Agreement of Different Drug-Drug Interaction Checkers for Proton Pump Inhibitors

Importance

Proton pump inhibitors (PPIs) are a widely prescribed class of drugs, potentially interacting with a large number of medicines, especially among older patients with multimorbidity and polypharmacy. Beyond summary of product characteristics (SPCs), interaction checkers (ICs) are routinely used tools to help clinicians in medication review interventions.

Objective

To assess the consistency of information on drugs potentially interacting with PPIs as reported in their SPCs and different ICs.

Design, Setting, and Participants

This cross-sectional study was conducted using data from SPCs for 5 PPIs (omeprazole, esomeprazole, lansoprazole, pantoprazole, and rabeprazole) and 5 ICs (ie, INTERCheck WEB, Micromedex, Lexicomp, Epocrates, and drugs.com). Information from the SPCs and the ICs were extracted between July 15 and 30, 2023.

Main Outcomes and Measures

The main outcome was the level of agreement among SPCs and the 5 ICs in identifying drugs potentially interacting with PPIs and attributing drug-drug interaction (DDI) severity categories. The level of agreement was computed using Gwet AC1 statistic on the 5 ICs and by comparing 4-sets and 2-sets of ICs. As a sensitivity analysis, the level of agreement in listing PPI-related DDIs was evaluated using Cohen κ and Fleiss κ coefficients.

Results

Considering SPCs and the 5 ICs, a total of 518 potentially interacting drugs with omeprazole were reported, 455 for esomeprazole, 433 for lansoprazole, 421 for pantoprazole, and 405 for rabeprazole. As compared with the ICs, the SPCs reported a much smaller number of drugs potentially interacting with PPIs, with proportions ranging from 2.7% (11 potentially interacting drugs) for rabeprazole to 7.6% (33 potentially interacting drugs) for lansoprazole of the total identified drugs at risk of interaction with a PPI. The overall level of agreement among the 5 ICs for identifying potential interactions was poor (from 0.23 [95% CI, 0.21-0.25] for omeprazole to 0.27 [95% CI, 0.24-0.29] for pantoprazole and 0.27 [95% CI, 0.25-0.29] for rabeprazole). Similarly, the level of agreement was low in 4-set and 2-set analyses as well as when restricting the analysis to the potential DDIs identified as severe (range, 0.30-0.32).

Conclusions and Relevance

This cross-sectional study found significant disagreement among different ICs and SPCs, highlighting the need to focus on standardizing DDI databases. Therefore, to ensure evaluation and prevention of clinically relevant DDIs, it is recommended to revise multiple ICs and consult with specialists, such as clinical pharmacologists, particularly for patients with complex medical conditions.

Exploring the level of agreement among different drug-drug interaction checkers: a comparative study on direct oral anticoagulants

BACKGROUND

Direct oral anticoagulants (DOACs) may be involved in drug-drug interactions (DDIs) potentially increasing the risk of adverse drug reactions. This study aimed to evaluate the level of agreement among interaction checkers (ICs) and DOACs' summary of product characteristics (SPCs), in listing DDIs and in attributing DDIs' severity.

RESEARCH DESIGN AND METHODS

The level of agreement among five ICs (i.e. INTERCheck WEB, Micromedex, Lexicomp, Epocrates, and drugs.com) in identifying potential DDIs and in attributing severity categories was evaluated using Gwet's AC1 on all five ICs and by comparing groups of four- and two-pair sets of ICs.

RESULTS

A total of 486 potentially interacting drugs with dabigatran, 556 for apixaban, 444 for edoxaban, and 561 for rivaroxaban were reported. The level of agreement among the ICs in identifying potential DDIs was poor (range: 0.12-0.16). Similarly, it was low in 4 and 2 sets analyses. The level of agreement among the ICs in classifying the severity of potential DDIs was poor (range: 0.32-0.34), also in 4 and 2 sets analyses.

CONCLUSIONS

The heterogeneity among different ICs and SPCs underscores the need to standardize DDI datasets and to conduct real-world studies to generate evidence regarding the frequency and clinical relevance of potential DOAC-related DDIs.

Adverse Safety Events in Emergency Medical Services Care of Children With Out-of-Hospital Cardiac Arrest

Importance

Survival for children with out-of-hospital cardiac arrest (OHCA) remains poor despite improvements in adult OHCA survival.

Objective

To characterize the frequency of and factors associated with adverse safety events (ASEs) in pediatric OHCA.

Design, Setting, and Participants

This population-based retrospective cohort study examined patient care reports from 51 emergency medical services (EMS) agencies in California, Georgia, Oregon, Pennsylvania, Texas, and Wisconsin for children younger than 18 years with an OHCA in which resuscitation was attempted by EMS personnel between 2013 and 2019. Medical record review was conducted from January 2019 to April 2022 and data analysis from October 2022 to February 2023.

