Leveraging Electronic Health Records to Assess Residential Mobility Among Veterans in the Veterans Health Administration.

BACKGROUND: Residential mobility, or a change in residence, can influence health care utilization and outcomes. Health systems can leverage their patients' residential addresses stored in their electronic health records (EHRs) to better understand the relationships among patients' residences, mobility, and health. The Veteran Health Administration (VHA), with a unique nationwide network of health care systems and integrated EHR, holds greater potential for examining these relationships. METHODS: We conducted a cross-sectional analysis to examine the association of sociodemographics, clinical conditions, and residential mobility. We defined residential mobility by the number of VHA EHR residential addresses identified for each patient in a 1-year period (1/1-12/31/2018), with 2 different addresses indicating one move. We used generalized logistic regression to model the relationship between a priori selected correlates and residential mobility as a multinomial outcome (0, 1, ≥2 moves). RESULTS: In our sample, 84.4% (n=3,803,475) veterans had no move, 13.0% (n=587,765) had 1 move, and 2.6% (n=117,680) had ≥2 moves. In the multivariable analyses, women had greater odds of moving [aOR=1.11 (95% CI: 1.10,1.12) 1 move; 1.27 (1.25,1.30) ≥2 moves] than men. Veterans with substance use disorders also had greater odds of moving [aOR=1.26 (1.24,1.28) 1 move; 1.77 (1.72,1.81) ≥2 moves]. DISCUSSION: Our study suggests about 16% of veterans seen at VHA had at least 1 residential move in 2018. VHA data can be a resource to examine relationships between place, residential mobility, and health.

Ten Years of Bipolar Telehealth: Program Evaluation of a Team-Based Telemental Health Clinic.

Objectives: Telemental health via videoconferencing (TMH-V) can overcome many of the barriers to accessing quality mental health care. Toward this end, in 2011, the U.S. Department of Veterans Affairs (VA) established the National Bipolar Disorders TeleHealth (BDTH) Program to provide expert mental health consultation and treatment to Veterans with bipolar spectrum disorders. Methods: Initial analyses of BDTH services suggested that participants had positive changes in quality-of-care indices and clinical outcomes; however, that evaluation was based on a limited sample of both participants and VA medical centers. We were able to confirm and expand upon those early results by using nearly eight times the number of participants and more than twice as many medical centers. Results: For the 2,456 Veterans who completed the intake to our program, there were significant improvements in some of the quality metrics (e.g., lithium use) and a 54% reduction in positive suicide screens (p < 0.05). The Veterans who completed the initial and postprogram assessments (n = 815) reported a 16.6% reduction in manic symptoms (p < 0.001), a 29.3% reduction in depressive symptoms (p < 0.001), and a 21.2% reduction in mood episodes (p < 0.001). Additionally, these Veterans demonstrated significant improvements (p < 0.001) in mental health-related quality of life between the two assessments. Conclusions: These analyses provide further support for the general effectiveness and safety of telemental health via videoconferencing. Future research should examine the generalizability of these findings across various subgroups (e.g., minority patients, patients in rural areas), populations, and health care systems.

The Good, The Bad, The Uncertain: Diverse Provider Experiences with Telemental Health During COVID-19.

This study assessed mental health provider attitudes and perceptions of telemental health (TMH) prior to and during the COVID-19 Pandemic. The study expands on earlier work by providing a more detailed qualitative analysis of provider perceptions of TMH, including its efficacy, advantages, and limitations. The current study is part of a larger mixed methods project utilizing a repeated cross-sectional design. An online survey was administered to a sample of 1,448 mental health providers. Of the survey participants, 934 offered narrative responses to open-ended questions and were included in the present study. Qualitative data was analyzed using a coding team and the Consensual Qualitative Research paradigm. Providers described both positive and negative feelings about using TMH during the COVID-19 Pandemic. Several advantages were identified, with providers clearly appreciating the role of TMH in allowing them to work continuously and safely during the public health emergency. An array of negative views and concerns were also expressed, including that TMH may not be optimal or effective in certain settings or situations. A portion of respondents also indicated a preference for face-to-face care and illuminated ways they found TMH lacking or limited.

