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Diagnostic Data and AI as a Catalyst for Health System Decision Making
⏲ 36 min 93 sec ✓ 17-Apr-2020
CIHI’s Rural Health System Decision-Support Resources
⏲ 2 minutes 👁 770
Animated workflow - Clinical Decision Support System - Ascom Healthcare Platform
⏲ 54 seconds 👁 165
Webinar: Integrated Care Systems – Understanding Your Starting Point
⏲ 19 min 68 sec ✓ 11-Jul-2018
Clinical Decision Support Concerns
⏲ 1 minute 31 seconds 👁 380
Healthcare Forum 2013: Interview with CT Lin
⏲ 1 min 95 sec ✓ 04-Jun-2013
Guest Lecuture by Mike Martin on Healthy Longevity, 10 Dec 2021
⏲ 24 min 27 sec ✓ 15-Dec-2021
APCDs - How Big Data in Health Care will Empower Patients and Transform Health Care
⏲ 37 min 2 sec ✓ 13-Dec-2012
COVID-19: modelling and public health policy (Allen Cheng & Freya Shearer)
⏲ 39 min 74 sec ✓ 30-Apr-2020
Care Coordination - How can we measure it? (21)
⏲ 10 min 53 sec ✓ 01-Jun-2016
Dr. Eric E. Whitaker & Miriam Rivera | Acumen America Leadership Series on Tackling Poverty and Racism in America
⏲ 36 min 63 sec ✓ 28-Aug-2020
Solving the XAI conundrum – but how?
⏲ 11 min 23 sec ✓ 18-Apr-2023
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_diagnostic-data-and-ai-as-a-catalyst-for-health-system-decision-making.webp "Diagnostic data is transformative and underutilized. Diagnostic claims and financial data – by its sheer volume – is ripe for harvesting insights that could be a catalyst for health system decision making. Identifying leading indicators such as payor behavior and reimbursement trends can assist outreach programs and laboratories in optimizing their processes, and better managing their bottom-line. However, those insights should be shared back into the larger health system as a potential cata")
_cihis-rural-health-system-decision-support-resources.webp "CIHICanada")
_animated-workflow-clinical-decision-support-system-ascom-healthcare-platform.webp "AscomUK")
_webinar-integrated-care-systems-understanding-your-starting-point.webp "This webinar explores the evidence-based domains that underpin successful integrated care systems and presents a framework and toolkit called the Accountable Integrated Care Health Check that enables health and care systems to understand where they are on their journey of integration. nnThe Health Check comprises 10 domains which are used to gather and analyse evidence using range of methods including document review, analysis of unstructured data, surveys, 1-1 semi-structured interviews, focus")
_clinical-decision-support-concerns.webp "ClinicalKey")
_healthcare-forum-2013-interview-with-ct-lin.webp "Dr. Lin is the Chief Medical Information Officer at the University ofnColorado Health in Aurora, Colorado. He is responsible for advocatingnand deploying innovative clinical information systems at the largestnacademic medical center in the Rocky Mountain region. Dr. Lin isna nationally recognized expert in innovative research on personalnhealth records and online patient communication and has extensivenexperience creating physician leadership structures related to clinical system implementations")
_guest-lecuture-by-mike-martin-on-healthy-longevity-10-dec-2021.webp "About Mike MartinnnMike Martin (1965) is professor for gerontopsychology at UZH. He studied Psychology and Gerontology at the Universities of Mainz and Athens, USA, and received his PhD 1994. Before directing the UZH Gerontology Center in 2002, he was co-director at The German Center for Research on Ageing in Heidelberg. In 2013, Martin has initiated the interdisciplinary UZH Research Priority Program “Dynamics of Healthy Aging” and works with WHO to improve measuring healthy aging. He recen")
_apcds-how-big-data-in-health-care-will-empower-patients-and-transform-health-care.webp "“All payer claims databases (APCDs) are collections of the health claims data for all citizens of a state.This powerful data is revitalizing public health, and provider performance measurement – all to the benefit of patients, who now have access to unprecedented information in support of their own medical decision making.”nnJohn's Bio:nnJohn Freedman, MD, MBA, Principal at Freedman HealthCare, has 20 years' experience in systems management, managed care, health care quality measurement")
_covid-19-modelling-and-public-health-policy-allen-cheng-amp-freya-shearer.webp "https://statsoc.org.au/event-3821183nnEpidemiological modelling is critical to help make evidence-based decisions about how to handle and respond to the COVID-19 pandemic. Join us to hear from two experts who are deeply involved in this effort.nnAllen Cheng is an infectious diseases physician, Director of the Infection Prevention and Healthcare Epidemiology Unit at Alfred Health and Professor of Infectious Diseases Epidemiology at the School of Public Health and Preventive Medicine. He is involv")
_care-coordination-how-can-we-measure-it-21.webp "Dr. Karen Kinder, Johns Hopkins University, USnnIn the definition of primary care put forward by Dr. Barbara Starfield, primary care refers those health-related needs of people “too uncommon to maintain competence and coordinates care when people receive services at other levels of care” (1) nnPatients with poorly coordinated care are likely to have more costly and lower quality health care due to factors such as excess utilization resulting from redundant investigations, potentially harmful")
_dr-eric-e-whitaker-amp-miriam-rivera-124-acumen-america-leadership-series-on-tackling-poverty-and-racism-in-america.webp "This is a recording of our first event in a four-part Acumen America Leadership Series on Tackling Poverty and Racism in America. nnThe COVID-19 crisis and enduring racial injustice have highlighted failed systems and disproportionately impacted low-income communities and people of color.It has also emphasized the inextricable relationship between poverty and race in the United States.To address poverty and inequality, we need new solutions to upend America’s broken systems–from transfor")
_solving-the-xai-conundrum-but-how.webp "Explainable AI (XAI) has emerged as a promising solution for addressing the implementation challenges of AI/ML in healthcare. However, little is known about how developers and clinicians interpret XAI and what conflicting goals and requirements they may have. This talk presents the findings of a longitudinal multi-method study involving 112 developers and clinicians who co-developed XAI solutions for a clinical decision support system.nnOur study identifies three key differences between develope")
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