Minimum Data Set Research Articles

Applicability of soil health assessment dominated by biological indicators in facility agriculture

The minimum data set (MDS) is widely used for soil health index (SHI) assessment, with the selection of indicators being crucial. However, biological indicators are less frequently used compared to physical and chemical indicators. This study aimed to establish a biologically-centered MDS for assessing soil health in tomato facility agriculture in Ningbo. Using biochemical, microbiological, and nematode data from 60 continuous cropping soils, we identified key indicators for the MDS. Principal component analysis revealed a strong correlation between the MDS and the total data set (TDS), with the final MDS including available phosphorus, electrical conductivity, β-glucosidase, urease, bacterial Chao1 index, bacterial Shannon index, Ralstonia solanacearum, nematode Shannon index, structure index, and channel index. Random forest modeling showed that the predicted SHI had a high fit with the MDS-SHI, with bacterial and nematode Shannon indices being the most influential predictors, emphasizing the critical role of biological communities in maintaining soil health. Furthermore, the study identified three distinct phases in soil health during long-term continuous cropping: healthy (0–10 years), sub-healthy (11–15 years), and recovery (16–20 years), demonstrating the soil's potential for self-recovery. By incorporating biodiversity as a core component, this biologically-focused MDS provides a more comprehensive and precise method for evaluating soil health in facility agriculture. The findings suggest that this MDS could inform future research and applications in similar agricultural systems. Moreover, the results highlight the vital role of biodiversity in agroecosystem stability, suggesting that future soil health assessments should place greater emphasis on biological indicators to better capture the complexity of soil functions.

What imaging does my AIS patient need? A multi-group survey of provider preferences.

Adolescent idiopathic scoliosis (AIS) is a common diagnosis managed by pediatric orthopedic surgeons with nonoperative radiographic monitoring representing a cornerstone of treatment. Differences in practices and techniques for obtaining radiographic studies contribute to variation, cost of care, and hamper data aggregation. We surveyed several large organizations dedicated to children's orthopedics or scoliosis care to obtain a consensus for radiographic evaluation of AIS. A REDCap-based survey was developed across four institutions and beta-tested by staff and fellows from a single institution. The finalized survey was distributed to members of POSNA, PSSG, and SOSORT, and shared on social media. Participants were asked to rank the importance of various datapoints in radiographic assessment of the spinal deformity, skeletal maturity, and study indications during initial, subsequent, preoperative, and final office visits for AIS. Response rate for the overall group was 26%. Cobb angle was considered the most important (> 94%) radiographic index across all time points. For positioning, 46% of respondents favored arms bent touching clavicles as the ideal positioning for X-rays, and another 24% favored arms down with palms forward (Table2). The majority of respondents obtain lateral X-rays at the first visit (99%) and at the preoperative visit (70%). At the preoperative visit, sagittal contour (86%), apex location (85%), and Lenke classification (73%) were considered important factors to record. Flexibility studies are primarily obtained at the preoperative visit (89%) and 81% of respondents prefer bending films as the flexibility technique of choice. Regarding measures of skeletal maturity, Sanders bone age was considered to be the most important by over 70% of respondents across initial, subsequent, preoperative and brace wean visits (Fig.2). MRIs were obtained routinely by 34% of respondents and only when the patient had a concerning symptom or finding for 67% of respondents. Despite large variations in radiographic examination of AIS, large areas of agreement were found. It is important to establish standards for positioning patients, evaluating skeletal maturity, and obtaining assessments including lateral views, flexibility studies, and advanced imaging. Establishing common practices for radiographic evaluation of AIS will allow for less variation in care and for critical questions to be answered through registry formation and large multicenter data collection. This study establishes current practitioner opinion on the radiographic evaluation of the AIS patient. Minimum data sets are useful for data aggregation and answering research questions in the face of data variability. Level V.

