Adaptation for sustainability in an implementation trial of team-based collaborative care.

Background: Sustaining healthcare interventions once they have been implemented is a pivotal public health endeavor. Achieving sustainability requires context-sensitive adaptations to evidence-based practices (EBPs) or the implementation strategies used to ensure their adoption. For replicability of adaptations beyond the specific setting in question, the underlying logic needs to be clearly described, and adaptations themselves need to be plainly documented. The goal of this project was to describe the process by which implementation facilitation was adapted to improve the uptake of clinical care practices that are consistent with the collaborative chronic care model (CCM). Method: Quantitative and qualitative data from a prior implementation trial found that CCM-consistent care practices were not fully sustained within outpatient general mental health teams that had received 1 year of implementation facilitation to support uptake. We undertook a multistep consensus process to identify adaptations to implementation facilitation based on these results, with the goal of enhancing the sustainability of CCM-based care in a subsequent trial. The logic for these adaptations, and the resulting adaptations themselves, were documented using two adaptation-oriented implementation frameworks (the iterative decision-making for evaluation of adaptations [IDEA] and the framework for reporting adaptations and modifications to evidence-based implementation strategies [FRAME-IS], respectively). Results: Three adaptations emerged from this process and were documented using the FRAME-IS: (a) increasing the scope of implementation facilitation within the medical center, (b) having the internal facilitator take a greater role in the implementation process, and (c) shortening the implementation timeframe from 12 to 8 months, while increasing the intensity of facilitation support during that time. Conclusions: EBP sustainability may require careful adaptation of EBPs or the implementation strategies used to get them into routine practice. Recently developed frameworks such as the IDEA and FRAME-IS may be used to guide decision-making and document resulting adaptations themselves. An ongoing funded study is investigating the utility of the resulting adaptations for improving healthcare.

Evidence-based treatments may not be sustained after they have been implemented in healthcare settings. To address this, treatments and implementation strategies may need to be adapted to fit the local context or the patient population. Maximizing the usefulness of such adaptations requires documenting the decision-making process. Understanding how an implementation strategy has been adapted for a given study or setting is crucial to ensuring that adaptations don't compromise fidelity to the implementation strategy while enabling its replicability in similar settings. This article uses two adaptation frameworks to describe the process by which implementation facilitation, a common implementation strategy, was adapted to help establish and sustain effective mental health clinical teams in VA medical centers. It is our hope that our description of this process may help healthcare researchers, administrators, and policymakers to describe and document adaptations to implementation strategies in their own settings.

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

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

Using the Matrixed Multiple Case Study approach to identify factors affecting the uptake of IPV screening programs following the use of implementation facilitation.

BACKGROUND: Intimate partner violence (IPV) is a prevalent social determinant of health. The US Preventive Services Task Force recommends routine IPV screening of women, but uptake remains variable. The Veterans Health Administration (VHA) initiated implementation facilitation (IF) to support integration of IPV screening programs into primary care clinics. An evaluation of IF efforts showed variability in IPV screening rates across sites. The follow-up study presented here used a Matrixed Multiple Case Study (MMCS) approach to examine the multilevel factors impacting IPV screening program implementation across sites with varying levels of implementation success. METHODS: This mixed methods study is part of a larger cluster randomized stepped wedge Hybrid-II program evaluation. In the larger trial, participating sites received 6 months of IF consisting of an external facilitator from VHA's Office of Women's Health working closely with an internal facilitator and key site personnel. Recognizing the heterogeneity in implementation outcomes across sites, the MMCS approach was used to enable interpretation of qualitative and quantitative data within and across sites to help contextualize the primary findings from the larger study. Qualitative data collection was guided by the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework and included interviews with key informants involved in IPV screening implementation at eight sites. Quantitative data on IPV screening uptake was derived from medical records and surveys completed by key personnel at the same eight sites to understand implementation facilitation activities. RESULTS: Fifteen factors influencing IPV screening implementation spanning all four i-PARIHS domains were identified and categorized into three distinct categories: (1) factors with enabling influence across all sites, (2) factors deemed important to implementation success, and (3) factors differentiating sites with high/medium versus low implementation success. CONCLUSIONS: Understanding the influencing factors across multi-level domains contributing to variable success of IPV screening implementation can inform the tailoring of IF efforts to promote spread and quality of screening. Implementation of IPV screening programs in primary care with IF should consider consistent engagement of internal facilitators with clinic staff involved in implementation, the resourcefulness of external facilitators, and appending resources to IPV screening tools to help key personnel address positive screens. TRIAL REGISTRATION: ClinicalTrials.gov NCT04106193. Registered on September 26, 2019.

