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To investigate the relationship between community care (CC) treatment and a postoperative surgical complication in elective hernia surgery among Veterans using multiple approaches to control for potential selection bias.Veterans Health Administration (VHA) data sources included Corporate Data Warehouse (VHA encounters and patient data), the Program Integrity Tool and Fee tables (CC encounters), the Planning Systems Support Group (geographic information), and the Paid file (VHA primary care providers).Prior works suggest patient outcomes are better in VHA than in CC settings; however, these studies may not have appropriately accounted for the selection of higher-risk cases into CC. We estimated (1) a naïve logistic regression model to calculate the effect of CC setting on the probability of a complication, controlling for facility fixed effects and patient and procedure characteristics, and (2) a 2-stage model using the hernia patient's primary care provider's 1-year prior CC referral rate as the instrument.We identified patients residing ≤40 miles from a VHA surgical facility with elective VHA or CC hernia surgery from 2018 to 2019.Of 7991 hernia surgeries, 772 (9.7%) were in CC. The overall complication rate was 4.2%; 286/7219 (4.0%) among VHA surgeries versus 51/5772 (6.6%, p 0.05) in CC. We observed a 2.8 percentage point increase in the probability of postoperative complication given CC surgery (95% confidence interval: 0.7, 4.8) in the naïve model. After accounting for the VHA provider's historical rate of CC referral, we no longer observed a relationship between surgery setting and risk of postoperative complication.After accounting for the selection of higher-risk patients to CC settings, we found no difference in hernia surgery postoperative complications between CC and VHA. Future VHA and non-VHA comparisons should account for unobserved as well as observed differences in patients seen in each setting.

Background Antibiotics are one of the leading causes of emergency room visits for adverse drug events, yet surveillance for antimicrobial allergy adverse events is limited and identifying true cases is challenging. As part of a larger study to improve antimicrobial use, we sought to develop and validate a tool for near real-time measurement of antimicrobial allergy adverse events. Methods An existing cohort of patients undergoing cardiac device procedures with known antimicrobial exposure was split into a development and validation set. Candidate triggers for identifying allergic reactionswere identified a priori, using disease phenotype codes “phecodes”, allergy documentation on allergy module of the electronic medical record (EMR), and keyword searches applied to clinical notes (e.g., “anaphylaxis,” “rash”), medication administration (e.g, corticosteroids alone or with antihistamines) and administrative codes (ICD-10 codes and phecodes). Cases were reviewed for presence of a true event, and the tool was iteratively updated based on chart review findings. The tool was then applied to the validation cohort and a sample of trigger-flagged and unflagged cases underwent manual review. Data were analyzed in SAS and model triggers were selected using a LASSO technique. Results Among 34,703 patients, N=431 cases underwent manual review (350 development; 120 validation), and 104 true allergy adverse events were identified. Among chart reviewed cases, the most frequently detected flags were keywords in unstructured clinical notes (35%), phecodes (26%), corticosteroid administration (15%), observed allergy documentation in EMR (14%) and reported allergy documentation in EMR (13%). The final model contained 7 triggers and had an AUC of 0.95, and a positive predictive value of 67% (Figure). The strongest predictors of true adverse events were the allergy health factors (aOR 358, 95% CI 76.3-999) and specific Phecodes (Table1). Conclusion We developed an antibiotic allergy measurement tool using structured and unstructured data that can be applied to detect antimicrobial adverse events in near-real time. This model may be applied to provide near real-time feedback to clinicians about antimicrobial allergy adverse events and may be useful for antimicrobial stewardship programs. Disclosures Westyn Branch-Elliman, MD, MMSc, DLA Piper,LLC/Medtronic: Advisor/Consultant|Gilead Pharmaceuticals: Grant/Research Support.