Transfers Among Vulnerable Long-Term Nursing Home Residents

ObjectivesTo determine whether the risk of nursing home-to-nursing home transfer is higher among long-term nursing home residents with intellectual and developmental disabilities (IDD), or serious mental illness (SMI), and/or Alzheimer's disease and related dementias (ADRD), relative to residents without these clinical diagnoses, and to assess the factors associated with transfer overall and for residents with these diagnoses. DesignCross-sectional cohort study of nursing home residents in 2019. Setting and ParticipantsMichigan long-term nursing home residents identified from the Minimum Data Set. MethodsResidents who had a nursing home-to-nursing home transfer were allocated into 5 groups: IDD, SMI and ADRD, ADRD, SMI, and all others. We examined transfer rates for each group. We assessed the odds of transfer for each group, adjusting for resident and nursing home characteristics, and behavioral issue and clinical indicators. We used stratified logistic regression to determine factors associated with transfers within each group. ResultsAmong 37,638 long-term nursing home residents, 2.3% had a nursing home-to-nursing home transfer. Transfers varied across diagnosis groups: 1.9% in IDD, 2.8% in SMI and ADRD, 1.9% in ADRD, 2.6% in SMI, and 2.5% in all others. After adjustment, residents in the SMI and ADRD group were 39% more likely to transfer than those in the all others group (adjusted odds ratio, 1.39; 95% CI, 1.14–1.68). Age ≥75 years, moderate to severe cognitive impairment, and falls were associated with a lower odds of transfer. Being married and wandering were associated with a higher odds of transfer. Factors associated with transfers varied within each group. Conclusions and ImplicationsAmong Michigan long-term nursing home residents, residents with both SMI and ADRD are at the highest risk for transfer to another nursing home when compared with residents with SMI or ADRD alone and with IDD and none of these diagnoses. Understanding the drivers of transfer of this vulnerable group warrants further investigation.

Minimum Dataset of Lung Cancer Patients: An Initial Step Towards Developing a Web-Based Personal Health Record

Background: Personal Health Records (PHR), which utilize advanced health information technology tools, play a crucial role in patient self-management and improving the control of chronic diseases such as lung cancer. To optimize the design of these systems, it is essential to determine the necessary data elements. Objectives: This study aims to identify the minimum dataset required for designing a web-based PHR for lung cancer patients. Methods: This descriptive, cross-sectional research was conducted in 2023. Initially, a lung cancer dataset was extracted through text analysis. In the next phase, a proposed minimum lung cancer dataset was formulated into a questionnaire containing 18 data groups, including 126 data elements. The dataset underwent expert validation in two phases using the Delphi technique. Data analysis was performed using SPSS version 26, with descriptive statistics employed. Results: The minimum web-based PHR dataset for lung cancer patients, consisting of 18 data groups (112 data elements), includes demographics, insurance information, emergency contact details, patient symptoms, tumor-related data, physician details, treatment information, patient-reported measurements, personal medical history, history of procedures and surgeries, visits, allergies, family history, medication information, test results, imaging data, dietary information, and educational materials. Conclusions: Based on the study findings, it is recommended that lung cancer data management encompass not only routine information but also additional dimensions such as allergies, tumor-related information, and dietary details. Collecting comprehensive and complete data can significantly enhance the treatment process and post-treatment follow-up.

Advancing Dementia Care in Austria: developing a Dementia Registry using a multimethod approach

Abstract Background Austria faces an increasing demand for dementia care in an ageing population. However, a lack of representative data hampers evidence-based policy development and evaluation of care. To address this gap, the Austrian National Institute of Public Health is undertaking the task of developing the Austrian Dementia Quality Registry (ÖDQR). Methods Based on the AIHTA Good Practice Framework for Dementia Registries, the development and testing of the ÖDQR has unfolded in 4 distinct phases: 1) planning; 2) registry design (including definition of quality indicators and minimum data set, recruitment, and governance); 3) definition of data collection, sources, and management; 4) pilot testing. A steering committee of government representatives and dementia care experts was convened to oversee the project. A scientific committee provided oversight and ensured methodological rigor. Working groups of national and international dementia care experts focused on standards for diagnosis and therapy, activities of daily living and quality of life, legal aspects, and technical implementation, thus contributing to the content development of the ÖDQR. Results An initial systematic literature review informed the selection of quality indicators in the working groups. A conceptual framework of 15 descriptive and 30 quality indicators was developed. Preliminary results of pilot testing indicate feasibility and content validity. As a result, the ÖDQR will be established as a longitudinal survey-based registry, based on an instrument comprising 163 variables and emphasizing data collection across care settings. Legal and technical frameworks are being developed. Conclusions The öDQR holds the promise of informing evidence-based policy and improving the quality of dementia care in Austria. Careful planning and collaboration have laid the foundation for a data repository that will inform policy and improve care for people with dementia and their caregivers. Key messages • Dementia registries require a complex development to assure validity and adherence. • The Austrian Dementia Registry aims to establish best practice by focusing on the life situation of those affected by this condition.

