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Background Atrial fibrillation (AFib) is associated with high morbidity and mortality. Traditionally, AFib was treated with warfarin, yet recent evidence suggests patients may favor direct oral anticoagulants (DOACs). Variation in preferences is common and we explored patients' perceptions of satisfaction and convenience of DOACs versus warfarin within the Veterans Health Administration (VA). Patients and methods We administered a cross-sectional survey, the Perception of Anticoagulant Treatment Questionnaire 2 (PACT-Q2), to Veterans residing in New England, age ≥65, diagnosed with AFib, and actively taking anticoagulant medication in fiscal year 2018. Survey recipients were randomly selected among patients on warfarin (n=200) or DOACs (n=200). A selection of survey respondents agreed to a follow-up semi-structured interview (n=16) to further investigate perceptions of satisfaction and convenience. Results Of 400 patients, 187 completed the PACT-Q2 survey (49% on DOACs; 51% on warfarin). DOACs received significantly higher convenience ratings than warfarin (87.6, SD 13.5 vs 81.1, SD 18.8; p=0.007); there was no difference in satisfaction (64.2, SD 20.5 SD, warfarin vs, 67.3, SD 19.4, DOACs). Interview results showed that participants perceived their treatment to be convenient. However, participants expressed challenges related to the convenience of taking warfarin or DOACs, such as warfarin users having to follow dietary recommendations or DOAC users desiring some additional monitoring to answer questions or concerns. Overall, warfarin and DOAC users reported satisfaction with ongoing monitoring methods, although a few DOAC users expressed uncertainties with the frequency of monitoring. For most participants, concerns about side effects did not differ by anticoagulant type nor affect satisfaction. Conclusion Our survey and interview results showed variable patient satisfaction and perceptions of convenience with both DOACs and warfarin. Although DOACs are increasingly prescribed for AFib, some Veterans felt that regular follow-up on warfarin was advantageous. Our findings demonstrate the importance of patient-centered decision-making in AFib treatment in the VA patient population.

Background The extent of preoperative opioid utilization and the relationship with pain-related readmissions are not well understood. Methods VA Surgical Quality Improvement Program data on general, vascular, and orthopedic surgeries (2007–2014) were merged with pharmacy data to evaluate preoperative opioid use and pain-related readmissions. Opioid use in the 6-month preoperative period was categorized as none, infrequent, frequent, and daily. Results In the six-month preoperative period, 65.7% had no opioid use, 16.7% had infrequent use, 6.3% frequent use, and 11.4% were daily opioid users. Adjusted odds of pain-related readmission were higher for opioid-exposed groups vs the opioid-naive group: infrequent (OR 1.17; 95% CI:1.04–1.31), frequent (OR 1.28; 95% CI:1.08–1.52), and daily (OR 1.49; 95% CI:1.27–1.74). Among preoperative opioid users, those with a pain-related readmission had higher daily preoperative oral morphine equivalents (mean 44.5 vs. 36.1, p Conclusions Patients using opioids preoperatively experienced higher rates of pain-related readmissions, which increased with frequency and dosage of opioid exposure.

Objective:To measure the association between receipt of specific infection prevention interventions and procedure-related cardiac implantable electronic device (CIED) infections.Design:Retrospective cohort with manually reviewed infection status.Setting:Setting: National, multicenter Veterans Health Administration (VA) cohort.Participants:Sampling of procedures entered into the VA Clinical Assessment Reporting and Tracking-Electrophysiology (CART-EP) database from fiscal years 2008 through 2015.Methods:A sample of procedures entered into the CART-EP database underwent manual review for occurrence of CIED infection and other clinical/procedural variables. The primary outcome was 6-month incidence of CIED infection. Measures of association were calculated using multivariable generalized estimating equations logistic regression.Results:We identified 101 procedure-related CIED infections among 2,098 procedures (4.8% of reviewed sample). Factors associated with increased odds of infections included (1) wound complications (adjusted odds ratio [aOR], 8.74; 95% confidence interval [CI], 3.16–24.20), (2) revisions including generator changes (aOR, 2.4; 95% CI, 1.59–3.63), (3) an elevated international normalized ratio (INR) >1.5 (aOR, 1.56; 95% CI, 1.12–2.18), and (4) methicillin-resistant Staphylococcus colonization (aOR, 9.56; 95% CI, 1.55–27.77). Clinically effective prevention interventions included preprocedural skin cleaning with chlorhexidine versus other topical agents (aOR, 0.41; 95% CI, 0.22–0.76) and receipt of β-lactam antimicrobial prophylaxis versus vancomycin (aOR, 0.60; 95% CI, 0.37–0.96). The use of mesh pockets and continuation of antimicrobial prophylaxis after skin closure were not associated with reduced infection risk.Conclusions:These findings regarding the real-world clinical effectiveness of different prevention strategies can be applied to the development of evidence-based protocols and infection prevention guidelines specific to the electrophysiology laboratory.

