Veterans Affairs Patients Research Articles

Lack of differential impact of del17p on survival in African Americans compared with White patients with multiple myeloma: a VA study

Multiple myeloma (MM) is a heterogeneous disease that has an increased incidence in African Americans (AAs). We previously observed that, with equal access to health care, younger AA patients (age < 65 years) have superior overall survival (OS) compared with younger White patients. Because MM prognosis is influenced by 17p deletion (del17p), we investigated racial differences in its occurrence and impact in a large cohort of MM patients from the Veterans Affairs (VA) system. Among 2243 VA patients with MM for whom del17p data were available, del17p was present in 8.83% of all patients, with a significantly lower prevalence in AAs (5.56%) compared with Whites (10.52%; P < .001). The difference was even more pronounced among younger AAs (<65 years) vs younger Whites (4.34% vs 9.8%, respectively; P = .004). However, we did not observe any significant difference in survival between AA and White patients with del17p, regardless of age category, suggesting that del17p carries a poor prognosis across race and age. Interestingly, among patients without del17p, we still noted a significantly superior OS in younger AAs compared with younger Whites (7.75 vs 5.10 years; P = .042). Our study shows a lower incidence of del17p in AAs but suggests that the survival advantage for younger AAs is primarily due to factors other than del17p.

Provider and clinical setting characteristics associated with tobacco pharmacotherapy dispensed in the Veterans Health Administration.

INTRODUCTIONWhile initiation rates of tobacco cessation pharmacotherapy have improved both inside and outside the Department of Veteran Affairs (VA), prescribing rates remain low. The objective of this study was to examine correlation of the characteristics of providers, clinics, and facilities with initiation of tobacco cessation pharmacotherapy.METHODSThis retrospective, observational study used VA outpatient electronic medical record data from federal fiscal year 2011. Logistic regression models estimated the adjusted odds ratio associated with provider characteristics for pharmacotherapy initiation.RESULTSFor the 639507 veterans who used tobacco, there were 30388 providers caring for them. Younger (p<0.001) and female (p<0.001) providers were more likely to initiate tobacco cessation pharmacotherapy. Compared to physicians, pharmacists were 74% more likely to initiate pharmacotherapy, while all groups of nurses were 5–8% and physicians’ assistants were 12% less likely (p<0.001). Compared to those seen in primary care clinics, patients assessed in substance use treatment clinics were 16% more likely to have pharmacotherapy initiated (p<0.001), while those in psychiatry were 10% less likely (p<0.001), and those in outpatient surgery were 39% less likely to initiate pharmacotherapy (p<0.001). Compared to almost all other classes of VA facilities, patients seen in primary care community-based outpatient clinics (CBOCs) were 7–28% more likely to initiate pharmacotherapy (p<0.0001).CONCLUSIONSWhile the VA is at the leading edge of providing tobacco cessation pharmacotherapy, targeting quality improvement efforts towards providers, clinics, and facilities with low prescribing rates will be essential to continue the declining rates of tobacco use among VA patients.

Use and Toxicity of Checkpoint Inhibitors for Solid Tumor Treatment in a Veteran Population.

New immunotherapy agents have provided additional options for the treatment of a variety of malignancies, including the programmed death 1 (PD-1) protein inhibitors nivolumab and pembrolizumab. Initial dosing was based on patient weight, but subsequent studies supported fixed dosing, thereby prompting a change in US Food and Drug Administration-approved dosing. Depending on patient weight, one dosing strategy may be more cost-effective than another; thereby, a combination of dosing strategies may be beneficial for institutions. While these agents have been shown to be efficacious, they have been associated with immune-related adverse events (IrAEs). The purpose of this study was to determine the dosing strategy used and identify actual and potential cost savings, as well as to determine the incidence of hypothyroidism with PD-1 inhibitors in patients of the US Department of Veterans Affairs (VA). This was a retrospective chart review of VA patients who received a PD-1 inhibitor for the treatment of a solid tumor between January 2015 and July 2017. Data were collected from the VA Corporate Data Warehouse through the VA Informatics and Computing Infrastructure. The dosing strategy for a PD-1 inhibitor was categorized into weight-based vs fixed-dosing where possible and used to identify actual and potential cost-savings opportunities. Thyroid laboratory values and levothyroxine prescriptions were evaluated to determine the overall incidence of the prespecified IrAEs. Descriptive statistics were used for primary and secondary outcomes. Nivolumab was the primary PD-1 inhibitor used for solid tumor treatment. Both nivolumab and pembrolizumab were primarily dosed based on patient weight. Nivolumab orders resulted in $8,514,300 estimated actual cost savings with $5,591,250 estimated missed cost savings identified. Of the patients who received nivolumab, 3249 patients were evaluated for thyroid dysfunction; 514 (15.8%) developed primary hypothyroidism based on laboratory values and levothyroxine prescription data. Utilization of a combination of both weight-based and fixed-dosing strategies for nivolumab has the potential for cost savings, thereby benefiting the health care institution. The incidence of IrAEs identified among patients who received PD-1 inhibitor within the VA health care system was similar to the incidences reported in published literature. This further supports recommendations for close IrAE monitoring and treatment.