Main Outcomes and Measure

Severe ASEs during the patient encounter (eg, failure to give an indicated medication, 10-fold medication overdose).

Results

A total of 1019 encounters of EMS-treated pediatric OHCA were evaluated; 465 patients (46%) were younger than 12 months. At least 1 severe ASE occurred in 610 patients (60%), and 310 patients (30%) had 2 or more. Neonates had the highest frequency of ASEs. The most common severe ASEs involved epinephrine administration (332 [30%]), vascular access (212 [19%]), and ventilation (160 [14%]). In multivariable logistic regression, the only factor associated with severe ASEs was young age. Neonates with birth-related and non-birth-related OHCA had greater odds of a severe ASE compared with adolescents (birth-related: odds ratio [OR], 7.0; 95% CI, 3.1-16.1; non-birth-related: OR, 3.4; 95% CI, 1.2-9.6).

Conclusions and Relevance

In this large geographically diverse cohort of children with EMS-treated OHCA, 60% of all patients experienced at least 1 severe ASE. The odds of a severe ASE were higher for neonates than adolescents and even higher when the cardiac arrest was birth related. Given the national increase in out-of-hospital births and ongoing poor outcomes of OHCA in young children, these findings represent an urgent call to action to improve care delivery and training for this population.

Harnessing personalized tailored medicines to digital-based data-enriched edible pharmaceuticals

Tailoring drug products to personalized medicines poses challenges for conventional dosage forms. The prominent reason is the restricted availability of flexible dosage strengths in the market. Inappropriate dosage strengths lead to adverse drug reactions or compromised therapeutic effects. The situation worsens when the drug has a narrow therapeutic window. To overcome these challenges, data-enriched edible pharmaceuticals (DEEP) are novel concepts for designing solid oral products. DEEP have individualized doses and information embedded in quick response (QR) code form. When data are presented in a QR code, the information is printed with edible ink that contains the drug in tailored doses required for the patients.

A Comparison of Innovative App-Based Prescriptions With Conventional Prescriptions for Children by General Dentists: A Mixed Methods Study

Introduction Writing drug prescriptions for children with accurate drug dosages and clear instructions is a must for general dentists. A digital tool in the form of a software application (app) to write, save and share prescriptions can potentially overcome the possible limitations of handwritten prescriptions such as handwriting illegibility, errors in calculations, and incomplete descriptions. However, it is also important to assess the satisfaction of dentists with making prescriptions using a digital tool such as an android application. A mixed methods study comparing an innovative "app-based" and handwritten prescriptions in dental settings is presented. Methodology An indigenously developed and piloted app "PREscribing children made EASY (PREASY)" was used in this study. Based on the preliminary study, a sample size of 20 was found to be adequate. Twenty-two dentists participated in the study. The conventional handwritten and an Android app PREASY-based prescriptions were compared in terms of the time taken, precision of writing, and satisfaction of the dentists. Qualitative feedback regarding the PREASY app was obtained in Google Forms (Google, Inc., Mountain View, CA, USA). Results A study sample of 20 subjects was calculated based on a pilot study, and 22 dentists were recruited. The mean time taken in seconds for handwritten prescriptions (199.14 (+ 59.18)) was almost four times higher than that for app-based prescriptions (52.05 (+ 23.89)) (t-test, P < 0.00001). The accuracy of handwritten prescriptions versus app-based prescriptions was compared by two examiners independently using analysis of variance (ANOVA) in three domains: dosage accuracy, legible handwriting, and completeness of instructions, the differences (Domain 1 mean + SD: 1.04 + 0.89, Domain 2 mean + SD: 1.38 + 0.40, Domain 3 mean + SD: 0.88 + 0.58) being statistically significant (P < 0.05). The differences in the percentages of the three domains (dosage accuracy: 40.9%, legibility of handwriting: 63.6%, completeness of instructions: 18.1%) were found to be statistically significant (P < 0.05; chi-squared statistic, 9.4017). Of the participants, 59% were very satisfied, 36.3% were satisfied, and 4.5% were neutral (chi-squared test, P < 0.00001). Participants' feedback/comments were categorized under technical suggestions, dosage suggestions, criticism, and positive remarks and were thematically analyzed. Conclusion App-based prescriptions proved to be more instantaneous and detailed than handwritten ones with the majority of dentists satisfied. Valuable feedback pertaining to the limitations of the tool was obtained for improving the app. PREASY-based prescriptions could be recommended for prescribing to pediatric dental patients.

