This section allows you to post and view resources to support population health management in CKD.
Reading List & Learning Tools
Population Health Overview
Health Informatics Overview
- Textbook: Hoyt, RE and Yoshihashi, A. Health Informatics: Practical Guide for Healthcare and Information Technology Professionals. 6th ed. Informatics Education, 2014.
Successful population health management programs require tight integration with information systems and understanding of informatics principles. This textbook provides administrators, clinicians, and researchers a foundational understanding of the field of health informatics and is particularly valuable for those lacking formal training.
- Textbook: Richesson, RL and Andrews, JE. Clinical Research Informatics. 1st ed. Springer, 2012.
Clinical research informatics (CRI) deals with the application of informatics principles to clinical research. The discipline places a particular emphasis on data standards, quality, and re-use of electronic health record data to conduct clinical research, all of which are germane to population health management.
- Education: AMIA 10x10 Courses
These virtual courses provide focused training in specific aspects of health informatics. Classes are drawn from numerous academic institutions with demonstrated success in distance informatics education.
Defining the Population: Clinical Phenotyping and Cohort Identification
A "computable clinical phenotype" is a definition of a health condition or health event that can be applied algorithmically within an electronic health record to identify a cohort of patients. The 'phenotyping' terminology reflects the origin of these definitions in genetic association projects.
- Tools for electronic health record-based phenotyping (chapter in NIH Collaboratory Living Textbook of Pragmatic Clinical Trials)
Understanding the Population: Analytics and Data Science
- Book: Burke, J. Health Analytics: Gaining the Insights to Transform Health Care. 1st ed. Wiley, 2013.
- Education: Data Science Specialization offered by Johns Hopkins University via Coursera
Intervening for Improved Health
Patient Personas: Understanding Chronic Kidney Disease Patients and End-Stage Renal Disease Patients. Understanding patient types can give us a window into how they make decisions. Personas can help us represent patient types. Personas are not the “end all be all,” but they allow for representation of a larger sample of patients in regard to the context of clinical status, psycho-social status, socio-economic status and values, goals and preferences. These patient personas were developed as part of the Mayo Clinic's Project RED.
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