Exploring rates of PCSK9 inhibitor persistence and reasons for treatment non-persistence in an integrated specialty pharmacy model.

BACKGROUND: Nearly 40% of patients do not continue proprotein convertase subtilisin/kexin type 9 inhibitor (PCSK9i) therapy after 6 months, despite their ability to lower low-density lipoprotein cholesterol (LDL-C) and risk of cardiovascular events. Limited work has assessed persistence to PCSK9i therapy in an integrated specialty pharmacy model. OBJECTIVE: To assess rates of persistence to PCSK9i therapy and report reasons for non-persistence in patients serviced within an integrated specialty pharmacy. METHODS: We conducted a single-center, retrospective review of patients prescribed a PCSK9i at an academic health system between September 2015 and August 2018. Persistence was calculated as a binary measure (yes/no) of whether the patient was still receiving PCSK9i therapy at 3-, 12-, and 24-months; frequency distributions described reasons for non-persistence and descriptive statistics described the change in LDL-C from baseline to 24 months. RESULTS: 477 patients met inclusion criteria, 53% were male with median age of 63 years [IQR 56-70]. Median LDL-C at baseline was 157mg/dL and 86% had an atherosclerotic cardiovascular disease indication. Persistence at 3-, 12-, and 24-months was 94%, 80%, and 68%, respectively. Of the 262 patients persistent on PCSK9i therapy at 24 months with LDL-C values available, median LDL-C was 65 mg/dL. The most common reasons for non-persistence at 24 months included medication adverse effects (54%) and loss to follow-up (17%). CONCLUSIONS: High rates of persistence to PCSK9i were seen in patients receiving care within an integrated specialty pharmacy model compared with rates in previous studies, suggesting specialty pharmacists may play a role in mitigating many common reasons for PCSK9i non-persistence.

Primary medication nonadherence to oral oncology specialty medications.

BACKGROUND: Patients prescribed specialty oncology medications face logistical and financial challenges to medication procurement, leading to primary medication nonadherence (PMN). Limited research has evaluated rates and reasons for PMN within a specialty oncology population. Addressing PMN is essential to ensuring patient access and uptake and realizing benefits of these therapies. OBJECTIVES: The objectives of this study were to compute the rates of and reasons for PMN in patients prescribed oral oncology medications at an integrated health-system specialty pharmacy (IHSSP). METHODS: We performed a single-center, retrospective analysis of specialty oncology prescriptions electronically prescribed between January and December 2018. Data were extracted from electronic health record (EHR) and pharmacy claims databases. Prescriptions were PMN eligible if none of the following were met: fill of any cancer medication within the previous 180-day lookback window, duplicate prescription, cancellation within 30 days, rerouting to an external pharmacy within 30 days of prescribing, filled through alternate method, or nononcology or hematology condition. PMN was calculated by dividing eligible prescriptions unfilled during the study period by all eligible prescriptions. Reasons for a lack of prescription fulfillment were assessed via EHR review. Data were analyzed using descriptive statistics. RESULTS: We evaluated 4482 prescriptions from 1422 patients, resulting in 861 PMN-eligible prescriptions. Most PMN-eligible prescriptions (n = 668, 78%) were filled within 30 days, leaving 193 prescriptions as potential instances of PMN. After EHR review, 158 prescriptions met the exclusion criteria, resulting in a PMN rate of 4%. Of PMN prescriptions (n = 35), most were caused by clinical reasons (n = 22, 63%); however, 10 prescriptions were unfilled owing to patient decision, 2 owing to unaffordable treatment, and 1 owing to inability to reach the patient. Patients with PMN had a median age of 72 years and were mostly male (60%), with a median Charlson comorbidity index score of 7. CONCLUSION: Low rates of PMN to prescribed anticancer medications were found among electronic prescriptions intended to be filled at an IHSSP.

Primary medication nonadherence calculation method specifications impact resulting rates.