Integrating Intimate Partner Violence Screening Programs in Primary Care: Results from a Hybrid-II Implementation-Effectiveness RCT.

INTRODUCTION: The Veterans Health Administration initiated implementation facilitation to integrate intimate partner screening programs in primary care. This study investigates implementation facilitation's impact on implementation and clinical effectiveness outcomes. STUDY DESIGN: A cluster randomized, stepped-wedge, hybrid-II implementation-effectiveness trial (January 2021-April 2022) was conducted amidst the COVID-19 pandemic. SETTING/PARTICIPANTS: Implementation facilitation was applied at 9 Veterans Health Administration facilities, staged across 2 waves. Participants were all women receiving care at participating primary care clinics 3 months before (pre-implementation facilitation n=2,272) and 9 months after initiation of implementation facilitation (implementation facilitation n=5,149). INTERVENTION: Implementation facilitation included an operations-funded external facilitator working for 6 months with a facility-funded internal facilitator from participating clinics. The pre-implementation facilitation period comprised implementation as usual in the Veterans Health Administration. MAIN OUTCOME MEASURES: Primary outcomes were changes in (1) reach of intimate partner violence (IPV) screening programs among eligible women (i.e., those seen within participating clinics during the assessment period; implementation outcome) and (2) disclosure rates among screened women (effectiveness outcome). Secondary outcomes included disclosure rates among all eligible women and post-screening psychosocial service use. Administrative data were analyzed. RESULTS: For primary outcomes, women seen during the implementation facilitation period were nearly 3 times more likely to be screened for IPV than women seen during the pre-implementation facilitation period (OR=2.70, 95% CI=2.46, 2.97). Women screened during the implementation facilitation period were not more likely to disclose IPV than those screened during the pre-implementation facilitation period (OR=1.14, 95% CI=0.86, 1.51). For secondary outcomes, owing to increased reach of screening during implementation facilitation, women seen during the implementation facilitation period were more likely to disclose IPV than those seen during the pre-implementation facilitation period (OR=2.09, 95% CI=1.52, 2.86). Women screened during implementation facilitation were more likely to use post-screening psychosocial services than those screened during pre-implementation facilitation (OR=1.29, 95% CI=1.06, 1.57). CONCLUSIONS: Findings indicate that implementation facilitation may be a promising strategy for increasing the reach of IPV screening programs in primary care, thereby increasing IPV detection and strengthening connections to support services among the patient population. TRIAL REGISTRATION: This study is registered at www. CLINICALTRIALS: gov NCT04106193.

One-Year All-Cause Mortality and Delivery of the Collaborative Chronic Care Model in General Mental Health Clinics.

OBJECTIVE: This study aimed to determine whether the evidence-based collaborative chronic care model (CCM) is associated with reduced all-cause mortality among adult patients treated in general mental health clinics. METHODS: Data came from a stepped-wedge, cluster-randomized CCM implementation trial across nine U.S. Department of Veterans Affairs medical centers. Survival analysis was used to estimate the relative effect of the treatment (N=5,570) compared with a control group (N=46,443) over 1 year. RESULTS: After adjustment for site-level and individual-level acute care utilization factors, analyses indicated that patients treated with the CCM experienced a reduction in all-cause mortality relative to patients in the control cohort (hazard ratio=0.76, 95% CI=0.60-0.95). CONCLUSIONS: This study is the first in which CCM has been shown to reduce all-cause mortality for patients treated in general mental health clinics. Care delivery models should be considered part of efforts to reduce the life expectancy gap between individuals with psychiatric conditions and those without such conditions.

