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The motivations that govern the adoption of digital contact tracing (DCT) tools are complex and not well understood. Hence, we assessed the factors influencing the acceptance and adoption of Singapore's national DCT tool - TraceTogether - during the COVID-19 pandemic. We surveyed 3943 visitors of Tan Tock Seng Hospital from July 2020 to February 2021 and stratified the analyses into three cohorts. Each cohort was stratified based on the time when significant policy interventions were introduced to increase the adoption of TraceTogether. Binary logistic regression was preceded by principal components analysis to reduce the Likert items. Respondents who 'perceived TraceTogether as useful and necessary' had higher likelihood of accepting it but those with 'Concerns about personal data collected by TraceTogether' had lower likelihood of accepting and adopting the tool. The injunctive and descriptive social norms were also positively associated with both the acceptance and adoption of the tool. Liberal individualism was mixed in the population and negatively associated with the acceptance and adoption of TraceTogether. Policy measures to increase the uptake of a national DCT bridged the digital divide and accelerated its adoption. However, good public communications are crucial to address the barriers of acceptance to improve voluntary uptake widespread adoption. Nanyang Technological University Published version This project is supported by the NISTH Seed Grant from the NTU Institute of Science and Technology for Humanity, Nanyang Technological University.

BackgroundWe assessed the preferences and trade-offs for social interactions, incentives, and being traced by a digital contact tracing (DCT) tool post lockdown in Singapore.MethodsWe conducted a discrete choice experiment (DCE) among visitors of a large public hospital in Singapore between July 2020 – February 2021. Respondents were sampled proportionately by gender and four age categories (21 – 80 years). The DCE questionnaire had three attributes (1. Social interactions, 2. Being traced by a DCT tool, 3. Incentives to use a DCT tool) and two levels each. The final dataset comprised 3839 respondents after dropping 53 with “irrational” responses. Panel fixed conditional logit model was used to analyze the data.ResultsRespondents were more willing to trade being traced by a DCT tool for social interactions than incentives and unwilling to trade social interactions for incentives. The proportion of respondents preferring no incentives and could only be influenced by their family members increases with age. Among proponents of monetary incentives, the preferred median value for a month’s usage of DCT tools amounted to S$10 (USD7.25) and S$50 (USD36.20) for subsidies and lucky draw.ConclusionsDCE can be used to elicit profile-specific preferences to optimize the uptake of DCT tools during a pandemic. Social interactions are highly valued by the population, who are willing to trade them for being traced by a DCT tool during the COVID-19 pandemic. Although a small amount of incentive is sufficient to increase the satisfaction of using a DCT tool, incentives alone may not increase DCT tool uptake.

Objective Real-time locating systems (RTLS) enable contact tracing and hand hygiene reminders, to improve hospital safety. Successful implementation requires healthcare personnel (HCP) to carry RTLS tags continuously. We assessed for determinants of HCP’s willingness to use RTLS tags during routine inpatient care, and evaluated concerns using mixed-methods analysis. Materials and Methods We conducted a cross-sectional study in the 330-bed purpose-built National Centre for Infectious Diseases in Singapore, from January 15 through February 4, 2020. The anonymous survey comprised 24 questions based on constructs from behavioral models and an open-ended question. Principal component analysis was performed to derive the latent factor structure applied in the multivariable logistic regression analysis. Concerns were analyzed using thematic analysis. Results Of 260 HCP (nurses [40.8%], ancillary and administrative staff [23.1%], allied health professionals [18.5%], and physicians [17.7%]), 75% were willing to use the RTLS tag. After adjusting for age, gender, healthcare professional group, and duration of practice, the acceptance of the use of the RTLS tag (adjusted OR 11.28 [95% CI 4.39–29.00], P Conclusion More communications on the intentions and data protection standards of the RTLS, and accessory enhancements for HCP’s convenient and sustained use of the RTLS tag are crucial, to optimize RTLS’s usefulness during the COVID-19 pandemic.