Use of Proton Pump Inhibitors Increases Risk of Incident Kidney Stones.

BACKGROUND AND AIMS: Proton pump inhibitors (PPIs) are widely prescribed and have effects on gut ion absorption and urinary ion concentrations. PPIs might therefore protect against or contribute to development of kidney stones. We investigated the association between PPI use and kidney stones. METHODS: We performed a retrospective study using data from the Women's Veteran's Cohort Study, which comprised men and women, from October 1, 1999 through September 30, 2017. We collected data from 465,891 patients on PPI usage over time, demographics, laboratory results, comorbidities, and medication usage. Time-varying Cox proportional hazards and propensity matching analyses determined risk of PPI use and incident development of kidney stones. Use of histamine-2 receptor antagonists (H2RAs) was measured and levothyroxine use was a negative control exposure. RESULTS: PPI use was associated with kidney stones in the unadjusted analysis, with PPI use as a time-varying variable (hazard ratio [HR], 1.74; 95% CI, 1.67-1.82), and persisted in the adjusted analysis (HR, 1.46; CI, 1.38-1.55). The association was maintained in a propensity score-matched subset of PPI users and nonusers (adjusted HR, 1.25; CI 1.19-1.33). Increased dosage of PPI was associated with increased risk of kidney stones (HR, 1.11; CI, 1.09-1.14 for each increase in 30 defined daily doses over a 3-month period). H2RAs were also associated with increased risk (adjusted HR, 1.47; CI 1.31-1.64). We found no association, in adjusted analysis, of levothyroxine use with kidney stones (adjusted HR, 1.06; CI 0.94-1.21). CONCLUSIONS: In a large cohort study of veterans, we found PPI use to be associated with a dose-dependent increase in risk of kidney stones. H2RA use also has an association with risk of kidney stones, so acid suppression might be an involved mechanism. The effect is small and should not change prescribing for most patients.

Validity of Incident Opioid Use Disorder (OUD) Diagnoses in Administrative Data: a Chart Verification Study.

BACKGROUND: An important strategy to address the opioid overdose epidemic involves identifying people at elevated risk of overdose, particularly those with opioid use disorder (OUD). However, it is unclear to what degree OUD diagnoses in administrative data are inaccurate. OBJECTIVE: To estimate the prevalence of inaccurate diagnoses of OUD among patients with incident OUD diagnoses. SUBJECTS: A random sample of 90 patients with incident OUD diagnoses associated with an index in-person encounter between October 1, 2016, and June 1, 2018, in three Veterans Health Administration medical centers. DESIGN: Direct chart review of all encounter notes, referrals, prescriptions, and laboratory values within a 120-day window before and after the index encounter. Using all available chart data, we determined whether the diagnosis of OUD was likely accurate, likely inaccurate, or of indeterminate accuracy. We then performed a bivariate analysis to assess demographic or clinical characteristics associated with likely inaccurate diagnoses. KEY RESULTS: We identified 1337 veterans with incident OUD diagnoses. In the chart verification subsample, we assessed 26 (29%) OUD diagnoses as likely inaccurate; 20 due to systems error and 6 due to clinical error; additionally, 8 had insufficient information to determine accuracy. Veterans with likely inaccurate diagnoses were more likely to be younger and prescribed opioids for pain. Clinical settings associated with likely inaccurate diagnoses were non-mental health clinical settings, group visits, and non-patient care settings. CONCLUSIONS: Our study identified significant levels of likely inaccurate OUD diagnoses among veterans with incident OUD diagnoses. The majority of these cases reflected readily addressable systems errors. The smaller proportion due to clinical errors and those with insufficient documentation may be addressed by increased training for clinicians. If these inaccuracies are prevalent throughout the VHA, they could complicate health services research and health systems responses.

