Referral waiting time analysis at paediatrics wards in Region Västra Götaland

Abstract

Variation in waiting time connected to the referral process is an aspect that a healthcare provider battles within the endeavour of providing treatment services for incoming patients. VGR (Region Västra Götaland) is a healthcare provider currently facing this issue. One reason for this is a deficit in understanding the causes of variation in the referral process, which consequently has elicited an increased variation in patient waiting time. This study aims to explain why and where, in the referral process, causes of variation emerge and, moreover, how to manage the causes of variation. A literature review provided substance and deeper insights into how the referral process works and possible factors that generate causes of variation in the patient referral time. A Gemba walk was undertaken to obtain a holistic overview of the referral process at VGR. The method used for this thesis was a case study involving quantitative and qualitative data. The quantitative data presented an overview of what the distribution of the number of referrals looks like across different units in the county of Västra Götaland. Furthermore, the quantitative data showcased the length of waiting time for incoming patients. Answers and insights from the semi-structured interviews represented the qualitative data.

From the empirical findings, a specific disease and two units in the VGR organisation were chosen for further analysis due to considerable differences between the two in terms of waiting meantime for patients in the referral process and the number of incoming referrals. The analysis entailed a discussion and reflection on the causes of variation for the two chosen units. The causes of variation were categorised as internal and external variation, implying that if the cause of variation occurs within the unit, respectively, outside the unit. These variations were then split into controllable or non-controllable variations to understand how to manage the variation. Recommendations and suggestions based on the results have been laid out, attributed to the categorisation of variation.