Predictive analytics is gradually beginning to infiltrate the healthcare industry, growing at a rate of almost 30% over the next eight years despite minimal growth in the recent past. The successful integration of predictive analytics in healthcare has the potential to improve patient outcomes, increase operational efficiency, and result in increased treatment options and enhanced ease of treatment. However, the question remains as to whether or not the healthcare industry is fully equipped and prepared to properly use and benefit from the innovations that predictive analytics offers. Here are three major factors that healthcare institutions need to keep in mind when considering the impact predictive analytics can have:
Major Factors to consider to Understand the Impact of Predictive Analytics
Factor #1: People
As with many other industries, the cooperation and proper training of healthcare professionals on the use of predictive and data analytics in healthcare makes a big difference in the integration and overall success of analytics solutions. To gain actual benefits and form plans and strategies from the actionable insights that predictive analytics provides, healthcare workers must be properly trained on and informed of the purpose of predictive analysis and the results that healthcare institutions hope to derive from their use. This can, at times, be extremely challenging: for healthcare institutions with large workforces, training employees on the use of predictive analytics can be time-consuming, expensive, and difficult to coordinate. To get around these potential obstacles, healthcare institutions should properly budget and plan for training, and make predictive analysis a priority early on when forming strategies.
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Factor #2: Infrastructure
In addition to training and personnel, another important factor for the success of predictive analytics is infrastructure. Healthcare institutions must invest in appropriate analytics solutions and technologies in order to seek maximum benefit. Ideally, these institutions should already have some experience with an understanding of analytics and will be able to add predictive analytics solutions that work with their existing healthcare analytics services and solutions, making integration a much smoother process.
Factor #3: Use
Healthcare institutions need to have a clear idea of what they hope to get out of predictive analytics for healthcare. Healthcare institutions must decide what clinical decisions they want analytics and algorithms to inform, as well as how they will use the insights from predictive analytics. Predictive analytics has many potential applications, including reducing hospital readmission, solving staffing problems, identifying patients most vulnerable to specific hospital-acquired infections, and reducing budgeting and spend issues. Because of this wide variety of uses, healthcare institutions must decide how exactly they intend to use predictive analytics, what their priorities will be, and how they will go about deriving value from the results. Different institutions may have different priorities: for example, those that have experienced a high incidence of hospital-acquired infections will be more inclined to use predictive analytics to reduce infections than institutions where the incidence of hospital-inquired infections is already low. Healthcare institutions should use efficient analytics services and solutions to determine what they should be prioritizing and to avoid getting bogged down in a vast sea of data and predictions.
As data and predictive analytics become more involved with the routine delivery of healthcare, healthcare professionals and institutions will need to adapt to keep up with changing healthcare standards and new practices. They must consider whether or not they have appropriately trained staff and proper infrastructure, as well as proper and comprehensive strategies as to how they will use the insights and anticipated outcomes provided by predictive analytics. Despite the associated challenges, the healthcare industry can fully benefit from the increased use of analytics solutions and services simply through proper preparation and planning.