New York, NY, USA: Springer Verlag (2018)

Benjamin Smart
University of Johannesburg
Olaf Dammann
Tufts University
This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.
Keywords No keywords specified (fix it)
Categories (categorize this paper)
Reprint years 2019
Buy this book $24.99 new   Amazon page
ISBN(s) 978-3-319-96307-5   978-3-319-96306-8   3319963066   303007174X   9783319963075   3319963074   3319963082
Edit this record
Mark as duplicate
Export citation
Find it on Scholar
Request removal from index
Revision history

Download options

PhilArchive copy

Upload a copy of this paper     Check publisher's policy     Papers currently archived: 70,337
External links

Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
Through your library
Chapters BETA
Conclusion and Invite

The main point of this book is that causal inference and causal explanation are crucially important to population health informatics and data science. We hope that we have gathered in the preceding chapters material that will help improve theoretical and applied work towards better population health... see more

Integrating Evidence

In this concluding chapter we describe our view how different kinds of information are integrated in order to arrive at causal explanation in population health science. In particular, such information comes from individuals and populations , from epidemiology and the bench sciences , and from observ... see more

Population Risk

In the previous chapters we have focused on metaphysical and epistemological concepts of causation, in medicine and population health. In this chapter, we discuss risk estimation, the focus of public health informatics methods. First, we introduce the concepts of risk and prediction. We contrast ind... see more

Making Population Health Knowledge

This chapter revolves around the idea that knowledge is generated from data. We briefly describe Ackoff’s hierarchy, which starts with data and proceeds via information to knowledge, understanding and wisdom. In contrast, we propose to de-emphasize understanding and wisdom, and to insert evidence be... see more

Causal Inference in Population Health Informatics

Having discussed the metaphysics of disease etiology in Chap. 3, in this chapter we discuss a number of important epistemological problems concerning causal inference in medicine and population health informatics. With origins tracing back to at least the eighteenth century, the problem of induction... see more

The Metaphysics of Illness Causation

In this chapter we provide a philosophical discussion of the nature of causation, as applied to the investigation of disease etiology and preventive and curative interventions. This chapter is primarily an exercise in metaphysics and conceptual analysis, in which we analyze existing concepts of caus... see more

Health Data Science

In this chapter, we introduce the concept of Health Data Science and define its three domains: technology, analytics, and conceptual. In the technology domain, we drill down from computer science via health informatics to public health informatics. The analytics domain includes biostatistics, bioinf... see more


The goal of this book is to take a first step towards a framework for causal explanation in public/population health informatics and analytics. We first provide an introduction to the concepts of public health informatics and population health informatics . Next, we introduce the general approach we... see more

References found in this work BETA

No references found.

Add more references

Citations of this work BETA

Philosophy of medicine in 2021.Jeremy R. Simon & Maël Lemoine - 2021 - Theoretical Medicine and Bioethics 42 (5):187-191.

Add more citations

Similar books and articles

Epidemiology and Causation.Leen De Vreese - 2009 - Medicine, Health Care and Philosophy 12 (3):345-353.
Causal Criteria and the Problem of Complex Causation.Andrew Ward - 2009 - Medicine, Health Care and Philosophy 12 (3):333-343.
On the Relationship Between Individual and Population Health.Onyebuchi A. Arah - 2009 - Medicine, Health Care and Philosophy 12 (3):235-244.
Public Health.Dean Rickles - 2010 - In Fred Gifford (ed.), Philosophy of Medicine. Elsevier.


Added to PP index

Total views
3 ( #1,358,478 of 2,507,886 )

Recent downloads (6 months)
2 ( #276,895 of 2,507,886 )

How can I increase my downloads?


My notes