Personal digital health apps for managing diabetes should include functions that enable the provision of pharmaceutical care services and allow within-app communication with pharmacists and other healthcare providers, thereby improving patient outcomes. The primary aim of this study was to assess the functions of diabetes apps that were relevant to providing pharmaceutical care services (i.e., medication management, adherence, non-pharmacological management, interoperability, and communication). Sixteen criteria related to pharmaceutical care were developed and then used to assess ten popular diabetes apps. The highest numbers of pharmaceutical care criteria were met by the apps Diabetes:M and mySugr (11 criteria); Contour™Diabetes, Dario Health, and OneTouch Reveal^® (ten); and DiabetesConnect and ESYSTA (nine); followed by Glucose Buddy (eight), meala (seven), and lumind (three). The most prevalent functions were related to promoting adherence and non-pharmacological management, but most criteria relevant to medication management were lacking. Five apps allowed within-app communication between patients and healthcare professionals (HCPs); however, no app included communication with pharmacists. High-quality diabetes apps are powerful tools to support pharmaceutical care and remotely monitor diabetes patients. Improvements are needed as they often lack many medication management functions, including within-app communication with HCPs (especially pharmacists). To maximize diabetes app use and improve outcomes, app developers should consider including pharmacists alongside other healthcare providers when customizing app designs.

The widespread adoption of wearable devices (wearables) for monitoring vital signs, including blood pressure and glucose levels, has experienced a considerable surge in recent times. This surge has led to the generation of a substantial amount of health data, accessible to pharmacists during patient consultations as the healthcare sector advances in digitalization. To enhance the digital competencies of future pharmacists required by the rapidly changing digital health landscape, the Institute of Clinical Pharmacy and Pharmacotherapy, Heinrich Heine University (HHU) Duesseldorf has developed an innovative elective practical course aimed to bolster pharmacy students' competencies in handling wearables and the health data generated. The three-week practical elective course employed wearables FreeStyle Libre® 3 (Continuous Glucose Monitoring, CGM) and Aktiia (Cuffless Blood Pressure Monitoring). The hands-on activities allowed participants to obtain and interpret wearable-generated health-related data and acquainted them with simulated patient cases. Final-year pharmacy students' subjective assessments before and after the course depicted the increased knowledge and competence regarding analysing wearables data.

Digital Medication Review Tools (DMRTs) are increasingly important in pharmacy practice. To ensure that young pharmacists are sufficiently competent to perform medication reviews after graduation, the introduction of DMRTs teaching in academic education is necessary. The aim of our study was to demonstrate the effect of DMRTs use on pharmacy students’ performance when conducting a medication review (MR) in a randomized controlled pre-post design. Forty-one pharmacy students were asked to complete a MR within 60 min, followed by a 10-min consultation with (intervention group) and without a DMRT (control group). The MR performance was subdivided into four categories: communication skills, subjective and objective patient data, assessment, and plan. Performance was assessed using objective structured clinical examinations (OSCEs) and analytical checklists. With the use of DMRTs, the overall performance was improved by 17.0% compared to the control group (p < 0.01). Improvement through DMRTs was seen in the subcategories “Assessment” and “Plan”. Furthermore, pharmacy students liked using DMRTs and felt more confident overall. Our study results demonstrate that DMRTs improve the performance of MRs, hence DMRTs should become an integral part of pharmacy curriculum. Consequently, digitally enabled pharmacists using DMRTs will be better prepared for their professional careers in pharmacy practice.

Obarcanin E, Ali-Sherazi B, Dabidian A, Schlottau S, Deters MA, Läer S. Introducing m-Health and Digital Diabetes Apps in Clinical Pharmacy Education in Germany. J Diabetes Clin Res. 2022;4(1):17-19.

Background: Clinical decision support systems (CDSSs) already support community pharmacists in conducting medication reviews (MRs) by identifying important information on interactions and suggesting clinical solutions. However, their impact in terms of quality and time savings is widely unexplored. The aim of our study was to investigate whether MRs are performed faster and better with or without using a CDSS. Methods: In a randomized controlled study with a cross-over design, 71 pharmacists performed a total of four MRs, two with and two without the use of a CDSS. The primary endpoint was defined as the time required for the MRs. The secondary endpoints were the number of predefined relevant drug-related problems (DRPs) detected and pharmacist satisfaction. Results: Without the use of a CDSS, pharmacists needed between 25.7% and 30.7% more time to perform a MR than with a CDSS. In addition, significantly more relevant DRPs were detected in the MRs with CDSS than without CDSS (70% vs. 50%; p = 0.0037). Furthermore, participants stated that they felt more confident using a CDSS for MRs than without. Conclusions: Our results demonstrate that MRs can be performed both faster and better when using a CDSS than without. Consequently, community pharmacists benefit from the use of CDSSs for MRs, as do patients in terms of their drug therapy safety.

Introduction: Blood pressure follows a circadian rhythm and is influenced by various factors. Blood pressure rises in the morning and decreases at night. It is known that deviations from this pattern are associated with an increased cardiovascular risk. Therefore, it is important to analyze blood pressure profiles and blood pressure variability.Methods: A blood pressure model was developed based on data from cuffless blood pressure measurements of six healthy volunteers over a 14-day period. Exponential formulas were applied for the description of blood pressure curves (systolic and diastolic), which were used for a non-linear regression model in R.Results: All six subjects showed a circadian pattern in systolic and diastolic blood pressure over a 14-day period. Both the measured values and the predicted values show that each subject's blood pressure was lower at night than during the day. Differences emerged in the level of blood pressure, the fluctuation, and the sleep times, which revealed individual characteristics in the daily blood pressure curves.Discussion: This novel blood pressure model can be used to visualize blood pressure profiles for several days and enables the assessment of the intra- and inter-individual variability of blood pressure.