BACKGROUND AND OBJECTIVE

The Philippine Package of Essential Noncommunicable Disease Interventions (PhilPEN) was introduced by the Department of Health through AO 2012-0029. This is anchored to WHO PEN, a prioritized set of cost-effective interventions that can be carried out to provide an acceptable standard of care at the primary health care level, even in low-resource settings. The study aims to evaluate the availability and adequacy of primary health care facilities in providing the PhilPEN package of interventions using the WHO assessment tool.

A cross-sectional survey was conducted in 25 randomly selected primary health care facilities in Metro Manila. Data were collected through structured interviews with facility staff and direct observation using a standardized questionnaire aligned with PhilPEN and WHO PEN guidelines. The tool assessed PhilPEN inputs (infrastructure, human resources, basic tools and equipment, essential medicines, record-keeping, financing) and services (risk assessment and screening, early diagnosis and monitoring, treatment and follow-up, counseling, referral of patients).

All facilities met the basic standards for infrastructure, human resources, record keeping, and financing. However, only 40% had all essential medicines, and just 16% had complete tools, including urine ketone/protein test strips. Risk assessment and patient counseling were consistently implemented, but early diagnosis and follow-up services were inconsistent due to training and supply gaps.

Primary health care centers in Metro Manila demonstrate partial readiness for PhilPEN implementation. Gaps in tools, medicines, and protocol availability should be addressed to optimize NCD service delivery.

Effective discharge planning is crucial for ensuring safe transitions and sustained occupational participation as clients transition from professional care to their desired community settings. Despite its importance, current discharge practices in occupational therapy remain inconsistent, often relying on informal communication, variable team coordination, and unstructured decision-making. These gaps contribute to client–caregiver unpreparedness, fragmented services, and increased readmissions. This manuscript presents the Building Rehabilitation Into Discharge Goals and Engagement (BRIDGE) Framework, a client-centered, occupation-focused conceptual model designed to structure and support the discharge planning process in occupational therapy.

The BRIDGE framework was developed through an iterative process of literature review, theoretical grounding, and integration of clinical experience. It synthesizes principles from the Canadian Practice Process Framework, Person–Environment–Occupation frameworks, the Kawa Model, and Bioecological Systems Theory. The framework outlines six discharge planning steps, ranging from goal and timeline setting to follow-up and monitoring, supported by four foundational pillars: patient and family factors, occupational therapy factors, interdisciplinary team factors, and environmental or system influences. Together, these components provide a comprehensive guide for clinical reasoning, collaborative planning, caregiver preparation, and transitional support.

The framework clarifies the role of occupational therapy, enhances interprofessional coordination, and promotes consistent transition planning. Future work should include empirical testing, case-based application, and population-specific adaptations.

Introduction: Insulin therapy is essential in the management of type 2 diabetes mellitus (T2DM), but is often associated with treatment burden, hypoglycemia, and potential overtreatment. Insulin deintensification is increasingly recommended for appropriately selected patients; however, there is limited real-world evidence to guide patient selection and to identify modifiable factors that influence successful insulin deintensification. This study aimed to identify clinical predictors, including modifiable factors, associated with successful insulin deintensification in a primary care setting. Methodology: A multicentre retrospective observational study was conducted across seven government primary care clinics in the Petaling District. Adult patients with T2DM undergoing insulin deintensification were included. Successful insulin deintensification was defined as maintenance or improvement of hemoglobin A1c following insulin discontinuation, dose reduction, or reduction in injection frequency. Paired outcomes were analyzed using the Wilcoxon signed-rank test. Between-group comparisons were performed using the Mann–Whitney U test and Chi-square or Fisher’s exact test. Multivariable logistic regression was used to identify independent predictors of successful insulin deintensification. Results: A total of 261 patients were included. Glycemic control remained stable following insulin deintensification (p = 0.334). Significant reductions in body weight (−0.41 kg, p = 0.012) and total daily insulin dose (23.1% reduction, p <0.001) were observed. Univariate analysis did not demonstrate significant differences between groups. However, multivariable logistic regression identified SGLT-2 inhibitor use (aOR 3.23, 95% CI 1.28–8.18, p = 0.013) and regular SMBG (aOR 2.00, 95% CI 1.05–3.81, p = 0.035) as independent predictors of successful insulin deintensification. Conclusion Insulin deintensification can be successfully implemented without compromising glycemic control. Identified predictors, including modifiable factors such as SGLT-2 inhibitor use and SMBG, provide clinically actionable insights to guide patient selection and treatment optimization. These findings challenge the traditional reluctance toward insulin deintensification and support a more evidence-based and individualized approach in routine clinical practice.
Primary Health Care ; Insulins

