Health System Specialty Pharmacy: The Evolution of SP Outcome Metrics

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Specialty Pharmacy By the Numbers


Many specialty prescriptions are allowed to be filled only by a payer-designated specialty pharmacy within a payer-designated network. In some cases, the prescription fill is limited to one mail-order specialty pharmacy that is owned by the pharmacy benefit manager (PBM) that is managing the pharmacy benefit for the plan sponsor. Patients no longer have control over where they have their prescriptions filled. If health system specialty pharmacies (HSSPs) can show equal or superior performance in key metrics, it is reasonable that they should be included in the payer network.


Currently, most payers use pharmacy dispense metrics to approximate a perceived outcome. These are proxy markers rather than true patient outcome measures. To measure and compare true patient outcomes, many structured and unstructured data points must be used to derive insights. These unstructured data points are found in electronic health records (EHRs), registries, patient-reported outcome platforms, and many other data verticals that are not currently used by PBMs to compare their specialty pharmacy to others in terms of patient outcomes and total cost of care. Metrics such as abandonment rate, proportion of days covered (PDC), and medication possession ratio (MPR) are used by payers to determine adherence and persistence.* These metrics assume that a proper fill-and-refill rate correlates to a positive patient outcome. Although this correlation is usually valid for negative outcomes, it lacks the bandwidth to predict positive outcomes. The patient could be taking the drug correctly, but the medication may not be working as the provider had hoped for a myriad of clinical reasons not related to adherence. In the future, health care practitioners will have access to real outcome measures to compare various drug and treatment modalities. Many different data assets will be needed to do this, but the transformation has begun to use the rich data contained in EHRs to answer these questions.


HSSPs are uniquely positioned to provide optimal pharmaceutical care for their specialty patients based on the following attributes:

  • Unique resources (financial and care advocates embedded in the clinics)
  • Aligned incentives (a hospital readmission is harmful to the patient and hospital)
  • Faster identification and response to prevent medication-related complications
  • Shared access to the EHR by all health care staff
  • Meaningful in-clinic discussion with patient and family on medication use adherence
  • Pharmacists often delegated prescriptive and medication therapy management authority
  • Ability to coordinate care within a consolidated EHR

As a result of these unique assets, health systems can provide better care than an outsourced mail order model for some, if not most, disease states. The following figures compare current state measures for HSSPs with national average metrics used to measure pharmaceutical care performance.

Specialty drugs can have extremely high abandonment rates, up to 60 percent; the leading cause of this is patient financial hardship. A survey from Surescripts found that half of specialty pharmacists say the average specialty prescription takes at least 4 days to fill and wait times of 7 to 10 days are not uncommon.

Surescript Survey

When these same metrics are measured in an HSSP, the picture is very different, with values that are dramatically better.

Acentrus Specialty, in conjunction with Loopback Analytics, has collected real-world adherence rates that are evidential, not anecdotal stories. It is important to evaluate these metrics at the disease and drug level, as the results may not be applicable across the spectrum. Therapy initiation may be a critical metric for some disease states and not as critical for other chronic diseases. All of these metrics must be viewed with a clinical lens to evaluate the relevance to a real clinical outcome that they are approximating until we can derive true outcome metrics. Health systems must continue to improve their collection and utilization of current proxy metrics while diligently working to create real-world evidence (RWE)-based outcome benchmarking metrics.

The data for the 11 specialty drugs listed above were collected from 21 health systems over a one-year period from May 2020 to May 2021. The following adherence parameters were defined and had to be met:

  • Prescription was routed to a health system pharmacy for filing
  • Prescription was NOT discontinued within 30 days
  • Prescription was NOT rerouted to another pharmacy
  • Prescription was a new start therapy (the patient did NOT have an order for the same drug within the last 6 months).

For these 11 specialty drugs, the average fill rate was 91 percent, which is an abandonment rate of 9 percent. This is significantly better than the national average abandonment rate for these drugs, which can be as high as 69 percent.** This variance raises the question of why is there such a large disparity.

Research from the IQVIA Institute for Human Data Science shows that when cost sharing rises, patients are more likely to abandon their medicines. In 2017, 69 percent of commercially insured patients did not fill their new prescriptions when they had to pay more than $250 out of pocket, whereas only about 11 percent of patients with out-of-pocket costs of less than $30 abandoned their prescriptions at the pharmacy.

