Can data analytics really reduce health care costs?
Postmodern times, it was a huge task to be able to track any kind of disease at all. This was one of the main reasons for many outbreaks of epidemics. Medical information was either unavailable or there was no medium through which it could be kept a track of. With the advent of technology, it became very possible to store massive amounts of medical records on PC’s which later moved to the cloud. The cloud technology enhanced the ability and opened new avenues of storing data and its accessibility. What seemed impossible to inform everyone about certain outbreaks where easily made possible with cloud technology. Data Analytics steps in when data has bee stored and now enabled people to occurrences of epidemics.
As the healthcare industry is continuously generating enormous amounts of data in various forms, it is almost difficult to manage this data in any of the traditional formats. The current trends and technology such as analytics are used to satisfy the healthcare requirements in an efficient way. This promising technique supports a wide range of healthcare organizations to improve their performance and ability to tackle major problems like reporting to government, adherence to privacy laws, enabling healthcare practitioners to make decisions better, etc. in the healthcare sector. Health care costs are driving the demand for data analytics-driven Healthcare applications to cut unnecessary testing and reducing fraud waste and prevention etc. It delivers better care for a better cost.
Some of the key areas where Analytics in combination with other key technologies like Cloud storage & computing, Mobile technology, Social Media, telecommunication, IOT (internet of things) continue to help the Healthcare sector in the following manner:
1 Reduce Patient Care Cost: By using analytics, healthcare organizations and clinicians are enabled to make decisions about patient care and operational efficiency that impact lives and save money. Combining nurse training with mobile device technology designed to help clinicians recognize early warning signs of high-risk conditions like sepsis and congestive heart failure.
2 Optimise Health Insurance costs: Health Insurance companies are shifting from fee-for-service compensation to value-based data driven incentives that reward high quality, cost effective patient care, and demonstrate meaningful use of electronic health records. Insurance service providers can leverage big data to understand optimum testing patterns across diseases and medical conditions and get hospitals to modify their standards of care and reduce the number of costly tests pushed onto unsuspecting patients. With this, commercial and government players can identify fraud before an eligible claim is processed.
3 Streamline Supply Chain: In health care, obtaining the right supplies, drugs and equipment of the right quality at the right location at the right time—and in the right quantity for the patient—is critical to optimizing patient care and safety. One way to reduce costs is to consolidate orders and buy necessary supplies in bulk, as well as to rationalize the supplier base to leverage volume and negotiate more favourable contracts. This can be achieved by looking at the historical records and using predictive analytics.
4 Preventive Maintenance: Using Data analytics tools, health care analytics teams can monitor essential hardware to predict and prevent breakdowns. the dashboard provides real-time visualizations of performance, enabling IT teams to predict breakdowns and seek solutions, or even to replace equipment’s proactively.
5 Spend Analytics: Operations staff can track all spend and procurement closely and make informed decisions when sourcing and contracting negotiations are on-going.
Nu-pie supplies data analytics services that are used in healthcare sector to improve the quality and reduce the costs and wastage. For more information contact us at email@example.com.