Harnessing the Power of Business Intelligence to Influence Oncology Practice

TOP - November 2018, Vol 11, No 3 - HOPA 2018 Highlights
Meg Barbor, MPH

Chicago, IL—Business intelligence is the process of collecting data from disparate systems internally and externally, and turning it into information that is meaningful and actionable toward achieving strategic goals. It encompasses reporting, analysis, data mining, data quality and interpretation, and predictive and prescriptive analytics.

According to Jeffrey Reichard, PharmD, MS, BCPS (RPD), Director of Pharmacy, Hospital-Based Infusion, Oncology, and Specialty Pharmacy Service Lines, Novant Health Infusion, Winston-Salem, NC, the pharmacy provides a tremendous amount of data to their organizations; therefore, establishing the organizational drive to create, maintain, and develop data management and business intelligence is not only necessary, but provides a tremendous opportunity for data consumers.

“How are specialty pharmacists being alerted at the right time, for the right patient, to make their intervention?” he asked at the Hematology/Oncology Pharmacy Association (HOPA) 2018 Practice Management Conference. “It does not just happen; to get it right for the right patient, there really needs to be some technology to help them.”

According to Dr Reichard, pharmacy leaders often assume they can undertake data analysis without external help.

“But, this is where collaboration is helpful, especially in the case of large organizations, where you get a much better long-term product and better long-term buy-in if operational finance, business intelligence, and data architects are involved, also taking into account the intended outcomes and impact,” he said.

“So, knowing the larger targets is
really helpful. Many of us assume we can use our experience in all aspects of situations, but in hindsight, we may not have had clear visibility with regard to those aspects in which analytics can really help us; we may not have seen the decision-making opportunity on our own,” he added.

Two problems commonly faced are data value and data availability, even as the demand for data and reports are increasing over time. Although this is a good “problem” to have, the demand outweighs the supply, Dr Reichard said. “There is a lot of noise in our data, so it is really important that we think about what we are trying to extract and then use.”

Novant Health’s Approach

Novant Health set out to modify their business intelligence program goals. They accelerated their strategic approach to analytics to leapfrog their competitors who invested earlier in business intelligence and information technology infrastructure. They also integrated their fragmented systems and built a single repository of clinical, nonclinical, and external data. Finally, they transitioned to a proactive, action-oriented approach to data analytics that now drives their clinical and business decision-making. Through the use of these strategies, they continue to maximize the benefits from their past and ongoing investment in their own technology.

A coordinated deployment approach to this strategy involves participation from the business intelligence team and the business unit or pharmacist.

“If they don’t all work together, we don’t solve the problems,” Dr Reichard said.

The business intelligence team is made up of the consumer, the data owner, and the individual who creates and curates the information and works in collaboration with other members of the business intelligence team to get data incorporated into the business intelligence warehouse, with the eventual goal of obtaining feedback on metrics for other departments. The data owners then employ and train business intelligence wizards, or stakeholders, in the department with a higher level of understanding and training, and they then create further content. Finally, the data scientist is involved in the architecture creation and management of the infrastructure, as well as incorporating and removing pieces of systems around the data.

External data goes into the data warehouse and then moves into units that process and maintain it. It is then organized into analytic tools before reaching the scientists, wizards, analysts, and, finally, the consumer. Dr Reichard noted that this type of coordination also involves a financial commitment.

Getting started begins with a conversation with the team, he said. “You have to have the right people as part of the conversation, and often they are not in pharmacy.” They could be subject matter experts, analytics leaders, or data scientists.

“Pharmacy should develop data capability alongside other system partners and seek opportunities to collaborate. Pharmacy really can, and should, be a key partner alongside other health systems parties,” Dr Reichard concluded. l

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Last modified: December 4, 2018