ImportanceStandardized processes for identifying when allergic-type reactions occur and linking reactions to drug exposures are limited.ObjectiveTo develop an informatics tool to improve detection of antibiotic allergic-type events.Design, Setting, and ParticipantsThis retrospective cohort study was conducted from October 1, 2015, to September 30, 2019, with data analyzed between July 1, 2021, and January 31, 2022. The study was conducted across Veteran Affairs hospitals among patients who underwent cardiovascular implantable electronic device (CIED) procedures and received periprocedural antibiotic prophylaxis. The cohort was split into training and test cohorts, and cases were manually reviewed to determine presence of allergic-type reaction and its severity. Variables potentially indicative of allergic-type reactions were selected a priori and included allergies entered in the Veteran Affair’s Allergy Reaction Tracking (ART) system (either historical [reported] or observed), allergy diagnosis codes, medications administered to treat allergic reactions, and text searches of clinical notes for keywords and phrases indicative of a potential allergic-type reaction. A model to detect allergic-type reaction events was iteratively developed on the training cohort and then applied to the test cohort. Algorithm test characteristics were assessed.ExposurePreprocedural and postprocedural prophylactic antibiotic administration.Main Outcomes and MeasuresAntibiotic allergic-type reactions.ResultsThe cohort of 36 344 patients included 34 703 CIED procedures with antibiotic exposures (mean [SD] age, 72 [10] years; 34 008 [98%] male patients); median duration of postprocedural prophylaxis was 4 days (IQR, 2-7 days; maximum, 45 days). The final algorithm included 7 variables: entries in the Veteran Affair’s hospitals ART, either historic (odds ratio [OR], 42.37; 95% CI, 11.33-158.43) or observed (OR, 175.10; 95% CI, 44.84-683.76); PheCodes for “symptoms affecting skin” (OR, 8.49; 95% CI, 1.90-37.82), “urticaria” (OR, 7.01; 95% CI, 1.76-27.89), and “allergy or adverse event to an antibiotic” (OR, 11.84, 95% CI, 2.88-48.69); keyword detection in clinical notes (OR, 3.21; 95% CI, 1.27-8.08); and antihistamine administration alone or in combination (OR, 6.51; 95% CI, 1.90-22.30). In the final model, antibiotic allergic-type reactions were identified with an estimated probability of 30% or more; positive predictive value was 61% (95% CI, 45%-76%); and sensitivity was 87% (95% CI, 70%-96%).Conclusions and RelevanceIn this retrospective cohort study of patients receiving periprocedural antibiotic prophylaxis, an algorithm with a high sensitivity to detect incident antibiotic allergic-type reactions that can be used to provide clinician feedback about antibiotic harms from unnecessarily prolonged antibiotic exposures was developed.

This cohort study examines the association between same-day preoperative glycemic control and postoperative adverse events among patients with diabetes undergoing ambulatory hernia surgery.

Despite the active posttraumatic stress disorder (PTSD) screening program in Department of Veterans Affairs (VA) primary care clinics and the availability of empirically supported treatments for PTSD at VA, many veterans for whom screening suggests treatment may be indicated do not gain access to VA-based mental health care. To determine where we may be losing veterans to follow-up, we need to begin by identifying the initial action taken in response to a positive PTSD screen in primary care. Using VA administrative data and chart review, we identified the spectrum of initial actions taken after veterans screened positive for PTSD in VA primary care clinics nationwide between October 2017 and September 2018 (

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.

