Characterization of the medication regimen complexity index in high-utilizer, adult psychiatric patients

Association between medication regimen complexity and glycemic control among patients with type 2 diabetes

INTRODUCTION

Type 2 diabetes mellitus (T2DM) and comorbid conditions require patients to take complex medication regimens. Greater regimen complexity has been associated with poorer T2DM management; however, the relationship between overall regimen complexity and glycemic control is unclear.

OBJECTIVES

Our objectives were: (1) to examine associations between regimen complexity (with the Medication Regimen Complexity Index [MRCI]) and glycemic control (A1C), and (2) to compare overall MRCI with other measures of regimen complexity (overall and diabetes-specific medication count) and diabetes-specific MRCI.

METHODS

This was a secondary data analysis of cross-sectional data from a parent trial. Participants were patients with T2DM taking at least 3 chronic medications followed in safety net clinics in the Chicago area. The MRCI measures complexity based on dosing frequency, route of administration, and special instructions for prescribed medications. MRCI scores were created for overall regimens and diabetes-specific medications. Sociodemographics and outpatient visit utilization were included in models as covariates. Linear regression was used to examine the associations between variables of interest and hemoglobin A1C.

RESULTS

Participants (N = 432) had a mean age of 56.9 years, most were female (66.0%), and Hispanic or Latino (73.3%). Regimen complexity was high based on overall medications (mean = 6.6 medications, SD: 3.09) and MRCI (mean = 21.4, SD: 11.3). Higher diabetes-specific MRCI was associated with higher A1C in bivariate and multivariable models. In multivariable models, overall MRCI greater than 14, fewer outpatient health care visits, male gender, and absence of health insurance were independently associated with higher A1C. The variance in A1C explained by MRCI was higher compared to medication count for overall and diabetes-specific regimen complexity.

CONCLUSIONS

More complex regimens are associated with worse A1C and measuring complexity with MRCI may have advantages. Deprescribing, increasing insurance coverage, and promoting engagement in health care may improve A1C among underserved populations with complex regimens.

Comparison of potential psychiatric drug interactions in six drug interaction database programs: A replication study after 2 years of updates

OBJECTIVE

Drug interaction database programs are a fundamental clinical tool. In 2018, we compared the category of potential drug-drug interaction (DDI) provided by six drug interaction database programs for 100 drug interaction pairs including psychiatric drugs, and found the category often differed. This study replicated the comparison in 2020 after 2 years of updates to all six drug interaction database programs.

METHODS

The 100 drug pairs included 94 different drugs: 67 pairs with a psychiatric and non-psychiatric drug, and 33 pairs with two psychiatric drugs. The assigned category of potential DDI for the drug pairs was compared using percent agreement and Fleiss kappa statistic of interrater reliability.

RESULTS

Despite 67 updates involving 46 of the 100 drug pairs, differences remained. The overall percent agreement among the six drug interaction database programs for the category of potential DDI was 67%. The interrater agreement results did not change. The Fleiss kappa overall interrater agreement was fair. The kappa agreement for a drug pair with any severe category rating was substantial, and the kappa agreement for a drug pair with any major category rating was fair.

CONCLUSIONS

Physicians should be aware of the inconsistency among drug interaction database programs in the category of potential DDI for drug pairs including psychiatric drugs. Additionally, the category of potential DDI for a drug pair may change over time. This study highlights the importance of ongoing international efforts to standardize methods used to define and classify potential DDI.

Complexity of Medication Regimens for Children With Neurological Impairment

IMPORTANCE

Parents of children with severe neurological impairment (SNI) manage complex medication regimens (CMRs) at home, and clinicians can help support parents and simplify CMRs.

OBJECTIVE

To measure the complexity and potentially modifiable aspects of CMRs using the Medication Regimen Complexity Index (MRCI) and to examine the association between MRCI scores and subsequent acute visits.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study was conducted between April 1, 2019, and December 31, 2020, at a single-center, large, hospital-based, complex care clinic. Participants were children with SNI aged 1 to 18 years and 5 or more prescribed medications.

EXPOSURE

Home medication regimen complexity was assessed using MRCI scores. The total MRCI score is composed of 3 subscores (dosage form, dose frequency, and specialized instructions).

MAIN OUTCOMES AND MEASURES

Patient-level counts of subscore characteristics and additional safety variables (total doses per day, high-alert medications, and potential drug-drug interactions) were analyzed by MRCI score groups (low, medium, and high score tertiles). Associations between MRCI score groups and acute visits were tested using Poisson regression, adjusted for age, complex chronic conditions, and recent health care use.

RESULTS

Of 123 patients, 73 (59.3%) were male with a median (interquartile range [IQR]) age of 9 (5-13) years. The median (IQR) MRCI scores were 46 (35-61 [range, 8-139]) overall, 29 (24-35) for the low MRCI group, 46 (42-50) for the medium MRCI group, and 69 (61-78) for the high MRCI group. The median (IQR) counts for the subscores were 6 (4-7) dosage forms per patient, 7 (5-9) dose frequencies per patient, and 5 (4-8) instructions per patient, with counts increasing significantly across higher MRCI groups. Similar trends occurred for total daily doses (median [IQR], 31 [20-45] doses), high-alert medications (median [IQR], 3 [1-5] medications), and potential drug-drug interactions (median [IQR], 3 [0-6] interactions). Incidence rate ratios of 30-day acute visits were 1.26 times greater (95% CI, 0.57-2.78) in the medium MRCI group vs the low MRCI group and 2.42 times greater (95% CI, 1.10-5.35) in the high MRCI group vs the low MRCI group.

CONCLUSIONS AND RELEVANCE

Higher MRCI scores were associated with multiple dose frequencies, complicated by different dosage forms and instructions, and associated with subsequent acute visits. These findings suggest that clinical interventions to manage CMRs could target various aspects of these regimens, such as the simplification of dosing schedules.