Browsing by Author "Myers, Jennifer"
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Item Association Between Antithrombotic Medication Use After Bioprosthetic Aortic Valve Replacement and Outcomes in the Veterans Health Administration System(American Medical Association (AMA), 2018-12-26) Bravata, Dawn M.; Coffing, Jessica M.; Kansagara, Devan; Myers, Jennifer; Murphy, Lauren; Homoya, Barbara J.; Perkins, Anthony J.; Snow, Kathryn; Quin, Jacquelyn A.; Zhang, Ying; Myers, Laura J.; Medicine, School of MedicineIMPORTANCE: The recommendations about antithrombotic medication use after bioprosthetic aortic valve replacement (bAVR) vary. OBJECTIVES: To describe the post-bAVR antithrombotic medication practice across the Veterans Health Administration (VHA) and to assess the association between antithrombotic strategies and post-bAVR outcomes. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study. Multivariable modeling with propensity scores was conducted to adjust for differences in patient characteristics across the 3 most common antithrombotic medication strategies (aspirin plus warfarin sodium, aspirin only, and dual antiplatelets). Text mining of notes was used to identify the patients with bAVR (fiscal years 2005-2015). MAIN OUTCOMES AND MEASURES: This study used VHA and non-VHA outpatient pharmacy data and text notes to classify the following antithrombotic medications prescribed within 1 week after discharge from the bAVR hospitalization: aspirin plus warfarin, aspirin only, dual antiplatelets, no antithrombotics, other only, and warfarin only. The 90-day outcomes included all-cause mortality, thromboembolism risk, and bleeding events. Outcomes were identified using primary diagnosis codes from emergency department visits or hospital admissions. RESULTS: The cohort included 9060 veterans with bAVR at 47 facilities (mean [SD] age, 69.3 [8.8] years; 98.6% male). The number of bAVR procedures per year increased from 610 in fiscal year 2005 to 1072 in fiscal year 2015. The most commonly prescribed antithrombotic strategy was aspirin only (4240 [46.8%]), followed by aspirin plus warfarin (1638 [18.1%]), no antithrombotics (1451 [16.0%]), dual antiplatelets (1010 [11.1%]), warfarin only (439 [4.8%]), and other only (282 [3.1%]). Facility variation in antithrombotic prescription patterns was observed. During the 90-day post-bAVR period, adverse events were uncommon, including all-cause mortality in 127 (1.4%), thromboembolism risk in 142 (1.6%), and bleeding events in 149 (1.6%). No differences in 90-day mortality or thromboembolism were identified across the 3 antithrombotic medication groups in either the unadjusted or adjusted models. Patients receiving the combination of aspirin plus warfarin had higher odds of bleeding than patients receiving aspirin only in the unadjusted analysis (odds ratio, 2.58; 95% CI, 1.71-3.89) and after full risk adjustment (adjusted odds ratio, 1.92; 95% CI, 1.17-3.14). CONCLUSIONS AND RELEVANCE: These data demonstrate that bAVR procedures are increasingly being performed in VHA facilities and that aspirin only was the most commonly used antithrombotic medication strategy after bAVR. The risk-adjusted results suggest that the combination of aspirin plus warfarin does not improve either all-cause mortality or thromboembolism risk but increases the risk of bleeding events compared with aspirin only.Item Association of Intensive Care Unit Patient Load and Demand With Mortality Rates in US Department of Veterans Affairs Hospitals During the COVID-19 Pandemic(AMA, 2021) Bravata, Dawn M.; Perkins, Anthony J.; Myers, Laura J.; Arling, Greg; Zhang, Ying; Zillich, Alan J.; Reese, Lindsey; Dysangco, Andrew; Agarwal, Rajiv; Myers, Jennifer; Austin, Charles; Sexson, Ali; Leonard, Samuel J.; Dev, Sharmistha; Keyhani, Salomeh; Medicine, School of MedicineImportance Although strain on hospital capacity has been associated with increased mortality in nonpandemic settings, studies are needed to examine the association between coronavirus disease 2019 (COVID-19) critical care capacity and mortality. Objective To examine whether COVID-19 mortality was associated with COVID-19 intensive care unit (ICU) strain. Design, Setting, and Participants This cohort study was conducted among veterans with COVID-19, as confirmed by polymerase chain reaction or antigen testing in the laboratory from March through August 2020, cared for at any Department of Veterans Affairs (VA) hospital with 10 or more patients with COVID-19 in the ICU. The follow-up period was through November 2020. Data were analyzed from March to November 2020. Exposures Receiving treatment for COVID-19 in the ICU during a period of increased COVID-19 ICU load, with load defined as mean number of patients with COVID-19 in