Studies have explored the association of particular conditions, or combinations of conditions, and pain among specific populations. However, there is limited information regarding the association of the number of comorbid conditions, as well as other demographic, economic, health, and limitation variables, with pain among adults in the United States. This cross-sectional database study aimed to examine the relationships between number of comorbid conditions (including cancer, arthritis, joint pain, stroke, heart attack, angina, coronary heart disease, high cholesterol, high blood pressure, other heart diseases, diabetes, asthma, chronic bronchitis, and emphysema), demographic, economic, health, and limitation variables with pain among United States adults using 2021 Medical Expenditure Panel Survey data. A multivariable logistic model assessed the association between the number of comorbid conditions (≥6, 5, 4, 3, 2, 1, versus 0 conditions) and quite a bit/extreme (versus little/moderate) pain, adjusting for demographic, economic, health, and limitation variables. The study found that greater numbers of comorbid conditions were associated with higher odds of quite a bit or extreme pain. In addition, age, education, employment, income, overall health, regular physical activity, and three limitation variables were each associated with pain in the multivariable model. These findings offer insight into the association between number of comorbid conditions and other variables with pain and suggest areas where interventions may be helpful to help improve pain outcomes for United States adults.

This study evaluated a pharmacist-led telephonic Medication Therapy Management (MTM) program for rural patients in Arizona with poor access to healthcare services. A pharmacist provided telephonic MTM services to eligible adult patients living in rural Arizona communities with a diagnosis of diabetes and/or hypertension. Data were collected and summarized descriptively for demographic and health conditions, clinical values, and medication-related problems (MRPs) at the initial consultation, and follow-up data collected at 1 and 3 months. A total of 33 patients had baseline and one-month follow-up data, while 15 patients also had three-month follow-up data. At the initial consultation, the following MRPs were identified: medication adherence issues, dose-related concerns, adverse drug events (ADE), high-risk medications, and therapeutic duplications. Recommendations were made for patients to have the influenza, herpes zoster, and pneumonia vaccines; and to initiate a statin, angiotensin converting enzyme inhibitor, angiotensin receptor blocker, beta-blocker, and/or rescue inhaler. In conclusion, this study demonstrated that while pharmacists can identify and make clinical recommendations to patients, the value of these interventions is not fully realized due to recommendations not being implemented and difficulties with patient follow-up, which may have been due to the COVID-19 pandemic. Additional efforts to address these shortcomings are therefore required.

(1) Background: Adverse drug events and inappropriate use of medications lead to hospitalizations, medication-related morbidity, and mortality. This study examined whether a novel medication risk prediction tool, the MedWise Risk Score™, was associated with medication safety-related problem (MRP) identification and whether integration into an existing innovative transitions of care (TOC) service could decrease readmissions. (2) Methods: This retrospective comparator group study assessed patients discharged from a hospital in southern Arizona between January and December 2020. Participants were included in the study if they were 18 years of age or older, referred to the pharmacist for TOC services, and received a pharmacist consultation within one-week post discharge. Patients were categorized into two groups: (1) medication safety review (MSR)-TOC service (intervention) or (2) existing innovative TOC service (control). (3) Results: Of 164 participants, most were male (57%) and were between 70–79 years of age. Overall, there were significantly more drug-drug interactions (DDI) MRPs identified per patient in the intervention vs. control group for those who were readmitted (3.7 ± 1.5 vs. 0.9 ± 0.6, p < 0.001) and those who were not readmitted (2 ± 1.3 vs. 1.3 ± 1.2, p = 0.0120). Furthermore, of those who were readmitted, the average number of identified MRPs per patient was greater in the intervention group compared to the control (6.3 vs. 2.5, respectively, p > 0.05). Relative to the control, the readmission frequency was 30% lower in the treatment group; however, there was insufficient power to detect significant differences between groups. (4) Conclusions: The integration of a medication risk prediction tool into this existing TOC service identified more DDI MRPs compared to the previous innovative TOC service, which lends evidence that supports its ability to prevent readmissions. Future work is warranted to demonstrate the longitudinal impact of this intervention in a larger sample size.