Background: Despite a strong evidence base and clinical guidelines specifically recommending against prolonged post-procedural antimicrobial use, studies indicate that the practice is common following cardiac device procedures. Formative evaluations conducted by the study team suggest that inappropriate antimicrobial use may be driven by information silos that drive provider belief that antimicrobials are not harmful, in part due to lack of complete feedback about all types of clinical outcomes. De-implementation is recognized as an important area of research that can lead to reductions in unnecessary, wasteful, or harmful practices, such as excess antimicrobial use following cardiac device procedures; however, investigations into strategies that lead to successful de-implementation are limited. The overarching hypothesis to be tested in this trial is that a bundle of implementation strategies that includes audit and feedback about direct patient harms caused by inappropriate prescribing can lead to successful de-implementation of guideline-discordant care.Methods: We propose a Hybrid Type III effectiveness-implementation stepped-wedge intervention trial at three high-volume, high-complexity VA medical centers. The main study intervention (an informatics-based, real-time audit-and-feedback tool) was developed based on learning/unlearning theory and formative evaluations and guided by the integrated-Promoting Action on Research Implementation in Health Services (i-PARIHS) Framework. Elements of the bundled and multifaceted implementation strategy to promote appropriate prescribing will include audit-and-feedback reports that include information about antibiotic harms, stakeholder engagement, patient and provider education, identification of local champions, and blended facilitation. The primary study outcome is adoption of evidence-based practice (de-implementation of inappropriate antimicrobial use). Clinical outcomes (cardiac device infections, acute kidney injuries and Clostridioides difficile infections) are secondary. Qualitative interviews will assess relevant implementation outcomes (acceptability, adoption, fidelity, feasibility).Discussion: De-implementation theory suggests that factors that may have a particularly strong influence on de-implementation include strength of the underlying evidence, the complexity of the intervention, and patient and provider anxiety and fear about changing an established practice. This study will assess whether a multifaceted intervention mapped to identified de-implementation barriers leads to measurable improvements in provision of guideline-concordant antimicrobial use. Findings will improve understanding about factors that impact successful or unsuccessful de-implementation of harmful or wasteful healthcare practices.Trial Registration: Clinicaltrials.gov (NCT05020418)

BACKGROUND: Direct oral anticoagulants (DOACs) are an alternative to warfarin for treatment of atrial fibrillation (AF). Evidence demonstrating the efficacy and safety of DOACs has primarily been from clinical trial settings. The real-world effectiveness of DOACs in specific nontrial populations that differ in age, comorbidity burden, and socioeconomic status is unclear. OBJECTIVE: To compare total downstream medical expenditure between AF patients treated with warfarin and DOACs dually enrolled in the Veterans Affairs (VA) Healthcare System and fee-for-service Medicare. METHODS: This was an exploratory treatment effectiveness study that analyzed VA administrative data and Medicare claims. We examined patients with an incident diagnosis for AF and initiated warfarin or DOAC treatment between 2012 and 2015. The primary outcome was total medical expenditure over 3 years following treatment initiation. To address potential informative censoring, we applied a multipart estimator that extends traditional 2-part models to separate differences between groups due to survival and cost accumulation effects. Inverse probability weighting was applied to address potential treatment selection bias. RESULTS: We identified 31,276 and 17,021 patients receiving warfarin and DOACs, respectively. Mean unadjusted (SD) expenditure was higher for warfarin ($56,265 [$96,666]) compared with DOAC patients ($32,736 [$52,470]). Compared with patients receiving DOACs, adjusted 3-year expenditure was $25,688 (P < 0.001) higher for patients receiving warfarin. CONCLUSIONS: VA patients with AF initiating warfarin incurred markedly higher downstream expenditure compared with similar patients receiving DOACs. The benefits of DOACs found in previous clinical trials were present in this population, suggesting that these DOACs may be the preferred option for treatment of AF in older VA patients. DISCLOSURES: This study was funded by a VA Health Services Research and Development Investigator Initiated Research Award (IIR 15-139). Support for VA/CMS data was provided by the Department of Veterans Affairs, Veterans Health Administration, Office of Research and Development, Health Services Research and Development, VA Information Resource Center (Project Numbers SDR 02-237 and 98-004). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs, the University of Washington, Northeastern University, and Boston University. The authors declare no conflicts of interest. This research includes data obtained from the VHA Office of Performance Measurement (17API2), which resides within the Office of Analytics and Performance Integration (API), under the Office of Quality and Patient Safety (QPS; formerly known as RAPID). An oral presentation documenting a subset of the findings from this study was presented at the 2020 AcademyHealth Annual Research Meeting, delivered virtually on July 29, 2020.

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.