BACKGROUND Effective contact tracing is labor intensive and time sensitive during the COVID-19 pandemic, but also essential in the absence of effective treatment and vaccines. Singapore launched the first Bluetooth-based contact tracing app—TraceTogether—in March 2020 to augment Singapore’s contact tracing capabilities. OBJECTIVE This study aims to compare the performance of the contact tracing app—TraceTogether—with that of a wearable tag-based real-time locating system (RTLS) and to validate them against the electronic medical records at the National Centre for Infectious Diseases (NCID), the national referral center for COVID-19 screening. METHODS All patients and physicians in the NCID screening center were issued RTLS tags (CADI Scientific) for contact tracing. In total, 18 physicians were deployed to the NCID screening center from May 10 to May 20, 2020. The physicians activated the TraceTogether app (version 1.6; GovTech) on their smartphones during shifts and urged their patients to use the app. We compared patient contacts identified by TraceTogether and those identified by RTLS tags within the NCID vicinity during physicians’ 10-day posting. We also validated both digital contact tracing tools by verifying the physician-patient contacts with the electronic medical records of 156 patients who attended the NCID screening center over a 24-hour time frame within the study period. RESULTS RTLS tags had a high sensitivity of 95.3% for detecting patient contacts identified either by the system or TraceTogether while TraceTogether had an overall sensitivity of 6.5% and performed significantly better on Android phones than iPhones (Android: 9.7%, iPhone: 2.7%; P CONCLUSIONS TraceTogether had a much lower sensitivity than RTLS tags for identifying patient contacts in a clinical setting. Although the tag-based RTLS performed well for contact tracing in a clinical setting, its implementation in the community would be more challenging than TraceTogether. Given the uncertainty of the adoption and capabilities of contact tracing apps, policy makers should be cautioned against overreliance on such apps for contact tracing. Nonetheless, leveraging technology to augment conventional manual contact tracing is a necessary move for returning some normalcy to life during the long haul of the COVID-19 pandemic.

BACKGROUND In early 2020, coronavirus disease (COVID-19) emerged and spread by community and nosocomial transmission. Effective contact tracing of potentially exposed health care workers is crucial for the prevention and control of infectious disease outbreaks in the health care setting. OBJECTIVE This study aimed to evaluate the comparative effectiveness of contact tracing during the COVID-19 pandemic through the real-time locating system (RTLS) and review of the electronic medical record (EMR) at the designated hospital for COVID-19 response in Singapore. METHODS Over a 2-day study period, all admitted patients with COVID-19, their ward locations, and the health care workers rostered to each ward were identified to determine the total number of potential contacts between patients with COVID-19 and health care workers. The numbers of staff-patient contacts determined by EMR reviews, RTLS-based contact tracing, and a combination of both methods were evaluated. The use of EMR-based and RTLS-based contact tracing methods was further validated by comparing their sensitivity and specificity against self-reported staff-patient contacts by health care workers. RESULTS Of 796 potential staff-patient contacts (between 17 patients and 162 staff members), 104 (13.1%) were identified by both the RTLS and EMR, 54 (6.8%) by the RTLS alone, and 99 (12.4%) by the EMR alone; 539 (67.7%) were not identified through either method. Compared to self-reported contacts, EMR reviews had a sensitivity of 47.2% and a specificity of 77.9%, while the RTLS had a sensitivity of 72.2% and a specificity of 87.7%. The highest sensitivity was obtained by including all contacts identified by either the RTLS or the EMR (sensitivity 77.8%, specificity 73.4%). CONCLUSIONS RTLS-based contact tracing showed higher sensitivity and specificity than EMR review. Integration of both methods provided the best performance for rapid contact tracing, although technical adjustments to the RTLS and increasing user compliance with wearing of RTLS tags remain necessary.

