Machine learning models using symptoms and clinical variables to predict coronary artery disease on coronary angiography.

Introduction: Coronary angiography (CAG) is invasive and expensive, while numbers of patients suspected of coronary artery disease (CAD) undergoing CAG results have no coronary lesions. Aim: To develop machine learning algorithms using symptoms and clinical variables to predict CAD. Material and methods: This study was conducted as a cross-sectional study of patients undergoing CAG. We randomly chose 2082 patients from 2602 patients suspected of CAD as the training set, and 520 patients as the test set. We utilized LASSO regression to do feature selection. The area under the receiver operating characteristic curve (AUC), confusion matrix of different thresholds, positive predictive value (PPV) and negative predictive value (NPV) were shown. Support vector machine algorithm performances in 10 folds were conducted in the training set for detecting severe CAD, while XGBoost algorithm performances were conducted in the test set for detecting severe CAD. Results: The algorithm of logistic regression achieved an average AUC of 0.77 in the training set during 10-fold validation and an AUC of 0.75 in the test set. When probability predicted by the model was less than 0.1, 11 patients in the test set (520 patients) were screened out, and NPV reached 90.9%. When probability predicted by the model was less than 0.2, 110 patients in the test set were screened out, and reached 83.6%. Meanwhile, when threshold was set to 0.9, PPV reached 97.4%. When the threshold was set to 0.8, PPV reached 91.5%. Conclusions: Machine learning algorithm using data from hospital information systems could assist in severe CAD exclusion and confirmation, and thus help patients avoid unnecessary CAG.

Factors impacting clinical data and documentation quality in Australian aged care and disability services: a user-centred perspective.

BACKGROUND: Research has highlighted a need to improve the quality of clinical documentation and data within aged care and disability services in Australia to support improved regulatory reporting and ensure quality and safety of services. However, the specific causes of data quality issues within aged care and disability services and solutions for optimisation are not well understood. OBJECTIVES: This study explored aged care and disability workforce (referred to as 'data-users') experiences and perceived root causes of clinical data quality issues at a large aged care and disability services provider in Western Australia, to inform optimisation solutions. METHODS: A purposive sample of n = 135 aged care and disability staff (including community-based and residential-based) in clinical, care, administrative and/or management roles participated in semi-structured interviews and web-based surveys. Data were analysed using an inductive thematic analysis method, where themes and subthemes were derived. RESULTS: Eight overarching causes of data and documentation quality issues were identified: (1) staff-related challenges, (2) education and training, (3) external barriers, (4) operational guidelines and procedures, (5) organisational practices and culture, (6) technological infrastructure, (7) systems design limitations, and (8) systems configuration-related challenges. CONCLUSION: The quality of clinical data and documentation within aged care and disability services is influenced by a complex interplay of internal and external factors. Coordinated and collaborative effort is required between service providers and the wider sector to identify behavioural and technical optimisation solutions to support safe and high-quality care and improved regulatory reporting.

Does the health information system in Jordan support equity to improve health outcomes? Assessment and recommendations.

BACKGROUND: This study is based on extensive evidence-based assessments. The aim of this paper is to evaluate how well Jordan's health information system (HIS) incorporates social determinants of health inequity (SDHI) and to propose suggestions for future actions. METHODS: An extensive evidence-based assessment was performed. A meta-synthesis of the inclusion of the SDHI in the HIS in Jordan was conducted. After searching and shortlisting, 23 papers were analyzed using Atlas.ti 9.0 employing thematic analysis technique. RESULTS: The HIS in Jordan is quite comprehensive, comprising numerous data sources, various types of information, and data from multiple producers and managers. Nevertheless, the HIS confronts several obstacles and fails to ensure the timely and secure publication of available data. The assessment of the inclusion of the SDHI in the HIS showed that the HIS allows for the measurement of progress in relation to social policies and actions but has a very limited database for supporting the inclusion of health inequity measures. One reason for the difficulty in identifying fairness is that certain crucial information necessary for this task cannot be obtained through the available institutional HIS or population survey tools. Additionally, relevant modules for fairness may be missing from population surveys, possibly due to a failure to fully utilize the capabilities of the institutional HIS. CONCLUSION: There are opportunities to make use of Jordan's dedication to fairness and its already established strong HIS. Some social determinants of health exist in the HIS, but much more data, information, and effort are needed to integrate the SDHI into the Jordanian HIS. A proposal from a regional initiative has put forward a comprehensive set of indicators for integrating SDHI into HIS, which could aid in achieving health equity in Jordan.

