Big Data is a big deal these days. Healthcare systems are gaining a deeper understanding that the ability to quickly access and leverage the reams of data created and collected each day can lead to more efficiency, significant cost savings, and better patient care. For instance, one area in which Big Data management can make a considerable difference is in pharmacy, where access and deeper understanding of data allow for more efficient ordering, storage, and distribution of meds and related medical supplies.
Amid this opportunity is considerable challenge as healthcare providers work to find the best technology solution, while focusing on informing and training physicians and staff on new systems and procedures. Recently, Darwin Cooley, director of pharmacy services, Great River Medical Center, and Michael Hunt, DO, CMO/CMIO, St. Vincent’s Health Partners (SVHP), offered their perspectives on how effectively leveraging Big Data can impact the bottom line and quality of care.
Compiled by Scott Westcott, Contributing Writer
Two health systems show how Big Data is playing an increasingly prominent role in their ongoing quest to operate more efficiently, drive down costs, and improve patient care.
![]()
Big Data is a big deal these days. Healthcare systems are gaining a deeper understanding that the ability to quickly access and leverage the reams of data created and collected each day can lead to more efficiency, significant cost savings, and better patient care. For instance, one area in which Big Data management can make a considerable difference is in pharmacy, where access and deeper understanding of data allow for more efficient ordering, storage, and distribution of meds and related medical supplies.
Amid this opportunity is considerable challenge as healthcare providers work to find the best technology solution, while focusing on informing and training physicians and staff on new systems and procedures. Recently, Darwin Cooley, director of pharmacy services, Great River Medical Center, and Michael Hunt, DO, CMO/CMIO, St. Vincent’s Health Partners (SVHP), offered their perspectives on how effectively leveraging Big Data can impact the bottom line and quality of care.
![]()
Q: How has your organization begun to harness Big Data and how has it impacted organizational efficiency and/or patient care?
Cooley: At Great River Medical Center, we realized that we needed to be more efficient in how we delivered our services. We are challenged with doing more with less, and we know that with new regulations, if we don’t do things more efficiently, we’ll end up losing money. We realized that leveraging the power of our data was the best way to become more efficient. Now data collected from our cloud is being utilized to improve efficiencies of drug delivery, reduce inventory costs, and meet regulatory requirements of the Joint Commission, CMS, and the State Board of Pharmacy. It is also enabling us to more easily meet our Meaningful Use requirements, thus ensuring maximum reimbursement for our services.
The most prominent example of how we are harnessing our data is in our pharmacy. Great River pharmacy has utilized data from Omnicell reports, run on Microsoft embedded software, to improve our services and serve our patients better. We’ve seen benefits in the following areas:
- Speed of service to our patients helps to prevent lengthy delays in receiving much needed medication.
- Information collected helps to prevent medication errors from reaching the patient, which improves patient safety.
- More efficient inventory management as well as efficiency in medication administration enable pharmacists and nurses to spend more time with the patient to help improve patient outcomes and patient safety.
Specifically, one of the solutions we ended up with was a pharmacy carousel. The carousel and historical data it captures have allowed us to maximize efficiency of quantity on hand. We can keep fewer medications at any given time because we have a better understanding of what is needed. This has initially returned $400,000 back into the bottom line at Great River by reduction in inventory. That reduction also allows us to save waste from having to discard out-of-date medication to the tune of $40,000 a year.
Hunt: We take Big Data and make it usable. Each month, PCPs receive data on their attribution, patients with high risk, care gaps, and scorecard. We focus on making sure information is timely, actionable, and accurate and have seen many positive outcomes. Patients with the highest risk have improved, SVHP utilization metrics are demonstrating significant improvement, out of network utilization has been reduced by 30 percent, and we’ve seen a reduction in ambulatory-sensitive conditions seen in the emergency department.
Q: How did your organization decide what areas or applications would benefit most from leveraging Big Data?