Inpatients with culture-positive diabetic foot infections are at elevated risk for subsequent invasive infection with the same causative organism. In outpatients with index diabetic foot ulcers, we found that wound culture positivity was independently associated with increased odds of 1-year admission for systemic infection when compared with culture-negative wounds.

Procedure-related cardiac electronic implantable device (CIED) infections have high morbidity and mortality, highlighting the urgent need for infection prevention efforts to include electrophysiology procedures. We developed and validated a semi-automated algorithm based on structured electronic health records data to reliably identify CIED infections. A sample of CIED procedures entered into the Veterans’ Health Administration Clinical Assessment Reporting and Tracking program from FY 2008–2015 was reviewed for the presence of CIED infection. This sample was then randomly divided into training (2/3) validation sets (1/3). The training set was used to develop a detection algorithm containing structured variables mapped from the clinical pathways of CIED infection. Performance of this algorithm was evaluated using the validation set. 2,107 unique CIED procedures from a cohort of 5,753 underwent manual review; 97 CIED infections (4.6%) were identified. Variables strongly associated with true infections included presence of a microbiology order, billing codes for surgical site infections and post-procedural antibiotic prescriptions. The combined algorithm to detect infection demonstrated high c-statistic (0.95; 95% confidence interval: 0.92–0.98), sensitivity (87.9%) and specificity (90.3%) in the validation data. Structured variables derived from clinical pathways can guide development of a semi-automated detection tool to surveil for CIED infection.

Background Antimicrobial prophylaxis is an evidence-proven strategy for reducing procedure-related infections; however, measuring this key quality metric typically requires manual review, due to the way antimicrobial prophylaxis is documented in the electronic medical record (EMR). Our objective was to electronically measure compliance with antimicrobial prophylaxis using both structured and unstructured data from the Veterans Health Administration (VA) EMR. We developed this methodology for cardiac device implantation procedures. Methods With clinician input and review of clinical guidelines, we developed a list of antimicrobial names recommended for the prevention of cardiac device infection. We trained the algorithm using existing fiscal year (FY) 2008–15 data from the VA Clinical Assessment Reporting and Tracking-Electrophysiology (CART-EP), which contains manually determined information about antimicrobial prophylaxis. We merged CART-EP data with EMR data and programmed statistical software to flag an antimicrobial orders or drug fills from structured data fields in the EMR and hits on text string searches of antimicrobial names documented in clinician’s notes. We iteratively tested combinations of these data elements to optimize an algorithm to accurately classify antimicrobial use. The final algorithm was validated in a national cohort of VA cardiac device procedures from FY2016–2017. Discordant cases underwent expert manual review to identify reasons for algorithm misclassification. Results The CART-EP dataset included 2102 procedures at 38 VA facilities with manually identified antimicrobial prophylaxis in 2056 cases (97.8%). The final algorithm combining structured EMR fields and text note search results correctly classified 2048 of the CART-EP cases (97.4%). In the validation sample, the algorithm measured compliance with antimicrobial prophylaxis in 16,606 of 18,903 cardiac device procedures (87.8%). Misclassification was due to EMR documentation issues, such as antimicrobial prophylaxis documented only in hand-written clinician notes in a format that cannot be electronically searched. Conclusions We developed a methodology with high accuracy to measure guideline concordant use of antimicrobial prophylaxis before cardiac device procedures using data fields present in modern EMRs. This method can replace manual review in quality measurement in the VA and other healthcare systems with EMRs; further, this method could be adapted to measure compliance in other procedural areas where antimicrobial prophylaxis is recommended.

