The Growing Focus on Pharmacy Data Analytics
Published on 09 February 2018
In today’s digital age, industries are embracing data analysis as a tool for success. This has become especially evident in health system pharmacy, where the integration of comprehensive pharmacy analytics is helping organizations improve patient outcomes and reduce costs.
In the health care industry, advances in technology have made it possible for large volumes of patient and transaction-based data to be collected and made available via electronic libraries. Data gathered includes patient records, insurance billing and claims information, prescription transaction data and data from the external marketplace.
“When we talk about electronic health records, we’re talking about the information that gets shared between entities,” said Shelly Spiro, executive director of the Pharmacy Health Information Technology Collaborative. “Today, we are starting to see an increase in the capture of information into registries where the data has been normalized. As such, the data is becoming more usable for analytical purposes in outcomes measurement.”
At St. Louis College of Pharmacy, the Center for Health Outcomes Research and Education is working to build project-based datasets to support community-wide information exchange and research capacity.
“Access to data, while expensive, is more readily available than ever,” said Scott Micek, Pharm.D., FCCP, BCPS, associate professor of pharmacy practice and director of the center. “From a clinical pharmacy perspective, we can use data to find out something that hasn’t been answered in previous studies. Our results are then provided to current and future health care providers, pharmacists and others, with the goal of helping them improve the care they deliver.”
The work of Micek and his team at the center places specific emphasis on examining how the optimal use of medications can improve health outcomes.
“We seek to create innovation from our efforts,” noted Micek. “We hope our findings will lead to a practice change, a hypothesis for subsequent study or an intervention – some type of model that can be implemented at the bedside or at the clinic.”
Micek notes the use of pharmacy data analytics is a growing trend because it is more cost-effective and safer for patients than clinical trials.
“This methodology is changing the landscape of clinical trials because learning how to analyze existing data appropriately can supplement and, in some cases replace, the need to conduct experiments,” said Micek.
Information from big data sets also examines a larger number of patients over a longer period of time, which gives researchers the ability to look at the bigger picture and predict trends that can help inform health care.
“If you looked at 1,000 patients in a randomized control trial, one or two patients may experience an adverse drug event,” said Scott Vouri, Pharm.D., MSCI, FASCP, BCPS, BCGP, associate professor of pharmacy practice and assistant director of the center. “But if you look at a million patients, you’re going to get a few thousand adverse reactions, and you can really see those differences.”
Across the health care continuum, the use of data analytics is also helping to reduce costs associated with care transitions.
“The goal is to follow the patient analytics and intervene earlier,” said George L. Oestreich, Pharm.D., MPA, principal, G.L.O. and Associates. “Chronic disease management, medication therapy management and the coordination of care across multidisciplinary teams can all be synergized using data analytics – and that’s where we see a lot of costs that can be turned around.”
In his work with G.L.O. and Associates, Oestreich provides strategic consulting on Medicaid issues and has spent many years working with MO HealthNet, a division of the Missouri Department of Social Services that administers Medicaid, which purchases and monitors health care services for low income and vulnerable citizens of the State of Missouri.
“The use of analytics is important and will continue to grow,” said Oestreich. “But, in order for analytics to be successful to an organization, consistent handling and support is required. At MO HealthNet, we saw expenses grow when the aggressive use of analytics dropped off. Commitment is key.”