Predicting risk of suicidal behavior from insurance claims data vs. linked data from insurance claims and electronic health records.

PURPOSE: Observational studies assessing effects of medical products on suicidal behavior often rely on health record data to account for pre-existing risk. We assess whether high-dimensional models predicting suicide risk using data derived from insurance claims and electronic health records (EHRs) are superior to models using data from insurance claims alone. METHODS: Data were from seven large health systems identified outpatient mental health visits by patients aged 11 or older between 1/1/2009 and 9/30/2017. Data for the 5 years prior to each visit identified potential predictors of suicidal behavior typically available from insurance claims (e.g., mental health diagnoses, procedure codes, medication dispensings) and additional potential predictors available from EHRs (self-reported race and ethnicity, responses to Patient Health Questionnaire or PHQ-9 depression questionnaires). Nonfatal self-harm events following each visit were identified from insurance claims data and fatal self-harm events were identified by linkage to state mortality records. Random forest models predicting nonfatal or fatal self-harm over 90 days following each visit were developed in a 70% random sample of visits and validated in a held-out sample of 30%. Performance of models using linked claims and EHR data was compared to models using claims data only. RESULTS: Among 15 845 047 encounters by 1 574 612 patients, 99 098 (0.6%) were followed by a self-harm event within 90 days. Overall classification performance did not differ between the best-fitting model using all data (area under the receiver operating curve or AUC = 0.846, 95% CI 0.839-0.854) and the best-fitting model limited to data available from insurance claims (AUC = 0.846, 95% CI 0.838-0.853). Competing models showed similar classification performance across a range of cut-points and similar calibration performance across a range of risk strata. Results were similar when the sample was limited to health systems and time periods where PHQ-9 depression questionnaires were recorded more frequently. CONCLUSION: Investigators using health record data to account for pre-existing risk in observational studies of suicidal behavior need not limit that research to databases including linked EHR data.

Cost of Implementing an Evidence-Based Intervention to Support Safer Use of Antipsychotics in Youth.

To estimate the cost of implementing a clinical program designed to support safer use of antipsychotics in children and adolescents (youth) age 3-17 years at the time of initiating an antipsychotic medication. We calculate the costs of implementing a psychiatric consultation and navigation program for youth prescribed antipsychotic medications across 4 health systems, which included an electronic health record (EHR) decision support tool, consultation with a child and adolescent psychiatrist, and up to 6 months of behavioral health care navigation, as well as telemental health for patients (n = 348). Cost data were collected for both start-up and ongoing intervention phases and are estimated over a 1-year period. Data sources included study records and time-in-motion reports, analyzed from a health system perspective. Costs included both labor and nonlabor costs (2019 US dollars). The average total start-up and ongoing costs per health system were $34,007 and $185,174, respectively. The average total cost per patient was $2,128. The highest average ongoing labor cost components were telemental health ($901 per patient), followed by child and adolescent psychiatrist consultation ($659), and the lowest cost component was primary care/behavioral health provider time to review/respond to the EHR decision support tool and case consultation ($24). For health systems considering programs to promote safer and targeted use of antipsychotics among youth, this study provides estimates of the full start-up and ongoing costs of an EHR decision support tool, psychiatric consultation service, and psychotherapeutic services for patients and families.Trial registration: Clinicaltrials.gov, NCT03448575.

Suicide Deaths Before and During the Coronavirus Disease 2019 Pandemic: An Interrupted Time-series Study.