[From comprehensive geriatric assessment to an integrated multidimensional assessment system : interRAI tools and their applications]. / De l'évaluation gériatrique standardisée à un système intégré d'évaluation multidimensionnelle : les outils interRAI et leurs applications.

The multidimensional assessment carried out with interRAI tools constitutes an operationalization of the International Classification of Functioning, Disability and Health (ICF) and is adapted to the specificities of each place of care. From a single assessment, the interRAI approach makes it possible to conduct a multidimensional assessment of functional autonomy and to produce a series of indicators (health, areas of intervention, quality of care and consumption of resources). It helps to identify clinical needs to be the subject of a personalized care plan and the strengths and weaknesses of health organizations to modify the professional practices. Compared to standardized geriatric assessment, interRAI tools consider the person's expectations and resources, offer a universal common language, produce a multidimensional synthesis and facilitate the construction of an integrated information system. The basis for their development is scientificity based on evidence.

Local retail food environment exposure and diet quality in rural and urban adults: A longitudinal analysis of the ORISCAV-LUX cohort study.

Despite growing interest in understanding how food environments shape dietary behaviors, European longitudinal evidence is scarce. We aimed to investigate the associations of 9-year average and change in exposure to local retail food environments with the diet quality of residents in Luxembourg. We used data from 566 adults enrolled in both waves of the nationwide ORISCAV-LUX study (2007-2017). Dietary quality was assessed by the Diet Quality Index-International (DQI-I). Exposure to "healthy" and "less healthy" food outlets was assessed by both absolute and relative GIS-based measurements. The results showed a 56.3% increase in less healthy food outlets over the period. In adjusted linear mixed models, high (vs. low) 9-year average exposure to less healthy food outlets was associated with lower DQI-I, when examining spatial access (ß = -1.25, 95% CI: -2.29, -0.22) and proportions (ß = -1.24, 95% CI: -2.15, -0.33). Stratified analyses showed these associations to be significant only among urban residents. There was no association between change in exposure to less healthy food outlets and DQI-I. Increased exposure to healthy outlets in rural areas, using absolute measurements, was associated with worsened DQI-I. Neighborhood socioeconomic status did not moderate the above associations. Findings suggest that the proliferation of less healthy food outlets may have contributed to the deterioration of the diet quality of urban residents, and support the use of relative measurements to fully capture the healthiness of food environments.

GIS-based spatial analysis for lightning scenario in Bangladesh.

Bangladesh has witnessed alarmingly rising lightning frequency, particularly during pre-monsoon and monsoon seasons. This has resulted in significant annual death tolls from lightning strikes over the past decade. Recognizing this crisis, the country officially declared lightning casualties a natural disaster in 2016. This study delves deeper into the landscape of lightning fatalities and causalities in Bangladesh. Utilizing secondary data sources, this research introduces a unique approach by integrating Bangladesh Meteorological Department (BMD) data and NASA's Lightning Imaging Sensor (LIS) data from the International Space Station's (ISS) Near-real Time (NRT) mission. This combined dataset allows for a more comprehensive analysis. Furthermore, Geographic Information Systems (GIS) was employed to analyze spatial distributions and generate maps. The Inverse Distance Weighted (IDW) interpolation tool was used to create detailed spatial distribution maps of lightning fatalities, thunderstorm days (TSDs), and lightning flash frequency (LFF) across Bangladesh. The analysis revealed that farmers and fishermen were the most vulnerable populations, with the northeastern regions experiencing the highest impact. Sylhet division emerged as the area with the most fatalities, highlighting the northeastern zone's susceptibility. The study also identified monsoons as the period with the highest occurrences of lightning deaths and injuries. By combining innovative data integration and spatial analysis, this study offers valuable insights into the alarming trend of lightning fatalities in Bangladesh. These findings can inform targeted prevention strategies and interventions to safeguard vulnerable populations and communities.

