Patient-level Medication Regimen Complexity Index Research Articles

Medication regimen complexity and its association with adherence and blood pressure control among hypertensive patients at selected hospitals of South Gondar Zone: A hospital based cross sectional study.

Despite the availability of effective antihypertensive medications, blood pressure (BP) control is suboptimal. High medication regimen complexity index (MRCI) is known to reduce adherence and may be the reason for poor BP control. However, there is no data in the present study areas. Hence, the aim of this study was to assess MRCI and its association with adherence and BP control among hypertensive patients at selected hospitals of South Gondar Zone. A hospital based cross sectional study was conducted from December 1, 2020 to February 30, 2021 at selected hospitals of South Gondar Zone. Medication regimen complexity and adherence was evaluated using 65-item validated tool called MRCI (Text removed at time of retraction. See retraction notice for more information.). Multivariable logistic regression analysis was done to determine the association between predictive and outcome variables. About 3.3% of participants were classified as having high HTN specific MRCI whereas 34.75% of participants were classified as having high patient level MRCI. (Text removed at time of retraction. See retraction notice for more information.) Being illiterate, and having low HTN MRCI were more likely to have controlled BP in adjusted analyses. On the contrary, (Text removed at time of retraction. See retraction notice for more information.) not having health insurance, and having lower monthly income were less likely to have controlled BP. A considerable proportion of patients had high MRCI. Having low HTN MRCI was more likely to have controlled BP. Simplification of a complex medication regimen for patients with HTN should be sought by physicians and pharmacists to improve BP control.

Lower Cumulative Antiretroviral Exposure in People Living With HIV and Diabetes Mellitus.

People living with HIV (PLWH) are living longer and developing more non-AIDS comorbidities, which negatively impact antiretroviral therapy (ART) adherence. Tenofovir diphosphate (TFV-DP) in dried blood spots (DBS) is a novel pharmacologic measure of cumulative ART adherence that is predictive of viral suppression and future viremia. However, the relationship between non-AIDS comorbidities and this adherence measure is unknown. We aimed to evaluate the association between 3 non-AIDS comorbidities (diabetes mellitus (DM), hypertension, and hyperlipidemia) and TFV-DP in DBS in PLWH. Blood for TFV-DP in DBS and HIV viral load was prospectively collected from PLWH on tenofovir disoproxil fumarate for up to 3 times over 48 weeks. Non-AIDS comorbidities were recorded. Mixed effect multivariable linear regression models were used to estimate the changes in TFV-DP concentrations in DBS according to the presence of comorbidities and to estimate the percent differences in TFV-DP concentrations between these groups. A total of 1144 person-visits derived from 523 participants with available concentrations of TFV-DP in DBS were included in this analysis. In univariate analysis, no significant association between non-AIDS comorbidities (categorized as having 0, 1, 2, or 3 comorbidities) and the concentrations of TFV-DP in DBS was observed (P = 0.40). Participants who had DM had 25% lower (95% confidence interval: -36% to -12%; P < 0.001) TFV-DP in DBS than participants without DM after adjusting for age, gender, race, body mass index, estimated glomerular filtration rate, CD4 T-cell count, hematocrit, ART class, patient-level medication regimen complexity index, and 3-month self-reported adherence. Diabetic PLWH have lower concentrations of TFV-DP in DBS compared with those without DM. Further research is required to identify the clinical implications and biological mechanisms underlying these findings.

Medication Regimen Complexity in Patients Receiving Consultant Pharmacy Services in Home Health Care.

An interprofessional, team-based approach has become common in a variety of settings. However, consultant pharmacist participation in home health care (HHC) has been limited. To evaluate a potential need for pharmacists in HHC, the objective of this project was to document the medication complexity of patients seen by an established HHC consultant pharmacist service. This retrospective review reports on medication regimen complexity in 79 patients receiving this service using the Patient-Level Medication Regimen Complexity Index (MRCI) tool. The average MRCI score was 30 (± 15 standard deviation), suggesting a high level of medication regimen complexity in this population. High scores have been correlated with increased potential adverse drug events, 30-day hospital readmissions, and reduced adherence. Further research is needed for both the utilization of consultant pharmacists in HHC and the use of MRCI in identifying HHC patients needing pharmacist services.

Medication regimen complexity and its impact on medication adherence and glycemic control among patients with type 2 diabetes mellitus in an Ethiopian general hospital

BackgroundDifferent studies reported that higher diabetes-specific Medication Regimen Complexity Index (MRCI) has a negative impact on glycemic control potentially by decreasing medication adherence. However, information about regimen complexity and its...

Medication regimen complexity in ambulatory older adults with heart failure.

