Business Intelligence in Healthcare

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Table of Contents

Introduction
The State of Health BI Today
Cutting Healthcare Costs with BI
Wearable Technologies
Artificial Intelligence in Decision Making
Conclusion
References

Introduction

Large volumes of data gathered by healthcare organizations impede their analysis and effective use. Generating reports from big data requires extensive labor and much time, though the result may still lack reliability. In an effort to improve care quality, healthcare providers are applying IT-enabled business strategies, a key component of which is the application of business intelligence (BI).

BI systems take critical operational data and combine them with analytical tools in order to give comprehensive information to managers and decision-makers. This facilitates and improves the timeliness and quality of inputs to the decision process. Even though BI systems become widely used in healthcare, the changes to which they may lead in the future are still unclear. The given essay discusses the current benefits of BI and possible breakthroughs in preventative health, which may come about because of the use of such technologies.

The State of Health BI Today

Even though healthcare organizations have just moved into the data-driven world with BI systems, there are already great advancements in the industry. In particular, they include insurance provider benefits, streamlined emergency rooms, and improved patient healthcare (Moscovici, 2015). Insurance provider benefits are associated with getting a clear picture of healthcare spending and avoiding coverage gaps and duplication.

Quality of patient healthcare has now significantly increased as BI applications enable physicians to see how treatment correlates with outcomes. Data dashboards may be used in emergency rooms to track and keep information in one place. This will enable the person to have a better overview of patients and recognize the significance of their needs. Apart from that, BI promises to not only improve patient outcomes but also to reduce costs and streamline the care process for healthcare organizations.

Cutting Healthcare Costs with BI

Despite the fact that there are certain barriers to the use of digital technologies in healthcare, one may suppose there are several ways how the use of BI may revolutionize this industry. To begin with, the use of BI will help save as much as 25 percent or more in annual costs of health organizations over the next several years (Society of Actuaries, 2018). The ways to achieve saving funds include the cutting rate of hospital readmissions, forecasting operating room demands, optimizing staffing, and minimizing costs by maximizing patient care.

A considerable number of hospital readmissions are considered to be a significant cost burden for healthcare organizations. This issue is rampant in the US, and it may be explained by the fact that discharged patients get confused when they return home and have no idea how to take care of themselves. Incorporating prediction models based on risk factors of being readmitted and establishing protocols on how to deal with patients with high risks of readmission will significantly lower costs on re-hospitalization.

Optimizing operating room use may reduce costs on its building, equipping, and support. In this respect, BI may serve as a powerful tool in better understanding the relationships between operating room variables, which adversely affect scheduling. These variables may include “surgeon availability and preference, operating hours, and equipment availability and functionality” (Edwards, 2017). BI software may be of help in scheduling an operating room, studying its operation patterns, and rational matching the operating rooms with the most suitable human and support resources.

Another way to trim costs is by optimizing staffing by means of BI systems. Predicting demand in advance to match personnel and resources may help avoid incurring expenses. Using BI in making forecasts will help establish workforce requirements beforehand. BI is also critical in delivering high-quality care and ensuring patient safety. Elaboration of algorithms to forecast emergency medical situations will allow clinicians to react to events much faster and make quick decisions much more accurately. Apart from that, BI technologies may be used for making accurate on-the-spot diagnoses and swift detection if hospital admittance is required.

Wearable Technologies

Medical research is among the areas in health care, where the power of big data has had the most visible impact. Therefore, one may suppose that medical data may be collected using multiple sources, such as invisible or implanted wearable devices. In the future, smartphones with biosensors and wearable devices may create continuous streams of health data to measure almost any health parameter of people without the need to go to the doctor. This would mean that information and health variables would finally not only be available in the healthcare facility but also at home. This may lead to the betterment of health management and one’s lifestyle.

Also, patients will no longer need to experience physical illness to get medical attention as the wearable device will be able to sift out early signs of diseases and infections and report this information to a doctor (Dusheck, 2017). In particular, this refers to the early detection of sepsis, which is a major issue in the US healthcare system. In fact, a majority of people already agree that they would be excited to experience wearable technology from a doctor (65%), from a hospital (62%), or a health insurance company (62%) (PWC, 2016). Therefore, wearable technologies have all the potential to be widely used in the future.

Artificial Intelligence in Decision Making

As BI solutions evolve, healthcare organizations can take advantage of artificial intelligence features to assess more data. In the future, artificial intelligence technology may be expected to be standard in the majority of BI solutions. A considerable percent of analytic queries will be generated using natural language processing or will be auto-generated by artificial intelligence. The most significant potential breakthrough is associated with the use of artificial intelligence in the decision-making process.

Even though nowadays, it is hard to imagine, but in the future, supercomputers may be used for giving medical treatment recommendations, patient data processing, medical diagnosis assistance, and converting paperwork into digital data. Also, supercomputers may automatically generate reports, check medical records, and be involved in hospital patient management systems and biomarker discovery. With the growing demand for improved healthcare, artificial intelligence will be the tool that helps align the interests of doctors and patients, as it will provide more transparency and accountability to the healthcare system.

Conclusion

To sum up, the healthcare industry has undergone a significant evolution shifting from a paper-based records system to a more efficient system with BI, which helps manage the massive amounts of structured and unstructured data. Today’s business intelligence tools offer hospital clinical and executive leadership visibility into the operation of their organization, which allows them to reach their objectives and minimize the costs.

With the development and proliferation of BI, the healthcare industry can offer more personalized and cost-effective care systems. The potential breakthroughs associated with the use of BI include cutting healthcare organizations’ costs, collecting data on one’s physical condition via wearable devices, and incorporating artificial intelligence in the decision-making process.

References

Dusheck, J. (2017). Wearable sensors can tell when you are getting sick. Web.

Edwards, J. (2017). Predictive analytics cut healthcare costs. Web.

Moscovici, M. (2015). How can business intelligence improve healthcare? Web.

PWC. (2016). The wearable life 2.0: Connected living in a wearable world. Web.

Society of Actuaries. (2018). 2018 Predictive Analytics in Healthcare Trend Forecast. Web.

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