At the most strategic level, the role of a data management strategy to a healthcare organization is one of unifying the diverse set of information assets, systems, processes and platforms into unified architecture that can support an organization in the attainment of its objectives. Data management strategies have progressed far beyond the development of static, difficult-to-change data structures that take months to re-architect to meet internal information requirements (Hickman, Smaltz, 2008). The focus of data management strategies in healthcare are centered on creating a more agile, patient-centered and market responsive IT architecture that can flex over time to the needs of stakeholders and served communities (Tan, Payton, 2010). Another critically important aspect of an effective data management strategy in healthcare is the exponential increase in the reliance healthcare providers have on analytics. The real-time reporting of analytics, key performance indicators (KPIs) and metrics is now driving disruptive innovation throughout many healthcare organizations globally as they are gaining greater insights into their operations than they ever had in the past (Hickman, Smaltz, 2008). Data management strategies in healthcare organizations make all of these innovations possible and drive greater levels of intelligence and insight into healthcare providers than ever before. It all starts with a scalable, effective data management strategy that unifies all available information assets.
¶ … Management in Healthcare
What is the importance of a data management strategy to a health care organization?
At the most strategic level, the role of a data management strategy to a healthcare organization is one of unifying the diverse set of information assets, systems, processes and platforms into unified architecture that can support an organization in the attainment of its objectives. Data management strategies have progressed far beyond the development of static, difficult-to-change data structures that take months to re-architect to meet internal information requirements (Hickman, Smaltz, 2008). The focus of data management strategies in healthcare are centered on creating a more agile, patient-centered and market responsive IT architecture that can flex over time to the needs of stakeholders and served communities (Tan, Payton, 2010).
Another critically important aspect of an effective data management strategy in healthcare is the exponential increase in the reliance healthcare providers have on analytics. The real-time reporting of analytics, key performance indicators (KPIs) and metrics is now driving disruptive innovation throughout many healthcare organizations globally as they are gaining greater insights into their operations than they ever had in the past (Hickman, Smaltz, 2008). Data management strategies in healthcare organizations make all of these innovations possible and drive greater levels of intelligence and insight into healthcare providers than ever before. It all starts with a scalable, effective data management strategy that unifies all available information assets.
2. How can the service process model be used to achieve enterprise resource planning and single data entry points through the multiple organizations?
The service process model is predicated on the concept of defining the core business processes, their improvements and synthesis of key workflows, and then unifying them to a common series of strategic objectives. The service process model is also predicated on a very clear concept of governance unifying information systems, databases, and the resulting workflows that are driving the main functional areas of the enterprise (Tan, Payton, 2010). The critical task of redesigning the most critical business processes in a healthcare organization is first completed and the service process model used to re-align IT systems to governance requirements (Hickman, Smaltz, 2008).
Once processes are aligned to the specific compliance frameworks of the healthcare organization, the IT systems are mapped to the areas that can be automated the most effectively. Automating the business processes then defines each of the data entry points as they relate to business processes and the overarching governance requirements of the healthcare provider (Hickman, Smaltz, 2008). This ensures each data entry point has a very clear purpose in the overarching development of the enterprise-wide IT systems throughout a healthcare provider (Tan, Payton, 2010). By taking this top-down governance and process management approach to defining an IT structure with data points, a healthcare organization can also ensure a much higher level of security to their entire network as well (Dwyer, Reiner, Siegel, 2004). Aligning IT spending to processes and governance frameworks ensures a higher level of performance.
3. Describe a situation where you would use a CHIN or RHINO system to provide care. How would you utilize cloud computing?
The Community Health Information Network (CHIN) and Regional Health Information Network Organizations (RHINO) are best suited to serving a broad base of patients across a wide geographic and socioeconomic area. The CHIN platform has been specifically tailored to the development of metro and urban requirements, with success in supporting preventative health education and treatment programs (Hickman, Smaltz, 2008). The RHINO network architecture also has been tailored to larger urban environments, and also found use in those regions that have very broad geographic areas that defy coverage by clinics and regional healthcare providers (Hickman, Smaltz, 2008).
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