Use of Complementary and Alternative Therapy for Knee Osteoarthritis: Race and Gender Variations.

ObjectiveTo evaluate race and gender variations in complementary and alternative medicine (CAM) use for knee osteoarthritis (OA) (unadjusted and adjusted for demographic and clinical factors).MethodsA secondary analysis of cross‐sectional data was conducted. The sample included Veterans Affairs patients 50 years of age or older with symptomatic knee OA. Current use of various CAM therapies was assessed at baseline. Logistic regression models were used to compare race and gender differences in the use of specific CAMs.ResultsThe sample included 517 participants (52.2% identified as African American [AA]; 27.1% identified as female). After adjusting for demographic and clinical factors, AA participants, compared with white participants, were less likely to use joint supplements (odds ratio [OR]: 0.53; 95% confidence interval [CI], 0.31‐0.90]); yoga, tai chi, or pilates (OR: 0.39; 95% CI: 0.19‐0.77); and chiropractic care (OR: 0.51; 95% CI: 0.26‐1.00). However, they were more likely to participate in spiritual activities (OR: 2.02; 95% CI: 1.39‐2.94). Women, compared with men, were more likely to use herbs (OR: 2.42; 95% CI: 1.41‐4.14); yoga, tai chi, or pilates (OR: 2.09; 95% CI: 1.04‐4.19); acupuncture, acupressure, or massage (OR: 2.45; 95% CI: 1.28‐4.67); and spiritual activities (OR: 1.68; 95% CI: 1.09‐2.60). The interactive effects of race and gender were significant in the use of herbs (P = 0.008); yoga, tai chi, or pilates (P = 0.011); acupuncture, acupressure or massage (P = 0.038); and spiritual activities (P < 0.001).ConclusionThere are race and gender differences in the use of various CAMs for OA. As benefits and limitations of CAM therapies vary, clinicians must be aware of these differences.

Estimating the Cost of Surgical Care Purchased in the Community by the Veterans Health Administration.

Background. Veterans’ access to Veterans Affairs (VA)-purchased community care expanded due to large increases in funding provided in the 2014 Veterans Choice Act. Objectives. To compare costs between VA-delivered care and VA payments for purchased care for two commonly performed surgeries: total knee arthroplasties (TKAs) and cataract surgeries. Research Design. Descriptive statistics and regressions examining costs in VA-delivered and VA-purchased care (fiscal year [FY] 2018 [October 2017 to September 2018]). Subjects. A total of 13,718 TKAs, of which 6,293 (46%) were performed in VA. A total of 91,659 cataract surgeries, of which 65,799 (72%) were performed in VA. Measures. Costs of VA-delivered care based on activity-based cost estimates; costs of VA-purchased care based on approved and paid claims. Results. Ninety-eight percent of VA-delivered TKAs occurred in inpatient hospitals, with an average cost of $28,969 (SD $10,778). The majority (86%) of VA-purchased TKAs were also performed at inpatient hospitals, with an average payment of $13,339 (SD $23,698). VA-delivered cataract surgeries were performed at hospitals as outpatient procedures, with an average cost of $4,301 (SD $2,835). VA-purchased cataract surgeries performed at hospitals averaged $1,585 (SD $629); those performed at ambulatory surgical centers cost an average of $1,346 (SD $463). We also found significantly higher Nosos risk scores for patients who used VA-delivered versus VA-purchased care. Conclusions. Costs of VA-delivered care were higher than payments for VA-purchased care, but this partly reflects legislative caps limiting VA payments to community providers to Medicare amounts. Higher patient risk scores in the VA could indicate that community providers are reluctant to accept high-risk patients because of Medicare reimbursements, or that VA providers prefer to keep the more complex patients in VA.

Health care costs associated with primary care physicians versus nurse practitioners and physician assistants.

Significant primary care provider (PCP) shortage exists in the United States. Expanding the scope of practice for nurse practitioners (NPs) and physician assistants (PAs) can help alleviate this shortage. The Department of Veterans' Affairs (VA) has been a pioneer in expanding the role of NPs and PAs in primary caregiving. This study evaluated the health care costs associated with VA patients cared for by NPs and PAs versus primary care physicians (physicians). A retrospective data analysis using two separate cohorts of VA patients, one with diabetes and the other with cardiovascular disease (CVD), was performed. The associations between PCP type and health care costs were analyzed using ordinary least square regressions with logarithmically transformed costs. The analyses estimated 12% to 13% (US dollars [USD] 2,626) and 4% to 5% (USD 924) higher costs for patients assigned to physicians as compared with those assigned to NPs and PAs, after adjusting for baseline patient sociodemographics and disease burden, in the diabetes and CVD cohort, respectively. Given the average patient population size of a VA medical center, these cost differences amount to a total difference of USD 14 million/year per center and USD 5 million/year per center for diabetic and CVD patients, respectively. This study highlights the potential cost savings associated with primary caregiving by NPs and PAs. In light of the PCP shortage, the study supports increased involvement of NPs and PAs in primary caregiving. Future studies examining the reasons for these cost differences by provider type are required to provide more scientific evidence for regulatory decision making in this area.

