A data model can be defined an abstract model that organizes elements of data and standardizes how they relate to one another and to properties of the real world entities. A Physician Data Model is a type of data model that makes use of physician-level data in the healthcare industry to make similar models for the purpose of quality replication and information dissemination.
Data Modeling is a process that’s used in many industries. It is used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, the process of data modeling involves professional data modelers working closely with business stakeholders and healthcare data specialists, as well as potential users of the information system. For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner.
What’s Next for Physician Data
Model in Health Analytics?
The healthcare analytics market is expected to increase by 25 percent in 2018 and 2019, according to a 2014 iHealthBeat report. There are several factors that are expected to contribute to the global growth in health care analytics:
- Mandates for centralizing health care around the world
- Growth in the fields of prescriptive and predictive analytics
- Increasing investments by venture capital firms
- Increasing adoption of technology in the healthcare field
- The growing use of big data
- The increasing digitization of commerce on a global scale
- Quickly advancing technologies that provide a stream of new growth opportunities
- North America constitutes the largest share of the worldwide healthcare analytics market, the report found, in part due to the implementation of the Affordable Care Act and the recent changeover to ICD-10 Standards.
In addition, the 2009 economic stimulus package provided Medicaid and Medicare incentive payments for health care providers that demonstrate the significant use of electronic health records. These and other mandates are helping drive adoption of both electronic health records and healthcare information exchanges that promote using data in health analytics.
The Rise of the Enterprise
The potential for using physician data model in health analytics lies in the ability to increase the quality and efficiency of care while controlling costs. One technology driving the move toward widespread data use is the enterprise data warehouse, which enables analysis of enterprise-wide data through clinical, financial and operational lenses.
Enterprise data warehouses collect and analyze broad data sets, allowing health care providers to develop a deeper understanding of patients and all the factors that affect care. The technology can help healthcare organizations uncover and correct waste in delivery processes.
Despite many potential benefits of enterprise data warehouses, many healthcare organizations — more than nine in 10 — do not yet use the technology. However, adoption and beneficial use are growing in the industry.
Moving Physician Data to the Cloud
Almost everyone uses the cloud now. Tons and tons of information are being stored in the cloud and has given insight into the use of data for other purposes. Healthcare organizations are moving to cloud services for a number of reasons, including more effectively using data in health analytics. Organizations are experiencing a number of benefits from using cloud services:
- Increases in technological capabilities
- Faster deployment times
- Better financial outcomes
- Increased employee productivity
- Improved data security and regulatory compliance
- More efficient business processes
Cloud services in health care commonly support data-based functions, including hosting of clinical data and applications, data backup and recovery, and exchange of health information. More than 37 percent of organizations surveyed are using private cloud architecture, while just over 23 percent use public clouds and 36.3 percent use a model that combines public and private elements.
Many organizations incorporate cloud-based applications for hosting data related to human resources, finance, operations, and clinical and back-office functions. More than 21 percent of organizations noted that they use cloud-based applications in more than five departments.
Improving Quality, Reducing Costs
As the use of data in health analytics increasingly permeates the healthcare sector, organizations are expected to see improvements in efficiency and quality of care as they reduce costs. Patients can expect to reap benefits in better health outcomes and reduced financial outlays for care.