Cooley: To make the decision, we looked at where there was the greatest need and opportunity. The pharmacy and nursing departments were constantly asking for more staff to keep up with an increasing workload. Much of the extra work was a result of regulatory requirements, which meant more work with no more revenue. Nursing staff was complaining about poor and slow service, missing meds, and other medication management problems. We knew of better automation and technology and felt that was the only way we could improve service and efficiency without adding more staff.
Optimizing efficiency was a top priority for improving care and controlling costs, as well as satisfying regulatory compliance. CMS states that after medication is ordered, it must be administered within 30 minutes. However, with time-consuming manual processes, it could take up to an hour and a half for patients to receive medication. Great River knew that getting medication to patients faster and spending more time educating them on proper use would improve outcome and reduce the rate of readmission. Manual processes not only slowed medication distribution; they also reduced the time nurses and pharmacists had available for patients.
Hunt: We have focused on infrastructure, process, and quality. SVHP has created a unique model of care coordination, and developed significant cultural transformation to manage the change from fee-for-service to performance and quality. The organization was the first healthcare network to be recognized by URAC (Utilization Review Accreditation Commission) for clinical integration. The accreditation demonstrates our commitment to meeting the FTC’s (Federal Trade Commission) and DOJ’s (Department of Justice) guidance for antitrust. We have developed relationships with our membership and payors to help develop the infrastructure that will allow us to compete with risk contracts. In addition, SVHP is investing in a data infrastructure with McKesson’s Population, Risk, and Care Manager software. As this tool matures, we are using other analytics to facilitate payor data evaluation. All data is shared with organization membership to address infrastructure, process, and quality opportunities. We are also working closely with payors to create medical management services that will allow SVHP to be a leader in population health.
Q: What steps did you need to take to ensure you were ready to ingest, analyze, and store the increases in data your project would subject you to?
Cooley: It wasn’t a matter of getting ready to ingest new data; rather, we needed to use the data we already had. Everything we do provides us with more data. The data was there, but we couldn’t get to it. We had to ensure that we had a system in place that would let us leverage the data already being collected. With the improved Omnicell hardware, Microsoft software, and embedded devices, data was very easy to retrieve in a usable and meaningful format. This data has helped us to reduce inventory, reduce outages of meds, and identify and reduce narcotic diversion. The reporting software we use takes historical usage of every medication in every cabinet and makes recommendations for us on reorder points, reorder quantities, and most efficient medication levels to keep on hand. This prevents outages from understocking as well as reduces waste from overstocking.
![]()
Plus, in the past, when the administration or our board of directors needed a report that required data, it was extremely difficult, time-consuming, and sometimes impossible to provide. Now, we have data at our fingertips. We no longer have to spend two days with six or eight staff members physically counting tabs, caps, injections, and more for the year-end inventory. The carousel keeps a perpetual, running inventory. All we have to do is select the report and run it. Hundreds of hours were previously required to do this task. Now, it’s done in minutes.
Hunt: We have created a positive relationship with McKesson to understand our operational vision to improve alignment and strategic planning of tool selection. We have steadfastly developed the list of data sources necessary to be successful with quality and performance metrics that meet contractual requirements. As another step on this journey, we have developed a method to distribute data unique to each office to accommodate each site that services patients. With constant outreach to each practice site, we help each physician and staff member use available data to successfully meet care and quality metrics locally.
Q: What were the biggest challenges your organization has faced in regards to working with Big Data? How did you address these issues?
Cooley: Once it’s all set up, it works smoothly, but the staff has to know how to use it. Therefore, training of the nursing and pharmacy staff was probably one of the biggest challenges we faced. Even though this made us more efficient, there was a lot for them to learn in order to get to that level of efficiency. Since systems only work as well as you use them, this was a critical element for our success. Staff members need to know which buttons to press and how to use it in the right way.