Objective Develop and validate a surveillance model to identify outpatient surgical adverse events (AEs) based on previously developed electronic triggers. Data sources Veterans Health Administration's Corporate Data Warehouse. Study design Six surgical AE triggers, including postoperative emergency room visits and hospitalizations, were applied to FY2012-2014 outpatient surgeries (n = 744,355). We randomly sampled trigger-flagged and unflagged cases for nurse chart review to document AEs and measured positive predictive value (PPV) for triggers. Next, we used chart review data to iteratively estimate multilevel logistic regression models to predict the probability of an AE, starting with the six triggers and adding in patient, procedure, and facility characteristics to improve model fit. We validated the final model by applying the coefficients to FY2015 outpatient surgery data (n = 256,690) and reviewing charts for cases at high and moderate probability of an AE. Principal findings Of 1,730 FY2012-2014 reviewed surgeries, 350 had an AE (20 percent). The final surveillance model c-statistic was 0.81. In FY2015 surgeries with >0.8 predicted probability of an AE (n = 405, 0.15 percent), PPV was 85 percent; in surgeries with a 0.4-0.5 predicted probability of an AE, PPV was 38 percent. Conclusions The surveillance model performed well, accurately identifying outpatient surgeries with a high probability of an AE.

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.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.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, P0.01), more likely to have a psychiatric comorbidities (51.3% vs. 19.4%, P0.01) and less likely to have other medical comorbidities such as hypertension (57.1% vs. 70.8%, P0.01). Homeless individuals were more likely to be readmitted [odds ratio (OR), 1.43; confidence interval (CI), 1.30-1.56; P0.001]. Discharge destination other than community (OR, 0.57; CI, 0.44-0.74; P0.001), recent alcohol abuse (OR, 1.45; CI, 1.15-1.84; P0.01), and elevated American Society Anesthesiologists classification (OR, 1.86; CI, 1.30-2.68; P0.01) were significant risk factors associated with readmissions within the homeless cohort.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.

Little is known about patient safety risks in outpatient surgery. Inpatient surgical adverse events (AEs) risk factors include patient- (e.g., advanced age), process- (e.g., inadequate preoperative assessment), or structure-related characteristics (e.g., low surgical volume); however, these factors may differ from outpatient care where surgeries are often elective and in younger/healthier patients. We undertook an exploratory qualitative research project to identify risk factors for AEs in outpatient surgery.We developed a conceptual framework of patient, process, and structure factors associated with surgical AEs on the basis of a literature review. This framework informed our semistructured interview guide with (1) open-ended questions about a specific outpatient AE that the participant experienced and (2) outpatient surgical patient safety risk factors in general. We interviewed nationwide Veterans Health Administration surgical staff. Results were coded on the basis of categories in the conceptual framework, and additional themes were identified using content analysis.Fourteen providers representing diverse surgical roles participated. Ten reported witnessing an AE, and everyone provided input on risk factors in our conceptual framework. We did not find evidence that patient race/age, surgical technique, or surgical volume affected patient safety. Emerging factors included patient compliance, postoperative patient assessments/instruction, operating room equipment needs, and safety culture.Surgical staff are familiar with AEs and patient safety problems in outpatient surgery. Our results show that processes of care undertaken by surgical providers, as opposed to immutable patient characteristics, may affect the occurrence of AEs. The factors we identified may facilitate more targeted research on outpatient surgical AEs.

Surgical quality improvement efforts have focused on tracking and reducing postoperative mortality and morbidity. However, the prevalence of intraoperative adverse events (IAEs) and their association with postoperative surgical outcomes has been poorly studied. In this study, we detected IAEs using both retrospective chart review and prospective provider reporting. We then examined the association of IAEs with postoperative outcomes. The overall IAE detection rate per case was 0.7 and 0.07 (P 0.0001) based on chart review and provider reporting, respectively. Types of IAEs varied between detection methods. Provider-reported IAEs were more serious, i.e., had a stronger association with 30-day postoperative complications than chart-identified IAEs (risk-adjusted odds ratios were 1.52 vs 1.02, respectively, both p 0.0001). Our findings suggest that IAEs can be detected using either retrospective chart review or prospective provider reporting. However, provider reporting appears more likely to detect serious (albeit infrequent) IAEs compared to chart review.

