This is the second half of my thoughts on the question “When will the IT industry provide reusable clinical and administrative data warehouses for the Medicaid enterprise?” The first posting discussed the current models and systems, and enumerated some barriers to creating a common data model. In this post I consider how to overcome the barriers to reach the goal of a comprehensive data model for analytics and administration for the HHS enterprise.
How might these barriers be overcome? How might a common data model be created and adopted?
The profit motivation of commercial business combined with the altruistic drive for health care solutions shown by standards organizations is the most powerful and likely path to a successful HHS data model standard. One example of this success is the Consolidated Clinical Document Architecture (C-CDA) developed by HL7 and adopted by CMS for Meaningful Use regulations.
Creating a common model is challenging in any industry, but has been accomplished by industry groups for accounting and government billing. Industry and vocational groups provide the most promising avenue for development of enduring standard data models. Business focused non-profit standards organizations coupled with government target-setting has been the most successful approach in the finance industry, and is the best path to a standard model for HHS.
However, healthcare industry standards organizations dealing with IT have less history and weaker accreditation associations than some other industries, e.g. accounting and finance. To the large healthcare IT organizations, and to the medical profession itself, there is still significant financial dis-incentives to promote interoperability. This leads to lackluster results in health and human services data model standards. Two promising standards come from Health Level 7 (HL7) and Observational Medical Outcomes Partnership (OMOP).
- HL7 – Reference Information Model (RIM) http://www.hl7.org/implement/standards/rim.cfm
- OMOP – Common Data Model (CDM) http://omop.org/CDM
These models are designed for a specific purpose to meet a specific need. Consequently they have limited scope, and are for the most part, very generalized. These models are hindered by their development process… development by committee, and also by the need for a solution that attempts to satisfy everyone at the cost of specificity. The result is a “one size fits all” data model containing compromises, including some designs using academic/institutional logic rather than direct business requirements.
Effects of establishing a common data model
If a common data model is established, would the healthcare IT industry respond?