Provider Perceptions toward Extended-Release Buprenorphine for Treatment of Opioid Use Disorder.

OBJECTIVES: The persistence of the opioid crisis and the proliferation of synthetic fentanyl have heightened the demand for the implementation of novel delivery mechanisms of pharmacotherapy for the treatment of opioid use disorder, including injectable extended-release buprenorphine (buprenorphine-ER). The purpose of this study was to understand provider-level barriers to prescribing buprenorphine in order to facilitate targeted strategies to improve implementation for patients who would benefit from this novel formulation. METHODS: Using an interview template adapted from the Consolidated Framework for Implementation Research (CFIR), we conducted structured focus group interviews with 20 providers in an outpatient addiction clinic across 4 sessions to assess providers' perceptions of buprenorphine-ER. Ninety-four unique comments were identified and deductively coded using standardized CFIR constructs. RESULTS: Providers expressed mixed receptivity and confidence in using buprenorphine-ER. Although providers could identify a number of theoretical advantages to the injectable formulation over sublingual buprenorphine, many expressed reservations about using it due to inexperience, negative patient experiences, uncertainties about patient candidacy, cost, and logistical constraints. CONCLUSIONS: Provider concerns about buprenorphine-ER may limit utilization. Some concerns may be mitigated through improved education, research, and logistical support. Given the putative benefits of buprenorphine-ER, future research should target barriers to implementation, in part based on hypotheses generated by these findings.

Performance of Phenotype Algorithms for the Identification of Opioid-Exposed Infants.

OBJECTIVE: Observational studies examining outcomes among opioid-exposed infants are limited by phenotype algorithms that may under identify opioid-exposed infants without neonatal opioid withdrawal syndrome (NOWS). We developed and validated the performance of different phenotype algorithms to identify opioid-exposed infants using electronic health record data. METHODS: We developed phenotype algorithms for the identification of opioid-exposed infants among a population of birthing person-infant dyads from an academic health care system (2010-2022). We derived phenotype algorithms from combinations of 6 unique indicators of in utero opioid exposure, including those from the infant record (NOWS or opioid-exposure diagnosis, positive toxicology) and birthing person record (opioid use disorder diagnosis, opioid drug exposure record, opioid listed on medication reconciliation, positive toxicology). We determined the positive predictive value (PPV) and 95% confidence interval for each phenotype algorithm using medical record review as the gold standard. RESULTS: Among 41 047 dyads meeting exclusion criteria, we identified 1558 infants (3.80%) with evidence of at least 1 indicator for opioid exposure and 32 (0.08%) meeting all 6 indicators of the phenotype algorithm. Among the sample of dyads randomly selected for review (n = 600), the PPV for the phenotype requiring only a single indicator was 95.4% (confidence interval: 93.3-96.8) with varying PPVs for the other phenotype algorithms derived from a combination of infant and birthing person indicators (PPV range: 95.4-100.0). CONCLUSIONS: Opioid-exposed infants can be accurately identified using electronic health record data. Our publicly available phenotype algorithms can be used to conduct research examining outcomes among opioid-exposed infants with and without NOWS.

Factors Associated with Acute Telemental Health Consultations in Older Veterans.

Introduction: The United States Veterans Health Administration is a leader in the use of telemental health (TMH) to enhance access to mental healthcare amidst a nationwide shortage of mental health professionals. The Tennessee Valley Veterans Affairs (VA) Health System piloted TMH in its emergency department (ED) and urgent care clinic (UCC) in 2019, with full 24/7 availability beginning March 1, 2020. Following implementation, preliminary data demonstrated that veterans ≥65 years old were less likely to receive TMH than younger patients. We sought to examine factors associated with older veterans receiving TMH consultations in acute, unscheduled, outpatient settings to identify limitations in the current process. Methods: This was a retrospective cohort study conducted within the Tennessee Valley VA Health System. We included veterans ≥55 years who received a mental health consultation in the ED or UCC from April 1, 2020-September 30, 2022. Telemental health was administered by a mental health clinician (attending physician, resident physician, nurse practitioner, or physician assistant) via iPad, whereas in-person evaluations were performed in the ED. We examined the influence of patient demographics, visit timing, chief complaint, and psychiatric history on TMH, using multivariable logistic regression. Results: Of the 254 patients included in this analysis, 177 (69.7%) received TMH. Veterans with high-risk chief complaints (suicidal ideation, homicidal ideation, or agitation) were less likely to receive TMH consultation (adjusted odds ratio [AOR]: 0.47, 95% confidence interval [CI] 0.24-0.95). Compared to attending physicians, nurse practitioners and physician assistants were associated with increased TMH use (AOR 4.81, 95% CI 2.04-11.36), whereas consultation by resident physicians was associated with decreased TMH use (AOR 0.04, 95% CI 0.00-0.59). The UCC used TMH for all but one encounter. Patient characteristics including their visit timing, gender, additional medical complaints, comorbidity burden, and number of psychoactive medications did not influence use of TMH. Conclusion: High-risk chief complaints, location, and type of mental health clinician may be key determinants of telemental health use in older adults. This may help expand mental healthcare access to areas with a shortage of mental health professionals and prevent potentially avoidable transfers in low-acuity situations. Further studies and interventions may optimize TMH for older patients to ensure safe, equitable mental health care.

