Evidence Based Public Health Policy Making: Tool Support

EasyChair Preprint no. 1755

Abstract

The effective management of various health conditions depends on and requires appropriate public health policies (PHP). Such policies are important for several aspects of healthcare provision, including: (a) screening for prevention of disease; (b) early diagnosis and treatment; (c) long-term management of chronic diseases and disabilities; and (d) setting-up standards. Although it is widely recognised that the PHP life cycle (i.e., the analysis, action plan design, execution, monitoring and evaluation of public health policies) should be evidenced based, current support for it is mainly in the form of guidelines, and is not supported by data analytics and decision making tools tailored to it. In this paper, we present a novel model driven approach to PHP life cycle management and an integrated platform for realising this life cycle. Our approach is based on PHP decision making models. Such models steer the PHP decision making process by defining the data that need to be collected and the ways in which these data should be analysed in order to produce the evidence required for PHP making. Our work is part of a new research programme on public health policy making for the management of hearing loss, called EVOTION, that is funded by the European Union.

Keyphrases: evidence-informed health policymaking, Model driven big data analytics, Public Health Policy

@Booklet{EasyChair:1755,
  author = {Ioannis Basdekis and Konstantin Pozdniakov and Marios Prasinos and Konstantina Koloutsou},
  title = {Evidence Based Public Health Policy Making: Tool Support},
  howpublished = {EasyChair Preprint no. 1755},

  year = {EasyChair, 2019}}