Robust identification of environmental exposures and community characteristics predictive of rapid lung disease progression.

Environmental exposures and community characteristics have been linked to accelerated lung function decline in people with cystic fibrosis (CF), but geomarkers, the measurements of these exposures, have not been comprehensively evaluated in a single study. To determine which geomarkers have the greatest predictive potential for lung function decline and pulmonary exacerbation (PEx), a retrospective longitudinal cohort study was performed using novel Bayesian joint covariate selection methods, which were compared with respect to PEx predictive accuracy. Non-stationary Gaussian linear mixed effects models were fitted to data from 151 CF patients aged 6-20 receiving care at a CF Center in the midwestern US (2007-2017). The outcome was forced expiratory volume in 1 s of percent predicted (FEV1pp). Target functions were used to predict PEx from established criteria. Covariates included 11 routinely collected clinical/demographic characteristics and 45 geomarkers comprising 8 categories. Unique covariate selections via four Bayesian penalized regression models (elastic-net, adaptive lasso, ridge, and lasso) were evaluated at both 95 % and 90 % credible intervals (CIs). Resultant models included one to 6 geomarkers (air temperature, percentage of tertiary roads outside urban areas, percentage of impervious nonroad outside urban areas, fine atmospheric particulate matter, fraction achieving high school graduation, and motor vehicle theft) representing weather, impervious descriptor, air pollution, socioeconomic status, and crime categories. Adaptive lasso had the lowest information criteria. For PEx predictive accuracy, covariate selection from the 95 % CI elastic-net had the highest area under the receiver-operating characteristic curve (mean ±â€¯standard deviation; 0.780 ±â€¯0.026) along with the 95 % CI ridge and lasso methods (0.780 ±â€¯0.027). The 95 % CI elastic-net had the highest sensitivity (0.773 ±â€¯0.083) while the 95 % CI adaptive lasso had the highest specificity (0.691 ±â€¯0.087), suggesting the need for different geomarker sets depending on monitoring goals. Surveillance of certain geomarkers embedded in prediction algorithms can be used in real-time warning systems for PEx onset.

Current status and future prospects of Chinese mobile apps for hypertension management.

OBJECTIVE: This study aimed to evaluate the current situation of Chinese mobile apps for hypertension management and explore patients' real requirements for app use, providing a theoretical basis for the future improvement of hypertension apps. METHODS: We reviewed hypertension management apps from mobile app platforms, and summarized their functional characteristics. In addition, we conducted an online survey among 1000 hypertensive patients, collected valid responses, and analyzed the feedback data. RESULTS: Forty hypertension management apps were analyzed, with 72.5% offering no more than six functions, indicating limited coverage of advanced and comprehensive functionalities. Among the 934 valid survey responses, patients emphasized four main functions in apps for hypertension management: long-term dynamic blood pressure monitoring, scientific lifestyle management, strict medication management and systematic health knowledge delivering. CONCLUSION: The existing hypertension management apps mainly serve as "Digital Health" tools with unclear clinical efficacy. The future development of these apps lies in how they transition to "Digital Therapeutics" solutions to better meet patients' needs and provide clear clinical advantages.

A Cross-Sectional Study of Health-Related Quality of Life in Patients with Predominantly Antibody Deficiency.