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

Despite the active posttraumatic stress disorder (PTSD) screening program in Department of Veterans Affairs (VA) primary care clinics and the availability of empirically supported treatments for PTSD at VA, many veterans for whom screening suggests treatment may be indicated do not gain access to VA-based mental health care. To determine where we may be losing veterans to follow-up, we need to begin by identifying the initial action taken in response to a positive PTSD screen in primary care. Using VA administrative data and chart review, we identified the spectrum of initial actions taken after veterans screened positive for PTSD in VA primary care clinics nationwide between October 2017 and September 2018 (N = 41,570). We collapsed actions into those that could lead to VA-based mental health care (e.g., consult placed to a VA mental health clinic) versus not (e.g., veteran declined care), and then examined the association between these categories of actions and contextual- and individual-level variables. More than 61% of veterans with positive PTSD screens had evidence that an initial action toward VA-based mental health care was taken. Urban-dwelling and female veterans were significantly more likely to have evidence of these initial actions, whereas White and Vietnam-era veterans were significantly less likely to have this evidence. Our findings suggest that most veterans screening positive for PTSD in VA primary care clinics have evidence of initial actions taken toward VA-based mental health care; however, a substantial minority do not, making them unlikely to receive follow-up care. Findings highlight the potential benefit of targeted primary care-based access interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Guardianship Before and Following Hospitalization.

When ethics committees are consulted about patients who have or need court-appointed guardians, they lack empirical evidence about several common issues, including the relationship between guardianship and prolonged, potentially medically unnecessary hospitalizations for patients. To provide information about this issue, we conducted quantitative and qualitative analyses using a retrospective cohort from Veterans Healthcare Administration. To examine the relationship between guardianship appointment and hospital length of stay, we first compared 116 persons hospitalized prior to guardianship appointment to a comparison group (n = 348) 3:1 matched for age, diagnosis, date of admission, and comorbidity. We then compared 91 persons hospitalized in the year following guardianship appointment to a second matched comparison group (n = 273). Mean length of stay was 30.75 days (SD = 46.70) amongst those admitted prior to guardianship, which was higher than the comparison group (M = 7.74, SD = 9.71, F = 20.75, p < .001). Length of stay was lower following guardianship appointment (11.65, SD = 12.02, t = 15.16, p < .001); while higher than the comparison group (M = 7.60, SD = 8.46), differences were not associated with guardianship status. In a separate analysis involving 35 individuals who were hospitalized both prior to and following guardianship, length of stay was longer in the year prior (M = 23.00, SD = 37.55) versus after guardianship (M = 10.37, SD = 10.89, F = 4.35, p = .045). In qualitative analyses, four themes associated with lengths of stay exceeding 45 days prior to guardianship appointment were: administrative issues, family conflict, neuropsychiatric comorbidity, and medical complications. Our results suggest that persons who are admitted to hospitals, and subsequently require a guardian, experience extended lengths of stay for multiple complex reasons. Once a guardian has been appointed, however, differences in hospital lengths of stay between patients with and without guardians are reduced.

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

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

Direct-to-consumer strategies to promote deprescribing in primary care: a pilot study.

