Support Health Care Professionals Research Articles

Supporting healthcare professionals from ethnic minority backgrounds to ‘Step Into’ a clinical academic career

Supporting healthcare professionals from ethnic minority backgrounds to ‘Step Into’ a clinical academic career

Commentary: Supporting healthcare professionals from ethnic minority backgrounds to ‘Step Into’ a clinical academic career

Commentary: Supporting healthcare professionals from ethnic minority backgrounds to ‘Step Into’ a clinical academic career

Cardiovascular disease risk assessment in patients with rheumatoid arthritis: A scoping review.

Patients with rheumatoid arthritis (RA) have an increased risk of developing cardiovascular disease (CVD). Identification of at-risk patients is paramount to initiate preventive care and tailor treatments accordingly. Despite international guidelines recommending all patients with RA undergo CVD risk assessment, rates remain suboptimal. The objectives of this review were to map the strategies used to conduct CVD risk assessments in patients with RA in routine care, determine who delivers CVD risk assessments, and identify what composite measures are used. The Joanna Briggs Institute methodological guidelines were used. A literature search was conducted in electronic and grey literature databases, trial registries, medical clearing houses, and professional rheumatology organisations. Findings were synthesised narratively. A total of 12 studies were included. Strategies reported in this review used various system-based interventions to support delivery of CVD risk assessments in patients with RA, operationalised in different ways, adopting two approaches: (a) multidisciplinary collaboration, and (b) education. Various composite measures were cited in use, with and without adjustment for RA. Results from this review demonstrate that although several strategies to support CVD risk assessments in patients with RA are cited in the literature, there is limited evidence to suggest a standardised model has been applied to routine care. Furthermore, extensive evidence to map how health care professionals conduct CVD risk assessments in practice is lacking. Research needs to be undertaken to establish the extent to which healthcare professionals are CVD risk assessing their patients with RA in routine care. Key Points • A limited number of system-based interventions are in use to support the delivery of CVD risk assessments in patients with RA. • Multidisciplinary team collaboration, and education are used to operationalise interventions to support Health Care Professionals in conducting CVD risk assessments in practice. • The extent to which Health Care Professionals are CVD risk assessing their patients with RA needs to be established.

Large Language Models and User Trust: Consequence of Self-Referential Learning Loop and the Deskilling of Health Care Professionals.

As the health care industry increasingly embraces large language models (LLMs), understanding the consequence of this integration becomes crucial for maximizing benefits while mitigating potential pitfalls. This paper explores the evolving relationship among clinician trust in LLMs, the transition of data sources from predominantly human-generated to artificial intelligence (AI)-generated content, and the subsequent impact on the performance of LLMs and clinician competence. One of the primary concerns identified in this paper is the LLMs' self-referential learning loops, where AI-generated content feeds into the learning algorithms, threatening the diversity of the data pool, potentially entrenching biases, and reducing the efficacy of LLMs. While theoretical at this stage, this feedback loop poses a significant challenge as the integration of LLMs in health care deepens, emphasizing the need for proactive dialogue and strategic measures to ensure the safe and effective use of LLM technology. Another key takeaway from our investigation is the role of user expertise and the necessity for a discerning approach to trusting and validating LLM outputs. The paper highlights how expert users, particularly clinicians, can leverage LLMs to enhance productivity by off-loading routine tasks while maintaining a critical oversight to identify and correct potential inaccuracies in AI-generated content. This balance of trust and skepticism is vital for ensuring that LLMs augment rather than undermine the quality of patient care. We also discuss the risks associated with the deskilling of health care professionals. Frequent reliance on LLMs for critical tasks could result in a decline in health care providers' diagnostic and thinking skills, particularly affecting the training and development of future professionals. The legal and ethical considerations surrounding the deployment of LLMs in health care are also examined. We discuss the medicolegal challenges, including liability in cases of erroneous diagnoses or treatment advice generated by LLMs. The paper references recent legislative efforts, such as The Algorithmic Accountability Act of 2023, as crucial steps toward establishing a framework for the ethical and responsible use of AI-based technologies in health care. In conclusion, this paper advocates for a strategic approach to integrating LLMs into health care. By emphasizing the importance of maintaining clinician expertise, fostering critical engagement with LLM outputs, and navigating the legal and ethical landscape, we can ensure that LLMs serve as valuable tools in enhancing patient care and supporting health care professionals. This approach addresses the immediate challenges posed by integrating LLMs and sets a foundation for their maintainable and responsible use in the future.

