The more we hear about data, the more we realize its importance and relevance. Spreading all around the globe impressively fast, it has already become a vital component in a number of industries. While some are already making data-driven decisions to increase their revenue or attract new customers, others are only beginning to learn how to improve processes within their companies using data.
Healthcare data today is developing quicker than ever. As reported by MarketsAndMarkets, by 2024 the global healthcare analytics market is estimated to reach $50.5 billion at a compounded annual growth rate (CAGR) of over 28%.
In particular, the majority of organizations today recognize BI platforms as a smart solution to deal with challenges met by healthcare workers. Tools like Tableau, are trending due to the growing demand of its features. These features include comprehensive dashboards and processing healthcare data from various sources typically configured by consultants.
But what is the actual applications of data in healthcare and how can it change the industry?
From the moment they feel sick to the moment they are discharged from the hospital; patients are a part of a complex web of procedures that may either improve or worsen the situation. Data analytics supports the creation of an ideal environment in which healthcare organizations can work at their best.
While diagnostics still depends on physicians, data analytics is able to improve the diagnostic process to a great extent. Analyzing medical histories faster than any doctor, analytical tools process data about symptoms, side effects caused by previous medication, the patient’s habits, and other relevant data to suggest a diagnosis and a treatment, which facilitates the challenge of dealing with many patients at once.
Genetic markers, habits, medical history—all of these play a crucial role in one’s well-being and response to treatment. Yet, these are extremely hard to track and put into practice, especially when there is a limited number of medical personnel to handle large numbers of patients. Analytics automates data tracking and visualization and thus reveals patterns, impact on patients, and better recovery strategies.
One of the areas significantly influenced by BI is cancer treatment. With big data analytics, it’s easier to investigate genetic changes each patient undergoes, as well as the treatment effects. This contributes to the creation of effective personalized treatment plans.
Caregiver performance can be tracked and corrected faster and more efficiently with the help of automated analytics. Internal data analysis, surveys, social media sentiment analysis and other data-oriented processes can provide healthcare managers with an opportunity to estimate caregivers’ approach and effectiveness as well as the costs of the recovery period.
Predictive analytics is perhaps one of the most important advantages brought to any industry by advanced business intelligence systems. Healthcare is where it is truly crucial.
Unlike humans, BI software can analyze unlimited amounts of both historical and real-time data, contributing to the positive course of treatment and leading to better outcomes.
Until recently, the factors considered in one’s medical history were blood pressure, age, and hereditary conditions. Today, we have a unique ability to trace patients’ habits, working conditions and living environment. Analyzing combinations of these factors, predictive analytics lets professionals take steps to prevent diseases. For instance, tools can identify patients with suicidal and self-harming tendencies and provide professional help. Also, predictive analytics is effective in preventing readmission. In particular, it can identify the reasons patients fall into a risk group and provide insights on how to avoid this.
Implemented in healthcare organizations, predictive analytics brings care delivery to a new level, where early intervention may result in reduced costs, efforts, and stress for both patients and caregivers.
Making use of data analytics, industries aim at financial gain, and healthcare is not an exception. To organize patient care and administrative operations in a way that is effective and profitable, organizations have to make the most out of their analytical capabilities.
Healthcare BI software reveals patterns and insights about an organization’s budgeting and expenses, thus contributing to decision making. Analyzing metrics such as patient care costs, the most and least profitable services, underused inventory, the busiest times of the day or week, data analytics allows organizations to improve how they plan their schedules, procurement, and budget overall.
Particular attention should be paid to prescriptive analytics. By comparing analogous drugs it helps find treatment strategies and medications that might work more effectively at a lower cost than the ones currently in use by the organization.
How to Implement BI Successfully?
- Healthcare is rich with various data channels, but multiple sources may be difficult to analyze all at once. In order to avoid overburdening your in-house analytical capacities, start with a limited number of reliable sources that provide the most important information.
- To make the most out of data, organizations need to adopt a data-driven culture—the one in which each team member has access to data, knows how to turn it into valuable insights, and, which is more important, recognizes data as a critical element of the decision-making process.
- Data protection and compliance should be at the core of any organization’s practices, and it becomes more relevant with the adoption of a BI platform. Due to the sensitive nature of data in healthcare, the safety of information plays a significant role in the industry. So, executives should take all the steps required to keep data protected.
- Once you are ready to make BI part of your routine, you need to decide on whether to employ a professional team of analysts or democratize data and let it spread within the organization. The latter approach will let decision-makers get information to act upon without delay and share insights with their colleagues.
In healthcare, data is a powerful asset that can bring value to patients, care providers, and stakeholders across the board. When aggregated from reliable sources and made useful through dedicated business intelligence systems, it can nurture everyday clinical decision-making, population health initiatives, and cross-facility collaboration.
This approach is not without its adoption pitfalls, though, so it takes extra preparatory steps in line with the data-driven organizational mindset, some of which are outlined above.