Twenty Years of Progress and the Way Forward: Immunization Registry Information System in Korea.

The National Immunization Program in The Republic of Korea offers mandatory and free vaccinations to children under 12, regulated by the Infectious Disease Prevention and Control Act. Tracking vaccination coverage is crucial for population protection and public health strategies. Since 2002, the Immunization Registry Information System (IRIS) has been used nationwide to capture vaccination data. This study reviewed documents related to IRIS's establishment and development. The Republic of Korea legally supports IRIS's construction and data collection, integrating vaccination data with the Ministry of the Interior and Safety's resident registration to minimize errors. This collaboration also facilitates cost reimbursement and digital registration, promoting wider vaccination coverage. IRIS manages expense claims once vaccination details are logged, and authorized medical institutions can access these records in real-time. Since 2015, the Korea Disease Control and Prevention Agency has been compiling annual data on national vaccination coverage. IRIS also sends automated reminders in 12 languages, reports adverse effects, and issues vaccination certificates. However, IRIS lacks integration between vaccine and disease registries, unlike countries such as England, Denmark, and the Netherlands. Improving integration capabilities could enhance IRIS's support for public health through an integrated information system.

Insider Threats to the Military Health System: A Systematic Background Check of TRICARE West Providers.

Background: To address the pandemic, the Defense Health Agency (DHA) expanded its TRICARE civilian provider network by 30.1%. In 2022, the DHA Annual Report stated that TRICARE's provider directories were only 80% accurate. Unlike Medicare, the DHA does not publicly reveal National Provider Identification (NPI) numbers. As a result, TRICARE's 9.6 million beneficiaries lack the means to verify their doctor's credentials. Since 2013, the Department of Health and Human Services' (HHS) Office of Inspector General (OIG) has excluded 17,706 physicians and other providers from federal health programs due to billing fraud, neglect, drug-related convictions, and other offenses. These providers and their NPIs are included on the OIG's List of Excluded Individuals and Entities (LEIE). Patients who receive care from excluded providers face higher risks of hospitalization and mortality. Objective: We sought to assess the extent to which TRICARE screens health care provider names on their referral website against criminal databases. Methods: Between January 1-31, 2023, we used TRICARE West's provider directory to search for all providers within a 5-mile radius of 798 zip codes (38 per state, ≥10,000 residents each, randomly entered). We then copied and pasted all directory results' first and last names, business names, addresses, phone numbers, fax numbers, degree types, practice specialties, and active or closed statuses into a CSV file. We cross-referenced the search results against US and state databases for medical and criminal misconduct, including the OIG-LEIE and General Services Administration's (GSA) SAM.gov exclusion lists, the HHS Office of Civil Rights Health Insurance Portability and Accountability Act (HIPAA) breach reports, 15 available state Medicaid exclusion lists (state), the International Trade Administration's Consolidated Screening List (CSL), 3 Food and Drug Administration (FDA) debarment lists, the Federal Bureau of Investigation's (FBI) list of January 6 federal defendants, and the OIG-HHS list of fugitives (FUG). Results: Our provider search yielded 111,619 raw results; 54 zip codes contained no data. After removing 72,156 (64.65%) duplicate entries, closed offices, and non-TRICARE West locations, we identified 39,463 active provider names. Within this baseline sample group, there were 2398 (6.08%) total matches against all exclusion and sanction databases, including 2197 on the OIG-LEIE, 2311 on the GSA-SAM.gov list, 2 on the HIPAA list, 54 on the state Medicaid exclusion lists, 69 on the CSL, 3 on the FDA lists, 53 on the FBI list, and 10 on the FUG. Conclusions: TRICARE's civilian provider roster merits further scrutiny by law enforcement. Following the National Institute of Standards and Technology 800, the DHA can mitigate privacy, safety, and security clearance threats by implementing an insider threat management model, robust enforcement of the False Claims Act, and mandatory security risk assessments. These are the views of the author, not the Department of Defense or the US government.

Ambient long-term exposure to organophosphorus pesticides and the human gut microbiome: an observational study.