Improving supportive, palliative and end of life care for teenagers and young adults with cancer in adult haematology services.

Adolescents with haematological malignancies within adult services, in the UK from 16years old, have unique needs and require developmentally targeted services and approaches to care delivery. High-risk intensive treatments are common for this cohort and a better understanding of what individualised supportive and palliative care means in this context is required. Being known and understood as an emerging adult, with particular recognition of developmental stage, is an essential component of quality measures and underpins the adolescent, and caregiver, experience when faced with an uncertain or poor cancer prognosis (UPCP). Healthcare professionals (HCPs) can experience increased emotional labour and feelings of professional inadequacy when caring for adolescents with UPCP. Therapeutic alliance improves HCPs understanding of optimum individualised care by improving communication and supported decision making. Access to training and support for HCPs is required to address the emotional impact of therapeutic alliance with teenage/adolescent and young adults (T/AYAs) with advanced cancer. Investment in therapeutic alliance, alongside robust support mechanisms and targeted training, can improve the skills, confidence and wellbeing for HCPs, and can also ensure optimum individualised care for T/AYAs with UPCP. Evidence for optimum care for adolescents with advanced cancer is relatively scarce, especially for younger T/AYAs (16-24) in the UK who sit within adult services. Further evaluation of the impact of current UK expertise, services and programs are needed to inform future development.

Miniature mass spectrometer-based point-of-care assay for quantification of metformin and sitagliptin in human blood and urine.

Metformin (MET) and sitagliptin (STG) are widely used as the first-line and long-term oral hypoglycemic agents for managing type 2 diabetes mellitus (T2DM). However, the current lack of convenient and rapid measurement methods poses a challenge for individualized management. This study developed a point-of-care (POC) assay method utilizing a miniature mass spectrometer, enabling rapid and accurate quantification of MET and STG concentrations in human blood and urine. By combining the miniature mass spectrometer with paper spray ionization, this method simplifies the process into three to four steps, requires minimal amounts of bodily fluids (50 μL of blood and 2 μL of urine), and is able to obtain quantification results within approximately 2min. Stable isotope-labeled internal standards were employed to enhance the accuracy and stability of measurement. The MS/MS responses exhibited good linear relationship with concentration, with relative standard deviations (RSDs) below 25%. It has the potential to provide immediate treatment feedback and decision support for patients and healthcare professionals in clinical practice.

Stories of social and emotional resilience among pregnant Bangladeshi and Sri Lankan migrant women during COVID-19 lockdowns in Victoria, Australia: A qualitative study using photo-elicitation.

The COVID-19 pandemic disrupted family and community support systems that typically nurture pregnancy and birth experiences of migrant Bangladeshi and Sri Lankan women in Australia. Very little is known about how COVID-19 lockdown measures impacted Bangladeshi and Sri Lankan pregnant women living in Australia during the pandemic. Using an intersectional and resilience thinking approach, we explored the social and emotional resilience of Bangladeshi and Sri Lankan pregnant women living in Victoria, Australia during COVID-19 lockdowns. Semi-structured photo-elicitation interviews were conducted in English, Tamil and Bangla and audio-recorded in-person and virtually. Inductive thematic analysis was used to analyse the visual and oral qualitative data produced. Twenty-five Bangladeshi and Sri Lankan-born women were interviewed. Three key themes emerged from data analysis: challenges exacerbated by COVID-19, sources of social resilience, and sources of emotional resilience. Participants were negatively impacted by closed international borders, care for children, financial pressures of temporary residence and their physical and mental health was impacted. Primary sources of social resilience were derived from family, community and healthcare professional support. Photo data produced by participants depicted patterns of emotional resilience to overcome the challenges of social isolation during their pregnancy in lockdown. The visual and oral data highlighted that participants were significantly impacted by social isolation during COVID-19 lockdowns in Australia. Findings from this study can contribute to understanding how social support networks influence maternity during a pandemic and how culturally safe maternal health practices can be reinforced to support the motherhood of migrant women regardless of visa status.