Dual Use of a Patient Portal and Clinical Video Telehealth by Veterans with Mental Health Diagnoses: Retrospective, Cross-Sectional Analysis.

BACKGROUND: Access to mental health care is challenging. The Veterans Health Administration (VHA) has been addressing these challenges through technological innovations including the implementation of Clinical Video Telehealth, two-way interactive and synchronous videoconferencing between a provider and a patient, and an electronic patient portal and personal health record, My HealtheVet. OBJECTIVE: This study aimed to describe early adoption and use of My HealtheVet and Clinical Video Telehealth among VHA users with mental health diagnoses. METHODS: We conducted a retrospective, cross-sectional analysis of early My HealtheVet adoption and Clinical Video Telehealth engagement among veterans with one or more mental health diagnoses who were VHA users from 2007 to 2012. We categorized veterans into four electronic health (eHealth) technology use groups: My HealtheVet only, Clinical Video Telehealth only, dual users who used both, and nonusers of either. We examined demographic characteristics and mental health diagnoses by group. We explored My HealtheVet feature use among My HealtheVet adopters. We then explored predictors of My HealtheVet adoption, Clinical Video Telehealth engagement, and dual use using multivariate logistic regression. RESULTS: Among 2.17 million veterans with one or more mental health diagnoses, 1.51% (32,723/2,171,325) were dual users, and 71.72% (1,557,218/2,171,325) were nonusers of both My HealtheVet and Clinical Video Telehealth. African American and Latino patients were significantly less likely to engage in Clinical Video Telehealth or use My HealtheVet compared with white patients. Low-income patients who met the criteria for free care were significantly less likely to be My HealtheVet or dual users than those who did not. The odds of Clinical Video Telehealth engagement and dual use decreased with increasing age. Women were more likely than men to be My HealtheVet or dual users but less likely than men to be Clinical Video Telehealth users. Patients with schizophrenia or schizoaffective disorder were significantly less likely to be My HealtheVet or dual users than those with other mental health diagnoses (odds ratio, OR 0.50, CI 0.47-0.53 and OR 0.75, CI 0.69-0.80, respectively). Dual users were younger (53.08 years, SD 13.7, vs 60.11 years, SD 15.83), more likely to be white, and less likely to be low-income than the overall cohort. Although rural patients had 17% lower odds of My HealtheVet adoption compared with urban patients (OR 0.83, 95% CI 0.80-0.87), they were substantially more likely than their urban counterparts to engage in Clinical Video Telehealth and dual use (OR 2.45, 95% CI 1.95-3.09 for Clinical Video Telehealth and OR 2.11, 95% CI 1.81-2.47 for dual use). CONCLUSIONS: During this study (2007-2012), use of these technologies was low, leaving much potential for growth. There were sociodemographic disparities in access to My HealtheVet and Clinical Video Telehealth and in dual use of these technologies. There was also variation based on types of mental health diagnosis. More research is needed to ensure that these and other patient-facing eHealth technologies are accessible and effectively used by all vulnerable patients.

Estimating healthcare mobility in the Veterans Affairs Healthcare System.

BACKGROUND: Healthcare mobility, defined as healthcare utilization in more than one distinct healthcare system, may have detrimental effects on outcomes of care. We characterized healthcare mobility and associated characteristics among a national sample of Veterans. METHODS: Using the Veterans Health Administration Electronic Health Record, we conducted a retrospective cohort study to quantify healthcare mobility within a four year period. We examined the association between sociodemographic and clinical characteristics and healthcare mobility, and characterized possible temporal and geographic patterns of healthcare mobility. RESULTS: Approximately nine percent of the sample were healthcare mobile. Younger Veterans, divorced or separated Veterans, and those with hepatitis C virus and psychiatric disorders were more likely to be healthcare mobile. We demonstrated two possible patterns of healthcare mobility, related to specialty care and lifestyle, in which Veterans repeatedly utilized two different healthcare systems. CONCLUSIONS: Healthcare mobility is associated with young age, marital status changes, and also diseases requiring intensive management. This type of mobility may affect disease prevention and management and has implications for healthcare systems that seek to improve population health.

