OBJECTIVES

Timely access to appropriate levels of care is essential for improving maternal, newborn,
and child health outcomes. To address persistent service delivery fragmentation and strengthen referral systems, the Philippine Department of Health issued Administrative Order 2020-0019 to guide the design of Health Care Provider Networks (HCPNs) under the Universal Health Care Act of 2019. This study assessed the extent to which sixteen municipalities across four provinces in Eastern Visayas comply with the HCPN service delivery guidelines in the context of maternal and newborn care.

METHODS

The study employed a descriptive cross-sectional mixed-methods design, utilizing structured facility checklists to assess compliance with HCPN standards. Qualitative data were gathered through key informant interviews and focus group discussions with purposively selected stakeholders—decision makers, health personnel, and mothers—to contextualize findings. A three-lever framework for integrated care (policy, operational, and cross- cutting) guided the analysis

RESULTS

The findings revealed significant gaps between the current capacities of study health facilities and the requirements outlined in the HCPN guidelines. Major gaps included (1) weak cooperative governance mechanisms to support network-wide coordination; (2) limited systematic linkages between facilities, including fragmented referral protocols and non-interoperable health information systems; (3) inadequate investments in infrastructure, health human resources, and medical commodities; and (4) absence of performance monitoring systems across HCPNs.

CONCLUSION

 

Human ; Information Systems ; Occupational Groups ; Referral And Consultation ; Universal Health Care ; Delivery Of Health Care

BACKGROUND AND OBJECTIVE

Access to healthcare remains a challenge in most areas in the Philippines. Fifty-three percent (53%) of the Philippine population do not have access to a rural health unit (RHU) within a 30-minute travel t ime. As a response, the Department of Health (DOH) needs to construct an additional 2400 RHUs by 2025. This paper uses the Philippine Health Facility Development Plan 2020-2040 (PHFDP) as a reference to present a solution for locating sites for RHU placement in under-served areas using neural networks to meet the 30-minute travel time by maximizing population accessibility.

METHODS

RHU accessibility was measured using geographic attributes as inputs to a back propagation neural network (BPNN) and a recurrent neural network (RNN): (1) land coverage and hazard data, representing geographical limitations; (2) population density and distribution, indicating demand for healthcare services; and (3) infrastructure-related features, such as road networks, points of interest, and the locations of existing RHUs, which influence healthcare accessibility. The models were trained to identify underserved areas and were implemented on a nationwide scale, excluding NCR, to locate candidate areas to increase population access to the new RHUs. The models were validated using a healthcare facility accessibility index (HCFAI) to assess RHU coverage improvement.

RESULTS

The BPNN showed stronger generalization across regions, achieving 79.1% average accuracy in distinguishing low from high accessible areas on Region 1 and identifying 1668 out of 3305 locations in the region as candidate sites. The RNN, better capturing unique regional characteristics, required separate training: 77.2% average accuracy on Region 1, identifying 1593 candidate sites. Our findings suggest expanding the use of land improves population access to healthcare facilities. Both models found more than the needed number of RHUs by 2040. The BPNN was more consistent than RNN to improve a region’s overall accessibility by increasing the HCFAI. The BPNN can increase population access to an RHU from 2.5-98.5% from its original population with access to an RHU.

CONCLUSION

The study demonstrates the usage of geographic attributes and neural networks to improve healthcare accessibility. The BPNN and RNN are adequate algorithms to find under-served areas and candidate sites for RHU construction to maximize population accessibility. The HCFAI metric validates the locations to highlight which neural network maximizes more of the region’s populat ion. The study contributes to ongoing efforts to improve healthcare infrastructure and accessibility, offering datadriven recommendations for RHU locations.

Human ; Universal Health Care ; Rural Health ; Delivery Of Health Care ; Health Services Needs And Demand ; Health Facilities ; Algorithms ; Back

OBJECTIVES

Clinical pathways (CPs) ensure adherence to heart failure (HF) management guidelines. To optimize quality care in a low resource setting, an evidence-based care pathway for the management of acute HF was implemented at the emergency department (ED) of the Philippine General Hospital (PGH), the designated national tertiary hospital and referral center. This study aimed to describe the characteristics of adults with acute HF admitted at the ED and evaluate the quality of care they received, measured using physician adherence to the hospital’s acute heart failure CP.

METHODS

This was a retrospective, descriptive cohort study. We reviewed the inpatient charts of all adult patients with acute HF admitted to the ED of the PGH and referred to the Division of Cardiovascular Medicine between December 1, 2022 and May 31, 2023. Quality of care was assessed based on adherence to quality indicators adapted from routine and conditional order sets detailed in the pathway. Descriptive statistics was utilized to describe patient characteristics, quality of care, and outcomes.

