Improving population health using electronic health records : methods for data management and epidemiological analysis

著者

書誌事項

Improving population health using electronic health records : methods for data management and epidemiological analysis

Neal Goldstein

Routledge, 2017

  • (hbk)
  • (pbk)

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注記

Includes bibliographical references

内容説明・目次

内容説明

Electronic health records (EHRs) have become commonplace in the medical profession. Health data are readily captured and permanently stored in a digital fashion, and consequently, are increasingly being utilized in health research. The quality of this research depends upon the investigator's ability to obtain the correct data to answer the correct question. It is easy to churn out poor quality research from the EHR; it is much harder to produce meaningful results that influence the population's health. Improving Population Health Using Electronic Health Records takes the reader through the process of conducting meaningful research from data in the EHR. It de-mystifies the entire research process, from how to ask the right kind of research questions, to obtaining data with particular emphasis on data management and manipulation, to performing a valid statistical analyses, and interpreting and presenting the results in a clear, concise fashion that has the potential to improve population health. This book can be used as a hands-on how-to guide of performing research from EHR data in either a piece-meal fashion, selecting only the topics of greatest interest, or a complete guide to the entire research process. Readers will benefit from the intuitive presentation of complex methods with a multitude of examples. It is invaluable reading for researchers and clinicians who are not otherwise familiar with the complexities of working with large data sets.

目次

1. Research in the era of electronic health records 2. How to use this book for research Part 1: Understanding the data 3. Planning the research 4. Accessing health data 5. Organizing, merging, and linking data 6. Data management and the research dataset Part 2: Conducting the research 7. Study design and sampling 8. Measures of frequency and risk 9. Threats to validity 10. The analytic dataset 11. Epidemiological analysis I 12. Epidemiological analysis II Part 3: Interpretation to implementation 13. Interpreting the results 14. Publication and presentation 15. Improving population health Appendices

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