Improvements to PTSD quality metrics with natural language processing.

As quality measurement becomes increasingly reliant on the availability of structured electronic medical record (EMR) data, clinicians are asked to perform documentation using tools that facilitate data capture. These tools may not be available, feasible, or acceptable in all clinical scenarios. Alternative methods of assessment, including natural language processing (NLP) of clinical notes, may improve the completeness of quality measurement in real-world practice. Our objective was to measure the quality of care for a set of evidence-based practices using structured EMR data alone, and then supplement those measures with additional data derived from NLP. As a case example, we studied the quality of care for posttraumatic stress disorder (PTSD) in the United States Department of Veterans Affairs (VA) over a 20-year period. We measured two aspects of PTSD care, including delivery of evidence-based psychotherapy (EBP) and associated use of measurement-based care (MBC), using structured EMR data. We then recalculated these measures using additional data derived from NLP of clinical note text. There were 2 098 389 VA patients with a diagnosis of PTSD between 2000 and 2019, 72% (n=1 515 345) of whom had not previously received EBP for PTSD and were treated after a 2015 mandate to document EBP using templates that generate structured EMR data. Using structured EMR data, we determined that 3.2% (n=48 004) of those patients met our EBP for PTSD quality standard between 2015 and 2019, and 48.1% (n=23 088) received associated MBC. With the addition of NLP-derived data, estimates increased to 4.1% (n=62 789) and 58.0% (n=36 435), respectively. Healthcare quality data can be significantly improved by supplementing structured EMR data with NLP-derived data. By using NLP, health systems may be able to fill the gaps in documentation when structured tools are not yet available or there are barriers to using them in clinical practice.

Use of Video Telehealth Tablets to Increase Access for Veterans Experiencing Homelessness.

BackgroundVeterans experiencing homelessness face substantial barriers to accessing health and social services. In 2016, the Veterans Affairs (VA) healthcare system launched a unique program to distribute video-enabled tablets to Veterans with access barriers.ObjectiveEvaluate the use of VA-issued video telehealth tablets among Veterans experiencing homelessness in the VA system.DesignGuided by the RE-AIM framework, we first evaluated the adoption of tablets among Veterans experiencing homelessness and housed Veterans. We then analyzed health record and tablet utilization data to compare characteristics of both subpopulations, and used multivariable logistic regression to identify factors associated with tablet use among Veterans experiencing homelessness.PatientsIn total, 12,148 VA patients receiving tablets between October 2017 and March 2019, focusing on the 1470 VA Veterans experiencing homelessness receiving tablets (12.1%).Main MeasuresTablet use within 6 months of receipt for mental health, primary or specialty care.Key ResultsNearly half (45.9%) of Veterans experiencing homelessness who received a tablet had a video visit within 6 months of receipt, most frequently for telemental health. Tablet use was more common among Veterans experiencing homelessness who were younger (AOR = 2.77; P <.001); middle-aged (AOR = 2.28; P <.001); in rural settings (AOR = 1.46; P =.005); and those with post-traumatic stress disorder (AOR = 1.64; P <.001), and less common among those who were Black (AOR = 0.43; P <.001) and those with a substance use disorder (AOR = 0.59; P <.001) or persistent housing instability (AOR = 0.75; P = .023).ConclusionsTelehealth care and connection for vulnerable populations are particularly salient during the COVID-19 pandemic but also beyond. VA’s distribution of video telehealth tablets offers healthcare access to Veterans experiencing homelessness; however, barriers remain for subpopulations. Tailored training and support for these patients may be needed to optimize telehealth tablet use and effectiveness.

Cancer specialists in the VA as early adopters of clinical genetic services.

