Remote Monitoring: Tracking Congestion & Beyond
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The document discusses the significance of congestion in heart failure (HF) patients, illustrating its impact on hospital admissions and readmission rates. It emphasizes the importance of remote patient monitoring (RPM) in managing HF, highlighting components such as patient engagement, data analysis, and centralized care. The study reveals a need for targeted interventions to reduce congestion at discharge and improve clinical outcomes for HF patients.
Remote Monitoring: Tracking Congestion & Beyond
- 1. Remote Monitoring: Tracking Congestion & Beyond Daniel Bensimhon, MD Medical Director Advanced HF & Mechanical Circulatory Support Program Cone Health
- 2. Disclosures ◆ Consulting/speaker/ownership interests: Boehringer-Ingelheim, Pfizer, Janssen, AstraZeneca, Sensible Medical, Caption Health, AquaPass, scPharmaceuticals, Adjacent Health, Ventricle Health
- 3. The Importance of Congestion Congestion: ◆ Most common symptoms experienced ◆ Most common reason patients seek medical attention ◆ Most common reason for hospital admission ◆ Associated with reduced Quality of Life ◆ Persistent congestion at discharge is associated with worse outcomes and hospital readmission
- 4. Admission 89.7% of the Acute HF patients are wet at admission Discharge 36.5% of the Acute HF patients are still wet at discharge Clinical Outcome AHF patients presenting as ‘wet-warm’ and ‘wet- cold’ had the highest 1-year HF hospitalization rate Patients free of congestion at discharge had a significantly lower 1-year mortality compared to patients with residual congestion (18.5 vs. 28.0%; P<0.001) Chioncel et al. Eur J Heart Fail 2019; 21;1338-1352 Congestion & Clinical Outcomes
- 5. Setting: Hospital discharge with 30d & 90d FU Protocol: ReDS reading for HF patients deemed clinically ready for discharge (N = 108) Randomization: Treatment: ReDS ≥ 39% – additional treatment + 2nd ReDS reading + referral to HF program ReDS < 39% – discharge as planned Control: all discharged as planned Results: 43% of the HF patients are discharged wet (ReDS > 35%) ReDS guided management led to mean additional weight loss of 5.7 lbs (2.6kg) Regardless of study arm wet patients were at higher risk for 30- day readmission (wet vs dry) 11.8% vs 1.4%, P= 0.03 Bensimhon D et al. Heart & lung. 50, 1, 59-64, 2021 Patients are being discharged congested • 32% are discharged with ReDS ≥ 39% • 44% are discharged with ReDS > 35% 32% 12% 56% Hospital Discharge– Guided Management & Prognostics
- 6. 2021 ESC Guidelines Discharge Outpatient Management of patients after HF hospitalization Prevention and monitoring
- 7. June 2023 JACC Scientific Statement – Remote Monitoring for HF Management ◆ Early telemonitoring of weights and symptoms did not decrease heart failure hospitalizations ◆ A signal that is accurate and actionable with response kinetics for early re- assessment is required ◆ Tracking of congestion with cardiac filling pressures or lung water content has shown most impact to decrease hospitalization
- 8. Modified from: Adamson PB. Curr Heart Fail Rep. 2009;6:287-292. Window of Opportunity to Intervene Progression to Acute Decompensated Heart Failure
- 9. Why RPM in HF? Mismatch outcomes vs resources 53% of cardiologists > 50 y/o4 14,669 people in US per cardiologist4 Avg time to see cardiologist post d/c = 33d5 Problem worse in rural states (MT 52, SD 46 ID 46, AK 39, ND 36, WY 16)5 1 Solomon SD Circ 2017;10:63-70 2. Greene S JACC 2018 Jul, 72 (4) 351–366 22.3% 33.3% 40.2% 0 5 10 15 20 25 30 35 40 45 30-day readmission rate 60-day readmission rate 90-day readmission rate Patients readmitted for all causes following hospitalization for heart failure, % High readmission/mortality rates1 Low rates GDMT utilization2 with poor clinical inertia -> 48.6% visits without GDMT titration3 CHAMP-HF - 22% on 3/3 classes GDMT - 1% optimized 3. Swat S JACC: HF Vol 11 (11), No 2023, 1592-94 4. AAMC 2022 Physician Specialty Data report 5. Kaiser Family Foundation Data
- 10. Evolution of RPM in HF
- 11. RPM Key Components ◆ Components of RPM programs ◆ Patient selection/engagement ◆ Choices of devices/data collection ◆ Data transmission ◆ Data analysis/presentation ◆ Care team review & clinical action ◆ Reimbursement/ROI 1. Bhatia IJHF 2021 Jan; 3(1) 31-50
