For years, big data and analytics have been buzz words across many industries including healthcare. Although data has long been held as the answer to healthcare's problems, it still hasn't come to fruition due to a lack of resources and resistance to adopting new technology.
In fact, a recent survey by KPMG found that only ten percent of organizations believe they are using big data and analytics tools to their fullest potential. Analytics offer deep insights into patient outcomes or highlight areas of improvement for specific patient populations. But the healthcare industry needs to lay the proper foundation to foster organizational alignment towards utilizing that data to unlock those unique insights around patient population health and factors impacting their care.
To ensure a successful transition and properly address roadblocks, healthcare organizations must establish a defined data repository and platform to properly store, view and manipulate information. Once the proper platforms are in place, mechanisms and tools need to be utilized, like analytics, to benchmark and track organizational progress. Although costly and time consuming, this is the building block that is fundamental to creating a data-driven approach to healthcare.
Once the infrastructure is established, organizations need to devise a roadmap involving the entire healthcare organization and remain committed. Big data means just that – there is a lot of information to work through and it's not something to dive into without a strategy. Healthcare organizations who align on a strategy towards analytics have experienced success, in fact, a Jvion survey found that 92 percent of analytics users are forecasting patient risk or predicting imminent illness. So, before sifting through endless amounts of information, it's important to understand and define primary goals that specifically address questions that need answers. For example, how can we predict which children are going to be at high-risk for health problems so that we can reach out to them, their parents and communities to improve outcomes. Also, having the right data to model the outcome is imperative. For instance, a health outcome like heart disease has many complex factors including genetic, behavioral and environmental factors but if the only data available is related to the financial health of patients than it may not be a good data model.
There are endless ways for organizations to gather insights from analytics. Geo-spatial mapping is an invaluable tool that can be used to recognize geographically-based relationships that are impacting the organization. This methodology maps the relationship between members and providers, both professional and institutional. Geo-spatial mapping capabilities are broad and allow users to visualize patterns in the data that may be hidden, highlighting location as a factor in health and providing actionable information. For instance, insurers can map the distribution of diseases and care demand, ensuring that they can match resources to member needs. In a particular case, geospatial mapping and analysis can display the region with high asthma prevalence and increased ER usage where urgent care centers are scarce or have a shortage of pulmonologists. With spatial analytics, these links can become visually apparent and illustrate where increased member services could be beneficial. These mapping tools would offer an invaluable resource for the development of more targeted member outreach programs aimed at reducing cost and improving the quality of service.
In addition to analytics being used to identify patients who are at high-risk for sickness, it can also track and inform healthcare organizations around wellness initiatives. This person-centric approach to health aims to not only maintain and improve health, but to improve overall quality of life as well as defray healthcare costs. It is a $10 billion and growing industry with at least 50 percent of companies providing some kind of wellness program to their employees. Analytics allows organizations to understand how effective their programs are for patient populations, determine who benefits the most and learn what motivates people to make healthy changes.
Establishing big data as more than a buzzword within healthcare is a slow process. The value that data can offer is recognized throughout the industry, but the infrastructure and clear, organized approach is sometimes lacking. However, change is imminent; analytics investments reached $197 million in the first quarter of 2016. If the industry continues to drive adoption and integration of data, there will be a noticeable transformation in how the healthcare industry treats patients. Analytics will bridge the gap in understanding how factors in health, like genetics and environment, affect one another. As more and more data becomes available, healthcare can truly become patient-centric. The future is bright for both analytics and healthcare and it's a future where big data is no longer a buzzword, but an integrated part of every organization.
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