Preference and usage pattern of mobile medical apps for drug information purposes among hospital pharmacists in Sarawak, Malaysia

Introduction

Pharmacists are frequent users of mobile medical apps (MMA) for drug information (DI) and clinical decision-making purposes. However, the wide range of available MMA may be of variable credibility and results in heterogeneous recommendations. The need for subscription may also influence choice of apps.

Objective

The objective of this study was to determine the usage pattern of MMA among hospital pharmacists, including their perceptions and factors affecting their choice of apps.

Methods

This cross-sectional study required respondents to fill in an online questionnaire. The questionnaire included sections on respondents' demographic data, MMA usage pattern, perceived usefulness and opinion on subscription fees. Items were adapted from available literature and validated locally. It was made accessible for 6 weeks starting November 2019 for all pharmacists working in the 23 public hospitals in Sarawak to response (universal sampling). Collected data were analysed using descriptive and inferential statistics.

Results

A response rate of 37.2% was achieved (n = 162). Respondents were heavily reliant on MMA, with 78.4% accessing them multiple times daily. The majority also agreed that MMA contain correct and up-to-date information. A median of 5 apps were downloaded, suggesting an ultimate app catering for all DI needs was lacking. The Malaysian Drug Formulary was the most downloaded app (88.3%), whereas Lexicomp® was the most “well-rounded” in terms of functionality. Clinical pharmacists were significantly more likely to purchase MMA, in particular UpToDate® (p < 0.01) due to their need to access clinical updates. Respondents highly recommended institutional access for either UpToDate® or Lexicomp® be made available. Pre-registration pharmacists should be guided on judicious MMA usage, as they downloaded significantly more apps and were more likely to indicate not knowing which DI recommendation to follow (both p < 0.01).

Conclusion

MMA has become an indispensable tool for hospital pharmacists, however there was a tendency to download multiple apps for DI needs. Institutional access can be considered for credible apps identified to ensure accuracy and uniformity of DI recommendations, with purchase decision made after surveying the needs and preferences of end users.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-022-01949-9.

Mobile Health Apps Providing Information on Drugs for Adult Emergency Care: Systematic Search on App Stores and Content Analysis

Background

Drug-referencing apps are among the most frequently used by emergency health professionals. To date, no study has analyzed the quantity and quality of apps that provide information on emergency drugs.

Objective

This study aimed to identify apps designed to assist emergency professionals in managing drugs and to describe and analyze their characteristics.

Methods

We performed an observational, cross-sectional, descriptive study of apps that provide information on drugs for adult emergency care. The iOS and Android platforms were searched in February 2021. The apps were independently evaluated by 2 hospital clinical pharmacists. We analyzed developer affiliation, cost, updates, user ratings, and number of downloads. We also evaluated the main topic (emergency drugs or emergency medicine), the number of drugs described, the inclusion of bibliographic references, and the presence of the following drug information: commercial presentations, usual dosage, dose adjustment for renal failure, mechanism of action, therapeutic indications, contraindications, interactions with other medicinal products, use in pregnancy and breastfeeding, adverse reactions, method of preparation and administration, stability data, incompatibilities, identification of high-alert medications, positioning in treatment algorithms, information about medication reconciliation, and cost.

Results

Overall, 49 apps were identified. Of these 49 apps, 32 (65%) were found on both digital platforms; 11 (22%) were available only for Android, and 6 (12%) were available only for iOS. In total, 41% (20/49) of the apps required payment (ranging from €0.59 [US $0.64] to €179.99 [US $196.10]) and 22% (11/49) of the apps were developed by non–health care professionals. The mean weighted user rating was 4.023 of 5 (SD 0.71). Overall, 45% (22/49) of the apps focused on emergency drugs, and 55% (27/49) focused on emergency medicine. More than half (29/47, 62%) did not include bibliographic references or had not been updated for more than a year (29/49, 59%). The median number of drugs was 66 (range 4 to >5000). Contraindications (26/47, 55%) and adverse reactions (24/47, 51%) were found in only half of the apps. Less than half of the apps addressed dose adjustment for renal failure (15/47, 32%), interactions (10/47, 21%), and use during pregnancy and breastfeeding (15/47, 32%). Only 6% (3/47) identified high-alert medications, and 2% (1/47) included information about medication reconciliation. Health-related developer, main topic, and greater amount of drug information were not statistically associated with higher user ratings (P=.99, P=.09, and P=.31, respectively).

Conclusions

We provide a comprehensive review of apps with information on emergency drugs for adults. Information on authorship, drug characteristics, and bibliographic references is frequently scarce; therefore, we propose recommendations to consider when developing an app of these characteristics. Future efforts should be made to increase the regulation of drug-referencing apps and to conduct a more frequent and documented review of their clinical content.