INTRODUCTION: With stressors that are often associated with suicide increasing during the coronavirus disease 2019 (COVID-19) pandemic, there has been concern that suicide mortality rates may also be increasing. Our objective was to determine whether suicide mortality rates increased during the COVID-19 pandemic. METHODS: We conducted an interrupted time-series study using data from January 2019 through December 2020 from 2 large integrated health care systems. The population at risk included all patients or individuals enrolled in a health plan at HealthPartners in Minnesota or Henry Ford Health System in Michigan. The primary outcome was change in suicide mortality rates, expressed as annualized crude rates of suicide death per 100,000 people in 10 months following the start of the pandemic in March 2020 compared with the 14 months prior. RESULTS: There were 6,434,675 people at risk in the sample, with 55% women and a diverse sample across ages, race/ethnicity, and insurance type. From January 2019 through February 2020, there was a slow increase in the suicide mortality rate, with rates then decreasing by 0.45 per 100,000 people per month from March 2020 through December 2020 (SE=0.19, P=0.03). CONCLUSIONS: Overall suicide mortality rates did not increase with the pandemic, and in fact slightly declined from March to December 2020. Our findings should be confirmed across other settings and, when available, using final adjudicated state mortality data.

Development of a machine learning model to predict mild cognitive impairment using natural language processing in the absence of screening.

BACKGROUND: Patients and their loved ones often report symptoms or complaints of cognitive decline that clinicians note in free clinical text, but no structured screening or diagnostic data are recorded. These symptoms/complaints may be signals that predict who will go on to be diagnosed with mild cognitive impairment (MCI) and ultimately develop Alzheimer's Disease or related dementias. Our objective was to develop a natural language processing system and prediction model for identification of MCI from clinical text in the absence of screening or other structured diagnostic information. METHODS: There were two populations of patients: 1794 participants in the Adult Changes in Thought (ACT) study and 2391 patients in the general population of Kaiser Permanente Washington. All individuals had standardized cognitive assessment scores. We excluded patients with a diagnosis of Alzheimer's Disease, Dementia or use of donepezil. We manually annotated 10,391 clinic notes to train the NLP model. Standard Python code was used to extract phrases from notes and map each phrase to a cognitive functioning concept. Concepts derived from the NLP system were used to predict future MCI. The prediction model was trained on the ACT cohort and 60% of the general population cohort with 40% withheld for validation. We used a least absolute shrinkage and selection operator logistic regression approach (LASSO) to fit a prediction model with MCI as the prediction target. Using the predicted case status from the LASSO model and known MCI from standardized scores, we constructed receiver operating curves to measure model performance. RESULTS: Chart abstraction identified 42 MCI concepts. Prediction model performance in the validation data set was modest with an area under the curve of 0.67. Setting the cutoff for correct classification at 0.60, the classifier yielded sensitivity of 1.7%, specificity of 99.7%, PPV of 70% and NPV of 70.5% in the validation cohort. DISCUSSION AND CONCLUSION: Although the sensitivity of the machine learning model was poor, negative predictive value was high, an important characteristic of models used for population-based screening. While an AUC of 0.67 is generally considered moderate performance, it is also comparable to several tests that are widely used in clinical practice.

Effect of Offering Care Management or Online Dialectical Behavior Therapy Skills Training vs Usual Care on Self-harm Among Adult Outpatients With Suicidal Ideation: A Randomized Clinical Trial.

