Abstract
Purpose: The primary objective of this study was to estimate the percentage of opioid analgesic (OA) prescriptions dispensed by Kentucky independent pharmacies with correctly entered days' supply in the state prescription drug monitoring program (PDMP) system in 2019. Methods: Using a two-stage cluster design, pharmacies were sampled with probabilities proportional to the volume of dispensed OAs; 100 random OA prescriptions were sampled from PDMP records submitted by each pharmacy. Following recruitment, demographic information and hard-copy prescription data for sampled records were abstracted on-site. Days' supply was independently calculated by two pharmacists using a standard formula with disagreements adjudicated blindly by a third pharmacist. Adjudicated days' supply was compared with that submitted to the PDMP and classified as accurate/inaccurate. Descriptive statistics were used to characterize the sample and a multivariable logistic regression model was used to assess the relationship between accuracy and prescription/practice-related factors. Results: A total of 1281 OA prescriptions were reviewed at 13 participating pharmacies. Accuracy of reported OA days' supply was 89.85%, (95% CI: 86.90, 92.80). Factors associated with accuracy were presence of special instructions from the prescriber (OR 3.13 [95% CI: 1.43, 6.82]), presence of ‘as-needed’ directions (OR 0.29 [95% CI: 0.18, 0.47]), and billing to a third-party payer (OR 1.43 [95% CI: 1.01, 2.02]). Conclusions: Accuracy of OA days' supply reported to the state PDMP was found to be moderately high. Certain prescription-related factors influence accuracy and should be accounted for in future studies. Patterns, including opioid ‘split-billing’ were identified and may impact validity of PDMP and administrative claims studies.
| Original language | English |
|---|---|
| Pages (from-to) | 1253-1261 |
| Number of pages | 9 |
| Journal | Pharmacoepidemiology and Drug Safety |
| Volume | 31 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2022 |
Bibliographical note
Publisher Copyright:© 2022 John Wiley & Sons Ltd.
Funding
The authors would like to thank participating Kentucky independent pharmacies and their respective staffs for their support in this project. The authors also acknowledge the support for this study from the Kentucky All Schedule Prescription Electronic Reporting (KASPER) program. The project described was funded by the U.S. Food and Drug Administration (FDA) through grant number HHSF223201810183C. Additional support was provided by the National Institutes of Health (NIH) National Center for Advancing Translational Sciences through grant number UL1TR001998. The content is solely the responsibility of the authors and does not necessarily represent the official views of the FDA or NIH. The authors would like to thank participating Kentucky independent pharmacies and their respective staffs for their support in this project. The authors also acknowledge the support for this study from the Kentucky All Schedule Prescription Electronic Reporting (KASPER) program. The project described was funded by the U.S. Food and Drug Administration (FDA) through grant number HHSF223201810183C. Additional support was provided by the National Institutes of Health (NIH) National Center for Advancing Translational Sciences through grant number UL1TR001998. The content is solely the responsibility of the authors and does not necessarily represent the official views of the FDA or NIH. The project described was funded by the U.S. Food and Drug Administration (FDA) through grant number HHSF223201810183C. Additional support was provided by the National Institutes of Health (NIH) National Center for Advancing Translational Sciences through grant number UL1TR001998. The content is solely the responsibility of the authors and does not necessarily represent the official views of the FDA or NIH.
| Funders | Funder number |
|---|---|
| Kentucky All Schedule Prescription Electronic Reporting | |
| National Institutes of Health (NIH) | |
| U.S. Food and Drug Administration | HHSF223201810183C |
| National Center for Advancing Translational Sciences (NCATS) | UL1TR001998 |
Keywords
- PDMP
- accuracy
- days' supply
- opioids
- prescription billing
- validation
- validity
ASJC Scopus subject areas
- Epidemiology
- Pharmacology (medical)