Introduction: Insulin deintensification is an emerging strategy to reduce hypoglycemia and treatment burden in patients on multiple daily injection (MDI ≥3), with potential to improve adherence and glycemic control. However, evidence in poorly controlled type 2 diabetes mellitus (T2DM) remains limited. This study evaluated its effectiveness and identified factors associated with achieving adequate glycemic control following deintensification among patients with poorly controlled T2DM attending Malaysian primary care. Methodology: A retrospective cohort study was conducted among 107 T2DM patients with hemoglobin A1c (HbA1c) >9%, attending Enhanced Diabetic Clinic at Cheras Health Clinic between 2021 and 2025. All patients on basal-bolus insulin (BBI) underwent deintensification. Multivariate logistic regression was performed to identify factors associated with achieving adequate glycemic control (HbA1c <7.5%). Changes in HbA1c following deintensification were assessed using paired t-tests. Results: Overall, 50.5% of patients achieved adequate glycemic control. Hypoglycemia events (AOR 9.5, 95% confidence interval [CI] 1.6–58.3; p = 0.015), MDI (AOR 9.6, 95% CI 1.4–67.1; p = 0.023) and Diabetes Medication Therapy Adherence Clinic (DMTAC) visits (AOR 1.1, 95% CI 1.0– 1.2; p = 0.039) were significantly associated with achieving HbA1c <7.5%. Conversely, patients transitioned from BBI to premixed regimens were less likely to achieve HbA1c <7.5% (AOR 0.22, 95% CI 0.05–0.93, p = 0.039). All insulin deintensification strategies were associated with significant HbA1c improvements with transitioned from BBI to premixed human insulin (mean difference -2.54%, 95% CI 1.77–3.31, p <0.001, Cohen’s d = 1.09), BBI to premixed analogue insulin (mean difference -3.38%, 95% CI 2.26– 4.49, p <0.001, Cohen’s d = 1.62), BBI to basal insulin (mean difference -3.67%, 95% CI 1.79–5.54, p = 0.004, Cohen’s d = 2.05). Conclusion Insulin deintensification is an effective strategy for improving glycemic control in poorly controlled T2DM. These findings highlight the importance of deintensification with careful consideration of hypoglycemia, MDI-related treatment burden, and patient engagement through regular DMTAC visits, which are integral to achieving optimal outcomes and support a personalized approach to diabetes management in primary care.
Diabetes Mellitus, Type 2 ; Glycemic Control ; Retrospective Studies ; Primary Health Care ; Insulins

BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surgical intervention remains the primary treatment option for early-stage lung cancer, and video-assisted thoracoscopic surgery (VATS) has become a common approach due to its minimal invasiveness and rapid recovery. However, post-discharge recovery remains incomplete, underscoring the importance of postoperative care. Traditional follow-up methods, lack standardization, consume significant medical resources, and increase the burden of the patients. Artificial intelligence (AI)-driven disease management platforms offer a novel solution to optimize postoperative follow-up. This study followed 463 lung cancer surgery patients using an AI-based platform, aiming to identify common postoperative issues, propose solutions, improve quality of life, reduce recurrence-related costs, and promote AI integration in healthcare. METHODS: Using the AI disease management platform, this study integrated educational videos, collaboration between healthcare teams and AI assistants, daily health logs, health assessment forms, and personalized interventions to monitor postoperative recovery. The postoperative rehabilitation status of the patients was assessed by the Leicester Cough Questionnaire (LCQ-MC). Two independent t-test and one-way ANOVA were used to analyze the causes of postoperative cough in lung cancer. RESULTS: Most issues occurred within 7 d post-discharge, significantly declined on 14 d post-discharge. Factors such as gender, smoking history, and surgical approaches were found to influence cough recovery. The incidence of cough on 7 d post-discharge in females was higher than that in males (P<0.01), while the incidence of cough on 14 d post-discharge in elderly patients was lower than that in young patients (P=0.03). The AI-based platform effectively addressed cough, pain, and sleep disturbances through phased interventions. CONCLUSIONS The AI-based platform significantly enhanced postoperative management efficiency and the self-care capabilities of the patients, particularly in phased cough management. Future integration with wearable devices could enable more precise and personalized postoperative care, further advancing the application of AI technology across multidisciplinary healthcare domains.
Humans ; Lung Neoplasms/rehabilitation* ; Male ; Female ; Middle Aged ; Aged ; Patient Discharge ; Artificial Intelligence ; Adult ; Postoperative Care ; Postoperative Period ; Disease Management ; Quality of Life

