Arteriovenous Graft Failure in the Veterans Health Administration: Outcome Disparities Associated with Race.

Background Vascular access for ongoing hemodialysis often fails, frequently requiring repeated procedures to maintain vascular patency. While research has shown racial discrepancies in multiple aspects of renal failure treatment, there is poor understanding of how these factors might relate to vascular access maintenance procedures after arteriovenous graft (AVG) placement. Purpose To evaluate racial disparities associated with premature vascular access failure after percutaneous access maintenance procedures following AVG placement using a retrospective national cohort from the Veterans Health Administration (VHA). Materials and Methods All hemodialysis vascular maintenance procedures performed at VHA hospitals between October 2016 and March 2020 were identified. To ensure the sample represented patients who consistently used the VHA, patients without AVG placement within 5 years of their first maintenance procedure were excluded. Access failure was defined as a repeat access maintenance procedure or as hemodialysis catheter placement occurring 1-30 days after the index procedure. Multivariable logistic regression analyses were performed to calculate prevalence ratios (PRs) measuring the association between hemodialysis maintenance failure and African American race compared with all other races. Models controlled for vascular access history, patient socioeconomic status, and procedure and facility characteristics. Results In total, 1950 access maintenance procedures in 995 patients (mean age, 69 years ± 9 [SD], 1870 men) with an AVG created in one of 61 VHA facilities were identified. Most procedures involved African American patients (1169 of 1950, 60%) and patients residing in the South (1002 of 1950, 51%). Premature access failure occurred in 215 of 1950 (11%) procedures. When compared with all other races, African American race was associated with premature access site failure (PR, 1.4; 95% CI: 1.07, 1.43; P = .02). Among the 1057 procedures in 30 facilities with interventional radiology resident training programs, there was no evidence of racial disparity in the outcome (PR, 1.1; P = .63). Conclusion African American race was associated with higher risk-adjusted rates of premature arteriovenous graft failure after dialysis maintenance. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Forman and Davis in this issue.

Novel methodology to measure pre-procedure antimicrobial prophylaxis: integrating text searches with structured data from the Veterans Health Administration's electronic medical record.

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.

Homeless Status, Postdischarge Health Care Utilization, and Readmission After Surgery.

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

A study to reduce readmissions after surgery in the Veterans Health Administration: design and methodology.

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.

Postoperative 30-day Readmission: Time to Focus on What Happens Outside the Hospital.

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

Does Use of a Hospital-wide Readmission Measure Versus Condition-specific Readmission Measures Make a Difference for Hospital Profiling and Payment Penalties?

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.

Medical and surgical readmissions in the Veterans Health Administration: what proportion are related to the index hospitalization?

BACKGROUND: Readmissions are an attractive quality measure because they offer a broad view of quality beyond the index hospitalization. However, the extent to which medical or surgical readmissions reflect quality of care is largely unknown, because of the complexity of factors related to readmission. Identifying those readmissions that are clinically related to the index hospitalization is an important first step in closing this knowledge gap. OBJECTIVES: The aims of this study were to examine unplanned readmissions in the Veterans Health Administration, identify clinically related versus unrelated unplanned readmissions, and compare the leading reasons for unplanned readmission between medical and surgical discharges. METHODS: We classified 2,069,804 Veterans Health Administration hospital discharges (Fiscal Years 2003-2007) into medical/surgical index discharges with/without readmissions per their diagnosis-related groups. Our outcome variable was "all-cause" 30-day unplanned readmission. We compared medical and surgical unplanned readmissions (n=217,767) on demographics, clinical characteristics, and readmission reasons using descriptive statistics. RESULTS: Among all unplanned readmissions, 41.5% were identified as clinically related. Not surprisingly, heart failure (10.2%) and chronic obstructive pulmonary disease (6.5%) were the top 2 reasons for clinically related readmissions among medical discharges; postoperative complications (ie, complications of surgical procedures and medical care or complications of devices) accounted for 70.5% of clinically related readmissions among surgical discharges. CONCLUSIONS: Although almost 42% of unplanned readmissions were identified as clinically related, the majority of unplanned readmissions were unrelated to the index hospitalization. Quality improvement interventions targeted at processes of care associated with the index hospitalization are likely to be most effective in reducing clinically related readmissions. It is less clear how to reduce nonclinically related readmissions; these may involve broader factors than inpatient care.

Travel distance and outcomes after surgical aortic valve among veterans.