BACKGROUND: Organophosphorus pesticides (OP) have been associated with various human health conditions. Animal experiments and in-vitro models suggested that OP may also affect the gut microbiota. We examined associations between ambient chronic exposure to OP and gut microbial changes in humans. METHODS: We recruited 190 participants from a community-based epidemiologic study of Parkinson's disease living in a region known for heavy agricultural pesticide use in California. Of these, 61% of participants had Parkinson's disease and their mean age was 72 years. Microbiome and predicted metagenome data were generated by 16S rRNA gene sequencing of fecal samples. Ambient long-term OP exposures were assessed using pesticide application records combined with residential addresses in a geographic information system. We examined gut microbiome differences due to OP exposures, specifically differences in microbial diversity based on the Shannon index and Bray-Curtis dissimilarities, and differential taxa abundance and predicted Metacyc pathway expression relying on regression models and adjusting for potential confounders. RESULTS: OP exposure was not associated with alpha or beta diversity of the gut microbiome. However, the predicted metagenome was sparser and less evenly expressed among those highly exposed to OP (p = 0.04). Additionally, we found that the abundance of two bacterial families, 22 genera, and the predicted expression of 34 Metacyc pathways were associated with long-term OP exposure. These pathways included perturbed processes related to cellular respiration, increased biosynthesis and degradation of compounds related to bacterial wall structure, increased biosynthesis of RNA/DNA precursors, and decreased synthesis of Vitamin B1 and B6. CONCLUSION: In support of previous animal studies and in-vitro findings, our results suggest that ambient chronic OP pesticide exposure alters gut microbiome composition and its predicted metabolism in humans.

Optimizing coal mine planning and design for sustainable development in the context of mass exploitation of coal deposits.

Sustainable mining practices is a concept that embeds the principles of sustainable development into the whole mine life-cycle, from exploration, extraction and processing through to mine closure. The optimization of coal mine planning and the developing a standardized design for its sustainable development is very challenging and requires more effort. The present research attempts to address the conditions of sustainability and necessary measures for sustainable development, thereby providing appropriate solutions for each stage of mining operation besides expressing the necessity of sustainable development integration at different stages of mining life cycle (MLC). The approach of systems engineering is essential to assist the sustainability goals which are integrated with the expected results. Hence a method depending more on systems engineering principles and optimization can be incorporated to attain better results. Several socio-environmental factors associated with sustainability depends on the geographic condition and few mining engineering considerations such as mine location, topography, coal seam characteristics and so on. These systems engineering approach can be further enhanced by incorporating tools like Geographic Information System (GIS), which provides more accuracy and precision of the geographic conditions of the site identified for the coal mining plan. In order to begin this way of approach towards the sustainability development and mining planning, the appropriate optimization parameters should be identified. The outcome of these optimization parameters can be also achieved by optimizing coal mining system models.

Travelling numbers and broken loops: A qualitative systematic review on collecting and reporting maternal and neonatal health data in low-and lower-middle income countries.

Data and indicator estimates are considered vital to document persisting challenges in maternal and newborn health and track progress towards global goals. However, prioritization of standardised, comparable quantitative data can preclude the collection of locally relevant information and pose overwhelming burdens in low-resource settings, with negative effects on the provision of quality of care. A growing body of qualitative studies aims to provide a place-based understanding of the complex processes and human experiences behind the generation and use of maternal and neonatal health data. We conducted a qualitative systematic review exploring how national or international requirements to collect and report data on maternal and neonatal health indicators are perceived and experienced at the sub-national and country level in low-income and lower-middle income countries. We systematically searched six electronic databases for qualitative and mixed-methods studies published between January 2000 and March 2023. Following screening of 4084 records by four reviewers, 47 publications were included in the review. Data were analysed thematically and synthesised from a Complex Adaptive Systems (CAS) theoretical perspective. Our findings show maternal and neonatal health data and indicators are not fixed, neutral entities, but rather outcomes of complex processes. Their collection and uptake is influenced by a multitude of system hardware elements (human resources, relevancy and adequacy of tools, infrastructure, and interoperability) and software elements (incentive systems, supervision and feedback, power and social relations, and accountability). When these components are aligned and sufficiently supportive, data and indicators can be used for positive system adaptivity through performance evaluation, prioritization, learning, and advocacy. Yet shortcomings and broken loops between system components can lead to unforeseen emergent behaviors such as blame, fear, and data manipulation. This review highlights the importance of measurement approaches that prioritize local relevance and feasibility, necessitating participatory approaches to define context-specific measurement objectives and strategies.

