A doctor’s job isn’t easy. And with the ongoing shift towards value-based care, it’s only getting harder.
Doctors are rigorously trained to treat individuals, committing decades of their life – not to mention hundreds of thousands of dollars – to their education and practice. The advent of value-based care, however, is forcing many to acquire an entirely new set of skills, or risk being excluded from the transition altogether.
Rather than focusing on the needs of individual patients, they are now being asked to lead big data initiatives and strategically examine large groups of patients, taking a holistic view to determine broader trends in entire patient populations.
This additional level of analysis also requires a specialized skill set, and has generally involved thrusting additional responsibility on already overworked clinical staff. this trend should open the door for an unexpected, but mutually beneficial, partnership.
Tools that enable vast amounts of data to be pulled from internal and external sources include EHR systems, labs, insurance companies, and pharmacies, among others. Initiatives to implement and integrate these resources are happening within singular health systems and across entire states, with the goal of uncovering patterns, trends and other insight among various patient populations.
As with any data-based research, the more data you can access, the more insightful your analysis becomes. With the right information in hand, practitioners can determine best practices to improve patient-centric care and reduce costs – as mandated by the value-based care initiative.
As the name implies, however, big data analysis initiatives are a massive undertaking. They require integration capabilities to pull data from disparate systems in participating facilities and then aggregate them into an analytics platform for analysis. They frequently employ analytic methods developed in data mining, including classification, clustering, and regression, and extend far beyond traditional clinical epidemiology. Business intelligence (BI) and analytics tools transform this abundance of data into insights and opportunities, but often require specialized knowledge of multiple platforms, applications, and their various capabilities.
For a busy doctor – 65% of whom report being overworked – simply learning how to operate these tools, let alone spend hours mining them for useful insights, is simply not possible.
Building Effective Partnerships
Most healthcare business offices have analytics tools in place, as well as staff that have the skills to use them. If they don’t, this function is likely outsourced to a business partner or consultant.
Regardless of where the skillset resides, analysts can (and should) work with clinicians and doctors to help them mine the wealth of information created by big data analytics initiatives for useful insight. This collaborative effort, however, requires breaking down the silos between business office staff and doctors, who have traditionally had only limited interaction.
Initiating a dyadic leadership structure – which pairs an administrative leader with a clinical leader – will help break down these silos.
A great place to start is a pilot project that pairs an analyst with a doctor, making each available to the other at regular intervals for in-person conversations. Encourage the doctor and analyst to collaborate on creating specialized reports that will benefit clinical staff and improve their decision making abilities, and to determine a reporting schedule that ensures timely, accurate data. This will leverage the data analysts existing skill set, while allowing doctors to understand and utilize the wealth of data available to them as they make daily treatment decisions. Additionally, it improves the analyst’s connection to the clinical side of the hospital’s operations. This will become even more critical as the role of the business office evolves during the transition towards payment for care quality and overall cost effectiveness.
Use this time to create awareness among participating doctors of the analytical expertise that already exists within the business office, and the benefit of these relationships as they implement value-based care initiatives. Further, measure improvements before and after implementing the program to prove these benefits. This will help transform the clinician / analyst partnership into a cooperative relationship for the benefit of patients, which is the ideal goal.
Doctors and clinicians should not be alone when it comes to big data analytics. A wealth of analytical knowledge exists within the business office. With a little clinical guidance, significant improvements can be made in quality care and the lives of patients.
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