Evaluating Patient-Level Medication Regimen Complexity Over Time in Heart Transplant Recipients.

BACKGROUND: Medication regimen complexity describes multiple characteristics of a patient's prescribed drug regimen. Heart transplant recipients must comply with a lifelong regimen that consists of numerous medications. However, a systematic assessment of medication regimen complexity over time has not been conducted in this, or any other, transplant population. OBJECTIVE: The objective of this study was to quantify patient-level medication regimen complexity over time following primary heart transplantation and heart retransplantation, using the validated patient-level Medication Regimen Complexity Index (pMRCI) tool. METHODS: Medication lists were reviewed at transplant discharge and years 1, 3, and 5 post-primary heart transplant, and at transplant discharge and years 1 and 3 post-heart retransplantation. Medications were categorized as transplant-specific, other prescription, and over-the-counter (OTC). RESULTS: In primary heart transplant recipients (n = 60), mean total medication count was 14.3 ± 3.4 at transplant discharge and did not change significantly over time ( P = 0.64). Transplant-specific medication count decreased significantly from discharge (2.9 ± 0.4) to year 5 (2.3 ± 0.6); P = 0.02. However, 32% of patients were taking 16 or more total medications at year 5 posttransplant. More than 70% of the pMRCI score was attributed to other prescription and OTC medications, which was largely driven by dosing frequency in this cohort. Medication complexity did not differ significantly between heart retransplant recipients (n = 11) and matched primary heart transplant controls (n = 22). CONCLUSION: Together, these data highlight the substantial medication burden after heart transplantation and reveal opportunities to address medication regimen complexity in this, and other, transplant populations.

Bleeding, Recurrent Venous Thromboembolism, and Mortality Risks During Warfarin Interruption for Invasive Procedures.

IMPORTANCE: The risk of bleeding and recurrent venous thromboembolism (VTE) among patients receiving long-term warfarin sodium therapy for secondary VTE prevention who require temporary interruption of anticoagulant therapy for surgery or invasive diagnostic procedures has not been adequately described. OBJECTIVE: To describe the rates of clinically relevant bleeding and recurrent VTE among patients in whom warfarin therapy is interrupted for invasive procedures and compare these rates among patients who did and did not receive bridge therapy. DESIGN, SETTING, AND PARTICIPANTS: A retrospective cohort study was conducted at Kaiser Permanente Colorado, an integrated health care delivery system. Patients in whom warfarin therapy was interrupted for invasive diagnostic or surgical procedures between January 1, 2006, and March 31, 2012, were identified via queries of administrative data sets. A total of 1812 procedures in 1178 patients met inclusion criteria. Data on outcomes and exposures were collected between June 1, 2005, and April 30, 2012. EXPOSURES: Use of bridge therapy vs no bridge therapy during warfarin interruption. MAIN OUTCOMES AND MEASURES: Thirty-day clinically relevant bleeding, recurrent VTE, and all-cause mortality. Outcomes were verified via manual review of medical records. RESULTS: Among the 1178 patients, the mean (SD) age was 66.1 (12.7) years, 830 procedures (45.8%) were in men, and the most common indication for warfarin therapy was deep vein thrombosis (56.3%). Most patients were considered to be at low risk for VTE recurrence at the time of warfarin interruption (1431 procedures [79.0%]) according to the consensus guidelines of the American College of Chest Physicians. Clinically relevant bleeding within 30 days after the procedure in the bridge therapy and non-bridge therapy groups occurred in 15 patients (2.7%) and 2 patients (0.2%), respectively (hazard ratio, 17.2; 95% CI, 3.9-75.1). There was no significant difference in the rate of recurrent VTE between the bridge and non-bridge therapy groups (0 vs 3; P = .56). No deaths occurred in either group. CONCLUSIONS AND RELEVANCE: Bridge therapy was associated with an increased risk of bleeding during warfarin therapy interruption for invasive procedures in patients receiving treatment for a history of VTE and is likely unnecessary for most of these patients. Further research is needed to identify patient- and procedure-related characteristics associated with a high risk of perioperative VTE recurrence during warfarin therapy interruption.

Patient-level medication regimen complexity in older adults with depression.

PURPOSE: Polypharmacy and medication adherence are well known challenges facing older adults. Medication regimen complexity increases the demands of self-care in the home. Some medication regimens may be more complex than others, especially when dosage form, frequency of dosing, and additional usage directions are included in complexity along with the number of medications In older adults with depression, it is unknown what features of their medications most influence their medication regimen complexity. METHODS: A sample cohort of 100 adults ≥65 years old with a diagnosis of depression was randomly selected from electronic medical records (EMR) in ambulatory clinics at the University of Colorado (CU) and University of San Diego (SD). Demographic, medical history, and medication-related information was extracted from the EMR. Complexity was determined using the Medication Regimen Complexity Index (MRCI). IRB approval was obtained. FINDINGS: The cohort mean age was 74.3 years (SD) and 79.7 years (CU). The mean unweighted Charlson comorbidity index for 1.0 (SD) and 1.8 (CU). The mean number of medications was 7.1 and 8.0, with 1.1 and 1.2 depression meds, 5.4 and 4.3 non-depression prescription meds, and 0.6 and 2.4 OTC meds for the SD and CU cohorts, respectively. 66% of SD adults and 70% of CU adults took six or more meds. Individual MRCI scores were on average 17.62 (SD) and 19.36 (CU). Dosing frequency contributed to 57-58% of the MRCI score, with patients facing an average of 7-8 unique dosing frequencies in their regimen. In both cohorts, there was an average of 3 additional directions added to the regimens to clarify dosing. IMPLICATIONS: As expected, in our older adult cohorts with depression the majority of patients took multiple medications. Using a standardized instrument, we characterized the regimen complexity and found that it was increasingly complex due to numerous dosing forms, frequencies and additional directions for use. Patient-level medication regimen complexity should go beyond depression medication to encompass the patient's entire regimen for opportunities to reduce complexity and improve ease of self-care.

