Integrating Monitoring into the Infrastructure and Workflow of Routine Practice

1. Integrating Monitoring into the Infrastructure and Workflow of Routine Practice Philip B. Adamson, MD Associate Professor of PhysiologyDirector, The Heart Failure Institute at Oklahoma Heart Hospital Oklahoma City, Oklahoma

2. Call us – We’ll Talk Patient reported symptoms Daily weights Come See Us! Frequent Assessment JVP, AJR Ancillary Providers PA/NP/RN Device-based monitoring Remote acquisition Continuous assessment with early warning Monitoring Strategies forHeart Failure Patients Reactive

3. Why Is This Important? • Device era has created many new opportunities in patient management • Advances in technology • Ability to proactively monitor patient • Ability to monitor therapeutic responses • Device era has also created many new challenges • Need for coordination of care • Need for collaboration • Risk of data overload

4. Patients not knowing who to contract with symptoms Important monitoring data not utilized to influence care Important clinical data not integrated into device programming decisions Numerous opportunities to improve quality of care and clinical outcomes missed The Risks of Poor Integration

5. Head-to-Head Comparison:Body Weights and RVDPBefore Hospitalization Weight (lb) RV Diastolic Pressure (mm Hg) 300 25 250 20 200 15 150 * * * 100 10 7weeks 4weeks 2weeks 1day 5days post 7weeks 4weeks 2weeks 1day 5days post *P<0.05 vs 1 day before hospitalization. Bourge RC, et al. Presented at the American College of Cardiology Scientific Sessions 2006. RVDP, right ventricle diastolic pressure.

6. Pressure Change Detection Concept 50 45 40 P(mmHg) 35 HF Hospitalization ePAD Reference 30 25 4 3 Threshold Crossing - Detection Detector 2 Detection Threshold 1 0 05/20/04 06/14/04 07/10/04 08/04/04 08/30/04 09/24/04 10/20/04 Date ePAD, estimate of pulmonary artery diastolic pressure; HF, heart failure.Adamson PB, et al. Circulation. 2005:abstract.

7. Continuous Hemodynamic Information: Prediction of Congestion • Adamson PB, et al. Circulation. 2005:abstract.

8. Monitoring Features of Therapy Devices Atrial Depolarization Heart rate AFIB/ATACH APACE Patient Activity Heart Rate Variability Ventricular Rate Response Heart rate VT/VF VPACE Impedance AFIB, atrial fibrillation; ATACH, atrial tachycardia; APACE, atrial pacemaker skike; VT/VF, ventricular tachycardia/ ventricular fibrillation; VPACE, ventricular pacer spike.

9. Origins of Heart Rate Variability VHP(ms) 1000 750 500 + + 250 PC 0 0 100 200 300 400 (ms) VHP, variation in heart period. Katona PG and Jih F. J Appl Physiol. 1975;39:801-805..

10. Heart Rate Variability and CRT 200 175 150 125 Cycle Length (ms) Standard Deviation of Atrial 100 75 50 CRT-OFF CRT-ON CRT, cardiac resynchronization therapy. Adamson PB, et al Circulation. 2003;108:266-269.

11. Device-Based HRVand Survival 1.00 SDAAM >100ms SDAAM 50-100ms 0.95 SDAAM <50ms Survival 0.90 0.85 SDAAM <50ms vs SDAAM >100ms: Hazard ratio =3.2; P=0.02 0.80 0 2 4 6 8 10 12 Months HRV, heart rate variability; SDAAM, standard deviation of 5-minute median atrial-atrial intervals..Adamson PB, et al. Circulation 2004;110:2389-2394.

12. Heart Rate Variability and Outcomes 100 N=262 90 No-HF 80 Minor event HRV (ms) 70 Hospitalized 60 50 40 1 3 5 7 9 11 13 15 17 19 21 Week HF, heart failure; HRV, heart rate variability.Adamson PB, et al. Circulation 2004;110:2389-2394.

13. Continuous HRVBefore Hospitalization 80 Heart Rate Variability (ms) 70 60 -80 -60 -40 -20 0 20 80 78 Night Heart Rate (BPM) 76 74 72 -80 -60 -40 -20 0 20 220 200 Patient Activity (minutes/day) 180 160 140 -80 -60 -40 -20 0 20 Days Relative to Hospital Admission HRV, heart rate variability.Adamson PB, et al. Circulation 2004;110:2389-2394.

14. Clinical Application of Continuously Measured Heart Rate Variability HRV, heart rate variability.Adamson PB. Congest Heart Fail. 2005;11:327-330.

15. Other Parameters thatHerald Congestion 90 Reference Baseline 80 MoreFluidLess 70 Impedance (W) Impedance Reduction 60 Duration of Impedance Reduction -28 -21 -14 -7 0 Days Before Hospitalization

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17. Information Flow from Device

18. Insight into Patient Status Intrathoracic Impedance Physiologic Information AT/AF V rate during AF Patient Activity Resting Night HR HR Variability % Pacing

19. Barriers to Change • EP and heart failure collaboration • Time • Established routines • Geographic separation • Financial concerns • Patient volumes • Information Systems • Schedule • Utility • EP, electrophysiology.

20. Suggested Information Integration EP Clinical Team CHF Patient EP Data Device Follow-up Remote orin-office Device Referral Device Implant Data Exchange HF Data CHF Clinical Team CHF, congestive heart failure; EP, electrophysiology; HF, heart failure.

21. Strategies for Effective Collaboration • Develop relationships: “same team” • Determine preferred communication methods HF, EP, referring MDs • Know what you want to find out or report • Package information • Much easier with new device diagnostics • Context of clinical situation • Which details are most appropriate to share? • Which details directly affect best clinical decisions? • Reporting clinically essential information? • Explain findings within appropriate context Adapted from Burke M, et al. AJN.104;(12) 40-44.

22. Key Aspects for Improving Outcomes • Optimization of medical therapy • Optimization of device therapy • Education for both inpatients and outpatients • Reasonable expectations being given to patients • Consistent information being given to patients • Increased outpatient access to healthcare professionals • Long-term patient follow-up • Routine communication between HF and EP HF, heart failure; EP, electrophysiology.

23. Monitoring for Proactive Management • Continuous physiologic parameters predict impending congestion • Autonomic control alterations, impedance changes, and intracardiac pressure increases • “Early warning” of meaningful changes • Communication Is the key element to success • EP and HF collaboration • Prevent congestion – Prevent progression? EP, electrophysiology; HF, heart failure.