Health-related quality of life (HRQoL) measures individual well-being across physical, psychological, and social domains. Patients with predominantly antibody deficiency (PAD) are at risk for morbidity and mortality, however, the effect of these complications on HRQoL requires additional study. Patients with PAD were asked to voluntarily complete the Centers for Disease Control (CDC) HRQoL-14 Healthy Days Measure questionnaire. These results were compared to data from the CDC-initiated Behavioral Risk Factor Surveillance System (BRFSS), a cross-sectional questionnaire including questions from CDC-HRQOL-14. Statistical analyses included two-proportion Z-test, t-tests, and analysis of variance. 83 patients with PAD completed the survey. Patients were sub-stratified into mild (23.7%), moderate (35.5%), severe (40.8%), and secondary (8.4%) PAD. "Fair or poor" health status was reported in 52.6% of PAD patients. Mental health challenges ≥ 14 days/month occurred in 25% of patients. Physical health issues ≥ 14 days/month was reported in 44.7% of patients. Activity limitations were noted by 80.3% of patients. There were no statistically significant differences by PAD severity. Patients with autoimmune and inflammatory disease co-morbidities reported more mental health challenges compared to those without (78% vs. 54.3%, p = 0.02). Compared to the CDC-BRFSS data, significantly more patients with PAD reported "fair or poor" health status (53% vs 12.0%; p < 0.0001), mental health challenges (24.1% vs 14.7%; p = 0.02), and poor physical health (44.6% vs 8.0%; p < 0.0001). Patients with PAD had significantly reduced HRQoL compared to CDC-BRFSS respondents from a similar geographical region. Decreased HRQoL was prevalent across all PAD severity levels. Additional research is needed to improve HRQoL for patients with PAD.

Telehealth-Supported Exercise or Physical Activity Programs for Knee Osteoarthritis: Systematic Review and Meta-Analysis.

BACKGROUND: The integration of telehealth-supported programs in chronic disease management has become increasingly common. However, its effectiveness for individuals with knee osteoarthritis (KOA) remains unclear. OBJECTIVE: This study aimed to assess the effectiveness of telehealth-supported exercise or physical activity programs for individuals with KOA. METHODS: A comprehensive literature search encompassing Embase, MEDLINE, CENTRAL, Web of Science, PubMed, Scopus, PEDro, GreyNet, and medRxiv from inception to September 2023 was conducted to identify randomized controlled trials comparing telehealth-supported exercise or physical activity programs to a control condition for KOA. Data were extracted and qualitatively synthesized across eligible studies, and a meta-analysis was performed to evaluate the effects. The study was reported according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020. RESULTS: In total, 23 studies met eligibility criteria, with 20 included in the meta-analysis. Results showed that telehealth-supported exercise or physical activity programs reduced pain (g=-0.39; 95% CI -0.67 to -0.11; P<.001), improved physical activity (g=0.13; 95% CI 0.03-0.23; P=.01), and enhanced physical function (g=-0.51; 95% CI -0.98 to -0.05; P=.03). Moreover, significant improvements in quality of life (g=0.25; 95% CI 0.14-0.36; P<.001), self-efficacy for pain (g=0.72; 95% CI 0.53-0.91; P<.001), and global improvement (odds ratio 2.69, 95% CI 1.41-5.15; P<.001) were observed. However, self-efficacy for physical function (g=0.14; 95% CI -0.26 to 0.53; P=.50) showed insignificant improvements. Subgroup analyses based on the World Health Organization classification of digital health (pain: χ22=6.5; P=.04 and physical function: χ22=6.4; P=.04), the type of teletechnology in the intervention group (pain: χ24=4.8; P=.31 and function: χ24=13.0; P=.01), and active or inactive controls (pain: χ21=5.3; P=.02 and physical function: χ21=3.4; P=.07) showed significant subgroup differences. CONCLUSIONS: Telehealth-supported exercise or physical activity programs might reduce knee pain and improve physical activity, physical function, quality of life, self-efficacy, and global improvement in individuals with KOA. Future research should consider longer implementation durations and assess the feasibility of incorporating wearables and standardized components into large-scale interventions to evaluate the effects. TRIAL REGISTRATION: PROSPERO CRD42022359658; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=359658.

Randomised pilot study comparing a coach to SMARTPhone reminders to aid the management of heart failure (HF) patients: humans or machines.

Ambulatory management of congestive heart failure (HF) continues to be a challenging clinical problem. Recent studies have focused on the role of HF clinics, nurse practitioners and disease management programmes to reduce HF readmissions. This pilot study is a pragmatic factorial study comparing a coach intervention, a SMARTPHONE REMINDER system intervention and BOTH interventions combined to Treatment as USUAL (TAU). We determined that both modalities were acceptable to patients prior to randomisation. Fifty-four patients were randomised to the four groups. The COACH group had no readmissions for HF 6 months after enrolment compared with 18% for the SMARTPHONE REMINDER Group, 8% for the BOTH intervention group and 13% for TAU. Medium-to-high medication adherence was maintained in all four groups although sodium consumption was lower at 3 months for the COACH and combined (BOTH) groups. This pilot study suggests a beneficial effect on rehospitalisation with the use of support measures including coaches and telephone reminders that needs confirmation in a larger trial.

