Transforming Value-Based Dementia Care-Implications for the GUIDE Model.

This Viewpoint reviews the Guiding an Improved Dementia Experience (GUIDE) Model to assess its suitability in providing equitable and cost-effective dementia care and to compare it with previously introduced specialty care payment models to identify opportunities for refining payment innovation in dementia care.

Association of Early Seizure Prophylaxis With Posttraumatic Seizures and Mortality: A Meta-analysis With Evidence Quality Assessment.

Purpose of the Review: To evaluate the quality of evidence about the association of primary seizure prophylaxis with antiseizure medication (ASM) within 7 days postinjury and the 18- or 24-month epilepsy/late seizure risk or all-cause mortality in adults with new-onset traumatic brain injury (TBI), in addition to early seizure risk. Results: Twenty-three studies met the inclusion criteria (7 randomized and 16 nonrandomized studies). We analyzed 9,202 patients, including 4,390 in the exposed group and 4,812 in the unexposed group (894 in placebo and 3,918 in no ASM groups). There was a moderate to serious bias risk based on our assessment. Within the limitations of existing studies, our data revealed a lower risk for early seizures in the ASM prophylaxis group compared with placebo or no ASM prophylaxis (risk ratio [RR] 0.43, 95% confidence interval [CI] 0.33-0.57, p < 0.00001, I 2 = 3%). We identified high-quality evidence in favor of acute, short-term primary ASM use to prevent early seizures. Early ASM prophylaxis was not associated with a substantial difference in the 18- or 24-month risk of epilepsy/late seizures (RR 1.01, 95% CI 0.61-1.68, p = 0.96, I 2 = 63%) or mortality (RR 1.16, 95% CI 0.89-1.51, p = 0.26, I 2 = 0%). There was no evidence of strong publication bias for each main outcome. The overall quality of evidence was low and moderate for post-TBI epilepsy risk and all-cause mortality, respectively. Summary: Our data suggest that the evidence showing no association between early ASM use and 18- or 24-month epilepsy risk in adults with new-onset TBI was of low quality. The analysis indicated a moderate quality for the evidence showing no effect on all-cause mortality. Therefore, higher-quality evidence is needed as a supplement for stronger recommendations.

Evaluating The Accuracy Of Medicare Risk Adjustment For Alzheimer's Disease And Related Dementias.

In 2020 Medicare reintroduced Alzheimer's disease and related dementias (ADRD) Hierarchical Condition Categories (HCCs) to risk-adjust Medicare Advantage and accountable care organization (ACO) payments. The potential for Medicare spending increases from this policy change are not well understood because the baseline accuracy of ADRD HCCs is uncertain. Using linked 2016-18 claims and electronic health record data from a large ACO, we evaluated the accuracy of claims-based ADRD HCCs against a reference standard of clinician-adjudicated disease. An estimated 7.5 percent of beneficiaries had clinician-adjudicated ADRD. Among those with ADRD HCCs, 34 percent did not have clinician-adjudicated disease. The false-negative and false-positive rates were 22.7 percent and 3.2 percent, respectively. Medicare spending for those with false-negative ADRD HCCs exceeded that of true positives by $14,619 per beneficiary. If, after the reintroduction of risk adjustment for ADRD, all false negatives were coded as having ADRD, expenditure benchmarks for beneficiaries with ADRD would increase by 9 percent. Monitoring ADRD coding could become challenging in the setting of concurrent incentives to decrease false-negative rates and increase false-positive rates.

Identifying Medicare Beneficiaries With Delirium.

BACKGROUND: Each year, thousands of older adults develop delirium, a serious, preventable condition. At present, there is no well-validated method to identify patients with delirium when using Medicare claims data or other large datasets. We developed and assessed the performance of classification algorithms based on longitudinal Medicare administrative data that included International Classification of Diseases, 10th Edition diagnostic codes. METHODS: Using a linked electronic health record (EHR)-Medicare claims dataset, 2 neurologists and 2 psychiatrists performed a standardized review of EHR records between 2016 and 2018 for a stratified random sample of 1002 patients among 40,690 eligible subjects. Reviewers adjudicated delirium status (reference standard) during this 3-year window using a structured protocol. We calculated the probability that each patient had delirium as a function of classification algorithms based on longitudinal Medicare claims data. We compared the performance of various algorithms against the reference standard, computing calibration-in-the-large, calibration slope, and the area-under-receiver-operating-curve using 10-fold cross-validation (CV). RESULTS: Beneficiaries had a mean age of 75 years, were predominately female (59%), and non-Hispanic Whites (93%); a review of the EHR indicated that 6% of patients had delirium during the 3 years. Although several classification algorithms performed well, a relatively simple model containing counts of delirium-related diagnoses combined with patient age, dementia status, and receipt of antipsychotic medications had the best overall performance [CV- calibration-in-the-large <0.001, CV-slope 0.94, and CV-area under the receiver operating characteristic curve (0.88 95% confidence interval: 0.84-0.91)]. CONCLUSIONS: A delirium classification model using Medicare administrative data and International Classification of Diseases, 10th Edition diagnosis codes can identify beneficiaries with delirium in large datasets.