Tri-State Evaluation of the Effects of the COVID-19 Pandemic on Routine Vaccine Uptake in Iowa, Minnesota, and North Dakota, 2017-2021.

The objective of this analysis was to evaluate and compare the effects of the COVID-19 pandemic on routine and annual influenza vaccination in Iowa, Minnesota, and North Dakota. Routine and annual influenza vaccination uptake and coverage between 2017 and 2021 was collected from each state's immunization information system (IIS) by age group and stratified by provider and vaccine type. Data from 2017 to 2019 were averaged to obtain a pre-pandemic baseline and compared to 2020 and 2021 data. Percent changes were calculated to evaluate differences in uptake and coverage. Changes in coverage and administration varied by state, but each state had some level of decreased administration across the different age groups and vaccine types. The most consistent decreases in vaccine administration occurred in the 15-year-old cohort with each state finding decreased administrations in 2020 and 2021. The 12-year-old age group had decreased administration of hepatitis B, measles, mumps, and rubella, and varicella vaccine while the 2-year-old age group had the most consistent decrease in coverage across all vaccines analyzed. Trends by provider type were also noted in all three states, with local public health (LPH) experiencing the largest and most consistent declines in vaccine administrations by age group. Adult influenza coverage improved to varying degrees in 2020 (+ 14.1% IA, + 2.1% MN, + 1.5% ND), but either decreased or approached the 2017-19 average in 2021. All three states saw some level of decreased vaccine administration across the age groups, vaccines, and provider types assessed. The COVID-19 pandemic affected how many children and adults received recommended immunizations, leaving communities vulnerable to vaccine-preventable diseases.

The unique identifier as one of the essential tools for steering universal health coverage: The case of Morocco / L'identifiant unique comme un des instruments indispensables au pilotage de la couverture sanitaire universelle, le cas du Maroc.

INTRODUCTION: Morocco is carrying out several actions to generalize basic compulsory health insurance (CHI). Managing this project requires coordination, information sharing, and the commitment of all actors to the goal of covering an additional 22 million people. One of the key factors for achieving this objective is the implementation of a unified registration system. PURPOSE OF THE RESEARCH: The aim is to analyze the existing situation and the feasibility of implementing a unified registration system, and to describe the potential positive impact of the latter on the extension of CHI. RESULTS: This work is based on a diagnosis of the current situation. It draws on the legal framework, all available documents and figures, and on an analytical reading supported by existing literature. It reveals that due to the inadequacy or even the absence of an appropriate legal basis, each managing body has its own registration system. The lack of a unified system has given rise to a number of constraints. These concern, among other things: (i) mobility between or within schemes, which does not operate smoothly because it leads to re-registration (ii) inadequate monitoring of double benefit claims, which is the case for more than one scheme, due to insufficient and hesitant anti-fraud action (iii) the sharing and use of reliable data, which hinders decision making, evaluation, and monitoring. CONCLUSIONS: It is essential to adopt legal texts that will provide the basis for a unified system with regulations enabling the participation of all stakeholders, with the aim of steering the roll-out of CHI effectively and efficiently.