Personal health record reach in the Veterans Health Administration: a cross-sectional analysis.

BACKGROUND: My HealtheVet (MHV) is the personal health record and patient portal developed by the United States Veterans Health Administration (VA). While millions of American veterans have registered for MHV, little is known about how a patient's health status may affect adoption and use of the personal health record. OBJECTIVE: Our aim was to characterize the reach of the VA personal health record by clinical condition. METHODS: This was a cross-sectional analysis of all veterans nationwide with at least one inpatient admission or two outpatient visits between April 2010 and March 2012. We compared adoption (registration, authentication, opt-in to use secure messaging) and use (prescription refill and secure messaging) of MHV in April 2012 across 18 specific clinical conditions prevalent in and of high priority to the VA. We calculated predicted probabilities of adoption by condition using multivariable logistic regression models adjusting for sociodemographics, comorbidities, and clustering of patients within facilities. RESULTS: Among 6,012,875 veterans, 6.20% were women, 61.45% were Caucasian, and 26.31% resided in rural areas. The mean age was 63.3 years. Nationwide, 18.64% had registered for MHV, 11.06% refilled prescriptions via MHV, and 1.91% used secure messaging with their clinical providers. Results from the multivariable regression suggest that patients with HIV, hyperlipidemia, and spinal cord injury had the highest predicted probabilities of adoption, whereas those with schizophrenia/schizoaffective disorder, alcohol or drug abuse, and stroke had the lowest. Variation was observed across diagnoses in actual (unadjusted) adoption and use, with registration rates ranging from 29.19% of patients with traumatic brain injury to 14.18% of those with schizophrenia/schizoaffective disorder. Some of the variation in actual reach can be explained by facility-level differences in MHV adoption and by differences in patients' sociodemographic characteristics (eg, age, race, income) by diagnosis. CONCLUSIONS: In this phase of early adoption, opportunities are being missed for those with specific medical conditions that require intensive treatment and self-management, which could be greatly supported by functions of a tethered personal health record.

The association of pain screening and pain level with suicide among US veterans with comorbid musculoskeletal and bipolar disorder diagnoses.

BACKGROUND: High suicide rates are documented among persons with bipolar disorder diagnoses and pain diagnoses, but few studies have examined the association of pain with suicide mortality in individuals with comorbid pain and bipolar disorders. This study assessed the association of pain screening and pain severity with suicide mortality among veterans with comorbid bipolar and musculoskeletal disorder (MSD) diagnoses. METHODS: A retrospective cohort study was conducted on 168,021 patients within the Veterans Health Administration (VHA) who received an MSD diagnosis from 2000 to 2015 and had a bipolar disorder diagnosis. Pain severity, comorbidities, demographics, and suicide mortality were extracted from VHA databases. Poisson regression examined relative risk of suicide by the presence pain screening and pain severity ratings. RESULTS: Pain was assessed in 72.73 % of veterans. Suicide risk was greater in those not assessed (0.98 % versus 0.77 % in assessed group). However, this result did not persist after adjusting for covariates (RR = 1.06). Among those assessed, higher suicide risk was associated with moderate (RR = 1.10), severe pain (RR = 1.06), and no pain (reference) relative to mild pain (RR = 0.99). Major depression, substance use disorders, and prescribed opioids and benzodiazepines increased risk. LIMITATIONS: Data were obtained from medical records; diagnoses were not confirmed via formal assessment, and no information was available on actual medication use or purpose. Over 25 % of the sample were missing pain severity ratings, which could have affected results. CONCLUSIONS: Suicide risk factors among persons with bipolar disorder are complex and multifactorial. Providers should prioritize suicide prevention efforts following new onset or worsening pain.