The Impact of Using mHealth Apps on Improving Public Health Satisfaction during the COVID-19 Pandemic: A Digital Content Value Chain Perspective

The use of mobile technology and equipment has been found to be successful in the governance of public health. In the context of the coronavirus disease 2019 (COVID-19) pandemic, mobile health (mhealth) apps are expected to play an important role in the governance of public health. This study establishes a structural equation model based on the digital content value chain framework, identifies the main values created by mhealth apps in the prevention and control of COVID-19, and surveys 500 citizens of China. The data were analyzed using an independent t-test and partial least squares structural equations (PLS-SEM). The results showed that people who use mhealth apps are more satisfied with public health governance than those who do not; the healthcare assurance value of mhealth apps and healthcare confidence positively influence the interaction between users and mhealth app functions, the interaction with information, and the interaction with doctors to improve users’ satisfaction with public health governance; and the parasocial relationships between doctors and users of mhealth apps positively affect the interactions between users and doctors to improve users’ satisfaction with public health governance. This study confirms the potential of mhealth apps toward improving public health governance during the COVID-19 pandemic from a new perspective and provides a new theoretical basis whereby mobile technology can contribute toward improving public health governance.

Medical Prognosis of Infectious Diseases in Nursing Homes by Applying Machine Learning on Clinical Data Collected in Cloud Microservices

BACKGROUND

treating infectious diseases in elderly individuals is difficult; patient referral to emergency services often occurs, since the elderly tend to arrive at consultations with advanced, serious symptoms.

AIM

it was hypothesized that anticipating an infectious disease diagnosis by a few days could significantly improve a patient's well-being and reduce the burden on emergency health system services.

METHODS

vital signs from residents were taken daily and transferred to a database in the cloud. Classifiers were used to recognize patterns in the spatial domain process of the collected data. Doctors reported their diagnoses when any disease presented. A flexible microservice architecture provided access and functionality to the system.

RESULTS

combining two different domains, health and technology, is not easy, but the results are encouraging. The classifiers reported good results; the system has been well accepted by medical personnel and is proving to be cost-effective and a good solution to service disadvantaged areas. In this context, this research found the importance of certain clinical variables in the identification of infectious diseases.

CONCLUSIONS

this work explores how to apply mobile communications, cloud services, and machine learning technology, in order to provide efficient tools for medical staff in nursing homes. The scalable architecture can be extended to big data applications that may extract valuable knowledge patterns for medical research.

Characterization of the gut microbiota among Veterans with unique military-related exposures and high prevalence of chronic health conditions: A United States-Veteran Microbiome Project (US-VMP) study

The gut microbiome is impacted by environmental exposures and has been implicated in many physical and mental health conditions, including anxiety disorders, affective disorders, and trauma- and stressor-related disorders such as posttraumatic stress disorder (PTSD). United States (US) military Veterans are a unique population in that their military-related exposures can have consequences for both physical and mental health, but the gut microbiome of this population has been understudied. In this publication, we describe exposures, health conditions, and medication use of Veterans in the US Veteran Microbiome Project (US-VMP) and examine the associations between these characteristics and the gut microbiota. This cohort included 331 US Veterans seeking healthcare with the Veterans Health Administration who were 83% male with an average (±SD) age of 47.6 ​± ​13.4 years. The cohort displayed a high prevalence of PTSD (49.8%) and history of traumatic brain injuries (76.1%), and high current use of prescription medications (74.9%) to treat various acute and chronic conditions. We observed significant associations between the gut microbiota composition and gastroenteritis, peripheral vascular disease (PVD), bipolar disorders, symptoms of severe depression based on the Beck Depression Inventory, stimulant and opioid use disorders, beta-blockers, serotonin and norepinephrine reuptake inhibitor antidepressants, diabetes medications, and proton pump inhibitors. Many of the Veteran characteristics examined were associated with altered relative abundances of specific taxa. We found that PVD and cardiovascular disease were associated with lower microbiota diversity in the gut (i.e., α-diversity), while supplemental vitamin use was associated with higher α-diversity. Our study contributes novel insights as to whether the unique exposures of Veterans in this cohort correlate with gut microbiota characteristics and, in line with previous findings with other population-level studies of the microbiome, confirms associations between numerous health conditions and medications with the gut microbiome.