Background The efficacy of smartphone apps for improving medication adherence in type 2 diabetes is not well studied in Asian populations. Objective This study aimed to determine the feasibility, acceptability, and clinical outcomes of using a smartphone app to improve medication adherence in a multiethnic Asian population with type 2 diabetes. Methods We block randomized 51 nonadherent and digitally literate patients with type 2 diabetes between the ages of 21 and 75 years into two treatment arms (control: usual care; intervention: usual care+Medisafe app) and followed them up for 12 weeks. Recruitment occurred at a public tertiary diabetes specialist outpatient center in Singapore. The intervention group received email reminders to complete online surveys monthly, while the control group only received an email reminder(s) at the end of the study. Barriers to medication adherence and self-appraisal of diabetes were assessed using the Adherence Starts with Knowledge-12 (ASK-12) and Appraisal of Diabetes Scale (ADS) questionnaires at baseline and poststudy in both groups. Perception toward medication adherence and app usage, attitude, and satisfaction were assessed in the intervention group during and after the follow-up period. Sociodemographic data were collected at baseline. Clinical data (ie, hemoglobin A1c, body mass index, low-density lipoprotein, high-density lipoprotein, and total cholesterol levels) were extracted from patients’ electronic medical records. Results A total of 51 (intervention group: 25 [49%]; control group: 26 [51%]) participants were randomized, of which 41 (intervention group: 22 [88.0%]; control group: 19 [73.1%]) completed the poststudy survey. The baseline-adjusted poststudy ASK-12 score was significantly lower in the intervention group than in the control group (mean difference: 4.7, P=.01). No changes were observed in the clinical outcomes. The average 12-week medication adherence rate of participants tracked by the app was between 38.3% and 100% in the intervention group. The majority (>80%) of the participants agreed that the app was easy to use and made them more adherent to their medication. Conclusions Our feasibility study showed that among medication-nonadherent patients with type 2 diabetes, a smartphone app intervention was acceptable, improved awareness of medication adherence, and reduced self-reported barriers to medication adherence, but did not improve clinical outcomes in a developed Asian setting.

The formation of complexes between plant proteins and polyphenols is being explored for the development for functional ingredients with new or improved properties. In this study, complexes were fabricated from moringa seed residue protein (MSRP) and tannic acid (TA). Fourier transform infrared spectroscopy and isothermal titration calorimetry suggested that the main interactions between MSRP and TA were hydrophobic and hydrogen bonding. The MSRP-TA complexes had near neutral wettability (θow = 86.1°), which meant that they could adsorb strongly to oil-water interfaces and thereby form and stabilize Pickering emulsions. The stability of the emulsions was improved by optimizing the MSRP:TA ratio. Confocal laser scanning microscopy indicated that higher tannic acid concentrations enhanced the thickness and compactness of the MSRP-TA interfacial layers formed around the oil droplets. The physicochemical properties of the emulsions were measured over a range of pH (3–9) and ionic strength (0–0.4 M NaCl) conditions. These results showed that the complexes were able to form stable emulsions at lower ionic strengths (

BackgroundEffective contact tracing is labor intensive and time sensitive during the COVID-19 pandemic, but also essential in the absence of effective treatment and vaccines. Singapore launched the first Bluetooth-based contact tracing app—TraceTogether—in March 2020 to augment Singapore’s contact tracing capabilities.ObjectiveThis study aims to compare the performance of the contact tracing app—TraceTogether—with that of a wearable tag-based real-time locating system (RTLS) and to validate them against the electronic medical records at the National Centre for Infectious Diseases (NCID), the national referral center for COVID-19 screening.MethodsAll patients and physicians in the NCID screening center were issued RTLS tags (CADI Scientific) for contact tracing. In total, 18 physicians were deployed to the NCID screening center from May 10 to May 20, 2020. The physicians activated the TraceTogether app (version 1.6; GovTech) on their smartphones during shifts and urged their patients to use the app. We compared patient contacts identified by TraceTogether and those identified by RTLS tags within the NCID vicinity during physicians’ 10-day posting. We also validated both digital contact tracing tools by verifying the physician-patient contacts with the electronic medical records of 156 patients who attended the NCID screening center over a 24-hour time frame within the study period.ResultsRTLS tags had a high sensitivity of 95.3% for detecting patient contacts identified either by the system or TraceTogether while TraceTogether had an overall sensitivity of 6.5% and performed significantly better on Android phones than iPhones (Android: 9.7%, iPhone: 2.7%; PConclusionsTraceTogether had a much lower sensitivity than RTLS tags for identifying patient contacts in a clinical setting. Although the tag-based RTLS performed well for contact tracing in a clinical setting, its implementation in the community would be more challenging than TraceTogether. Given the uncertainty of the adoption and capabilities of contact tracing apps, policy makers should be cautioned against overreliance on such apps for contact tracing. Nonetheless, leveraging technology to augment conventional manual contact tracing is a necessary move for returning some normalcy to life during the long haul of the COVID-19 pandemic.