RESULTS

Two hundred thirty-six (236) patients were included, with a mean age of 51.8 years. Majority were male (53.4%); hypertension (61.4%) and ischemic heart disease (53.8%) were the most common comorbidities, and infection the most common precipitant of decompensation (60.6%). There were optimal adherence rates to routine orders, which included referrals to Internal Medicine and Cardiology, baseline vital signs monitoring, fluid intake and output monitoring, chest radiograph, complete blood count, blood urea nitrogen, sodium, potassium, prothrombin time, partial thromboplastin time, arterial blood gas, urinalysis, and N-terminal pro b-type natriuretic peptide. Conditional orders, such as oxygen support, focused echocardiography, thyroid - stimulating hormone, and the use of vasopressors, diuretics, and venous thromboembolism prophylactic agents, were optimally performed when warranted. However, we noted suboptimal adherence to certain resource-intensive conditional orders, such as hourly monitoring of urine output (61.4%), hooking to cardiac monitor (53.8%), and performance of 12-lead ECG within 10 minutes (56.8%). Further, only 43.9% of patients were referred to the intensive care unit. Troponin I, calcium, magnesium, and albumin were ordered in excess.

CONCLUSION

Overall adherence rate of physicians to the hospital’s Acute Heart Failure Pathway was satisfactory. Work is needed to improve adherence to hourly urine output monitoring, consistent hooking to cardiac monitor, and timely performance of 12-lead ECG – an effort that begins with expanding in-hospital diagnostic equipment and human resource supply. We recommend continuous pathway implementation with periodic evaluation and stakeholder feedback to further improve quality of care.

Human ; Male ; Female ; Middle Aged: 45-64 Yrs Old ; Adult ; Albumins ; Blood ; Blood Urea Nitrogen ; Calcium ; Cardiology ; Chart ; Charts ; Cohort Studies ; Critical Care ; Critical Pathways ; Diagnostic Equipment ; Disease ; Diuretics ; Echocardiography ; Electrocardiography ; Emergencies ; Emergency Service, Hospital ; Equipment And Supplies ; Evaluation Studies As Topic ; Feedback ; Heart ; Heart Diseases ; Heart Failure ; Hormones ; Hospitals ; Hospitals, General ; Humans ; Hypertension ; Indicators And Reagents ; Infection ; Infections ; Inpatients ; Intensive Care Units ; Internal Medicine ; Lead ; Magnesium ; Male ; Medicine ; Myocardial Ischemia ; Natriuretic Peptide, Brain ; Natriuretic Peptides ; Nitrogen ; Overall ; Oxygen ; Partial Thromboplastin Time ; Patients ; Peptides ; Philippines ; Physicians ; Potassium ; Prothrombin ; Prothrombin Time ; Quality Of Health Care ; Referral And Consultation ; Sodium ; Statistics ; Tertiary Care Centers ; Thorax ; Thromboembolism ; Thromboplastin ; Thyroid Gland ; Time ; Troponin ; Troponin I ; Universities ; Urea ; Urinalysis ; Urine ; Venous Thromboembolism ; Vital Signs ; Work ; Workforce

Workforce ; Delivery Of Health Care ; Healthcare

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.

METHODS

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).

RESULTS

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.

CONCLUSION

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.

Human ; Primary Health Care ; Noncommunicable Diseases ; Delivery Of Health Care ; Standard Of Care ; Cardiovascular Diseases

OBJECTIVE: The aim of this study is to investigate the risk factors of prognosis in patients with early-onset prostate cancer treated without surgery. A nomogram will be constructed and validated to predict overall survival (OS) of patients with early-onset prostate cancer treated without surgery. METHODS: The clinical data was obtained from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database on prostate cancer patients aged 18－55 years who were treated without surgery between 2010 and 2015. The clinical data set was divided into training set and validation set according to 7∶3 ratio, including age, race, marital status, Gleason score, prostate specific antigen (PSA) and other 8 factors. And significant variables were screened by univariate Cox regression analysis. Multivariate Cox regression analysis was used to identify the influence factors. Stepwise regression method was used to select the most influential factors on the total OS, and R software was used to build a nomogram model. The accuracy and prediction ability of the model were verified by drawing receiver operating characteristic (ROC) and Calibration Plot. The clinical benefit of the model was evaluated by decision curve analysis (DCA). RESULTS: A total of 8 212 patients who met the criteria were randomly assigned to the training set (n=5 752) or validation set (n=2 460), with no statistical difference between the two groups (all P>0.05). Six factors were identified through univariate and multivariate Cox regression analysis including marital status, N stage, M stage, radiotherapy, PSA and Gleason score, which were most closely associated with the OS of prostate cancer patients, and a column graph model was constructed based on these factors. The Consistency index (C-index) of the model in the training set and the verification set were 0.802 and 0.794, respectively. And the apparent diffusion coefficient (AUC) was 0.851, 0.855 and 0.855 for training sets 1, 3 and 5 years, and 0.694, 0.860 and 0.832 for verification sets 1, 3 and 5 years. The calibration chart showed a good agreement between the predicted and actual values of the model. In the analysis of decision curve, the model showed good clinical application value. CONCLUSION The prediction model based on marital status, radiotherapy, M stage, N stage, PSA and Gleason score for early-onset prostate cancer patients without surgical treatment has certain reference value which is expected to become an effective tool for clinicians to treat in future prospective studies on large and multi-center samples.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Middle Aged ; Nomograms ; SEER Program ; Prognosis ; Adult ; Prostate-Specific Antigen ; Risk Factors ; Proportional Hazards Models ; Neoplasm Grading ; ROC Curve