Personalized and Self-Management: Systematic Search and Evaluation Quality Factors and User Preference of Drug Reference Apps in Taiwan

Background: Drug reference apps promote self-management and improve the efficiency and quality of work for physicians, nurses, pharmacists, and patients. This study aimed to describe a systematic and stepwise process to identify drug reference apps in Taiwan, assess the quality of these apps, and analyze the influential factors for user ratings. Methods: A two-step algorithm (KESS) consisting of keyword growing and systematic search was proposed. Seven independent reviewers were trained to evaluate these apps using Mobile App Rating Scale (MARS). A logistic regression model was fitted and average marginal effects (AME) were calculated to identify the effects of factors for higher user ratings. Results: A total of 23 drug reference apps in Taiwan were identified and analyzed. Generally, these drug reference apps were evaluated as acceptable quality with an average MARS score of 3.23. Higher user engagement, more functionality, better aesthetics, and more information associated with higher user ratings. Navigation is the most influential factor on higher user ratings (AME: 13.15%) followed by performance (AME: 11.03%), visual appeal (AME: 10.87%), credibility (AME: 10.67%), and quantity of information (AME: 10.42%). Conclusions: User experience and information clearly affect user ratings of drug reference apps. Five key factors should be considered when designing drug reference apps.

Development and validation of explicit criteria to identify potentially inappropriate prescribing for adults with type 2 diabetes mellitus

BACKGROUND

Early detection and timely resolution of potentially inappropriate prescribing (PIP) prevents adverse outcomes and improves patient care. An explicit tool specifically designed to detect PIP among people with Type 2 Diabetes Mellitus (T2DM) has not been published.

OBJECTIVES

This study aims to develop and validate the Inappropriate Medication Prescribing Assessment Criteria for Type 2 Diabetes Mellitus (IMPACT2DM); an explicit tool that can be used to identify PIP for adults with T2DM.

METHODS

Current national and international guidelines for the management of T2DM and drug information software programs were used to generate potential items. The content of the IMPACT2DM was validated by 2 consecutive rounds of Delphi method. Physicians and clinical pharmacists experienced in providing care for people with diabetes and authors of selected diabetes guidelines were invited to participate in the Delphi panel. Consensus was assumed if 90% (first round) and 85% (second round) of expert panelists showed agreement to include or exclude an item.

RESULTS

A total of 95 potential items were generated from selected diabetes guidelines and drug information software programs. After the first Delphi round 27 items had ≥90% agreement and were included in the tool; 19 items were considered not PIP and were excluded from the tool. The second round contained 49 items; of these 43 were included and 6 were excluded from the tool. The final IMPACT2DM contains 70 items categorized by type of PIP and arranged in terms of medical conditions and medication classes. IMPACT2DM can be applied using information on medical charts and requires minimal or no clinical knowledge to assess quality of diabetes care and improve medication selection.

CONCLUSIONS

IMPACT2DM has been developed from current quality evidence and undergone content validation. It is the first explicit tool specifically designed to identify PIP for adults with T2DM.

Differences in information accessed in a pharmacologic knowledge base using a conversational agent vs traditional search methods

INTRODUCTION

Clinicians rely on pharmacologic knowledge bases to answer medication questions and avoid potential adverse drug events. In late 2018, an artificial intelligence-based conversational agent, Watson Assistant (WA), was made available to online subscribers to the pharmacologic knowledge base, Micromedex®. WA allows users to ask medication-related questions in natural language. This study evaluated search method-dependent differences in the frequency of information accessed by traditional methods (keyword search and heading navigation) vs conversational agent search.

MATERIALS AND METHODS

We compared the proportion of information types accessed through the conversational agent to the proportion of analogous information types accessed by traditional methods during the first 6 months of 2020.

RESULTS

Addition of the conversational agent allowed early adopters to access 22 different information types contained in the 'quick answers' portion of the knowledge base. These information types were accessed 117,550 times with WA during the study period, compared to 33,649,651 times using traditional search methods. The distribution across information types differed by method employed (c² test, P < .0001). Single drug/dosing, FDA/non-FDA uses, adverse effects, and drug administration emerged as 4 of the top 5 information types accessed by either method. Intravenous compatibility was accessed more frequently using the conversational agent (7.7% vs. 0.6% for traditional methods), whereas dose adjustments were accessed more frequently via traditional methods (4.8% vs. 1.4% for WA).

CONCLUSION

In a widely used pharmacologic knowledge base, information accessed through conversational agents versus traditional methods differed. User-centered studies are needed to understand these differences.