Introduction: Le Maroc mène, depuis quelques années, plusieurs actions permettant de généraliser l'assurance maladie obligatoire (AMO). Le pilotage de ce chantier nécessite la coordination, le partage d'informations et l'engagement de tous les acteurs afin de couvrir 22 millions de personnes supplémentaires. L'un des éléments clés pour optimiser la réalisation de cet objectif consiste à mettre en place un système unifié d'immatriculation. But de l'étude: Analyser l'existant et la faisabilité de la mise en place d'un système unifié d'immatriculation, tout en précisant ses retombées positives sur l'extension de l'AMO. Résultats: Ce travail, fondé sur un diagnostic, appuyé par l'arsenal juridique, des documents et des chiffres disponibles ainsi qu'une lecture analytique renforcée par la littérature existante, a permis de constater que, du fait de l'insuffisance voire l'absence d'un soubassement juridique adapté, chaque organisme gestionnaire a son propre système d'immatriculation. L'absence d'un système unifié gêne notamment : 1) la mobilité entre régimes ou intra-régimes, étant donné qu'elle ne se fait pas de manière fluide car elle génère la ré-immatriculation ; 2) le contrôle du double bénéfice d'un régime insuffisamment organisé et incapable de lutter contre la fraude ; 3) le partage et l'exploitation de données fiables empêchant d'assurer de manière appropriée le suivi, l'évaluation et la prise de décision. Conclusion: Il est indispensable d'adopter des textes juridiques pour fonder un système unifié qui permettra l'encadrement et l'engagement de toutes les parties prenantes dans l'objectif de piloter la généralisation de l'AMO avec efficacité et efficience.

Strengths, Weaknesses, Opportunities, and Threats (SWOT) Analysis of Hemodialysis Electronic Health Record Implementation.

BACKGROUND AND AIM: The Nephrology Department of Hassan II Hospital in Fez, Morocco, has implemented an Electronic Medical Record (EMR) system for managing patients undergoing acute hemodialysis. This initiative aims to digitize patient monitoring and enhance the management of acute dialysis within the department. Conducting strengths, weaknesses, opportunities, and threats (SWOT) analysis - assessing strengths, weaknesses, opportunities, and threats - was crucial to identifying and understanding the internal strengths and weaknesses, as well as the external opportunities and threats. This article outlines the SWOT analysis findings that may impact the project's success and shape decision-making. It also discusses strategies that could be implemented to allocate resources, mitigate risks, and capitalize on potential advantages. MATERIALS AND METHODS: This study involved a multidisciplinary team, including professors, nephrologists, nephrology residents, and a healthcare information system engineer. Brainstorming sessions were held during the specification drafting phase to pinpoint both internal and external factors affecting the project. User feedback during testing further refined these factors, ensuring the project's alignment with real-world needs and challenges. RESULTS: The study identifies the project's strengths as providing safe and immediate access to information, along with strong communication between the department (application users) and the project manager. The significant EMR weakness is the lack of logistical resources and the absence of a long-term maintenance plan for the application. The opportunity presented by this EMR implementation is its functionality's potential to evolve, enabling the solution to be deployed in other dialysis centers across the region. The project's threat is the potential abandonment of EMR use by future practitioners. CONCLUSION: These SWOT analysis findings enable the development and implementation of strategies to reduce the current deployment's vulnerabilities and ensure the success of future HIS implementations in the nephrology network of the Fez-Meknes region, Morocco.

BBDash: An Electron-based tool for analyzing blood product utilization.

Blood transfusions can be associated with side effects ranging from occasional febrile reactions to extremely rare fatal reactions. Monitoring blood product orders and ensuring appropriate utilization is therefore an important strategy to ensure patient safety. However, data extracted from laboratory information systems can be difficult to interpret. We created BBDash, an Electron-based tool that reads Sunquest reports to create easy-to-interpret graphs related to blood product utilization.

Utility of PROMIS Measures in Predicting Shoulder Arthroplasty in Patients with Shoulder Osteoarthritis.