Efficacy of life goals collaborative care for bipolar disorder: A systematic review.

BACKGROUND: Bipolar disorder remains a disabling mental health condition despite the availability of effective treatments. Collaborative chronic care models (CCMs) represent an evidence-based way to structure care for conditions like bipolar disorder. Life Goals Collaborative Care (LGCC) was designed specifically for bipolar disorder, featuring psychoeducation alongside collaborative components (e.g. nurse care management or expert psychiatric consultation). Despite the use of Life Goals across health systems, a systematic review summarizing its effectiveness has never been conducted. METHODS: We conducted a systematic review of randomized controlled trials (RCTs) of LGCC through December 2023 to help guide the field in treating bipolar disorder (PROSPERO: #404581). We evaluated study quality and outcomes in several symptom and quality of life domains. RESULTS: Ten articles describing eight studies met inclusion criteria. All studies featured group-based LGCC; most were compared to treatment as usual (TAU). Three of eight studies found LGCC to be associated with statistically significant effects for the prevention of manic episodes. Most studies finding positive effects featured additional collaborative care components beyond psychoeducation and were conducted in capitated healthcare systems. LIMITATIONS: Limitations include: several types of potential bias in included studies; exclusion of observational studies of LGCC; lack of generalizability to pediatric populations; insufficient studies to conduct subgroup analyses; and low confidence in the quality of the evidence. CONCLUSIONS: In this systematic review, group-based LGCC demonstrated some positive effects for reducing mania recurrence; results for other outcome domains were equivocal. Future studies should investigate one-on-one LGCC, both in person and virtually, to enhance well-being for people with bipolar disorder.

Variation in Specialist Palliative Care Reach and Associated Factors Among People With Advanced Heart Failure in the Department of Veterans Affairs.

CONTEXT: Clinical practice guidelines recommend palliative care for people with advanced heart failure (aHF), yet it remains underutilized. OBJECTIVES: We examined medical center variation in specialist palliative care (SPC) and identified factors associated with variation among people with aHF. METHODS: We conducted a retrospective cohort study of 21,654 people with aHF who received healthcare in 83 Veterans Affairs Medical Centers (VAMCs) from 2018-2020. We defined aHF with ICD-9/10 codes and hospitalizations. We used random intercept multilevel logistic regression to derive SPC reach (i.e., predicted probability) for each VAMC adjusting for demographic and clinical characteristics. We then examined VAMC-level SPC delivery characteristics associated with predicted SPC reach including the availability of outpatient SPC (proportion of outpatient consultations), cardiology involvement (number of outpatient cardiology-initiated referrals), and earlier SPC (days from aHF identification to consultation). RESULTS: Of the sample the mean age = 72.9+/-10.9 years, 97.9% were male, 61.6% were White, and 32.2% were Black. The predicted SPC reach varied substantially across VAMCs from 9% to 57% (mean: 28% [95% Confidence Interval: 25%-30%]). Only the availability of outpatient SPC was independently associated with higher SPC reach. VAMCs, in which outpatient delivery made up the greatest share of SPC consultations (9% or higher) had 11% higher rates of SPC reach relative to VAMCs with a lower proportion of outpatient SPC. CONCLUSION: SPC reach varies widely across VAMCs for people with aHF. Outpatient palliative is common among high-reach VAMCs but its role in reach warrants further investigation. Strategies used by high-reach VAMCs may be potential targets to test for implementation and dissemination.

Association between early nonpharmacological management and follow-up for low back pain in the veterans health administration.

