Analyses suggest iron overload in red blood cell (RBC) transfusion-dependent (TD) patients with myleodysplastic syndrome (MDS) portends inferior overall survival (OS) that is attenuated by iron chelation therapy (ICT) but may be biassed by unbalanced patient-related factors. The Canadian MDS Registry prospectively measures frailty, comorbidity and disability. We analysed OS by receipt of ICT, adjusting for these patient-related factors. TD International Prognostic Scoring System (IPSS) low and intermediate-1 risk MDS, at RBC TD, were included. Predictive factors for OS were determined. A matched pair analysis considering age, revised IPSS, TD severity, time from MDS diagnosis to TD, and receipt of disease-modifying agents was conducted. Of 239 patients, 83 received ICT; frailty, comorbidity and disability did not differ from non-ICT patients. Median OS from TD was superior in ICT patients (5·2 vs. 2·1 years; P < 0·0001). By multivariate analysis, not receiving ICT independently predicted inferior OS, (hazard ratio for death 2·0, P = 0·03). In matched pair analysis, OS remained superior for ICT patients (P = 0·02). In this prospective, non-randomized analysis, receiving ICT was associated with superior OS in lower IPSS risk MDS, adjusting for age, frailty, comorbidity, disability, revised IPSS, TD severity, time to TD and receiving disease-modifying agents. This provides additional evidence that ICT may confer clinical benefit.

Background A decreased capacity to self-manage medications results in nonadherence, medication errors, and drug-related problems in older adults. Previous research identified 80 electronic medication adherence products available to assist patients with self-management of medications. Unfortunately, the usability and workload of these products are unknown. Objective This study aimed to examine the usability and workload of a sample of electronic medication adherence products. Methods In a prospective, mixed methods study, a sample of older adults, health care professionals, and caregivers tested the usability and workload of 21 electronic medication adherence products. Each participant tested 5 products, one at a time, after which they completed the system usability scale (SUS) and NASA-task load index (NASA-TLX), instruments that measure the usability and workload involved in using a product. Higher SUS scores indicate more user-friendliness, whereas lower NASA-TLX raw scores indicate less workload when using a product. Results Electronic medication adherence products required a mean of 12.7 steps (range 5-20) for the appropriate use and took, on average, 15.19 min to complete the setup tasks (range 1-56). Participants were able to complete all steps without assistance 55.3% of the time (103 out of the 186 tests were completed by 39 participants; range 0%-100%). The mean SUS and NASA-TLX raw scores were 52.8 (SD 28.7; range 0-100) and 50.0 (SD 25.7; range 4.2-99.2), respectively, revealing significant variability among the electronic medication adherence products. The most user-friendly products were found to be TimerCap travel size (mean 78.67, SD 15.57; P=.03) and eNNOVEA Weekly Planner with Advanced Auto Reminder (mean 78.13, SD 14.13; P=.049) as compared with MedReady 1700 automated medication dispenser (mean 28.63, SD 21.24). Similarly, MedReady (72.92, SD 18.69) was found to be significantly more work intensive when compared with TimerCap (29.35, SD 20.35; P=.03), e-pill MedGlider home medication management system (28.43, SD 20.80; P=.02), and eNNOVEA (28.65, SD 14.97; P=.03). The e-pill MedTime Station automatic pill dispenser with tipper (71.77, SD 21.98) had significantly more workload than TimerCap (P=.04), MedGlider (P=.03), and eNNOVEA (P=.04). Conclusions This study demonstrated that variability exists in the usability and workload of different electronic medication adherence products among older adults, caregivers, and clinicians. With few studies having investigated the usability and workload of electronic medication adherence products, no benchmarks exist to compare the usability and workload of these products. However, our study highlights the need to assess the usability and workload of different products marketed to assist with medication taking and provides guidance to clinicians regarding electronic medication adherence product recommendations for their patients. Future development of electronic medication adherence products should ensure that the target populations of patients are able to use these products adequately to improve medication management.

Background Medication management among older adults continues to be a challenge, and innovative electronic medication adherence products have been developed to address this need. Objective The aim of this study is to examine user experience with electronic medication adherence products, with particular emphasis on features, usefulness, and preferences. Methods Older adults, caregivers, and health care providers tested the usability of 22 electronic medication adherence products. After testing 5 products, participants were invited to participate in a one-on-one interview to investigate their perceptions and experiences with the features, usefulness, and preference for electronic medication adherence products tested. The interviews were audio recorded, transcribed, and analyzed using exploratory inductive coding to generate themes. The first 13 interviews were independently coded by 2 researchers. The percentage agreement and Cohen kappa after analyzing those interviews were 79% and 0.79, respectively. A single researcher analyzed the remaining interviews. Results Of the 37 participants, 21 (57%) were older adults, 5 (14%) were caregivers, and 11 (30%) were health care providers. The themes and subthemes generated from the qualitative analysis included product factors (subthemes: simplicity and product features, including availability and usability of alarms, portability, restricted access to medications, and storage capacity) and user factors (subthemes: sentiment, affordability, physical and cognitive capability, and technology literacy and learnability). Conclusions Electronic medication adherence products have the potential to enable independent medication management in older adults. The choice of a particular product should be made after considering individual preferences for product features, affordability, and the sentiment of the users. Older adults, caregivers, and health care providers prefer electronic medication adherence products that are simple to set up and use, are portable, have easy-to-access medication compartments, are secure, and have adequate storage capacity.

Background: Smart medication adherence products (smart MAPs) capture and transmit real-time medication intake by using various means of connectivity, allowing for remote monitoring. Numerous such products with different features are available to address medication nonadherence. A comparison of the features of these products is needed for clinical decision-making. Therefore, the objective of this review was to compare smart MAPs available for in-home use. Methods: We searched grey and published literature and videos to identify smart MAPs. To be considered smart, products required 2 features: connectivity (the ability for collected data to exist outside the physical device) and automaticity (the ability for data to be analyzed or processed automatically). Products were excluded if product descriptions were not available in English, not for in-home use and unable to dispense medications. Results: Of the 51 products identified, 38 commercially available and 13 prototypes met the definition. Of these, 75% ( n = 38) contained alarms, 24% ( n = 12) were unit-dose, 63% ( n = 32) were multidose, 43% ( n = 22) had locking features, 41% ( n = 21) were portable and 88% ( n = 45) sent notifications to patients. The cost of marketed products, excluding subscriptions, ranged from $10 to $1500 USD. Some products required a monthly ( n = 16) or yearly ( n = 1) subscription ranging from $10 to $100 USD. Discussion: There is a growing market of smart MAPs for in-home patient use with variable features. Clinicians can use these features to identify and recommend products according to the specific needs of their patients to address medication adherence. Can Pharm J (Ott) 2021;154:xx-xx.