11029 Background: Genetic testing has become essential to delivery of cancer treatment, risk assessment, surveillance, and prevention. We sought to understand the use of genetic tests by clinicians in the Department of Veterans Affairs (VA). Methods: We administered a web-based survey to clinicians at 20 VA facilities with precision oncology programs. We excluded respondents if they were: not at one of the 20 VA facilities; not seeing patients in VA; not a physician, nurse practitioner (NP), physician assistant (PA), or pharmacist; a medical geneticist or specialty was not reported; or if the survey was incomplete. Using multiple logistic regression, we assessed the association between genetic test ordering, genetics referral, and clinician characteristics. Results: There were 909 (909/11,442, 8%) eligible respondents with 61% women and 64% under age 55. There were 571 physicians (63%), 200 NPs (22%), 93 pharmacists (10%), and 45 PAs 5(%). There were 361 (40%) primary care providers (PCPs), 90 (10%) cancer specialists, and 458 (50%) non-cancer specialists. Only 21% of clinicians reported feeling prepared to use genetic tests in their practice. In the past year, only 8% had ordered at least one multi-gene cancer test (germline, tumor or both), 12% a pharmacogenetic test, and 0.2%, an exome. Compared to physicians, NPs were 60% less likely (OR = 0.42, 0.23-0.77, p = 0.005), pharmacists, 80% less likely (OR = 0.22, 0.08-0.62, p = 0.005), and PAs, 90% less likely (OR = 0.08, 0.01-0.58, p = 0.01) to have ordered a genetic test. Compared to PCPs, cancer specialists were almost 5 times more likely to order a genetic test (OR = 4.74, 2.57-8.73, p &lt; 0.0001); there was no difference in genetic test ordering between PCPs and non-cancer specialists. Among clinicians (n = 72) who had ordered cancer genetic tests, only about two-thirds were confident in knowing the indications for testing; discussing the potential benefits, harms and limitations of testing; understanding the test report; and knowing implications of results on disease management and prevention. Clinicians (n = 106) who had ordered pharmacogenetic tests had lower frequencies of confidence in these tasks. About half (52%) of the cancer specialists had referred patients to genetics in the past year; they were 1.8 times more likely than PCPs to refer (OR = 1.82, 1.10-3.03, p = 0.02), and non-cancer specialists were about 50% less likely than PCPs to refer (OR = 0.46, 0.33-0.64, p &lt; 0.0001). Conclusions: In the VA, cancer specialists are integrating genetic testing and genetics referral into their practice more than PCPs and other specialists. However, genetic testing is underutilized, and many clinicians remain unprepared to use genetic tests in their practice. These results will inform workforce planning, clinician education, and development of clinical decision support to facilitate genetic risk assessment, informed consent, and ordering of genetic tests.

Outcomes that Matter: High-Needs Patients' and Primary Care Leaders' Perspectives on an Intensive Primary Care Pilot.

Quantitative evaluations of the effectiveness of intensive primary care (IPC) programs for high-needs patients have yielded mixed results for improving healthcare utilization, cost, and mortality. However, IPC programs may provide other value. To understand the perspectives of high-needs patients and primary care facility leaders on the effects of a Veterans Affairs (VA) IPC program on patients. A total of 66 semi-structured telephone interviews with high-needs VA patients and primary care facility leaders were conducted as part of the IPC program evaluation. High-needs patients (n = 51) and primary care facility leaders (n = 15) at 5 VA pilot sites. We used content analysis to examine interview transcripts for both a priori and emergent themes about perceived IPC program effects. Patients enrolled in VA IPCs reported improvements in their experience of VA care (e.g., patient-provider relationship, access to their team). Both patients and leaders reported improvements in patient motivation to engage with self-care and with their IPC team, and behaviors, especially diet, exercise, and medication management. Patients also perceived improvements in health and described receiving assistance with social needs. Despite this, patients and leaders also outlined patient health characteristics and contextual factors (e.g., chronic health conditions, housing insecurity) that may have limited the effectiveness of the program on healthcare cost and utilization. Patients and primary care facility leaders report benefits for high-needs patients from IPC interventions that translated into perceived improvements in healthcare, health behaviors, and physical and mental health status. Most program evaluations focus on cost and utilization, which may be less amenable to change given this cohort's numerous comorbid health conditions and complex social circumstances. Future IPC program evaluations should additionally examine IPC's effects on quality of care, patient satisfaction, quality of life, and patient health behaviors other than utilization (e.g., engagement, self-efficacy).

Surgical Timing for Carpal Tunnel Syndrome: A Comparison of Health Care Delivery in the Veterans Administration and Private Sector

The U.S. Department of Veterans Affairs (VA) health care system monitors time from referral to specialist visit. We compared wait times for carpal tunnel release (CTR) at a VA hospital and its academic affiliate. We selected patients who underwent CTR at a VA hospital and its academic affiliate (AA) (2010-2015). We analyzed time from primary care physician (PCP) referral to CTR, which was subdivided into PCP referral to surgical consultation and surgical consultation to CTR. Electrodiagnostic testing (EDS) was categorized in relation to surgical consultation (prereferral vs postreferral). Multivariable Cox proportional hazard models were used to examine associations between clinical variables and surgical location. Between 2010 and 2015, VA patients had a shorter median time from PCP referral to CTR (VA: 168 days; AA: 410 days), shorter time from PCP referral to surgical consultation (VA: 43 days; AA: 191 days), but longer time from surgical consultation to CTR (VA: 98 days; AA: 55 days). Using multivariable models, the VA was associated with a 35% shorter time to CTR (AA hazard ratio [HR], 0.65; 95% confidence interval [CI], 0.52-0.82) and 75% shorter time to surgical consultation (AA HR, 0.25; 95% CI, 0.20-0.03). Receiving both prereferral and postreferral EDS was associated with almost a 2-fold prolonged time to CTR (AA HR, 0.49; 95% CI, 0.36-0.67). The VA was associated with shorter overall time to CTR compared with its AA. However, the VA policy of prioritizing time from referral to surgical consultation may not optimally incentivize time to surgery. Repeat EDS was associated with longer wait times in both systems. Given differences in where delays occur in each health care system, initiatives to improve efficiency will require targeting the appropriate sources of preoperative delay. Judicious use of EDS may be one avenue to decrease wait times in both systems.