Key Points Question How can coded and free-text data from electronic medical records be used to support infection tracking and other patient safety surveillance following common but understudied cardiac device procedures? Findings In this national cohort study of 19 212 patients who underwent cardiovascular implantable electronic device procedures in the US Department of Veterans Affairs health care system, an algorithm to reliably identify cases with a true 90-day infection by combining coded data (eg, diagnosis of a comorbid condition) and free-text data extracted from clinical notes (eg, documentation of an infection by a cardiologist) was developed and validated. Text note searching was a useful and straightforward adjunct to coded data for surveillance. Meaning The findings of this study suggest that the algorithm to detect patients who received cardiovascular implantable electronic device and developed an infection has the potential to significantly enhance surveillance in an underserved area., This cohort study describes the development of an algorithm to identify cardiac implantable device infections using coded and free-text data from the Veterans Health Administration’s electronic medical record., Importance Health care–associated infections (HAIs) are preventable, harmful, and costly; however, few resources are dedicated to infection surveillance of nonsurgical procedures, particularly cardiovascular implantable electronic device (CIED) procedures. Objective To develop a method that includes text mining of electronic clinical notes to reliably and efficiently measure HAIs for CIED procedures. Design, Setting, and Participants In this multicenter, national cohort study using electronic medical record data for patients undergoing CIED procedures in Veterans Health Administration (VA) facilities for fiscal years (FYs) 2016 and 2017, an algorithm to flag cases with a true CIED-related infection based on structured (eg, microbiology orders, vital signs) and free text diagnostic and therapeutic data (eg, procedure notes, discharge summaries, microbiology results) was developed and validated. Procedure data were divided into development and validation data sets. Criterion validity (ie, positive predictive validity [PPV], sensitivity, and specificity) was assessed via criterion-standard manual medical record review. Exposures CIED procedure. Main Outcomes and Measures The concordance between medical record review and the study algorithm with respect to the presence or absence of a CIED infection. CIED infection in the algorithm included 90-day mortality, congestive heart failure and nonmetastatic tumor comorbidities, CIED or surgical site infection International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes, antibiotic treatment of Staphylococci, a microbiology test of a cardiac specimen, and text documentation of infection in specific clinical notes (eg, cardiology, infectious diseases, inpatient discharge summaries). Results The algorithm sample consisted of 19 212 CIED procedures; 15 077 patients (78.5%) were White individuals, 1487 (15.5%) were African American; 18 766 (97.7%) were men. The mean (SD) age in our sample was 71.8 (10.6) years. The infection detection threshold of predicted probability was set to greater than 0.10 and the algorithm flagged 276 of 9606 (2.9%) cases in the development data set (9606 procedures); PPV in this group was 41.4% (95% CI, 31.6%-51.8%). In the validation set (9606 procedures), at predicted probability 0.10 or more the algorithm PPV was 43.5% (95% CI, 37.1%-50.2%), and overall sensitivity and specificity were 94.4% (95% CI, 88.2%-97.9%) and 48.8% (95% CI, 42.6%-55.1%), respectively. Conclusions and Relevance The findings of this study suggest that the method of combining structured and text data in VA electronic medical records can be used to expand infection surveillance beyond traditional boundaries to include outpatient and procedural areas.

