Page 9 - PATIENT REGISTRY DATA FOR RESEARCH: A Basic Practical Guide

Preface

Analysis of patient data can be a complicated and challenging process, especially

when the data involve many subjects and many variables. A patient registry is a database that

organizes collecting the important set of data on a list of identifiable individuals for a specific

disease. This type of data usually has tons of data and hundreds of different variables. Thus,

the approach to conducting research by using a patient registry database will be more

complicated than the other types of dataset. Since the handling of patient registry data is a

challenging task, the authors have come out with this e-book/book to become a guideline for

the statisticians, medical officers and scientists for them to refer as a handbook whenever

they need to use patient registry data for their research.

The objective of this e-book/book is to describe a basic practical guide on conducting

research using the patient registry. It is a guideline that has been drawn up from the wealth of

practical experience in conducting registry-based research and a widespread consensus of

various statisticians and clinicians. This guideline emphasizes data acquisition, data

preparation and approach for statistical analysis. It also includes a checklist that summarizes a

list of pertinent points for consideration by a novice researcher before he/she plans to embark

on a registry-based study. The checklist can be used as a tool to guide all researchers,

especially statisticians and clinicians, to plan and conduct a research study by using data from

a patient registry.

The ultimate aim of this e-book/book is to provide a standardization regarding the

approach to conducting research by using patient registry data. The benefits of using the

checklist provided by this e-book/book are to avoid problems that are commonly encountered

by researchers when they are conducting a registry-based study, such as failure to identify

pertinent ethical issues when handling patients’ confidential data, inadvertently obtaining

invalid study findings due to improper and/or inadequate data preparation for statistical