The HEROES (HEalth woRkfOrcE to meet health challengeS) Joint Action

Abstract Background The HEROES (HEalth woRkfOrcE to meet health challengeS) Joint Action aims to advance health workforce planning across the EU, addressing the pressing need for a resilient, sustainable, and accessible health service systems. Given the evident strain on health systems demonstrated during the COVID-19 pandemic, this initiative seeks to address the critical need for strategic HWF planning. Building on previous projects, HEROES will foster the capacity of EU states in workforce planning, preparing the health systems to meet future challenges. Methods The study adopts a collaborative framework involving 19 EU countries, segmented into clusters based on health system characteristics. A stepwise approach (‘AS IS,’ ‘TO BE,’ ‘TO DO’) characterizes the methodology, incorporating extensive data collection, stakeholder engagement, and scenario forecasting. Country-level information on HWF Data and Planning will be compared both across countries in clusters and across clusters. Results Initial findings indicate significant disparities in health workforce data quality, availability, and planning methodologies among the states. Identified methodologies also involve real-world data applications and predictive analytics to refine health workforce planning. Efforts are underway to define an Advanced Minimum Dataset (AMDS) to synchronize health workforce data and define planning tools across the clusters, as country-level AS IS reports have been finalized and cross-country comparisons are ongoing. Conclusions Collaborative, data-driven health workforce planning can significantly enhance health system resilience and responsiveness. Recommended public health actions include enhancing HWF data integration, forecasting capabilities, and stakeholder participation, with the aim of shaping national health policies and practices. The public health impact is profound, as it allows to improve health service delivery and workforce adaptability in response to dynamic health demands. Key messages • The HEROES Joint Action advances EU health workforce planning, with the aim of enhancing the resilience and responsiveness of health systems. • Strategic data-driven approaches in health workforce planning are pivotal for resilient, accessible and sustainable healthcare systems.

Cultivated Land Quality Assessment and Obstacle Factors Diagnosis in Changtu County, Northeast China

ABSTRACTEffective evaluation of cultivated land quality is crucial for sustainable agricultural management. Existing research often focuses on regional scales and lacks sufficient detailed analysis of spatial distribution and limiting factors at localized scales. This study aims to select the key indicators to evaluate cultivated land quality and analyze their influence on cultivated land quality at the county level. Taking Changtu County as the research area, principal component analysis (PCA) was employed to identify the most effective Minimum Data Set (MDS) for evaluation, including cultivated layer thickness, soil organic matter (SOM), pH, bulk density (BD), and cultivated layer texture. Additionally, an obstacle degree model was used to analyze restricting factors and their degrees of impact. Results showed that the constructed MDS could replace all indicators for cultivated land quality evaluation. Quality was higher in central areas and lower in eastern and western regions. SOM content decreases with the decrease of quality grade, significantly affecting the quality distribution, and pH in the medium category (Grades III and VI) cultivated lands were lower compared to other categories. Low organic matter content and low pH levels were the main obstacles affecting cultivated land quality, with average obstacle degrees of 43.5% and 29.3%, respectively. Low SOM content significantly affected land quality, particularly in the western region, whereas acidic soils in the eastern region influenced quality grade distribution. Thus, strategies for pH control and SOM enhancement are essential for improving cultivated land quality. This study provides valuable insights into sustainable agriculture.

A simplified method for theoretical sum frequency generation spectroscopy calculation and interpretation: The "pop model".