Comparing Potential Drug-Drug Interactions in Companion Animal Medications Using Two Electronic Databases

Multiple-drug prescriptions can cause drug–drug interactions (DDIs), which increase risks associated with healthcare in veterinary medicine. Moreover, many human medicines are used in canine patients under the responsibility of veterinarians and may cause severe problems due to off-label use. Currently, many electronic databases are being used as tools for potential DDI prediction, for example, Micromedex and Drugs.com, which may benefit the prediction of potential DDIs for drugs used in canine. The purpose of this study was to examine different abilities for the identification of potential DDIs in companion animal medicine, especially in canine patients, by Micromedex and Drugs.com. Micromedex showed 429 pairs of potential DDIs, while Drugs.com showed 842 pairs of potential DDIs. The analysis comparing results between the two databases showed 139 pairs (12.28%) with the same severity and 993 pairs (87.72%) with different severities. The major mechanisms of contraindicated and major potential DDIs were cytochrome P450 induction–inhibition and QT interval prolongation. Veterinarians should interpret potential DDIs from several databases with caution and keep in mind that the results might not be reliable due to differences in sensitivity to drugs, drug-metabolizing enzymes, and elimination pathway between animals and humans.

Digital health and management of chronic disease: A multimodal technologies typology

This cross-sectional descriptive study aims to (1) describe the current digital technology (DT) use of people with chronic diseases (CD) by identifying different user profiles and (2) determine whether those profiles have specific characteristics regarding health-related variables and patient-doctor relationship quality (RQ). An online questionnaire assessing the uses of multiple types of DT (the Internet, mobile applications and connected devices) and several dimensions related to health and patient-doctor RQ was completed by 954 individuals living with CD. DT user groups were obtained by k-means cluster analysis and then compared using Mann-Whitney tests. The results show three profiles of DT users: (1) hyperconnected (8.9%, regular users of all DTs), (2) biconnected (19.1%, regular users of the Internet and mobile apps) and (3) hypoconnected (72%, casual users of the Internet only). The hyperconnected and biconnected groups are more empowered, more knowledgeable about their treatment and more committed to their doctors than the hypoconnected group. Nonadherence to treatment, health motivations, self-efficacy for health management and the trust dimension of the patient-doctor RQ did not differ between groups. We conclude by discussing the low use of the most recent technologies in the CD population, although these technologies seem to provide access to health information that empowers patients and leads to a better relationship with their doctors.

Current Knowledge about Providing Drug-Drug Interaction Services for Patients-A Scoping Review

Drug-drug interactions (DDIs) pose a major problem to patient safety. eHealth solutions have the potential to address this problem and generally improve medication management by providing digital services for health care professionals and patients. Clinical decision support systems (CDSS) to alert physicians or pharmacists about DDIs are common, and there is an extensive body of research about CDSS for professionals. Information about DDIs is commonly requested by patients, but little is known about providing similar support to patients. The aim of this scoping review was to explore and describe current knowledge about providing digital DDI services for patients. Using a broad search strategy and an established framework for scoping reviews, 19 papers were included. The results show that although some patients want to check for DDIs themselves, there are differences between patients, in terms of demands and ability. There are numerous DDI services available, but the existence of large variations regarding service quality implies potential safety issues. The review includes suggestions about design features but also indicates a substantial knowledge gap highlighting the need for further research about how to best design and provide digital DDI to patients without risking patient safety or having other unintended consequences.

Mobile Health Apps on COVID-19 Launched in the Early Days of the Pandemic: Content Analysis and Review

Background

Mobile health (mHealth) app use is a major concern because of the possible dissemination of misinformation that could harm the users. Particularly, it can be difficult for health care professionals to recommend a suitable app for coronavirus disease (COVID-19) education and self-monitoring purposes.

Objective

This study aims to analyze and evaluate the contents as well as features of COVID-19 mobile apps. The findings are instrumental in helping health care professionals to identify suitable mobile apps for COVID-19 self-monitoring and education. The results of the mobile apps’ assessment could potentially help mobile app developers improve or modify their existing mobile app designs to achieve optimal outcomes.

Methods

The search for the mHealth apps available in the android-based Play Store and the iOS-based App Store was conducted between April 18 and May 5, 2020. The region of the App Store where we performed the search was the United States, and a virtual private network app was used to locate and access COVID-19 mobile apps from all countries on the Google Play Store. The inclusion criteria were apps that are related to COVID-19 with no restriction in language type. The basic features assessment criteria used for comparison were the requirement for free subscription, internet connection, education or advisory content, size of the app, ability to export data, and automated data entry. The functionality of the apps was assessed according to knowledge (information on COVID-19), tracing or mapping of COVID-19 cases, home monitoring surveillance, online consultation with a health authority, and official apps run by health authorities.