In recent years, China has continued to face a high prevalence of oral diseases, along with uneven access to high-quality dental care. Against this backdrop, artificial intelligence (AI), as a data-driven, algorithm-supported, and model-centered technology system, has rapidly expanded its role in transforming the landscape of stomatology. This review summarizes recent advances in the application of AI in stomatology across clinical care, biomedical and materials research, education, and hospital management. In clinical settings, AI has improved diagnostic accuracy, streamlined treatment planning, and enhanced surgical precision and efficiency. In research, machine learning has accelerated the identification of disease biomarkers, deepened insights into the oral microbiome, and supported the development of novel biomaterials. In education, AI has enabled the construction of knowledge graphs, facilitated personalized learning, and powered simulation-based training, driving innovation in teaching methodologies. Meanwhile, in hospital operations, intelligent agents based on large language models (LLMs) have been widely deployed for intelligent triage, structured pre-consultations, automated clinical documentation, and quality control, contributing to more standardized and efficient healthcare delivery. Building on these foundations, a multi-agent collaborative framework centered around an AI assistant for stomatology is gradually emerging, integrating task-specific agents for imaging, treatment planning, surgical navigation, follow-up prediction, patient communication, and administrative coordination. Through shared interfaces and unified knowledge systems, these agents support seamless human-AI collaboration across the full continuum of care. Despite these achievements, the broader deployment of AI still faces challenges including data privacy, model robustness, cross-institution generalization, and interpretability. Addressing these issues will require the development of federated learning frameworks, multi-center validation, causal reasoning approaches, and strong ethical governance. With these foundations in place, AI is poised to move from a supportive tool to a trusted partner in advancing accessible, efficient, and high-quality stomatology services in China.
Artificial Intelligence ; Humans ; Oral Medicine/trends* ; China ; Delivery of Health Care ; Machine Learning

OBJECTIVE: To elucidate how spinal manipulative therapy (SMT) exerts its analgesic effects through regulating brain function in lumbar disc herniation (LDH) patients by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: From September 2021 to September 2023, we enrolled LDH patients (LDH group, n=31) and age- and sex-matched healthy controls (HCs, n=28). LDH group underwent rs-fMRI at 2 distinct time points (TPs): prior to the initiation of SMT (TP1) and subsequent to the completion of the SMT sessions (TP2). SMT was administered once every other day for 30 min per session, totally 14 treatment sessions over a span of 4 weeks. HCs did not receive SMT treatment and underwent only one fMRI scan. Additionally, participants in LDH group completed clinical questionnaires on pain using the Visual Analog Scale (VAS) and the Japanese Orthopedic Association (JOA) score, whereas HCs did not undergo clinical scale assessments. The effects on the brain were jointly characterized using the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo). Correlation analyses were conducted between specific brain regions and clinical scales. RESULTS: Following SMT treatment, pain symptoms in LDH patients were notably alleviated and accompanied by evident activation of effects in the brain. In comparison to TP1, TP2 exhibited the most significant increase in ALFF values for Temporal_Sup_R and the most notable decrease in ALFF values for Paracentral_Lobule_L (voxelwise P<0.005; clusters >30; FDR correction). Additionally, the most substantial enhancement in ReHo values was observed for the Cuneus_R, while the most prominent reduction was noted for the Olfactory_R (voxelwise P<0.005; clusters >30; FDR correction). Moreover, a comparative analysis revealed that, in contrast to HCs, LDH patients at TP1 exhibited the most significant increase in ALFF values for Temporal_Pole_Sup_L and the most notable decrease in ALFF values for Frontal_Mid_L (voxelwise P<0.005; clusters >30; FDR correction). Furthermore, the most significant enhancement in ReHo values was observed for Postcentral_L, while the most prominent reduction was identified for ParaHippocampal_L (voxelwise P<0.005; clusters >30; FDR correction). Notably, correlation analysis with clinical scales revealed a robust positive correlation between the Cuneus_R score and the rate of change in the VAS score (r=0.9333, P<0.0001). CONCLUSIONS Long-term chronic lower back pain in patients with LDH manifests significant activation of the "AUN-DMN-S1-SAN" neural circuitry. The visual network, represented by the Cuneus_R, is highly likely to be a key brain network in which the analgesic efficacy of SMT becomes effective in treating LDH patients. (Trial registration No. NCT06277739).
Humans ; Magnetic Resonance Imaging ; Intervertebral Disc Displacement/diagnostic imaging* ; Male ; Female ; Brain/diagnostic imaging* ; Adult ; Manipulation, Spinal/methods* ; Middle Aged ; Lumbar Vertebrae/physiopathology* ; Pain Management ; Rest ; Case-Control Studies