Existing methods to compute theoretical spectra are restricted to the use of time-correlation functions evaluated from accurate atomistic molecular dynamics simulations, often at the abinitio level. The molecular interpretation of the computed spectra requires additional steps to deconvolve the spectroscopic contributions from local water and surface structural populations at the interface. The lack of a standard procedure to do this often hampers rationalization. To overcome these challenges, we rewrite the equations for spectra calculation into a sum of partial contributions from interfacial populations, weighted by their abundance at the interface. We show that SFG signatures from each population can be parameterized into a minimum dataset of reference partial spectra. Accurate spectra can then be predicted by just evaluating the statistics of interfacial populations, which can be done even with force field simulations as well as with analytic models. This approach broadens the range of simulation techniques from which theoretical spectra can be calculated, opening toward non-atomistic and Monte Carlo simulation approaches. Most notably, it allows constructing accurate theoretical spectra for interfacial conditions that cannot even be simulated, as we demonstrate for the pH-dependent SFG spectra of silica/water interfaces.

THE FIGHT INHERITED RETINAL BLINDNESS! PROJECT: A NEW TREATMENT OUTCOME AND NATURAL HISTORY REGISTRY FOR INHERITED RETINAL DISEASE.

To design and build a new disease registry to track the natural history and outcomes of approved gene therapy in patients with inherited retinal diseases (IRDs). A core committee of 6 members was convened to oversee the construction of the FIRB! module. A further 11 experts formed a steering committee, which discussed disease classification and variables to form minimum datasets via a consensus approach. The web-based FIRB! registry records baseline demographic, clinical and genetic data together with follow-up data. The Human Phenotype Ontology and Monarch Disease Ontology nomenclature were incorporated within the FIRB! architecture to standardise nomenclature. The registry software assigns individual diagnoses to one of 7 broad phenotypic groups, with minimum datasets dependent upon the broad phenotypic group. Additionally, minimum datasets were agreed upon for patients undergoing approved gene therapy with voretigene neparvovec (Luxturna). New patient entries can be completed in 5 minutes, and follow-up data can be entered in 2 minutes. Fight Inherited Retinal Blindness! (FIRB!) is an organized, web-based system that uses observational study methods to collect uniform data from IRD patients to track natural history and (uniquely) treatment outcomes. It is free to Users, who have control over their data.

Exploring the Association between Complexity of Care, Medical Complexity, and Length of Stay in the Paediatric Setting Using a Nursing Minimum Data Set: A Study Protocol.

The complexity of care requires systematic documentation to fully understand its relationship with medical complexity and its impact on patient outcomes. The Nursing Minimum Data Set (NMDS) plays a crucial role by capturing essential nursing data, enabling a detailed analysis of care and its impact on outcomes, such as length of stay (LOS). However, despite its potential, the use of NMDS in paediatric care remains limited. This study aims to explore the association between nursing and medical complexities and LOS in paediatric patients. A descriptive, retrospective, monocentric study will be conducted. The data will be collected through a nursing information system (Professional Assessment Instrument (PAIped)) and the hospital discharge register of patients admitted to the paediatric department in 2022 in an Italian university hospital. Conclusions and Expected Results: The use of PAIped will allow for the description of the complexity of care and enable an analysis of its relationship with medical complexity and LOS.

A model to increase care delivery in nursing homes: The role of Institutional Special Needs Plans.

To estimate differences in facility-level outcomes between nursing homes which reached Institutional Special Needs Plan (I-SNP) maturity and those which never cared for I-SNP enrollees. We used a difference-in-differences design to estimate the effect of I-SNP maturity, defined as having at least 33.75% of Medicare long-stayers in the nursing home enrolled in any I-SNP. Our main outcome was the hospitalization rate in each nursing home-year. Secondary outcomes included the share of residents with medication use, fall, urinary tract infection, catheter insertion, pressure ulcer, physical restraint use, increased need for help with activities of daily living (ADLs), and mortality. This repeated cross-sectional study used 100% Medicare claims, Minimum Data Set assessments, and publicly available Medicare Advantage (MA) plan characteristics data (2004-2021). We included all MA beneficiaries who resided in US nursing homes which reached I-SNP maturity and those without I-SNP enrollees. We identified 2530 nursing homes which reached I-SNP maturity (treated) and 9830 nursing homes without I-SNP enrollees (untreated). There were some differences observed between these nursing homes, including shares of residents who were White (76.42% vs. 84.84%) and on Medicaid (66.94% vs. 55.45%). These nursing homes were also larger on average (141.76 beds vs. 87.56 beds). From the difference-in-differences model, nursing homes which reached I-SNP maturity experienced declines of 4.1 percentage points (pp) for hospitalizations, 1.0 pp for pressure ulcers, 1.3 pp for urinary tract infections (p < 0.001) alongside increases in the need for help with ADLs, use of antipsychotics, falls, and physical restraints. Nursing homes which reached I-SNP maturity experienced fewer hospitalizations and pressure ulcers but a decline in function and increase in other negative outcomes. I-SNPs may be a promising model to improve care for long-stay residents, but more research is needed to understand potential adverse consequences.