Determinants of appropriate antibiotic and NSAID prescribing in unscheduled outpatient settings in the veterans health administration.

BACKGROUND: Despite efforts to enhance the quality of medication prescribing in outpatient settings, potentially inappropriate prescribing remains common, particularly in unscheduled settings where patients can present with infectious and pain-related complaints. Two of the most commonly prescribed medication classes in outpatient settings with frequent rates of potentially inappropriate prescribing include antibiotics and nonsteroidal anti-inflammatory drugs (NSAIDs). In the setting of persistent inappropriate prescribing, we sought to understand a diverse set of perspectives on the determinants of inappropriate prescribing of antibiotics and NSAIDs in the Veterans Health Administration. METHODS: We conducted a qualitative study guided by the Consolidated Framework for Implementation Research and Theory of Planned Behavior. Semi-structured interviews were conducted with clinicians, stakeholders, and Veterans from March 1, 2021 through December 31, 2021 within the Veteran Affairs Health System in unscheduled outpatient settings at the Tennessee Valley Healthcare System. Stakeholders included clinical operations leadership and methodological experts. Audio-recorded interviews were transcribed and de-identified. Data coding and analysis were conducted by experienced qualitative methodologists adhering to the Consolidated Criteria for Reporting Qualitative Studies guidelines. Analysis was conducted using an iterative inductive/deductive process. RESULTS: We conducted semi-structured interviews with 66 participants: clinicians (N = 25), stakeholders (N = 24), and Veterans (N = 17). We identified six themes contributing to potentially inappropriate prescribing of antibiotics and NSAIDs: 1) Perceived versus actual Veterans expectations about prescribing; 2) the influence of a time-pressured clinical environment on prescribing stewardship; 3) Limited clinician knowledge, awareness, and willingness to use evidence-based care; 4) Prescriber uncertainties about the Veteran condition at the time of the clinical encounter; 5) Limited communication; and 6) Technology barriers of the electronic health record and patient portal. CONCLUSIONS: The diverse perspectives on prescribing underscore the need for interventions that recognize the detrimental impact of high workload on prescribing stewardship and the need to design interventions with the end-user in mind. This study revealed actionable themes that could be addressed to improve guideline concordant prescribing to enhance the quality of prescribing and to reduce patient harm.

Implementable Prediction of Pressure Injuries in Hospitalized Adults: Model Development and Validation.

Background: Numerous pressure injury prediction models have been developed using electronic health record data, yet hospital-acquired pressure injuries (HAPIs) are increasing, which demonstrates the critical challenge of implementing these models in routine care. Objective: To help bridge the gap between development and implementation, we sought to create a model that was feasible, broadly applicable, dynamic, actionable, and rigorously validated and then compare its performance to usual care (ie, the Braden scale). Methods: We extracted electronic health record data from 197,991 adult hospital admissions with 51 candidate features. For risk prediction and feature selection, we used logistic regression with a least absolute shrinkage and selection operator (LASSO) approach. To compare the model with usual care, we used the area under the receiver operating curve (AUC), Brier score, slope, intercept, and integrated calibration index. The model was validated using a temporally staggered cohort. Results: A total of 5458 HAPIs were identified between January 2018 and July 2022. We determined 22 features were necessary to achieve a parsimonious and highly accurate model. The top 5 features included tracheostomy, edema, central line, first albumin measure, and age. Our model achieved higher discrimination than the Braden scale (AUC 0.897, 95% CI 0.893-0.901 vs AUC 0.798, 95% CI 0.791-0.803). Conclusions: We developed and validated an accurate prediction model for HAPIs that surpassed the standard-of-care risk assessment and fulfilled necessary elements for implementation. Future work includes a pragmatic randomized trial to assess whether our model improves patient outcomes.