Opioid Management in Older Adults: Lessons Learned From a Geriatric Patient-Centered Medical Home.

The United States continues to confront an opioid crisis that also affects older adults. Best practices for prescription opioid management in older adults are challenging to implement in this population. We present our experience with a 1-year management of 48 high-risk older patients who received guideline-based best practices for chronic prescription opioid therapy at a US Department of Veterans Affairs (VA) patient aligned care team (PACT) patient-centered medical home. The GeriPACT population at the Nashville Campus of the VA Tennessee Valley Healthcare System has an enrollment of 745 patients of whom 48 (6.5%) receive chronic prescription opioid therapy. The practice is supported by the VA Computerized Patients Record System, including the electronic patient portal, My healtheVet, and telemedicine capabilities. Data were collected by chart review and operations data. The mean (range) age of patients was 70.4 (66-93) years. Many patients had comorbid conditions, such as diabetes mellitus (35%), congestive heart failure (18.6%), and dementia (8.3%). More than half had an estimated glomerular filtration rates (eGFR) < 60 mL/min, indicating at least stage 3 chronic kidney disease, 41.7% used mental health services (41.7%), and 20.8% had a history of opioid use disorder. Most indications for chronic pain were for musculoskeletal pain (95.8%). The mean (range) morphine equivalent daily dose was 37 mg (10-109). More than half had been seen in the emergency department, and 20.8% had been hospitalized in the previous year for an opioid-related hospitalization, and 3% had expired. Over the year, dose reductions of benzodiazepines or narcotics was performed for 12.5% of patients, accidental overdoses occurred in 4.2%, and positive urine drug screens (UDSs) for cocaine and cannabinoid/tetrahydrocannabinol occurred in 10.4%. One patient was terminated from the program for multiple positive UDSs. Guideline-based patient-centered medical home management of patients with chronic pain who were treated with opioids can be an effective model contributing to the health and well-being of older patients. Complex older patients on chronic opioid treatment are best managed by an interdisciplinary team.

Procedural Safety Profile of Cardiomems Heart Failure Sensor Implantation in a Veterans Association Patient Population

<h3>Purpose</h3> Implantation of a wireless pulmonary artery pressure monitoring device [CardioMEMS] has been shown to reduce heart failure hospitalization but safety profile and peri-procedural complications have not been well described in real world practice in a Veterans Affairs (VA) patient population. <h3>Methods</h3> Electronic medical records of our single VA institution were retrospectively evaluated for device implantation procedure data and follow up clinic visits between 2017 and 2020. <h3>Results</h3> 63 patients with NYHA Class 3 heart failure were implanted with the device (Table 1A). Average procedure time was 48 minutes with average fluoroscopy time of 13 minutes. Average total volume of contrast used was 23 mL. Estimated blood loss was 10 mL. At device implantation, average right atrial mean pressures were 11 mmHg and pulmonary artery systolic, diastolic, and mean pressures were 51/24/34 mmHg. There were three peri-procedural complications. One patient developed an access related pseudoaneurysm successfully treated with surgical intervention. One patient developed a 2 cm hematoma at the access site managed conservatively. One patient developed proximal sensor migration following device deployment which was re-advanced using a Swan wedge balloon catheter and position was confirmed with chest radiograph and proper waveform analysis on device interrogation. All implants were successful and no patients were lost to follow up at clinic visits. There were no major adverse cardiovascular events (stroke, myocardial infarction and cardiovascular death) in hospital or at 30-day follow up. Procedural complications are summarized in Table 1B as compared to previously published data in the CHAMPION Trial. <h3>Conclusion</h3> This real world study demonstrates that the safety profile of pulmonary artery pressure monitoring device implantation in a single VA healthcare center serving a VA patient population is a feasible and safe management approach to patients with NYHA Class 3 heart failure.

62541 Continuity of Care for Patients with Chronic Gastrointestinal Disease: A Latent Class Analysis of Patients With High-Intensity Specialty Care Needs