Spatial Heterogeneity of Soil Nutrient in Principal Paddy and Cereal Production Landscapes of Fengtai County within the Huai River Basin, Eastern China

The problem of cultivated land soil quality in the Huaihe River Basin has become increasingly prominent. How to accurately and quantitatively evaluate the soil quality of regional cultivated land and realize its efficient use has become an urgent problem. In order to explore the spatial autocorrelation and variation in soil nutrients in cultivated land in the plain of Fengtai County in the Huaihe River Basin, a total of 306 soil samples and mature wheat samples were collected in the study area to analyze soil pH, total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), available potassium (AK) and slow-release potassium (SK) content and wheat biomass, and combined with geostatistical methods and GIS technology. The Kriging interpolation method and Moram‘s I index method were systematically analyzed. Principal component analysis (PCA) and Pearson correlation analysis were used to establish the minimum data set (MDS) of soil quality, which was used to calculate the soil quality index (SQI) and determine the key factors affecting soil quality. The results showed that the soil pH was in weak variation, and the other nutrient indexes were in medium variation. The spatial variability of soil-available potassium nutrients was affected by random factors such as human activities and structural factors such as soil parent materials. The spatial autocorrelation of organic matter, total nitrogen, alkali-hydrolyzable nitrogen, available phosphorus, available potassium and mitigation potassium was weak, which was mainly affected by random factors such as human activities. An unequivocal positive spatial nexus was discerned across all nutrients. Cumulatively, the nutrient dispersion across the investigated territory was somewhat diffuse, manifesting in a mosaic pattern with pronounced zonal nutrient allocation disparities in the meridional, median, and septentrional segments. An explicit latitudinal dichotomy delineating zones of nutrient opulence and paucity was also observed. These insights can pave the way for tailored fertilization strategies and judicious pedological stewardship in Fengtai County.

Feasibility of Implementing Dementia Collaborative Coaching into Routine Care in Nursing Homes

ABSTRACT Objectives The study evaluated the feasibility of implementing Dementia Collaborative Coaching (DCC) into the routine workflow of speech-language pathologists (SLPs) working in nursing homes (NHs). DCC is an intervention delivered by SLPs to train nursing assistants (CNAs) in communication strategies to support people living with dementia (PLWD). Methods We assessed the feasibility of identifying eligible PLWD; estimated intervention fidelity; evaluated suitability of outcome measures; and determined the preliminary impact on behavioral and psychological symptoms of distress (BPSD) among PLWD. SLPs completed a semi-structured interview to collect further acceptability data. Results Four SLPs in four NHs completed DCC with 10 CNAs and 15 eligible PLWD that they appropriately identified from their caseloads. SLPs conducted 90 DCC sessions with 64% fidelity and billed Medicare for all sessions. The outcome measure of Minimum Data Set item E0200B: Rejection of Care did not vary enough to be useful, but positive changes were noted on the Cohen-Mansfield Agitation Inventory, t(14) = 10.51, p < .001, Cohen’s d = 2.76. Interviews further indicated feasibility. Conclusions It is feasible to implement DCC into the workflow of SLPs in NHs. Clinical Implications Given the feasibility and preliminary positive impacts, SLPs could consider implementing DCC in routine care.