More than 50% of outpatient surgeries predicted to have an increased likelihood of an adverse event were excluded from surgical site infection (SSI) surveillance based on Veterans Affairs Surgical Quality Improvement Program (VASQIP) eligibility criteria, defined by clinician determination of invasiveness. Burden of SSI for eligible versus ineligible surgeries was similar; thus, surveillance activities in the outpatient setting need to be re-evaluated.

Background Guidelines recommend discontinuation of antimicrobial prophylaxis within 24 h after incision closure in uninfected patients. However, how facility and surgical specialty factors affect the implementation of these evidence-based surgical prophylaxis guidelines in outpatient surgery is unknown. Thus, we sought to measure how facility complexity, including ambulatory surgical center (ASC) status and availability of ancillary services, impact adherence to guidelines for timely discontinuation of antimicrobial prophylaxis after outpatient surgery. A secondary aim was to measure the association between surgical specialty and guideline compliance. Methods A multi-center, national Veterans Health Administration retrospective cohort from 10/1/2015–9/30/2017 including any Veteran undergoing an outpatient surgical procedure in any of five specialties (general surgery, urology, ophthalmology, ENT, orthopedics) was created. The primary outcome was the association between facility complexity and proportion of surgeries not compliant with discontinuation of antimicrobials within 24 h of incision closure. Data were analyzed using logistic regression with adjustments for patient and procedural factors. Results Among 153,097 outpatient surgeries, 7712 (5.0%) received antimicrobial prophylaxis lasting > 24 h after surgery; rates ranged from 0.4% (eye surgeries) to 13.7% (genitourinary surgeries). Cystoscopies and cystoureteroscopy with lithotripsy procedures had the highest rates (16 and 20%), while hernia repair, cataract surgeries, and laparoscopic cholecystectomies had the lowest (0.2–0.3%). In an adjusted logistic regression model, lower complexity ASC and hospital outpatient departments had higher odds of prolonged antimicrobial prophylaxis compared to complex hospitals (OR ASC, 1.3, 95% CI: 1.2–1.5). Patient factors associated with higher odds of noncompliance with antimicrobial discontinuation included younger age, female sex, and white race. Genitourinary and ear/nose/throat surgeries were associated with the highest odds of prolonged antimicrobial prophylaxis. Conclusions Facility complexity appears to play a role in adherence to surgical infection prevention guidelines. Lower complexity facilities with limited infection prevention and antimicrobial stewardship resources may be important targets for quality improvement. Such interventions may be especially useful for genitourinary and ear/nose/throat surgical subspecialties. Increasing pharmacy, antimicrobial stewardship and/or infection prevention resources to promote more evidence-based care may support surgical providers in lower complexity ambulatory surgery centers and hospital outpatient departments in their efforts to improve this facet of patient safety. Electronic supplementary material The online version of this article (10.1186/s13756-019-0503-9) contains supplementary material, which is available to authorized users.

IMPORTANCE: Proteinuria indicates renal dysfunction and is a risk factor for morbidity among medical patients, but less is understood among surgical populations. There is a paucity of studies investigating how preoperative proteinuria is associated with surgical outcomes, including postoperative acute kidney injury (AKI) and readmission. OBJECTIVE: To assess preoperative urine protein levels as a biomarker for adverse surgical outcomes. DESIGN, SETTING, AND PARTICIPANTS: A retrospective, population-based study was conducted in a cohort of patients with and without known preoperative renal dysfunction undergoing elective inpatient surgery performed at 119 Veterans Affairs facilities from October 1, 2007, to September 30, 2014. Data analysis was conducted from April 4 to December 1, 2016. Preoperative dialysis, septic, cardiac, ophthalmology, transplantation, and urologic cases were excluded. EXPOSURES: Preoperative proteinuria as assessed by urinalysis using the closest value within 6 months of surgery: negative (0 mg/dL), trace (15-29 mg/dL), 1+ (30-100 mg/dL), 2+ (101-300 mg/dL), 3+ (301-1000 mg/dL), and 4+ (>1000 mg/dL). MAIN OUTCOMES AND MEASURES: Primary outcome was postoperative predischarge AKI and 30-day postdischarge unplanned readmission. Secondary outcomes included any 30-day postoperative outcome. RESULTS: Of 346 676 surgeries, 153 767 met inclusion criteria, with the majority including orthopedic (37%), general (29%), and vascular procedures (14%). Evidence of proteinuria was shown in 43.8% of the population (trace: 20.6%, 1+: 16.0%, 2+: 5.5%, 3+: 1.6%) with 20.4%, 14.9%, 4.3%, and 0.9%, respectively, of the patients having a normal preoperative estimated glomerular filtration rate (eGFR). In unadjusted analysis, preoperative proteinuria was significantly associated with postoperative AKI (negative: 8.6%, trace: 12%, 1+: 14.5%, 2+: 21.2%, 3+: 27.6%; P

