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An exploratory analysis of public health communication interventions and their effect on GP referral rates.

White, A., 2021. An exploratory analysis of public health communication interventions and their effect on GP referral rates. Masters Thesis (Masters). Bournemouth University.

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Abstract

Decreases in the number of GPs, increase in per-patient consultations and ageing populations are placing growing pressure on primary healthcare services around the world. At scale, effective public health initiatives are seen as a ‘prevention is better than cure’ solution to the long-term mitigation of these challenges. This study reviews how referral rates from general practitioners are impacted through communication interventions in interprofessional healthcare settings. The investigation is conducted using a case study analysis of a public health authority organisation Public Health Dorset. Drawing upon their implementation and existing data regarding referrals to public health entities, this research reviews the organisation's effectiveness in this area. Through means of case-study research, a chronology of archival public health communication interventions was captured. The effectiveness of the interventions was quantified by utilising a causal inference analysis of the trend in the number of referrals following targeted communication activities over a 37 month period. The results did not demonstrate a statistical significance in a change in the rate of GP referrals to the target health programme. This outcome was, in part, attributed to systematically poor tracking of intervention delivery. Supporting analysis identified seasonality trends as affecting both the rate of referrals from GPs and alternative sources such as self-referral. These trends suggested greater importance of patient participation in decision making as part of the referral process. Recommendations are proposed for the delivery, supervision and analysis of communication interventions at an organisational level in a primary healthcare setting. Data analysis written in Python and submitted supporting this thesis in part of the fulfilment requirements for the degree of Master of Research can be found at the following website location https://andyist.github.io/mres/

Item Type:Thesis (Masters)
Additional Information:If you feel that this work infringes your copyright please contact the BURO manager. The image on page 31 has been redacted for copyright reasons.
Uncontrolled Keywords:healthcare communication; public health; general practitioners; time-series data analysis
Group:Faculty of Media & Communication
ID Code:36114
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:18 Oct 2021 09:50
Last Modified:18 Oct 2021 09:50

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