BACKGROUND: Deprescribing, or the intentional discontinuation or dose-reduction of medications, is an approach to reduce harms associated with inappropriate medication use. We sought to determine how direct-to-patient educational materials impacted patient-provider discussion about and deprescribing of potentially inappropriate medications. METHODS: We conducted a pre-post pilot trial, using an historical control group, at an urban VA medical center. We included patients in one of two cohorts: 1) chronic proton pump inhibitor users (PPI), defined as use of any dose for 90 consecutive days, or 2) patients at hypoglycemia risk, defined by diabetes diagnosis; prescription for insulin or sulfonylurea; hemoglobin A1c < 7%; and age ≥ 65 years, renal insufficiency, or cognitive impairment. The intervention consisted of mailing medication-specific patient-centered EMPOWER (Eliminating Medications Through Patient Ownership of End Results) brochures, adapted to a Veteran patient population, two weeks prior to scheduled primary care appointments. Our primary outcome - deprescribing - was defined as clinical documentation of target medication discontinuation or dose-reduction. Our secondary outcome was documentation of a discussion about the target medication (yes/possible vs. no/absent). Covariates included age, sex, race, specified comorbidities, medications, and utilization. We used chi-square tests to examine the association of receiving brochures with each outcome. RESULTS: The 348 subjects (253 intervention, 95 historical control) were primarily age ≥ 65 years, white, and male. Compared to control subjects, intervention subjects were more likely to have deprescribing (36 [14.2%] vs. 4 [4.2%], p = 0.009) and discussions about the target medication (31 [12.3%] vs. 1 [1.1%], p = 0.001). CONCLUSIONS: Targeted mailings of EMPOWER brochures temporally linked to a scheduled visit in primary care clinics are a low-cost, low-technology method associated with increases in both deprescribing and documentation of patient-provider medication discussions in a Veteran population. Leveraging the potential for patients to initiate deprescribing discussions within clinical encounters is a promising strategy to reduce drug burden and decrease adverse drug effects and harms.

Time-motion analysis of external facilitation for implementing the Collaborative Chronic Care Model in general mental health clinics: Use of an interval-based data collection approach.

Background: Facilitation is an effective strategy to implement evidence-based practices, often involving external facilitators (EFs) bringing content expertise to implementation sites. Estimating time spent on multifaceted EF activities is complex. Furthermore, collecting continuous time-motion data for facilitation tasks is challenging. However, organizations need this information to allocate implementation resources to sites. Thus, our objectives were to conduct a time-motion analysis of external facilitation, and compare continuous versus noncontinuous approaches to collecting time-motion data. Methods: We analyzed EF time-motion data from six VA mental health clinics implementing the evidence-based Collaborative Chronic Care Model (CCM). We documented EF activities during pre-implementation (4-6 weeks) and implementation (12 months) phases. We collected continuous data during the pre-implementation phase, followed by data collection over a 2-week period (henceforth, "a two-week interval") at each of three time points (beginning/middle/end) during the implementation phase. As a validity check, we assessed how closely interval data represented continuous data collected throughout implementation for two of the sites. Results: EFs spent 21.8 ± 4.5 h/site during pre-implementation off-site, then 27.5 ± 4.6 h/site site-visiting to initiate implementation. Based on the 2-week interval data, EFs spent 2.5 ± 0.8, 1.4 ± 0.6, and 1.2 ± 0.6 h/week toward the implementation's beginning, middle, and end, respectively. Prevalent activities were preparation/planning, process monitoring, program adaptation, problem identification, and problem-solving. Across all activities, 73.6% of EF time involved email, phone, or video communication. For the two continuous data sites, computed weekly time averages toward the implementation's beginning, middle, and end differed from the interval data's averages by 1.0, 0.1, and 0.2 h, respectively. Activities inconsistently captured in the interval data included irregular assessment, stakeholder engagement, and network development. Conclusions: Time-motion analysis of CCM implementation showed initial higher-intensity EF involvement that tapered. The 2-week interval data collection approach, if accounting for its potential underestimation of irregular activities, may be promising/efficient for implementation studies collecting time-motion data.

Patient and provider predictors of telemental health use prior to and during the COVID-19 pandemic within the Department of Veterans Affairs.