BACKGROUND Emergency department (ED) use following outpatient surgery may be associated with a surgery-related patient safety problem. We characterized ED use within 7 days of general, urology, orthopedic, ear/nose/throat, and podiatry surgical procedures and assessed factors associated with these visits by specialty. METHODS We calculated the 2011-2013 postoperative ED visit rate for Veterans older than 65 years dually enrolled in the Veterans Health Administration (VA) and Medicare, examined diagnoses, and used logistic regression to model patient, procedure, and facility factors associated with ED care. RESULTS Among 63 279 outpatient surgical procedures, 2778 (4.4%) resulted in an ED visit within 7 days; 23% of these were to non-VA facilities. Rates varied from more than 5% for urology and ear/nose/throat, to less than 3% for orthopedic and podiatry specialties. Genitourinary symptoms and surgical complications were common diagnoses across specialties. No patient, procedure, or facility factors were associated with ED use for every specialty. CONCLUSIONS A small proportion of VA outpatient surgical procedures result in ED use. Notably, nearly one-fourth of the postoperative ED visits may be missed by the VA because they occur in non-VA facilities. ED visits for urinary issues or surgical complications may be preventable; however, factors associated with ED use vary by specialty, suggesting different approaches may be needed to improve outcomes.

Background: The Centers for Medicare and Medicaid Services (CMS) use public reporting and payment penalties as incentives for hospitals to reduce readmission rates. In contrast to the current condition-specific readmission measures, CMS recently developed an all-condition, 30-day all-cause hospital-wide readmission measure (HWR) to provide a more comprehensive view of hospital performance. Objectives: We examined whether assessment of hospital performance and payment penalties depends on the readmission measure used. Research Design: We used inpatient data to examine readmissions for patients discharged from VA acute-care hospitals from Fiscal Years 2007–2010. We calculated risk-standardized 30-day readmission rates for 3 condition-specific measures (heart failure, acute myocardial infarction, and pneumonia) and the HWR measure, and examined agreement between the HWR measure and each of the condition-specific measures on hospital performance. We also assessed the effect of using different readmission measures on hospitals’ payment penalties. Results: We found poor agreement between the condition-specific measures and the HWR measure on those hospitals identified as low or high performers (eg, among those hospitals classified as poor performers by the heart failure readmission measure, only 28.6% were similarly classified by the HWR measure). We also found differences in whether a hospital would experience payment penalties. The HWR measure penalized only 60% of those hospitals that would have received penalties based on at least 1 of the condition-specific measures. Conclusions: The condition-specific measures and the HWR measure provide a different picture of hospital performance. Future research is needed to determine which measure aligns best with CMS’s overall goals to reduce hospital readmissions and improve quality.

Background Opioid-related adverse drug events are common following inpatient surgical procedures. Little is known about opioid prescribing after outpatient surgical procedures and if opioid use is associated with short term risks of outpatient surgical adverse events (AEs). Methods VA Corporate Data Warehouse was used to identify opioid use within 48 h for FY2012-14 chart-reviewed cases from a larger VA study of AEs in outpatient surgeries. We estimated a multilevel logistic regression model to determine the effect of opioid exposure on risk of AEs between 2 and 30 days postoperatively. Results Of the 1730 outpatient surgical cases, 628 (36%) had postoperative opioid use and 12% had an AE. Opioid use following outpatient surgery was not significantly associated with higher surgical AE rates after controlling for relevant covariates (OR = 1.1 95% CI 0.79–1.54). Only procedure RVUs were associated with higher odds of postoperative AEs. Conclusions Postoperative opioid use following outpatient surgery is not a significant driver of postoperative AEs.