Background: Low back pain (LBP) is a common reason individuals seek healthcare. Nonpharmacologic management (NPM) is often recommended as a primary intervention, and earlier use of NPM for LBP shows positive clinical outcomes. Our purpose was to evaluate how timing of engagement in NPM for LBP affects downstream LBP visits during the first year. Methods: This study was a secondary analysis of an observational cohort study of national electronic health record data. Patients entering the Musculoskeletal Diagnosis/Complementary and Integrative Health Cohort with LBP from October 1, 2016 to September 30, 2017 were included. Exclusive patient groups were defined by engagement in NPM within 30 days of entry ("very early NPM"), between 31 and 90 days ("early NPM"), or not within the first 90 days ("no NPM"). The outcome was time, in days, to the final LBP follow-up after 90 days and within the first year. Cox proportional hazards regression was used to model time to final follow up, controlling for additional demographic and clinical covariables. Results: The study population included 44,175 patients, with 16.7% engaging in very early NPM and 13.1% in early NPM. Patients with very early NPM (5.2 visits, SD=4.5) or early NPM (5.7 visits, SD=4.6) had a higher mean number of LBP visits within the first year than those not receiving NPM in the first 90 days (3.2 visits, SD = 2.5). The very early NPM (HR=1.50, 95% CI: 1.46-1.54; median=48 days, IQR=97) and early NPM (HR=1.27, 95% CI: 1.23-1.30; median=88 days, IQR=92) had a significantly shorter time to final follow-up than the no NPM group (median=109 days, IQR=150). Conclusions: Veterans Health Administration patients receiving NPM for LBP within the first 90 days after initially seeking care demonstrate a significantly faster time to final follow-up visit within the first year compared to those who do not.

Continuing the transformation: charting the path for the future delivery of Veteran emergency care.

Important changes in the delivery of Veteran emergency care in the early 2000s in the Department of Veteran Affairs (VA) emergency departments and urgent care clinics substantially elevated the role of emergency medicine (EM) in Veteran health care. Focused on enhancing the quality of care, emergency care visits in both VA and non-VA (community) care locations have nearly doubled from the 1980s to more than 3 million visits in Fiscal Year 2022. Recognizing the need to plan for continued growth and the opportunity to address key research priorities, the VA Office of Emergency Medicine, together with the VA Health Services Research and Development Service, collaborated to convene a State of the Art Conference on Veteran Emergency Medicine (SAVE) in the winter of 2022. The goal of this conference was to identify research gaps and priorities for implementation of policies for three priority groups: geriatric Veterans, Veterans with mental health and substance use complaints, and Veterans presenting to non-VA (community) emergency care sites. In this article we discuss the rationale for the SAVE conference including a brief history of VA EM and the planning process and conclude with next steps for findings from the conference.

Research and policy recommendations from the SOTA XVI: State of the Art Conference on VA Emergency Medicine.

To better understand and prioritize research on emergency care for Veterans, the Department of Veteran Affairs (VA) Health Services Research and Development convened the 16th State of the Art Conference on VA Emergency Medicine (SAVE) in Winter 2022 with emergency clinicians, researchers, operational leaders, and additional stakeholders in attendance. Three specific areas of focus were identified including older Veterans, Veterans with mental health needs, and emergency care in the community (non-VA) settings. Among older Veterans, identified priorities included examination of variation in care and its impact on patient outcomes, utilization, and costs; quality of emergency department (ED) care transitions and strategies to improve them; impact of geriatric ED care improvement initiatives; and use of geriatric assessment tools in the ED. For Veterans with mental health needs, priorities included enhancing the reach of effective, multicomponent suicide prevention interventions; development and evaluation of interventions to manage substance use disorders; and identifying and examining safety and effective acute psychosis practices. Community (non-VA) emergency care priorities included examining changes in patterns of use and costs in VA and the community care settings as a result of recent policy and coverage changes (with an emphasis on modifiable factors); understanding quality, safety, and Veteran experience differences between VA and community settings; and better understanding follow-up needs among Veterans who received emergency care (or urgent care) and how well those needs are being coordinated, communicated, and met. Beyond these three groups, cross-cutting themes included the use of telehealth and implementation science to refine multicomponent interventions, care coordination, and data needs from both VA and non-VA sources. Findings from this conference will be disseminated through multiple mechanisms and contribute to future funding applications focused on improving Veteran health.

