Challenges, trends of data analytics in pharmacy: 3 insights

Data analytics can be leveraged to address various challenges in the pharmacy industry, from drug shortages to identifying high-risk readmissions.

Pharmacy leaders explored some of these issues and shared insights on how their own organizations are using data analytics at Becker's Hospital Review 2nd Annual Health IT + Clinical Leadership + Pharmacy conference in Chicago, May 2-4.

Three key insights:

1. Drug shortages and increasing specialty supply chain. Two of the biggest challenges today for the pharmacy industry are drug shortages and increasing use of more expensive, higher regulated medications coming through the supply chain, said Andre Smith, executive director of the central and west regions for Dublin, Ohio-based Cardinal Health.

"We're seeing a large shift to that specialty supply chain from the normal supply chain," Mr. Smith said. "These are extremely expensive drugs and [the challenge is] trying to combat the effect and the cost of those with being able to supply patients with needed medications. To help offset the rising costs of specialty drugs, many hospitals are looking at where profitability is in service lines to identify savings opportunities and help determine what types of patients they're providing to."

2. Use data analytics to pinpoint drug shortage risk. HC Pharmacy and Supply Chain Commercial Services, a division of UPMC, has been increasingly investing in data analytics over the past 18 months to analyze drug shortages, said Jessica Daley, the organization's vice president. Data analysts can compile reports and insights on drug shortage risk to identify shortages before they hit the market.

"We're moving the majority of [our data analysis] into a more hardened data warehouse architecture, so we have an entire team of data analysts, software engineers, data managers and even some data scientists who are using all of the pieces of information that we were manually manipulating in [Microsoft] Excel," Ms. Daley said. "And they have devised a way to pull all of that data in automatically into a data overlay."

3. Target interventions around population health parameters. Institutions should use analytics to help identify what the biggest drivers are for drug use, such as inpatient or ambulatory use, said Bhavesh Shah, director of specialty and hematology/oncology pharmacy at Boston Medical Center.

"Why don't we target those patients who actually have this really high risk of readmission and really target those interventions around those patients… that's what we [Boston Medical Center] use data to do," Mr. Shah said. "We have a relative risk admission that we calculate on every single patient, and they're basically categorized into four different categories: super utilizer, high risk, moderate and lower risk."

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