Forecasting Patient Care with Predictive Analytics
Predicting patient outcomes with the help of Blockchain and AI data analytics, enabled by interoperability for seamless data exchange.
Peace of mind comes from reassuring your safety and well-being, so what if you were able to accurately predict your health outcomes before it’s too late? This is referred to as “Predictive Analytics” and is critical for solidifying the security you feel when you can prepare…to prevent.
To put it simply, a predictive analysis involves pin-pointing patterns in patient data history to then anticipate potential risks and outcomes, enhancing provider decision-making. [1] To be able to decipher these patterns in real-time, specific algorithms are created and guided by collectively using mining strategies and machine learning tools, like Blockchain and AI (BAIB), that have the power and accuracy to produce optimum results and insightful outcomes. That’s not all though; predictive analytics can also help healthcare organizations make insightful improvements to their operational efficiency, while strengthening patient data security. [4]
As mentioned in “Trends that are Sculpting Digitization in Healthcare,” predictive analytics is beneficial for reducing waiting room time, medication errors, readmissions, etc. Predicting potential health concerns based on a patient’s history can help speed up action time and reduce chronic outcomes for patients. This is a constructive method for providers to prioritize their focus on administering holistic care that not only has prolonged benefits but catches any problems before they become irreversible. [2]
Enabling Predictive Analytics
Step 1:
Permitting Data Democratization with the help of BAIB
Why is Data Democratization the first step in predictive analytics? Well, how do you analyze crucial data that you don’t have access to? You can’t. If a provider only has access to the first layer of a patient’s data history, the consistency of the patterns revealed in the analysis will not be reliable enough for you to make an adequately educated projection of their future health outcomes.
Think of it this way, you are planning a trip and are trying to figure out which hotel will be the best option, but is it better to make your decision based on three reviews or 300 reviews? Of course, the answer is always 300 reviews, that way you have a deeper pool of guest experiences to compare and make connections between.
Now you may be wondering, what does BAIB have to do with creating a data democracy? These software tools ensure data security once transfer rights are relinquished to providers. If data security is guaranteed, healthcare legislators will repeal the rules and regulations that prohibit data democratization.
Assuring that data is safe in the hands of AI and blockchain technology opens the door for seamless data exchange between providers; although, that’s not where BAIB’s role ends – once data sharing is enabled, BAIB continues to secure that data, while analyzing various patterns hidden in its history.
Step 2:
Successful, Secure Interoperability
Secure data freedom facilitates interoperability – the digital connectivity between various platforms and systems. To supplement interoperability, AI and blockchain functions are used collectively to safely communicate correct data between those systems that have been connected digitally.
Essentially, interoperability enables data to securely gather in a blockchain database that then uses AI analysis to identify premature patterns that are too subtle to normally pinpoint. Organizing and
compartmentalizing those patterns into risk categories to classify their severity as it pertains to the patient is what enables provider predictions. [1] Blockchain helps AI scale to complete an optimum analysis for the most intuitive insights and accurate predictions, while sustaining a trusting and transparent foundation between the patient and provider. [3]
Step 3:
Perform Predictive Analytics
Bring IT Solutions
A patient’s success starts and ends with the provider’s expertise and preparedness. Bring IT is dedicated to enabling successful interoperability for providers to be as prepared as possible when administering patient care. Ensuring seamless communication with 360° digital interoperability is the best practice for scaled operational efficiency and success for emerging healthcare trends. We will continue providing insightful solutions that enable actionable predictive medicine so providers can focus on what matters most: putting the patient first.
Sources
Sources
[1] Giordano C, Brennan M, Mohamed B, Rashidi P, Modave F and Tighe P (2021) Accessing Artificial
Intelligence for Clinical Decision-Making. Frontiers in Digital Health, Vol 3:645232. doi:10.3389/fdgth.2021.645232.
[2] “5 Critical Priorities for the U.S. Health Care System.” Harvard Business Review, December 15,
2021. https://hbr.org/2021/12/5-critical-priorities-for-the-u-s-health-care-system.
[3] “Blockchain and Artificial Intelligence (AI).” IBM. Accessed June 1, 2023. https://www.ibm.com/topics/blockchain-ai#:~:text=By%20providing%20access%20to%20large,trustworthy%20and%20transparent%20data%20economy.
[4] “What Is Predictive Analytics?” IBM. Accessed June 1, 2023. https://www.ibm.com/topics/predictive-analytics#:~:text=Predictive%20analytics%20is%20a%20branch,to%20identify%20risks%20and%20opportunities.