Development and Evaluation of a Natural Language Processing Annotation Tool to Facilitate Phenotyping of Cognitive Status in Electronic Health Records: Diagnostic Study.

BACKGROUND: Electronic health records (EHRs) with large sample sizes and rich information offer great potential for dementia research, but current methods of phenotyping cognitive status are not scalable. OBJECTIVE: The aim of this study was to evaluate whether natural language processing (NLP)-powered semiautomated annotation can improve the speed and interrater reliability of chart reviews for phenotyping cognitive status. METHODS: In this diagnostic study, we developed and evaluated a semiautomated NLP-powered annotation tool (NAT) to facilitate phenotyping of cognitive status. Clinical experts adjudicated the cognitive status of 627 patients at Mass General Brigham (MGB) health care, using NAT or traditional chart reviews. Patient charts contained EHR data from two data sets: (1) records from January 1, 2017, to December 31, 2018, for 100 Medicare beneficiaries from the MGB Accountable Care Organization and (2) records from 2 years prior to COVID-19 diagnosis to the date of COVID-19 diagnosis for 527 MGB patients. All EHR data from the relevant period were extracted; diagnosis codes, medications, and laboratory test values were processed and summarized; clinical notes were processed through an NLP pipeline; and a web tool was developed to present an integrated view of all data. Cognitive status was rated as cognitively normal, cognitively impaired, or undetermined. Assessment time and interrater agreement of NAT compared to manual chart reviews for cognitive status phenotyping was evaluated. RESULTS: NAT adjudication provided higher interrater agreement (Cohen κ=0.89 vs κ=0.80) and significant speed up (time difference mean 1.4, SD 1.3 minutes; P<.001; ratio median 2.2, min-max 0.4-20) over manual chart reviews. There was moderate agreement with manual chart reviews (Cohen κ=0.67). In the cases that exhibited disagreement with manual chart reviews, NAT adjudication was able to produce assessments that had broader clinical consensus due to its integrated view of highlighted relevant information and semiautomated NLP features. CONCLUSIONS: NAT adjudication improves the speed and interrater reliability for phenotyping cognitive status compared to manual chart reviews. This study underscores the potential of an NLP-based clinically adjudicated method to build large-scale dementia research cohorts from EHRs.

Brazilian Public Health System: history and profile of heart failure care and the impacts of COVID-19 / Sistema Público de Saúde Brasileiro: história e perfil dos cuidados com a insuficiência cardíaca e os impactos da COVID-19

Objective: The objective of this study is to describe the general and specific context of hospitalizations for Heart Failure (HF) in the Unified Health System and its main care indicators and economic aspects in the period before and during COVID-19. Methods: The economic indicators were evaluated between January 2011 and June 2022, comparing these indicators before and during the COVID-19 pandemic, using data from the DataSUS Health Information of the Ministry of Health of Brazil. The number of hospitalizations, length of stay, lethality and hospitalization costs were evaluated. The ARIMA method and the general regression model were used to analyze monthly results before and during COVID-19. Results: Hospitalization for HF has decreased in the last 11 years, with the most significant drop in the COVID-19 pandemic. After the pandemic, there was an increase in lethality in patients hospitalized for HF and also an increase in length of stay, despite the decrease in hospitalizations. When analyzing the economic aspects, more than US$ 725 million were spent. The average ticket showed a clear drop in per capita investment, with a real devaluation of 30.46% in the period from 2011 to 2022, which can be related to two main hypotheses: increased effectiveness and effectiveness of the analysis of service costs and/ or chronic underfunding of the Brazilian Public Health System. Conclusion: HF has its lethality worsened over time, especially in the COVID-19 period, also associated with a significant expense with the SUS and a tendency to decrease the allocation of resources.

