Retrospective evaluation of preconception care opportunities in a chain community pharmacy setting.

OBJECTIVES: Certain prescription medications should be avoided during pregnancy to reduce the risk of fetal harm. Identification of these medications to minimize exposure may be achieved through the integration of preconception care recommendations into medication therapy management (MTM) services. The primary objective of this study was to identify missed opportunities for pharmacists to provide preconception care support related to medications associated with adverse pregnancy outcomes for reproductive-aged women who received MTM consultations at a regional supermarket pharmacy chain. Secondary objectives examined the concurrent use of prenatal vitamins, folic acid, or hormonal contraception in patients receiving medications associated with adverse pregnancy outcomes. METHODS: The study examined all MTM and prescription drug claims submitted by a regional chain of supermarket pharmacies from January 1, 2018 to June 30, 2019, to identify female patients aged 15-45 years who received MTM services. Prescription claims were cross-referenced to determine which of these patients also received medications associated with adverse pregnancy outcomes. To identify patients with long-term use of opioids and nonsteroidal anti-inflammatory drugs, a restriction based on days supplied was then applied. RESULTS: Of the 2020 female patients who received MTM services and filled at least 1 prescription during the study period, 731 (36.2%) were found to have received at least 1 medication associated with adverse pregnancy outcomes for the minimal days' threshold. Of these, 509 (69.6%) lacked evidence of concurrent prescription contraception, and 74 (10.1%) had a concurrent prescription for folic acid or prenatal vitamins. CONCLUSION: The use of medications associated with adverse pregnancy outcomes was widespread in this sample of reproductive-aged women. The findings of this study indicate the need for additional research to investigate the implementation of targeted MTM interventions to build standard workflow processes and facilitate pharmacists' management of this critical clinical issue.

Engaging pharmacogenomics in pain management and opioid selection.

Opioid misuse and mismanagement has been a public health crisis for several years. Pharmacogenomics (PGx) has been proposed as another tool to enhance opioid selection and optimization, with recent studies demonstrating successful implementation and outcomes. However, broad engagement with PGx for opioid management is presently limited. The purpose of this article is to highlight a series of barriers to PGx implementation within the specific context of opioid management. Areas of advancement needed for more robust pharmacogenomic engagement with opioids will be discussed, including clinical and economic research needs, education and training needs, policy and public health considerations, as well as legal and ethical issues. Continuing efforts to address these issues may help to further operationalize PGx toward improving opioid use.

Barriers, solutions, and effect of using pharmacogenomics data to support opioid prescribing.

Opioid use and misuse are continued issues facing clinicians across all aspects of health care. As clinicians struggle to effectively manage opioid prescribing, pharmacogenomics (PGx) further offers the prescriber an improved ability to understand the potential for an individual patient's genetics to influence opioid efficacy and safety. When PGx data are available at the point of initial prescribing, clinicians can apply that data to drug therapy selection. However, barriers continue to exist relative to PGx data sharing and interpretation, which have created difficulties for widespread PGx implementation. This article briefly describes potential barriers to PGx data integration, strategies to overcome those barriers, and the potential positive effect of successful data sharing on opioid prescribing. Prescription drug monitoring programs (PDMPs) have been successfully operationalized to share controlled substance prescribing data across health care settings. Such data sharing enables clinicians to, among other things, better understand risks associated with misuse. Because a relatively limited volume of PGx data is currently pertinent to opioid prescribing, such PGx data could be added to PDMPs as a way to communicate genetic information within current technology platforms. Not only would this integrate into existing clinical workflow models where PDMP data are accessed at this point of prescribing and/or dispensing, but associated clinical guidance for PGx data interpretation in the context of opioids could be integrated into the workflow process. Such clinical decision support could be provided directly through the PDMP interface for uniformity or could be provided via systems that access PDMP data. Clinical, economic, and policy implications of the inclusion of PGx data within PDMPs are also discussed. Through harnessing PDMP for data sharing, multiple barriers to PGx implementation could be mitigated, and clinicians may have better access to PGx data to optimize opioid prescribing. DISCLOSURES: No outside funding supported this study. Bright has a patent pending related to opioid use disorder risk assessment that includes genetic information and was a collaborator on funded research projects with pharmacogenomics-related companies. Petry has been a consultant to the North Dakota Department of Health and has received grants from IGNITE I and IGNITE II (NIH), unrelated to this work. The other authors are aware of no financial conflicts of interest.