BackgroundThe rate of cardiovascular implantable electronic device (CIED) infection is increasing coincident with an increase in the number of device procedures. Preprocedural antimicrobial prophylaxis reduces CIED infections; however, there is no evidence that prolonged postprocedural antimicrobials additionally reduce risk. Thus, we sought to quantify the harms associated with this approach.ObjectiveTo measure the association betweenClostridium difficileinfection (CDI), acute kidney injury (AKI) and receipt of prolonged postprocedural antimicrobials.MethodsCIED procedures entered into the VA Clinical Assessment Reporting and Tracking Electrophysiology (CART-EP) database during fiscal years 2008–2016 were included. The primary outcome was 90-day incidence of CDI and the secondary outcome was the 7-day incidence of AKI. The primary exposure measure was duration of postprocedural antimicrobial therapy. Associations were measured using Cox-proportional hazards and binomial regression.ResultsProlonged postprocedural antimicrobial therapy was identified following 3,331 of 6,497 CIED procedures (51.3%), and the median duration of prophylaxis was 5 days. Prolonged postprocedural antimicrobial use was associated with increased risk of CDI (hazard ratio [HR], 2.90; 95% confidence interval [CI], 1.54–5.46). Of the 27 patients who developed CDI, 11 subsequently died. Postprocedural antimicrobial use with ≥2 antimicrobials was associated with an increased risk of AKI (OR, 4.16; 95% CI, 2.50–6.90). The impact was particularly significant when one of the dual agents prescribed was vancomycin (adjusted OR, 8.41; 95% CI, 5.53–12.79).ConclusionsProlonged antimicrobial prophylaxis following CIED procedures increases preventable harm; this practice should be discouraged in procedural settings such as the cardiac electrophysiology laboratory.

This study evaluates the prevalence of postprocedure emergency department visits and admissions and the association of these outcomes with relevant patient, procedure, and facility factors.

Objective To examine factors associated with 0- to 7-day admission after outpatient surgery in high-volume specialties: general surgery, orthopedics, urology, ear/nose/throat, and podiatry. Study design We calculated rates and assessed diagnosis codes for 0- to 7-day admission after outpatient surgery for Centers for Medicare and Medicaid Services (CMS) and Veterans Health Administration (VA) dually enrolled patients age 65 and older. We also estimated separate multilevel logistic regression models to compare patient, procedure, and facility characteristics associated with postoperative admission. Data collection 2011-2013 surgical encounter data from the VA Corporate Data Warehouse; geographic data from the Area Health Resources File; CMS enrollment and hospital admission data. Principal findings Among 63,585 outpatient surgeries in 124 facilities, 0- to 7-day admission rates ranged from 5 percent (podiatry) to 28 percent (urology); nearly 66 percent of the admissions occurred on the day of surgery. Only 97 admissions were detected in the CMS data (1 percent). Surgical complications were diagnosed in 4 percent of admissions. Procedure complexity, measured by relative value units or anesthesia risk score, was associated with admission across all specialties. Conclusion As many as 20 percent of VA outpatient surgeries result in an admission. Complex procedures are more likely to be followed by admission, but more evidence is required to determine how many of these reflect potential safety or quality problems.