Objetivo: O objetivo deste estudo é descrever o contexto geral e específico das internações por insuficiência cardíaca (IC) junto ao Sistema Único de Saúde e seus principais indicadores assistenciais e aspectos econômicos no período pré e durante a COVID-19. Métodos: Os indicadores econômicos foram avaliados no período entre janeiro de 2011 e junho de 2022, comparando esses indicadores antes e durante a pandemia por COVID-19, utilizando dados do DataSUS Informações de Saúde do Ministério da Saúde do Brasil. Foram avaliados o número de internações, tempo de internação, etalidade e custos de internação. O método ARIMA e o modelo de regressão geral foram usados para analisar os resultados mensais antes e durante a COVID-19. Resultados: A hospitalização por IC diminuiu nos últimos 11 anos, com queda mais significativa na pandemia da COVID-19. Após a pandemia, houve aumento da letalidade em pacientes internados por IC e também um aumento do tempo de permanência, mesmo diante da diminuição das internações. Ao analisar os aspectos econômicos, foram gastos mais de US$ 725 milhões. O ticket médio apresentou uma clara queda no investimento per capita, com desvalorização real de 30,46% no período de 2011 a 2022, o que pode estar relacionado a duas hipóteses principais: aumento da efetividade e efetividade da análise de custos do atendimento e/ou subfinanciamento crônico do Sistema Público de Saúde Brasileiro. Conclusão: A IC tem sua letalidade agravada ao longo do tempo, principalmente no período da COVID-19, associada também a um gasto relevante com o sistema público brasileiro e a uma tendência de diminuição da alocação de recursos.

Drivers of US health care spending for persons with seizures and/or epilepsies, 2010-2018.

OBJECTIVE: This study was undertaken to characterize spending for persons classified with seizure or epilepsy and to determine whether spending has increased over time. METHODS: In this cross-sectional study, we pooled data from the Medical Expenditure Panel Survey (MEPS) household component files for 2010-2018. We matched cases to controls on age and sex of a population-based sample of MEPS respondents (community-dwelling persons of all ages) with records associated with a medical event (e.g., outpatient visit, hospital inpatient) for seizure, epilepsy, or both. Outcomes were weighted to be representative of the civilian, noninstitutionalized population. We estimated the treated prevalence of epilepsy and seizure, health care spending overall and by site of care, and trends in spending growth. RESULTS: We identified 1078 epilepsy cases and 2344 seizure cases. Treated prevalence was .38% (95% confidence interval [CI] = .34-.41) for epilepsy, .76% (95% CI = .71-.81) for seizure, and 1.14% (95% CI = 1.08-1.20) for epilepsy or seizure. The difference in annual spending for cases compared to controls was $4580 (95% CI = $3362-$5798) for epilepsy, $7935 (95% CI, $6237-$9634) for seizure, and $6853 (95% CI = $5623-$8084) for epilepsy or seizure, translating into aggregate costs of $5.4 billion, $19.0 billion, and $24.5 billion. From 2010 to 2018, the annual growth rate in total spending incurred for seizures and/or epilepsies was 7.6% compared to 3.6% among controls. SIGNIFICANCE: US economic burden of seizures and/or epilepsies is substantial and warrants interventions focused on their unique and overlapping causes.

Linking the Paul Coverdell National Acute Stroke Program to commercial claims to establish a framework for real-world longitudinal stroke research.

BACKGROUND: Non-interventional large-scale research on real-world patients who had a stroke requires the use of multiple data sources ensuring access to longitudinal data from large populations with clinically-detailed information. We sought to establish a framework for longitudinal research on patients hospitalised with stroke by linking information-rich, deidentified inpatient data from the Paul Coverdell National Acute Stroke Program (PCNASP) to commercial and Medicare Advantage longitudinal claims data. METHODS: All stroke admissions in PCNASP between 2008 and 2015 were evaluated for linkage to longitudinal claims from a commercial insurer using an algorithm based on six available common data fields (patient age, gender, admission date, discharge date, discharge diagnosis and state) and a hospital match. We evaluated the linkage quality (via the percentage of unique records in the linked dataset) and the representativeness of the linked population. We also described medical history, stroke severity and patterns of medication use among the PCNASP-claims linked cohort. RESULTS: The linkage produced uniqueness equal to 99.1%. We identified 5644 linked and 98 896 unlinked patients who had an ischaemic stroke hospitalisation in claims data. Linked patients were younger than unlinked (69.7 vs 72.5 years), but otherwise similar by medical history, prestroke medication use or lab values. Stroke severity was mild and most patients were discharged home. Prestroke and discharge use of antihypertensive and statins in the PCNASP were greater than their use as measured by filled prescriptions in claims. CONCLUSIONS: High-quality linkage between the PCNASP and commercial claims data is feasible. This linkage identified differences between reported or recommended versus actual out-of-hospital medication utilisation, highlighting the importance of longitudinal data availability for research aimed to improve the care of patients who had a stroke.