Background In early 2020, coronavirus disease (COVID-19) emerged and spread by community and nosocomial transmission. Effective contact tracing of potentially exposed health care workers is crucial for the prevention and control of infectious disease outbreaks in the health care setting. Objective This study aimed to evaluate the comparative effectiveness of contact tracing during the COVID-19 pandemic through the real-time locating system (RTLS) and review of the electronic medical record (EMR) at the designated hospital for COVID-19 response in Singapore. Methods Over a 2-day study period, all admitted patients with COVID-19, their ward locations, and the health care workers rostered to each ward were identified to determine the total number of potential contacts between patients with COVID-19 and health care workers. The numbers of staff-patient contacts determined by EMR reviews, RTLS-based contact tracing, and a combination of both methods were evaluated. The use of EMR-based and RTLS-based contact tracing methods was further validated by comparing their sensitivity and specificity against self-reported staff-patient contacts by health care workers. Results Of 796 potential staff-patient contacts (between 17 patients and 162 staff members), 104 (13.1%) were identified by both the RTLS and EMR, 54 (6.8%) by the RTLS alone, and 99 (12.4%) by the EMR alone; 539 (67.7%) were not identified through either method. Compared to self-reported contacts, EMR reviews had a sensitivity of 47.2% and a specificity of 77.9%, while the RTLS had a sensitivity of 72.2% and a specificity of 87.7%. The highest sensitivity was obtained by including all contacts identified by either the RTLS or the EMR (sensitivity 77.8%, specificity 73.4%). Conclusions RTLS-based contact tracing showed higher sensitivity and specificity than EMR review. Integration of both methods provided the best performance for rapid contact tracing, although technical adjustments to the RTLS and increasing user compliance with wearing of RTLS tags remain necessary.

Background Control of blood glucose levels is needed not only to alleviate symptoms of hypoglycaemia and hyperglycaemia, but also to prevent or delay diabetes-related complications. Advice for glucose control is usually provided to patients by members of the health care team. However, many diabetes apps claim to enhance self-management of blood glucose by providing decision support to patients when an out-of-range blood glucose level is recorded. In this study, we investigated the appropriateness of action prompts provided by diabetes apps for hypoglycaemia and hyperglycaemia against evidence-based guidelines. Methods We used methods previously reported to identify and select diabetes apps, which were downloaded and assessed against the American Diabetes Association (ADA) guidelines. Screenshots of action prompts corresponding to low or high out-of-range blood glucose values were subjected to content analysis. Results Of 371 diabetes self-management apps evaluated, only 217 and 216 apps alerted patients about hypoglycaemia and hyperglycaemia, respectively. Of these, 20.7% (45/217) and 15.3% (33/216) also provided action prompts. We found 5.1% of apps (hypoglycaemia: 11/217; hyperglycaemia: 11/216) provided prompts that were either too general to be helpful or not aligned with ADA guidelines. Overall, only 17.9% (39/217) and 14.8% (32/216) provided appropriate action prompts for hypoglycaemia and hyperglycaemia, respectively. Conclusion Less than one fifth of apps provided evidence-based steps to guide patients through hypoglycaemia and hyperglycaemia. The majority of apps failed to provide just-in-time diabetes self-management education to prevent frequent or severe episodes of hypoglycaemia and hyperglycaemia. Our findings emphasize the need for better design and quality assurance of diabetes apps.