OBJECTIVE: To investigate the current status of long-term quality of life in patients with severe acute pancreatitis (SAP) who have been cured and discharged, and to analyze the influencing factors affecting long-term quality of life in SAP cured patients after discharge. METHODS: A retrospective collection was conducted. Patients who were received standardized treatment before being cured and discharged from the hospital admitted to the first department of critical care medcine of the Second Affiliated Hospital of Anhui Medical University from January 2017 to December 2023 were enrolled. According to the 36-item short form health survey scale (SF-36) score, patients were divided into high score group (high quality of life, the top 50% of patients with total SF-36 score) and low score group (low quality of life, the bottom 50% of patients with total SF-36 score). The gender, age, history of hypertension and diabetes, etiology of pancreatitis, acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), CT severity index (CTSI), laboratory indicators such as C-reactive protein (CRP), procalcitonin (PCT), blood glucose, and triglycerides upon admission, use of vasoactive drugs, non-invasive/high-flow ventilation, invasive ventilation, retroperitoneal puncture and drainage, open pancreatic surgery treatment and secondary infection during hospitalization were collected, as well as the retention of abdominal drainage tubes at discharge from hospital. Distribute follow-up questionnaires or telephone follow-up surveys through WeChat and Question Star programs to investigate the pancreatic secretion function, chronic abdominal pain, and recurrence of pancreatitis of patients after discharge. Multivariable Logistic regression was used to analyze the relevant factors affecting the long-term quality of life of cured patients with SAP. RESULTS: A total of 86 patients were ultimately enrolled. There were 43 patients in both the high and low score groups. Among 86 patients, 20 experienced acute pancreatitis recurrence, with a recurrence rate of 23.26%. Twenty-two (25.58%) experienced chronic abdominal pain after discharge, and 5 patients (5.81%) needed medication to relieve pain. Thirty-three patients (38.37%) had pancreatic exocrine dysfunction after discharge, characterized by abdominal distension, constipation or diarrhea. Twenty-two patients (25.58%) suffered from pancreatic endocrine dysfunction, and were diagnosed with diabetes. Univariate analysis showed that compared with the high score group, the low score group had more patients with hypertension, initial renal dysfunction, initial severe metabolic acidosis, initial serum calcium < 2.0 mmol/L, blood glucose > 11.1 mmol/L and cultured Gram positive bacteria (from blood/body fluid/pancreatic necrotic tissue) during treatment (48.84% vs. 16.28%, 60.47% vs. 32.56%, 18.60% vs. 4.65%, 88.37% vs. 62.79%, 55.81% vs. 30.23%, 34.88% vs. 13.95%), had higher CTSI score (6.60±1.61 vs. 5.77±1.32), lower hemoglobin level at discharge (g/L: 102.30±18.78 vs. 110.72±16.68), and a lower proportion of etiological interventions after discharge (34.88% vs. 67.44%), the differences were statistically significant (all P < 0.05). Multivariate Logistic regression analysis showed that hypertension [odds ratio (OR) = 4.814, 95% confidence interval (95%CI) was 1.196-19.378], initial serum calcium < 2.0 mmol/L (OR = 6.688, 95%CI was 1.321-33.873) and initial blood glucose > 11.1 mmol/L (OR = 6.473, 95%CI was 1.399-29.950) were risk factors for long-term quality of life in cured SAP patients (all P < 0.05), while post discharge prophylactic intervention was a protective factor for long-term quality of life (OR = 0.092, 95%CI was 0.020-0.425, P < 0.01). CONCLUSIONS Cured SAP patients have varying degrees of impaired secretion function and the possibility of recurrence of acute pancreatitis. Hypertension, initial serum calcium < 2.0 mmol/L and blood glucose > 11.1 mmol/L are independent influencing factors for low long-term quality of life in cured SAP patients. Prevention and intervention targeting the etiology of pancreatitis after discharge can improve the long-term quality of life of cured SAP patients.
Humans ; Quality of Life ; Retrospective Studies ; Pancreatitis/therapy* ; Patient Discharge ; Male ; Female ; Middle Aged ; APACHE ; Adult ; Acute Disease ; Aged