the ICU during the patient’s hospital stay divided by the number of ICU beds at that facility, or increased COVID-19 ICU demand, with demand defined as mean number of patients with COVID-19 in the ICU during the patient’s stay divided by the maximum number of patients with COVID-19 in the ICU. Main Outcomes and Measures All-cause mortality was recorded through 30 days after discharge from the hospital. Results Among 8516 patients with COVID-19 admitted to 88 VA hospitals, 8014 (94.1%) were men and mean (SD) age was 67.9 (14.2) years. Mortality varied over time, with 218 of 954 patients (22.9%) dying in March, 399 of 1594 patients (25.0%) dying in April, 143 of 920 patients (15.5%) dying in May, 179 of 1314 patients (13.6%) dying in June, 297 of 2373 patients (12.5%) dying in July, and 174 of 1361 (12.8%) patients dying in August (P < .001). Patients with COVID-19 who were treated in the ICU during periods of increased COVID-19 ICU demand had increased risk of mortality compared with patients treated during periods of low COVID-19 ICU demand (ie, demand of ≤25%); the adjusted hazard ratio for all-cause mortality was 0.99 (95% CI, 0.81-1.22; P = .93) for patients treated when COVID-19 ICU demand was more than 25% to 50%, 1.19 (95% CI, 0.95-1.48; P = .13) when COVID-19 ICU demand was more than 50% to 75%, and 1.94 (95% CI, 1.46-2.59; P < .001) when COVID-19 ICU demand was more than 75% to 100%. No association between COVID-19 ICU demand and mortality was observed for patients with COVID-19 not in the ICU. The association between COVID-19 ICU load and mortality was not consistent over time (ie, early vs late in the pandemic). Conclusions and Relevance This cohort study found that although facilities augmented ICU capacity during the pandemic, strains on critical care capacity were associated with increased COVID-19 ICU mortality. Tracking COVID-19 ICU demand may be useful to hospital administrators and health officials as they coordinate COVID-19 admissions across hospitals to optimize outcomes for patients with this illness.Item Correction to: The “State of Implementation” Progress Report (SIPREP): a pilot demonstration of a navigation system for implementation(BMC, 2020-12-03) Miech, Edward J.; Larkin, Angela; Lowery, Julie C.; Butler, Andrew J.; Pettey, Kristin M.; Rattray, Nicholas A.; Penney, Lauren S.; Myers, Jennifer; Damush, Teresa M.; Regenstrief Institute, IU School of MedicineFollowing publication of the original article [1], it was reported that the incorrect version of a reviewer’s comments were published. The correct version has now been uploaded and the original article has been corrected.Item Estimating and Reporting on the Quality of Inpatient Stroke Care by Veterans Health Administration Medical Centers(2012-01) Arling, Greg; Reeves, Mathew; Ross, Joseph S.; Williams, Linda S.; Keyhani, Salomeh; Chumbler, Neale R.; Phipps, Michael S.; Roumie, Christianne L; Myers, Laura J.; Salanitro, Amanda H; Ordin, Diana L.; Myers, Jennifer; Bravata, Dawn M.Background—Reporting of quality indicators (QIs) in Veterans Health Administration Medical Centers is complicated by estimation error caused by small numbers of eligible patients per facility. We applied multilevel modeling and empirical Bayes (EB) estimation in addressing this issue in performance reporting of stroke care quality in the Medical Centers. Methods and Results—We studied a retrospective cohort of 3812 veterans admitted to 106 Medical Centers with ischemic stroke during fiscal year 2007. The median number of study patients per facility was 34 (range, 12–105). Inpatient stroke care quality was measured with 13 evidence-based QIs. Eligible patients could either pass or fail each indicator. Multilevel modeling of a patient's pass/fail on individual QIs was used to produce facility-level EB-estimated QI pass rates and confidence intervals. The EB estimation reduced interfacility variation in QI rates. Small facilities and those with exceptionally high or low rates were most affected. We recommended 8 of the 13 QIs for performance reporting: dysphagia screening, National Institutes of Health Stroke Scale documentation, early ambulation, fall risk assessment, pressure ulcer risk assessment, Functional Independence Measure documentation, lipid management, and deep vein thrombosis prophylaxis. These QIs displayed sufficient variation across facilities, had room for improvement, and identified sites with performance that was significantly above or below the population average. The remaining 5 QIs were not recommended because of too few eligible patients or high pass rates with little variation. Conclusions—Considerations of statistical uncertainty should inform the choice of QIs and their application to performance reporting.Item Evaluating