Impact of a Hospital-Based Food Pharmacy Program on Health Outcomes of Vulnerable Patients.

Access to healthy foods, especially for those who are living with diabetes and hypertension, is crucial in managing these chronic diseases. This study evaluates the implementation of a food pharmacy and food prescription program at a safety-net hospital that serves vulnerable populations. Patients who screen as food insecure using the USDA adult food security survey receive a referral from the physician to the food pharmacy program where a dietician reviews their dietary requirements based on their chronic disease and develops a diet plan. Patients then receive fresh produce, meats and other products every 2 weeks that meets their nutritional needs from the food pharmacy. Biometric data from the patient's most recent clinic visit at the time of enrollment was collected as the baseline measures including blood pressure, weight, and HbA1c (if diabetic). Additionally, biometric information was collected from the patient's medical records from regularly scheduled clinic visits at 6 month intervals. A total of 266 patients were enrolled in the program during the 13-month period that was studied (121 patients with 6-month data and 68 patients with 12-month data). The statistical analysis showed a significant improvement in diastolic blood pressure at 12 months and in weight at both the 6 months and 12 months timeframes when comparing to baseline biometrics.

Telemedicine in Improving Glycemic Control Among Children and Adolescents With Type 1 Diabetes Mellitus: Systematic Review and Meta-Analysis.

BACKGROUND: Type 1 diabetes mellitus (T1DM) is the most common chronic autoimmune disease among children and adolescents. Telemedicine has been widely used in the field of chronic disease management and can benefit patients with T1DM. However, existing studies lack high-level evidence related to the effectiveness of telemedicine for glycemic control in children and adolescents with T1DM. OBJECTIVE: This study aims to systematically review the evidence on the effectiveness of telemedicine interventions compared with usual care on glycemic control among children and adolescents with T1DM. METHODS: In this systematic review and meta-analysis, we searched PubMed, Cochrane Library, Embase, Web of Science (all databases), and CINAHL Complete from database inception to May 2023. We included randomized controlled trials (RCTs) that evaluated the effectiveness of a telemedicine intervention on glycemic control in children and adolescents with T1DM. In total, 2 independent reviewers performed the study selection and data extraction. Study quality was assessed using the Cochrane Risk of Bias 2 tool. Our primary outcome was glycated hemoglobin (HbA1c) levels. Secondary outcomes were quality of life, self-monitoring of blood glucose, the incidence of hypoglycemia, and cost-effectiveness. A random-effects model was used for this meta-analysis. RESULTS: Overall, 20 RCTs (1704 participants from 12 countries) were included in the meta-analysis. Only 5% (1/20) of the studies were at high risk of bias. Compared to usual care, telemedicine was found to reduce HbA1c levels by 0.22 (95% CI -0.33 to -0.10; P<.001; I2=35%). There was an improvement in self-monitoring of blood glucose (mean difference [MD] 0.54, 95% CI -0.72 to 1.80; P=.40; I2=67.8%) and the incidence of hypoglycemia (MD -0.15, 95% CI -0.57 to 0.27; P=.49; I2=70.7%), although this was not statistically significant. Moreover, telemedicine had no convincing effect on the Diabetes Quality of Life for Youth score (impact of diabetes: P=.59; worries about diabetes: P=.71; satisfaction with diabetes: P=.68), but there was a statistically significant improvement in non-youth-specific quality of life (MD -0.24, 95% CI -0.45 to -0.02; P=.04; I2=0%). Subgroup analyses revealed that the effect of telemedicine on HbA1c levels appeared to be greater in studies involving children (MD -0.41, 95% CI -0.62 to -0.20; P<.001), studies that lasted <6 months (MD -0.32, 95% CI -0.48 to -0.17; P<.001), studies where providers used smartphone apps to communicate with patients (MD -0.37, 95% CI -0.53 to -0.21; P<.001), and studies with medication dose adjustment (MD -0.25, 95% CI -0.37 to -0.12; P<.001). CONCLUSIONS: Telemedicine can reduce HbA1c levels and improve quality of life in children and adolescents with T1DM. Telemedicine should be regarded as a useful supplement to usual care to control HbA1c levels and a potentially cost-effective mode. Meanwhile, researchers should develop higher-quality RCTs using large samples that focus on hard clinical outcomes, cost-effectiveness, and quality of life.