Atrial fibrillation (AFib) is the second most common cardiovascular condition affecting up to 6.1 million individuals in the United States. Treatment of AFib focuses on preventing blood clots to reduce stroke risk. Traditionally, warfarin, a vitamin‐k antagonist, has been used to reduce stroke risk by two‐thirds. However, warfarin requires regular laboratory monitoring to ensure safety and efficacy, and may be cumbersome for patients. Newer direct oral anticoagulants (DOACs) are an alternative treatment and do not require laboratory monitoring due to their more predictable pharmacokinetics. DOACs are either noninferior or superior to warfarin on a variety of outcomes and may be cost‐effective for certain patient populations. Much of the evidence demonstrating benefits of DOACs over warfarin have been in clinical trial settings, which may have limited generalizability to real‐world practice. For example, patients enrolled in the Veterans Affairs (VA) Health care System have increased burden of illness and greater socioeconomic challenges relative to other populations. This study examined whether advantages of DOACs found in prior trials translated to the VA population by comparing total downstream costs between AFib patients treated with warfarin and DOACs. Using administrative data from VA and Medicare, we examined total medical costs (inpatient and outpatient costs incurred in VA and Medicare) over three years following initiation of pharmacological treatment for AFib. To address potential informative censoring, we applied a multipart estimator that extends traditional two‐part models to separate differences between groups due to effects on survival and cost accumulation. This estimator requires modeling the probability of surviving to each time period, hazard probability, expected patient‐level costs over period t conditional on death and expected costs over period t conditional on surviving the full period. We applied inverse probability weighting to address imbalance in characteristics between patients treated with warfarin and DOACs. Weights were estimated as a function of 99 baseline patient and clinic characteristics using boosted regression trees allowing for complex interactions between predictors. 75 547 veterans dually enrolled in VA and fee‐for‐service Medicare who had a new diagnosis for AFib and initiated warfarin or DOAC treatment between 2011 and 2015 The majority of patients initiated warfarin (64%) with the remainder initiating the DOACs apixaban (14%), dabigatran (12%), and rivaroxaban (9%). Mean annual costs in the first through third years of the follow‐up period were $33 364 (SD = $64 493), $18 379 (SD = $38 089), and $17 081 (SD = $38 725), respectively. In adjusted analysis, patients receiving warfarin had lower median survival time (−0.107 years, 95% confidence interval (CI) = −0.213 to −0.011) and higher annual cost conditional on death ($12 873, 95% CI = $8681 to $17 065) and surviving the full year ($9163, 95% CI = $8311 to $10 015). Total three‐year costs were higher among patients receiving warfarin ($22 718, 95% CI = $19 851 to $25 478). VA AFib patients initiating warfarin compared to DOACs incurred significantly higher downstream costs, even after accounting for a greater likelihood of death. The benefits of DOACs found in prior clinical trials appear to also be present among this patient population, suggesting these drugs may be the preferred option for treatment of AFib in elderly VA patients. Department of Veterans Affairs.

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.

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 combine structured and unstructured data from the Veterans’ Health Administration (VA) EMR to create an electronic tool for measuring preincisional antimicrobial prophylaxis. We assessed this methodology in 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. Next, we iteratively combined positive flags for an antimicrobial order or drug fill from structured data fields in the EMR and hits on text string searches of antimicrobial names documented in electronic clinical notes to optimize an algorithm to flag preincisional antimicrobial use with high sensitivity and specificity. 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 then validated the performance of the final version of the algorithm using a national cohort of VA patients who underwent cardiac device procedures in FY 2016 or 2017. Discordant cases underwent expert manual review to identify reasons for algorithm misclassification and to identify potential future implementation barriers. Results: The CART-EP dataset included 2,102 procedures at 38 VA facilities with manually identified antimicrobial prophylaxis in 2,056 cases (97.8%). The final algorithm combining structured EMR fields and text-note search results flagged 2,048 of the CART-EP cases (97.4%). Algorithm validation identified antimicrobial prophylaxis in 16,334 of 19,212 cardiac device procedures (87.9%). Misclassifications occurred due to EMR documentation issues. 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 that does not rely on manual review. In addition to broad applicability in the VA and other healthcare systems with EMRs, this method could be adapted for other procedural areas in which antimicrobial prophylaxis is recommended but comprehensive measurement has been limited to resource-intense manual review.Funding: NoneDisclosures: None