Background Hospital readmission rates after surgery can represent an overall hospital effect or a combination of specialty and patient effects. We hypothesized that hospital readmission rates for procedures within specialties were more strongly correlated than rates across specialties within the same hospital. Study Design For general, orthopaedic, and vascular specialties at Veterans Affairs hospitals during 2008 to 2014, 30-day risk-adjusted readmission rates were estimated for 6 high-volume procedures and each specialty. Relationships were assessed using the Pearson correlation coefficient. Results At 84 hospitals, 64,724 orthopaedic, 24,963 general, and 10,399 vascular inpatient procedures were performed; mean readmission rates were 6.3%, 13.6%, and 16.4%, respectively. There was no correlation between specialty-specific adjusted hospital readmission rates: general and orthopaedic ( r = 0.21; p = 0.06), general and vascular ( r = 0.15; p = 0.19), and vascular and orthopaedic surgery ( r = 0.07; p = 0.55). Within specialties, we found modest correlations between knee and hip arthroplasty readmission rates ( r = 0.39; p r = 0.24; p = 0.03), but not between lower-extremity bypass and endovascular aortic repair ( r = 0.13; p = 0.26). Overall, controlling for patient-level factors, 1.9% of the variation in readmissions was attributable to specialty-level factors; only 0.6% was attributable to hospital-level factors. Conclusions Hospital readmission rates for orthopaedic, vascular, and general surgery were not correlated between specialties; within each of the 3 specialties, modest correlations were found between 2 procedures within 2 of these specialties. These findings suggest that hospital surgical readmission rates are primarily explained by patient- and procedure-specific factors and less by broader specialty and/or hospital effects.

Background Adverse event (AE) rates in outpatient surgery are inconsistently reported, partly because of the lack of a standard definition of outpatient surgery. We compared the types and rates of surgical procedures defined by two national healthcare agencies: Health Care Cost Institute (HCCI) and the Healthcare Cost and Utilization Project (HCUP) and considered implications for quality measurement. Methods We used HCCI and HCUP definitions to identify FY2012-14 VA outpatient surgeries. Results There were six times as many HCCI surgeries as HCUP (6,575,830 versus 1,086,640). Ninety-nine percent of HCUP-defined surgeries were also identified by HCCI. More HCUP surgeries had higher average Medicare Relative Value Units then HCCI surgeries [5.3 (SD = 4.4) versus 1.6 (SD = 2.3) RVUs]. Conclusions Rates and types of procedures vary widely between definitions. Quality measurement using HCCI versus HCUP may produce significantly lower AE rates because many of the surgeries included reflect low complexity and potentially low risk of AEs.

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.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.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.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%, P0.001). 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).Postoperative readmissions are difficult to predict at the time of discharge, and of information available at that time, preoperative factors are the most important.

Background Hospital readmissions are associated with higher resource utilization and worse patient outcomes. Causes of unplanned readmission to the hospital are multiple with some being better targets for intervention than others. To understand risk factors for surgical readmission and their incremental contribution to current Veterans Health Administration (VA) surgical quality assessment, the study, Improving Surgical Quality: Readmission (ISQ-R), is being conducted to develop a readmission risk prediction tool, explore predisposing and enabling factors, and identify and rank reasons for readmission in terms of salience and mutability. Methods Harnessing the rich VA enterprise data, predictive readmission models are being developed in data from patients who underwent surgical procedures within the VA 2007–2012. Prospective assessment of psychosocial determinants of readmission including patient self-efficacy, cognitive, affective and caregiver status are being obtained from a cohort having colorectal, thoracic or vascular procedures at four VA hospitals in 2015–2017. Using these two data sources, ISQ-R will develop readmission categories and validate the readmission risk prediction model. A modified Delphi process will convene surgeons, non-surgeon clinicians and quality improvement nurses to rank proposed readmission categories vis-à-vis potential preventability. Discussion ISQ-R will identify promising avenues for interventions to facilitate improvements in surgical quality, informing specifications for surgical workflow managers seeking to improve care and reduce cost. ISQ-R will work with Veterans Affairs Surgical Quality Improvement Program (VASQIP) to recommend potential new elements VASQIP might collect to monitor surgical complications and readmissions which might be preventable and ultimately improve surgical care.