- 12. ◆ Patient selection ◆ Patients who need it most often resistant or have challenges with access/technology ◆ Benefit appears limited in stable patients due to low event rates ◆ Post-d/c & NYHA III patients may have biggest benefit though trial results have been mixed ◆ TIM-HF1 HF event within past 2 years -> no ↓ in HF events ◆ TIM-HF22 had event in last year -> 20% ↓ hHF days/all-cause mortality 1.Koehler F. TIM HF Eur J Heart Fail 2010;12:1354–1362 2. Koehler F, TIM HF2 Lancet 2018;392:1047–1051 RPM Optimization
- 13. ◆ Patient engagement ◆ Patient engagement can be difficult & adherence wanes with time ◆ Human contact likely better than automated ◆ Tele-HF1– early HF telemonitoring trial ◆ Adherence to automated voice-response system ◆ 14% never used it ◆ At 1 week 90% used it > 3x/week ◆ At 26 weeks 55% used the system at all ◆ Other strategies to increase adherence2 ◆ Ease-of-use, passive monitors, patient rewards/gamification 1. Chaudhry SI, Tele HF NEJM 2010;363:2301–2309 2. Bhatia IJHF Jan; 3(1) 31-50 RPM Optimization
- 14. ◆ Patient & device selection ◆ Optimal devices not yet determined ◆ Key components likely included accurate/early hemodynamic sensor + algorithms that lead to GDMT titration ◆ Non-invasive devices – lower cost/greater access ◆ Passive sensors highest compliance ◆ Cellular-enabled devices – avoid need for Wi-Fi RPM Optimization
- 15. ◆ Data transmission, analysis & presentation ◆ Cellular devices over Wi-Fi ◆ Optimize signal-to-noise ratio ◆ ”Don’t measure everything” ◆ Limit # of systems/dashboards ◆ Carefully plan alerts ◆ clinical alerts with poor specificity and high false positive rates -> ↑increase in unnecessary office visits and hospitalizations1 ◆ Evaluate HIPPA compliance carefully 1. van Veldhuisen DJ. Circ 2011;124:1719–1726 RPM Optimization
- 16. ◆ Care team review & clinical action ◆ Centralized monitoring/management with clinically-led (MD/APP/PharmD) team generally produce best outcomes ◆ More timely & effective responses ◆ EMR nudges -> ↑ GDMT but no ↓ in ER visits or hHF (PROMPT-HF) ◆ Telemonitoring + texting after hHF -> no ↓ BNP, hHF or CVD (MESSAGE-HF) ◆ Need care algorithms to allow RNs & other team members to participate ◆ EMR integration 1. Ghazi L. JACC 2022 Jun, 79 (22) 2203-13. 2. Rohde L. JAMA Cardiol. 2024;9(2):105-113 RPM Optimization
- 17. ◆ Reimbursement/ROI ◆ Most devices do not have CPT code ◆ Can bill CCM time but requires careful documentation ◆ CPT 99490 = 20 mins -> $62/mo ◆ CPT 99492 = add’l 20 mins -> $47/mo ◆ CPT 99487 (Complex CM) = 60 mins -> $132/mo ◆ CPT 99489 (Complex CM) = add’l 30 mins -> $71/mo ◆ Often hard to fund unless part of value-based system of care RPM Optimization
- 18. Critical Components of a Successful RPM Program ◆ Summary ◆ High-risk patients likely benefit most ◆ Hemodynamic sensors + GDMT titration ◆ Keep devices simple with limited patient effort ◆ Centralized monitoring with MD/APP/PharmD likely best ◆ Build focused care algorithms and alerts ◆ ROI can be tricky ◆ Excellent Resource – Bhatia A, Maddox TM. IJHF 2021 Jan;3(1):31-50 https://doi.org/10.36628/ijhf.2020.0023
- 19. Can RPM Partnerships be a Pathway to HF Success?
- 20. Todays Journey Ventricle Health Managed Patient has been without proper medication for more than 30 days 22% chance of 30-day readmission Patient waits for cardiologist for 33+ days, low GDMT utilization Patient is hospitalized with HF but is discharged while congested and is advised to see a cardiologist Patient continues cycle of readmission to hospital and/or 1/3 die in 12 months Ventricle Health HF Patient Journey Ventricle Health’s evidence-based medicine approach, supported by an extensive cardiology network, not only result in reduced hospitalizations but also ensure cost savings while delivering the highest standards of care Throughout the patient journey we are continually analyzing data to identify at risk patients and HF stage changes 40% chance of 90 days readmission Savings Generated 0 30 90 Transition of Care Seamlessly transition the patient into the stabilization treatment Cardiology Visit & RPM Timely start of GDMT combined with RPM Post Acute Stabilization Medication adherence, disease state education and lifestyle modification coaching Emergency Action Plan Diuretic regimen established, ER avoidance, RPM triage Graduation Patient condition remains stable without HF readmissions and related health events. <5 30 90 120 1 14 Post discharge PCP follow up DAY
- 21. Disclaimer: This presentation contains confidential material. Please do not distribute. HF Clinical Dashboard
- 22. Disclaimer: This presentation contains confidential material. Please do not distribute. © Ventricle Health 2024 Ventricle Health Clinical Outcomes
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