![]()
Hunt: We have disparate EMRs, practice management software (PMS), and ancillary data sources. Each practice requires four unique data sources to develop more than 40 disease and preventive care registries. In the most basic concept, more than 2,000 data connections, or four per practice, are required to successfully develop the analytics necessary to create the patient registries and report to providers and the community how the network performs. A key part of this effort has been education of both medical professionals and patients. The changes occurring are coming at such a fast pace that both struggle to understand and appreciate how the new reimbursement models affect them. For medical professionals, understanding the intricacies of how to adapt to pay-for-performance from fee-for-service are challenging at best. The details and understanding from economic and operational perspectives remain a moving target since no single model of success has been identified. Most likely, multiple operational models will need to function simultaneously, and the data to support the models will continue to evolve over time. Analytics will be required to accommodate the evolution.
Q: What advice would you give other providers considering a Big Data initiative?
Cooley: Do your homework. We did site visits, looked at different systems and models of drug delivery, and compared different vendor products. You need to do this to ensure you get the best value for your system. Initially, we had a consultant come in and deliver a report that outlined the areas where we could improve. We knew exactly where we were falling down, which meant we could easily see which vendor provided what we needed at the right price. Along the same lines, do a thorough comparison. Talk with other hospitals that have gone this direction. An initial upfront investment in our time was able to drive significant cost savings as we deployed. Finally, it was essential that all of our systems work together so Microsoft technology was a natural choice since that made it easy to get the different systems to work together. We liked what we already had with our Omnicell products, and by using Microsoft embedded technology, it ensured we didn’t need new hardware and that our EMR, billing, and drug information all interfaced well together.
Hunt: First and foremost, identify your basic operational model before selecting an information system. Understand and catalogue the opportunities and challenges to establish realistic timelines.
You have to keep in mind that single technologies may not have the functionality necessary to be operationally successful. Establish a comprehensive technology strategy that builds methodically with the organization. Develop a communication plan to establish short- and long-term expectations. Use information systems as quickly as possible with tangible, actionable, timely data that can be consumed by the stakeholder. All too often, medical professionals are significantly challenged by little time available for investigation and evaluation. Concise and actionable information that can be consumed appropriately is the goal. Cultural change within an office setting requires buyin from all staff. Without a coordinated effort to use data wisely, frustration overwhelms success.
Big Data is a big deal these days. Healthcare systems are gaining a deeper understanding that the ability to quickly access and leverage the reams of data created and collected each day can lead to more efficiency, significant cost savings, and better patient care. For instance, one area in which Big Data management can make a considerable difference is in pharmacy, where access and deeper understanding of data allow for more efficient ordering, storage, and distribution of meds and related medical supplies.
Q: How has your organization begun to harness Big Data and how has it impacted organizational efficiency and/or patient care?
Plus, in the past, when the administration or our board of directors needed a report that required data, it was extremely difficult, time-consuming, and sometimes impossible to provide. Now, we have data at our fingertips. We no longer have to spend two days with six or eight staff members physically counting tabs, caps, injections, and more for the year-end inventory. The carousel keeps a perpetual, running inventory. All we have to do is select the report and run it. Hundreds of hours were previously required to do this task. Now, it’s done in minutes.
Hunt: We have disparate EMRs, practice management software (PMS), and ancillary data sources. Each practice requires four unique data sources to develop more than 40 disease and preventive care registries. In the most basic concept, more than 2,000 data connections, or four per practice, are required to successfully develop the analytics necessary to create the patient registries and report to providers and the community how the network performs. A key part of this effort has been education of both medical professionals and patients. The changes occurring are coming at such a fast pace that both struggle to understand and appreciate how the new reimbursement models affect them. For medical professionals, understanding the intricacies of how to adapt to pay-for-performance from fee-for-service are challenging at best. The details and understanding from economic and operational perspectives remain a moving target since no single model of success has been identified. Most likely, multiple operational models will need to function simultaneously, and the data to support the models will continue to evolve over time. Analytics will be required to accommodate the evolution.