Results

Of the 223 COVID-19–related mobile apps, only 30 (19.9%) found in the App Store and 28 (44.4%) in the Play Store matched the inclusion criteria. In the basic features assessment, most App Store (10/30, 33.3%) and Play Store (10/28, 35.7%) apps scored 4 out of 7 points. Meanwhile, the outcome of the functionality assessment for most App Store apps (13/30, 43.3%) was a score of 3 compared to android-based apps (10/28, 35.7%), which scored 2 (out of the maximum 5 points). Evaluation of the basic functions showed that 75.0% (n=36) of the 48 included mobile apps do not require a subscription, 56.3% (n=27) provide symptom advice, and 41.7% (n=20) have educational content. In terms of the specific functions, more than half of the included mobile apps are official mobile apps maintained by a health authority for COVID-19 information provision. Around 37.5% (n=18) and 31.3% (n=15) of the mobile apps have tracing or mapping and home monitoring surveillance functions, respectively, with only 17% (n=8) of the mobile apps equipped with an online consultation function.

Conclusions

Most iOS-based apps incorporate infographic mapping of COVID-19 cases, while most android-based apps incorporate home monitoring surveillance features instead of providing focused educational content on COVID-19. It is important to evaluate the contents and features of COVID-19 mobile apps to guide users in choosing a suitable mobile app based on their requirements.

Comorbid depression in medical diseases

Depression is one of the most common comorbidities of many chronic medical diseases including cancer and cardiovascular, metabolic, inflammatory and neurological disorders. Indeed, the prevalence of depression in these patient groups is often substantially higher than in the general population, and depression accounts for a substantial part of the psychosocial burden of these disorders. Many factors can contribute to the occurrence of comorbid depression, such as shared genetic factors, converging biological pathways, social factors, health behaviours and psychological factors. Diagnosis of depression in patients with a medical disorder can be particularly challenging owing to symptomatic overlap. Although pharmacological and psychological treatments can be effective, adjustments may need to be made for patients with a comorbid medical disorder. In addition, symptoms or treatments of medical disorders may interfere with the treatment of depression. Conversely, symptoms of depression may decrease adherence to treatment of both disorders. Thus, comprehensive treatment plans are necessary to optimize care.

eHealth technologies assisting in identifying potential adverse interactions with complementary and alternative medicine (CAM) or standalone CAM adverse events or side effects: a scoping review

BACKGROUND

While there are several existing eHealth technologies for drug-drug interactions and stand-alone drug adverse effects, it appears that considerably less attention is focussed on that of complementary and alternative medicine (CAM). Despite poor knowledge of their potential interactions and side effects, many patients use CAM. This justifies the need to identify what eHealth technologies are assisting in identifying potential 1) adverse drug interactions with CAM, 2) adverse CAM-CAM interactions or 3) standalone CAM adverse events or side effects.

METHODS

A scoping review was conducted to identify eHealth technologies assisting in identifying potential adverse interactions with CAM or standalone CAM adverse events or side effects, following Arksey and O'Malley's five-stage scoping review framework. MEDLINE, EMBASE, and AMED databases and the Canadian Agency for Drugs and Technologies in Health website were systematically searched. Eligible articles had to have assessed or referenced an eHealth technology assisting in identifying potential one or more of the three aforementioned items. We placed no eligibility restrictions on type of eHealth technology.

RESULTS

Searches identified 3467 items, of which 2763 were unique, and 2674 titles and abstracts were eliminated, leaving 89 full-text articles to be considered. Of those, 48 were not eligible, leaving a total of 41 articles eligible for review. From these 41 articles, 69 unique eHealth technologies meeting our eligibility criteria were identified. Themes which emerged from our analysis included the following: the lack of recent reviews of CAM-related healthcare information; a large number of databases; and the presence of government adverse drug/event surveillance.

CONCLUSIONS

The present scoping review is the first, to our knowledge, to provide a descriptive map of the literature and eHealth technologies relating to our research question. We highlight that while an ample number of resources are available to healthcare providers, researchers, and patients, we caution that the quality and update frequency for many of these resources vary widely, and until formally assessed, remain unknown. We identify that a need exists to conduct an updated and systematically-searched review of CAM-related healthcare or research resources, as well as develop guidance documents associated with the development and evaluation of CAM-related eHealth technologies.