Service development project to pilot a digital technology innovation for video direct observation of therapy in adult patients with asthma.

BACKGROUND: Adherence to pharmacotherapy and use of the correct inhaler technique are important basic principles of asthma management. Video- or remote-direct observation of therapy (v-DOT) could be a feasible approach to facilitate monitoring and supervising therapy, supporting the delivery of standard care. OBJECTIVE: To explore the utility and the feasibility of v-DOT to monitor inhaler technique and adherence to treatment in adults attending the asthma outpatient service in a tertiary hospital in Northern Ireland. METHOD: The project evaluated use of the technology with 10 asthma patients. Patient and clinician feedback was obtained, in addition to measures of patient engagement and disease-specific clinical markers to assess the feasibility and utility of v-DOT technology in this group of patients. RESULTS: The engagement rate with v-DOT for participating patients averaged 78% (actual video uploads vs expected video uploads) over a median 7 week usage period. Although 50% of patients reported a technical issue at some stage during the usage period, all patients and clinicians reported that the technology was easy to use and that they were satisfied with the outcomes. A range of positive impacts were observed, including optimised inhaler technique and an observed improvement in lung function. An increase in asthma control test scores aligned with clinical aims to promote adherence and alleviate symptoms. CONCLUSION: The v-DOT technology was shown to be a feasible method of assessing inhaler technique and monitoring adherence in this small group of adult asthma patients. A range of positive impacts for participating patients and clinicians were observed. Not all patients invited to join the project agreed to participate or engage with using the technology, highlighting that in this setting, digital modes of delivering care provide only one of the approaches in the necessary "tool kit" for clinicians and patients.

Compassionate Curiosity: Mitigating the Effects of Bias Through Motivational Interviewing.

There is strong evidence that the implicit biases of health care professionals affect the treatment of patients, and that minority and other marginalized patients are disproportionately harmed. Assumptions made about patient knowledge or lack thereof function as judgments that are prone to bias, which then affect the education and advice imposed upon patients. We review how the motivational interviewing (MI) approach to patient engagement includes components of evidence-based bias-mitigating strategies, such as understanding circumstances from the patient's point of view, and therefore we propose that the MI approach can reduce the impact of bias in patient care.

A Cross-Sectional Study of Health-Related Quality of Life in Patients with Predominantly Antibody Deficiency.

Health-related quality of life (HRQoL) measures individual well-being across physical, psychological, and social domains. Patients with predominantly antibody deficiency (PAD) are at risk for morbidity and mortality, however, the effect of these complications on HRQoL requires additional study. Patients with PAD were asked to voluntarily complete the Centers for Disease Control (CDC) HRQoL-14 Healthy Days Measure questionnaire. These results were compared to data from the CDC-initiated Behavioral Risk Factor Surveillance System (BRFSS), a cross-sectional questionnaire including questions from CDC-HRQOL-14. Statistical analyses included two-proportion Z-test, t-tests, and analysis of variance. 83 patients with PAD completed the survey. Patients were sub-stratified into mild (23.7%), moderate (35.5%), severe (40.8%), and secondary (8.4%) PAD. "Fair or poor" health status was reported in 52.6% of PAD patients. Mental health challenges ≥ 14 days/month occurred in 25% of patients. Physical health issues ≥ 14 days/month was reported in 44.7% of patients. Activity limitations were noted by 80.3% of patients. There were no statistically significant differences by PAD severity. Patients with autoinflammatory disease co-morbidities reported more mental health challenges compared to those without (78% vs. 54.3%, p = 0.02). Compared to the CDC-BRFSS data, significantly more patients with PAD reported "fair or poor" health status (53% vs 12.0%; p < 0.0001), mental health challenges (24.1% vs 14.7%; p = 0.02), and poor physical health (44.6% vs 8.0%; p < 0.0001). Patients with PAD had significantly reduced HRQoL compared to CDC-BRFSS respondents from a similar geographical region. Decreased HRQoL was prevalent across all PAD severity levels. Additional research is needed to improve HRQoL for patients with PAD.

