Pharmacotherapy adherence in patients with heart failure: Easier said than done

Perceptions and satisfaction of patients with chronic heart failure when using a remote monitoring web application named Satelia® Cardio

INTRODUCTION

The use of telehealth, such as remote patient monitoring (RPM), for chronic heart failure (CHF) impacts patient pathways. Patient-centricity in chronic disease management is valuable. Even though RPM is recommended in practice, the evaluation of patient satisfaction has been limited to date. The objective of this study was to assess the perceptions and satisfaction of patients with CHF when using RPM.

METHODS

A voluntary declarative survey was conducted with users of Satelia® Cardio, an RPM web application which was included in an experimental model program in France funded by the ETAPES program initiative sponsored by the French Ministry of Health. Monitoring was based on patient-reported outcomes (seven questions on symptoms, one question on weight) which were answered online (digitally literate patients) or by phone with a nurse (patients with poor digital literacy). The survey included questions on perceived usefulness, ease of use and impact on quality of life (QoL).

RESULTS

Overall, 87% of the 825 patients were satisfied with having their CHF digitally monitored. Patients found that the application was easy to use (94%), problem free (95%), provided well-timed notifications (98%), easily accessible (96.5%), understandable (89%), and did not require an unreasonable amount of time to answer questions (99%). Most patients felt that RPM helped physicians provide better care during their follow-ups (70%, mean score: 7.98/10) and 45% of the digitally literate patients indicated an improved QoL.

CONCLUSION

Poor digitally literate patients may need human-based or assisted RPM. Patients monitored daily for CHF through RPM expressed strong satisfaction and acceptance.

A nonlinear dynamic factor model of health and medical treatment

Quantitative assessments of the relationship between health and medical treatment are of great importance to policy makers. To overcome endogeneity problems we formulate and estimate a tractable dynamic factor model where observed health outcomes are driven by the individual's latent health. The dynamics of latent health reflects both exogenous health deterioration and endogenous health investments. Our model allows us to investigate the effect of medical treatment on current health, as well as on future medical treatment and health outcomes. We estimate the model by maximum simulated likelihood and minimum distance methods using a rich longitudinal data set from Italy obtained by merging a number of administrative archives. These data contain detailed information on medical drug purchase, hospitalization, and mortality for a representative sample of elderly hypertensive patients. Our findings show that the observed autocorrelation in medical treatment reflects both permanent and time-varying observed and unobserved heterogeneity. They also show that medical drug purchase significantly maintains future health levels and prevents transitions to worse health. This suggests that policies aimed at increasing the awareness and the compliance of hypertensive patients help reduce cardiovascular risks and consequent hospitalization and mortality.