Device diagnostics and early identification of acute decompensated heart failure: a systematic review

A framework to characterize the performance of early warning index alarm systems for patient monitoring

In [Scully, C.G., and Daluwatte, C., Evaluating performance of early warning indices to predict physiological instabilities. J Biomed Inform. 75 (2017) 14–21], a framework was presented to characterize the performance of warning indices to provide information on the 1) probability a critical health event will occur when a warning is given (analogous to positive predictive value) and 2) proportion of warned events to all events (analogous to sensitivity). This framework also provides information about the timeliness of the warnings with respect to event occurrence and the warning burden of the system.

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In the current work, we provide information on how this framework can be used when cases without events are present in a dataset to examine the proportion of warned non-events to all non-events (analogous to false positive rate).

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Information on steps to apply the method, software, data and results for the case study are also provided to enable implementation of the framework.

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Application and extension of the framework is demonstrated and discussed by adding non-event records to our previous case study comparing two warning strategies to predict physiologic instabilities.

A Mobile Application for Patients With Heart Failure: Theory- and Evidence-Based Design and Testing

Self-care is vital for the successful management of heart failure. Mobile health can enable patients with heart failure to perform effective self-care. This article describes the theory-guided development and beta testing of a mobile application intervention to support self-care and increase symptom awareness in community-dwelling patients with heart failure. Ten participants entered physiologic data, answered qualitative questions about symptoms, and reviewed heart failure education within the HF App daily. Two validated instruments, the Self-care of Heart Failure Index and Heart Failure Somatic Awareness Scale, were administered both before and after the intervention, and results were compared using t tests. Results indicated that there were clinically significant changes from preintervention to postintervention in self-care scores in each subscale, with a statistically significant difference in the confidence subscale scores (P = .037). However, there were no statistically significant differences between preintervention and postintervention symptom awareness scores. These results indicate that incorporating mobile applications that comprise symptom monitoring, reminders, education, and the ability to track trends in physiologic data is most useful to assist individuals with heart failure to perform effective self-care.

Evaluating performance of early warning indices to predict physiological instabilities

Patient monitoring algorithms that analyze multiple features from physiological signals can produce an index that serves as a predictive or prognostic measure for a specific critical health event or physiological instability. Classical detection metrics such as sensitivity and positive predictive value are often used to evaluate new patient monitoring indices for such purposes, but since these metrics do not take into account the continuous nature of monitoring, the assessment of a warning system to notify a user of a critical health event remains incomplete. In this article, we present challenges of assessing the performance of new warning indices and propose a framework that provides a more complete characterization of warning index performance predicting a critical event that includes the timeliness of the warning. The framework considers 1) an assessment of the sensitivity to provide a notification within a meaningful time window, 2) the cumulative sensitivity leading up to an event, 3) characteristics on if the warning stays on until the event occurs once a warning has been activated, and 4) the distribution of warning times and the burden of additional warnings (e.g., false-alarm rate) throughout monitoring that may or may not be associated with the event of interest. Using an example from an experimental study of hemorrhage, we examine how this characterization can differentiate two warning systems in terms of timeliness of warnings and warning burden.

Simulated case management of home telemonitoring to assess the impact of different alert algorithms on work-load and clinical decisions

BACKGROUND

Home telemonitoring (HTM) of chronic heart failure (HF) promises to improve care by timely indications when a patient's condition is worsening. Simple rules of sudden weight change have been demonstrated to generate many alerts with poor sensitivity. Trend alert algorithms and bio-impedance (a more sensitive marker of fluid change), should produce fewer false alerts and reduce workload. However, comparisons between such approaches on the decisions made and the time spent reviewing alerts has not been studied.

METHODS

Using HTM data from an observational trial of 91 HF patients, a simulated telemonitoring station was created and used to present virtual caseloads to clinicians experienced with HF HTM systems. Clinicians were randomised to either a simple (i.e. an increase of 2 kg in the past 3 days) or advanced alert method (either a moving average weight algorithm or bio-impedance cumulative sum algorithm).

RESULTS

In total 16 clinicians reviewed the caseloads, 8 randomised to a simple alert method and 8 to the advanced alert methods. Total time to review the caseloads was lower in the advanced arms than the simple arm (80 ± 42 vs. 149 ± 82 min) but agreements on actions between clinicians were low (Fleiss kappa 0.33 and 0.31) and despite having high sensitivity many alerts in the bio-impedance arm were not considered to need further action.

CONCLUSION

Advanced alerting algorithms with higher specificity are likely to reduce the time spent by clinicians and increase the percentage of time spent on changes rated as most meaningful. Work is needed to present bio-impedance alerts in a manner which is intuitive for clinicians.