Supporting Healthcare Professionals in Clinical Practice

Supporting Healthcare Professionals in Clinical Practice

The social and healthcare professional support drawn upon by women antenatally during the COVID-19 pandemic: A recurrent, cross-sectional, thematic analysis

ObjectiveTo explore antenatal experiences of social and healthcare professional support during different phases of social distancing restriction implementation in the UK. DesignSemi-structured interviews were conducted via telephone or video-conferencing software between 13 July 2020 – 2 September 2020. Interviews were transcribed and a recurrent, cross-sectional, thematic analysis was conducted. ParticipantsTwelve antenatal women were interviewed during UK social distancing restrictions (Timepoint 1; T1) and a separate sample of twelve women were interviewed in the initial easing of these restrictions (Timepoint 2; T2). FindingsT1 themes were: ‘Maternity care as non-essential’ and ‘Pregnancy is cancelled’. T2 themes were: ‘Technology is a polarised tool’ and ‘Clinically vulnerable, or not clinically vulnerable? That is the question’. Key conclusionsAt T1, anxieties were ascribed to the exclusion of partners from routine care, and to perceived insensitivity and aggression from the public. For T2, insufficient Governmental transparency led to disillusionment, confusion, and anger. Covert workplace discrimination also caused distress at T2. Across timepoints: deteriorated mental wellbeing was attributed to depleted opportunities to interact socially and scaled back maternity care. Implications for practiceRecommendations are made to: protect maternal autonomy; improve quality of mental health and routine care signposting; prioritise parental community support in the re-opening of ‘non-essential’ services; prioritise the option for face-to-face appointments when safe and legal; and protecting the rights of working mothers.

Health sciences librarians' instructional engagement in continuing education: a scoping review.

Healthcare professionals (HCPs) have an ongoing need for continuing education (CE) while Health Science Librarians (HSLs), accustomed to supporting a range of learning needs in a variety of contexts, are well situated to provide CE that addresses information retrieval, literacy, management, and more. To better understand the extent of HSL delivered CE activities, we undertook a scoping review to determine how HSLs instruct practicing HCPs in support of their CE. We searched for published and unpublished literature sources including PubMed (NCBI), Embase (Elsevier); Dissertations and Theses Global (ProQuest); CINAHL (EBSCO); Library, Information Science and Technology Abstracts (EBSCO); and Library Literature and Information Science Full Text (EBSCO). To identify unpublished sources, we searched the internet using Google and contacted two health sciences library listservs. We also performed backwards and forwards searching of our included sources. Our database searches yielded 4842 sources, and we retrieved an additional 579 sources through supplementary retrieval methods. After duplicate removal and screening, we included 105 sources in this review. The included sources were published between 1970 to 2021 and covered a range of topics such as searching methods and tools, critical appraisal, and many more. Those related to evidence-based practice (EBP) appeared around 2001 and bibliometrics and bioinformatics arose after 2016. Publications depicting HSLs teaching CE most commonly occurred in academic settings. The most common population taught was nurses, followed by physicians. Most sources did not report using an information literacy framework or instructional design model, undertaking needs assessments, or reporting formal objectives or assessment. While HSLs are active supporters of EBP, we need to apply the same principles to our own professional practice. Formal structure of programming and program assessment combined with clear, detailed reporting can help to build a more robust evidence base to support future CE provision.

Machine Learning First Response to COVID-19: A Systematic Literature Review of Clinical Decision Assistance Approaches during Pandemic Years from 2020 to 2022

Background: The declaration of the COVID-19 pandemic triggered global efforts to control and manage the virus impact. Scientists and researchers have been strongly involved in developing effective strategies that can help policy makers and healthcare systems both to monitor the spread and to mitigate the impact of the COVID-19 pandemic. Machine Learning (ML) and Artificial Intelligence (AI) have been applied in several fronts of the fight. Foremost is diagnostic assistance, encompassing patient triage, prediction of ICU admission and mortality, identification of mortality risk factors, and discovering treatment drugs and vaccines. Objective: This systematic review aims to identify original research studies involving actual patient data to construct ML- and AI-based models for clinical decision support for early response during the pandemic years. Methods: Following the PRISMA methodology, two large academic research publication indexing databases were searched to investigate the use of ML-based technologies and their applications in healthcare to combat the COVID-19 pandemic. Results: The literature search returned more than 1000 papers; 220 were selected according to specific criteria. The selected studies illustrate the usefulness of ML with respect to supporting healthcare professionals for (1) triage of patients depending on disease severity, (2) predicting admission to hospital or Intensive Care Units (ICUs), (3) search for new or repurposed treatments and (4) the identification of mortality risk factors. Conclusion: The ML/AI research community was able to propose and develop a wide variety of solutions for predicting mortality, hospitalizations and treatment recommendations for patients with COVID-19 diagnostic, opening the door for further integration of ML in clinical practices fighting this and forecoming pandemics. However, the translation to the clinical practice is impeded by the heterogeneity of both the datasets and the methodological and computational approaches. The literature lacks robust model validations supporting this desired translation.