the feasibility of implementing a Telesleep pilot program using two-tiered external facilitation(BMC, 2020) Rattray, Nicholas A.; Khaw, Andrew; McGrath, Mackenzie; Damush, Teresa M.; Miech, Edward J.; Lenet, Adam; Stahl, Stephanie M.; Ferguson, Jared; Myers, Jennifer; Guenther, David; Homoya, Barbara J.; Bravata, Dawn M.; Anthropology, School of Liberal ArtsBackground: Obstructive sleep apnea (OSA) can negatively impact patients' health status and outcomes. Positive airway pressure (PAP) reverses airway obstruction and may reduce the risk of adverse outcomes. Remote monitoring of PAP (as opposed to in-person visits) may improve access to sleep medicine services. This study aimed to evaluate the feasibility of implementing a clinical program that delivers treatment for OSA through PAP remote monitoring using external facilitation as an implementation strategy. Methods: Participants included patients with OSA at a Veteran Affairs Medical Center (VAMC). PAP adherence and clinical disease severity on treatment (measured by the apnea hypopnea index [AHI]) were the preliminary effectiveness outcomes across two delivery models: usual care (in-person) and Telehealth nurse-delivered remote monitoring. We also assessed visit duration and travel distance. A prospective, mixed-methods evaluation examined the two-tiered external facilitation implementation strategy. Results: The pilot project included N = 52 usual care patients and N = 38 Telehealth nurse-delivered remote monitoring patients. PAP adherence and disease severity were similar across the delivery modalities. However, remote monitoring visits were 50% shorter than in-person visits and saved a mean of 72 miles of travel (median = 45.6, SD = 59.0, mode = 17.8, range 5.4-220). A total of 62 interviews were conducted during implementation with a purposive sample of 12 clinical staff involved in program implementation. Weekly external facilitation delivered to both front-line staff and supervisory physicians was necessary to ensure patient enrollment and treatment. Synchronized, "two-tiered" facilitation at the executive and coordinator levels proved crucial to developing the clinical and administrative infrastructure to support a PAP remote monitoring program and to overcome implementation barriers. Conclusions: Remote PAP monitoring had similar efficacy to in-person PAP services in this Veteran population. Although external facilitation is a widely-recognized implementation strategy in quality improvement projects, less is known about how multiple facilitators work together to help implement complex programs. Two-tiered facilitation offers a model well-suited to programs where innovations span disciplines, disrupt professional hierarchies (such as those between service chiefs, clinicians, and technicians) and bring together providers who do not know each other, yet must collaborate to improve access to care.Item Heterogeneity in COVID-19 patient volume, characteristics and outcomes across US Department of Veterans Affairs facilities: an observational cohort study(BMJ, 2021) Bravata, Dawn M.; Myers, Laura J.; Perkins, Anthony J.; Keyhani, Salomeh; Zhang, Ying; Zillich, Alan J.; Dysangco, Andrew; Lindsey, Reese; Sharmitha, Dev; Myers, Jennifer; Austin, Charles; Sexson, Ali; Arling, Greg; Medicine, School of MedicineObjective Studies describe COVID-19 patient characteristics and outcomes across populations, but reports of variation across healthcare facilities are lacking. The objectives were to examine differences in COVID-19 patient volume and mortality across facilities, and understand whether facility variation in mortality was due primarily to differences in patient versus facility characteristics. Design Observational cohort study with multilevel mixed effects logistic regression modelling. Setting The Veterans Health Administration (VA) is the largest healthcare system in the USA. Participants Patients with COVID-19. Main outcome All-cause mortality within 45 days after COVID-19 testing (March–May, follow-up through 16 July 2020). Results Among 13 510 patients with COVID-19, 3942 (29.2%) were admitted (2266/3942 (57.5%) ward; 1676/3942 (42.5%) intensive care unit (ICU)) and 679/3942 (17.2%) received mechanical ventilation. Marked heterogeneity was observed across facilities in median age (range: 34.3–83.9 years; facility mean: 64.7, SD 7.2 years); patient volume (range: 1–737 at 160 facilities; facility median: 48.5, IQR 14–105.5); hospital admissions (range: 1–286 at 133 facilities; facility median: 11, IQR 1–26.5); ICU caseload (range: 1–85 at 115 facilities; facility median: 4, IQR 0–12); and mechanical ventilation (range: 1–53 at 90 facilities; facility median: 1, IQR 0–5). Heterogeneity was also observed in facility mortality for all patients