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: Cardiovascular implantable electronic device (CIED) infections are highly morbid, yet infection control resources dedicated to preventing them are limited. Infection surveillance in outpatient care is also challenging because there are no infection reporting mandates, and monitoring patients after discharge is difficult. Objective: Thus, we sought to develop a replicable electronic infection detection methodology that integrates text mining with structured data to expand surveillance to outpatient settings. Methods: Our methodology was developed to detect 90-day CIED infections. We tested an algorithm to accurately flag only cases with a true CIED-related infection using diagnostic and therapeutic data derived from the Veterans Affairs (VA) electronic medical record (EMR), including administrative data fields (visit and hospital stay dates, diagnoses, procedure codes), structured data fields (laboratory microbiology orders and results, pharmacy orders and dispensed name, quantity and fill dates, vital signs), and text files (clinical notes organized by date and type containing unstructured text). We evenly divided a national dataset of CIED procedures from 2016–2017 to create development and validation samples. We iteratively tested various infection flag types to estimate a model predicting a high likelihood of a true infection, defined using chart review, to test criterion validity. We then applied the model to the validation data and reviewed cases with high and low likelihood of infection to assess performance. Results: The algorithm development sample included 9,606 CIED procedures in 67 VA hospitals. Iterative testing over 381 chart reviewed cases with 47 infections produced a final model with a C-statistic of 0.95 (Table 1). We applied the model to the 9,606 CIED procedures in our validation sample and found 100 infections of the 245 cases identified by the model to have a high likelihood of infection We identified no infections among cases the model as having low likelihood. The final model included congestive heart failure and coagulopathy as comorbidities, surgical site infection diagnosis, a blood or cardiac microbiology order, and keyword hits for infection diagnosis and history of infection from clinical notes. Conclusions: Evolution of infection prevention programs to include ambulatory and procedural areas is crucial as healthcare delivery is increasingly provided outside traditional settings. Our method of algorithm development and validation for outpatient healthcare-associated infections using EMR-derived data, including text-note searching, has broad application beyond CIED infections. Furthermore, as integrated healthcare systems employ EMRs in more outpatient settings, this approach to infection surveillance could be replicated in non-VA care.Funding: NoneDisclosures: None

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 In the USA, administrative data-based readmission rates such as the Centers for Medicare and Medicaid Services’ all-cause readmission measures are used for public reporting and hospital payment penalties. To improve this measure and identify better quality improvement targets, 3M developed the Potentially Preventable Readmissions (PPRs) measure. It matches clinically related index admission and readmission diagnoses that may indicate readmissions resulting from admission- or post-discharge-related quality problems. Objective To examine whether PPR software-flagged pneumonia readmissions are associated with poorer quality of care. Methods Using a retrospective observational study design and Veterans Health Administration (VA) data, we identified pneumonia discharges associated with 30-day readmissions, and then flagged cases as PPR–yes or PPR–no using the PPR software. To assess quality of care, we abstracted electronic medical records of 100 random readmissions using a tool containing explicit care processes organised into admission work-up, in-hospital evaluation/treatment, discharge readiness and post-discharge period. We derived quality scores, scaled to a maximum of 25 per section (maximum total score=100) and compared cases by total and section-specific mean scores using t tests and effect size (ES) to characterise the clinical significance of findings. Results Our abstraction sample was selected from 11 278 pneumonia readmissions (readmission rate=16.5%) during 1 October 2005–30 September 2010; 77% were flagged as PPR–yes. Contrary to expectations, total and section mean quality scores were slightly higher, although non-significantly, among PPR–yes (N=77) versus PPR–no (N=23) cases (respective total scores, 71.2±8.7 vs 65.8±11.5, p=0.14); differences demonstrated ES >0.30 overall and for admission work-up and post-discharge period sections. Conclusions Among VA pneumonia readmissions, PPR categorisation did not produce the expected quality of care findings. Either PPR–yes cases are not more preventable, or preventability assessment requires other data collection methods to capture poorly documented processes (eg, direct observation).

BACKGROUND: A standard definition of outpatient surgery that is aligned with the perspective of surgical providers is needed for consistent and focused surgical quality measurement. We sought to clarify the procedure characteristics that define outpatient surgery through a consensus process with multidisciplinary surgical staff from the Veterans Health Administration (VA). METHODS: A convenience sample of 14 VA surgical staff participated in three rounds of a modified-Delphi process. They rated procedure characteristics (e.g., settings, providers, anesthesia, and incision type) to include in a definition of outpatient surgery for adverse event detection. RESULTS: Consensus was reached on 63% of the criteria. Participants agreed to exclude procedures performed by gastroenterologists; in contrast, they agreed to retain endoscopic procedures. There was inter and intra-variation between rounds but no pattern based on staff discipline. CONCLUSIONS: Contradictory responses and the lack of consensus on several key questions revealed few procedure characteristics that surgical staff agreed could be used to define outpatient surgery. Our findings suggest that contextual factors associated with specific procedures may be important; future efforts to define outpatient surgery should consider both the characteristics of the procedure and the procedure itself.