AI Hesitancy and Acceptability-Perceptions of AI Chatbots for Chronic Health Management and Long COVID Support: Survey Study.

Background: Artificial intelligence (AI) chatbots have the potential to assist individuals with chronic health conditions by providing tailored information, monitoring symptoms, and offering mental health support. Despite their potential benefits, research on public attitudes toward health care chatbots is still limited. To effectively support individuals with long-term health conditions like long COVID (or post-COVID-19 condition), it is crucial to understand their perspectives and preferences regarding the use of AI chatbots. Objective: This study has two main objectives: (1) provide insights into AI chatbot acceptance among people with chronic health conditions, particularly adults older than 55 years and (2) explore the perceptions of using AI chatbots for health self-management and long COVID support. Methods: A web-based survey study was conducted between January and March 2023, specifically targeting individuals with diabetes and other chronic conditions. This particular population was chosen due to their potential awareness and ability to self-manage their condition. The survey aimed to capture data at multiple intervals, taking into consideration the public launch of ChatGPT, which could have potentially impacted public opinions during the project timeline. The survey received 1310 clicks and garnered 900 responses, resulting in a total of 888 usable data points. Results: Although past experience with chatbots (P<.001, 95% CI .110-.302) and online information seeking (P<.001, 95% CI .039-.084) are strong indicators of respondents' future adoption of health chatbots, they are in general skeptical or unsure about the use of AI chatbots for health care purposes. Less than one-third of the respondents (n=203, 30.1%) indicated that they were likely to use a health chatbot in the next 12 months if available. Most were uncertain about a chatbot's capability to provide accurate medical advice. However, people seemed more receptive to using voice-based chatbots for mental well-being, health data collection, and analysis. Half of the respondents with long COVID showed interest in using emotionally intelligent chatbots. Conclusions: AI hesitancy is not uniform across all health domains and user groups. Despite persistent AI hesitancy, there are promising opportunities for chatbots to offer support for chronic conditions in areas of lifestyle enhancement and mental well-being, potentially through voice-based user interfaces.

Leveraging Machine Learning to Develop Digital Engagement Phenotypes of Users in a Digital Diabetes Prevention Program: Evaluation Study.