The current study examined patient and provider differences in use of phone, video, and in-person mental health (MH) services. Participants included patients who completed ≥ 1 MH appointment within the Department of Veterans Affairs (VA) from 10/1/17-7/10/20 and providers who completed ≥ 100 VA MH appointments from 10/1/17-7/10/20. Adjusted odds ratios (aORs) are reported of patients and providers: (a) completing ≥1 video MH appointment in the pre-COVID (10/1/17-3/10/20) and COVID (3/11/20-7/10/20) periods; and (b) completing the majority of MH visits via phone, video, or in-person during COVID. The sample included 2,480,119 patients/31,971 providers in the pre-COVID period, and 1,054,670 patients/23,712 providers in the COVID period. During the pre-COVID and COVID periods, older patients had lower odds of completing ≥ 1 video visit (aORs < .65). During the COVID period, older age and low socioeconomic status predicted lower odds of having ≥ 50% of visits via video versus in-person or phone (aORs < .68); schizophrenia and MH hospitalization history predicted lower odds of having ≥ 50% of visits via video or phone versus in-person (aORs < . 64). During the pre-COVID and COVID periods, nonpsychologists (e.g., psychiatrists) had lower odds of completing video visits (aORs < . 44). Older providers had lower odds of completing ≥ 50% of visits via video during COVID (aORs <. 69). Findings demonstrate a digital divide, such that older and lower income patients, and older providers, engaged in less video care. Nonpsychologists also had lower video use. Barriers to use must be identified and strategies must be implemented to ensure equitable access to video MH services. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Intimate Partner Violence Screening for Women in the Veterans Health Administration: Temporal Trends from the Early Years of Implementation 2014-2020.

Thousands of women Veterans experience intimate partner violence (IPV) each year. The Veterans Health Administration (VHA) has encouraged IPV screening in Veterans Affairs medical centers (VAMCs) since 2014. Through retrospective analysis of VHA administrative data from fiscal year (FY) 2014 into FY2020, we examined IPV screening implementation outcomes of reach and adoption, as well as screen-positive rates using descriptive and multivariate linear regression analyses. We examined reach and screen-positive rates overall and as a function of childbearing age (18-44 vs. 45+ years). In FY2014 only one VAMC was screening women for IPV; by FY2020, over half of VAMCs had adopted IPV screening. This rollout of IPV screening was associated with a large increase in the number of women primary care patients screened (from fewer than 500 in FY2014, to nearly 35,000 in early FY2020). Overall, among women screened, 6.7% screened positive for IPV; this rate was higher among women of childbearing age (8.1% vs. 5.6%). Despite the spread of IPV screening practices during the early years of implementation in VHA, additional work is needed. This study is the first comprehensive analysis of implementation outcomes associated with VHA's IPV screening efforts, and lays the groundwork for ongoing evaluation and quality improvement.

Time course and heterogeneity of treatment effect of the collaborative chronic care model on psychiatric hospitalization rates: A survival analysis using routinely collected electronic medical records.

BACKGROUND: Health systems are undergoing widespread adoption of the collaborative chronic care model (CCM). Care structured around the CCM may reduce costly psychiatric hospitalizations. Little is known, however, about the time course or heterogeneity of treatment effects (HTE) for CCM on psychiatric hospitalization. RATIONALE: Assessment of CCM implementation support on psychiatric hospitalization might be more efficient if the timing were informed by an expected time course. Further, understanding HTE could help determine who should be referred for intervention. OBJECTIVES: (i) Estimate the trajectory of CCM effect on psychiatric hospitalization rates. (ii) Explore HTE for CCM across demographic and clinical characteristics. METHODS: Data from a stepped wedge CCM implementation trial were reanalyzed using 5 570 patients in CCM treatment and 46 443 patients receiving usual care. Time-to-event data was constructed from routine medical records. Effect trajectory of CCM on psychiatric hospitalization was simulated from an extended Cox model over one year of implementation support. Covariate risk contributions were estimated from subset stratified Cox models without using simulation. Ratios of hazard ratios (RHR) allowed comparison by trial arm for HTE analysis, also without simulation. No standard Cox proportional hazards models were used for either estimating the time-course or heterogeneity of treatment effect. RESULTS: The effect of CCM implementation support increased most rapidly immediately after implementation start and grew more gradually throughout the rest of the study. On the final study day, psychiatric hospitalization rates in the treatment arm were 17% to 49% times lower than controls, with adjustment for all model covariates (HR 0.66; 95% CI 0.51-0.83). Our analysis of HTE favored usual care for those with a history of prior psychiatric hospitalization (RHR 4.92; 95% CI 3.15-7.7) but favored CCM for those with depression (RHR 0.61; 95% CI: 0.41-0.91). Having a single medical diagnosis, compared to having none, favored CCM (RHR 0.52; 95% CI 0.31-0.86). CONCLUSION: Reduction of psychiatric hospitalization is evident immediately after start of CCM implementation support, but assessments may be better timed once the effect size begins to stabilize, which may be as early as six months. HTE findings for CCM can guide future research on utility of CCM in specific populations.

