Big data is a large part of the global business landscape and healthcare is no exception. However, the combination of data and the end-user requires a particular talent, particularly in the healthcare industry in which sensitive data and the human element requires someone who not only understands data but who can also work with clinicians.
Healthcare organisations are finding it difficult to remain competitive and to fill this talent gap. Complex big data analytics can help them gain an edge, but this is a critical journey that will only provide actionable insights for improved service and offer a solid return on the investment of time and resources if done properly.. Visualization is a key component of this strategy.
The Importance of Visualization
When you imagine where your organisation will be in 5 or 10 years, you imagine the end result of a process yet without actionable objectives it may be difficult to reach your ultimate goal. This is where visualization helps you to chart your path. It allows you to process complex information and present it in a coherent fashion, bringing buy-in to your plan and understanding data science is critical to its success.
However, insufficient data can be detrimental, making finding the right personnel imperative, whilst the complex nature of data, particularly in healthcare, can be overwhelming. It can increase not only data complexity, but also its final model, potentially creating ineffective communication.
The most crucial step of any endeavor is the people. The visualization process helps people understand complex analytics and with it more effective communication, as well as accurately predicting consumer behaviors and impactful indicators for businesses. These actionable insights and behavioral understandings can also be used to alleviate organisational challenges such budgetary concerns and lack of buy-in.
The Need for a Talented Data Communicator
Big data gathered from artificial learning or machine learning data network applications helps inform the planning process, crafting a streamlined collection process.. Using the Internet of Things (IoT) in regard to patient-generated health data has spurred interest and opened a wealth of options to providers, however it requires a skilled data scientist and their team to analyse the information in order to create actionable insights. An effective data scientist can not only assist with the process, but also has the knowledge to explain the information to end users. The best of both worlds is a data scientist who can not only understand the complex data, but also someone who understands the industry, patients, and most importantly, the clinicians. This type of data scientist is the holy grail of healthcare data analytics with a skillset in high demand.
Though healthcare data scientists are in high demand and can command high salaries, healthcare organisations have notoriously tight budgets and few resources. There is still an opportunity to create a big data team through outsourcing, even if you can’t add one to your in-house team though this too has its advantages and disadvantages, particularly in regard to data security as well as dependence on the partnership.
Whether your organisation has an in-house team or has chosen to outsource, it’s important for these providers to conduct data integrity reviews and implement health information management programs. This helps to ensure clinicians also understand how to collect data and process it into actionable insights.
Developing the right infrastructure to retain members, improve health management, and raise the level of care using analytics can greatly improve quality and bottom line of healthcare providers, but it is having the right personnel to help develop this analytical roadmap into a solid technical and human resources understanding that will keep an organisation moving forward.
Topic: Mind the Gap – Closing the Big Data Analytics Talent Gap
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