The rapid dynamics of the healthcare industry has triggered changes in data analytics best practices because healthcare providers need access to real-time information. Even though we live in an age of virtual information, the demand for real-time data analytics is moving faster than most health providers expected.

Best practices enable sharing information through a secure IT platform for healthcare decision makers, comprised of community leaders, patients, and practitioners. In 2009, the healthcare industry underwent a major change with its first step toward electronic data analytics aligned with the industry’s best practices. The purpose was to create a method to improve health procedures and reduce costs, without compromising private information or loss of treatment quality.

To achieve the purpose, data analytics need to contain reliable and useful performance information. Integrating analytics software designed to fit the organization’s resources and industry best practices ensures the delivery of coordinated data. To understand the whole picture, you need to see how data analytics best practices impact healthcare activities.

Healthcare Industry Challenges

Data Analytics Best Practices

The biggest challenge for best practices has been the multitude of networks, each supported by individual applications that need to adapt data so that everyone is talking the same language. The industry’s data management requirements are straightforward. It comes down to healthcare operations integrating three data features.

  • Interoperability
  • Automation
  • Centralized data warehouse

Interoperability allows computer systems or software to exchange data generating analytic conclusions. The information is used to understand the past, current and future health status. The lack of interoperability is an obstacle for systems and healthcare practices struggling to use structured data.

Data analytics is a valuable management tool for making informed treatment decisions. The automated systems are programmed to find the gaps and address them without deleting the information. The goal is to improve healthcare approaches through actionable insights.

Technology can now centralized data collected from several sources accelerating sharing or collaboration accessibility. This feature would create consistency between patient information and general industry data reports. More important it allows retrieval of information and extraction of specific data, transforming statistical analysis into calculated data analytics.

Business Strategy Benefits

The government instigated the change and technology designed an application to manage and control the data. The next step involves configuring a business strategy using data analytics to improve the healthcare outcomes to the patient, secured population data, and healthcare performance.

Our knowledge and experience gained from the past have shaped the next course of action based on external and internal issues. Priorities have been defined and the goals are set. Formulating the data identifies the strengths, weaknesses, threats and the opportunities for improvements. Because the internal and external issues continue to evolve, the data needs to be stored centrally preventing any escape of critical information. The Performa measurements according to the parameters set up by the healthcare industry for systems should include:

  • Ease of extraction
  • Data standardization

Because no two patients or circumstances are the same, the ease of extraction allows commonalities to be visible quickly, enabling precision care decisions for standard or life-threatening events. The largest gain to the ease of extraction and creation of analytics is the attention to prevention to healthcare.

Standardizing how the pool of resources share and extract the information is critical to benchmarking the patient outcomes. Data analytics best practices will measure the performance of population health management based on value care.

Conclusion

Data Analytics Best Practices

Technology and healthcare share a similar trait, there is no single solution, as both continue to change. Uniting our future health may be brighter than many realize. Projected improvements are based on the quality and precision of data assets. Add data analytics best practices to the formula and we have an increase in performance based on the ability to make healthier decisions. In a world where healthcare conversations have become mainstream topics, there is a necessity to understand more precisely smaller aspects of the whole picture.

Almost everyone has been to the doctors’ office at some point or some other type of healthcare facility. Unless you are a returning patient, there are forms to fill out with a myriad of repetitive questions that we always seem to have to answer no matter where we end up.

This information is entered into a computer, and most likely, a chart of some sort is made. Vital information is then added. Then, the almost eternal wait for the doctor begins. So in some way, you have contributed to the healthcare data and to the continuous growth of big data.