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A Patient-Centered Approach Towards Designing a Novel CIED Remote Monitoring Report
The 22nd Annual Scientific Meeting patients with heart failure. Methods: We performed a retrospective analysis of 1,114 patients with a primary diagnosis of heart failure who were enrolled in the Visiting Nurse Service of New York cardiac home hospice program from January 2013 and May 2017. The primary outcome was survival time. Results: The majority of home hospice patients in our analysis were female (56.6%), 85 years or older, and had a primary caregiver (83.8%). All patients lived in New York City and were racially and ethnically diverse (22.4% Hispanic, 17.8% African American and 7.6% Asian). Most patients were insured through Medicare (63.4%) or Managed Medicare (e.g., Medicare Advantage; 29.4%) and were admitted into hospice from the hospital (53.6%). PPSv2 scores on admission independently predict survival time among hospice patients with heart failure. Lower PPSv2 scores on admission were associated with decreased median survival time (PPSv2 10 = 2 (interquartile range (IQR: 4) days; PPSv2 20 = 3 (IQR: 6) days; PPSv2 30 = 13 (IQR: 48) days). Kaplan-Meier survival curves indicate a graded increase in mortality risk from higher to lower PPSv2 scores. The discrimination of the PPSv2 at baseline for predicting death was highest at 7 days (area under the curve (AUC)=0.802), followed by an AUC of 0.774 at 14 days, an AUC of 0.736 at 30 days, and an AUC of 0.705 at 90 days. Conclusions: The PPSv2 tool can be used by healthcare providers for prognostication of hospice-enrolled patients with heart failure who are at high risk of near-term death. It has the greatest utility in patients who have the most functional impairment.
HFSA
S77
Table:. Relevant patient reported characteristics
205 A Patient-Centered Approach Towards Designing a Novel CIED Remote Monitoring Report Michael J. Mirro, Romisa Rohani Ghahari, Ryan Ahmed, Lauren Reining, Shauna Wagner, Gavin Lehmann, Jaime Heller, Melissa Omlor, Tammy Toscos; Parkview Health, Fort Wayne, IN
204 Understanding socioecoNomiC & Lifestyle factors in patiEnts with heArt failuRe-UNCLEAR Study. Tarun W. Dasari, Michael Stout, Christopher Aston, Jennifer Verbick, Christina Murray; University of Oklahoma HSC, OKC, OK Introduction: Patients with heart failure face enormous challenges with disease burden. Socioeconomic and lifestyle patterns and disease insights have been sparsely reported in the past. The current study aims to go in-depth into understanding these characteristics in patients with heart failure. Methods: 110 patients with heart failure with reduced ejection fraction (HFrEF) were enrolled in the study. During clinic/hospital visit, patients filled out a questionnaire survey identifying various socioeconomic and lifestyle characteristics. Data were expressed as %. Gender comparisons were made using Pearson chi-squared tests. Results: Of the 110 patients. 56% were male. Mean age was 63§ 14 yrs. 49% of patients were >65 yrs. Major self-reported co-morbidities were heart attack (35%), erectile dysfunction (55%), rhythm issues (60%), diabetes (44%) and arthritis (49%). Depression was common at 44%. 70% of the subjects had Medicare and 9% were uninsured. 81% had NYHA class 2 or more symptoms. Vision (79%) and hearing issues (33%) were common and 8% had trouble with combined vision, hearing and reading. 22% had trouble reading pill bottles. 39% of patients lived alone. Only 42% of the patients knew the names of their HF medications and 84% set their own pill schedules. 35% of patients reported forgetfulness as the main reason for missing pills. A summary of author reported significant characteristics are listed in the table with gender-based differences. While no key gender-based differences exist, females fared better in being able to recollect the names of their HF medications. Conclusion: The current analysis highlights the significant limitations HFrEF. patients face on a day to day basis. While certain variables are non-modifiable; patients, caregivers and healthcare systems need to continue to evolve and adapt to these limitations/barriers to make a meaningful improvement in the morbidity and mortality associated with HFrEF.
Background: Individuals with cardiac implantable electronic devices (CIEDs) currently are not given access to their remote monitoring data. The information is managed by their cardiology clinic and each center receives a high-level notification if serious abnormalities are detected in CIED function or cardiac rhythm. The ability to access one’s own health information can provide an opportunity for self-reflection, engagement and shared decision making with clinicians. Objective: This study sought to identify key CIED data points that patients feel would be helpful for selfmanagement and cardiac disease awareness. Methods: We conducted four focus groups with CIED patients and caregivers: two for patients with implantable cardioverter defibrillators (ICDs) (N= 13, 9 patients and 4 caregivers) and two for patients with pacemakers (N = 14, 10 patients and 4 caregivers). First, participants were educated about the types of data collected through remote monitoring. Second, participants engaged in a card-sorting activity where they were presented with a deck of cards containing all possible reported remote monitoring data points (55 data points for ICDs and 37 for pacemakers). Participants selected and prioritized the cards based on what information they would like to receive from their device. Patients sorted the cards into one of three categories: most preferred (no more than 5 cards), moderately preferred (no limit), and not preferred/discarded (no limit). Participants also indicated how frequently they would like to be updated with a data report and if they would like to receive any additional supporting information to facilitate the interpretation of this data. Results: Device activity (e.g., total shocks and ventricular pacing) and cardiac episodes (e.g., monitored and treated episodes) were the top selected data categories chosen by 80% and 72% of all participants, respectively. Device settings (programmed parameters) and device information (e.g., lead impedance) were the least selected data categories discarded by 58% and 48% of participants, respectively. Through discussion, we identified the emerging reasons for discarding specific content cards, which included: insufficient understanding, unclear relevance to health condition, information overload, and difficulty interpreting numbers. Conclusion: In this presentation, we will share the user-centered design methodology and resulting patient preferences for CIED data, all used to shape a novel patient-centered remote monitoring report.