Impact of inpatient addiction psychiatry consultation on opioid use disorder outcomes.

BACKGROUND AND OBJECTIVES: Addiction consultation services provide access to specialty addiction care during general hospital admission. This study assessed opioid use disorder (OUD) outcomes associated with addiction consultation. METHODS: Retrospective cohort study of individuals with OUD admitted to an academic medical center between 2018 and 2023. The exposure was addiction consultation. Outcomes included initiating medication for OUD (MOUD), hospital length of stay, before-medically-advised (BMA) discharge, and 30- and 90-day postdischarge acute care utilization. RESULTS: Of 26,766 admissions (10,501 patients) with OUD, 2826 addiction consultations were completed. Consultation cohort was more likely to be young, male, and White than controls. Consultation was associated with greater MOUD initiation (adjusted odds ratio [aOR], 5.07; 95% confidence interval [CI], 4.41-5.82), fewer emergency department visits at 30 (aOR, 0.78; 95% CI, 0.67-0.92) and 90 (aOR, 0.79; 95% CI, 0.69-0.89) days, and fewer hospitalizations at 30 (aOR, 0.65; 95% CI, 0.56 to 0.76) and 90 (aOR, 0.67; 95% CI, 0.59-0.76) days. Additionally, consultation patients were more likely to have a longer hospital stay and leave BMA. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: Addiction consultation was associated with increased MOUD initiation and reduced postdischarge acute care utilization. This is the largest study to date showing a significant association between addiction psychiatry consultation and improved OUD outcomes when compared to controls. The observed reduction in postdischarge acute care utilization remains even after adjusting for MOUD initiation. Disparities in access to addiction consultation warrant further study.

Medical and genetic correlates of long-term buprenorphine treatment in the electronic health records.

Despite the benefits associated with longer buprenorphine treatment duration (i.e., >180 days) (BTD) for opioid use disorder (OUD), retention remains poor. Research on the impact of co-occurring psychiatric issues on BTD has yielded mixed results. It is also unknown whether the genetic risk in the form of polygenic scores (PGS) for OUD and other comorbid conditions, including problematic alcohol use (PAU) are associated with BTD. We tested the association between somatic and psychiatric comorbidities and long BTD and determined whether PGS for OUD-related conditions was associated with BTD. The study included 6686 individuals with a buprenorphine prescription that lasted for less than 6 months (short-BTD) and 1282 individuals with a buprenorphine prescription that lasted for at least 6 months (long-BTD). Recorded diagnosis of substance addiction and disorders (Odds Ratio (95% CI) = 22.14 (21.88-22.41), P = 2.8 × 10-116), tobacco use disorder (OR (95% CI) = 23.4 (23.13-23.68), P = 4.5 × 10-111), and bipolar disorder (OR(95% CI) = 9.70 (9.48-9.92), P = 1.3 × 10-91), among others, were associated with longer BTD. The PGS of OUD and several OUD co-morbid conditions were associated with any buprenorphine prescription. A higher PGS for OUD (OR per SD increase in PGS (95%CI) = 1.43(1.16-1.77), P = 0.0009), loneliness (OR(95% CI) = 1.39(1.13-1.72), P = 0.002), problematic alcohol use (OR(95%CI) = 1.47(1.19-1.83), P = 0.0004), and externalizing disorders (OR(95%CI) = 1.52(1.23 to 1.89), P = 0.0001) was significantly associated with long-BTD. Associations between BTD and the PGS of depression, chronic pain, nicotine dependence, cannabis use disorder, and bipolar disorder did not survive correction for multiple testing. Longer BTD is associated with diagnoses of psychiatric and somatic conditions in the EHR, as is the genetic score for OUD, loneliness, problematic alcohol use, and externalizing disorders.

