Complex Care Management Program Overview

This report includes brief updates on various forms of complex care management including: Aetna - Medicare Advantage Embedded Case Management ProgramBrigham and Women's Hospital - Care Management ProgramIndependent Health - Care PartnersIntermountain Healthcare and Oregon Health and Science University - Care Management PlusJohns Hopkins University - Hospital at HomeMount Sinai Medical Center -- New York - Mount Sinai Visiting Doctors Program/ Chelsea-Village House Calls ProgramsPartners in Care Foundation - HomeMeds ProgramPrinceton HealthCare System - Partnerships for PIECEQuality Improvement for Complex Chronic Conditions - CarePartner ProgramSenior Services - Project Enhance/EnhanceWellnessSenior Whole Health - Complex Care Management ProgramSumma Health/Ohio Department of Aging - PASSPORT Medicaid Waiver ProgramSutter Health - Sutter Care Coordination ProgramUniversity of Washington School of Medicine - TEAMcar

Complex Care Management Program Overview - Technology

This report provides an overview of technology based complex care management programs, including:Cook County Health and Hospitals System - Computer Assisted Quality of Life and Symptom Assessment of Complex PatientsUniversity of Missouri - TigerPlaceWenatchee Valley Medical Center - Health Buddy -- Patient Telemonitoring Progra

Cognitive-behavioral therapy for obsessive-compulsive disorder: access to treatment, prediction of long-term outcome with neuroimaging.

This article reviews issues related to a major challenge to the field for obsessive-compulsive disorder (OCD): improving access to cognitive-behavioral therapy (CBT). Patient-related barriers to access include the stigma of OCD and reluctance to take on the demands of CBT. Patient-external factors include the shortage of trained CBT therapists and the high costs of CBT. The second half of the review focuses on one partial, yet plausible aid to improve access - prediction of long-term response to CBT, particularly using neuroimaging methods. Recent pilot data are presented revealing a potential for pretreatment resting-state functional magnetic resonance imaging and magnetic resonance spectroscopy of the brain to forecast OCD symptom severity up to 1 year after completing CBT

Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts

Electronic patient records remain a rather unexplored, but potentially rich data source for discovering correlations between diseases. We describe a general approach for gathering phenotypic descriptions of patients from medical records in a systematic and non-cohort dependent manner. By extracting phenotype information from the free-text in such records we demonstrate that we can extend the information contained in the structured record data, and use it for producing fine-grained patient stratification and disease co-occurrence statistics. The approach uses a dictionary based on the International Classification of Disease ontology and is therefore in principle language independent. As a use case we show how records from a Danish psychiatric hospital lead to the identification of disease correlations, which subsequently can be mapped to systems biology frameworks

Pilot Study of Behavioral Activation as Adjunct Treatment for Depression in Primary Care

Many individuals receiving care at a predominantly free primary health care clinic in the northern part of West Virginia are experiencing depression, and medication therapy is the most common form of management with limited resources for psychosocial treatment. Brief psychosocial therapy interventions provided by the primary care provider should be explored as an adjunct treatment for this population in the primary care setting. A pilot study was conducted to explore the integration of behavioral activation, a brief psychosocial intervention focused on decreasing depressed behavior by increasing nondepressed behavior to reinforce corresponding improvements in mood. Eligible patients were invited to attend five sessions once for five weeks. Visits were conducted according to the revised manual for Behavioral Activation Treatment for Depression. Data collection included measurements for adherence to treatment, PHQ-9, and BADS scores. Three primary aims were evaluated for this project: 1) To assess the feasibility of implementing this intervention in this clinic population; 2) To decrease overall PHQ-9 scores and increase overall BADS scores; and 3) To increase medication adherence in conjunction with a psychosocial intervention. The feasibility evaluation of this project was performed according to Bowen’s feasibility criteria and showed mixed results. Data suggests there was no statistically significant difference in depressive symptoms or daily functioning but minor improvements were noted, indicating potential clinical significance. Limitations of this study included low patient enrollment and the COVID-19 pandemic. Future research could include implementation of this intervention in an integrated care center, larger clinic, or with a different clinic population

A Case for Delirium Risk Prediction Models to Aid in Triaging Resources to those Most at Risk an Integrative Literature Review

Abstract Delirium is a complex syndrome resulting from compounding effects of acute illness, comorbidities, and the environment. It results in adverse outcomes: elevated mortality rates, length of stay, readmissions, institutionalization, long-term cognitive changes, and diminished quality of life. The rate of iatrogenic delirium is astounding, ranging from 10%-89%. There are no curative treatments; thus, primary prevention is the key. The purpose of this literature review is to identify and critique the research for the accuracy of risk stratification and feasibility in practice. Support for interventions that prevent delirium is mounting; however, interventions are resource-intensive and often not implemented. Researchers have responded to this problem by developing risk stratification tools to triage interventions toward those of the highest risk. There is evidence that some of the models\u27 implementation is successful; however, they are not yet widely operationalized. A compilation of seven published models of risk prediction was critiqued and compared using the Stetler Model of Evidence-Based Practice as a guiding model. The Newcastle-Ottawa Scale and the Critical Appraisal and the Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS checklist) are employed to aid in the critical appraisal, evaluation of the study\u27s quality, and aid in data abstraction. The models show the ability to stratify risk. Still, their effectiveness in practice cannot be studied without directed interventions because they risk prediction models are created to aid healthcare staff in making clinical decisions. Therefore, a complete clinical pathway with evidence-based interventions should be employed with a delirium risk prediction model to triage the interventions to patients at the highest risk. Recommendations are to implement an automated electronic model (automatic calculation using the EMR or a machine learning model) into clinical practice along with a delirium prevention care pathway. Electronic versions of risk scores allow for an opportunity to achieve clinical efficiency and show statistical superiority to the other models. Published evidence on the impact of the models is diminutive. Their ability to triage patients and aid in clinical decision-making should be published in an impact study. Keywords: Delirium, risk assessment, risk prediction, risk model, risk score, patient safety, patient-centered outcomes researc