OBJECTIVE: To investigate the association between travel distance and postoperative length of stay (LOS) and discharge disposition among veterans undergoing surgical aortic valve replacement (SAVR). DATA SOURCES/STUDY SETTING: We performed a retrospective cohort study of patients undergoing SAVR, with or without coronary artery bypass grafting (CABG) at VA Boston Healthcare (January 1, 2005-December 31, 2015). STUDY DESIGN: Postoperative LOS and discharge disposition were compared for SAVR patients based on travel distance to the facility: <100 miles or ≥100 miles. Multivariable regression was performed to ascertain factors associated with LOS and home discharge. DATA COLLECTION/EXTRACTION METHODS: Data were collected via chart review. All patients undergoing SAVR at our institution who primarily resided within the defined region were included. PRINCIPAL FINDINGS: Of 597 patients studied, 327 patients underwent isolated SAVR; 270 patients underwent SAVR/CABG. Overall median (IQR) distance between the patient's residence and the hospital was 49.95 miles (27.41-129.94 miles); 190 patients (32%) resided further than 100 miles away. There were no differences in the proportion of patients with diabetes, hypertension, chronic obstructive pulmonary disease (COPD), cerebrovascular disease, atrial fibrillation, or prior myocardial infarction between groups. Overall LOS (IQR) was 9 (7-13) days and did not differ between groups (p = 0.18). The proportion of patients discharged home was higher among patients who resided more than 100 miles from the hospital (71% vs. 58%, p = 0.01). On multivariable analysis, residing further than 100 miles from the hospital was independently associated with home discharge (OR = 1.64, 95% CI: 1.09-2.48). Travel distance was not associated with LOS. CONCLUSIONS: Based on our institutional experience, potential concerns of longer hospital stay or discharge to other inpatient facilities for geographically distanced patients undergoing SAVR do not appear supported. Continued examination of the drivers underlying the marked shift of veterans to the private sector appears warranted.

Development and Validation of an Electronic Adverse Event Model for Patient Safety Surveillance in Interventional Radiology.

BACKGROUND: Comprehensive adverse event (AE) surveillance programs in interventional radiology (IR) are rare. Our aim was to develop and validate a retrospective electronic surveillance model to identify outpatient IR procedures that are likely to have an AE, to support patient safety and quality improvement. METHODS: We identified outpatient IR procedures performed in the period from October 2017 to September 2019 from the Veterans Health Administration (n = 135,283) and applied electronic triggers based on posyprocedure care to flag cases with a potential AE. From the trigger-flagged cases, we randomly sampled n = 1,500 for chart review to identify AEs. We also randomly sampled n = 600 from the unflagged cases. Chart-reviewed cases were merged with patient, procedure, and facility factors to estimate a mixed-effects logistic regression model designed to predict whether an AE occurred. Using model fit and criterion validity, we determined the best predicted probability threshold to identify cases with a likely AE. We reviewed a random sample of 200 cases above the threshold and 100 cases from below the threshold from October 2019 to March 2020 (n = 20,849) for model validation. RESULTS: In our development sample of mostly trigger-flagged cases, 444 of 2,096 cases (21.8%) had an AE. The optimal predicted probability threshold for a likely AE from our surveillance model was >50%, with positive predictive value of 68.9%, sensitivity of 38.3%, and specificity of 95.3%. In validation, chart-reviewed cases with AE probability >50% had a positive predictive value of 63% (n = 203). For the period from October 2017 to March 2020, the model identified approximately 70 IR cases per month that were likely to have an AE. CONCLUSIONS: This electronic trigger-based approach to AE surveillance could be used for patient-safety reporting and quality review.

Comparing 2 methods of assessing 30-day readmissions: what is the impact on hospital profiling in the veterans health administration?

BACKGROUND: The Centers for Medicare and Medicaid Services' (CMS) all-cause readmission measure and the 3M Health Information System Division Potentially Preventable Readmissions (PPR) measure are both used for public reporting. These 2 methods have not been directly compared in terms of how they identify high-performing and low-performing hospitals. OBJECTIVES: To examine how consistently the CMS and PPR methods identify performance outliers, and explore how the PPR preventability component impacts hospital readmission rates, public reporting on CMS' Hospital Compare website, and pay-for-performance under CMS' Hospital Readmission Reduction Program for 3 conditions (acute myocardial infarction, heart failure, and pneumonia). METHODS: We applied the CMS all-cause model and the PPR software to VA administrative data to calculate 30-day observed FY08-10 VA hospital readmission rates and hospital profiles. We then tested the effect of preventability on hospital readmission rates and outlier identification for reporting and pay-for-performance by replacing the dependent variable in the CMS all-cause model (Yes/No readmission) with the dichotomous PPR outcome (Yes/No preventable readmission). RESULTS: The CMS and PPR methods had moderate correlations in readmission rates for each condition. After controlling for all methodological differences but preventability, correlations increased to >90%. The assessment of preventability yielded different outlier results for public reporting in 7% of hospitals; for 30% of hospitals there would be an impact on Hospital Readmission Reduction Program reimbursement rates. CONCLUSIONS: Despite uncertainty over which readmission measure is superior in evaluating hospital performance, we confirmed that there are differences in CMS-generated and PPR-generated hospital profiles for reporting and pay-for-performance, because of methodological differences and the PPR's preventability component.

