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HeartPhone – positioning remote patient monitoring in Heart Failure ecosystem Dr. Mark Ledwidge, Research Director, Heart Failure Unit, St Vincent’s University Hospital Sept 16th, 2011
Agenda Our journey in remote patient monitoring Challenges and opportunities What does the ecosystem need
Heart Failure – Ideal for remote patient monitoring 1-2% of population, high readmission rates, many are preventable Hospitalisation rates for heart failure 1971-2000 (NHLBI)  age  stratified rates US
Manual Remote Patient Monitoring 50 45 40 35 30 RC 25 Event Rate (%) MC 20 15 10 5 0 Rich '93 Rich '95 Stewart '99 McDonald 02 Components – outbound calls from trained healthcare professional, home weight monitoring
Weight monitoring in HF 2 Kg over 2-3 days
Weight monitoring in HF 2 Kg over 2-3 days ,[object Object]
Non adherence > 30-50%
Assumes all patients are the same
Most weight gains are too subtle,[object Object]
TENS-HMS Remote Patient monitoring Telemonitoring Usual Care Cleland et al JACC 2005;45(10):1654–64
Heartphone Collaboration Crofton  Cardiac  Systems
DAILY WEIGHT Heartphone
DAILY WEIGHT TRENDS ANALYSIS Heartphone
7/7 NURSE/REGISTRAR REVIEW DAILY WEIGHT CARDIOLOGIST REVIEW TRENDS ANALYSIS Heartphone
ADDITIONAL  INPUTS 7/7 NURSE/REGISTRAR REVIEW DAILY WEIGHT CARDIOLOGIST REVIEW TRENDS ANALYSIS Heartphone
Large spread of patients
Large spread of patients Mr BF, West Cork
Mr BF, West Cork Unstable, high risk Referrals to GP
Mr BF, West Cork Unstable, high risk Referrals to GP Multiple GP referrals to hospital, no heart failure unit in CUH, 6 months echo waiting list, diagnostic BNP unavailable Compliance <50%, confidence reduced
Mr BF, West Cork Ecosystem not primed
Ecosystem primed TENS-HMS
Ecosystem not-primed Tel-HF
The hype is over
Challenges Soft endpoints do not convince payers in heart failure care The Ecosystem needs integration Evidence base needs to evolve
Opportunity - improve the algorithm Better sensitivity Manual Weight Monitoring, N=34 consecutive HF events. Remote weight monitoring, n=28 consecutive HF events including 3 admissions
Opportunity - improve the algorithm Better sensitivity Manual Weight Monitoring, N=34 consecutive HF events. Remote weight monitoring, n=28 consecutive HF events including 3 admissions
Opportunity - improve the algorithm Better sensitivity ** ** **P<0.001 Manual Weight Monitoring, N=34 consecutive HF events. Remote weight monitoring, n=28 consecutive HF events including 3 admissions
Opportunity - improve the algorithm Example Reported Symptomatic Deterioration
Opportunity - improve the algorithm Example Reported Symptomatic Deterioration
Opportunity - improve the algorithm Example Reported Symptomatic Deterioration
Opportunity - improve the algorithm Example Reported Symptomatic Deterioration
Opportunity - Demographics 2010 1 in 10 60+ yrs old 30  2050 1 in 5
Opportunity – 80% of what we do Chronic disease, mostly managed poorly
Opportunity – 80% of what we do Chronic disease, mostly managed poorly
Opportunity - Economics
Opportunity - Economics ‘Healthcare Unbound’, Forrester
Opportunity - multimarkers 5 question daily patient reported outcome
Opportunity - multimarkers 5 question daily patient reported outcome  Other peripherals: BP, glucometer, pulse Oximeter Improve the algorithm Reduce workload
Opportunity - multimarkers
Opportunity - multimarkers
Opportunity – this cannot continue

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Mark Ledwidge - Heartbeat Trust

Notes de l'éditeur

  1. In 2010 1 in 10 people with be over 60 years of age. By 2015 that number will have changed to 1 in 5. By 2150 it is estimated that one third of the world’s population with be over 60.These changing figures mean that chronic illnesses will become more challenging and more costly to manage. Today chronic illnesses such as COPD, CHF and diabetes account for three quarters of our healthcare spend.It is estimated that remote telemonitoring systems can reduce 20-30% of costs associated with chronic illness.They also empower the patient to become involved in their own care.Benefits to healthcare providers and third party payers:Real-time, effective patient management, monitoring and therapyIllness prevention through timely, accurate diagnosis Reductions in treatment and management costsQuality care without pressures on healthcare staffIncreased efficiency through remote diagnosing and treatmentCost savings through minimized treatment in the hospitalBetter patient or disease management resourcesEnables personalized and interactive treatmentMinimizes patient security issues and post-treatment care issues Accurate data enables correct diagnosis of emerging deterioration that saves resourcesBenefits to PatientsPeace of mind and better quality of lifeAccess to anytime, anywhere quality treatment and careSecurity and comfort in acquiring immediate supportAbility to live as normally as possibleAssurance of treatment based on valid, authentic dataRelevant therapy and care through continuous monitoring