ABSTRACT IMPACT: Grouping patients with potentially high intensity specialty care needs based on their propensity for healthcare continuity patterns can inform the development of personalized care coordination and care navigation interventions OBJECTIVES/GOALS: To examine variation in healthcare continuity patterns across primary care, mental health care, and specialty care for a patient population with chronic gastrointestinal conditions and a high risk for healthcare utilization. METHODS/STUDY POPULATION: We analyzed data for Veterans Affairs patients with chronic gastrointestinal disease (cirrhosis, inflammatory bowel disease, chronic pancreatitis) whose 1-year hospitalization risk was ≥90th percentile in 2014, and who had a minimum of 4 office visits. To assess continuity, we examined frequency of office visits, number of outpatient providers, and two established continuity of care measures (the usual provider of care index and the Bice-Boxerman continuity of care index) over 12 months. We used latent class analysis to categorize patients into classes based on overall, primary care (PCP)-specific, gastroenterology (GI)-specific, and mental health specific-healthcare continuity patterns. RESULTS/ANTICIPATED RESULTS: The 26,751 Veterans in the analytic cohort had a mean of 13.3 (sd 8.63) office visits and 7.2 (sd 3.83) providers per patient. Patients were classified into five phenotypes: (1) moderate overall use and continuity; (2) low overall continuity of care; (3) high GI- and PCP-specific continuity of care; (4) low overall continuity of care with some mental health use; and (5) high utilization with substantial mental health use. In the subsequent year, 11,259 (42.1%) patients had a hospitalization and 16,167 (60.4%) had an emergency department visit. These groups varied in their sociodemographic and clinical characteristics, and in their risk for hospitalization and emergency department use. DISCUSSION/SIGNIFICANCE OF FINDINGS: Latent class analysis revealed five distinct primary and specialty care utilization patterns. Grouping patients with high intensity specialty care needs based on their propensity for healthcare continuity patterns can inform the development of personalized care navigation interventions.

846. Trends in Acinetobacter baumanii Antibiotic Resistance Rates

BackgroundCarbapenem-resistant Acinetobacter baumannii is described as an urgent threat by the Centers for Disease Control and Prevention and several older studies have indicated increasing resistance in Acinetobacter. We sought to describe these trends in the national Veterans Affairs (VA) Healthcare System.MethodsWe assessed A. baumannii positive clinical cultures collected from VA patients (> 18 years) from 2010 to 2018. We categorized cultures based on location at the time of collection: VA medical center (VAMC), community living center (CLC), or outpatient (Outpt). Multidrug resistance (MDR) and extensive drug resistance (XDR) were defined as resistance to > 1 drug in > 3 or all of the following categories, respectively: extended-spectrum cephalosporins (es-CS), fluoroquinolones (FQ), aminoglycosides (AMG), carbapenems (CARB), piperacillin/tazobactam (PIP/TAZ), and ampicillin/sulbactam (AMP/SUL). Joinpoint Software was used for regression analyses of trends over time and to estimate annual average percent changes (AAPC) with 95% confidence intervals.ResultsWe identified 19,376 A. baumannii positive cultures over the study period (53% VAMCs, 4% CLCs, 43% Outpts), which represented 0.5% of all positive cultures in the VA. In VAMCs, the number of A. baumannii cultures decreased significantly by 12.5% per year. Of all positive cultures in VAMCs, the proportion that were A. baumannii decreased significantly by 5.4% per year. Similar trends were observed in CLCs, while Outpt cultures remained stable. Over the 9-year study period, resistance decreased significantly, with MDR decreasing by 10.2% per year and XDR decreasing by 9.4%. Carbapenem resistance decreased significantly by 4.9% per year in VAMCs (2010, 39%; 2018 28%) and 11.3% in Outpts (2010, 12%; 2018, 6%). Similar annual significant decreases were observed with AMG (9.4%), es-CS (1.4%), and FQ (7.4%) in VAMCs; es-CS (2.7%) and FQ (5.6%) in CLCs; and AMG (9.5%) and FQ (8.2%) in Outpts.ConclusionIn the national VA Healthcare System, the prevalence of A. baumannii is decreasing, as is the resistance previously observed with this organism. MDR A. baumannii still made up one-third of cultures in VAMCs and CLCs in 2018, and thus remains a treatment challenge.Disclosures Aisling Caffrey, PhD, Merck (Research Grant or Support)Pfizer (Research Grant or Support)Shionogi (Research Grant or Support) Haley J. Appaneal, Pharm.D, Shionogi, Inc. (Research Grant or Support) Kerry LaPlante, PharmD, Merck (Advisor or Review Panel member, Research Grant or Support)Ocean Spray Cranberries, Inc. (Research Grant or Support)Pfizer Pharmaceuticals (Research Grant or Support)Shionogi, Inc. (Research Grant or Support)

Factors Related to Prescription Drug Monitoring Program Queries for Veterans Receiving Long-Term Opioid Therapy.

State prescription drug monitoring programs (PDMPs) identify controlled medications dispensed across providers and systems. Department of Veterans Affairs (VA) policy requires electronic health record documentation of PDMP queries at least annually for VA patients receiving controlled medications; however, queries are not uniformly conducted. We examined factors associated with PDMP queries for veterans receiving long-term opioid therapy. Veterans with a VA provider who received long-term opioid therapy between August 2015 and August 2016 within a four-state region were identified; 9,879 were due for a PDMP query between August 2016 and February 2017. Likelihood of veterans' PDMP queries during this follow-up period was modeled as a function of patient, provider, and facility characteristics of interest in mixed-effects modified Poisson models estimating relative risk and 95% confidence intervals. Multivariable models controlled for potential confounders identified through the use of directed acyclic graphs. PDMP queries were documented for 62.1% of veterans that were due for a PDMP query. Veterans were more likely to be queried if they were Hispanic or if they received methadone, had average daily milligram morphine equivalents >20, or received urine drug screening during the studied period. Veterans were less likely to be queried if they had a rural address, mail order medication, or cancer diagnosis. Likelihood of PDMP queries was also lower for veterans whose opioid-prescribing provider was an oncologist or working in a low-complexity facility. Adherence to PDMP query policy within the VA varied by patient, clinician, and facility factors. Mechanisms to standardize the conduct of PDMP queries may be needed.