HFSA
S77
Table:. Relevant patient reported characteristics
205 A Patient-Centered Approach Towards Designing a Novel CIED Remote Monitoring Report Michael J. Mirro, Romisa Rohani Ghahari, Ryan Ahmed, Lauren Reining, Shauna Wagner, Gavin Lehmann, Jaime Heller, Melissa Omlor, Tammy Toscos; Parkview Health, Fort Wayne, IN
204 Understanding socioecoNomiC & Lifestyle factors in patiEnts with heArt failuRe-UNCLEAR Study. Tarun W. Dasari, Michael Stout, Christopher Aston, Jennifer Verbick, Christina Murray; University of Oklahoma HSC, OKC, OK Introduction: Patients with heart failure face enormous challenges with disease burden. Socioeconomic and lifestyle patterns and disease insights have been sparsely reported in the past. The current study aims to go in-depth into understanding these characteristics in patients with heart failure. Methods: 110 patients with heart failure with reduced ejection fraction (HFrEF) were enrolled in the study. During clinic/hospital visit, patients filled out a questionnaire survey identifying various socioeconomic and lifestyle characteristics. Data were expressed as %. Gender comparisons were made using Pearson chi-squared tests. Results: Of the 110 patients. 56% were male. Mean age was 63§ 14 yrs. 49% of patients were >65 yrs. Major self-reported co-morbidities were heart attack (35%), erectile dysfunction (55%), rhythm issues (60%), diabetes (44%) and arthritis (49%). Depression was common at 44%. 70% of the subjects had Medicare and 9% were uninsured. 81% had NYHA class 2 or more symptoms. Vision (79%) and hearing issues (33%) were common and 8% had trouble with combined vision, hearing and reading. 22% had trouble reading pill bottles. 39% of patients lived alone. Only 42% of the patients knew the names of their HF medications and 84% set their own pill schedules. 35% of patients reported forgetfulness as the main reason for missing pills. A summary of author reported significant characteristics are listed in the table with gender-based differences. While no key gender-based differences exist, females fared better in being able to recollect the names of their HF medications. Conclusion: The current analysis highlights the significant limitations HFrEF. patients face on a day to day basis. While certain variables are non-modifiable; patients, caregivers and healthcare systems need to continue to evolve and adapt to these limitations/barriers to make a meaningful improvement in the morbidity and mortality associated with HFrEF.
Background: Individuals with cardiac implantable electronic devices (CIEDs) currently are not given access to their remote monitoring data. The information is managed by their cardiology clinic and each center receives a high-level notification if serious abnormalities are detected in CIED function or cardiac rhythm. The ability to access one’s own health information can provide an opportunity for self-reflection, engagement and shared decision making with clinicians. Objective: This study sought to identify key CIED data points that patients feel would be helpful for selfmanagement and cardiac disease awareness. Methods: We conducted four focus groups with CIED patients and caregivers: two for patients with implantable cardioverter defibrillators (ICDs) (N= 13, 9 patients and 4 caregivers) and two for patients with pacemakers (N = 14, 10 patients and 4 caregivers). First, participants were educated about the types of data collected through remote monitoring. Second, participants engaged in a card-sorting activity where they were presented with a deck of cards containing all possible reported remote monitoring data points (55 data points for ICDs and 37 for pacemakers). Participants selected and prioritized the cards based on what information they would like to receive from their device. Patients sorted the cards into one of three categories: most preferred (no more than 5 cards), moderately preferred (no limit), and not preferred/discarded (no limit). Participants also indicated how frequently they would like to be updated with a data report and if they would like to receive any additional supporting information to facilitate the interpretation of this data. Results: Device activity (e.g., total shocks and ventricular pacing) and cardiac episodes (e.g., monitored and treated episodes) were the top selected data categories chosen by 80% and 72% of all participants, respectively. Device settings (programmed parameters) and device information (e.g., lead impedance) were the least selected data categories discarded by 58% and 48% of participants, respectively. Through discussion, we identified the emerging reasons for discarding specific content cards, which included: insufficient understanding, unclear relevance to health condition, information overload, and difficulty interpreting numbers. Conclusion: In this presentation, we will share the user-centered design methodology and resulting patient preferences for CIED data, all used to shape a novel patient-centered remote monitoring report.