OBJECTIVE: To evaluate the impact of critical care warning platform (CWP) on clinical outcomes of patients transferred from internal medical ward to intensive care unit (ICU) based on real-world data. METHODS: A retrospective cohort study was conducted. The patients transferred from internal medical ward to ICU of Zhongda Hospital, Southeast University, between January 2022 and October 2024, were enrolled. They were divided into critical care warning group and conventional treatment group based on whether they were connected to the CWP. The patients in the critical care warning group were connected to the CWP, which collected real-time vital signs and treatment data. The platform automatically calculated severity scores, generated individualized risk assessments, and triggered warning alerts, allowing clinicians to adjust treatment plans accordingly. The patients in the conventional treatment group were not connected to the CWP and relied on conventional clinical judgment and nursing measures for treatment management. Baseline characteristics [gender, age, body mass index (BMI), admission type, severity score of illness, underlying diseases, and disease type at ICU admission], primary clinical outcome (in-hospital mortality), and secondary clinical outcomes [ICU mortality, length of ICU stay, total length of hospital stay, and mechanical ventilation and continuous renal replacement therapy (CRRT) status] were collected. Multivariate Logistic regression was used to analyze the impact of CWP on in-hospital death, and subgroup analyses were performed based on different patient characteristics. RESULTS: A total of 1 281 patients were enrolled, with 768 in the critical care warning group and 513 in the conventional treatment group. Compared with the conventional treatment group, the proportion of patients in the critical care warning group with underlying diseases of diabetes and malignancy and transferred to ICU due to sepsis was lowered, however, there were no statistically significant differences in other baseline characteristics between the two groups. Regarding the primary clinical outcome, the in-hospital mortality in the critical care warning group was significantly lower than that in the conventional treatment group [17.6% (135/768) vs. 25.7% (132/513), P < 0.01]. For secondary clinical outcomes, compared with the conventional treatment group, the patients in the critical care warning group had significantly fewer days of mechanical ventilation within 28 days [days: 2 (1, 6) vs. 2 (1, 8), P < 0.05], significantly shorter length of ICU stay [days: 3 (2, 8) vs. 4 (2, 10), P < 0.01], and significantly lower ICU mortality [15.1% (116/768) vs. 21.4% (110/513), P < 0.01]. Multivariate Logistic regression analysis showed that, after adjusting for age and underlying diseases, the use of CWP was significantly associated with a reduction of in-hospital mortality among patients transferred from internal medical ward to ICU [odds ratio (OR) = 0.670, 95% confidence interval (95%CI) was 0.502-0.894, P = 0.006]. Further subgroup analysis revealed that, among patients transferred to ICU due to sepsis, the use of CWP significantly reduced in-hospital mortality (OR = 0.514, 95%CI was 0.367-0.722, P < 0.001). In patients aged ≥ 70 years old (OR = 0.587, 95%CI was 0.415-0.831, P = 0.003) and those with underlying diseases of malignancy (OR = 0.124, 95%CI was 0.046-0.330, P < 0.001), CWP also showed significant protective effects on in-hospital prognosis. CONCLUSION The use of CWP is significantly associated with a reduction in in-hospital mortality among patients transferred from internal medical ward to ICU, demonstrating its potential in assessing the deterioration of hospitalized patients.
Humans ; Intensive Care Units ; Retrospective Studies ; Hospital Mortality ; Prognosis ; Critical Care ; Male ; Female ; Patient Transfer ; Middle Aged ; Aged ; Cohort Studies