Importance: People at risk of self-harm or suicidal behavior can be accurately identified, but effective prevention will require effective scalable interventions. Objective: To compare 2 low-intensity outreach programs with usual care for prevention of suicidal behavior among outpatients who report recent frequent suicidal thoughts. Design, Setting, and Participants: Pragmatic randomized clinical trial including outpatients reporting frequent suicidal thoughts identified using routine Patient Health Questionnaire depression screening at 4 US integrated health systems. A total of 18 882 patients were randomized between March 2015 and September 2018, and ascertainment of outcomes continued through March 2020. Interventions: Patients were randomized to a care management intervention (n = 6230) that included systematic outreach and care, a skills training intervention (n = 6227) that introduced 4 dialectical behavior therapy skills (mindfulness, mindfulness of current emotion, opposite action, and paced breathing), or usual care (n = 6187). Interventions, lasting up to 12 months, were delivered primarily through electronic health record online messaging and were intended to supplement ongoing mental health care. Main Outcomes and Measures: The primary outcome was time to first nonfatal or fatal self-harm. Nonfatal self-harm was ascertained from health system records, and fatal self-harm was ascertained from state mortality data. Secondary outcomes included more severe self-harm (leading to death or hospitalization) and a broader definition of self-harm (selected injuries and poisonings not originally coded as self-harm). Results: A total of 18 644 patients (9009 [48%] aged 45 years or older; 12 543 [67%] female; 9222 [50%] from mental health specialty clinics and the remainder from primary care) contributed at least 1 day of follow-up data and were included in analyses. Thirty-one percent of participants offered care management and 39% offered skills training actively engaged in intervention programs. A total of 540 participants had a self-harm event (including 45 deaths attributed to self-harm and 495 nonfatal self-harm events) over 18 months following randomization: 172 (3.27%) in care management, 206 (3.92%) in skills training, and 162 (3.27%) in usual care. Risk of fatal or nonfatal self-harm over 18 months did not differ significantly between the care management and usual care groups (hazard ratio [HR], 1.07; 97.5% CI, 0.84-1.37) but was significantly higher in the skills training group than in usual care (HR, 1.29; 97.5% CI, 1.02-1.64). For severe self-harm, care management vs usual care had an HR of 1.03 (97.5% CI, 0.71-1.51); skills training vs usual care had an HR of 1.34 (97.5% CI, 0.94-1.91). For the broader self-harm definition, care management vs usual care had an HR of 1.10 (97.5% CI, 0.92-1.33); skills training vs usual care had an HR of 1.17 (97.5% CI, 0.97-1.41). Conclusions and Relevance: Among adult outpatients with frequent suicidal ideation, offering care management did not significantly reduce risk of self-harm, and offering brief dialectical behavior therapy skills training significantly increased risk of self-harm, compared with usual care. These findings do not support implementation of the programs tested in this study. Trial Registration: ClinicalTrials.gov Identifier: NCT02326883.

Changes in Clinician Attitudes Toward Sharing Visit Notes: Surveys Pre-and Post-Implementation.

BACKGROUND: Clinician perceptions before and after inviting patients to read office notes (open notes) are unknown. OBJECTIVE: To describe changes in clinicians' attitudes about sharing notes with patients. DESIGN, PARTICIPANTS, AND MAIN MEASURE: Survey of outpatient primary and specialty care clinicians who were from a large group practice and had one or more patients who accessed notes. The main outcome was percent change (before vs. after implementation) in clinician perception that online visit notes are beneficial overall. KEY RESULTS: Of the 563 invited clinicians, 400 (71%) took the baseline survey; 295 were eligible for a follow-up survey with 192 (65%) responding (119 primary care, 47 medical specialties, 26 surgical specialties). Before implementation, 29% agreed or somewhat agreed that visit notes online are beneficial overall, increasing to 71% following implementation (p<0.001); 44% switched beliefs from bad to good idea; and 2% reported the opposite change (p<0.001). This post-implementation change was observed in all clinician categories. Compared to pre-implementation, fewer clinicians had concerns about office visits taking longer (47% pre vs. 15% post) or requiring more time for questions (71% vs. 16%), or producing notes (57% vs. 28%). Before and after implementation, most clinicians reported being less candid in documentation (65% vs. 52%) and that patients would have more control of their care (72% vs. 78%) and worry more (72% vs. 65%). CONCLUSIONS: Following implementation, more primary and specialty care clinicians agreed that sharing notes with patients online was beneficial overall. Fewer had concerns about more time needed for office visits or documentation. Most thought patients would worry more and reported being less candid in documentation.

If You Listen, I Will Talk: the Experience of Being Asked About Suicidality During Routine Primary Care.