Development and Validation of a Machine Learning Algorithm Using Clinical Pages to Predict Imminent Clinical Deterioration.

BACKGROUND: Early detection of clinical deterioration among hospitalized patients is a clinical priority for patient safety and quality of care. Current automated approaches for identifying these patients perform poorly at identifying imminent events. OBJECTIVE: Develop a machine learning algorithm using pager messages sent between clinical team members to predict imminent clinical deterioration. DESIGN: We conducted a large observational study using long short-term memory machine learning models on the content and frequency of clinical pages. PARTICIPANTS: We included all hospitalizations between January 1, 2018 and December 31, 2020 at Vanderbilt University Medical Center that included at least one page message to physicians. Exclusion criteria included patients receiving palliative care, hospitalizations with a planned intensive care stay, and hospitalizations in the top 2% longest length of stay. MAIN MEASURES: Model classification performance to identify in-hospital cardiac arrest, transfer to intensive care, or Rapid Response activation in the next 3-, 6-, and 12-hours. We compared model performance against three common early warning scores: Modified Early Warning Score, National Early Warning Score, and the Epic Deterioration Index. KEY RESULTS: There were 87,783 patients (mean [SD] age 54.0 [18.8] years; 45,835 [52.2%] women) who experienced 136,778 hospitalizations. 6214 hospitalized patients experienced a deterioration event. The machine learning model accurately identified 62% of deterioration events within 3-hours prior to the event and 47% of events within 12-hours. Across each time horizon, the model surpassed performance of the best early warning score including area under the receiver operating characteristic curve at 6-hours (0.856 vs. 0.781), sensitivity at 6-hours (0.590 vs. 0.505), specificity at 6-hours (0.900 vs. 0.878), and F-score at 6-hours (0.291 vs. 0.220). CONCLUSIONS: Machine learning applied to the content and frequency of clinical pages improves prediction of imminent deterioration. Using clinical pages to monitor patient acuity supports improved detection of imminent deterioration without requiring changes to clinical workflow or nursing documentation.

Using intervention mapping to design and implement a multicomponent intervention to improve antibiotic and NSAID prescribing.

Successfully changing prescribing behavior to reduce inappropriate antibiotic and nonsteroidal anti-inflammatory drug (NSAID) prescriptions often requires combining components into a multicomponent intervention. However, multicomponent interventions often fail because of development and implementation complexity. To increase the likelihood of successfully changing prescribing behavior, we applied a systematic process to design and implement a multicomponent intervention. We used Intervention Mapping to create a roadmap for a multicomponent intervention in unscheduled outpatient care settings in the Veterans Health Administration. Intervention Mapping is a systematic process consisting of six steps that we grouped into three phases: (i) understand behavioral determinants and barriers to implementation, (ii) develop the intervention, and (iii) define evaluation plan and implementation strategies. A targeted literature review, combined with 25 prescriber and 25 stakeholder interviews, helped identify key behavioral determinants to inappropriate prescribing (e.g. perceived social pressure from patients to prescribe). We targeted three desired prescriber behaviors: (i) review guideline-concordant prescribing and patient outcomes, (ii) manage diagnostic and treatment uncertainty, and (iii) educate patients and caregivers. The intervention consisted of components for academic detailing, prescribing feedback, and alternative prescription order sets. Implementation strategies consisted of preparing clinical champions, conducting readiness assessments, and incentivizing use of the intervention. We chose a mixed-method study design with a commonly used evaluation framework to assess effectiveness and implementation outcomes in a subsequent trial. This study furthers knowledge about causes of inappropriate antibiotic and NSAID prescribing and demonstrates how theoretical, empirical, and practical information can be systematically applied to develop a multicomponent intervention to help address these causes.

