Harnessing Patient Data to Transform Health Spending

Specialty pharmacies, through frequent patient and provider interactions, are often called upon to manage data sets that demonstrate both improvements in quality of care and cost reduction. So why is it that specialty pharmacy data tend to be left out of the conversation as it relates to improving quality care for patients in the United States? Blockchain, artificial intelligence, and other cutting-edge models of data management drive discussions centered on the big health data revolution. However, some fundamental improvements will likely need to take place for actionable data to raise the visibility of specialty data across the industry as a whole.

If You Don’t Know, Now You Know

In 2004, the Office of the National Coordinator for Health Information Technology (ONC) was created. The ONC is intended to support adoption of health information technology (HIT) and promote health information exchange nationwide.

A road map was designed and put forth in 2014 detailing the need for standardization across all domains of health care in the United States over the following 10 years. We’re currently in the phase of the road map in which constituents “expand interoperable health [information technology] and users to improve health and lower cost” from 2018 to 2020, and certain milestones continue to be targeted.¹

Within this road map, several domains focus on use of patient data as a driver of cost reduction, especially as it relates to consistency in data formatting, semantics, and matching; contributions of data to the larger pool; and associated workflows to integrate multiple relevant patient data sources. Each domain holds key milestones for attaining goals of greater data use, standardization, and transparency.

Although it contains a plethora of information, the ONC website has largely been silent as we’ve entered this phase of the project plan, with only 8 news releases since 2018 and none detailing progress toward appropriate areas of the road map. With the intent in place and the execution seemingly on its way, one might think that would be enough.

Pardon Me...Are You Spending More?

Let’s talk for a moment about health care spending as a whole. According to the Kaiser Family Foundation, the United States spends almost twice as much per person as comparable countries around the globe. Health spending per person in the United States averaged $10,739 in 2017.² This equates to approximately 17.9% of our country’s gross domestic product being tied to health care expenditures. Research suggests that HIT adoption helps to control expenditures overall. In other industrialized countries in which HIT adoption has been more aggressively pursued, particularly in regard to electronic medical records (EMRs), there have been instances of lower overall spending and an improvement in quality of health care services delivered.³

Since the inception of the ONC, and aside from the roadmap, multiple private organizations have attempted to enhance the EMR process to create a more usable, integrated patient data set across all points of care. For example, Cerner collaborated with the Duke Clinical Research Institute on the Cerner Learning Health Network to provide additional data-driven insights, enhanced clinical research, and identification tools to enhance overall patient care.

Similarly, Epic has made strides to pull together multiparty patient data sets from all their clients to provide broader insight across disease and diagnosis; however, they have documented difficulties related to both patient de-identification and data-sharing permissions.

If We Lay a Strong Enough Foundation

Both of the aforementioned instances of EMR data initiatives lend themselves to an emerging area of patient data use: Population health management is the latest buzzworthy term in cost containment within the health care industry. Identifying unique patient populations that could benefit from focused product or service offerings can put better outcomes at a lower cost within reach.

By providing the right treatment at the right time in the right setting, health care expenditures can more easily be con- trolled and approached thoughtfully. So, where does one look to identify the most appropriate patients targeted for population health initiatives? Data.

An analysis of certain population health determinants can not only identify suitable target patients for whom the greatest benefit can be achieved, but it can also provide appropriate insight into outcomes achieved through these initiatives. However, historically, most population health programs tend to focus on primary care conditions such as congestive heart failure, hypertension, or diabetes. The concept of data utilization to improve target patient outreach, care, and overall cost reduction goes hand in hand with the specialty pharmacy experience.

With more than 700 accredited specialty pharmacy locations in the United States handling high-cost products with high-touch programs to manage disease states,⁴ the population health framework should clearly align with the ability to execute actionable programs across specialty populations.

There Are a Million Things We Haven’t Done

How can specialty pharmacies join the conversation related to value-focused data? Let’s face it, depending on how patients are being managed across their individual journeys, specialty pharmacies add yet another complex layer to the data management continuum. The ability to effectively track the patient journey could easily position specialty pharmacies to best obtain and decipher disparate data systems.

Most specialty pharmacy technologies do not integrate with EMRs and have not yet entered into the ONC health infor- mation exchange conversation. Specialty data capture tends to focus on the capability of the individual provider at either the software or the contract level through the data requirements of an aggregator, payer, or pharmaceutical manufacturer. Data standards have been proposed for specialty data through National Council for Prescription Drug Programs work groups; however, specialty molecules don’t hold a one-size-fits-all data capture approach, by the very nature of their complexity.

This complexity is not just a specialty problem, as it is even called out in the ONC road map: “the approach to standards development in which individual standards pieces are built to solve a particular part of a challenge, but require implementers to put together multiple standards to fully solve the whole challenge.”¹

Historically, the approach to specialty data is just that: an approach to a particular part of the challenge but not fully solving the problem, which is overall patient data capture and utilization.

What Comes Next?

Until data sets are standardized and having a common goal to improve both the specialty industry and the health care industry as a whole is realized, we stand to continue repeating this conversation in a few years. Furthermore, standardized data would allow for the needs of our industry to be dictated to us. History has its eyes on us, specifically those who have the ability to demonstrate how the specialty pharmacy model can best impact health care spending as a whole.

Specialty pharmacies have the needed pieces in place, but until there are standards of outcomes data capture and reporting, there really is no benefit to pursuing cutting-edge models just yet. What can be done right here and now to drive positive change? How can we shift the conversation away from just drug costs and more toward overall value-based outcomes and quality? It’s going to take some collaboration to surmount the challenges we’re facing. I’m willing to wait for it.

References

• Office of the National Coordinator for Health Information Technology. Connecting Health and Care for the Nation: A Shared Nationwide Interoperability Roadmap. Washington, DC: US Department of Health and Human Services; 2019. healthit.gov/sites/default/files/hie-interoperability/nationwide-interoperability-roadmap-final-version-1.0.pdf. Accessed August 23, 2019.
• Peterson-Kaiser Health System Tracker. How does health spending in the U.S. compare to other countries? - Peterson-Kaiser Health System Tracker website. healthsystemtracker.org/chart-collection/health-spending-u-s-compare-countries/?_sf_s=health+spending. Published December 7, 2018. Accessed August, 23, 2019.
• Anderson GF, Frogner BK, Johns RA, Reinhardt UE. Health care spending and use of information technology in OECD countries. Health Aff (Millwood). 2006;25(3):819-831.
• Fein AJ. Exclusive: a record number of specialty pharmacies now have accreditation. Drug Channels website. www.drugchannels.net/2018/04/exclusive-record-number-of-specialty.html. Published April 10, 2018. Accessed August 23, 2019.