BACKGROUND: Routine population-based screening for depression is an essential part of evolving health care models integrating care for mental health in primary care. Depression instruments often include questions about suicidal thoughts, but how patients experience these questions in primary care is not known and may have implications for accurate identification of patients at risk. OBJECTIVES: To explore the patient experience of routine population-based depression screening/assessment followed, for some, by suicide risk assessment and discussions with providers. DESIGN: Qualitative, interview-based study. PARTICIPANTS: Thirty-seven patients from Kaiser Permanente Washington who had recently screened positive for depression on the 2-item Patient Health Questionnaire [PHQ] and completed the full PHQ-9. APPROACH: Criterion sampling identified patients who had recently completed the PHQ-9 ninth question which asks about the frequency of thoughts about self-harm. Patients completed semi-structured interviews by phone, which were recorded and transcribed. Directive and conventional content analyses were used to apply knowledge from prior research and elucidate new information from interviews; thematic analysis was used to organize key content overall and across groups based on endorsement of suicide ideation. KEY RESULTS: Four main organizing themes emerged from analyses: (1) Participants believed being asked about suicidality was contextually appropriate and valuable, (2) some participants described a mismatch between their lived experience and the PHQ-9 ninth question, (3) suicidality disclosures involved weighing hope for help against fears of negative consequences, and (4) provider relationships and acts of listening and caring facilitated discussions about suicidality. CONCLUSIONS: All participants believed being asked questions about suicidal thoughts was appropriate, though some who disclosed suicidal thoughts described experiencing stigma and sometimes distanced themselves from suicidality. Direct communication with trusted providers, who listened and expressed empathy, bolstered comfort with disclosure. Future research should consider strategies for reducing stigma and encouraging fearless disclosure among primary care patients experiencing suicidality.

Team-Based Clinic Redesign of Opioid Medication Management in Primary Care: Effect on Opioid Prescribing.

PURPOSE: Six key elements of opioid medication management redesign in primary care have been previously identified. Here, we examine the effect of implementing these Six Building Blocks on opioid-prescribing practices. METHODS: Six rural-serving organizations with 20 clinic locations received support for 15 months during the period October 2015 to May 2017 to implement the Six Building Blocks. Patients undergoing long-term opioid therapy (LtOT) at these study sites were compared with patients undergoing LtOT enrolled in a regional health plan who did not receive care at the study sites but who resided in the same primary care service areas (control group). Outcomes were monthly trend in the proportion of patients undergoing LtOT prescribed a ≥100 morphine equivalent dose (MED) of opioids daily and the total number of patients receiving an opioid prescription. An interrupted time series using difference-indifference analysis was used for tests of significance. RESULTS: The proportion of patients prescribed a ≥100 MED of opioids daily decreased 2.2% (11.8% to 9.6%) among patients at the intervention clinics and 1.3% (14.0% to 12.7%) among patients in the control group. The rate of decrease was significantly greater among study patients than among patients in the control group (P = .018). The rate of decrease in the number of patients on LtOT at intervention clinics increased during the intervention period compared with the preintervention period (P <.001). CONCLUSIONS: Efforts to redesign opioid medication management in primary care resulted in a significant decrease in opioid prescribing. Future research is needed to determine if these results are generalizable to other settings and to assess implications for patient-reported outcomes.

A Randomized Trial of External Practice Support to Improve Cardiovascular Risk Factors in Primary Care.