Reducing adverse drug events from antibiotics and nonsteroidal anti-inflammatory drugs (NSAIDs) is a patient safety priority. Successfully changing prescribing behavior to reduce inappropriate prescriptions can require combining intervention components, each with different mechanisms for behavior change, into a multicomponent intervention. However, multicomponent interventions often fail because of development and implementation complexity. To increase the chance of successfully changing antibiotic and NSAID prescribing, the objective this study was to apply a systematic process to design and implement a multicomponent intervention. Three desired prescriber behaviors were targeted: (i) review guideline-concordant prescribing and patient outcomes, (ii) manage diagnostic and treatment uncertainty, and (iii) educate patients and caregivers. The designed intervention consisted of components for prescribing feedback, academic detailing, and alternative prescription order sets. Strategies to improve use of the intervention consisted of preparing clinical champions, conducting readiness assessments prior to study onset, and incentivizing use of the intervention. We chose a mixed-method study design with a commonly used evaluation framework to assess effectiveness and implementation outcomes of the multicomponent intervention in a subsequent trial.

Modification of the synaptic cleft under excitatory conditions.

The synaptic cleft is the extracellular part of the synapse, bridging the pre- and postsynaptic membranes. The geometry and molecular organization of the cleft is gaining increased attention as an important determinant of synaptic efficacy. The present study by electron microscopy focuses on short-term morphological changes at the synaptic cleft under excitatory conditions. Depolarization of cultured hippocampal neurons with high K+ results in an increased frequency of synaptic profiles with clefts widened at the periphery (open clefts), typically exhibiting patches of membranes lined by postsynaptic density, but lacking associated presynaptic membranes (18.0% open clefts in high K+ compared to 1.8% in controls). Similarly, higher frequencies of open clefts were observed in adult brain upon a delay of perfusion fixation to promote excitatory/ischemic conditions. Inhibition of basal activity in cultured neurons through the application of TTX results in the disappearance of open clefts whereas application of NMDA increases their frequency (19.0% in NMDA vs. 5.3% in control and 2.6% in APV). Depletion of extracellular Ca2+ with EGTA also promotes an increase in the frequency of open clefts (16.6% in EGTA vs. 4.0% in controls), comparable to that by depolarization or NMDA, implicating dissociation of Ca2+-dependent trans-synaptic bridges. Dissociation of transsynaptic bridges under excitatory conditions may allow perisynaptic mobile elements, such as AMPA receptors to enter the cleft. In addition, peripheral opening of the cleft would facilitate neurotransmitter clearance and thus may have a homeostatic and/or protective function.

POINT: Pipeline for Offline Conversion and Integration of Geocodes and Neighborhood Data.

OBJECTIVES: Geocoding, the process of converting addresses into precise geographic coordinates, allows researchers and health systems to obtain neighborhood-level estimates of social determinants of health. This information supports opportunities to personalize care and interventions for individual patients based on the environments where they live. We developed an integrated offline geocoding pipeline to streamline the process of obtaining address-based variables, which can be integrated into existing data processing pipelines. METHODS: POINT is a web-based, containerized, application for geocoding addresses that can be deployed offline and made available to multiple users across an organization. Our application supports use through both a graphical user interface and application programming interface to query geographic variables, by census tract, without exposing sensitive patient data. We evaluated our application's performance using two datasets: one consisting of 1 million nationally representative addresses sampled from Open Addresses, and the other consisting of 3,096 previously geocoded patient addresses. RESULTS: A total of 99.4 and 99.8% of addresses in the Open Addresses and patient addresses datasets, respectively, were geocoded successfully. Census tract assignment was concordant with reference in greater than 90% of addresses for both datasets. Among successful geocodes, median (interquartile range) distances from reference coordinates were 52.5 (26.5-119.4) and 14.5 (10.9-24.6) m for the two datasets. CONCLUSION: POINT successfully geocodes more addresses and yields similar accuracy to existing solutions, including the U.S. Census Bureau's official geocoder. Addresses are considered protected health information and cannot be shared with common online geocoding services. POINT is an offline solution that enables scalability to multiple users and integrates downstream mapping to neighborhood-level variables with a pipeline that allows users to incorporate additional datasets as they become available. As health systems and researchers continue to explore and improve health equity, it is essential to quickly and accurately obtain neighborhood variables in a Health Insurance Portability and Accountability Act (HIPAA)-compliant way.

Leveraging natural language processing to identify eligible lung cancer screening patients with the electronic health record.

