Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia.

ObjectivesEarly recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]).DesignRetrospective cohort study.SettingKaiser Permanente Washington (KPWA), an integrated healthcare delivery system.ParticipantsA total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples.MeasurementsEHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills).ResultsOverall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia.ConclusionThe eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019

The Impact of Inter-Hospital Transfer on Clinical Outcomes following Endovascular Treatment for Acute Ischemic Stroke

PURPOSE Hospitals designated as primary stroke centers offer noninvasive treatment for acute ischemic stroke, but only comprehensive stroke centers are equipped to provide endovascular treatment. When stroke patients needing endovascular treatment present to the emergency department at a primary stroke center, they then require inter-hospital transfer to a comprehensive center for definitive treatment. Recent studies have found significant treatment delays and poor clinical outcomes in patients requiring inter-hospital transfer1,2. The primary aim of this study is to determine if inter-hospital transfer impacts clinical outcomes after endovascular treatment for acute ischemic stroke. A secondary aim is to determine whether inter-hospital transfer coincides with any significant treatment delay. METHODS This study involves retrospective chart review for 107 patients undergoing endovascular treatment for acute ischemic stroke at one of three hospitals in Austin, Texas from October 2016 to September 2018. 26 patients required inter-hospital transfer, while 81 (the control group) presented directly to a hospital offering endovascular treatment. Two-tailed T- and U-tests were used for analysis of parametric and non-parametric variables pertaining to time intervals and baseline characteristics. Odds ratios were calculated to compare dichotomized outcomes between groups, with significance determined by chi-square. RESULTS Inter-hospital transfer significantly prolonged onset to groin (mean difference = 37.2 min, p=.02). The transfer group was more likely to experience intracranial hemorrhage (53.9% > 22.2%, p<.01). Clinical outcomes did not significantly differ between groups. CONCLUSIONS Although observed trends in these data suggest poor outcomes for transfer patients, small sample size limits the significance of these findings. However, the significant treatment delay seen in the transfer group warrants a discussion on city protocol changes regarding patient transport via emergency services. Protocol changes favoring direct delivery of patients to comprehensive stroke centers may reduce treatment delay and yield improved clinical outcomes.Dell Medical Schoo

Engaging with clinicians to implement and evaluate the ICF in neurorehabilitation practice

INTRODUCTION: Although deemed a globally accepted framework, there remains scare evidence on the process and outcome of implementing the International Classification of Functioning, Disability and Health (ICF) within neurorehabilitation. OBJECTIVES: This review briefly explores the existing, broader literature and then reports on two action research projects, undertaken in England, specifically within stroke and neurorehabilitation. Working with participants, including clinicians from in-patient and community settings, there are now 35 different ways identified for the use of the ICF. CONCLUSION: The outcome of the first project highlights that using the ICF enhances communication within and beyond the acute stroke service, fosters holistic thinking and clarifies team roles. To adopt it into clinical practice, the ICF must be adapted to meet local service needs. The use of action research has facilitated the knowledge translation process which has enabled the ICF to become a clinical reality in neurorehabilitation, with clinicians identifying a range of potential uses

Depression in Low-Income Adolescents: Guidelines for School-Based Depression Intervention Programs

Adolescent depression is growing in interest to clinicians. In addition to the estimated 2 million cases of adolescent major depressive episodes each year, depressive symptoms in youth have become indicators of mental health complications later in life. Studies indicate that being low-income is a risk factor for depression and that socioeconomically disadvantaged teenagers are more than twice as likely to develop mental illnesses. Only an estimated 1 in 4 children with mental illnesses receive adequate help and 80% of these resources come through schools. Thus, this study focuses on establishing the importance of depression intervention programs in low-income high schools and designing novel guidelines for effective protocols. A compilation of expert opinion on depression screening, education, and treatment, as well as analysis of previously implemented school screening and awareness programs, are examined in order to understand key strategies. The results of this study finds that a multi-layered approach with screening, universal education, and interventions for those identified as being high-risk is most effective in addressing the mental health needs of low-income adolescents. To ensure feasibility and efficacy, screening should be conducted with a modified PHQ-a test and followed-up by timely clinical interviews by school psychologists. All students should receive universal depression education curriculum consisting of principles such as: depression literacy, asset theory, and promotion of help-seeking behaviors. Extending universal education to teachers would also be beneficial in promoting mental health communication and positive classroom environments. It is vital that those screening positive for depression or suicidality receive protocols geared towards high-risk youths, such as group Cognitive-Behavioral Therapy and facilitated mental health center referrals based on individual severity. Effectively addressing depression in school systems requires integration of mental health promotion, depression prevention, and psychotherapy—by taking this multidimensional approach, public health officials and school administrations can ensure that adequate resources are directed to those most in need