PURPOSE: We conducted a randomized controlled trial to compare the effectiveness of adding various forms of enhanced external support to practice facilitation on primary care practices' clinical quality measure (CQM) performance. METHODS: Primary care practices across Washington, Oregon, and Idaho were eligible if they had fewer than 10 full-time clinicians. Practices were randomized to practice facilitation only, practice facilitation and shared learning, practice facilitation and educational outreach visits, or practice facilitation and both shared learning and educational outreach visits. All practices received up to 15 months of support. The primary outcome was the CQM for blood pressure control. Secondary outcomes were CQMs for appropriate aspirin therapy and smoking screening and cessation. Analyses followed an intention-to-treat approach. RESULTS: Of 259 practices recruited, 209 agreed to be randomized. Only 42% of those offered educational outreach visits and 27% offered shared learning participated in these enhanced supports. CQM performance improved within each study arm for all 3 cardiovascular disease CQMs. After adjusting for differences between study arms, CQM improvements in the 3 enhanced practice support arms of the study did not differ significantly from those seen in practices that received practice facilitation alone (omnibus P = .40 for blood pressure CQM). Practices randomized to receive both educational outreach visits and shared learning, however, were more likely to achieve a blood pressure performance goal in 70% of patients compared with those randomized to practice facilitation alone (relative risk = 2.09; 95% CI, 1.16-3.76). CONCLUSIONS: Although we found no significant differences in CQM performance across study arms, the ability of a practice to reach a target level of performance may be enhanced by adding both educational outreach visits and shared learning to practice facilitation.

Near Real-time Surveillance for Consequences of Health Policies Using Sequential Analysis.

BACKGROUND: New health policies may have intended and unintended consequences. Active surveillance of population-level data may provide initial signals of policy effects for further rigorous evaluation soon after policy implementation. OBJECTIVE: This study evaluated the utility of sequential analysis for prospectively assessing signals of health policy impacts. As a policy example, we studied the consequences of the widely publicized Food and Drug Administration's warnings cautioning that antidepressant use could increase suicidal risk in youth. METHOD: This was a retrospective, longitudinal study, modeling prospective surveillance, using the maximized sequential probability ratio test. We used historical data (2000-2010) from 11 health systems in the US Mental Health Research Network. The study cohort included adolescents (ages 10-17 y) and young adults (ages 18-29 y), who were targeted by the warnings, and adults (ages 30-64 y) as a comparison group. Outcome measures were observed and expected events of 2 possible unintended policy outcomes: psychotropic drug poisonings (as a proxy for suicide attempts) and completed suicides. RESULTS: We detected statistically significant (P<0.05) signals of excess risk for suicidal behavior in adolescents and young adults within 5-7 quarters of the warnings. The excess risk in psychotropic drug poisonings was consistent with results from a previous, more rigorous interrupted time series analysis but use of the maximized sequential probability ratio test method allows timely detection. While we also detected signals of increased risk of completed suicide in these younger age groups, on its own it should not be taken as conclusive evidence that the policy caused the signal. A statistical signal indicates the need for further scrutiny using rigorous quasi-experimental studies to investigate the possibility of a cause-and-effect relationship. CONCLUSIONS: This was a proof-of-concept study. Prospective, periodic evaluation of administrative health care data using sequential analysis can provide timely population-based signals of effects of health policies. This method may be useful to use as new policies are introduced.

Hospital-Community Partnerships: Facilitating Communication for Population Health on Columbus' South Side.

Previous studies have focused on the role anchor institutions play in community development. However, less attention has been directed to how hospitals can effectively partner with community-organizations and residents as part of population health efforts. This article examines community views of one initiative developed by a major American children's hospital in partnership with local community organizations. The data for this study come from 35 in-depth interviews with local residents from the neighborhood adjacent to the hospital and two interviews with hospital administrators. Our findings suggest that the contexts in which hospitals and other non-profit corporations operate pose unique challenges to effective communication. In particular, hospitals and community organizations may think differently about the merits and nature of open communication. Especially when acting as anchor institutions working beyond their formal medical expertise, hospitals may struggle to communicate the scope and goals of their non-medical work in the community.

Community Perceptions of Hospitals and Shared Physical Space: A Qualitative Study.

In addition to providing critical medical services to communities, hospitals are also forces of broader change when seen from the perspective of neighborhood development. Over the past few decades the obligation on the part of U.S. nonprofit hospitals to positively impact the communities in which they are located has become entrenched in both U.S. tax law and the practices of many hospitals. This article presents findings from a grounded theory qualitative study of the relationship between a non-profit children's hospital in Columbus, Ohio, and the neighborhood in which it is located. Based on in-depth interviews with local residents and community leaders, findings suggest that community members often interpret distance, safety, and transportation in different, and often counter-intuitive ways. Drawing upon literature from medical geography and sociology, the authors argue that hospitals may benefit from working closely with community members to determine how space is understood and constructed when planning community health interventions.

