Instability Windows and Emergency Admission in Complex Multimorbidity: A Retrospective Cohort Analysis of Longitudinal Relational Monitoring

How often periods of instability in complex multimorbidity pass without hospital admission has not been quantified at scale. We analysed 16,383 structured telephone monitoring contacts from 243 people at high predicted risk of recurrent hospitalisation in the MonashWatch programme (2016 to 2019), linked to 1,698 emergency admission events. An instability window was defined as two or more consecutive contacts each recording three or more alerts; 621 windows were detected in 157 participants. Of 540 windows with a determined outcome, 83.0% (participant-level bootstrap 95% CI 78.7 to 86.8) had no recorded emergency admission within 14 days, against 93.3% of contacts outside windows. Classing each contact using only what was known at that point, admission within 14 days followed 13.8% of contacts at which a window could first be recognised, against 6.9% of contacts not in a recognised window (ratio 1.99, 95% CI 1.54 to 2.47). Of 726 admissions during monitoring, 21% fell within a window and 64% had no window within 14 days. After truncation at admission, the specified analyses did not demonstrate differences in window duration or breadth between windows followed by admission and other windows. Monitoring signals were each associated with admission (odds ratios 1.08 to 1.45), but a joint model discriminated weakly (mean hold-out AUC 0.60 across 200 participant-level splits). Detected instability marks a period of roughly doubled short-term risk in which most people are not admitted. Absence of a recorded admission is not clinical recovery, and whether monitoring averted admissions cannot be determined from these data.

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Publication Details

Journal
Preprints.org
Published
2026-11-04
DOI
https://doi.org/10.20944/preprints202611.0274.v1
Primary Topic
Chronic Disease Management Strategies
Type
preprint
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preprint

Instability Windows and Emergency Admission in Complex Multimorbidity: A Retrospective Cohort Analysis of Longitudinal Relational Monitoring

Ishbel L. Henderson, Carmel Mary Martin, Donald A. Campbell, Keith Stockman
Preprints.org
Chronic Disease Management Strategies
preprint

Instability Windows and Emergency Admission in Complex Multimorbidity: A Retrospective Cohort Analysis of Longitudinal Relational Monitoring

Ishbel L. Henderson, Carmel Mary Martin, Donald A. Campbell, Keith Stockman
preprint en

Abstract

How often periods of instability in complex multimorbidity pass without hospital admission has not been quantified at scale. We analysed 16,383 structured telephone monitoring contacts from 243 people at high predicted risk of recurrent hospitalisation in the MonashWatch programme (2016 to 2019), linked to 1,698 emergency admission events. An instability window was defined as two or more consecutive contacts each recording three or more alerts; 621 windows were detected in 157 participants. Of 540 windows with a determined outcome, 83.0% (participant-level bootstrap 95% CI 78.7 to 86.8) had no recorded emergency admission within 14 days, against 93.3% of contacts outside windows. Classing each contact using only what was known at that point, admission within 14 days followed 13.8% of contacts at which a window could first be recognised, against 6.9% of contacts not in a recognised window (ratio 1.99, 95% CI 1.54 to 2.47). Of 726 admissions during monitoring, 21% fell within a window and 64% had no window within 14 days. After truncation at admission, the specified analyses did not demonstrate differences in window duration or breadth between windows followed by admission and other windows. Monitoring signals were each associated with admission (odds ratios 1.08 to 1.45), but a joint model discriminated weakly (mean hold-out AUC 0.60 across 200 participant-level splits). Detected instability marks a period of roughly doubled short-term risk in which most people are not admitted. Absence of a recorded admission is not clinical recovery, and whether monitoring averted admissions cannot be determined from these data.

Preprints.org
Chronic Disease Management Strategies
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