Read time: 4 minutes
By: Nicole Mayo
Understanding Predictive Analytics
The increased adoption of electronic health records has improved the way in which patient information is collected and stored. The resulting volume of generated patient data has prompted healthcare entities to invest in tools which analyze patient data and provide actionable insights.
According to a BBC Research report1, hospitals spent an estimated $6.2 billion on analytics resources in 2017. This number was expected to soar to $14.9 billion by close of 2022.
Hospitals have begun identifying links between disease states, social determinants of health, and drug therapies and missed appointments, utilization of medical services, and readmission rates. Armed with these insights, they are addressing these gaps by incorporating additional support and resources where needed most.
By targeting specific outcomes and examining historic data, predictive analytics allows stakeholders to identify patterns and commonalities across data points. Stakeholders can then proactively devise strategies to minimize the recurrence of those future events.
Health system pharmacies deploy similar predictive analytics methods to alter drug procurement patterns, render formulary decisions, and establish pharmacy budgets.
Predictive Analytics Moving Forward
Health systems are now leveraging all available insights to make better informed decisions. Algorithms and predictive analytics allow for more proactive decision-making and drive sustainability strategies. By examining historic trends and fluctuations in drug utilization, procurement teams can establish analytically sound strategies to avoid over- or under-purchasing drugs. In addition, health care entities will be able to see the value in understanding how drugs are being reimbursed and why this is important when making formulary decisions and establishing best practices.
With the increase of new drug therapies and biosimilar agents, health system pharmacies are shifting their cost containment strategies and investing more resources into tools that will streamline the decision-making process.
How McKesson Uses Predictive Analytics to Help Customers
Data insights within the Utilization Analytics (UA) tool allow health system customers to fully understand the impact of their formulary and purchasing decisions while equipping them to have larger conversations with multidisciplinary teams outside of pharmacy.
Through the incorporation of assumptions within the analysis, UA customers can examine scenarios on a more granular level. Understanding the implications of payer distribution, site of care nuances, and fluctuating reimbursement rates allows UA users to conduct predictive profitability analysis and identify drug profit margins.
Click to learn how McKesson’s Utilization Analytics can help your health system achieve more while enhancing visibility into the financial performance of your health system pharmacy.
Expect more from your distributor. Achieve more with McKesson.
1BCC Research LLC. (Nov 2017). Healthcare analytics: Technologies and global markets.
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