Readmissions are higher in homeless individuals discharged to the community after surgery. Judicious use of postoperative nursing or residential rehabilitation programs may be effective in reducing readmission and improving care transitions among these vulnerable Veterans. Relative costs and benefits of alternatives to community discharge merit investigation.


Subject(s)
Ill-Housed Persons/statistics & numerical data , Patient Discharge/statistics & numerical data , Patient Readmission/statistics & numerical data , Surgical Procedures, Operative/statistics & numerical data , Veterans/statistics & numerical data , Adult , Female , Humans , Male , Middle Aged , Postoperative Complications/epidemiology , Poverty , Residence Characteristics , Risk Factors , United States/epidemiology
3.
JAMA Surg ; 153(8): 728-737, 2018 08 01.
Article in English | MEDLINE | ID: mdl-29710234

ABSTRACT

Importance: Postoperative readmission data are used to measure hospital performance, yet the extent to which these readmissions reflect surgical quality is unknown. Objective: To establish expert consensus on whether reasons for postoperative readmission are associated with the quality of surgery in the index admission. Design, Setting, and Participants: In a modified Delphi process, a panel of 14 experts in medical and surgical readmissions comprising physicians and nonphysicians from Veterans Affairs (VA) and private-sector institutions reviewed 30-day postoperative readmissions from fiscal years 2008 through 2014 associated with inpatient surgical procedures performed at a VA medical center between October 1, 2007, and September 30, 2014. The consensus process was conducted from January through May 2017. Reasons for readmission were grouped into categories based on International Classification of Diseases, Ninth Revision (ICD-9) diagnosis codes. Panelists were given the proportion of readmissions coded by each reason and median (interquartile range) days to readmission. They answered the question, "Does the readmission reason reflect possible surgical quality of care problems in the index admission?" on a scale of 1 (never related) to 5 (directly related) in 3 rounds of consensus building. The consensus process was completed in May 2017 and data were analyzed in June 2017. Main Outcomes and Measures: Consensus on proportion of ICD-9-coded readmission reasons that reflected quality of surgical procedure. Results: In 3 Delphi rounds, the 14 panelists achieved consensus on 50 reasons for readmission; 12 panelists also completed group telephone calls between rounds 1 and 2. Readmissions with diagnoses of infection, sepsis, pneumonia, hemorrhage/hematoma, anemia, ostomy complications, acute renal failure, fluid/electrolyte disorders, or venous thromboembolism were considered associated with surgical quality and accounted for 25 521 of 39 664 readmissions (64% of readmissions; 7.5% of 340 858 index surgical procedures). The proportion of readmissions considered to be not associated with surgical quality varied by procedure, ranging from to 21% (613 of 2331) of readmissions after lower-extremity amputations to 47% (745 of 1598) of readmissions after cholecystectomy. Conclusions and Relevance: One-third of postoperative readmissions are unlikely to reflect problems with surgical quality. Future studies should test whether restricting readmissions to those with specific ICD-9 codes might yield a more useful quality measure.


Subject(s)
Consensus , Patient Readmission/statistics & numerical data , Postoperative Complications/diagnosis , Quality Indicators, Health Care , Surgical Procedures, Operative/standards , Aged , Female , Follow-Up Studies , Humans , Incidence , Male , Middle Aged , Postoperative Complications/epidemiology , Retrospective Studies , Risk Factors , Surgical Procedures, Operative/adverse effects , Time Factors , United States/epidemiology
4.
Ann Surg ; 264(4): 621-31, 2016 10.
Article in English | MEDLINE | ID: mdl-27355263

ABSTRACT

OBJECTIVE: The aim of this study is to understand the relative contribution of preoperative patient factors, operative characteristics, and postoperative hospital course on 30-day postoperative readmissions. BACKGROUND: Determining the risk of readmission after surgery is difficult. Understanding the most important contributing factors is important to improving prediction of and reducing postoperative readmission risk. METHODS: National Veterans Affairs Surgical Quality Improvement Program data on inpatient general, vascular, and orthopedic surgery from 2008 to 2014 were merged with laboratory, vital signs, prior healthcare utilization, and postoperative complications data. Variables were categorized as preoperative, operative, postoperative/predischarge, and postdischarge. Logistic models predicting 30-day readmission were compared using adjusted R and c-statistics with cross-validation to estimate predictive discrimination. RESULTS: Our study sample included 237,441 surgeries: 43% orthopedic, 39% general, and 18% vascular. Overall 30-day unplanned readmission rate was 11.1%, differing by surgical specialty (vascular 15.4%, general 12.9%, and orthopedic 7.6%, P < 0.001). Most common readmission reasons were wound complications (30.7%), gastrointestinal (16.1%), bleeding (4.9%), and fluid/electrolyte (7.5%) complications. Models using information available at the time of discharge explained 10.4% of the variability in readmissions. Of these, preoperative patient-level factors contributed the most to predictive models (R 7.0% [c-statistic 0.67]); prediction was improved by inclusion of intraoperative (R 9.0%, c-statistic 0.69) and postoperative variables (R 10.4%, c-statistic 0.71). Including postdischarge complications improved predictive ability, explaining 19.6% of the variation (R 19.6%, c-statistic 0.76). CONCLUSIONS: Postoperative readmissions are difficult to predict at the time of discharge, and of information available at that time, preoperative factors are the most important.


Subject(s)
Patient Readmission , Postoperative Complications/epidemiology , Aged , Female , Humans , Logistic Models , Male , Middle Aged , Operative Time , Patient Discharge , Quality Improvement , Retrospective Studies , Risk Factors , Time Factors
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