UNASSIGNED: Patients with Chronic Obstructive Pulmonary Disease (COPD) frequently face substantial medication burdens. Follow-up care on medication management is critical in achieving disease control. This study aimed to analyze the complexity of COPD-specific medication and determine how it impacted patients\' attendance on follow-up care.
UNASSIGNED: This multicenter study includes patients with COPD from 1,223 hospitals across 29 provinces in China from January 2021 to November 2022. The medication Regimen Complexity Index (MRCI) score was used to measure COPD-specific medication complexity. The association between medication complexity and follow-up care attendance was evaluated using the Cox Proportional Hazard Model.
UNASSIGNED: Among 16,684 patients, only 2,306 (13.8%) returned for follow-up medication management. 20.3% of the patients had high complex medication regimen (MRCI score >15.0). The analysis revealed that compared to those with less complex regimens, patients with more complex medication regimens were significantly less likely to attend the follow-up medication care, with a Hazard Ratio (HR) of 0.82 (95% Confidence Interval [CI], 0.74-0.91). Specifically, patients with more complex dosage forms were 51% less likely to attend the follow-up care (95% CI, 0.43-0.57). This pattern was especially marked among male patients, patients younger than 65 years, and those without comorbid conditions.
UNASSIGNED: Higher medication complexity was associated with a decreased likelihood of attending follow-up care. To promote care continuity in chronic disease management, individuals with complex medication regimens should be prioritized for enhanced education. Furthermore, pharmacists collaborating with respiratory physicians to deprescribe and simplify dosage forms should be considered in the disease management process.

UNASSIGNED: Smartphone applications aimed at patients with gastroesophageal reflux disease (GERD) have been downloaded more than 100,000 times, yet no systematic assessment of their quality has been completed. This study aimed to objectively assess the quality of GERD smartphone applications for patient education and disease management.
UNASSIGNED: The Apple App Store and Google Play Store were systematically searched for relevant applications. Two independent reviewers performed the application screening and eligibility assessment. Included applications were graded using the validated Mobile Application Rating Scale, which encompasses 4 domains (engagement, functionality, aesthetics, and information) as well as an overall application quality score. The associations between overall application quality, user ratings and download numbers were evaluated.
UNASSIGNED: Of the 4816 unique applications identified, 46 met inclusion criteria (patient education = 37, disease management = 9). Mean overall application quality score was 3.02 ± 0.40 out of 5 (\"acceptable\"), with 61% (28/46) rated as \"poor\" (score 2.0-2.9). Applications scored highest for aesthetics (3.24 ± 0.48) and functionality (3.88 ± 0.37) and lowest for information (2.58 ± 0.64) and engagement (2.39 ± 0.65). Disease management applications were of significantly higher quality than education-focused applications (3.59 ± 0.38 vs 2.88 ± 0.26, P < .001). There was no correlation between graded quality and either user ratings or the number of downloads.
UNASSIGNED: While numerous smartphone applications exist to support patients with GERD, their quality is variable. Patient education applications are of particularly low quality. Our findings can help to inform the selection of applications by patients and guide clinicians\' recommendations. This study also highlights the need for higher-quality, evidence-informed applications aimed at GERD patient education.

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.
CONCLUSIONS: 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.

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 ± standard deviation; 0.780 ± 0.026) along with the 95 % CI ridge and lasso methods (0.780 ± 0.027). The 95 % CI elastic-net had the highest sensitivity (0.773 ± 0.083) while the 95 % CI adaptive lasso had the highest specificity (0.691 ± 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.

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.

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.
BACKGROUND: PROSPERO CRD42022359658; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=359658.

UNASSIGNED: Enhancing community based Chronic Disease Management (CDM) will make significant impacts on all major chronic disease management outcome measures. There are no successful models of community hubs to triage and manage chronic diseases that significantly reduce readmissions, cost and improve chronic disease knowledge. Chronic heart failure (CHF) management foundations are built on guideline derived medical therapies (GDMT). These consensuses evidenced building blocks have to be interwoven into systems and processes of care which create access, collaboration and coordinate effective and innovative health services.
UNASSIGNED: Perspective and short communication.
UNASSIGNED: This review explores: (i) conventional chronic disease management in Australia; (ii) Possible options for future chronic diseases models of care that deliver key components of CHF management.

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.

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.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.