Healthcare has lot of data coming from various internal and external sources. Integration of Electronic health records has proved to be a great helping hand for doctors as well as pharma companies in systematic collection of patient data. But only collection of data is not worth, its analysis is required to find out valuable insights that can prove to be beneficial for doctors as well as pharma companies. As the data is huge, its analysis is not at all an easy job and requires an expert solution.
Big data opportunity for healthcare providers
Big data has the potential to analyse the huge data collected in a healthcare organization and provide valuable insights that can transform the life sciences/pharmaceuticals and healthcare industry. EMR Solution is the stepping stone for this analysis. When analytics is applied on the data collected in EMR Solution it can effectively track the at-risk patient population and improve management of chronic diseases. This will automatically improve the operational efficiency of the organization. In addition to these, it can also help the organization to better foresee and manage issues that result in emergency department visits, lengthy hospital stays and readmissions. This can be managed by Comprehensive population health management.
Core capabilities of Comprehensive population health management
- Interoperability and openness: A comprehensive population health management system should be secure and information should be readily available to providers and other stakeholders so that proven, consistent and high-quality care is given to every patient regardless of their location.
- Actionable data: It should logically generate accurate data and valuable insights that will help the providers in making better informed decisions at any point of care.
- Patient engagement: Most importantly it should encourage the patients in actively exchanging the information about their health and also engage them with their care team and adopt healthier habits through various wellness programs.
Although Big data is capable of solving the data management and integration challenges but there are few other challenges of Big data itself that need a team with a high level of industry knowledge and expertise. That is why now IT industry is recognizing that big data represents a substantial and growing market opportunity. But to meet the escalating demand for better data there is a need of variety of tools that must be designed to help everyone from patients to physicians and researchers. The tools should be able to identify insights and derive value from big data that can improve healthcare outcomes. But these tools should be able to meet the weighty compliance requirements surrounding HIPAA and other regulations while maintaining patient privacy.
This is not all, a thorough understanding of the requirements of the healthcare organization and roadmap to fulfil those requirements should be planned to help any healthcare organization in utilizing the big data to make a difference in research and development, patient outcomes and fiscal health. This can only be done by industry experts.
Possible insights from Big data in healthcare
Big data holds the promise of helping the life sciences/pharmaceuticals and healthcare industry by giving following valuable insights:
- Most effective treatment for a group of patients
- Identify patterns responsible for hospital readmissions
- Ways to move to a value-based model
- Identify and address quality inconsistencies
- Accelerate time-to-market for effective new products
- Reduce cost of care
- Consumers and their buying patterns
- Better access to healthcare information for research
- Larger and quicker clinical trials
- Make strategic decisions and spur innovation
- Enhance customer relationships
For all the above facts, every healthcare organization is now adopting Big data and its relevant tools like hosting the program in the cloud. The cloud-based solution not only enables effective communication between disparate systems but also proves to be beneficial in terms of far less investment of time and cost as compared with in-house infrastructures. It also quickens the data aggregation process and increases the flow of data, facilitating faster access to information.
Matt Wilson
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