Implementing the Collaborative Chronic Care Model in Mental Health Clinics: Achieving and Sustaining Clinical Effects.

OBJECTIVE: Collaborative chronic care models (CCMs) were established with implementation support in nine mental health clinics. This study sought to determine whether their clinical impact was maintained after implementation support ceased. METHODS: Posttrial data were analyzed from a randomized stepped-wedge CCM implementation trial in general mental health clinics in nine Department of Veterans Affairs medical centers. Sites received 1 year of implementation support, which was associated with reduced mental health hospitalization rates compared with non-CCM clinics in the same medical centers. Hospitalization rates for the year after implementation support were analyzed by using repeated measures logistic regression comparing the same clinics. RESULTS: Hospitalization rates for the postsupport year did not differ from comparison clinics either in the population that initially showed the difference or the population active in the clinics at the end of the year of implementation support. CONCLUSIONS: Clinical effects of the CCM may wane after cessation of active implementation support.

End-of-Life Care for Persons Under Guardianship.

CONTEXT: Guardians are surrogate decision makers appointed by a court when other health care decision-makers are unable, unwilling, or unavailable to make decisions. Prior studies suggest that persons under guardianship may experience delays in transitions of care. OBJECTIVES: To compare quality of end-of-life care for persons under guardianship to a matched group on objective indicators and to identify narrative themes characterizing potential obstacles to quality end-of-life care. METHODS: One hundred sixty-seven persons under guardianship who died between 2003 and 2019 within the Veterans Healthcare Administration in Massachusetts and Connecticut matched on a 1:1 basis to persons without guardians. The groups were compared on treatment specialty at death, days of hospice and intensive care unit care, and receipt of palliative care consultation. Additionally, patient narratives for those under guardianship with extended lengths in intensive care unit were subjected to qualitative analysis. RESULTS: Overall, <1% were under guardianship. Within this sample of persons who died within the Veterans Health Administration, persons under guardianship were as likely as patients in the comparison group to receive palliative care consultation (odds ratio [CI] = 0.93 [.590-1.46], P = .359), but were more likely to have ethics consultation (odds ratio [CI] = 0.25 [0.66-0.92], P = .036) and have longer lengths of ICU admission (ß = -.34, t = -2.70, P = .009). Qualitative findings suggest that issues related to family conflict, fluctuating medical course, and limitations in guardian authority may underlie extended lengths of stay. CONCLUSION: Guardianship appears to be rare, and as a rule, those under guardianship have equal access to hospice and palliative care within Veterans Health Administration. Guardianship may be associated with health-care challenges in a small number of cases, and this may drive perceptions of adverse outcomes.

Rapid Increase in Telemental Health Within the Department of Veterans Affairs During the COVID-19 Pandemic.

Background: The use of telemental health via videoconferencing (TMH-V) became critical during the Coronavirus disease 2019 (COVID-19) pandemic due to restriction of non-urgent in-person appointments. The current brief report demonstrates the rapid growth in TMH-V appointments in the weeks following the pandemic declaration within the Department of Veterans Affairs (VA), the largest healthcare system in the United States. Methods: COVID-19 changes in TMH-V appointments were captured during the six weeks following the World Health Organization's pandemic declaration (March 11, 2020-April 22, 2020). Pre-COVID-19 TMH-V encounters were assessed from October 1, 2017 to March 10, 2020. Results: Daily TMH-V encounters rose from 1,739 on March 11 to 11,406 on April 22 (556% growth, 222,349 total encounters). Between March 11-April 22, 114,714 patients were seen via TMH-V, and 77.5% were first-time TMH-V users. 12,342 MH providers completed a TMH-V appointment between March 11-April 22, and 34.7% were first-time TMH-V users. The percentage growth of TMH-V appointments was higher than the rise in telephone appointments (442% growth); in-person appointments dropped by 81% during this time period. Discussion and Conclusions: The speed of VA's growth in TMH-V appointments in the wake of the COVID-19 pandemic was facilitated by its pre-existing telehealth infrastructure, including earlier national efforts to increase the number of providers using TMH-V. Longstanding barriers to TMH-V implementation were lessened in the context of a pandemic, during which non-urgent in-person MH care was drastically reduced. Future work is necessary to understand the extent to which COVID-19 related changes in TMH-V use may permanently impact mental health care provision.