BackgroundThe efficacy of smartphone apps for improving medication adherence in type 2 diabetes is not well studied in Asian populations.ObjectiveThis study aimed to determine the feasibility, acceptability, and clinical outcomes of using a smartphone app to improve medication adherence in a multiethnic Asian population with type 2 diabetes.MethodsWe block randomized 51 nonadherent and digitally literate patients with type 2 diabetes between the ages of 21 and 75 years into two treatment arms (control: usual care; intervention: usual care+Medisafe app) and followed them up for 12 weeks. Recruitment occurred at a public tertiary diabetes specialist outpatient center in Singapore. The intervention group received email reminders to complete online surveys monthly, while the control group only received an email reminder(s) at the end of the study. Barriers to medication adherence and self-appraisal of diabetes were assessed using the Adherence Starts with Knowledge-12 (ASK-12) and Appraisal of Diabetes Scale (ADS) questionnaires at baseline and poststudy in both groups. Perception toward medication adherence and app usage, attitude, and satisfaction were assessed in the intervention group during and after the follow-up period. Sociodemographic data were collected at baseline. Clinical data (ie, hemoglobin A1c, body mass index, low-density lipoprotein, high-density lipoprotein, and total cholesterol levels) were extracted from patients’ electronic medical records.ResultsA total of 51 (intervention group: 25 [49%]; control group: 26 [51%]) participants were randomized, of which 41 (intervention group: 22 [88.0%]; control group: 19 [73.1%]) completed the poststudy survey. The baseline-adjusted poststudy ASK-12 score was significantly lower in the intervention group than in the control group (mean difference: 4.7, P=.01). No changes were observed in the clinical outcomes. The average 12-week medication adherence rate of participants tracked by the app was between 38.3% and 100% in the intervention group. The majority (>80%) of the participants agreed that the app was easy to use and made them more adherent to their medication.ConclusionsOur feasibility study showed that among medication-nonadherent patients with type 2 diabetes, a smartphone app intervention was acceptable, improved awareness of medication adherence, and reduced self-reported barriers to medication adherence, but did not improve clinical outcomes in a developed Asian setting.

BACKGROUND Smartphone apps are increasingly used for disease management but the transparency and reliability of information sources for these apps are unclear. OBJECTIVE As part of a larger study investigating medication management features of diabetes apps, this study aimed to assess the transparency and reliability of information disseminated via these apps against eight criteria adapted from the Health On the Net (HONcode) principles. METHODS English language diabetes-related terms were searched on a market explorer (42matters) on 12 June 2018. Apps with both medication and blood glucose management features were downloaded and evaluated against the app-HONcode criteria adapted from the eight HONcode principles: Authoritative, Complementarity, Privacy, Attribution, Justifiability, Transparency, Financial disclosure, and Advertising policy. Apps were profiled by operating platforms (i.e. Android, iOS) and number of downloads (i.e. Android only: >100,000 downloads, RESULTS 143 apps (81 Android, 62 iOS) were downloaded and assessed against the adapted App-HONcode criteria. Most of the apps on both the Android and iOS platforms fulfilled between two to six criteria but very few apps mentioned the qualifications of individuals who contributed to app development (14.0%, 20/143). A higher proportion of iOS apps fulfilled six or more App-HONcode criteria compared with Android apps. However, Android apps were more likely to have the developer’s email listed on the apps store (Android: 97.6%, 75/81, iOS: 83.9%, 52/62, P=.005) compared with iOS apps. Of the Android apps assessed, a significantly higher proportion of highly downloaded apps had a privacy and confidentiality clause (High downloads: 88.2%, 15/17; Lower downloads DL: 51.6%, 33/64; P=.006) and were more likely to discuss their financial sources (High downloads: 82.4%, 14/17; Lower downloads: 50.0%, 32/64; P =.026) compared with apps with lower downloads. CONCLUSIONS Gaps in the disclosure of the developer’s qualification, funding source and the complementary role of the app in disease management were identified, which can be resolved with stricter pre-requisites set by the app stores. Future work can further examine the consent seeking process for data collection, data management policies, and the appropriateness of advertising content and clarity of privacy clause of these apps.

Frequency of app features grouped by number of downloads (Android apps only). (DOCX 26 kb)

List of smartphones and their operating systems used for app assessment. (DOCX 15 kb)

Background: Smartphone apps are increasingly used for diabetes self-management because of their ubiquity and ability to help users to personalize health care management. The number of diabetes apps has proliferated in recent years, but only a small subset of apps that pose a higher risk are regulated by governmental agencies. The transparency and reliability of information sources are unclear for apps that provide health care advice and are not regulated by governmental agencies. Objective: This study aimed to assess the transparency and reliability of information disseminated via diabetes apps against 8 criteria adapted from the Health On the Net code of conduct (HONcode) principles. Methods: English-language diabetes-related terms were searched on a market explorer (42matters) on June 12, 2018. Apps with medication and blood glucose management features were downloaded and evaluated against the App-HONcode criteria adapted from the 8 HONcode principles: authoritative, complementarity, privacy, attribution, justifiability, transparency, financial disclosure, and advertising policy. Apps were profiled by operating platforms (ie, Android and iOS) and the number of downloads (ie, Android only: ≥100,000 downloads and