What is the role of selection bias in quality comparisons between the Veterans Health Administration and community care? Example of elective hernia surgery.

OBJECTIVE: 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. DATA SOURCES AND STUDY SETTING: 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). STUDY DESIGN: 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. DATA COLLECTION: We identified patients residing ≤40 miles from a VHA surgical facility with elective VHA or CC hernia surgery from 2018 to 2019. PRINCIPAL FINDINGS: 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. CONCLUSIONS: 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.

Development of a Periprocedure Trigger for Outpatient Interventional Radiology Procedures in the Veterans Health Administration.

OBJECTIVES: Interventional radiology (IR) is the newest medical specialty. However, it lacks robust quality assurance metrics, including adverse event (AE) surveillance tools. Considering the high frequency of outpatient care provided by IR, automated electronic triggers offer a potential catalyst to support accurate retrospective AE detection. METHODS: We programmed previously validated AE triggers (admission, emergency visit, or death up to 14 days after procedure) for elective, outpatient IR procedures performed in Veterans Health Administration surgical facilities between fiscal years 2017 and 2019. We then developed a text-based algorithm to detect AEs that explicitly occurred in the periprocedure time frame: before, during, and shortly after the IR procedure. Guided by the literature and clinical expertise, we generated clinical note keywords and text strings to flag cases with high potential for periprocedure AEs. Flagged cases underwent targeted chart review to measure criterion validity (i.e., the positive predictive value), to confirm AE occurrence, and to characterize the event. RESULTS: Among 135,285 elective outpatient IR procedures, the periprocedure algorithm flagged 245 cases (0.18%); 138 of these had ≥1 AE, yielding a positive predictive value of 56% (95% confidence interval, 50%-62%). The previously developed triggers for admission, emergency visit, or death in 14 days flagged 119 of the 138 procedures with AEs (73%). Among the 43 AEs detected exclusively by the periprocedure trigger were allergic reactions, adverse drug events, ischemic events, bleeding events requiring blood transfusions, and cardiac arrest requiring cardiopulmonary resuscitation. CONCLUSIONS: The periprocedure trigger performed well on IR outpatient procedures and offers a complement to other electronic triggers developed for outpatient AE surveillance.

Prevalence of One-Year Mortality after Implantable Cardioverter Defibrillator Placement: An Opportunity for Palliative Care?

Background: Current guidelines recommend against placement of implantable cardioverter defibrillators in patients with a life expectancy less than one year. These patients may benefit from early palliative care services; however, identifying this population is challenging. Objective: Determine whether a validated prognostic tool, based on patient factors and health care utilization from electronic medical records, accurately predicts one-year mortality at the time of implantable cardioverter defibrillator placement. Design: We used the United States (U.S.) Veterans Administration's "Care Assessment Needs" one-Year Mortality Score to identify patients at high risk of mortality (score ≥95) before their procedure. Data were extracted from the Corporate Data Warehouse. Logistic regression was used to assess the odds of mortality at different score levels. Setting/Subjects: Patients undergoing a new implantable cardioverter defibrillator procedure between October 1, 2015 and September 30, 2017 in the U.S. Veterans Administration. Results: Of 3194 patients with a new implantable cardioverter defibrillator placed, 657 (21.8%) had a score ≥95. The mortality rate among these patients was 151/657 (22.9%) compared with 281/3194 (8.8%) for all patients undergoing a new implantable cardioverter defibrillator procedure. Patients with a score ≥95 had 14.0 (95% confidence interval 8.0-24.4) higher odds of death within one year of the procedure compared with those with a score ≤60. Conclusions: The "Care Assessment Needs" Score is a valid predictor of one-year mortality following implantable cardioverter defibrillator procedures. Integrating its use into the management of Veterans Administration (VA) patients considering implantable cardioverter defibrillators may improve shared decision making and engagement with palliative care.

Does screening for PTSD lead to VA mental health care? Identifying the spectrum of initial VA screening actions.