Anticonvulsant Primary and Secondary Prophylaxis for Acute Ischemic Stroke Patients: A Decision Analysis.

Background and Purpose: We examined the impact of 3 anticonvulsant prophylaxis strategies on quality-adjusted life-years (QALYs) among patients with an incident acute ischemic stroke. Methods: We created a decision tree to evaluate 3 strategies: (1) long-term primary prophylaxis; (2) short-term secondary prophylaxis after an early seizure with lifetime prophylaxis if persistent or late seizures (LSs) developed; and (3) long-term secondary prophylaxis if either early, late, or persistent seizures developed. The outcome was quality-adjusted life expectancy (QALY). We created 4 base cases to simulate common clinical scenarios: (1) female patient aged 40 years with a 2% or 11% lifetime risk of an LS and a 33% lifetime risk of an adverse drug reaction (ADR); (2) male patient aged 65 years with a 6% or 29% LS risk and 60% ADR risk; (3) male patient aged 50 years with an 18% or 65% LS risk and 33% ADR risk; and (4) female patient aged 80 years with a 29% or 83% LS risk and 80% ADR risk. In sensitivity analyses, we altered the parameters and assumptions. Results: Across all 4 base cases, primary prophylaxis yielded the fewest QALYs when compared with secondary prophylaxis. For example, under scenario 1, strategies 2 and 3 resulted in 7.17 QALYs each, but strategy 1 yielded only 6.91 QALYs. Under scenario 4, strategies 2 and 3 yielded 2.85 QALYs compared with 1.40 QALYs for strategy 1. Under scenarios in which patients had higher ADR risks, strategy 2 led to the most QALYs. Conclusions: Short-term therapy with continued anticonvulsant prophylaxis only after postischemic stroke seizures arise dominates lifetime primary prophylaxis in all scenarios examined. Our findings reinforce the necessity of close follow-up and discontinuation of anticonvulsant seizure prophylaxis started during acute ischemic stroke hospitalization.

Identifying Medicare beneficiaries with dementia.

BACKGROUND/OBJECTIVES: No data exist regarding the validity of International Classification of Disease (ICD)-10 dementia diagnoses against a clinician-adjudicated reference standard within Medicare claims data. We examined the accuracy of claims-based diagnoses with respect to expert clinician adjudication using a novel database with individual-level linkages between electronic health record (EHR) and claims. DESIGN: In this retrospective observational study, two neurologists and two psychiatrists performed a standardized review of patients' medical records from January 2016 to December 2018 and adjudicated dementia status. We measured the accuracy of three claims-based definitions of dementia against the reference standard. SETTING: Mass-General-Brigham Healthcare (MGB), Massachusetts, USA. PARTICIPANTS: From an eligible population of 40,690 fee-for-service (FFS) Medicare beneficiaries, aged 65 years and older, within the MGB Accountable Care Organization (ACO), we generated a random sample of 1002 patients, stratified by the pretest likelihood of dementia using administrative surrogates. INTERVENTION: None. MEASUREMENTS: We evaluated the accuracy (area under receiver operating curve [AUROC]) and calibration (calibration-in-the-large [CITL] and calibration slope) of three ICD-10 claims-based definitions of dementia against clinician-adjudicated standards. We applied inverse probability weighting to reconstruct the eligible population and reported the mean and 95% confidence interval (95% CI) for all performance characteristics, using 10-fold cross-validation (CV). RESULTS: Beneficiaries had an average age of 75.3 years and were predominately female (59%) and non-Hispanic whites (93%). The adjudicated prevalence of dementia in the eligible population was 7%. The best-performing definition demonstrated excellent accuracy (CV-AUC 0.94; 95% CI 0.92-0.96) and was well-calibrated to the reference standard of clinician-adjudicated dementia (CV-CITL <0.001, CV-slope 0.97). CONCLUSION: This study is the first to validate ICD-10 diagnostic codes against a robust and replicable approach to dementia ascertainment, using a real-world clinical reference standard. The best performing definition includes diagnostic codes with strong face validity and outperforms an updated version of a previously validated ICD-9 definition of dementia.