Health system specialty pharmacies often have access to foundations for financial assistance as well as financial care coordinators to mitigate financial barriers to prescription fulfillment. This is key to why these low abandonment numbers are achievable in health care settings. Direct face-to-face patient interaction is a key factor to getting the patients to “buy in” to their prescribed regimen.



Specialty pharmacy represents an important opportunity and unique challenge for hospitals and health care systems. Maintaining more control enables organizations to deliver integrated care that enhances the patient journey, improves patient outcomes, and reduces costs. An effective program also generates revenues that can help ensure financial viability as reimbursement tightens.

Therapy-Specific Outcomes Coalition

In addition to performing well in terms of current proxy outcome measures, HSSPs are also evolving rapidly to develop and use robust EHR data to identify actual clinical outcomes. Acentrus, as the nation’s largest HSSP network administrator, and Loopback Analytics have created a Therapy-Specific Outcomes Coalition (TSOC). This initiative is a collaborative, multi-system coalition of the nation’s leading HSSPs designed to enable sharing of data to develop therapy-specific best practices through clinical benchmarking from a standard platform. The initial collaboration is made up of large integrated delivery networks (IDNs) that are actively developing disease-state-specific measures that define key outcome metrics for each disease state. These data are then benchmarked among all the sites to determine who is performing optimally in that disease state therapy; then, those best practice techniques are shared with the entire network to improve care in those disease states. This project is just starting, with two primary endpoints in mind: first, to show that HSSPs have superior clinical outcomes when they can treat patients in their own specialty pharmacy and second, to show that the HSSP cohort has a lower total cost of care for the plan sponsor. TSOC yields results for all stakeholders: patients, payer/plan sponsors, HSSPs, and manufacturers.


As HSSPs continue to grow as a percentage of the specialty market, it is imperative for them to prove that they deserve the right to dispense limited distribution drugs and receive reimbursement at nondiscriminatory rates. This proof needs to be based on real-world data (RWD)/RWE, not anecdotal observations. HSSPs have a unique data asset with unstructured data that reside only in a health system’s EHRs. This data type is the key to predictive and prescriptive outcome analytics. There will no longer be a dependence on proxy outcome metrics that are relics from an era when only pharmacy dispense data were available from specialty pharmacies. The data use cases with robust EHR data include, but are not limited to, the following:

√ Identification of the patient populations (for benefit or risk)
√ Identification of providers for education and inclusion
√ Understanding the patient journey
√ Identification of obstacles to access
√ Establishing RWE on outcomes
√ Benchmarking data for key performance indicators and establishing best practices

Currently, RWE helps determine whether a medication should be reimbursed in general. Value-based payments are more focused on whether a product should be reimbursed for a specific patient population and, eventually, a specific patient. Standardized and routinely measured outcomes that are being defined by companies like OM1, a key Acentrus partner, will be critical to both. More and more, specialty pharmacy therapy requires measuring metrics such as genomic biomarkers, lab results, patient-reported outcomes, social determinant factors, and many others. These data are at the fingertips of HSSPs and positions them to excel in their patient care outcomes, financial performance, and overall cost savings. The key to this is marketing their data assets and utilization of those assets to improve clinical outcomes and reduce the total cost of care for the patient. If they can achieve this, then drug and payer access will naturally follow.

Acentrus Specialty and Loopback Analytics are committed to this vision and are actively creating the infrastructure to make it a reality.

* Lo-Ciganic, W.-H., Donohue, J. M., Thorpe, J. M., Perera, S., Thorpe, C. T., Marcum, Z. A., & Gellad, W. F. (2015).
Using Machine Learning to Examine Medication Adherence Thresholds and Risk of Hospitalization.
Medical Care, 53(8), 720–728.

** Sixty-nine percent of patients abandon medicines when cost sharing is more than $250, Aug 23, 2018. PhRMA

Tom Renshaw, MBA, RPh
Tom Renshaw, MBA, RPh, Senior Director of Business Solutions for Acentrus, specializes in business and technical infrastructure solutions required for reporting data to manufacturers and payers. He also develops analytics strategies and tools for unstructured data manipulation and conversion.