Background— The 3M Potentially Preventable Readmissions (3M-PPR) software matches clinically related index admission and readmission diagnoses that may signify in-hospital or postdischarge quality problems. To assess whether the PPR algorithm identifies preventable readmissions, we compared processes of care between PPR software-flagged and nonflagged cases. Methods and Results— Using 2006 to 2010 national VA administrative data, we identified acute myocardial infarction and heart failure discharges associated with 30-day all-cause readmissions, then flagged cases (PPR-Yes/PPR-No) using the 3M-PPR software. To assess care quality, we abstracted medical records of 100 readmissions per condition using tools containing explicit processes organized into admission work-up, in-hospital evaluation/treatment, discharge readiness, postdischarge period. We derived quality scores, scaled to a maximum of 25 per section (maximum total score=100) and compared cases on total and section-specific mean scores. For acute myocardial infarction, 77 of 100 cases were flagged as PPR-Yes. Section quality scores were highest for in-hospital evaluation/treatment (20.5±2.8) and lowest for postdischarge care (6.8±9.1). Total and section-related mean scores did not differ by PPR status; respective PPR-Yes versus PPR-No total scores were 61.6±11.1 and 60.4±9.4; P =0.98. For heart failure, 86 of 100 cases were flagged as PPR-Yes. Section scores were highest for discharge readiness (18.8±2.4) and lowest for postdischarge care (7.3±8.1). Like acute myocardial infarction, total and section-related mean scores did not differ by PPR status; PPR-Yes versus PPR-No total scores were 61.2±10.8 and 63.4±7.0, respectively; P =0.47. Conclusions— Among VA acute myocardial infarction and heart failure readmissions, the 3M-PPR software does not distinguish differences in case-level quality of care. Whether 3M-PPR software better identifies preventable readmissions by using other methods to capture poorly documented processes or performing different comparisons requires further study.

Identification of adverse events (AEs) is critical for improving patient safety. However, accurate measurement continues to be challenging, and efforts to detect and track surgical AEs in the outpatient setting lag behind those of the inpatient setting. Although numerous methods have been utilised over the years to detect AEs (eg, voluntary reporting systems, chart review and patient interviews), these detection systems suffer from a variety of limitations including resource constraints.1 ,2 More recent development of automated surveillance systems to detect AEs using electronic medical record (EMR) data has greatly facilitated the identification of AEs, particularly among ambulatory patients.3–6 Menendez et al illustrate how EMR data and electronic triggers can contribute to better measurement of patient safety in outpatient surgery.7 Trigger methodology has substantially improved since the seminal work of the Institute for Healthcare Improvement (IHI) in the early 2000s that helped promulgate the use of chart-based trigger tools for retrospective detection of AEs.8–10 Although triggers are still evolving as informatics tools, and are likely in their ‘early stages’ of development, the trigger methodology represents a good compromise between two modalities: automated surveillance systems and manual chart review (ie, the ‘gold standard’). Triggers rely on both electronic and manual review processes to search for patterns in the data consistent with a possible AE. Triggers use surveillance rules or algorithms derived from clinical logic to flag patient medical records for the presence of an AE. Once a trigger is flagged in the data, then the patient's medical record is reviewed to confirm the occurrence (yes/no) of the AE. …

Readmission is widely used as a quality metric to assess hospital performance. However, different methods to calculate readmissions may produce various results, leading to differences in classification with respect to hospital performance. This study compared 2 commonly used approaches to measure surgical readmissions: the 30-day all-cause hospital-wide readmissions (HWRs) and the potentially preventable readmissions (PPRs).We examined the correlation between hospitals' risk-adjusted HWR and PPR rates and whether there was agreement in categorizing hospital performance between these measures among 111 hospitals with inpatient surgical programs in the Veterans Health Administration.We found that hospitals' HWR and PPR rates were highly correlated (r = .85, P.0001). The overall agreement between these 2 methods in categorizing hospital performance was 82% for all surgeries, 82% for colectomy, 84% for coronary bypass, and 87% for hip/knee replacement, respectively.Despite differences in methodologies, the HWR and the PPR measures provided relatively consistent perceptions of hospitals' performance on surgical readmissions.

We acknowledge here and in our paper1 that the Potentially Preventable Readmissions (PPRs) and the Centers for Medicare and Medicaid Services (CMS) readmission measures are intended to be used for hospital-level comparisons of risk-adjusted rates. The premise behind both measures is that hospitals or providers with higher than expected rates have more readmissions associated with quality of care problems during the index admission and postdischarge periods.2 ,3 However, the PPRs purport to improve upon the CMS all-cause readmission measure by including readmissions that are more likely to be preventable. For both measures, in order to improve rates, a hospital or provider would have to drill down to the individual discharge or patient level to examine further if there were any quality-of-care issues. Since we wanted to know if the PPRs provided any additional benefit for this purpose beyond …