Patterns of anticonvulsant use and adverse drug events in older adults.

PURPOSE: To examine indications for, duration of use, and rate of adverse drug events (ADE) attributable to anticonvulsant initiation, as adjudicated by expert review of electronic health records (EHR) of older adults. METHODS: We identified a cohort of community dwelling Medicare beneficiaries with linked EHR (aged 65+, continuously enrolled with a large health system/until death between 2012 and 2014, n = 20 945) and drew a stratified EHR review sample (n = 1534). An expert reviewed all records to adjudicate anticonvulsant use, years of use, indication for use, and evidence of ADEs attributable to anticonvulsant initiation. After excluding patients with insufficient EHR data (n = 37; 2%), we reconstructed the cohort using inverse probability weights to resemble the original cohort of eligible beneficiaries (n = 20 380). Among incident users of a single anticonvulsant, we estimated the rate of ADEs and described the type and severity of ADEs. RESULTS: Overall, 12% (n = 2469) of eligible beneficiaries used at least one anticonvulsant in the 2012 to 2014 period (4% [n = 757] incident users, 8% [n = 1712] prevalent users). Incident users were most frequently prescribed gabapentin (n = 461/757, 61%), benzodiazepines (n = 122/757, 16%), and levetiracetam (n = 74/757, 10%); the most common indication was pain relief (n = 214; 28%) followed by epilepsy (n = 53; 7%). Among incident users, the overall ADE rate was 10/100 person-years (95% CI 4-20/100 person-years), of which 29% (n = 28/97) were life threatening (eg, somnolence). Most ADEs among incident monotherapy users were nervous system related (68%, n = 66/97). CONCLUSION: Many older adult community dwelling traditional Medicare beneficiaries had clinically significant ADEs likely attributable to the initiation of anticonvulsant therapy, which was begun for a range of indications.

A feasibility assessment of functioning and quality-of-life patient-reported outcome measures in adult epilepsy clinics: A systematic review.

OBJECTIVE: The objective of the study was to identify functioning and quality-of-life (QOL) patient-reported outcome measurements (PROMs) feasible for use in the waiting room of adult epilepsy clinics. MATERIAL AND METHODS: We searched PubMed and Web of Science for articles on in English, Spanish, Portuguese, Italian, and French published by the end of February 15th, 2019. We screened retrieved titles and abstracts looking for publications that reported the use of PROMs to measure functioning and QOL in epilepsy. The authors, clinical experts, and patient advocates from the Epilepsy Foundation of America conceptualized a set of desirable feasibility attributes for PROMs implementation in the waiting room of adult epilepsy clinics. These attributes included brief time for completion (i.e., ≤3 min), free cost, coverage of four minimum QOL domains and respective facets, and good evidence of psychometric properties. We defined QOL domains according to the World Health Organization's classification and created psychometric appraisal criteria based on the Food and Drug Administration's (FDA) Guidance. RESULTS: Eighteen candidate instruments were identified and compared with respect to desirable attributes for use in adult epilepsy clinics. We found that the Quality-of-life in epilepsy (QOLIE)-10 and Patient-Reported Outcome Measurement Information System-10 (PROMIS-10) were the most feasible PROMs for implementation in adult epilepsy clinics based on our criteria. The QOLIE-10 and PROMIS-10 still lack ideal evidence of responsiveness in people with epilepsy. CONCLUSION: This is the first systematic review that aimed to assess feasibility properties of available functioning and QOL PROMs. The QOLIE-10 and PROMIS-10 are potentially feasible instruments for implementation in the waiting room of adult epilepsy clinics. Further studies assessing the responsiveness of these PROMs are needed and will contribute to the selection of the most appropriate instrument for longitudinal use in adult epilepsy clinical practice.

Epilepsy Among Elderly Medicare Beneficiaries: A Validated Approach to Identify Prevalent and Incident Epilepsy.