BACKGROUND: Digital diabetes prevention programs (dDPPs) are effective "digital prescriptions" but have high attrition rates and program noncompletion. To address this, we developed a personalized automatic messaging system (PAMS) that leverages SMS text messaging and data integration into clinical workflows to increase dDPP engagement via enhanced patient-provider communication. Preliminary data showed positive results. However, further investigation is needed to determine how to optimize the tailoring of support technology such as PAMS based on a user's preferences to boost their dDPP engagement. OBJECTIVE: This study evaluates leveraging machine learning (ML) to develop digital engagement phenotypes of dDPP users and assess ML's accuracy in predicting engagement with dDPP activities. This research will be used in a PAMS optimization process to improve PAMS personalization by incorporating engagement prediction and digital phenotyping. This study aims (1) to prove the feasibility of using dDPP user-collected data to build an ML model that predicts engagement and contributes to identifying digital engagement phenotypes, (2) to describe methods for developing ML models with dDPP data sets and present preliminary results, and (3) to present preliminary data on user profiling based on ML model outputs. METHODS: Using the gradient-boosted forest model, we predicted engagement in 4 dDPP individual activities (physical activity, lessons, social activity, and weigh-ins) and general activity (engagement in any activity) based on previous short- and long-term activity in the app. The area under the receiver operating characteristic curve, the area under the precision-recall curve, and the Brier score metrics determined the performance of the model. Shapley values reflected the feature importance of the models and determined what variables informed user profiling through latent profile analysis. RESULTS: We developed 2 models using weekly and daily DPP data sets (328,821 and 704,242 records, respectively), which yielded predictive accuracies above 90%. Although both models were highly accurate, the daily model better fitted our research plan because it predicted daily changes in individual activities, which was crucial for creating the "digital phenotypes." To better understand the variables contributing to the model predictor, we calculated the Shapley values for both models to identify the features with the highest contribution to model fit; engagement with any activity in the dDPP in the last 7 days had the most predictive power. We profiled users with latent profile analysis after 2 weeks of engagement (Bayesian information criterion=-3222.46) with the dDPP and identified 6 profiles of users, including those with high engagement, minimal engagement, and attrition. CONCLUSIONS: Preliminary results demonstrate that applying ML methods with predicting power is an acceptable mechanism to tailor and optimize messaging interventions to support patient engagement and adherence to digital prescriptions. The results enable future optimization of our existing messaging platform and expansion of this methodology to other clinical domains. TRIAL REGISTRATION: ClinicalTrials.gov NCT04773834; https://www.clinicaltrials.gov/ct2/show/NCT04773834. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/26750.

Strategies for General Practitioners to Enhance Cancer Care: Insights from a Patient-Centered Questionnaire Survey in Southern China.

Background: The incidence of cancer is increasing, and cancer survivors are also growing exponentially. Cancer is defined as a new chronic disease. Nevertheless, the management of cancer in the form of chronic diseases in China is still in its infancy, without a standardized care model. Objective: This study aimed to explore the current status of management of cancer care from the patient's perspective. Methods: This cross-sectional study was a questionnaire survey of patients diagnosed with cancer, including information of the current situation of daily medical consultation, status of comorbidity, and expectations of seeking cancer care in future. Chi-square test and logistic regression analysis were used to explore the factors influencing patients' choice of cancer management mode. Results: A total of 200 cancer patients were included in the study. The majority (n = 150) of cancer patients chose an oncologist in a tertiary hospital for cancer care. Difficulty in registration (45%), time-consuming (34.5%), repeated examinations (34.5%) and different treatment opinions (12.0%) were the main difficulties they encountered currently during tertiary hospital visits. In community hospital, lack of trust in general practitioners (n = 33) and the necessary drugs or testing items in community hospitals (n = 47) were the main difficulties during their visits. Logistic regression analysis showed that male (OR = 2.737, 95% CI, 1.332-5.627, p = 0.006) and elderly patients (OR = 3.186, 95% CI, 1.172-8.661, p = 0.023) were more likely to choose general practitioners (GPs) in community hospitals. Twenty-nine (14.5%) patients hope to have an integrated multidisciplinary management in tertiary and community hospitals with the active participation of GPs for cancer care. Conclusion: Improving drug availability, equipment and quality of cancer care services can help to increase cancer patients' recognition of community hospital. In addition, the multidisciplinary management integrated tertiary hospitals and communities with the participation of GPs is a worth exploring mode that improves the management of cancer care.

Using the Translating Research into Practice framework to develop a diabetes prevention intervention in primary care: a mixed-methods study.