with COVID-19 (range: 0%–29.7%; facility median: 8.9%, IQR 2.4%–13.7%); inpatients (range: 0%–100%; facility median: 18.0%, IQR 5.6%–28.6%); ICU patients (range: 0%–100%; facility median: 28.6%, IQR 14.3%–50.0%); and mechanical ventilator patients (range: 0%–100%; facility median: 52.7%, IQR 33.3%–80.6%). The majority of variation in facility mortality was attributable to differences in patient characteristics (eg, age). Conclusions Marked heterogeneity in COVID-19 patient volume, characteristics and mortality were observed across VA facilities nationwide. Differences in patient characteristics accounted for the majority of explained variation in mortality across sites. Variation in unadjusted COVID-19 mortality across facilities or nations should be considered with caution.Item Inpatient stroke care quality for Veterans: Are there differences between VA medical centers in the stroke belt and other areas?(Wiley, 2015-01) Jia, Huanguang; Phipps, Michael S.; Bravata, Dawn M.; Castro, Jaime; Li, Xinli; Ordin, Diana L.; Myers, Jennifer; Vogel, W. Bruce; Williams, Linda S.; Chumbler, Neale R.; Department of Medicine, IU School of MedicineBackground Stroke mortality has been found to be much higher among residents in the stroke belt region than in the rest of United States, but it is not known whether differences exist in the quality of stroke care provided in Department of Veterans Affairs medical centers in states inside and outside this region. Objective We compared mortality and inpatient stroke care quality between Veterans Affairs medical centers inside and outside the stroke belt region. Methods Study patients were veterans hospitalized for ischemic stroke at 129 Veterans Affairs medical centers. Inpatient stroke care quality was assessed by 14 quality indicators. Multivariable logistic regression models were fit to examine differences in quality between facilities inside and outside the stroke belt, adjusting for patient characteristics and Veterans Affairs medical centers clustering effect. Results Among the 3909 patients, 28·1% received inpatient ischemic stroke care in 28 stroke belt Veterans Affairs medical centers, and 71·9% obtained care in 101 non-stroke belt Veterans Affairs medical centers. Patients cared for in stroke belt Veterans Affairs medical centers were more likely to be younger, Black, married, have a higher stroke severity, and less likely to be ambulatory pre-stroke. We found no statistically significant differences in short- and long-term post-admission mortality and inpatient care quality indicators between the patients cared for in stroke belt and non-stroke belt Veterans Affairs medical centers after risk adjustment. Conclusions These data suggest that a stroke belt does not exist within the Veterans Affairs health care system in terms of either post-admission mortality or inpatient care quality.Item The prospectively-reported implementation update and score (PRIUS): a new method for capturing implementation-related developments over time(Biomed Central, 2019-02-14) Miech, Edward J.; Rattray, Nicholas A.; Bravata, Dawn M.; Homoya, Barbara J.; Myers, Jennifer; Damush, Teresa M.; Emergency Medicine, School of MedicineBACKGROUND: Implementation of new programs within healthcare systems can be extraordinarily complex. Individuals within the same healthcare organization often have different perspectives on how implementation of a new program unfolds over time, and it is not always clear in the midst of implementation what issues are most important or how to address them. An implementation support team within the Veterans Health Administration (VHA) sought to develop an efficient method for eliciting an ongoing, detailed and nuanced account of implementation progress from multiple viewpoints that could support and inform active implementation of two new VHA programs. METHODS: The new Prospectively-Reported Implementation Update and Score ("PRIUS") provided a quick, structured, prospective and open-ended method for individuals to report on implementation progress. PRIUS updates were submitted approximately twice a month. Responding to the prompt "What are some things that happened over the past two weeks that seem relevant from your perspective to the implementation of this project?", individuals scored each update with a number ranging from + 3 to - 3. RESULTS: In 2016-17, individuals submitted over 600 PRIUS updates across the two QI projects. PRIUS-based findings included that staff from different services reported fundamentally different perspectives on program implementation. Rapid analysis and reporting of the PRIUS data led directly to changes in implementation. CONCLUSIONS: The PRIUS provided an efficient, structured method for developing a granular and context-sensitive