Selection of the minimum data set and quantitative soil quality indices for different azalea forest communities in southwestern China

Selection of the minimum data set and quantitative soil quality indices for different azalea forest communities in southwestern China

7234 Creation Of The Minimum Dataset Required For Monitoring The Safety And Efficacy of Growth Hormone Therapy in Children with Noonan Syndrome - A GloBE-Reg Initiative

Abstract Disclosure: S. Chen: Research Investigator; Self; Pfizer, Inc.. J. Bryce: None. M. Chen: None. G. Binder: Advisory Board Member; Self; Ascendis, Ferring Pharmaceuticals, Ipsen, Novo Nordisk, Pfizer, Inc., Sandoz. Grant Recipient; Self; Novo Nordisk. Speaker; Self; Ferring Pharmaceuticals, Ipsen, Lilly USA, LLC, Merck, Novo Nordisk, Pfizer, Inc., Sandoz. C.S. Choong: None. T. Edouard: Advisory Board Member; Self; Biomarin, Novo Nordisk. Speaker; Self; Biomarin, Novo Nordisk. A. Fu: None. R. Horikawa: None. A. Hubbard: None. J. Lebl: Speaker; Self; Pfizer, Inc., Novo Nordisk, Merck. L. Mazzanti: Speaker; Self; Novo Nordisk, Pfizer, Inc., Sandoz. A. Romano: Consulting Fee; Self; Novo Nordisk. Speaker; Self; Novo Nordisk. M. Shaikh: Consulting Fee; Self; Novo Nordisk, Pfizer, Inc.. F. Tamburrino: None. S. Tamponi: None. P. Yger: None. S. Ahmed: Grant Recipient; Self; Novo Nordisk, Pfizer, Inc., GenSci. Speaker; Self; Ipsen. A. Jorge: Grant Recipient; Self; Biomarin. Research Investigator; Self; Novo Nordisk. Speaker; Self; Novo Nordisk, Pfizer, Inc. Introduction: Recombinant human growth hormone (rhGH) is approved internationally for use in Noonan syndrome (NS); initially by the FDA in 2007 and most recently in Europe in 2020. Most studies have shown benefit in linear growth and adult height associated with rhGH therapy, although response to treatment often varies, and longer-term safety data is limited. Moreover, comparisons between studies are compromised by the lack of consistency in data collection. The objective of the current study was to identify the minimum dataset (MDS) that could be monitored and reported globally in a routine clinical setting. Methods: This study was undertaken by the NS Expert Working Group in GloBE-Reg, the Global Registry for Novel Therapies in Rare Bone and Endocrine Conditions (https://globe-reg.net/). Ten international clinical experts in NS from ten different countries and three patient representatives of patient organisations collaborated to develop this recommendation, based on a previously described and published methodology for the grading system to determine if an item fulfils the criteria for the MDS rhGH in childhood onset GH deficiency (GHD) (doi: 10.1159/000533763). Data fields that achieved &amp;gt;70% consensus in terms of importance qualified for the MDS, provided &amp;lt;50% of the group deemed the item difficult to collect. Results: Preparation for the development of the finalised MDS occurred over 4 months, including two teleconference meetings between the group members and a final consensus meeting also held virtually. A total of 256 items were compiled and 9 removed for redundancies, with 247 items subjected to the grading system. Of these, 169 items achieved at least 70% consensus as important data to collect and a total of 169, albeit different items, were deemed easy to collect when monitoring children with NS on rhGH. Combining the criteria of importance and ease of data collection, 124 fulfilled the criteria for the MDS. Six items were designated as core data, 2 were computed fields, 10 items were removed following detailed discussion and 48 items were merged, to produce the final MDS recommendation of 57 items which consisted of 20 items that were only required to be completed once, and the rest at least once annually. Importantly, the exercise also showed that the MDS for monitoring of safety and efficacy of rhGH therapy differs for the different licensed indications for rhGH use, as the need for growth hormone stimulation tests and information on reinitiation after final adult height was not included in the NS MDS in contrast to the MDS for GHD. Conclusion: In summary, this exercise performed through the GloBE-Reg initiative provides a recommendation of the MDS requirement that should be collected as part of routine clinical practice, for the reporting of core outcomes that relate to safety and effectiveness of all forms of rhGH in children with NS. Presentation: 6/3/2024

