The Importance of Real-Time Analytics

By Col (Dr) Rajendra P Vennam

In the current healthcare system’s state of transformation, data is acquiring importance as an important resource. As the use of electronic devices for health necessity, electronic patient management and even smart gadgets wearables grow patients’ data continues to accumulate. However, it is not only data collection that matters but rather its efficient and real time data analysis that makes the real difference. If adopted appropriately, data-driven decisions can change the face of healthcare for the better, yield positive results for patients and cut costs as well as enhance efficiency. This, and other factors, the rapidity and accuracy of diagnosis leverages the very efficient real time analytics which is redefining how patients are managed.

The Role of Data in Modern Healthcare

In the past, medical input, clinical studies and previous studies have been the basis in making decisions in healthcare especially in management. Though these approaches are quite useful especially on research, they seem to be associated with delays and fail to address the specific repercussions on the patients at the moment. In any case, within a background of evidence-based care and medicine, the changes in clinical practices do facilitate a clinical leadership model with the use of clinical real time analysis and clinical decision support systems.

Data-driven healthcare is the use of data from a wide variety of sources such as electronic health records, medical recordings, medical wearables, genetic screening, etc. Information collected this way is processed and used for doing further actions that help healthcare specialists to recognize patterns, make forecasts, or optimize therapy schemes.

Why is Real-Time data analytic useful to the healthcare system?

Real-time analytics is defined as the analysis of data and making the information available in actable formats at once. Conventional or historical analytics is frequently concerned with data that is collected over a time period but real-time analytics provides information when it is relevant to events or activities. In this context, it could be determined as constant checking of the vital signs of the patients monitoring their conditions, examining test results on the flash as soon as the test is completed or forecasting possible threats before they become greater.

Big data in real-time analytics is managed using advanced technologies and tools such as machine learning algorithms and AI and cloud computing. Such measures incorporated into ‘the system’ offered to (wishful but necessary) providers of health care services should help improve the reaction time to changing patient state and other relevant circumstances.

Why Real-Time Analytics Is Important in Healthcare

Enhancement in Patient Outcome One of the greatest advantages of employing real-time analytics in healthcare relates to the enhanced patient outcomes. It helps in instantly giving the health caregivers a chance to respond quickly to any fluctuations in the condition of the patient. For example, the patient can wear a device that will check the heart rate, BP and oxygen saturation levels and issue an alert when something is off. This facilitates prompt action therefore lowering the chances of complications while hastening recovery.

In a case of emergencies, real time statistics can be equated to a shot of a miracle. In ICUs, for example, the patient’s vitals can be monitored in real-time while data is aggregated by AI systems which look for trends that depict the patient is beginning to tilt and needs to be fixed. Such enables the healthcare teams to act appropriately before it gets to an ominous turn.

Optimized Operation Optimization of healthcare activities-related operations through the application of real-time analytics is experienced across healthcare organizations. The current utilization of patient movement dynamics, resourcing-and-recruitment needs and facilities management in hospitals is given the considerations of time. As a result, waiting times are reduced and congestion is avoided together with ensuring that healthcare workers who are supposed to be working optimally are able to do so.

In addition, inventory control can also be enhanced using real time data analytics. For instance, through analytics, hospitals can gain insights into how medications and equipment are used, and address such issues as avoiding shortages and excess inventory.

Individualized Treatment

The era of using a single approach to deliver healthcare is gradually coming to an end. With real time analytics, the treatment of an individual can now be more targeted to the patient by designing treatment strategies with individual patient data. Measurements such as pulse, blood pressure, temperature and others can be monitored continuously so that any changes in health status and treatment adjustments are carried out in real time.

Predictive Analytics and Preventive Care

Real-time healthcare analytics is used to assist in the management of a patient’s current health care diagnosis and treatment. Real health data obtained through big data or other mechanisms is utilized with predictive analytics to help in predicting healthcare outcomes. For example, algorithmic pattern recognition may harness data from patients with chronic diseases to estimate the name in trouble most likely to be hit by a major aggravation such as heart failure or stroke.

The change toward a paradigm shift of more predictive and preventive rather than exclusively reactive treatment is indeed incredible. Because the healthcare providers will be able to nip most of the problems in the bud before they develop, a reduction in spending and improvement in quality of outcome is expected over time.

Implementing Real-Time Analytics The Problems Faced

Although real-time analytics has its advantages, there are issues that impede its practical use. A major concern is data integration. For instance, in the healthcare setting, there are such organizations which use multiple systems that do not always interconnect or communicate, making its hard to come up with a single data platform. Furthermore, in healthcare, heightened worries or concerns have to do with data privacy and security; for obvious reasons.

One more issue is the necessity of very high costs in terms of technology and training. Adopting real time analytics systems involves acquiring advanced technology and discourage human resources who collect and analyze data.

Healthcare management is slowly experiencing an overwhelming marketing insight through the use of data analytics, whereby the world of analytics as witnessed today, is trending towards the real time insight. Healthcare providers are empowered to make such decisions swiftly and accurately through the use of real-time analytics, this not only improves patient care but also the operational efficiency of the health providers and healthcare as a whole. Moving into the integration of real time analytics, no doubt transactional businesses or real time analytics in healthcare services delivers the right care at the right time in the right way and this will be preventive not just reactive care and bring better future generations.

(The author is Col (Dr) Rajendra P Vennam, CEO and CTO, Drucare, and the views expressed in this article are his own)