Gaps in Treatment and Surveillance: Head and Neck Cancer Care in a Safety-Net Hospital.

Objective:Treatment delays and suboptimal adherence to posttreatment surveillance may adversely affect head and neck cancer (HNC) outcomes. Such challenges can be exacerbated in safety-net settings that struggle with limited resources and serve a disproportionate number of patients vulnerable to gaps in care. This study aims to characterize treatment delays and adherence with posttreatment surveillance in HNC care at an urban tertiary care public hospital in San Francisco. Study Design:Retrospective chart review. Setting:Urban tertiary care public hospital in San Francisco. Subjects and Methods:We identified all cases of HNC diagnosed from 2008 to 2010 through the electronic medical record. We abstracted data, including patient characteristics, disease characteristics, pathology and radiology findings, treatment details, posttreatment follow-up, and clinical outcomes. Results:We included 64 patients. Median time from diagnosis to treatment initiation (DTI) was 57 days for all patients, 54 days for patients undergoing surgery only, 49 days for patients undergoing surgery followed by adjuvant radiation ± chemotherapy, 65 days for patients undergoing definitive radiation ± chemotherapy, and 29 days for patients undergoing neoadjuvant chemotherapy followed by radiation or chemoradiation. Overall, 69% of patients completed recommended treatment. Forty-two of 61 (69%) patients demonstrated adherence to posttreatment visits in year 1; this fell to 14 out of 30 patients (47%) by year 5. Conclusion:DTI was persistently prolonged in this study compared with prior studies in other public hospital settings. Adherence to posttreatment surveillance was suboptimal and continued to decline as the surveillance period progressed

HealthE: Classifying Entities in Online Textual Health Advice

The processing of entities in natural language is essential to many medical NLP systems. Unfortunately, existing datasets vastly under-represent the entities required to model public health relevant texts such as health advice often found on sites like WebMD. People rely on such information for personal health management and clinically relevant decision making. In this work, we release a new annotated dataset, HealthE, consisting of 6,756 health advice. HealthE has a more granular label space compared to existing medical NER corpora and contains annotation for diverse health phrases. Additionally, we introduce a new health entity classification model, EP S-BERT, which leverages textual context patterns in the classification of entity classes. EP S-BERT provides a 4-point increase in F1 score over the nearest baseline and a 34-point increase in F1 when compared to off-the-shelf medical NER tools trained to extract disease and medication mentions from clinical texts. All code and data are publicly available on Github

Statistical and Clinical Aspects of Hospital Outcomes Profiling

Hospital profiling involves a comparison of a health care provider's structure, processes of care, or outcomes to a standard, often in the form of a report card. Given the ubiquity of report cards and similar consumer ratings in contemporary American culture, it is notable that these are a relatively recent phenomenon in health care. Prior to the 1986 release of Medicare hospital outcome data, little such information was publicly available. We review the historical evolution of hospital profiling with special emphasis on outcomes; present a detailed history of cardiac surgery report cards, the paradigm for modern provider profiling; discuss the potential unintended negative consequences of public report cards; and describe various statistical methodologies for quantifying the relative performance of cardiac surgery programs. Outstanding statistical issues are also described.Comment: Published in at http://dx.doi.org/10.1214/088342307000000096 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org