Predicting Life Expectancy Using Veterans Affairs Electronic Health Record Data

Electronic health records (EHRs) are a rich source of health data that could be used to create individualized life expectancy predictions to aid in clinical decision-making for long-term preventative treatments, such as cancer screening. Few previous studies have incorporated all possible predictors from the EHR. We aimed to screen and incorporate a large number of possible predictors from EHR data into a life expectancy (LE) prediction equation. Using the national Veteran’s Affairs (VA) EHR databases, we identified all patients aged 50+ with a primary care visit during 2005 and assessed demographics, diseases, medications, laboratory results, healthcare utilization, and vital signs during the one year prior to the visit. Mortality follow-up was complete through 2017. We used an 80% random sample for model development and a 20% random sample for model validation. We used a Gompertz survival model with backwards selection to identify approximately 100 variables for the final LE prediction equation. In 1,263,595 VA patients, the mean age was 68 years and the majority were male (94%) and white (87%). During 12 years of follow-up, 602,576 (47.7%) died. Of 930 predictors from the EHR, 99 were included in the LE prediction equation. Harrell’s C-statistic was 0.7705 (95%CI: 0.7693, 0.7718). The model estimated 10-year life expectancy with sensitivity of 81.6% (81.4%, 81.8%) and specificity of 68.8% (68.5%, 69.1%). In conclusion, we developed an LE prediction equation from hundreds of predictors in the VA EHR with good discrimination and calibration that may help clinicians weigh the potential benefit of long-term preventative treatments.

Screening is associated with a lower risk of hepatocellular carcinoma-related mortality in patients with chronic hepatitis B

Patients with chronic hepatitis B (CHB) infection routinely undergo screening for hepatocellular carcinoma (HCC), but the efficacy of screening remains unclear. We aimed to evaluate the impact of screening with ultrasound and/or serum alpha-fetoprotein (AFP) on HCC-related mortality in patients with CHB. We performed a matched case-control study of patients with CHB receiving care through the Veterans Affairs (VA) health administration. Cases were patients who died of HCC between 01/01/2004 and 12/31/2017, while controls were patients with CHB who did not die of HCC. Cases were matched to controls by CHB diagnosis date, age, sex, race/ethnicity, cirrhosis, antiviral therapy exposure, hepatitis B e antigen status, and viral load. We identified screening ultrasound and AFPs obtained in the 4 years preceding HCC diagnosis in cases and the equivalent index date in controls. Using conditional logistic regression, we compared cases and controls with respect to receipt of screening. A lower likelihood of screening in cases corresponds to an association between screening and reduced risk of HCC-related mortality. We identified 169 cases, matched to 169 controls. Fewer cases than controls underwent screening with either screening modality (33.7% vs. 58.6%) or both modalities (19.5% vs. 34.4%). In multivariable conditional logistic regression, screening with either modality was associated with a lower risk of HCC-related mortality (adjusted odds ratio [aOR] 0.21, 95% CI 0.09-0.50), as was screening with both modalities (aOR of 0.13; 95% CI 0.04-0.43). HCC screening was associated with a substantial reduction in HCC-related mortality in VA patients with CHB. Patients with hepatitis B infection have a high risk of developing liver cancer. It is therefore recommended that they undergo frequent screening for liver cancer, but whether this leads to a lower risk of dying from liver cancer is not clear. In this study, we show that liver cancer screening is associated with a reduction in the mortality from liver cancer in patients with hepatitis B infection.

Impact of Differences in Time from Diagnosis to Treatment on DLBCL Response and Survival Outcomes: A VA Study