OBJECTIVE: To develop and validate an approach that identifies patients eligible for lung cancer screening (LCS) by combining structured and unstructured smoking data from the electronic health record (EHR). METHODS: We identified patients aged 50-80 years who had at least one encounter in a primary care clinic at Vanderbilt University Medical Center (VUMC) between 2019 and 2022. We fine-tuned an existing natural language processing (NLP) tool to extract quantitative smoking information using clinical notes collected from VUMC. Then, we developed an approach to identify patients who are eligible for LCS by combining smoking information from structured data and clinical narratives. We compared this method with two approaches to identify LCS eligibility only using smoking information from structured EHR. We used 50 patients with a documented history of tobacco use for comparison and validation. RESULTS: 102,475 patients were included. The NLP-based approach achieved an F1-score of 0.909, and accuracy of 0.96. The baseline approach could identify 5,887 patients. Compared to the baseline approach, the number of identified patients using all structured data and the NLP-based algorithm was 7,194 (22.2 %) and 10,231 (73.8 %), respectively. The NLP-based approach identified 589 Black/African Americans, a significant increase of 119 %. CONCLUSION: We present a feasible NLP-based approach to identify LCS eligible patients. It provides a technical basis for the development of clinical decision support tools to potentially improve the utilization of LCS and diminish healthcare disparities.

Impact of notification policy on patient-before-clinician review of immediately released test results.

The 21st Century Cures Act mandates immediate availability of test results upon request. The Cures Act does not require that patients be informed of results, but many organizations send notifications when results become available. Our medical center implemented 2 sequential policies: immediate notifications for all results, and notifications only to patients who opt in. We used over 2 years of data from Vanderbilt University Medical Center to measure the effect of these policies on rates of patient-before-clinician result review and patient-initiated messaging using interrupted time series analysis. When releasing test results with immediate notification, the proportion of patient-before-clinician review increased 4-fold and the proportion of patients who sent messages rose 3%. After transition to opt-in notifications, patient-before-clinician review decreased 2.4% and patient-initiated messaging decreased 0.4%. Replacing automated notifications with an opt-in policy provides patients flexibility to indicate their preferences but may not substantially alleviate clinicians' messaging workload.

Transsynaptic Assemblies Link Domains of Presynaptic and Postsynaptic Intracellular Structures across the Synaptic Cleft.

The chemical synapse is a complex machine separated into three parts: presynaptic, postsynaptic, and cleft. Super-resolution light microscopy has revealed alignment of presynaptic vesicle release machinery and postsynaptic neurotransmitter-receptors and scaffolding components in synapse spanning nanocolumns. Cryo-electron tomography confirmed that postsynaptic glutamate receptor-like structures align with presynaptic structures in proximity to synaptic vesicles into transsynaptic assemblies. In our electron tomographic renderings, nearly all transcleft structures visibly connect to intracellular structures through transmembrane structures to form transsynaptic assemblies, potentially providing a structural basis for transsynaptic alignment. Here, we describe the patterns of composition, distribution, and interactions of all assemblies spanning the synapse by producing three-dimensional renderings of all visibly connected structures in excitatory and inhibitory synapses in dissociated rat hippocampal neuronal cultures of both sexes prepared by high-pressure freezing and freeze-substitution. The majority of transcleft structures connect to material in both presynaptic and postsynaptic compartments. We found several instances of assemblies connecting to both synaptic vesicles and postsynaptic density scaffolding. Each excitatory synaptic vesicle within 30 nm of the active zone contacts one or more assembly. Further, intracellular structures were often shared between assemblies, entangling them to form larger complexes or association domains, often in small clusters of vesicles. Our findings suggest that transsynaptic assemblies physically connect the three compartments, allow for coordinated molecular organization, and may combine to form specialized functional association domains, resembling the light-level nanocolumns.SIGNIFICANCE STATEMENT A recent tomographic study uncovered that receptor-like cleft structures align across the synapse. These aligned structures were designated as transsynaptic assemblies and demonstrate the coordinated organization of synaptic transmission molecules between compartments. Our present tomographic study expands on the definition of transsynaptic assemblies by analyzing the three-dimensional distribution and connectivity of all cleft-spanning structures and their connected intracellular structures. While one-to-one component alignment occurs across the synapse, we find that many assemblies share components, leading to a complex entanglement of assemblies, typically around clusters of synaptic vesicles. Transsynaptic assemblies appear to form domains which may be the structural basis for alignment of molecular nanodomains into synapse spanning nanocolumns described by super-resolution light microscopy.

