Kelli R Metz1, Douglas N Fish1, Patrick W Hosokawa2, Jan D Hirsch3, Anne M Libby4. 1. University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA. 2. University of Colorado School of Medicine, Aurora, CO, USA. 3. University of California San Diego Skaggs School of Pharmacy and Pharmaceutical Sciences, CA, USA. 4. University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO, USA kelli.metz@ucdenver.edu.
Abstract
BACKGROUND: Patients with HIV often have multiple medications besides antiretrovirals (ARV). Medication regimen complexity-formulations, dosing frequencies, and additional directions-expands pill burden by considering self-care demands. Studies show an inverse association between ARV adherence and medication complexity for ARVs only. Patient-level medication regimen complexity beyond ARV complexity is unknown. OBJECTIVE: To measure and characterize Patient-level Medication Regimen Complexity Index (pMRCI) and Antiretroviral Medication Regimen Complexity Index (ARCI) for patients in 2 HIV clinics. We hypothesized that an all-medication complexity metric will exceed disease-state-defined complexity metrics; for ARVs only, the pMRCI score will be smaller than the ARCI score by capturing fewer features of regimens. Associations between complexity and adherence were not assessed. METHOD: Electronic records supplied a retrospective, random sample of adult patients with HIV; medication lists were used to code the pMRCI (n=200). A random subsample (n=66) was coded using ARCI for ARV regimens only. RESULT: Medication counts ranged from 1 to 27; pMRCI scores ranged from 2 to 67.5. ARVs contributed roughly 25% to the pMRCI; other prescriptions contributed about 66%. Dosing frequency made the largest contribution of all components (62%) to the pMRCI. For ARVs, pMRCI and ARCI scores did not differ statistically. CONCLUSION: Unique dosing frequencies raised complexity and may provide opportunities for intervention. Other prescriptions drove pMRCI scores, suggesting that HIV management programs should review all medications. A patient-level approach added value to understanding the role of medications in patient complexity; future work can assess association of pMRCI with adherence and patient outcomes.
BACKGROUND:Patients with HIV often have multiple medications besides antiretrovirals (ARV). Medication regimen complexity-formulations, dosing frequencies, and additional directions-expands pill burden by considering self-care demands. Studies show an inverse association between ARV adherence and medication complexity for ARVs only. Patient-level medication regimen complexity beyond ARV complexity is unknown. OBJECTIVE: To measure and characterize Patient-level Medication Regimen Complexity Index (pMRCI) and Antiretroviral Medication Regimen Complexity Index (ARCI) for patients in 2 HIV clinics. We hypothesized that an all-medication complexity metric will exceed disease-state-defined complexity metrics; for ARVs only, the pMRCI score will be smaller than the ARCI score by capturing fewer features of regimens. Associations between complexity and adherence were not assessed. METHOD: Electronic records supplied a retrospective, random sample of adult patients with HIV; medication lists were used to code the pMRCI (n=200). A random subsample (n=66) was coded using ARCI for ARV regimens only. RESULT: Medication counts ranged from 1 to 27; pMRCI scores ranged from 2 to 67.5. ARVs contributed roughly 25% to the pMRCI; other prescriptions contributed about 66%. Dosing frequency made the largest contribution of all components (62%) to the pMRCI. For ARVs, pMRCI and ARCI scores did not differ statistically. CONCLUSION: Unique dosing frequencies raised complexity and may provide opportunities for intervention. Other prescriptions drove pMRCI scores, suggesting that HIV management programs should review all medications. A patient-level approach added value to understanding the role of medications in patient complexity; future work can assess association of pMRCI with adherence and patient outcomes.
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