BACKGROUND: The decision to treat shoulder osteoarthritis definitively with shoulder arthroplasty (SA) is multifactorial, considering objective findings, subjective information, and patient goals. The first goal of this study was to determine if Patient Reported Outcome Measurement Information System (PROMIS) measures correlated with patients with shoulder osteoarthritis (OA) who underwent SA within 1 year. The second goal of this study was to determine if score cut-offs in PROMIS domains could further discriminate which shoulder OA patients underwent SA within 1 year. METHODS: This retrospective case-control study examined patients with a diagnosis of shoulder OA who consulted an orthopedic provider from November 1, 2020, to May 23, 2022, and recorded PROMIS measures in the domains of Physical Function (PF), Depression, and/or Pain Interference (PI). A surgical group was defined as patients who underwent SA within 1 year of the most recent PROMIS measures, and the non-surgical patients were defined as the control group. Mean PROMIS scores were compared between the surgical and control groups. Separate logistic regression models controlling for age, race, ethnicity, and comorbidity count were performed for each PROMIS domain as a 1) continuous variable, then as 2) binary variable defined by PROMIS score cut-off points to determine which scores correlated with undergoing SA to further characterize the potential clinical utility of PROMIS score cut-offs in relating to undergoing SA. RESULTS: The surgical group of 478 patients was older (68.2 vs. 63.8 years), more often of White race (82.6% vs. 70.9%), and less often of Hispanic Ethnicity (1.5% vs. 2.9%) than the control group of 3343 patients. Using optimal cut-offs in PROMIS scores, PI ≥ 63 (Odds Ratio (OR) = 2.97 (2.41-3.64), p < 0.001), PF ≤ 39 (OR = 1.81 (95% CI, 1.48-2.22), p < 0.001), and Depression ≥ 49 (OR = 1.82 (95% CI, 1.50-2.22), p < 0.001) were all found to correlate with undergoing SA within 1 year in multivariable logistic regressions. CONCLUSION: The results of this study demonstrate that cut-off scores for PROMIS measures differentiated patients undergoing SA within 1 year. These cut-off scores may have clinical utility in aiding in decision-making regarding surgical candidates for SA. Further research is needed to validate these cut-off scores and determine how they relate to patient outcomes after SA.

A super SDM (species distribution model) 'in the cloud' for better habitat-association inference with a 'big data' application of the Great Gray Owl for Alaska.

The currently available distribution and range maps for the Great Grey Owl (GGOW; Strix nebulosa) are ambiguous, contradictory, imprecise, outdated, often hand-drawn and thus not quantified, not based on data or scientific. In this study, we present a proof of concept with a biological application for technical and biological workflow progress on latest global open access 'Big Data' sharing, Open-source methods of R and geographic information systems (OGIS and QGIS) assessed with six recent multi-evidence citizen-science sightings of the GGOW. This proposed workflow can be applied for quantified inference for any species-habitat model such as typically applied with species distribution models (SDMs). Using Random Forest-an ensemble-type model of Machine Learning following Leo Breiman's approach of inference from predictions-we present a Super SDM for GGOWs in Alaska running on Oracle Cloud Infrastructure (OCI). These Super SDMs were based on best publicly available data (410 occurrences + 1% new assessment sightings) and over 100 environmental GIS habitat predictors ('Big Data'). The compiled global open access data and the associated workflow overcome for the first time the limitations of traditionally used PC and laptops. It breaks new ground and has real-world implications for conservation and land management for GGOW, for Alaska, and for other species worldwide as a 'new' baseline. As this research field remains dynamic, Super SDMs can have limits, are not the ultimate and final statement on species-habitat associations yet, but they summarize all publicly available data and information on a topic in a quantified and testable fashion allowing fine-tuning and improvements as needed. At minimum, they allow for low-cost rapid assessment and a great leap forward to be more ecological and inclusive of all information at-hand. Using GGOWs, here we aim to correct the perception of this species towards a more inclusive, holistic, and scientifically correct assessment of this urban-adapted owl in the Anthropocene, rather than a mysterious wilderness-inhabiting species (aka 'Phantom of the North'). Such a Super SDM was never created for any bird species before and opens new perspectives for impact assessment policy and global sustainability.

A Mobile App (Concerto) to Empower Hospitalized Patients in a Swiss University Hospital: Development, Design, and Implementation Report.

BACKGROUND: Patient empowerment can be associated with better health outcomes, especially in the management of chronic diseases. Digital health has the potential to promote patient empowerment. OBJECTIVE: Concerto is a mobile app designed to promote patient empowerment in an in-patient setting. This implementation report focuses on the lessons learned during its implementation. METHODS: The app was conceptualized and prototyped during a hackathon. Concerto uses hospital information system (HIS) data to offer the following key functionalities: a care schedule, targeted medical information, practical information, information about the on-duty care team, and a medical round preparation module. Funding was obtained following a feasibility study, and the app was developed and implemented in four pilot divisions of a Swiss University Hospital using institution-owned tablets. IMPLEMENTATION (RESULTS): The project lasted for 2 years with effective implementation in the four pilot divisions and was maintained within budget. The induced workload on caregivers impaired project sustainability and warranted a change in our implementation strategy. The presence of a killer function would have facilitated the deployment. Furthermore, our experience is in line with the well-accepted need for both high-quality user training and a suitable selection of superusers. Finally, by presenting HIS data directly to the patient, Concerto highlighted the data that are not fit for purpose and triggered data curation and standardization initiatives. CONCLUSIONS: This implementation report presents a real-world example of designing, developing, and implementing a patient-empowering mobile app in a university hospital in-patient setting with a particular focus on the lessons learned. One limitation of the study is the lack of definition of a "key success" indicator.