Cryo-EM tomography and automatic segmentation delineate modular structures in the postsynaptic density.

Postsynaptic densities (PSDs) are large protein complexes associated with the postsynaptic membrane of excitatory synapses important for synaptic function including plasticity. Conventional electron microscopy (EM) typically depicts PSDs as compact disk-like structures of hundreds of nanometers in size. Biochemically isolated PSDs were also similar in dimension revealing a predominance of proteins with the ability to polymerize into an extensive scaffold; several EM studies noted their irregular contours with often small granular structures (<30 nm) and holes. Super-resolution light microscopy studies observed clusters of PSD elements and their activity-induced lateral movement. Furthermore, our recent EM study on PSD fractions after sonication observed PSD fragments (40-90 nm in size) separate from intact PSDs; however, such structures within PSDs remained unidentified. Here we examined isolated PSDs by cryo-EM tomography with our new approach of automatic segmentation that enables delineation of substructures and their quantitative analysis. The delineated substructures broadly varied in size, falling behind 30 nm or exceeding 100 nm and showed that a considerable portion of the substructures (>38%) in isolated PSDs was in the same size range as those fragments. Furthermore, substructures spanning the entire thickness of the PSD were found, large enough to contain both membrane-associated and cytoplasmic proteins of the PSD; interestingly, they were similar to nanodomains in frequency. The structures detected here appear to constitute the isolated PSD as modules of various compositions, and this modular nature may facilitate remodeling of the PSD for proper synaptic function and plasticity.

Perspectives of Patients About Immediate Access to Test Results Through an Online Patient Portal.

Importance: The 21st Century Cures Act Final Rule mandates the immediate electronic availability of test results to patients, likely empowering them to better manage their health. Concerns remain about unintended effects of releasing abnormal test results to patients. Objective: To assess patient and caregiver attitudes and preferences related to receiving immediately released test results through an online patient portal. Design, Setting, and Participants: This large, multisite survey study was conducted at 4 geographically distributed academic medical centers in the US using an instrument adapted from validated surveys. The survey was delivered in May 2022 to adult patients and care partners who had accessed test results via an online patient portal account between April 5, 2021, and April 4, 2022. Exposures: Access to test results via a patient portal between April 5, 2021, and April 4, 2022. Main Outcomes and Measures: Responses to questions related to demographics, test type and result, reaction to result, notification experience and future preferences, and effect on health and well-being were aggregated. To evaluate characteristics associated with patient worry, logistic regression and pooled random-effects models were used to assess level of worry as a function of whether test results were perceived by patients as normal or not normal and whether patients were precounseled. Results: Of 43 380 surveys delivered, there were 8139 respondents (18.8%). Most respondents were female (5129 [63.0%]) and spoke English as their primary language (7690 [94.5%]). The median age was 64 years (IQR, 50-72 years). Most respondents (7520 of 7859 [95.7%]), including 2337 of 2453 individuals (95.3%) who received nonnormal results, preferred to immediately receive test results through the portal. Few respondents (411 of 5473 [7.5%]) reported that reviewing results before they were contacted by a health care practitioner increased worry, though increased worry was more common among respondents who received abnormal results (403 of 2442 [16.5%]) than those whose results were normal (294 of 5918 [5.0%]). The result of the pooled model for worry as a function of test result normality was statistically significant (odds ratio [OR], 2.71; 99% CI, 1.96-3.74), suggesting an association between worry and nonnormal results. The result of the pooled model evaluating the association between worry and precounseling was not significant (OR, 0.70; 99% CI, 0.31-1.59). Conclusions and Relevance: In this multisite survey study of patient attitudes and preferences toward receiving immediately released test results via a patient portal, most respondents preferred to receive test results via the patient portal despite viewing results prior to discussion with a health care professional. This preference persisted among patients with nonnormal results.

Rapid-cycle designs to adapt interventions for COVID-19 in safety-net healthcare systems.