BACKGROUND: Pre-diabetes affects one-third of US adults and increases the risk of type 2 diabetes. Effective evidence-based interventions, such as the Diabetes Prevention Program, are available, but a gap remains in effectively translating and increasing uptake of these interventions into routine care. METHODS: We applied the Translating Research into Practice (TRiP) framework to guide three phases of intervention design and development for diabetes prevention: (1) summarise the evidence, (2) identify local barriers to implementation and (3) measure performance. In phase 1, we conducted a retrospective cohort analysis of linked electronic health record claims data to evaluate current practices in the management of pre-diabetes. In phase 2, we conducted in-depth interviews of 16 primary care physicians, 7 payor leaders and 31 patients to elicit common barriers and facilitators for diabetes prevention. In phase 3, using findings from phases 1 and 2, we developed the core elements of the intervention and performance measures to evaluate intervention uptake. RESULTS: In phase 1 (retrospective cohort analysis), we found few patients with pre-diabetes received diabetes prevention interventions. In phase 2 (stakeholder engagement), we identified common barriers to include a lack of knowledge about pre-diabetes among patients and about the Diabetes Prevention Program among clinicians. In phase 3 (intervention development), we developed the START Diabetes Prevention Clinical Pathway as a systematic change package to address barriers and facilitators identified in phases 1 and 2, performance measures and a toolkit of resources to support the intervention components. CONCLUSIONS: The TRiP framework supported the identification of evidence-based care practices for pre-diabetes and the development of a well-fitted, actionable intervention and implementation plan designed to increase treatment uptake for pre-diabetes in primary care settings. Our change package can be adapted and used by other health systems or clinics to target prevention of diabetes or other related chronic conditions.

Food prescribing in Canada: evidence, critiques and opportunities. / La prescription alimentaire au Canada : données probantes, critiques et possibilités.

INTRODUCTION: There is growing interest in food prescriptions, which leverage health care settings to provide patients access to healthy foods through vouchers or food boxes. In this commentary, we draw on our experiences and interest in food prescribing to provide a summary of the current evidence on this intervention model and critically assess its limitations and opportunities. RATIONALE: Food insecurity is an important determinant of health and is associated with compromised dietary adequacy, higher rates of chronic diseases, and higher health service utilization and costs. Aligning with recent discourse on social prescribing and "food is medicine" approaches, food prescribing can empower health care providers to link patients with supports to improve food access and limit barriers to healthy diets. Food prescribing has been shown to improve fruit and vegetable intake and household food insecurity, although impacts on health outcomes are inconclusive. Research on food prescribing in the Canadian context is limited and there is a need to establish evidence of effectiveness and best practices. CONCLUSION: As food prescribing continues to gain traction in Canada, there is a need to assess the effectiveness, cost-efficiency, limitations and potential paternalism of this intervention model. Further, it is necessary to assess how food prescribing fits into broader social welfare systems that aim to address the underlying determinants of food insecurity.

Effect of Implementing an Informatization Case Management Model on the Management of Chronic Respiratory Diseases in a General Hospital: Retrospective Controlled Study.

Background: The use of chronic disease information systems in hospitals and communities plays a significant role in disease prevention, control, and monitoring. However, there are several limitations to these systems, including that the platforms are generally isolated, the patient health information and medical resources are not effectively integrated, and the "Internet Plus Healthcare" technology model is not implemented throughout the patient consultation process. Objective: The aim of this study was to evaluate the efficiency of the application of a hospital case management information system in a general hospital in the context of chronic respiratory diseases as a model case. Methods: A chronic disease management information system was developed for use in general hospitals based on internet technology, a chronic disease case management model, and an overall quality management model. Using this system, the case managers provided sophisticated inpatient, outpatient, and home medical services for patients with chronic respiratory diseases. Chronic respiratory disease case management quality indicators (number of managed cases, number of patients accepting routine follow-up services, follow-up visit rate, pulmonary function test rate, admission rate for acute exacerbations, chronic respiratory diseases knowledge awareness rate, and patient satisfaction) were evaluated before (2019-2020) and after (2021-2022) implementation of the chronic disease management information system. Results: Before implementation of the chronic disease management information system, 1808 cases were managed in the general hospital, and an average of 603 (SD 137) people were provided with routine follow-up services. After use of the information system, 5868 cases were managed and 2056 (SD 211) patients were routinely followed-up, representing a significant increase of 3.2 and 3.4 times the respective values before use (U=342.779; P<.001). With respect to the quality of case management, compared to the indicators measured before use, the achievement rate of follow-up examination increased by 50.2%, the achievement rate of the pulmonary function test increased by 26.2%, the awareness rate of chronic respiratory disease knowledge increased by 20.1%, the retention rate increased by 16.3%, and the patient satisfaction rate increased by 9.6% (all P<.001), while the admission rate of acute exacerbation decreased by 42.4% (P<.001) after use of the chronic disease management information system. Conclusions: Use of a chronic disease management information system improves the quality of chronic respiratory disease case management and reduces the admission rate of patients owing to acute exacerbations of their diseases.