account of implementation progress. The approach appears to be highly adaptable to a wide range of settings and interventions.Item Rural-Urban Differences in Inpatient Quality of Care in US Veterans With Ischemic Stroke(2014-06) Phipps, Michael S.; Jia, Huanguang; Chumbler, Neale R.; Li, Xinli; Castro, Jaime G; Myers, Jennifer; Williams, Linda S.; Bravata, Dawn M.Purpose Differences in stroke care quality for patients in rural and urban locations have been suggested, but whether differences exist across Veteran Administration Medical Centers (VAMCs) is unknown. This study examines whether rural-urban disparities exist in inpatient quality among veterans with acute ischemic stroke. Methods In this retrospective study, inpatient stroke care quality was assessed in a national sample of veterans with acute ischemic stroke using 14 quality indicators (QIs). Rural-Urban Commuting Areas codes defined each VAMC's rural-urban status. A hierarchical linear model assessed the rural-urban differences across the 14 QIs, adjusting for patient and facility characteristics, and clustering within VAMCs. Findings Among 128 VAMCs, 18 (14.1%) were classified as rural VAMCs and admitted 284 (7.3%) of the 3,889 ischemic stroke patients. Rural VAMCs had statistically significantly lower unadjusted rates on 6 QIs: Deep vein thrombosis (DVT) prophylaxis, antithrombotic at discharge, antithrombotic at day 2, lipid management, smoking cessation counseling, and National Institutes of Health Stroke Scale completion, but they had higher rates of stroke education, functional assessment, and fall risk assessment. After adjustment, differences in 2 QIs remained significant—patients treated in rural VAMCs were less likely to receive DVT prophylaxis, but more likely to have documented functional assessment. Conclusions After adjustment for key demographic, clinical, and facility-level characteristics, there does not appear to be a systematic difference in inpatient stroke quality between rural and urban VAMCs. Future research should seek to understand the few differences in care found that could serve as targets for future quality improvement interventions.Item The "State of Implementation" Progress Report (SIPREP): a pilot demonstration of a navigation system for implementation(BMC, 2020-11-05) Miech, Edward J.; Larkin, Angela; Lowery, Julie C.; Butler, Andrew J.; Pettey, Kristin M.; Rattray, Nicholas A.; Penney, Lauren S.; Myers, Jennifer; Damush, Teresa M.; Regenstrief Institute, IU School of MedicineBACKGROUND: Implementation of new clinical programs across diverse facilities in national healthcare systems like the Veterans Health Administration (VHA) can be extraordinarily complex. Implementation is a dynamic process, influenced heavily by local organizational context and the individual staff at each medical center. It is not always clear in the midst of implementation what issues are most important to whom or how to address them. In recognition of these challenges, implementation researchers within VHA developed a new systemic approach to map the implementation work required at different stages and provide ongoing, detailed, and nuanced feedback about implementation progress. METHODS: This observational pilot demonstration project details how a novel approach to monitoring implementation progress was applied across two different national VHA initiatives. Stage-specific grids organized the implementation work into columns, rows, and cells, identifying specific implementation activities at the site level to be completed along with who was responsible for completing each implementation activity. As implementation advanced, item-level checkboxes were crossed off and cells changed colors, offering a visual representation of implementation progress within and across sites across the various stages of implementation. RESULTS: Applied across two different national initiatives, the SIPREP provided a novel navigation system to guide and inform ongoing implementation within and across facilities. The SIPREP addressed different needs of different audiences, both described and explained how to implement the program, made ample use of visualizations, and revealed both what was happening and not happening within and across sites. The final SIPREP product spanned distinct stages of implementation. CONCLUSIONS: The SIPREP made the work of implementation explicit at the facility level (i.e., who does what, and when) and provided a new common way for all stakeholders to monitor implementation progress and to help keep implementation moving forward. This approach could be adapted to a wide range of settings and interventions and is planned to be integrated into the national deployment of two additional VHA initiatives within the next 12 months.