BACKGROUND: Uncertain validity of epilepsy diagnoses within health insurance claims and other large datasets have hindered efforts to study and monitor care at the population level. OBJECTIVES: To develop and validate prediction models using longitudinal Medicare administrative data to identify patients with actual epilepsy among those with the diagnosis. RESEARCH DESIGN, SUBJECTS, MEASURES: We used linked electronic health records and Medicare administrative data including claims to predict epilepsy status. A neurologist reviewed electronic health record data to assess epilepsy status in a stratified random sample of Medicare beneficiaries aged 65+ years between January 2012 and December 2014. We then reconstructed the full sample using inverse probability sampling weights. We developed prediction models using longitudinal Medicare data, then in a separate sample evaluated the predictive performance of each model, for example, area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. RESULTS: Of 20,945 patients in the reconstructed sample, 2.1% had confirmed epilepsy. The best-performing prediction model to identify prevalent epilepsy required epilepsy diagnoses with multiple claims at least 60 days apart, and epilepsy-specific drug claims: AUROC=0.93 [95% confidence interval (CI), 0.90-0.96], and with an 80% diagnostic threshold, sensitivity=87.8% (95% CI, 80.4%-93.2%), specificity=98.4% (95% CI, 98.2%-98.5%). A similar model also performed well in predicting incident epilepsy (k=0.79; 95% CI, 0.66-0.92). CONCLUSIONS: Prediction models using longitudinal Medicare data perform well in predicting incident and prevalent epilepsy status accurately.

Medicare claims can identify post-stroke epilepsy.

OBJECTIVE: There have been no validated Medicare claims-based algorithms available to identify epilepsy by discrete etiology of stroke (e.g., post-stroke epilepsy, PSE) in community-dwelling elderly individuals, despite the increasing availability of large datasets. Our objective was to validate algorithms that detect which patients have true PSE. METHODS: We linked electronic health records (EHR) to Medicare claims from a Medicare Pioneer Accountable Care Organization (ACO) to identify PSE. A neurologist reviewed 01/2012-12/2014 EHR data from a stratified sample of Medicare patients aged 65+ years to adjudicate a reference-standard to develop an algorithm for identifying patients with PSE. Patient sampling strata included those with: A) epilepsy-related claims diagnosis (n = 534 [all]); B) no diagnosis but neurologist visit (n = 500 [randomly sampled from 4346]); C) all others (n = 500 [randomly sampled from 16,065]). We reconstructed the full sample using inverse probability sampling weights; then used half to derive algorithms and assess performance, and the remainder to confirm performance. We evaluated predictive performance across several measures, e.g., specificity, sensitivity, negative and positive predictive values (NPV, PPV). We selected our best performing algorithms based on the greatest specificity and sensitivity. RESULTS: Of 20,943 patients in the reconstructed sample, 13.6% of patients with epilepsy had reference-standard PSE diagnosis, which represents a 3-year overall prevalence of 0.28% or 28/10,000, and a prevalence within the subpopulation with stroke of 3%. The best algorithm included three conditions: (a) at least one cerebrovascular claim AND one epilepsy-specific anticonvulsant OR (b) at least one cerebrovascular claim AND one electroencephalography claim (specificity 100.0% [95% CI 99.9%-100.0%], NPV 98.8% [98.6%-99.0%], sensitivity 20.6% [95% CI 14.6%-27.9%], PPV 86.5% [95% CI 71.2%-95.5%]). CONCLUSION: Medicare claims can identify elderly Medicare beneficiaries with PSE with high accuracy. Future epidemiological surveillance of epilepsy could incorporate similar algorithms to accurately identify epilepsy by varying etiologies.

Antiepileptic drug treatment after an unprovoked first seizure: A decision analysis.

OBJECTIVE: To compare the expected quality-adjusted life-years (QALYs) in adult patients undergoing immediate vs deferred antiepileptic drug (AED) treatment after a first unprovoked seizure. METHODS: We constructed a simulated clinical trial (Markov decision model) to compare immediate vs deferred AED treatment after a first unprovoked seizure in adults. Three base cases were considered, representing patients with varying degrees of seizure recurrence risk and effect of seizures on quality of life (QOL). Cohort simulation was performed to determine which treatment strategy would maximize the patient's expected QALYs. Sensitivity analyses were guided by clinical data to define decision thresholds across plausible measurement ranges, including seizure recurrence rate, effect of seizure recurrence on QOL, and efficacy of AEDs. RESULTS: For patients with a moderate risk of recurrent seizures (52.0% over 10 years after first seizure), immediate AED treatment maximized QALYs compared to deferred treatment. Sensitivity analyses showed that for the preferred choice to change to deferred AED treatment, key clinical measures needed to reach implausible values were 10-year seizure recurrence rate ≤38.0%, QOL reduction with recurrent seizures ≤0.06, and efficacy of AEDs on lowering seizure recurrence rate ≤16.3%. CONCLUSION: Our model determined that immediate AED treatment is preferable to deferred treatment in adult first-seizure patients over a wide and clinically relevant range of variables. Furthermore, our analysis suggests that the 10-year seizure recurrence rate that justifies AED treatment (38.0%) is substantially lower than the 60% threshold used in the current definition of epilepsy.