PurposeHeart failure prevalence is increasing in older adults, and polypharmacy is a major problem in this population. We compared medication regimen complexity using the validated patient-level Medication Regimen Complexity Index (pMRCI) tool in “young-old” (60–74 years) versus “old-old” (75–89 years) patients with heart failure. We also compared pMRCI between patients with ischemic cardiomyopathy (ISCM) versus nonischemic cardiomyopathy (NISCM).Patients and methodsMedication lists were retrospectively abstracted from the electronic medical records of ambulatory patients aged 60–89 years with heart failure. Medications were categorized into three types – heart failure prescription medications, other prescription medications, and over-the-counter (OTC) medications – and scored using the pMRCI tool.ResultsThe study evaluated 145 patients (n=80 young-old, n=65 old-old, n=85 ISCM, n=60 NISCM, mean age 73±7 years, 64% men, 81% Caucasian). Mean total pMRCI scores (32.1±14.4, range 3–84) and total medication counts (13.3±4.8, range 2–30) were high for the entire cohort, of which 72% of patients were taking eleven or more total medications. Total and subtype pMRCI scores and medication counts did not differ significantly between the young-old and old-old groups, with the exception of OTC medication pMRCI score (6.2±4 young-old versus 7.8±5.8 old-old, P=0.04). With regard to heart failure etiology, total pMRCI scores and medication counts were significantly higher in patients with ISCM versus NISCM (pMRCI score 34.5±15.2 versus 28.8±12.7, P=0.009; medication count 14.1±4.9 versus 12.2±4.5, P=0.008), which was largely driven by other prescription medications.ConclusionMedication regimen complexity is high in older adults with heart failure, and differs based on heart failure etiology. Additional work is needed to address polypharmacy and to determine if medication regimen complexity influences adherence and clinical outcomes in this population.

Medication Regimen Complexity and A1C Goal Attainment in Underserved Adults With Type 2 Diabetes.

From 2009 to 2012, 51.8% of American adults with diabetes had a hemoglobin A1C (A1C) >7.0%. The complexity of antidiabetic medication regimens may have an impact on glycemic control. The primary objective was to test the hypothesis that higher diabetes-specific medication regimen complexity index (MRCI) was associated with lower attainment of A1C goal <7.0% in an underserved, predominantly Hispanic population of adults with type 2 diabetes. Secondary analyses included less stringent A1C goals of <8.0% and <9.0% and overall patient-level MRCI. This study was a retrospective, observational, cross-sectional study of individuals with type 2 diabetes from January 2011 to January 2016. Data was obtained from the electronic medical record and MRCI was calculated using the 65-item validated Microsoft Access Version 1.0 medication regimen complexity electronic data capture tool. Logistic regression was used to compute unadjusted and adjusted odds ratios. A total of 368 patients were included in the analysis. High diabetes-specific MRCI was associated with lower attainment of A1C goal <7.0% (adjusted OR = 0.09; 95% CI = 0.04-0.18) controlling for age, gender, ethnicity, insurance, body mass index, smoking status, hypertension, and hyperlipidemia. Similar results were obtained for the less stringent A1C goals. However, results for overall patient-level MRCI were mixed. Higher diabetes-specific medication regimen complexity was associated with poorer glycemic control. Simplifying antidiabetic medication regimens, especially where the treatment guidelines give no preference, could be a step toward achieving treatment goals.

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

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. 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. 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). 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). 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.

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

BackgroundThe 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.PurposeTo conduct a MRCI validation pertinent to the desired clinical use to identify patients for medication therapy management interventions.MethodsAn 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.ResultsModerate 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.LimitationsThis 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.ConclusionsThe 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 in Patients With HIV.

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. 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. 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. 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. 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.

Medication regimen complexity in patients with uncontrolled hypertension and/or diabetes

ObjectivesTo compare medication regimen complexity (MRC) for patients with uncontrolled hypertension, uncontrolled diabetes, or both, to examine the contribution of complexity components (dosage form, frequency, additional directions) to total MRC index (MRCI) score, and to explore the relationship of MRC with patient characteristics and medication regimen cost. MethodsThis cross-sectional retrospective study used electronic medical record data for patients’ most recent visit to a university internal medicine clinic during 2009. MRCI scores (disease specific and patient level [medications for all conditions]) were calculated for adults with uncontrolled hypertension, diabetes, or both (i.e., not at recommended treatment goals). Results206 patients (85 with hypertension, 60 with diabetes, and 61 with both) were included. The median (range) disease-specific MRCI was significantly greater for diabetes (8.0 [3–21]) than for hypertension (3.0 [2–11], P < 0.001), though the median number of disease-specific medications was identical (2). The majority of hypertension MRC was the result of dosage frequency (62.1%), while diabetes MRC was distributed among dosage form (38.3%), frequency (39.1%), and additional directions (27.6%). The median patient-level MRCI scores for each group were 11 to 15 points higher than the disease-specific MRCI scores. Higher MRCI scores were associated with higher regimen cost, comorbidity burden, and female gender. ConclusionThe magnitude of MRCI scores varied across the three disease groups, increased dramatically when all medications were considered, and revealed greater complexity than a simple count of prescribed medications. The MRCI may be a useful tool for targeting patients for whom medication therapy management services would be most beneficial and cost effective.