10,108 research outputs found

    Use of m-Health Technology for Preventive Interventions to Tackle Cardiometabolic Conditions and Other Non-Communicable Diseases in Latin America- Challenges and Opportunities

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    In Latin America, cardiovascular disease (CVD) mortality rates will increase by an estimated 145% from 1990 to 2020. Several challenges related to social strains, inadequate public health infrastructure, and underfinanced healthcare systems make cardiometabolic conditions and non-communicable diseases (NCDs) difficult to prevent and control. On the other hand, the region has high mobile phone coverage, making mobile health (mHealth) particularly attractive to complement and improve strategies toward prevention and control of these conditions in low- and middle-income countries. In this article, we describe the experiences of three Centers of Excellence for prevention and control of NCDs sponsored by the National Heart, Lung, and Blood Institute with mHealth interventions to address cardiometabolic conditions and other NCDs in Argentina, Guatemala, and Peru. The nine studies described involved the design and implementation of complex interventions targeting providers, patients and the public. The rationale, design of the interventions, and evaluation of processes and outcomes of each of these studies are described, together with barriers and enabling factors associated with their implementation.Fil: Beratarrechea, Andrea Gabriela. Instituto de Efectividad ClĂ­nica y Sanitaria; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; ArgentinaFil: Diez Canseco, Francisco. Universidad Peruana Cayetano Heredia; PerĂşFil: Irazola, Vilma. Instituto de Efectividad ClĂ­nica y Sanitaria; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; ArgentinaFil: Miranda, Jaime. Universidad Peruana Cayetano Heredia; PerĂşFil: Ramirez Zea, Manuel. Institute of Nutrition of Central America and Panama; GuatemalaFil: Rubinstein, Adolfo Luis. Instituto de Efectividad ClĂ­nica y Sanitaria; Argentina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; Argentin

    Self-monitoring Practices, Attitudes, and Needs of Individuals with Bipolar Disorder: Implications for the Design of Technologies to Manage Mental Health

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    Objective To understand self-monitoring strategies used independently of clinical treatment by individuals with bipolar disorder (BD), in order to recommend technology design principles to support mental health management. Materials and Methods Participants with BD (N = 552) were recruited through the Depression and Bipolar Support Alliance, the International Bipolar Foundation, and WeSearchTogether.org to complete a survey of closed- and open-ended questions. In this study, we focus on descriptive results and qualitative analyses. Results Individuals reported primarily self-monitoring items related to their bipolar disorder (mood, sleep, finances, exercise, and social interactions), with an increasing trend towards the use of digital tracking methods observed. Most participants reported having positive experiences with technology-based tracking because it enables self-reflection and agency regarding health management and also enhances lines of communication with treatment teams. Reported challenges stem from poor usability or difficulty interpreting self-tracked data. Discussion Two major implications for technology-based self-monitoring emerged from our results. First, technologies can be designed to be more condition-oriented, intuitive, and proactive. Second, more automated forms of digital symptom tracking and intervention are desired, and our results suggest the feasibility of detecting and predicting emotional states from patterns of technology usage. However, we also uncovered tension points, namely that technology designed to support mental health can also be a disruptor. Conclusion This study provides increased understanding of self-monitoring practices, attitudes, and needs of individuals with bipolar disorder. This knowledge bears implications for clinical researchers and practitioners seeking insight into how individuals independently self-manage their condition as well as for researchers designing monitoring technologies to support mental health management

    A survey of practices for the use of electronic health records to support research recruitment

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    Electronic health records (EHRs) provide great promise for identifying cohorts and enhancing research recruitment. Such approaches are sorely needed, but there are few descriptions in the literature of prevailing practices to guide their use. A multidisciplinary workgroup was formed to examine current practices in the use of EHRs in recruitment and to propose future directions. The group surveyed consortium members regarding current practices. Over 98% of the Clinical and Translational Science Award Consortium responded to the survey. Brokered and self-service data warehouse access are in early or full operation at 94% and 92% of institutions, respectively, whereas, EHR alerts to providers and to research teams are at 45% and 48%, respectively, and use of patient portals for research is at 20%. However, these percentages increase significantly to 88% and above if planning and exploratory work were considered cumulatively. For most approaches, implementation reflected perceived demand. Regulatory and workflow processes were similarly varied, and many respondents described substantive restrictions arising from logistical constraints and limitations on collaboration and data sharing. Survey results reflect wide variation in implementation and approach, and point to strong need for comparative research and development of best practices to protect patients and facilitate interinstitutional collaboration and multisite research

    Outlook Magazine, Summer 2018

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    https://digitalcommons.wustl.edu/outlook/1204/thumbnail.jp

    The Laboratory-Based Intermountain Validated Exacerbation (LIVE) Score Identifies Chronic Obstructive Pulmonary Disease Patients at High Mortality Risk.

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    Background: Identifying COPD patients at high risk for mortality or healthcare utilization remains a challenge. A robust system for identifying high-risk COPD patients using Electronic Health Record (EHR) data would empower targeting interventions aimed at ensuring guideline compliance and multimorbidity management. The purpose of this study was to empirically derive, validate, and characterize subgroups of COPD patients based on routinely collected clinical data widely available within the EHR. Methods: Cluster analysis was used in 5,006 patients with COPD at Intermountain to identify clusters based on a large collection of clinical variables. Recursive Partitioning (RP) was then used to determine a preferred tree that assigned patients to clusters based on a parsimonious variable subset. The mortality, COPD exacerbations, and comorbidity profile of the identified groups were examined. The findings were validated in an independent Intermountain cohort and in external cohorts from the United States Veterans Affairs (VA) and University of Chicago Medicine systems. Measurements and Main Results: The RP algorithm identified five LIVE Scores based on laboratory values: albumin, creatinine, chloride, potassium, and hemoglobin. The groups were characterized by increasing risk of mortality. The lowest risk, LIVE Score 5 had 8% 4-year mortality vs. 56% in the highest risk LIVE Score 1 (p < 0.001). These findings were validated in the VA cohort (n = 83,134), an expanded Intermountain cohort (n = 48,871) and in the University of Chicago system (n = 3,236). Higher mortality groups also had higher COPD exacerbation rates and comorbidity rates. Conclusions: In large clinical datasets across different organizations, the LIVE Score utilizes existing laboratory data for COPD patients, and may be used to stratify risk for mortality and COPD exacerbations

    Geisinger Health System: Achieving the Potential of System Integration Through Innovation, Leadership, Measurement, and Incentives

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    Presents a case study of a physician-led nonprofit healthcare group exhibiting the attributes of an ideal healthcare delivery system as defined by the Fund. Describes how its ProvenCare model improved clinical outcomes with reduced resource utilization
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