Empowering Second Victims: Supporting Healthcare Professionals after Adverse Health Events

Purpose: This essay provides a comprehensive analysis of support programs for healthcare professionals following an adverse health event. Through the use of electronic health records, health information exchange, and interoperability with data standards, these programs aim to address the effects on second victims.
 Methodology: The methodology utilized includes a thorough review of the literature on the topic and presents key findings and implications for future research.
 Findings: Overall, these results highlight the importance of supporting healthcare professionals to improve patient outcomes and minimize negative impacts within the healthcare system.
 Unique contribution to theory, policy and practice: As healthcare evolves ceaselessly, we must cultivate an environment where the shaken can recover their footing. Collaborative efforts and advances can weave together a support structure sturdy enough to hold up all harmed by mishaps as second victims.

Rewiring care delivery through Digital Therapeutics (DTx): a machine learning-enhanced assessment and development (M-LEAD) framework

BackgroundDigital transformation has sparked profound change in the healthcare sector through the development of innovative digital technologies. Digital Therapeutics offer an innovative approach to disease management and treatment. Care delivery is increasingly patient-centered, data-driven, and based on real-time information. These technological innovations can lead to better patient outcomes and support for healthcare professionals, also considering resource scarcity. As these digital technologies continue to evolve, the healthcare field must be ready to integrate them into processes to take advantage of their benefits. This study aims to develop a framework for the development and assessment of Digital Therapeutics.MethodsThe study was conducted relying on a mixed methodology. 338 studies about Digital Therapeutics resulting from a systematic literature review were analyzed using descriptive statistics through RStudio. Machine learning algorithms were applied to analyze variables and find patterns in the data. The results of these analytical analyses were summarized in a framework qualitatively tested and validated through expert opinion elicitation.ResultsThe research provides M-LEAD, a Machine Learning-Enhanced Assessment and Development framework that recommends best practices for developing and assessing Digital Therapeutics. The framework takes as input Digital Therapeutics characteristics, regulatory aspects, study purpose, and assessment domains. The framework produces as outputs recommendations to design the Digital Therapeutics study characteristics.ConclusionsThe framework constitutes the first step toward standardized guidelines for the development and assessment of Digital Therapeutics. The results may support manufacturers and inform decision-makers of the relevant results of the Digital Therapeutics assessment.

Causes and Ways of Death in Patients With Head and Neck Cancer

There is limited literature on the exact causes and ways of death in patients with head and neck cancer. To provide optimal care, especially in the palliative phase, more information on this is needed. To provide insights into the causes and ways of death among patients with head and neck cancer. This retrospective cohort study included a consecutive population of patients who received a diagnosis of primary squamous cell carcinoma of the head and neck between January 2006 and December 2013 who were treated in the Erasmus MC. Patient data were merged with nonpublic microdata from Statistics Netherlands. Follow-up time was specified as the date of diagnosis until death or December 3, 2019, whichever came first. The data were checked and reanalyzed in November 2023. Causes (eg, head and neck cancer, other cancer) and ways (eg, natural death, suicide) of death. A total of 1291 patients (59.2%; 342 women [26.5%]) died during follow-up (median [IQR] follow-up, 2.7 [1.2-5.6] years). The main cause of death was head and neck cancer (557 [43.1%]), followed by the competing cause of other cancers (344 [26.6%]). In total, 240 patients (18.6%) received palliative sedation and 70 patients (5.4%) euthanasia. Compared with patients with head and neck cancer as the underlying cause of death, lower odds ratios (ORs) were observed for receiving palliative sedation (OR, 0.32 vs 0.07; 95% CI, 0.22-0.46 vs 0.03-0.12) and euthanasia (OR, 0.22 vs 0.01; 95% CI, 0.11-0.41 vs 0-0.107) in patients with other causes of death. Patients with a middle and high income had higher ORs for receiving palliative sedation (OR, 1.46 vs 1.86; 95% CI, 1.05-2.04 vs 1.22-2.85) or euthanasia (OR, 2.25 vs 3.37; 95% CI, 1.18-4.3, 1.6-7.12) compared with low-income patients. Retired patients had lower ORs for receiving palliative sedation or euthanasia compared with employed patients (OR, 0.56 vs 0.44; 95% CI, 0.39-0.8 vs 0.24-0.82). The results of this cohort study suggest that more than half of the patients died of competing causes and palliative sedation and euthanasia were more common in patients with head and neck cancer as the underlying cause of death. Patients with a higher socioeconomic status had higher odds of receiving palliative sedation and euthanasia. These insights may support health care professionals in providing patient-centered care, especially for patients in the palliative phase.