Between-visit changes in suicidal ideation and risk of subsequent suicide attempt.

BACKGROUND: While clinicians are expected to routinely assess and address suicide risk, existing data provide little guidance regarding the significance of visit-to-visit changes in suicidal ideation. METHODS: Electronic health records from four large healthcare systems identified patients completing the Patient Health Questionnaire or PHQ9 at outpatient visits. For patients completing two questionnaires within 90 days, health system records and state vital records were used to identify nonfatal and fatal suicide attempts. Analyses examined how changes in PHQ9 item 9 responses between visits predicted suicide attempt or suicide death over 90 days following the second visit. RESULTS: Analyses included 430,701 pairs of item 9 responses for 118,696 patients. Among patients reporting thoughts of death or self-harm "nearly every day" at the first visit, risk of suicide attempt after the second visit ranged from approximately 2.0% among those reporting continued thoughts "nearly every day" down to 0.5% among those reporting a decrease to "not at all." Among those reporting thoughts of death or self-harm "not at all" at the first visit, risk of suicide attempt following the second visit ranged from approximately 0.2% among those continuing to report such thoughts "not at all" up to 1.2% among those reporting an increase to "nearly every day". CONCLUSIONS: Resolution of suicidal ideation between visits does imply a clinically important reduction in short-term risk, but prior suicidal ideation still implies significant residual risk. Onset of suicidal ideation between visits does not imply any special elevation compared to ongoing suicidal ideation. Risk is actually highest for patients repeatedly reporting thoughts of death or self-harm.

The Ascendancy of Second-Generation Antipsychotics as Frontline Antimanic Agents.

INTRODUCTION: Knowledge of the factors affecting the adoption of new medications can enhance mental health care and guide quality improvement and policy development. Food and Drug Administration indications for treating bipolar disorder with several second-generation antipsychotics (SGAs) in the 2000s represent an opportunity to identify factors that impact the spread of a then-innovative treatment through a new population. METHODS: Analysis of Department of Veterans Affairs administrative data identified the population of 170,811 veterans diagnosed with bipolar disorder from 2003 to 2010. We analyzed time trends and predictors of antimanic choice (SGA vs other) among the 40,512 outpatients with bipolar disorder who initiated their first VA outpatient antimanic prescription, using multinomial logistic regression in month-by-month analyses. We conducted classwise analyses and investigated prespecified predictors among specific agents. RESULTS: In classwise analyses, SGAs supplanted lithium, valproate, and carbamazepine/oxcarbazepine as the most commonly initiated antimanics by 2007. Psychosis, but not other indices of severity, predicted SGA initiation. Demographic analyses did not identify substantial disparities in initiation of SGAs. Drug-specific analyses revealed some consideration of medical comorbidities in choosing among specific antimanic agents, although effect sizes were small. Most patients initiating an antimanic had received an antidepressant in the previous year. DISCUSSION: Second-generation antipsychotics quickly became the frontline antimanic treatment for bipolar disorder, although antidepressants most commonly predated antimanic prescriptions. Second-generation antipsychotics were used for a broad range of patients rather than being restricted to a severely ill subpopulation. The modest association of antimanic choice with relevant medical comorbidities suggests that continued attention to quality prescribing practices is warranted.

Identification of Stevens-Johnson syndrome and toxic epidermal necrolysis in electronic health record databases.

BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) carry a high mortality risk. While identifying clinical and genetic risk factors for these conditions has been hindered by their rarity, large electronic health databases hold promise for identifying large numbers of cases for study, especially with the introduction in 2008 of ICD-9 codes more specific for these conditions. OBJECTIVE: The objective of this study is to estimate the validity of ICD-9 codes for ascertaining SJS/TEN in 12 collaborating research units in the USA, covering almost 60 million lives. METHODS: From the electronic databases at each site, we ascertained potential cases of SJS/TEN using ICD-9 codes. At five sites, a subset of medical records was abstracted and standardized criteria applied by board-certified dermatologists to adjudicate diagnoses. Multivariate logistic regression was used to identify factors independently associated with validated SJS/TEN cases. RESULTS: A total of 56 591 potential cases of SJS/TEN were identified. A subset of 276 charts was selected for adjudication and 39 (of the 276) were confirmed as SJS/TEN. Patients with the ICD-9 codes introduced after 2008 were more likely to be confirmed as cases (OR 3.32; 95%CI 0.82, 13.47) than those identified in earlier years. Likelihood of case status increased with length of hospitalization. Applying the probability of case status to the 56 591 potential cases, we estimated 475-875 to be valid SJS/TEN cases. CONCLUSION: Newer ICD-9 codes, along with length of hospitalization, identified patients with a high likelihood of SJS/TEN. This is important for identification of subjects for future pharmacogenomics studies.

Enumerating and indexing many-body intramolecular interactions: a graph theoretic approach.

The central idea observes a recursive mapping of [Formula: see text]-body intramolecular interactions to [Formula: see text]-body terms that is consistent with the molecular topology. Iterative application of the line graph transformation is identified as a natural and elegant tool to accomplish the recursion. The procedure readily generalizes to arbitrary [Formula: see text]-body potentials. In particular, the method yields a complete characterization of [Formula: see text]-body interactions. The hierarchical structure of atomic index lists for each interaction order [Formula: see text] is compactly expressed as a directed acyclic graph. A pseudo-code description of the generating algorithm is given. With suitable data structures (e.g., edge lists or adjacency matrices), automatic enumeration and indexing of [Formula: see text]-body interactions can be implemented straightforwardly to handle large bio-molecular systems. Explicit examples are discussed, including a chemically relevant effective potential model of taurocholate bile salt.

Patterns of initiation of second generation antipsychotics for bipolar disorder: a month-by-month analysis of provider behavior.

BACKGROUND: Several second generation antipsychotics (SGAs) received FDA approval for bipolar disorder in the 2000s. Although efficacious, they have been costly and may cause significant side effects. Little is known about the factors associated with prescribers' decisions to initiate SGA prescriptions for this condition. METHODS: We gathered administrative data from the Department of Veterans Affairs on 170,713 patients with bipolar disorder between fiscal years 2003-2010. Patients without a prior history of taking SGAs were considered eligible for SGA initiation during the study (n =126,556). Generalized estimating equations identified demographic, clinical, and comorbidity variables associated with initiation of an SGA prescription on a month-by-month basis. RESULTS: While the number of patients with bipolar disorder using SGAs nearly doubled between 2003 and 2010, analyses controlling for patient characteristics and the rise in the bipolar population revealed a 1.2% annual decline in SGA initiation during this period. Most medical comorbidities were only modestly associated with overall SGA initiation, although significant differences emerged among individual SGAs. Several markers of patient severity predicted SGA initiation, including previous hospitalizations, psychotic features, and a history of other antimanic prescriptions; these severity markers became less firmly linked to SGA initiation over time. Providers in the South were somewhat more likely to initiate SGA treatment. CONCLUSIONS: The number of veterans with bipolar disorder prescribed SGAs is rising steadily, but this increase appears primarily driven by a corresponding increase in the bipolar population. Month-by-month analyses revealed that higher illness severity predicted SGA initiation, but that this association may be weakening over time.

Patient Characteristics and Telemedicine Use in the US, 2022.

