Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jan 30, 2020
Open Peer Review Period: Jan 30, 2020 - Mar 26, 2020
Date Accepted: Aug 11, 2020
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Pragmatic Summative Evaluation of MonashWatch (MW): The Dandenong HLCC Pilot Service, Victoria, Australia.
ABSTRACT
Background:
The Victorian HealthLinksChronicCare (HLCC) hospital algorithm identifies patients with predicted 3+ hospitalisations per year in order to generate a capitated funding pool. Hospitals can innovate with the fund to address anticipated admission risk. MonashWatch (MW) is a hospital outreach service implemented to address potentially preventable hospitalisations in an HLCC cohort using telehealth and coaching. Telecare Guides (TCG) monitor self-reported patient journeys with outbound phone calls using the Patient Journey Record System (PaJR). Health Coaches (nursing and allied health) triage PaJR real-time flags that signify potential admission risk and instigate or adapt care for the individual with GP, health and social services.
Objective:
This paper aims to describe the MonashWatch pragmatic clinical evaluation at 30 months.
Methods:
Participants: Residents of a geo-zone area near Dandenong Hospital were recruited from a systematic sample of HLCC-identified patients to maintain an active telehealth cohort of 250-300. Methods. Primary Outcome: Length of stay (LOS) of acute (non-surgical) admissions from Victorian Admitted Episode database operationalised as Bed days in Intention-To-Treat (IT) group compared with systematically sampled usual care (UC) group sampled at ratio (4:1). Analysis: ANCOVA (analysis of covariance) least square (LS) means of LOS of ITT and UC groups were adjusted for covariates age, gender and MW exposure. Time series analysis using Kendall trend test and the Sen slope test change patterns.
Results:
Findings: MW identified 1373 suitable HLCC patients: UC (293) and ITT (1080: 471 active telehealth; 485 declined; 178 lost and 8 died). The ITT and UC had similar mean/median admission rates and similar common conditions profiles. Age, MW exposure and ITT/UC status independently predicted LOS. Bed Days in UC (LS) mean 4.5 ± 0.2 std were significantly higher than ITT 3.4 ± 0.13 std. Both groups demonstrated significant regression to the mean with a greater slope in ITT (-)406 vs (-)104 UC bed days. Savings of 1.14 days per each of 1080 patients (1236 bed days) was estimated during the evaluation.
Conclusions:
Discussion and Conclusion: Clinically and statistically meaningful reductions in bed days in ITT vs UC cohort is demonstrated. Sampling and propensity matching are challenging in an active service pragmatic evaluation. Nonetheless, MW achieved its HLCC funding objectives, to the satisfaction of funders and providers and participants and is expanding. Ongoing research needs to stimulate improvements in this cohort and diverse patient groups and settings. Clinical Trial: n/a
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