Patient-Level Medication Regimen Complexity in Patients With HIV.

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.

Validation of a patient-level medication regimen complexity index as a possible tool to identify patients for medication therapy management intervention.

BACKGROUND: The Medication Regimen Complexity Index (MRCI) is a 65-item instrument that can be used to quantify medication regimen complexity at the patient level, capturing all prescribed and over-the-counter medications. Although the MRCI has been used in several studies, the narrow scope of the initial validation limits application at a population or clinical practice level. PURPOSE: To conduct a MRCI validation pertinent to the desired clinical use to identify patients for medication therapy management interventions. METHODS: An expert panel of clinical pharmacists ranked medication regimen complexity for two samples of cases: a single-disease cohort (diabetes mellitus) and a multiple-disease cohort (diabetes mellitus, hypertension, human immunodeficiency virus infection, geriatric depression). Cases for expert panel review were selected from 400 ambulatory clinic patients, and each case description included data that were available via claims or electronic medical records (EMRs). Construct validity was assessed using patient-level MRCI scores, medication count, and additional patient data. Concordance was evaluated using weighted κ agreement statistic, and correlations were determined using Spearman rank-order correlation coefficient (ρ) or Kendall τ. RESULTS: Moderate to good concordance between patient-level MRCI scores and expert medication regimen complexity ranking was observed (claims data, consensus ranking: single-disease cohort 0.55, multiple disease cohort 0.63). In contrast, only fair to moderate concordance was observed for medication count (single-disease cohort 0.33, multiple-disease cohort 0.48). Adding more-detailed administration directions from EMR data did not improve concordance. MRCI convergent validity was supported by strong correlations with medication count (all cohorts 0.90) and moderate correlations with morbidity measures (e.g., all cohorts; number of comorbidities 0.46, Chronic Disease Score 0.46). Nonsignificant correlation of MRCI scores with age and gender (all cohorts 0.08 and 0.06, respectively) supported MRCI divergent validity. LIMITATIONS: This study used cross-sectional, retrospective patient data for a small number of patients and clinical pharmacists from only two universities; therefore, results may have limited generalizability. CONCLUSIONS: The patient-level MRCI is a valid tool for assessing medication regimen complexity that can be applied by using data commonly found in claims and EMR databases and could be useful to identify patients who may benefit from medication therapy management.

Patient-level medication regimen complexity across populations with chronic disease.

BACKGROUND: Expected treatment effectiveness from medications can be diminished due to suboptimal adherence. Medication nonadherence has been linked to pill burden from the quantity of medications; however, medication regimens with similar quantities of medications vary in complexity due to multiple dosage forms, frequency of dosing, and additional usage directions. Thus, a simple medication count ignores medication regimen complexity, especially as it pertains to a patient-level perspective that includes prescription and over-the-counter medications. A gap exists in the study of a patient-level medication regimen complexity metric across disease-specific populations. OBJECTIVE: The goal of this study was to implement the quantitative Medication Regimen Complexity Index (MRCI) at the patient level in defined populations with chronic disease (geriatric depression, HIV, diabetes mellitus, and hypertension). Patient-level medication regimen complexity included all prescribed medications and over-the-counter medications documented in the electronic medication list. METHODS: Using electronic medical records at the University of Colorado Hospital ambulatory clinics, we sampled 4 retrospective cohorts of adult patients in active care in 2011 with a qualifying medical diagnosis and prescribed disease-specific medication. Samples were randomly selected from all qualifying patients; de-identified information was coded using the MRCI. RESULTS: Cohort-defining disease-specific prescription medications (eg, antidepressants for the depression-defined cohort) contributed <20% to the total patient-level complexity MRCI score; the MRCI score was dominated by complexity associated with all other prescription medications. Within disease-specific cohorts, MRCI scores differentiated patients with the highest and lowest medication counts, comorbidity counts, and the Charlson comorbidity index scores. For example, geriatric depression patients had a highest quartile mean MRCI score of 41 and a lowest quartile mean MRCI score of 13. Between disease-specific cohorts, high and low MRCI scores differed because each cohort had its own MRCI ranges. For example, highest quartile MRCI scores varied from a mean MRCI score of 41 (geriatric depression) to 30 (hypertension); lowest quartile scores ranged from a mean MRCI score of 7 (hypertension and HIV) to 13 (geriatric depression). CONCLUSIONS: MRCI components of dosing frequency and prescribed medications outside of the cohort-defining disease medications contributed the most to the patient-level scores. Thus, chronic disease management programs may want to consider all medications that patients are taking and examine ways to reduce complexity, such as reducing multiple dosing frequencies when possible. MRCI scores differentiated high and low patient-level complexity measures, representing possible utility as a prospective tool to identify target patients for intervention. Future work includes simplifying the MRCI and enhancing the scores with medication risk factors, as well as explicitly linking to adherence and health services.