Moringa oleifera leaves contains antimicrobial protein, which is absent of optimized extraction and systematic analysis. The aim of this work is to provide a systematic research of its protein isolate hydrolysate on the optimized extraction via the response surface method and the functional properties. The isolated protein was obtained by alkali extraction and acid precipitation, which purity was 81.12%±0.03%. Through the response surface method, the result of the optimization obtained the enzymatic hydrolysis of antimicrobial protein was as follows, the substrate concentration of 5.09%, the Bromelain enzyme dosage of 3883.42 U/g, pH 7.0 and temperature of 55 °C for 3.64 h . And the protein hydrolysate was indicated that the purity was 88.59%±0.13%. Moreover, the ash, the crude fat and moisture were declined significantly compared with the protein isolate. This subject could provide basic theoretical basis for the application of M. oleifera leaves protein.

BACKGROUND There is a shortage of health care professionals competent in diabetes management worldwide. Digital education is increasingly used in educating health professionals on diabetes. Digital diabetes self-management education for patients has been shown to improve patients’ knowledge and outcomes. However, the effectiveness of digital education on diabetes management for health care professionals is still unknown. OBJECTIVE The objective of this study was to assess the effectiveness and economic impact of digital education in improving health care professionals’ knowledge, skills, attitudes, satisfaction, and competencies. We also assessed its impact on patient outcomes and health care professionals’ behavior. METHODS We included randomized controlled trials evaluating the impact of digitalized diabetes management education for health care professionals pre- and postregistration. Publications from 1990 to 2017 were searched in MEDLINE, EMBASE, Cochrane Library, PsycINFO, CINAHL, ERIC, and Web of Science. Screening, data extraction and risk of bias assessment were conducted independently by 2 authors. RESULTS A total of 12 studies met the inclusion criteria. Studies were heterogeneous in terms of digital education modality, comparators, outcome measures, and intervention duration. Most studies comparing digital or blended education to traditional education reported significantly higher knowledge and skills scores in the intervention group. There was little or no between-group difference in patient outcomes or economic impact. Most studies were judged at a high or unclear risk of bias. CONCLUSIONS Digital education seems to be more effective than traditional education in improving diabetes management–related knowledge and skills. The paucity and low quality of the available evidence call for urgent and well-designed studies focusing on important outcomes such as health care professionals’ behavior, patient outcomes, and cost-effectiveness as well as its impact in diverse settings, including developing countries.

Background We assessed the number, proportion, and clinical relevance of diabetes self-management apps in major languages spoken by 10 countries with the highest number of people with diabetes. Methods China, India, USA, Brazil, Russian Federation, Mexico, Indonesia, Egypt, Japan, and Pakistan were identified as the 10 countries with the largest number of people with diabetes based on the latest NCD-RisC survey. Android and iOS apps in the 10 national languages were extracted with a search strategy. App titles and descriptions were systematically screened by trained reviewers, including apps specific for diabetes self-management and excluding apps for health care providers, general well-being, health and product promotion, and traditional cure. Eighteen apps in the above languages were then downloaded based on availability and popularity and assessed for clinical relevance to diabetes self-management with reference to current clinical guidelines. Results The diabetes-related search terms identified 3374 Android and 4477 iOS apps, where 1019 Android and 1303 iOS apps were screened as being relevant for diabetes self-management. Chinese and English language apps constitute above 80% of the diabetes apps, have more downloads, and more comprehensive clinically relevant functions compared with other languages. None of the apps assessed met all criteria for information provision and app functionalities nor provided information cited from accredited sources. Conclusions Our study showed that apps could play an important role in complementing multifaceted diabetes care, but should preferably be regulated, context specific, and more tailored to users' needs with clear guidance for patients and clinicians about the choices.

