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Background The cost of surgical care is largely measured by charges or payments, both of which are inadequate. Actual cost data from the hospital's perspective are required to accurately quantify the financial return on investment of engaging in quality improvement. The objective of this study was to define the cost of individual, 30-day postoperative complications using robust cost data from a diverse group of hospitals. Methods Using clinical data derived from the American College of Surgeons National Surgical Quality Improvement Program, this retrospective study assessed postoperative complications for patients who underwent surgery at one of four hospitals in 2016. Actual direct and indirect 30-day costs were obtained, and the adjusted cost per complication was determined. Results From the 6,387 patients identified, the three complications associated with the highest independent adjusted cost per event were prolonged ventilation ($48,168; 95% confidence interval [CI]: $21,861–$74,476), unplanned intubation ($26,718; 95% CI: $15,374–$38,062), and renal failure ($18,528; CI: $17,076–$19,981). The three complications associated with the lowest independent adjusted cost per event were urinary tract infection (-$372; 95% CI: -$1,336–$592), superficial surgical site infection ($2,473; 95% CI: -$256–$5,201) and venous thromboembolism ($7,909; 95% CI: -$17,903–$33,721). After colectomy, the adjusted independent cost of anastomotic leak was $10,195 (95% CI: $5,941–$14,449), while the cost of postoperative ileus was $10,205 (95% CI: $6,259–$14,149). Conclusion The actual hospital costs of complications were estimated using cost data from four diverse hospitals. These data can be used by hospitals to estimate the financial benefit of reducing surgical complications.

To determine the positive predictive value of International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) discharge codes for acute deep vein thrombosis or pulmonary embolism.Retrospective review of 3456 cases hospitalized between 2005 and 2007 that had a discharge code for venous thromboembolism, using 3 sample populations: a single academic hospital, 33 University HealthSystem Consortium hospitals, and 35 community hospitals in a national Joint Commission study. Analysis was stratified by position of the code in the principal versus a secondary position.Among 1096 cases that had a thromboembolism code in the principal position the positive predictive value for any acute venous thrombosis was 95% (95%CI:93-97), whereas among 2360 cases that had a thromboembolism code in a secondary position the predictive value was lower, 75% (95%CI:71-80). The corresponding positive predictive values for lower extremity deep-vein thrombosis or pulmonary embolism were 91% (95%CI:86-95) and 50% (95%CI:41-58), respectively. More highly defined codes had higher predictive value. Among codes in a secondary position that were false positive, 22% (95%CI:16-27) had chronic/prior venous thrombosis, 15% (95%CI:10-19) had an upper extremity thrombosis, 6% (95%CI:4-8) had a superficial vein thrombosis, and 7% (95%CI:4-13) had no mention of any thrombosis.ICD-9-CM codes for venous thromboembolism had high predictive value when present in the principal position, and lower predictive value when in a secondary position. New thromboembolism codes that were added in 2009 that specify chronic thrombosis, upper extremity thrombosis and superficial venous thrombosis should reduce the frequency of false-positive thromboembolism codes.

Hospital administrative data are being used to identify patients with postoperative venous thromboembolism (VTE), either pulmonary embolism (PE) or deep-vein thrombosis (DVT). However, few studies have evaluated the accuracy of these ICD-9-CM codes across multiple hospitals.The Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicator (PSI)-12 was used to identify cases with postoperative VTE in 80 hospitals that volunteered for either an AHRQ or University HealthSystem Consortium (UHC) validation project. Trained abstractors using a standardized tool and guidelines retrospectively verified all coded VTE events.In the combined samples, the positive predictive value of the set of prespecified VTE codes for any acute VTE at any time during the hospitalization was 451 of 573 = 79% (95% CI: 75%-82%). However, the positive predictive value for acute lower extremity DVT or PE diagnosed after an operation was 209 of 452 = 44% (95% CI: 37%-51%) in the UHC sample and 58 of 121 = 48% (95% CI: 42-67%) in the AHRQ sample. Fourteen percent of all cases had an acute upper extremity DVT, 6% had superficial vein thrombosis and 21% had no acute VTE, however, 61% of the latter had a documented prior/chronic VTE. In the UHC cohort, the sensitivity for any acute VTE was 95.5% (95% CI: 86.4%-100%); the specificity was 99.5% (95% CI: 99.4%-99.7%).Current PSI 12 criteria do not accurately identify patients with acute postoperative lower extremity DVT or PE. Modification of the ICD-9-CM codes and implementation of "present on admission" flags should improve the predictive value for clinically important VTE events.

Background Research supports medical record review using screening triggers as the optimal method to detect hospital adverse events (AE), yet the method is labour-intensive. Method This study compared a traditional trigger tool with an enterprise data warehouse (EDW) based screening method to detect AEs. We created 51 automated queries based on 33 traditional triggers from prior research, and then applied them to 250 randomly selected medical patients hospitalised between 1 September 2009 and 31 August 2010. Two physicians each abstracted records from half the patients using a traditional trigger tool and then performed targeted abstractions for patients with positive EDW queries in the complementary half of the sample. A third physician confirmed presence of AEs and assessed preventability and severity. Results Traditional trigger tool and EDW based screening identified 54 (22%) and 53 (21%) patients with one or more AE. Overall, 140 (56%) patients had one or more positive EDW screens (total 366 positive screens). Of the 137 AEs detected by at least one method, 86 (63%) were detected by a traditional trigger tool, 97 (71%) by EDW based screening and 46 (34%) by both methods. Of the 11 total preventable AEs, 6 (55%) were detected by traditional trigger tool, 7 (64%) by EDW based screening and 2 (18%) by both methods. Of the 43 total serious AEs, 28 (65%) were detected by traditional trigger tool, 29 (67%) by EDW based screening and 14 (33%) by both. Conclusions We found relatively poor agreement between traditional trigger tool and EDW based screening with only approximately a third of all AEs detected by both methods. A combination of complementary methods is the optimal approach to detecting AEs among hospitalised patients.

Background Patient Safety Indicator (PSI) 11, or postoperative respiratory failure, was developed by the US Agency for Healthcare Research and Quality to detect incident cases of respiratory failure after elective operations through use of ICD-9-CM diagnosis and procedure codes. We sought to determine the positive predictive value (PPV) of this indicator. Study Design We conducted a retrospective cross-sectional study, sampling consecutive cases that met PSI 11 criteria from 18 geographically diverse academic medical centers on or before June 30, 2007. Trained abstractors from each center reviewed medical records using a standard instrument. We assessed the PPV of the indicator (with 95% CI adjusted for clustering within centers) and conducted descriptive analyses of the cases. Results Of 609 cases that met PSI 11 criteria, 551 (90.5%; 95% CI, 86.5–94.4%) satisfied the technical criteria of the indicator and 507 (83.2%; 95% CI, 77.2–89.3%) represented true cases of postoperative respiratory failure from a clinical standpoint. The most frequent reasons for being falsely positive were nonelective hospitalization, prolonged intubation for airway protection, and insufficient evidence to support a diagnosis of acute respiratory failure. Fifty percent of true-positive cases involved substantial baseline comorbidities, and 23% resulted in death. Conclusions Although PSI 11 predicts true postoperative respiratory failure with relatively high frequency, the indicator does not limit detection to preventable cases. The PPV of PSI 11 might be increased by excluding cases with a principal diagnosis suggestive of a nonelective hospitalization and those with head or neck procedures. Removing the diagnosis code criterion from the indicator might also increase PPV, but would decrease the number of true positive cases detected by 20%.