Voorspellen van no-show bij forensische poliklinieken met behulp van machine learning

Abstract:

Aanleiding:
The issue of patient non-attendance or tardy cancellation of appointments is a prevalent challenge for healthcare facilities (Fenger et al., 2011). These occurrences, commonly labeled as ‘no-shows’, have significant implications for financial costs, treatment progression, and patient waiting periods.

Doel onderzoek:
To determine if phone call reminders, for the group with a considerable predicted risk of no-show at the next appointment, leads to a reduction in no-show occurrences.

Centrale vraagstelling:
In order to test the model in clinical practice, the effect of the reminder phone calls was analysed using a one-sample t-test. The no-show rate in the intervention teams (two outpatient forensic locations of Transfore) during the intervention was compared with the no-show rate in the recent past.

Deelvragen:
Additionally, no-show rate in the intervention teams is compared to the no-show rate in the control group (the four other outpatient forensic locations of Transfore), using the chi square test.

Samenwerking:

Universiteit Twente

Co-onderzoeker:
In kader van:
DG-Connected thema: 'Meer met data'
Duur van het onderzoek:
november 2024 tot december 2025
Onderzoekslijn:
Overig
Status:
In aanvraag
Informatie:
Erik de Groot