Mobile Applications (Apps) to Support the Hepatitis C Treatment: A Systematic Search in App Stores

The purpose of this review was to identify apps to support the HCV treatment and perform a quality assessment. A comprehensive search was conducted until February 2020 in Apple App Store (iOs) and Google Play Store (Android) using search term such "hepatitis", "hepatology", and "HCV". Two independent authors identified the apps and performed data extraction and quality assessment using Mobile App Rating Scale (MARS). Spearman's correlation analysis was used to analyze the relationships between user's star ratings found in the app stores and quality app defined by the MARS instrument. A total of 316 potential apps were identified, of which 12 apps fully met the eligibility criteria. Most apps were available in both App Stores and developed by commercial developers for healthcare provider. Almost all of apps were updated within the last two year and received 3.7 or above star ratings from users. Overall, only one app was considered with a good quality. The average scores for objective and subjective MARS quality of these apps were 3.54 (SD = 0.65) and 3.27 (SD = 0.76), respectively. Moreover, a majority of apps received objective scores between 3.29 and 4.37/5. However, MARS items such "interactivity", "visual appeal", "quality information", and "credibility" obtained minimum acceptable scores. MARS scores were not significantly correlation the user's star ratings. This systematic search found gaps in apps to support the HCV treatment; 12 apps were identified in this study and only one app achieved a good quality. There is a need that users use these apps cautiously as well as involve expert healthcare professionals in the development of new HCV apps.

Positioning and Utilization of Information and Communication Technology in Community Pharmacies of Selangor, Malaysia: Cross-Sectional Study

BACKGROUND

Information and communication technology (ICT) is an essential element of modern "smart" cities. These smart cities have integrated housing, marketplace, public amenities, services, business, and transportation via ICT. ICT is also now widely used in urban health care delivery.

OBJECTIVE

The aim of this study was to determine the positioning and roles of ICT in community pharmacies in the state of Selangor, Malaysia.

METHODS

A cross-sectional study was conducted from November 2018 to January 2019 across 9 different subdistricts in the state of Selangor, including Subang Jaya, Cheras, Puchong, Port Klang, Kota Kemuning, Selayang, Chow Kit, Ampang, and Seri Kembangan. A total of 90 community pharmacists were approached from the 9 subdistricts and invited to participate in the study.

RESULTS

Of the 90 community pharmacies approached, 60 agreed to participate in the study, representing a response rate of 67%. The majority (36/60, 60%) of the respondents were women, and more than half (32/60, 53%) of the community pharmacies were run by young adults (ie, 30 years old and younger). More than three-quarters of the community pharmacies (46/60, 77%) used electronic health records. Half of the community pharmacies used online social media platforms for advertising and promoting their pharmacies. The vast majority of the community pharmacies (55/60, 92%) were using modern electronic payment systems, and some were also using other new electronic payment methods. Moreover, most of the community pharmacies (41/60, 68%) were using software and programs for accounting and logistics purposes. In addition, 47/60 (78%) of the community pharmacies used a barcode reading system for medicines/health products, and 16/60 (27%) of the pharmacies had online stores, and consumers could buy medicines and health products from these pharmacies via their online portal. In addition, 20/60 (33%) of the community pharmacies used at least one of the common online business platforms available in Southeast Asia to sell products/medicines. The telephone was the most commonly used means of communication with patients, although some pharmacies also used email, WhatsApp, SMS text messaging, and other communication platforms.

CONCLUSIONS

This study showed that the majority of community pharmacies in Selangor, Malaysia are using ICT for different purposes. However, there is still limited use of mobile apps to provide health services. Overall, community pharmacies have been adopting ICT apps for pharmacy services but the rate of adoption is relatively slower than that in other sectors of Malaysia.

Mobile Health Applications for Pediatric Care: Review and Comparison

BACKGROUND

Despite the surge in mobile health (mHealth) applications (apps) about pediatric care in commercial app stores, to our knowledge, reviews of the quality of such apps are lacking. Consequently, it is a great challenge for health care professionals (HCPs) to identify appropriate and reliable mHealth apps for delivering health care services. Thus, we performed a structured review of the extant literature about mHealth apps in pediatric care and quality assessment of selected apps found in commercial app stores.

METHODS

A review and comparison of mHealth apps in pediatric care found in Google's Play Store (Android system) and Apple's App Store (iOS system) were performed. For the structured review of the available literature, Google Scholar, PubMed, IEEE Xplore Digital Library, and Science Direct online databases were used for the literature search. The assessment criteria used for comparison included requirement for Internet connection, size of application, information on disease, diagnostic tools, medical calculator, information on disease treatments, dosage recommendations, and drug interaction checker.

RESULTS

Fifty mHealth apps for general pediatric care and 8 mHealth apps for specific pediatric diseases were discussed in the literature. Of the 90 mHealth apps we reviewed, 27 that fulfilled the study criteria were selected for quality assessment. Medscape, Skyscape, and iGuideline scored the highest (score=7), while PediaBP scored the lowest (score=3).

CONCLUSIONS

Medscape, Skyscape, and iGuideline are the most comprehensive mHealth apps for HCPs as quick references for pediatric care. More studies about mHealth apps in pediatric care are warranted to ensure the quality and reliability of mHealth apps.