BACKGROUND: Previous literature has illustrated a wide range of primary medication nonadherence (PMN) rates due to inconsistent calculation methods and parameters, but the impact of parameter specifications on PMN rates has not been assessed. OBJECTIVES: The objective of this study was to evaluate the impact of lookback window (LBW), duplicate window (DW), and fill window (FW) specifications on PMN rates in patients prescribed specialty self-administered oncology medications. METHODS: This was a single-center, retrospective cohort analysis. Patients receiving a new electronic specialty oncology prescription January-December 2018 were included; excluded if re-routed to an external pharmacy within 2 days, fell within a DW, or cancelled within a FW. Twenty-four methods were used to calculate PMN based on combinations of the following parameters: (i) absence of prior specialty self-administered oncology medication fill within LBW (90, 180 days); (ii) absence of a duplicate prescription within DW (2, 7, 30 days); and (iii) sold status within FW (14, 30, 60, 90 days). For each method, PMN was calculated as the number of unsold prescriptions within the FW divided by all eligible prescriptions. RESULTS: We evaluated 4,482 prescriptions, resulting in PMN ranging from 16% to 23%. Patients were commonly male (53%) and white (83%), with a median age of 64 years (interquartile range, IQR, 54, 72). Increasing the LBW from 90 to 180 days resulted in exclusion of 72 (2%) prescriptions and minimally impacted PMN rates. Most duplicate prescriptions (87%) occurred within two days of original prescription and PMN rates were minimally affected by DW. Most fulfilled prescriptions were filled within FW 30 days, 98% with a method of LBW 180, DW 2, and FW 30. Adjusting the FW consistently impacted PMN rates. CONCLUSIONS: Because various PMN definitions can significantly impact results, a thorough explanation of all parameter specifications should be reported in research using PMN.

An Integrated Health-System Specialty Pharmacy Model for Coordinating Transitions of Care: Specialty Medication Challenges and Specialty Pharmacist Opportunities.

Adherence and persistence to specialty medications are necessary to achieve successful outcomes of costly therapies. The increasing use of specialty medications has exposed several unique barriers to certain specialty treatments' continuation. Integrated specialty pharmacy teams facilitate transitions in sites of care, between different provider types, among prescribed specialty medications, and during financial coverage changes. We review obstacles encountered within these types of transitions and the role of the specialty pharmacist in overcoming these obstacles. Case examples for each type of specialty transition provide insight into the unique complexities faced by patients, and shed light on pharmacists' vital role in patient care. This insightful and real-world experience is needed to facilitate best practices in specialty care, particularly in the growing number of health-system specialty pharmacies.

Integrated specialty pharmacy yields high PCSK9 inhibitor access and initiation rates.

BACKGROUND: Access to proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors that lower low-density lipoprotein cholesterol in patients at high risk of atherosclerotic cardiovascular disease events has proven challenging. Methods to overcome access barriers are needed to fully realize the benefits of these novel agents. OBJECTIVE: This study evaluated medication access rates in patients prescribed a PCSK9 inhibitor at a health care system with integrated specialty pharmacy services. METHODS: We performed a single-center, ambispective cohort study of patients prescribed a PCSK9 inhibitor between September 2015 and December 2016 at Vanderbilt University Medical Center outpatient clinics. The primary end point was the percentage of PCSK9 inhibitor prescriptions resulting in access of the total prescriptions triaged to Vanderbilt Specialty Pharmacy. Secondary end points assessed among patients approved for therapy included time between benefits investigation and insurance approval, financial assistance use, and treatment initiation rates. RESULTS: Two hundred ninety-nine patients met inclusion criteria (average age = 63 years). Forty-six percent were female, 57% held commercial insurance, and 70% had an atherosclerotic cardiovascular disease indication. Overall, 96% of prescriptions resulted in access to a PCSK9 inhibitor. Most patients were approved with an initial prior authorization (58%) or after one appeal (29%). The median time to approval was 8 days. Among patients approved for therapy, 53% received financial assistance and 94% initiated therapy. CONCLUSION: An integrated specialty pharmacy service model in outpatient clinics produced high rates of PCSK9 inhibitor therapy access and initiation. This high level of access supports this model as a best practice for prescribing PCSK9 inhibitor therapy.

Risk factors for discharge on a new antipsychotic medication after admission to an intensive care unit.

PURPOSE: Increased awareness of delirium in the intensive care unit (ICU) has led to higher use of antipsychotic medications for treatment of delirium. These medications are often not discontinued at ICU or hospital discharge, which may increase the risk of inappropriate polypharmacy. Our study sought to identify risk factors for being discharged on a new antipsychotic medication after admission to a trauma-surgical ICU or neurocritical care unit. METHODS: This was a retrospective cohort study at an academic medical center and included patients who were admitted to the trauma-surgical ICU or neurocritical care unit and received an antipsychotic medication. Those younger than 18 years, died before hospital discharge, or did not have complete documentation were excluded. RESULTS: A total of 341 records were included in the final analysis. Of those, 82 (24%) were discharged on a new antipsychotic and 67% of those patients had no documented indication. Acute Physiology and Chronic Health Evaluation II (odds ratio, 1.030 [95% confidence interval, 1.030-1.110]) and days treated with benzodiazepines (odds ratio, 1.101 [95% confidence interval, 1.060-1.143]) were independently associated with being discharged on a new antipsychotic medication. CONCLUSIONS: Those patients with higher Acute Physiology and Chronic Health Evaluation II scores and more benzodiazepine days are at increased odds of being discharged on a new antipsychotic.