Utilization of Mental Health EHR Data to Identify Candidates for Chronic Care Health Homes in Kansas: Defining a Process to Identify Candidates Pubblico
Yang, Seng (2014)
Abstract
Background: Chronic conditions and mental health disorders are both common and compromise the quality of life for affected individuals. Mental health centers in Kansas are particularly interested in identifying individuals at their center who may have a qualifying chronic condition, are not classified with severe mental illness, and are not currently enrolled in a Health Home.
Purpose: Kansas adopted the Health Home model that is positioned to support individuals with chronic conditions. Health partners are concerned not all qualifying patients will be identified as candidates for Health Homes. Therefore, the purpose of this study is to define a process to identify candidate patients for enrollment into Chronic Condition Health Homes from the Kansas mental health EHR.
Methods: A data flow analysis was completed on the Kansas Mental Health Electronic Health Record system. The analysis identified where relevant clinical data were being captured within the EHR for use in identifying chronic conditions. A data model of the Kansas Mental Health Electronic Health Record system was created to help depict relevant data tables and a set of structured query language (SQL) queries was defined to extract relevant clinical data from structured and unstructured data fields.
Results: A process was defined that includes six SQL queries to extract relevant clinical data from the mental health electronic health record system and identify candidate patient. Four SQL queries aim to extract clinical data held in the system as structured data and two SQL queries were developed that would allow for extraction of unstructured clinical data.
Conclusions: The developed SQL queries directly links to relevant tables that hold the clinical data, structured or unstructured data, within the Kansas Mental Health EHR. The SQL queries for the structured data should be able to directly extract the required information for qualifying members with the chronic condition of asthma, extensible to additional chronic condition, based on the process defined through this research. The SQL queries for unstructured data need further analysis to determine if the data extract meets the correct criteria for enrollment into a Health Home. All the queries require testing against actual data to verify anticipated results.
Table of Contents
CHAPTER 1: INTRODUCTION 8
CHAPTER 2: REVIEW OF LITERATURE 15
CHAPTER 3: METHODOLOGY AND APPROACH 30
CHAPTER 4: PROCESS TO IDENTIFY INDIVIDUALS WITH CHRONIC CONDITIONS 34
CHAPTER 5: CONCLUSIONS, LIMITATIONS AND RECOMMENDATIONS 53
APPENDIX 58
REFERENCES 64
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