Importance: Telemedicine use was common during the COVID-19 pandemic, expanding many patients' approaches to accessing health care. Of concern is whether telemedicine access was poorer among higher-needs and disadvantaged populations. Objective: To assess patient characteristics associated with telemedicine use and telemedicine mode and describe telemedicine visit experiences by telemedicine mode. Design, Setting, and Participants: This cross-sectional study included data from the 2022 Health Information National Trends Survey and included US adults with a health care visit. Data were analyzed from May to September 2023. Exposure: Patient characteristics. Main Outcomes and Measures: Any telemedicine visits vs in-person visits only; telemedicine mode (video vs audio-only). Multivariable logistic models assessed patient characteristics associated with telemedicine visits and mode. Bivariate analyses compared telemedicine experiences by mode. Results: The study included 5437 adult patients (mean [SE] age, 49.4 [0.23] years; 3136 females [53.4%]; 1928 males [46.6%]). In 2022, 2384 patients (43%) had a telemedicine visit; 1565 (70%) had a video visit while 819 (30%) had an audio-only visit. In multivariable models, older age (≥75 years: adjusted odds ratio [aOR], 0.63; 95% CI, 0.42-0.94), no internet use (aOR, 0.62; 95% CI, 0.48-0.81), and living in the Midwest (aOR, 0.50; 95% CI, 0.35-0.70) were negatively associated with having telemedicine visits. Female sex (aOR, 1.43; 95% CI, 1.12-1.83), having chronic conditions (aOR, 2.13; 95% CI, 1.66-2.73), and multiple health care visits (2-4 visits: aOR, 1.77; 95% CI, 1.23-2.54; ≥5 visits: aOR, 3.29; 95% CI, 2.20-4.92) were positively associated. Among individuals who used telemedicine, older age (65-74 years: aOR, 2.13; 95% CI, 1.09-4.14; ≥75 years: aOR, 3.58; 95% CI, 1.60-8.00), no health insurance (aOR, 2.84; 95% CI, 1.42-5.67), and no internet use (aOR, 2.11; 95% CI, 1.18-3.78) were positively associated with having audio-only visits. We observed no significant differences in telemedicine use or mode by education, race and ethnicity, or income. Patients' experiences using telemedicine were generally similar for video and audio-only except more individuals who used audio-only had privacy concerns (20% vs 12%, P = .02). Conclusions and Relevance: In this cross-sectional study of adults with health care visits, many patients, including those with the greatest care needs, chose telemedicine even after in-person visits were available. These findings support continuing this care delivery approach as an option valued by patients. Differences were not observed by most common measures of socioeconomic status. Continued monitoring of telemedicine use is needed to ensure equitable access to health care innovations.

Improving Diabetes Control in a Medicaid Managed Care Population With Complex Needs.

INTRODUCTION: People enrolled in Medicaid managed care who struggle with diabetes control often have complex medical, behavioral, and social needs. Here the authors report the results of a program designed to partner with primary care teams to address those needs. METHODS: A nonprofit organization partnered with a Medicaid managed care plan and a Federally Qualified Health Center in California to enroll people with A1cs >9% in a 12-month program. The program team included a community health worker, certified diabetes care and education specialist/registered dietitian, behavioral health counselor, and registered nurse. They developed patient-led action plans, connected patients to community resources, and supported behavior changes to improve diabetes control. Baseline assessments of behavioral health conditions and social needs were collected. Monthly A1c values were tracked for participants and a comparison group. RESULTS: Of the 51 people enrolled, 83% had at least 1 behavioral health condition. More than 90% reported at least 1 unmet social need. The average monthly A1c among program participants was 0.699 lower than the comparison group post-enrollment (P = .0008), and the disparity in A1c between Hispanic and non-Hispanic White participants at enrollment declined. DISCUSSION: Participants had high levels of unmet medical, behavioral, and social needs. Addressing these needs resulted in a rapid and sustained improvement in A1c control compared to non-enrollees and a reduction in disparity of control among Hispanic participants. CONCLUSION: By partnering with a primary care team, a program external to Federally Qualified Health Center primary care can improve clinical outcomes for people with complex needs living with diabetes.