Racial/ethnic minority, low socioeconomic status, and rural populations are disproportionately affected by COVID-19. Developing and evaluating interventions to address COVID-19 testing and vaccination among these populations are crucial to improving health inequities. The purpose of this paper is to describe the application of a rapid-cycle design and adaptation process from an ongoing trial to address COVID-19 among safety-net healthcare system patients. The rapid-cycle design and adaptation process included: (a) assessing context and determining relevant models/frameworks; (b) determining core and modifiable components of interventions; and (c) conducting iterative adaptations using Plan-Do-Study-Act (PDSA) cycles. PDSA cycles included: Plan. Gather information from potential adopters/implementers (e.g., Community Health Center [CHC] staff/patients) and design initial interventions; Do. Implement interventions in single CHC or patient cohort; Study. Examine process, outcome, and context data (e.g., infection rates); and, Act. If necessary, refine interventions based on process and outcome data, then disseminate interventions to other CHCs and patient cohorts. Seven CHC systems with 26 clinics participated in the trial. Rapid-cycle, PDSA-based adaptations were made to adapt to evolving COVID-19-related needs. Near real-time data used for adaptation included data on infection hot spots, CHC capacity, stakeholder priorities, local/national policies, and testing/vaccine availability. Adaptations included those to study design, intervention content, and intervention cohorts. Decision-making included multiple stakeholders (e.g., State Department of Health, Primary Care Association, CHCs, patients, researchers). Rapid-cycle designs may improve the relevance and timeliness of interventions for CHCs and other settings that provide care to populations experiencing health inequities, and for rapidly evolving healthcare challenges such as COVID-19.

Racial/ethnic minority, low socioeconomic status, and rural populations experience a disproportionate burden of COVID-19. Finding ways to address COVID-19 among these populations is crucial to improving health inequities. The purpose of this paper is to describe the rapid-cycle design process for a research project to address COVID-19 testing and vaccination among safety-net healthcare system patients. The project used real-time information on changes in COVID-19 policy (e.g., vaccination authorization), local case rates, and the capacity of safety-net healthcare systems to iteratively change interventions to ensure interventions were relevant and timely for patients. Key changes that were made to interventions included a change to the study design to include vaccination as a focus of the interventions after the vaccine was authorized; change in intervention content according to the capacity of local Community Health Centers to provide testing to patients; and changes to intervention cohorts such that priority groups of patients were selected for intervention based on characteristics including age, residency in an infection "hot spot," or race/ethnicity. Iteratively improving interventions based on real-time data collection may increase intervention relevance and timeliness, and rapid-cycle adaptions can be successfully implemented in resource constrained settings like safety-net healthcare systems.

The effect of telemental versus in-person mental health consults in the emergency department on 30-day utilization and processes of care.

OBJECTIVES: We sought to characterize how telemental health (TMH) versus in-person mental health consults affected 30-day postevaluation utilization outcomes and processes of care in Veterans presenting to the emergency department (ED) and urgent care clinic (UCC) with acute psychiatric complaints. METHODS: This exploratory retrospective cohort study was conducted in an ED and UCC located in a single Veterans Affairs system. A mental health provider administered TMH via iPad. The primary outcome was a composite of return ED/UCC visits, rehospitalizations, or death within 30 days. The following processes of care were collected during the index visit: changes to home psychiatric medications, admission, involuntary psychiatric hold placement, parenteral benzodiazepine or antipsychotic medication use, and physical restraints or seclusion. Data were abstracted from the Veterans Affairs electronic health record and the Clinical Data Warehouse. Multivariable logistic regression was performed. Adjusted odds ratios (aORs) with their 95% confidence intervals (95% CIs) were reported. RESULTS: Of the 496 Veterans in this analysis, 346 (69.8%) received TMH, and 150 (30.2%) received an in-person mental health evaluation. There was no significant difference in the primary outcome of 30-day return ED/UCC, rehospitalization, or death (aOR 1.47, 95% CI 0.87-2.49) between the TMH and in-person groups. TMH was significantly associated with increased ED/UCC length of stay (aOR 1.46, 95% CI 1.03-2.06) and decreased use of involuntary psychiatric holds (aOR 0.42, 95% CI 0.23-0.75). There were no associations between TMH and the other processes-of-care outcomes. CONCLUSIONS: TMH was not significantly associated with the 30-day composite outcome of return ED/UCC visits, rehospitalizations, and death compared with traditional in-person mental health evaluations. TMH was significantly associated with increased ED/UCC length of stay and decreased odds of placing an involuntary psychiatric hold. Future studies are required to confirm these findings and, if confirmed, explore the potential mechanisms for these associations.