Introduction With an incidence of 5.6 per 100,000 per year, diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (Teras, 2016) and has a 5-year relative survival of 63.8% (SEER Statistics, 2018). While there is not currently a universally accepted timeline for initiation of therapy in DLBCL, retrospective studies have demonstrated that delays in initiation of treatment can lead to adverse outcomes in DLBCL, such as decreased overall survival (Phipps, 2018). We performed a retrospective review of Veterans Affairs (VA) patients nationwide to assess how frequently delays occurred in treatment initiation and we analyzed the impact of time to treatment on response rates to first-line chemotherapy and on survival outcomes. Methods We performed a retrospective chart review of 2036 randomly selected records of patients seen within the VA nationwide who were diagnosed with lymphoma between 1/1/2011 and 12/31/2017. We included patients diagnosed with DLBCL. We excluded other types of lymphoma, patients whose workup and treatment were outside of the VA system, and patients with primary central nervous system (CNS) lymphoma. We determined the time from diagnosis to treatment (TDT), defined as the number of days from the date of pathology results to the date of initiation of treatment for each patient, and divided these into two-week blocks. The Wilcoxon-Mann-Whitney test was used to compare median overall survival between the groups. Results 971 patients were included in the study. Patients were predominantly male (96.2%), with a median age of 67 (Table 1). The median TDT was 20 days. Those with TDT of 0-14 days, 15-28 days, 29-42 days, and 43+ days had an objective response rate (ORR) of 70.9%, 84.5%, 82.9%, and 77.6%, respectively (Table 2). The same groups had a 2-year overall survival (OS) rate of 61.6%, 77.6%, 80.7%, and 72.7%, respectively. They demonstrated median OS of 36.1 months, 46.9 months, 46.4 months, and 47.1 months, respectively. The 2-year OS rates were significantly lower for the 0-14 day group compared to the 15-28 days group (P = 0.0001), 29-42 group (P &amp;lt;0.0001), and 43+ days (P = 0.020). The ORR and median overall survival were also significantly lower in the 0-14 day group compared to the other TDT subgroups. Although the rates of high International Prognostic Index (IPI) scores and advanced stage disease were highest in the 0-14 day groups, we found that when we assessed only the patients with IPI 3-5, the 2-year OS rates, ORR, and median OS trends were similar, with inferior outcomes in the earlier treatment initiation groups (Table 3). When we analyzed only the patients with stage III-IV disease, as well as only those who were outpatient at time of diagnosis, we again found similar trends of inferior outcomes in those who began treatment within 0-14 days. The Cox proportional hazards model was employed to explore factors associated with survival time (Figure 1). An increase in age, a higher IPI score, and being an inpatient at the time of diagnosis were statistically significant factors that explained a lower OS in the 0-14 day TDT subgroup. When these were included in the model, TDT no longer made a significant difference in OS. Conclusion Our study demonstrated that shorter TDT did not improve survival outcomes for this aggressive lymphoma, contrary to what we expected. In fact, patients who had shorter TDT had statistically significant lower survival rates at 2 years, lower median OS, and lower ORR. We theorized that there was a propensity for patients who have more high-risk disease to be started on treatment more quickly because they are more often symptomatic or gravely ill at presentation. We found that when we controlled for inpatient status, high IPI, and advanced stage disease individually, the survival outcomes remained poorest in the earliest treatment initiation groups. However, when we controlled for all of these variables, there was no longer a statistically significant difference in OS based on TDT. Future studies are needed to better understand why our outcomes differed from prior studies which showed improved survival and response in shorter TDT subgroups, and to control for other possible confounders, such as treatment regimens and patients' comorbid conditions. Disclosures No relevant conflicts of interest to declare.

Patient-Reported Social and Behavioral Determinants of Health and Estimated Risk of Hospitalization in High-Risk Veterans Affairs Patients

Despite recognition of the association between individual social and behavioral determinants of health (SDH) and patient outcomes, little is known regarding the value of SDH in explaining variation in outcomes for high-risk patients. To describe SDH factors among veterans who are at high risk for hospitalization, and to determine whether adding patient-reported SDH measures to electronic health record (EHR) measures improves estimation of 90-day and 180-day all-cause hospital admission. A survey was mailed between April 16 and June 29, 2018, to a nationally representative sample of 10 000 Veterans Affairs (VA) patients whose 1-year risk of hospitalization or death was in the 75th percentile or higher based on a VA EHR-derived risk score. The survey included multiple SDH measures, such as resilience, social support, health literacy, smoking status, transportation barriers, and recent life stressors. The EHR-based characteristics of survey respondents and nonrespondents were compared using standardized differences. Estimation of 90-day and 180-day hospital admission risk was assessed for 3 logistic regression models: (1) a base model of all prespecified EHR-based covariates, (2) a restricted model of EHR-based covariates chosen via forward selection based on minimizing Akaike information criterion (AIC), and (3) a model of EHR- and survey-based covariates chosen via forward selection based on AIC minimization. In total, 4685 individuals (response rate 46.9%) responded to the survey. Respondents were comparable to nonrespondents in most characteristics, but survey respondents were older (eg, >80 years old, 881 [18.8%] vs 800 [15.1%]), comprised a higher percentage of men (4391 [93.7%] vs 4794 [90.2%]), and were composed of more White non-Hispanic individuals (3366 [71.8%] vs 3259 [61.3%]). Based on AIC, the regression model with survey-based covariates and EHR-based covariates better estimated hospital admission at 90 days (AIC, 1947.7) and 180 days (AIC, 2951.9) than restricted models with only EHR-based covariates (AIC, 1980.2 at 90 days; AIC, 2981.9 at 180 days). This result was due to inclusion of self-reported measures such as marital or partner status, health-related locus of control, resilience, smoking status, health literacy, and medication insecurity. Augmenting EHR data with patient-reported social information improved estimation of 90-day and 180-day hospitalization risk, highlighting specific SDH factors that might identify individuals who are at high risk for hospitalization.