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 (N = 41,570). We collapsed actions into those that could lead to VA-based mental health care (e.g., consult placed to a VA mental health clinic) versus not (e.g., veteran declined care), and then examined the association between these categories of actions and contextual- and individual-level variables. More than 61% of veterans with positive PTSD screens had evidence that an initial action toward VA-based mental health care was taken. Urban-dwelling and female veterans were significantly more likely to have evidence of these initial actions, whereas White and Vietnam-era veterans were significantly less likely to have this evidence. Our findings suggest that most veterans screening positive for PTSD in VA primary care clinics have evidence of initial actions taken toward VA-based mental health care; however, a substantial minority do not, making them unlikely to receive follow-up care. Findings highlight the potential benefit of targeted primary care-based access interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A Novel Informatics Tool to Detect Periprocedural Antibiotic Allergy Adverse Events for Near Real-time Surveillance to Support Audit and Feedback.

Importance: Standardized processes for identifying when allergic-type reactions occur and linking reactions to drug exposures are limited. Objective: To develop an informatics tool to improve detection of antibiotic allergic-type events. Design, Setting, and Participants: This 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. Exposure: Preprocedural and postprocedural prophylactic antibiotic administration. Main Outcomes and Measures: Antibiotic allergic-type reactions. Results: The 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 Relevance: In 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.

Factors associated with uptake of guideline-recommended cardiovascular implantable electronic device management: a nationwide, retrospective cohort study.

Clinical guidelines recommend device removal for cardiovascular implantable electronic device (CIED) infection management. In this retrospective, nationwide cohort, 60.8% of CIED infections received guideline-concordant care. One-year mortality was higher among those without procedural management (25% vs 16%). Factors associated with receipt of device procedures included pocket infections and positive microbiology.

Assessing the sustainability of compliance with surgical site infection prophylaxis after discontinuation of mandatory active reporting: study protocol.

BACKGROUND: Surgical site infections are common. Risk can be reduced substantially with appropriate preoperative antimicrobial administration. In 2005, the VA implemented the Surgical Care Improvement Project (SCIP) in the setting of high rates of non-compliance with antimicrobial prophylaxis guidelines. SCIP included public reporting of evidenced-based antimicrobial guideline compliance metrics in high-risk surgeries. SCIP was highly successful and led to high rates of adoption of preoperative antimicrobials and early discontinuation of postoperative antimicrobials (>95%). The program was retired in 2015, as the manual measurement and reporting process was costly with limited expected additional benefit. To our knowledge, no studies have assessed whether the gains achieved by SCIP were sustained since active support for the program was discontinued. Furthermore, there has been no investigation of the spread of antimicrobial prophylaxis guideline adoption beyond the limited set of procedures that were included in the program. METHODS: Using a mixed methods sequential exploratory approach, this study will (1) quantitatively measure compliance with SCIP metrics over time and across all procedures in the five major surgical specialties targeted by SCIP and (2) collect qualitative data from stakeholders to identify strategies that were effective for sustaining compliance. Diffusion of Innovation Theory will guide assessment of whether improvements achieved spread to procedures not included under the umbrella of the program. Electronic algorithms to measure SCIP antimicrobial use will be adapted from previously developed methodology. These highly novel data mining algorithms leverage the rich VA electronic health record and capture structured and text data and represent a substantial technological advancement over resource-intensive manual chart review or incomplete electronic surveillance based on pharmacy data. An interrupted time series analysis will be used to assess whether SCIP compliance was sustained following program discontinuation. Generalized linear models will be used to assess whether compliance with appropriate prophylaxis increased in all SCIP targeted and non-targeted procedures by specialty over the duration the program's active reporting. The Dynamic Sustainability Framework will guide the qualitative methods to assess intervention, provider, facility, specialty, and contextual factors associated with sustainability over time. Barriers and facilitators to sustainability will be mapped to implementation strategies and the study will yield an implementation playbook to guide future sustainment efforts. RELEVANCE: Sustainability of practice change has been described as one of the most important, but least studied areas of clinical medicine. Learning how practices spread is also a critically important area of investigation. This study will use novel informatics strategies to evaluate factors associated with sustainability following removal of active policy surveillance and advance our understanding about these important, yet understudied, areas.

Promoting de-implementation of inappropriate antimicrobial use in cardiac device procedures by expanding audit and feedback: protocol for hybrid III type effectiveness/implementation quasi-experimental study.

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.

Association Between Diabetic Foot Infection Wound Culture Positivity and 1-Year Admission for Invasive Infection: A Multicenter Cohort Study.

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.

Identifying Risks and Opportunities in Outpatient Surgical Patient Safety: A Qualitative Analysis of Veterans Health Administration Staff Perceptions.

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.