Healthcare Management agencies across the globe face rigorous challenges when it comes to managing healthcare information and formulating healthcare data for future predictions. Over the years, these challenges have taken a new magnitude defining an era that will require building a new road of possibilities in the development of Population Health Management or PHM, especially in countries like the U.S. and the U.K, where the healthcare cost is usually high.
Data Analytics, which is one of the widely used processes by various growing businesses, models and transforms data in order to draw useful information to support the decision-making process for future business needs. But, is it possible to imply data analytics in healthcare management? Would data analytics be beneficial to accommodate the growing requirements of Population Healthcare Management? This article discusses such questions and overviews the future of Population Health Management with data analytics in the current worsening COVID-19 situation.
Transforming the data analysis process from manual to automation
There is no denying of the fact that the current ongoing pandemic situation has taken a toll on the healthcare management system. From stringent analysis of a collective group of patients' data to gathering information and drawing conclusions, it all renders to a process that becomes complex within itself.
With various services moving to the online mode in the current pandemic situation—considering the "no-touch" and "maintain social distance" scenarios—there is a need for transforming data analysis and recognition from manual to automation, as this would make the process less and will effectively reduce the organization's cost on hiring requirements.
Utilizing Electronic Medical Records for analyzing patient's health data
It is easy to assume that working with paper records can promote easy analysis of the patient's medical records but, it isn't the case when the analysis is done on the grouped data coupled over for several months with the patient's history.
Data analysis on the electronic medical records (EMRs), in this case, proves to be a better alternative to tracking paper records with the patient's health history. Moreover, it becomes easier for the patient to transfer the EMRs from one hospital to another within seconds in an emergency situation. EMRs also prove to be a lot helpful in cases when there is a sudden requirement of a patient's prescription. The readily available electronic mode of prescriptions can save many lives.
Fostering data collection process and advancing health IT to improve PHM
Incorporating the data collection mechanism and utilizing health IT can enhance the overall functions of Population Health Management (PHM) by providing data on several patients in a group based on social determinants, geographical location, and age factors. This ability of data analytics to work on collective data and perform judicial analysis on the grouped form of patients' data can significantly improve the Population Health Management to achieve broader goals in a short time.
The cutting edge technologies in health IT provide various tools that can track and monitor a patient's health and keep a record of their medical history. These tools can also help the patients get in touch with their doctors immediately, schedule appointments, and get their medical reports timely without any hassle. Health IT, thus, enables the patients to take bare minimum efforts to keep track of their health check-ups and work effortlessly to maintain a healthy life.
Modifying fee-for-payment service models to value-based care model
While improving the PHM by effectively performing data analysis on collective data items to draw conclusions is one such aspect of enhancing the health care system, there are other factors as well which play equally an important role in promoting and upgrading health care management in the US.
The rising pressure of the COVID-19 situation has demanded many modifications in the current healthcare trend, and one such modification is transforming the fee-for-service payment models to value-based care models. This will analyze the overall cost and balance risk that can occur in the healthcare systems having payment support. If the healthcare systems foster a value-based payment model but lack a payment system, they will fail to deliver healthcare facilities to support PHM that recognizes individual healthcare data analysis or (collective) population data analysis.
Conclusion
The new normal has compelled the Population Health Management to take new call-to-action initiatives and bring about reforms that will improve and establish a plethora of possibilities in the entire healthcare dynamics.
Yes, Data Analytics plays a large part in analyzing health data, but it is not the only option left to transform healthcare management. It can be viewed as a back-up system to support healthcare perform better in terms of complicated analysis of collective patient's data. It is a mediator or a blessing to the health care systems to achieve broader objectives to perform better for you and your health. At the end of the day, it is us and the right choices that we make to improve our health and the healthcare system that we want.
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