The Patient Perceptions of Deprescribing (PPoD) Survey: Short-Form Development.

INTRODUCTION: Deprescribing, the intentional reduction of medication, is recognized as an important component of clinical care; however, standardized identification of patient attitudes and beliefs that contribute to deprescribing may be limited due to the length of current surveys. We sought to develop a short-form (≤ 15 items) of the patient perceptions of deprescribing (PPoD) questionnaire, a validated 30-item instrument that assesses dimensions relevant to deprescribing, to be used in clinical and research settings. METHODS: We conducted a secondary analysis of data from 803 US veteran respondents to the original PPoD survey, randomly divided into derivation and validation samples. In the derivation sample, we used ordinary least squares linear regression with R2 model selection to identify candidate items reflective of overall readiness for deprescribing. We then used iterative multitrait analysis, followed by confirmatory factor analysis (CFA) in the validation sample to assess the psychometric properties of the proposed short form. RESULTS: The resulting short-form PPoD consisted of 11 items representing two overarching domains reflective of overall readiness for deprescribing: 'Motivation for Deprescribing' and 'Primary Care Provider Relationship'. CFA fit statistics supported the proposed structure and the two new scales demonstrated high internal consistency reliability (Cronbach alphas: 0.82 and 0.91, respectively) and good discriminant validity (interscale correlation - 0.30). DISCUSSION: The proposed short-form PPoD captures two important sources of variance in patient readiness for deprescribing: motivation and patients' relationships with their primary care providers. This brief, 11-item survey may help foster the inclusion of patient perceptions into clinical decision making for deprescribing to yield safer, more appropriate medication use.

Novel Method to Flag Cardiac Implantable Device Infections by Integrating Text Mining With Structured Data in the Veterans Health Administration's Electronic Medical Record.

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

An Economic Analysis of the Implementation of Team-based Collaborative Care in Outpatient General Mental Health Clinics.

BACKGROUND: Collaborative Chronic Care Models represent an evidence-based way to structure care for chronic conditions, including mental health conditions. Few studies, however, have examined the cost implications of collaborative care for mental health. OBJECTIVE: We aimed to conduct an economic analysis of implementing collaborative care in 9 outpatient general mental health clinics. RESEARCH DESIGN: Analyses were derived from a stepped wedge hybrid implementation-effectiveness trial. We conducted cost-minimization analyses from the health system perspective, incorporating implementation costs, outpatient costs, and inpatient costs for the year before collaborative care implementation and the implementation year. We used a difference-in-differences approach and conducted 1-way sensitivity analyses to determine the robustness of results to variations ±15% in model parameters, along with probabilistic sensitivity analysis using Monte Carlo simulation. SUBJECTS: Our treatment group included 5507 patients who were initially engaged in care within 9 outpatient general mental health teams that underwent collaborative care implementation. We compared costs for this group to 45,981 control patients who received mental health treatment as usual at the same medical centers. RESULTS: Collaborative care implementation cost about $40 per patient and was associated with a significant decrease in inpatient costs and a nonsignificant increase in outpatient mental health costs. This implementation was associated with $78 in cost savings per patient. Monte Carlo simulation suggested that implementation was cost saving in 78% of iterations. CONCLUSIONS: Collaborative care implementation for mental health teams was associated with significant reductions in mental health hospitalizations, leading to substantial cost savings of about $1.70 for every dollar spent for implementation.