OBJECTIVE: To develop a digital intelligent multimodal shift handover system for the intensive care unit (ICU) and evaluate its application effect in ICU shift handovers. METHODS: A research and development team was established, consisting of 1 department director, 1 head nurse, 3 information technology engineers, 3 nurses, and 2 doctors. Team members were assigned responsibilities including overall coordination and planning, platform design and maintenance, pre-application training, collection and organization of clinical feedback, and research investigation respectively. A digital intelligent multimodal shift handover system was developed for ICU based on the Shannon-Weaver linear transmission model. This innovative system integrated automated data collection, intelligent dynamic monitoring, multidimensional condition analysis and visual reporting functions. A cloud platform was used to gather data from multi-parameter vital signs monitors, infusion pumps, ventilators and other devices. Artificial intelligence algorithms were employed to standardize and analyze the data, providing personalized recommendations for healthcare professionals. A self-controlled before-after method was adopted. Before the application of the ICU digital intelligent multimodal shift handover system (from December 2023 to March 2024), the traditional verbal bedside handover was used; from June 2024 to March 2025, the ICU digital intelligent multimodal shift handover system was applied for shift handovers. Questionnaires before the application of the shift handover system were collected in April 2024, and those after the application were collected in April 2025. The shift handover time, handover quality (scored by the nursing handover evaluation scale), satisfaction with doctor-nurse communication (scored by the ICU doctor-nurse scale) before and after the application of the handover system were compared, and nurses' satisfaction with the shift handover system (scored by the clinical nursing information system effectiveness evaluation scale) was investigated. RESULTS: After the application of the ICU digital intelligent multimodal shift handover system, the shift handover time was significantly shorter than that before the application [minutes: 20 (15, 25) vs. 30 (22, 40)], the handover quality was significantly higher than that before the application [score: 84.0 (78.0, 88.5) vs. 71.0 (55.0, 79.0)], and the satisfaction with doctor-nurse communication was also significantly higher than that before the application (score: 84.58±6.79 vs. 74.50±11.30). All differences were statistically significant (all P < 0.05). In addition, the nurses' system effectiveness evaluation scale score was 102.30±10.56, which indicated that nurses had a very high level of satisfaction with the ICU digital intelligent multimodal shift handover system. CONCLUSIONS The application of the ICU digital intelligent multimodal shift handover system can shorten the shift handover time, improve the handover quality, and enhance the satisfaction with doctor-nurse communication. Nurses have a high level of satisfaction with this system.
Intensive Care Units ; Humans ; Patient Handoff ; Artificial Intelligence ; Algorithms

Obesity is a significant public health problem in China. The development of a proactive and effective model to combat the obesity epidemic could alleviate the disease burden, improve population health, and ultimately support the achievement of the Healthy China goals. Obesity research has made significant progress domestically and internationally, resulting in continuous improvements in basic public health services within primary care. Therefore, the National Office of Basic Public Health Service Program for Primary Diabetes Care has organized experts to issue the National Guidelines for the Integrated Management of Obesity in Primary Care (2025). The aim of this guide is to assist primary care physicians with evidence-based recommendations for diagnosing and evaluating obesity, promoting standardized and integrated management for patients with obesity. It includes essential guidelines for patient management, an overview of obesity, diagnostic and evaluation criteria, integrated management strategies, and protocols for follow-up and referral.
Humans ; Primary Health Care ; Obesity/therapy* ; China ; Practice Guidelines as Topic

In China, the prevalence of diabetes has increased significantly, and rigorous challenges exist in diabetes prevention and glycemic control, especially in primary medical care. Under the guidance of the National Health Commission of the People's Republic of China and the Chinese Medical Association, the Office for Primary Diabetes Care of the National Basic Public Health Service Program issued the "National guidelines for the prevention and control of diabetes in primary care (2018)" in 2018. The present guideline, which incorporates the latest advances in diabetes research and practice from the 2018 and 2022 editions, aims to improve primary health facilities and provide standardized basic public health and medical services throughout China. It applies to healthcare providers who provide primary care to patients with type 2 diabetes aged 18 or older. It primarily includes basic management requirements; workflow of health management; diagnosis; classification; monitoring, screening, and assessment; treatment; identification and management of diabetic acute and chronic complications; traditional Chinese medicine; referral; health management; and health education.
Humans ; Primary Health Care ; China ; Diabetes Mellitus, Type 2/therapy* ; Diabetes Mellitus/prevention & control* ; Practice Guidelines as Topic