Clinical documentation of patient identities in the electronic health record: Ethical principles to consider.

The American Psychological Association's multicultural guidelines encourage psychologists to use language sensitive to the lived experiences of the individuals they serve. In organized care settings, psychologists have important decisions to make about the language they use in the electronic health record (EHR), which may be accessible to both the patient and other health care providers. Language about patient identities (including but not limited to race, ethnicity, gender, and sexual orientation) is especially important, but little guidance exists for psychologists on how and when to document these identities in the EHR. Moreover, organizational mandates, patient preferences, fluid identities, and shifting language may suggest different documentation approaches, posing ethical dilemmas for psychologists to navigate. In this article, we review the purposes of documentation in organized care settings, review how each of the five American Psychological Association Code of Ethics' General Principles relates to identity language in EHR documentation, and propose a set of questions for psychologists to ask themselves and their patients when making choices about documenting identity variables in the EHR. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Validation of Electronic Health Record-Based Algorithms to Identify Specialist Palliative Care Within the Department of Veterans Affairs.

BACKGROUND: The measurement of specialist palliative care (SPC) across Department of Veterans Affairs (VA) facilities relies on algorithms applied to administrative databases. However, the validity of these algorithms has not been systematically assessed. MEASURES: In a cohort of people with heart failure identified by ICD 9/10 codes, we validated the performance of algorithms to identify SPC consultation in administrative data and differentiate outpatient from inpatient encounters. INTERVENTION: We derived separate samples of people by receipt of SPC using combinations of stop codes signifying specific clinics, current procedural terminology (CPT), a variable representing encounter location, and ICD-9/ICD-10 codes for SPC. We calculated sensitivity, specificity, and positive and negative predictive values (PPV, NPV) for each algorithm using chart review as the reference standard. OUTCOMES: Among 200 people who did and did not receive SPC (mean age = 73.9 years (standard deviation [SD] = 11.5), 98% male, 73% White), the validity of the stop code plus CPT algorithm to identify any SPC consultation was: Sensitivity = 0.89 (95% Confidence Interval [CI] 0.82-0.94), Specificity = 1.0 [0.96-1.0], PPV = 1.0 [0.96-1.0], NPV = 0.93 [0.86-0.97]. The addition of ICD codes increased sensitivity but decreased specificity. Among 200 people who received SPC (mean age = 74.2 years [SD = 11.8], 99% male, 71% White), algorithm performance in differentiating outpatient from inpatient encounters was: Sensitivity = 0.95 (0.88-0.99), Specificity = 0.81 (0.72-0.87), PPV = 0.38 (0.29-0.49), and NPV = 0.99 (0.95-1.0). Adding encounter location improved the sensitivity and specificity of this algorithm. CONCLUSIONS: VA algorithms are highly sensitive and specific in identifying SPC and in differentiating outpatient from inpatient encounters. These algorithms can be used with confidence to measure SPC in quality improvement and research across the VA.

Long-term opioid therapy trajectories and overdose in patients with and without cancer.

Objective: Pain is experienced by most patients with cancer and opioids are a cornerstone of management. Our objectives were (1) to identify patterns or trajectories of long-term opioid therapy (LTOT) and their correlates among patients with and without cancer and (2) to assess the association between trajectories and risk for opioid overdose, considering the potential moderating role of cancer. Methods and Analysis: We conducted a retrospective cohort study among individuals in the US Veterans Health Administration (VHA) database with incident LTOT with and without cancer (N=44,351; N=285,772, respectively) between 2010-2017. We investigated the relationship between LTOT trajectory and all International Classification of Diseases-9 and 10-defined accidental and intentional opioid-related overdoses. Results: Trajectories of opioid receipt observed in patients without cancer and replicated in patients with cancer were: low-dose/stable trend, low-dose/de-escalating trend, moderate-dose/stable trend, moderate-dose/escalating with quadratic downturn trend, and high-dose/escalating with quadratic downturn trend. Time to first overdose was significantly predicted by higher-dose and escalating trajectories; the two low-dose trajectories conferred similar, lower risk. Conditional hazard ratios (99% CI) for the moderate-dose, moderate-dose/escalating with quadratic downturn and high-dose/escalating with quadratic downturn trends were 1·84 (1·18, 2·85), 2·56 (1·54, 4·25), and 2·41 (1·37, 4·26), respectively. Effects of trajectories on time to overdose did not differ by presence of cancer; inferences were replicated when restricting to patients with stage 3/4 cancer. Conclusion: Patients with cancer face opioid overdose risks like patients without cancer. Future studies should seek to expand and address our knowledge about opioid risk in cancer patients. Trial registration: None.