Background The Patient Safety Indicators (PSIs) use administrative data to screen for select adverse events (AEs). In this study, VA Surgical Quality Improvement Program (VASQIP) chart review data were used as the gold standard to measure the criterion validity of 5 surgical PSIs. Independent chart review was also used to determine reasons for PSI errors. Methods The sensitivity, specificity, and positive predictive value of PSI software version 4.1a were calculated among Veterans Health Administration hospitalizations (2003–2007) reviewed by VASQIP (n = 268,771). Nurses re-reviewed a sample of hospitalizations for which PSI and VASQIP AE detection disagreed. Results Sensitivities ranged from 31% to 68%, specificities from 99.1% to 99.8%, and positive predictive values from 31% to 72%. Reviewers found that coding errors accounted for some PSI-VASQIP disagreement; some disagreement was also the result of differences in AE definitions. Conclusions These results suggest that the PSIs have moderate criterion validity; however, some surgical PSIs detect different AEs than VASQIP. Future research should explore using both methods to evaluate surgical quality.

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.

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.

Background Surveillance is an essential aspect of infection prevention. Despite the high morbidity and mortality associated with procedure-related Cardiac Implantable Electronic Device (CIED) infections, methods for identifying them are limited. The objective of this study was to develop an algorithm with electronic flags to facilitate detection of CIED infections in a large, multi-center cohort. Methods A sample of patients who underwent CIED procedures entered into the VA Clinical Assessment Reporting and Tracking Electrophysiology (CART-EP) program from FY 2007 to 2015 were included in the nested case–control study. After cohort creation, data from this review process were combined with electronic variables (e.g., microbiology orders, ICD 9/10 codes) to develop a preliminary algorithm that categorized patients as high, intermediate, or low risk of CIED infection. Results A total of 1,014 unique patients out of a cohort of 5,955 procedures underwent manual review. Among these cases, 59 CIED infections and 955 controls were identified. Electronic variables predictive of CIED infection included ICD 9/10 infection codes and microbiology orders (table). ICD 9/10 codes had excellent PPV for flagging infections but sensitivity was limited (47.5%, see figure). Adding microbiology order flags increased sensitivity but lowered specificity. Specificity in patients without either flag was outstanding (99%). Conclusion Absence of ICD 9/10 and microbiology orders is highly specific for ruling out CIED infections. The discriminatory abilities of the algorithm for intermediate probability flags (+microbiology/−ICD9/10) need improvement. In patients without ICD codes, at least microbiology orders should be used as a flag to streamline review of possible device infections. Refinement of this tool using other clinical flags may improve operating characteristics and clinical utility. Disclosures W. Branch-Elliman, Veterans’ Integrated Service Network Career Development Award: Investigator, Research grant. American Heart Association: Investigator, Research grant.

This study compares rates of 11 Agency for Healthcare Research and Quality Patient Safety Indicators (PSIs) among 266 203 veteran dual users (ie, those with hospitalizations in both the Veterans Health Administration [VA] and the private sector through Medicare fee-for-service coverage) during 2002 to 2007. PSI risk-adjusted rates were calculated using the PSI software (version 3.1a). Rates of pressure ulcer, central venous catheter-related bloodstream infections, and postoperative sepsis, areas in which the VA has focused quality improvement efforts, were found to be significantly lower in the VA than in the private sector. VA had significantly higher rates for 7 of the remaining 8 PSIs, although the rates of only 2 PSIs (postoperative hemorrhage/hematoma and accidental puncture or laceration) remained higher in the VA after sensitivity analyses were conducted. A better understanding of system-level differences in coding practices and patient severity, poorly documented in administrative data, is needed before conclusions about differences in quality can be drawn.