We discuss the nursing intervention of nonstop minimally invasive tricuspid valve forming with simultaneous atrial flutter after secondary cardiac surgery. Patient is a 50-years-old male who undergoing repair of atrial septal defect by central thoracotomy with extracorporeal circulation as atrial septal defect in the 30 years ago require repair of atrial septal defect by central thoracotomy with extracorporeal circulation again as residual shunt after repair. In patient checking report of January 2019, it indicated that in the case of no obvious inducement patients appear palpitation, palpitation, is persistent. Base on admission dynamic electrocardiogram, it indicated: (1) Persistent atrial flutter (2) second degree atrioventricular block with junctional escape (3) severe tricuspid regurgitation. In result of operation, we successfully completed the operation, and the patient had no complications after the operation. The surgical procedure was to perform electrophysiological mapping of the right atrium, establish extracorporeal circulation, surgical bipolar radiofrequency ablation, and tricuspid valve formation. Base on result of this operation, effective implementation of prospective nursing interventions can reduce the risk of surgery. In addition, in operation process, as the operation involves a large number of instruments and equipment and surgical personnel, the position of equipment and the rationality of personnel station will influence the result of operation.

In 2018, an estimated 7.8% of individuals with diabetes who owned a smartphone used a diabetes app to support self-management.1 A meta-analysis found that using an app supporting blood glucose self-management was associated with a hemoglobin A1c (HbA1c) reduction of 0.5%.2 As most diabetes apps fall outside US Food and Drug Administration regulation, intended effect and clinical safety are not ensured.3 Previous studies of diabetes apps described features, privacy and security, and usability.4 This study analyzed key management features, namely decision support and alerts for self-management of blood glucose in type 2 diabetes.

Background: There is a shortage of health care professionals competent in diabetes management worldwide. Digital education is increasingly used in educating health professionals on diabetes. Digital diabetes self-management education for patients has been shown to improve patients’ knowledge and outcomes. However, the effectiveness of digital education on diabetes management for health care professionals is still unknown. Objective: The objective of this study was to assess the effectiveness and economic impact of digital education in improving health care professionals’ knowledge, skills, attitudes, satisfaction, and competencies. We also assessed its impact on patient outcomes and health care professionals’ behavior. Methods: We included randomized controlled trials evaluating the impact of digitalized diabetes management education for health care professionals pre- and postregistration. Publications from 1990 to 2017 were searched in MEDLINE, EMBASE, Cochrane Library, PsycINFO, CINAHL, ERIC, and Web of Science. Screening, data extraction and risk of bias assessment were conducted independently by 2 authors. Results: A total of 12 studies met the inclusion criteria. Studies were heterogeneous in terms of digital education modality, comparators, outcome measures, and intervention duration. Most studies comparing digital or blended education to traditional education reported significantly higher knowledge and skills scores in the intervention group. There was little or no between-group difference in patient outcomes or economic impact. Most studies were judged at a high or unclear risk of bias. Conclusions: Digital education seems to be more effective than traditional education in improving diabetes management–related knowledge and skills. The paucity and low quality of the available evidence call for urgent and well-designed studies focusing on important outcomes such as health care professionals’ behavior, patient outcomes, and cost-effectiveness as well as its impact in diverse settings, including developing countries. Published version

BackgroundGlobally, healthcare systems face major challenges with medicines management and medication adherence. Medication adherence determines medication effectiveness and can be the single most effective intervention for improving health outcomes. In anticipation of growth in eHealth interventions worldwide, we explore the role of eHealth in the patients’ medicines management journey in primary care, focusing on personalisation and intelligent monitoring for greater adherence.DiscussioneHealth offers opportunities to transform every step of the patient’s medicines management journey. From booking appointments, consultation with a healthcare professional, decision-making, medication dispensing, carer support, information acquisition and monitoring, to learning about medicines and their management in daily life. It has the potential to support personalisation and monitoring and thus lead to better adherence. For some of these dimensions, such as supporting decision-making and providing reminders and prompts, evidence is stronger, but for many others more rigorous research is urgently needed.ConclusionsGiven the potential benefits and barriers to eHealth in medicines management, a fine balance needs to be established between evidence-based integration of technologies and constructive experimentation that could lead to a game-changing breakthrough. A concerted, transdisciplinary approach adapted to different contexts, including low- and middle-income contries is required to realise the benefits of eHealth at scale.