Observational Health Data Sciences and Informatics

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====== Treatment Pathways in Chronic Disease ======

<WRAP box justify round>

**Objective:** The objective of this study is to characterize the prevalence of different treatment pathways for three chronic diseases: Hypertension, Type II Diabetes, and Depression.  We will systematically summarize the treatment pathways observed among patients who have at least 3 years of continuous observation and persistent treatment following initiation.  We will stratify the results by year to evaluate temporal trends, and will further stratify by data source to determine if treatment pathways vary by population, geography, and data capture process.

**Rationale:** While numerous treatment guidelines exist for chronic conditions, there is a paucity of data on the real-world treatment pathways that patients experience in practice. Understanding these pathways is essential for establishing context around questions of drug utilization, effectiveness, and adherence. 

**Project Leads:** Patrick Ryan, Jon Duke, George Hripcsak, Martijn Schuemie, Nigam Shah

**Coordinating Institution(s):** Janssen R&D, Columbia University, Regenstrief Institute, Stanford University

** Additional Participants:**

**Full Protocol:** [[https://dl.dropboxusercontent.com/u/505070/OHDSI%20treatment%20patterns%2030nov2014.docx|Hypertension Treatment Pathways 12-4-2014]]

**Initial Proposal Date:**  12/3/2014

**Launch Date:**  12/5/2014

**Study Closure Date:  12/31/2014**

**Results Submission:** [[mailto:contact@ohdsi.org|Email]] or SFTP

</WRAP>

===== Requirements =====
**CDM:** V4 or V5

**Database Dialect:** SQL Server, Postgres, Oracle

**Software:**  SQL as above, R (optional) 
 
===== Code ===== 
[[https://github.com/OHDSI/StudyProtocols]]

===== Discussion ===== 
[[http://forums.ohdsi.org/t/ohdsi-study-1-treatment-pathways-in-chronic-disease/112|Treatment Pathways Discussion Thread]] 

===== Datasets Run ===== 
  * Truven
  * Optum
  * CPRD
  * Indiana Network for Patient Care


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Observational Health Data Sciences and Informatics

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