As the motto implies, EHR Science is about the design and implementation of clinical systems.    Over the past two years, my personal explorations in architecture/design, discrete math, workflow and software development tools have lead me to search for underlying principles and precepts that could make EHR design less of an art and EHR implementation less of a gamble.  The posts listed below reflect the key topics that have emerged from my explorations. They also serve as introductions to the subjects I’ll be writing about over the next six months.    Enjoy…

Data Quality
Wrestling with EHR Data Quality

Data Stores
Database Shopping
Investigating NoSQL for EHR Systems: MongoDB

Graphs
Workflow Analysis–Doing the Math

Logic
What Are You Trying to Infer?
What Are You Trying to Infer? – Part 2
Universal Implications, External Validity, and Thomas Kuhn

Petri Nets and Workflow
Clinical Workflow Analysis: The Value of Task-Level Detail
Petri Nets and Clinical Information Systems—A Perfect Match
Petri Nets and Clinical Information Systems, Part II: A Closer Look at State
Petri Nets and Clinical Information Systems, Part III: Modeling Concepts and Tips

Software Design/Architecture
Software Architecture and Design, First Steps
Coupling and Cohesion: A View of Software Design from the Inside Out
Exchanging Data with JSON
SaaS EHRs, MVC, Flexibility and Innovation

Usability
Software Interaction Patterns: A Guide to User Behaviors

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