Incidence and Trends in the Use of Palliative Care among Patients with Reduced, Middle-Range, and Preserved Ejection Fraction Heart Failure.

Background: Clinical practice guidelines recommend integrating palliative care (PC) into the care of patients with heart failure (HF) to address their many palliative needs. However, the incidence rates of PC use among HF subtypes are unknown. Methods: We conducted a retrospective cohort study of patients with the following HF subtypes in the Department of Veterans Affairs: reduced ejection fraction (HFrEF), mid-range ejection fraction (HFmEF), and preserved ejection fraction (HFpEF). Patients were included at the time of HF diagnosis from 2011 to 2015 and followed until a minimum of five years or death. Incidence rates of receipt of PC (primary outcome) were calculated using generalized estimating equations. We evaluated the time to incident PC by HF subtype with Kaplan-Meier analyses and with adjusted restricted mean survival time. Results: Of the 113,555 patients, 69% were ≥65 years, 98% were male, 73% White, and 18% Black; 58% had HFrEF, 7% HFmEF, and 34% HFpEF. Twenty percent received PC during follow-up, and 66% died. Adjusted PC incidence rates were higher among patients with HFrEF (47 per 1000 person-years, confidence interval [95% CI] 43-52) than for HFmEF and HFpEF (42 per 1000 person-years, CI 38-47 for both). Restricting follow-up to five years, patients with HFrEF received PC six weeks earlier than patients with HFpEF. There was no significant difference in time to PC between patients with HFmEF versus HFpEF. Conclusion: About 1 in 20 patients with HFrEF and 1 in 25 patients with HFmEF and HFpEF receive PC annually. Patients with HFrEF receive PC sooner than patients with HFmEF and HFpEF.

Sex Differences in Use of a Clinical Complexity Measure to Predict Primary Care Utilization.

Background: The Veterans Affairs (VA)-developed Care Assessment Need (CAN) score, a risk-stratification tool used to identify complex high-risk patients and guide VA care coordination, was designed to predict hospitalization or death. Little is known about its utility in predicting primary care utilization or if gender differences in this metric are detectable. Our objective was to determine association of CAN score quintiles with high primary care visit (PCV) utilization among Veterans, the impact of adding reproductive health and psychosocial variables to the model and the difference between men and women Veterans. Methods: The sample included men and women from the post-9/11 cohort receiving VA care for at least 1 year, 2010-2017 (N = 665,379). PCV data for each year were collected from national Corporate Data Warehouse. A cumulative count ≥6 visits in a year was used as an indication for high PCV utilization in the analyses. Results: After accounting for potential confounding factors, women were associated with 42% higher odds of heavy PCV utilization (adjusted odds ratio: 1.42, 95% confidence interval: 1.37-1.46) than men. However, there was a significant interaction between sex and CAN quintiles (p < 0.001). After adjusting for all the covariates, CAN score quintiles appeared to have stronger associations and better predictive accuracy on the risk of 1-year heavy PCV utilization for men than for women. Conclusion: Further research is needed to understand sex differences in Veterans Health Administration clinical complexity measures and whether they can be successfully used to identify high-risk, high-utilizing women Veterans.