Data Sharing in a Decentralized Public Health System: Lessons From COVID-19 Syndromic Surveillance.

The COVID-19 pandemic revealed that data sharing challenges persist across public health information systems. We examine the specific challenges in sharing syndromic surveillance data between state, local, and federal partners. These challenges are complicated by US federalism, which decentralizes public health response and creates friction between different government units. The current policies restrict federal access to state and local syndromic surveillance data without each jurisdiction's consent. These policies frustrate legitimate federal governmental interests and are contrary to ethical guidelines for public health data sharing. Nevertheless, state and local public health agencies must continue to play a central role as there are important risks in interpreting syndromic surveillance data without understanding local contexts. Policies establishing a collaborative framework will be needed to support data sharing between federal, state, and local partners. A collaborative framework would be enhanced by a governance group with robust state and local involvement and policy guardrails to ensure the use of data is appropriate. These policy and relational challenges must be addressed to actualize a truly national public health information system.

Outcomes and Costs of the Transition From a Paper-Based Immunization System to a Digital Immunization System in Vietnam: Mixed Methods Study.

BACKGROUND: The electronic National Immunization Information System (NIIS) was introduced nationwide in Vietnam in 2017. Health workers were expected to use the NIIS alongside the legacy paper-based system. Starting in 2018, Hanoi and Son La provinces transitioned to paperless reporting. Interventions to support this transition included data guidelines and training, internet-based data review meetings, and additional supportive supervision visits. OBJECTIVE: This study aims to assess (1) changes in NIIS data quality and use, (2) changes in immunization program outcomes, and (3) the economic costs of using the NIIS versus the traditional paper system. METHODS: This mixed methods study took place in Hanoi and Son La provinces. It aimed to analyses pre- and postintervention data from various sources including the NIIS; household and health facility surveys; and interviews to measure NIIS data quality, data use, and immunization program outcomes. Financial data were collected at the national, provincial, district, and health facility levels through record review and interviews. An activity-based costing approach was conducted from a health system perspective. RESULTS: NIIS data timeliness significantly improved from pre- to postintervention in both provinces. For example, the mean number of days from birth date to NIIS registration before and after intervention dropped from 18.6 (SD 65.5) to 5.7 (SD 31.4) days in Hanoi (P<.001) and from 36.1 (SD 94.2) to 11.7 (40.1) days in Son La (P<.001). Data from Son La showed that the completeness and accuracy improved, while Hanoi exhibited mixed results, possibly influenced by the COVID-19 pandemic. Data use improved; at postintervention, 100% (667/667) of facilities in both provinces used NIIS data for activities beyond monthly reporting compared with 34.8% (202/580) in Hanoi and 29.4% (55/187) in Son La at preintervention. Across nearly all antigens, the percentage of children who received the vaccine on time was higher in the postintervention cohort compared with the preintervention cohort. Up-front costs associated with developing and deploying the NIIS were estimated at US $0.48 per child in the study provinces. The commune health center level showed cost savings from changing from the paper system to the NIIS, mainly driven by human resource time savings. At the administrative level, incremental costs resulted from changing from the paper system to the NIIS, as some costs increased, such as labor costs for supportive supervision and additional capital costs for equipment associated with the NIIS. CONCLUSIONS: The Hanoi and Son La provinces successfully transitioned to paperless reporting while maintaining or improving NIIS data quality and data use. However, improvements in data quality were not associated with improvements in the immunization program outcomes in both provinces. The COVID-19 pandemic likely had a negative influence on immunization program outcomes, particularly in Hanoi. These improvements entail up-front financial costs.