Health Analytics

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Health Analytics

 

The healthcare industry is growing at a breakneck speed and along with it is growing the amount of patients’ data available to healthcare organizations. The magnitude of the data is such that it is expected to reach about 25000 petabytes by 2020. While the organizations add patient’s records to the data centers, majority of the data goes unused and along with it an opportunity to improve quality and efficiency in the healthcare sector.

Health data analytics is a growing industry which powers data driven transformations to combine data, strategy and health analytics to improve the way pharmaceutical companies think, decide and act. This industry is expected to grow more than $18.7 billion by 2020 even with roughly 10% of the respondents using advanced tools for data collection and analyzing healthcare data.
Health data analytics focuses on areas of supply chain analysis, financial analysis, clinical analysis, HR and fraud analysis. It allows for investigating how the clinical care can be improved without incurring excessive spending. Broadly speaking, health analytics is the process of delivering insights from patterns and correlations in the collected data to improve the healthcare decisions. It extends beyond the management of data to making predictions about chances of success and finding meaning in historical or real time data.

While it stands true that the data management and analyzing healthcare data are two different tasks of the healthcare analytics process. But there is no denying that the analyzing cannot take place unless the data is acquired, cleansed and integrated from various sources. With correct and credible data in place, the pharmaceutical or healthcare enterprises can begin the process of carrying out interpretation to inform future interactions with the patients and prospects.

The Federal Health IT Strategic Plan 2015-2020 includes several key initiatives to meet the final goal. These initiatives include:

  • protecting the privacy and security of health information;
  • finalizing and implementing an interoperability roadmap;
  • identifying, prioritizing and advancing technical standards;
  • increasing user and market confidence in the safety and safe use of health IT;
  • advancing a national communication infrastructure;
  • Collaborating among all stakeholders.

This strategic plan focuses on the steps federal agencies will take to achieve widespread use of electronic health information and health information technology (health IT) to advance person-centered and self-managed health, to enhance the health IT infrastructure, to transform health care delivery, improve community health, and to foster research & innovation.

Health analytics companies like Dcube can help examine the root cause of a response or lack of response from the prospects or patients. The overall goal is to use health data analytics to engage a large number of patients to improve the quality of life of every patient. Organizations that fail in analyzing healthcare data to monitor business procedures and processes gain clinical and financial insights fall behind the competitors over the course of time. Therefore, irrespective of where an organization lies in the maturity curve of health data analytics, key to success for a healthcare provider is to effectively analyze data to induce responses and enhance patients’ overall experience.

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