Burden of illness for super-refractory status epilepticus patients.

OBJECTIVE: To provide an estimate of the annual number of super-refractory status epilepticus (SRSE) cases in the US and to evaluate utilization of hospital resources by these patients. METHODS: The Premier Hospital Database was utilized to estimate the number of SRSE cases based on hospital discharges during 2012. Discharges were classified as SRSE cases based on an algorithm using seizure-related International Classification of Diseases-9 (ICD-9) codes, Intensive Care Unit (ICU) length of stay (LOS), and treatment protocols (e.g. benzodiazepines, anti-epileptic drugs (AEDs), and ventilator use). Secondary analyses were conducted using more restrictive algorithms for SRSE. RESULTS: A total of 6,325 hospital discharges were classified as SRSE cases from a total of 5,300,000 hospital discharges. Applying a weighting based on hospital characteristics and 2012 US demographics, this projected to an estimated 41,156 cases of SRSE in the US during 2012, an estimated incidence rate of ∼13/100,000 annually for SRSE in the US. Secondary analyses using stricter SRSE algorithms resulted in estimated incidence rates of ∼11/100,000 and 8/100,000 annually. The mean LOS for SRSE hospitalizations was 16.5 days (median =11; interquartile range [IQR] = 6-20), and the mean ICU LOS was 9.3 days (median =6; IQR =3-12). The mean cost of an SRSE hospitalization was $51,247 (median = $33,294; 95% CI = $49,634-$52,861). LIMITATIONS: The analysis uses ICD-9 diagnostic codes and claims information, and there are inherent limitations in any methodology based on treatment protocol, which created challenges in distinguishing with complete accuracy between SRSE, RSE, and SE on the basis of care patterns in the database. CONCLUSION: SRSE is associated with high mortality and morbidity, which place a high burden on healthcare resources. Projections based upon the findings of this study suggest an estimated 25,821-41,959 cases of SRSE may occur in the US each year, but more in-depth studies are required.

Patient-reported financial barriers to adherence to treatment in neurology.

OBJECTIVE: Many effective medical therapies are available for treating neurological diseases, but these therapies tend to be expensive and adherence is critical to their effectiveness. We used patient-reported data to examine the frequency and determinants of financial barriers to medication adherence among individuals treated for neurological disorders. PATIENTS AND METHODS: Patients completed cross-sectional surveys on iPads as part of routine outpatient care in a neurology clinic. Survey responses from a 3-month period were collected and merged with administrative sources of demographic and clinical information (eg, insurance type). We explored the association between patient characteristics and patient-reported failure to refill prescription medication due to cost in the previous 12 months, termed here as "nonadherence". RESULTS: The population studied comprised 6075 adults who were presented between July and September 2015 for outpatient neurology appointments. The mean age of participants was 56 (standard deviation: 18) years, and 1613 (54%) were females. The patients who participated in the surveys (2992, 49%) were comparable to nonparticipants with respect to gender and ethnicity but more often identified English as their preferred language (94% vs 6%, p<0.01). Among respondents, 9.8% (n=265) reported nonadherence that varied by condition. These patients were more frequently Hispanic (16.7% vs 9.8% white, p=0.01), living alone (13.9% vs 8.9% cohabitating, p<0.01), and preferred a language other than English (15.3% vs 9.4%, p=0.02). CONCLUSION: Overall, the magnitude of financial barriers to medication adherence appears to vary across neurological conditions and demographic characteristics.

Feasibility of the collection of patient-reported outcomes in an ambulatory neurology clinic.