Enabling personalised disease diagnosis by combining a patient’s time-specific gene expression profile with a biomedical knowledge base

BackgroundRecent developments in the domain of biomedical knowledge bases (KBs) open up new ways to exploit biomedical knowledge that is available in the form of KBs. Significant work has been done in the direction of biomedical KB creation and KB completion, specifically, those having gene-disease associations and other related entities. However, the use of such biomedical KBs in combination with patients’ temporal clinical data still largely remains unexplored, but has the potential to immensely benefit medical diagnostic decision support systems.ResultsWe propose two new algorithms, LOADDx and SCADDx, to combine a patient’s gene expression data with gene-disease association and other related information available in the form of a KB, to assist personalized disease diagnosis. We have tested both of the algorithms on two KBs and on four real-world gene expression datasets of respiratory viral infection caused by Influenza-like viruses of 19 subtypes. We also compare the performance of proposed algorithms with that of five existing state-of-the-art machine learning algorithms (k-NN, Random Forest, XGBoost, Linear SVM, and SVM with RBF Kernel) using two validation approaches: LOOCV and a single internal validation set. Both SCADDx and LOADDx outperform the existing algorithms when evaluated with both validation approaches. SCADDx is able to detect infections with up to 100% accuracy in the cases of Datasets 2 and 3. Overall, SCADDx and LOADDx are able to detect an infection within 72 h of infection with 91.38% and 92.66% average accuracy respectively considering all four datasets, whereas XGBoost, which performed best among the existing machine learning algorithms, can detect the infection with only 86.43% accuracy on an average.ConclusionsWe demonstrate how our novel idea of using the most and least differentially expressed genes in combination with a KB can enable identification of the diseases that a patient is most likely to have at a particular time, from a KB with thousands of diseases. Moreover, the proposed algorithms can provide a short ranked list of the most likely diseases for each patient along with their most affected genes, and other entities linked with them in the KB, which can support health care professionals in their decision-making.

Primary care provision for young people with ADHD: a multi-perspective qualitative study.

Attention deficit hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder. UK guidance states that primary care has a vital role in effective ADHD management, including referral, medication prescribing and monitoring, and providing broader mental health and wellbeing support. However, many GPs feel unsupported to provide health care for young people with ADHD. Inadequate health care is associated with rising costs for patients and society. To investigate the experiences of young people with ADHD accessing primary care in England, from the perspectives of people with lived experience of ADHD and healthcare professionals (HCPs). A qualitative study. Interviews were conducted with HCPs (GPs, practice managers, and a wellbeing worker) and people with lived experience of ADHD (young people aged 16-25 years and their supporters) located in integrated care systems across England. Semi-structured interviews were conducted with participants at five purposively selected general practices (varying by deprivation, ethnicity, and setting). Questions focused on experiences of accessing/providing health care for ADHD. Reflexive thematic analysis was undertaken within a critical realist framework to understand how provision works in practice and to explore potential improvements. In total, 20 interviews were completed with 11 HCPs and nine people with lived experience. Three themes were generated: a system under stress, incompatibility between ADHD and the healthcare system, and strategies for change in ADHD primary care provision. Standardisation of ADHD management in primary care, providing better information and support for HCPs, and advising on reasonable adjustments for people with lived experience could help improve access to effective treatments for young people living with ADHD.

'Do I cry or just carry on': A story completion study of healthcare professionals' anticipated responses to experiencing chest pain.

Healthcare professionals may experience barriers to seeking healthcare that differ from the general population. We explored healthcare professionals' anticipated responses to experiencing chest pain following a period of stress using qualitative story completion method with healthcare professionals (n = 44). Data were analysed using reflexive thematic analysis, which identified three themes: '"Do I cry or just carry on?": A Culture of Suffering in Silence' identified worries that expressing health concerns would be perceived as weakness, with potential impact on career opportunities. Participants also described self-diagnosis and self-medication rather than help-seeking. '"Me? Have a panic attack?": Psychosomatic Shame' suggested mental health issues may be ignored due to stigma. '"We definitely don't take care of ourselves": Prioritising Pressures of Multiple Responsibilities over Self-care' identified real or perceived pressures to de-prioritise their health. Future research should explore the design of confidential, time efficient support for healthcare professionals that tackle cultural norms and barriers to self-care.

