Advanced Analytics – A Gamechanger for Healthcare
on 30th August, 2017
Advanced Analytics in healthcare is a trend to watch out for. Predictive Analytics and Machine Learning in healthcare are rapidly becoming some of the most discussed, perhaps most-hyped topics in the field of healthcare analytics. Worldwide, there is currently more information generated in a single day than we could possibly absorb in an entire lifetime. Needless to say, the healthcare industry is evolving at a rapid pace.
Predicting Hospital Readmissions through Population Health Management:
Opportunities for improved patient care and motivation to avoid financial penalties have resulted in a rapidly growing interest in predicting hospital readmission as is represented by the graph below:
Fortunately for healthcare, there are numerous existing models from other industries that are very efficient at Risk – Stratified Care Management (RSCM) in the realm of population health management. However, implementation itself may prove to be a challenge as it requires a hospital system to be prepared to embrace new methodologies. This may require a significant investment of time and capital and alignment of economic interests as well.
For the healthcare industry, like other industries, predictions will always be more useful in the framework of a more complete set of data, where the knowledge can be fully leveraged to action. Also, healthcare organizations need to be cognizant of their readiness for change, enabling them to create a plan that will enhance the organization’s ability to successfully drive change.
Challenges in implementing Advanced Analytics in Healthcare
- Developing cross-functional teams that understand data
- Recognizing that data is an engine for growth instead of a back-office function
- Developing a process-orientation around data and analytics
- Educating the public and developing policies that balance the interests of insurers with public privacy concerns
- Helping providers to develop robust data infrastructures.
This can be explained by the below given graphic representation. The graph clearly shows that 80% of the thinking process is spent on data preparation and data exploration, which forms the cohesive part of any implementation. This source is totally based on inputs of past records and current admissions, which can be obtained by remodeling the system.
Leverage Advanced Analytics with KloudKare IntelliKx
As part of KloudData’s KloudKare healthcare information framework, KloudData has released a highly sophisticated application suite “KloudKare IntelliKx” focused on patient satisfaction and consistent positive outcomes. As the name suggests, IntelliKx brings advanced intelligence into healthcare analytics. This healthcare application suite offers a gallery of advanced analytics applications that empower hospitals with timely and actionable information. IntelliKx helps you achieve the objectives of population health management along with risk stratification to focus on the patient care more proactively.
Interested in learning more about KloudKare IntelliKx? Request a Demo.