Objective:To observe the clinical progression of low-risk papillary thyroid microcarcinoma（LR-PTMC）, analyze the influencing factors of its oncological outcomes, and explore the feasibility of active surveillance（AS） of LR-PTMC. Methods:This study adopted a prospective observational research design. A total of 85 subjects diagnosed with LR-PTMC during health checkup in Health Management Center of our hospital from March 2021 to October 2022 were enrolled as the research subjects, for at least 2 years of AS follow-up observation. The clinical progress and oncological outcomes were recorded, disease progression was defined as any increase in nodule diameter ≥3 mm or the appearance of new lesions or lymph node metastasis or distant metastasis, and the oncological outcome was use disease progression defining. Cox proportional hazards regression model was used to analyze the influencing factors of oncological outcomes in LR-PTMC patients. Results:A total of 85 LR-PTMC patients who underwent physical examinations were included in this study. The median follow-up time was 2 years, and a total of 23 patients（27.06%） experienced disease progression. Among them, 18 patients（21.18%） had enlarged lesions（any nodule diameter increased by ≥3 mm）, and 5 patients（5.88%） had abnormal or metastatic cervical lymph nodes. The 2-year cumulative disease progression rate was 9.41%. The incidence age of LR-PTMC patients was younger, with a higher proportion of ≤45 years old. The proportion of baseline nodules with a maximum diameter greater than 5 mm is higher, and the proportion of baseline TPO Ab positivity was higher. Ultrasound showed a higher proportion of microcalcifications compared to the non progression group, and the differences were statistically significant（all P<0.05）. Multivariate Cox proportional hazards regression analysis showed that age of onset ≤45 years RR 95% CI 1.052（1.018-1.088） and ultrasound showing microcalcifications RR 95% CI 3.361（1.379-8.194） were independent risk factors affecting disease progression during AS in LR-PTMC patients（P<0.05）. Conclusion:Most LR-PTMC patients maintain stable lesion size and low lymph node metastasis rate during the AS process, with good oncological outcomes in the short term. AS can be considered as a safe and effective alternative to surgical treatment for LR-PTMC patients. But for patients with onset age ≤45 years and microcalcifications, the follow-up interval can be shortened for close observation.
Humans ; Thyroid Neoplasms/pathology* ; Disease Progression ; Prospective Studies ; Carcinoma, Papillary/pathology* ; Female ; Male ; Middle Aged ; Adult ; Watchful Waiting ; Lymphatic Metastasis ; Proportional Hazards Models ; Risk Factors

OBJECTIVES: To analyze the differences in the prognosis of gastric signet ring cell carcinoma (SRCC) among different races using the US Surveillance Epidemiology and End Results (SEER) database and The Cancer Genome Atlas (TCGA) database. METHODS: We analyzed the data of patients with gastric SRCC from the SEER database from 2000 to 2020, and divided the patients into cohorts of whites, blacks, Asians or Pacific Islanders, American Indians/Alaska Natives according to their race. The prognosis and treatment of the cohorts were evaluated using baseline demographic analysis, Kamplan-Meier survival curve, and nomogram analysis. RESULTS: We analyzed the data of a total of 2058 patients, including 8.6% blacks, 72.4% whites, 16.6% Asians or Pacific Islanders, 1.0% American Indians/Alaska Natives, and 1.4% other races. The tumor grade varied among different races, and the prevalence and survival rates of patients differed significantly across races. The differences in the white cohort were the most prominent, and all the differences were statistically significant (P<0.05). Racial differences were also noted in patient management and prognosis. CONCLUSIONS There are racial differences in tumor grades and prognosis of gastric SRCC, and these differences provide evidence for optimizing clinical diagnosis and treatment strategies for this malignancy.
Aged ; Female ; Humans ; Male ; Middle Aged ; Carcinoma, Signet Ring Cell/therapy* ; Databases, Factual ; Prognosis ; Racial Groups ; SEER Program ; Stomach Neoplasms/therapy* ; Survival Rate ; United States/epidemiology* ; White ; Asian American Native Hawaiian and Pacific Islander ; American Indian or Alaska Native ; Black or African American