Expert United Kingdom consensus on the preservation of joint health in people with moderate and severe haemophilia A: A modified Delphi panel.

For people with haemophilia A (PwHA), bleeding in the joints leads to joint damage and haemophilia-related arthropathy, impacting range of motion and life expectancy. Existing guidelines for managing haemophilia A support healthcare professionals (HCPs) and PwHA in their efforts to preserve joint health. However, such guidance should be reviewed, considering emerging evidence and consensus as presented in this manuscript. Fifteen HCPs experienced in the management of PwHA in the UK participated in a three-round Delphi panel. Consensus was defined at ≥70% of panellists agreeing or disagreeing for Likert-scale questions, and ≥70% selecting the same option for multiple- or single-choice questions. Questions not reaching consensus were revised for the next round. 26.8% (11/41), 44.8% (13/29) and 93.3% (14/15) of statements reached consensus in Rounds 1, 2 and 3, respectively. HCPs agreed that prophylaxis should be offered to patients with a baseline factor VIII (FVIII) level of ≤5 IU/dL and that, where there is no treatment burden, the aim of prophylaxis should be to achieve a trough FVIII level ≥15 IU/dL and maintain a longer period with FVIII levels of ≥20-30 IU/dL to provide better bleed protection. The aspirational goal for PwHA is to prevent all joint bleeds, which may be achieved by maintaining normalised (50-150 IU/dL) FVIII levels. The panel of experts were largely aligned on approaches to preserving joint health in PwHA, and this consensus may help guide HCPs.

How to Support Health Care Professionals in Emergencies

ABSTRACT In recurring emergencies, frontline health care professionals (HCPs) have taken on a dual responsibility of not only serving as medical professionals for patients but also disseminating medical knowledge online for the public to alleviate their anxiety. They are expected to perform both online and offline organizational citizenship behavior (OCB). However, HCPs carry out their duties with high risks, inhibiting their OCB. This study aims to understand how to effectively and efficiently integrate online and offline support to facilitate HCP’s online and offline OCB in recurring emergencies. Data was collected from a survey among HCPs amid the second wave of the COVID-19 pandemic from March to April 2021. It was found that perceived support helps promote HCPs’ OCB through increasing optimism and resilience. Moreover, offline problem-focused support is more helpful than online emotion-focused support for HCPs with more knowledge of the emergency.

Effects of Digitization of Self-Monitoring of Blood Glucose Records Using a Mobile App and the Cloud System on Outpatient Management of Diabetes: Single-Armed Prospective Study.

In recent years, technologies promoting the digitization of self-monitoring of blood glucose (SMBG) records including app-cloud cooperation systems have emerged. Studies combining these technological interventions with support from remote health care professionals have reported improvements in glycemic control. To assess the use of an app-cloud cooperation system linked with SMBG devices in clinical settings, we evaluated its effects on outpatient management of diabetes without remote health care professional support. In this multicenter, open-label, and single-armed prospective study, 48 patients with diabetes (including type 1 and type 2) at 3 hospitals in Japan treated with insulin or glucagon-like peptide 1 receptor agonists and performing SMBG used the app-cloud cooperation system for 24 weeks. The SMBG data were automatically uploaded to the cloud via the app. The patients could check their data, and their attending physicians reviewed the data through the cloud prior to the patients' regular visits. The primary outcome was changes in glycated hemoglobin (HbA1c) levels. Although HbA1c levels did not significantly change in all patients, the frequency of daily SMBG following applying the system was significantly increased before induction at 12 (0.60 per day, 95% CI 0.19-1.00; P=.002) and 24 weeks (0.43 per day, 95% CI 0.02-0.84; P=.04). In the subset of 21 patients whose antidiabetic medication had not been adjusted during the intervention period, a decrease in HbA1c level was observed at 12weeks (P=.02); however, this significant change disappeared at 24 weeks (P=.49). The Diabetes Treatment Satisfaction Questionnaire total score and "Q4: convenience" and "Q5: flexibility" scores significantly improved after using the system (all P<.05), and 72% (33/46) patients and 76% (35/46) physicians reported that the app-cloud cooperation system helped them adjust insulin doses. The digitization of SMBG records and sharing of the data by patients and attending physicians during face-to-face visits improved self-management in patients with diabetes. Japan Registry of Clinical Trials (jRCT) jRCTs042190057; https://jrct.niph.go.jp/en-latest-detail/jRCTs042190057.