A taxonomy of early diagnosis research to guide study design and funding prioritisation

Abstract

Researchers and research funders aiming to improve diagnosis seek to identify if, when, where, and how earlier diagnosis is possible. This has led to the propagation of research studies using a wide range of methodologies and data sources to explore diagnostic processes. Many such studies use electronic health record data and focus on cancer diagnosis. Based on this literature, we propose a taxonomy to guide the design and support the synthesis of early diagnosis research, focusing on five key questions:

• Do healthcare use patterns suggest earlier diagnosis could be possible?

• How does the diagnostic process begin?

• How do patients progress from presentation to diagnosis?

• How long does the diagnostic process take?

• Could anything have been done differently to reach the correct diagnosis sooner?

We define families of diagnostic research study designs addressing each of these questions and appraise their unique or complementary contributions and limitations. We identify three further questions on relationships between the families and their relevance for examining patient group inequalities, supported with examples from the cancer literature. Although exemplified through cancer as a disease model, we recognise the framework is also applicable to non-neoplastic disease. The proposed framework can guide future study design and research funding prioritisation.