OBJECTIVE: To determine whether patients could self-report physical and mental health assessments in the waiting room and whether these assessments would be associated with modified Rankin Scale (mRS) and Quality of Life in Epilepsy (QOLIE-10) scores. METHODS: We offered iPad-based surveys to consecutive adult neurology patients at check-in to collect patient-reported outcome measures (PROMs). We collected demographic and clinical data on 6,075 patients through survey or administrative claims and PROMs from participating patients. We compared demographic characteristics of participants and nonparticipants and tested associations between physical and mental health scores and mRS and QOLIE-10. RESULTS: Of 6,075 patients seen by neurologists during the study period, 2,992 (49.3%) participated in the survey. Compared to nonparticipating patients, participating patients more often were privately insured (53.5% vs 42.7%, p < 0.01), married (51.5% vs 47.9%, p < 0.01), and seen in general neurology (nonsubspecialty) clinics (53.1% vs 46.6%, p < 0.01) and more likely to report English as their preferred language (50.1% vs 38.4%, p < 0.01). Participating patients had a mean physical health T score of 28.7 (SD 15) and mental health T score of 33 (SD 15), which were 3 and 2 SD worse than the average for the US general population, respectively. Mean T scores in every category of the mRS were different from every other category (n = 232, p < 0.01). Patient Reported Outcomes Measurement Information System-10 T scores were linearly associated with QOLIE-10 scores (n = 202, p < 0.01) CONCLUSIONS: Systematic digital collection of PROMs is feasible. Differences among survey participants and nonparticipants highlight the need to develop multilingual measurement tools that may improve collection from vulnerable populations.

Avaliação da doença vascular do enxerto no transplante cardíaco: experiência de um centro brasileiro / Assessment of cardiac allograft vasculopathy in cardiac transplantation: experience of a Brazilian center

FUNDAMENTO: O transplante cardíaco continua sendo o tratamento de escolha para a insuficiência cardíaca refratária ao tratamento otimizado. Dois métodos diagnósticos apresentam elevada sensibilidade no diagnóstico de episódios de rejeição ao enxerto e Doença Vascular do Enxerto (DVE), causas importantes de mortalidade no pós-transplante. OBJETIVO: Avaliar a relação entre os resultados do ultrassom intracoronariano (USIV) e os laudos das biópsias endomiocárdicas (BX) no seguimento de pacientes submetidos a transplante cardíaco em um serviço de referência brasileiro. MÉTODOS: Foi realizado um ensaio epidemiológico retrospectivo observacional, com pacientes submetidos a transplante cardíaco ortotópico, no período de 2000 a 2009. Foram analisados os prontuários desses pacientes e os resultados dos USIV e BX realizados rotineiramente no seguimento clínico pós-transplante e terapêutica em uso. RESULTADOS: Dos 77 pacientes analisados, 63,63% são do sexo masculino, nas faixas etárias de 22 a 69 anos. Quanto aos resultados dos USIV, 33,96% foram classificados em Stanford classe I, e 32,08%, como Stanford IV. Dos 143 laudos das biópsias, 51,08% tiveram resultado 1R, 3R em 0,69% dos laudos, e 14,48% apresentaram a descrição de efeito Quilty. Todos usaram antiproliferativos, 80,51% usaram inibidores da calcineurina e 19,48% usaram inibidores do sinal de proliferação (ISP). CONCLUSÃO: A avaliação dos pacientes pós-transplante cardíaco por meio do USIV incorpora informações detalhadas para o diagnóstico precoce e sensível da DVE, que são complementadas pelas informações histológicas fornecidas pelas BX, estabelecendo uma possível relação causal entre a DVE e os episódios de rejeição humoral.

BACKGROUND: Cardiac transplantation continues to be the treatment of choice for heart failure refractory to optimized treatment. Two methods have high sensitivity for diagnosing allograft rejection episodes and cardiac allograft vasculopathy (CAV), important causes of mortality after transplantation. OBJECTIVE: To assess the relationship between intravascular ultrasound (IVUS) results and endomyocardial biopsy (BX) reports in the follow-up of patients undergoing cardiac transplantation in a Brazilian reference service. METHODS: A retrospective epidemiological observational study was carried out with patients undergoing orthotopic cardiac transplantation from 2000 to 2009. The study assessed the medical records of those patients and the results of the IVUS and BX routinely performed in the clinical post-transplant follow-up, as well as the therapy used. RESULTS: Of the 77 patients assessed, 63.63% were males, their ages ranging from 22 to 69 years. Regarding the IVUS results, 33.96% of the patients were classified as Stanford class I, and 32.08%, as Stanford class IV. Of the 143 BX reports, 51.08% were 1R, and 0.69%, 3R. The Quilty effect was described in 14.48% of the BX reports. All patients used antiproliferative agents, 80.51% used calcineurin inhibitors, and 19.48% used proliferation signal inhibitors. CONCLUSION: The assessment of cardiac transplant patients by use of IVUS provides detailed information for the early and sensitive diagnosis of CAV, which is complemented by histological data derived from BX, establishing a possible causal relationship between CAV and humoral rejection episodes.