Disparities in diabetes processes of care among people experiencing homelessness: An opportunity for intervention.

AIMS: To compare processes of diabetes care by homeless status. METHODS: A population-based propensity matched cohort study was conducted in Ontario, Canada. People with diabetes were identified in administrative healthcare data between April 2006 and March 2019. Those with a documented history of homelessness were matched to non-homeless controls. Data on processes of care measures included glucose monitoring tests, screening for microvascular complications, and physician follow-up. Differences in processes of care were compared by homeless status using proportions, risk ratios, and rate ratios. RESULTS: Of the 1,076,437 people with diabetes, 5219 matched pairs were identified. Homelessness was associated with fewer tests for glycated hemoglobin (RR = 0.63; 95 %CI: 0.60-0.67), LDL cholesterol (RR = 0.80; 95 %CI: 0.78-0.82), serum creatinine (RR = 0.94; 95 %CI: 0.92-0.97), urine protein quantification (RR = 0.62; 95 %CI: 0.59-0.66), and eye examinations (RR = 0.74; 95 %CI: 0.71-0.77). People with a history of homelessness were less likely to use primary care for diabetes management (RR = 0.62; 95 %CI: 0.59-0.66) or specialist care (RR = 0.87; 95 %CI: 0.83-0.91) compared to non-homeless controls. CONCLUSIONS: Disparities in diabetes care are evident for people with a history of homelessness and contribute to excess morbidity in this population. These data provide an impetus for investment in tailored interventions to improve healthcare equity and prevent long-term complications.

Self-care behaviours of first-generation Chinese immigrants living with cardiovascular disease: A qualitative study.

AIM: To identify and describe self-care behaviours performed by Chinese immigrants living with cardiovascular disease in Australia, and factors perceived as barriers and facilitators to evidence-based cardiac self-care. DESIGN: A qualitative descriptive design. METHODS: Individual semi-structured phone interviews were conducted among participants meeting the following criteria: (1) first-generation Chinese immigrants to Australia, born in Mainland China, Hong Kong, Macao or Taiwan; (2) Australian permanent residents or citizens; (3) self-reported or medically diagnosed with coronary heart disease, stroke or heart failure; (4) able to speak English or Mandarin; (5) able to provide informed consent, excluding those with history or evidence of impaired cognition such as dementia. Participants were recruited via social media, Chinese community associations and medical centres from September 2021 to June 2022. Data were analysed using inductive and deductive thematic analysis, guided by the Middle-Range Theory of Self-Care of Chronic Illness. The study was reported in line with the COREQ checklist. RESULTS: Twenty participants were interviewed, 60% female, mean age 69.9 years. Most migrated to Australia at older age following their retirement in China; most had limited English proficiency. Many practiced adequate self-care for their CVD in self-care maintenance and monitoring. Variously, they adopted heart-healthy diets, developed exercise routines, attended medical services and closely monitored their body signs and symptoms. However, self-adjusting medications, taking Traditional Chinese Medicine and self-administering health supplements were prevalent practices and first-response management of acute cardiac symptoms was suboptimal. Linguistic and cultural barriers to obtaining mainstream heart health information meant most participants resorted to informal, anecdotal and mainland Chinese sources. CONCLUSION: Diverse factors were held responsible for sub-optimal self-care behaviours but lack of access to linguistically and culturally appropriate heart health information was widely blamed. Linguistically and culturally appropriate community-based heart health education programmes are urgently needed, targeting healthy lifestyle modification, medication literacy and cardiac symptom management. IMPACT: Study findings can be used to improve cardiac nurses' cultural sensitivity and practices targeting Chinese immigrants. Partnering with Chinese community associations offers health service providers and policymakers an innovative route to co-design and deliver targeted heart health education interventions and support for this population. PUBLIC CONTRIBUTION: Chinese community centre managers contributed to data collection by supporting participant recruitment.