7194 The Use Of GloBE-Reg As A Global Platform For Performing Safety &amp; Efficacy Studies Of rhGH Therapy - First Year Results

Abstract Disclosure: M. Alimussina: None. J. Bryce: None. M. Chen: None. S. Koley: None. A. Al-Agha: None. N. Amin: None. N. Atapattu: None. J. Chen: None. Y. Deyanova: None. A. Fu: None. C. Gong: None. V. Iotova: None. D. Janus: None. A. Jorge: Consulting Fee; Self; Novo Nordisk. Grant Recipient; Self; BioMarin. R. Markosyan: None. S. Seneviratne: None. M.G. Shaikh: None. S. Shenoy: None. S. Shepherd: None. L. Tack: None. M. Wasniewska: None. S. Chen: Research Investigator; Self; Pfizer, Inc. S.F. Ahmed: Grant Recipient; Self; GenSci, Novo Nordisk, Pfizer, Inc.. Speaker; Self; Ipsen. Introduction: The Global Registry For Novel Therapies In Rare Bone &amp; Endocrine Conditions (GloBE-Reg, https://globe-reg.net/) project was launched in 2022 with the aim of supporting studies that focus on effectiveness and long-term safety of specific therapies. The project’s initial focus has been on recombinant human growth hormone therapy (rhGH). Although safety information on rhGH therapy has now been collected for several years, there are still existing gaps in our knowledge, especially with the introduction of new indications and novel forms of rhGH. Methods: The GloBE-Reg registry has three layers of datasets, with the first dataset consisting of internationally agreed core data elements that can apply to any rare condition, another set of data elements that allows the selection of a specific therapy and diagnosis, a third set of additional data elements that is made up of the therapy and diagnosis-specific minimum dataset (MDS) and an option to have a more extended dataset. The minimum dataset collects information on the diagnosis, therapy, clinician reported outcomes, patient reported outcomes and adverse events. The platform and the registry received ethics/IRB approval in the UK and is now extending internationally. The fields within the MDS are developed following guidance from short-life expert working groups (EWG). Results: Since its launch in November 2022, 51 centres from 29 countries have registered their interest to use the platform and of these, 14 centres from 11 countries in 3 continents have already included 444 (M:F, 282:162) patients with a median age of 11 yr (range &amp;lt;1, 29). Of these, 317 (71%) were on daily rhGH, 126 (28%) were on long-acting rhGH, one was on daily rhGH as an adult and in one, rhGH therapy had been discussed but not started. Nine different brands of rhGH were being used across these centres for 9 groups of indications, whereas long-acting rhGH was being used for only 4 indications. In addition, there were 11 (3%) cases receiving rhGH for other conditions associated with short stature or growth retardation. The largest indication group was GHD (65%) followed by SGA (10%), TS (7%), PWS (7%), ISS (5%) and others. Of the 444 cases, 67 (15%) had also been entered in other disease registries and 18 (27%) of these 67 had been entered by one centre into the GloBE-Reg through its bulk upload facility. A Childhood GHD MDS is now fully operational and MDS for other conditions are under development. Conclusion: Since its launch, GloBE-Reg has shown that a relatively low-cost platform operated through an academic institution can have sufficient stakeholder acceptability and versatility for collecting information that can support the development of long-term safety and effectiveness studies. The preliminary data that have been collected on rhGH show the long-term utility of the platform for collecting global brand and diagnosis-specific data. Presentation: 6/2/2024

Development of a minimum data set for a blockchain-based personal health records (PHRs), for patient/physician interaction in family medicine

BACKGROUND: The primary requirement for a capable patient health record (PHR) that can interact appropriately with the family medicine system and collect and share qualified data is a minimum data set (MDS) aligned with family medicine’s functions and goals. The aim of this research was to determine the MDS for a blockchain-based PHR system that can effectively interact with family medicine providers and collect and share qualified data. This MDS is intended to be applicable to all members of the community covered by family medicine. MATERIALS AND METHODS: This applied study was conducted in 2022 in a cross-sectional and descriptive approach in three phases. In the first phase, a content analysis related to the research objectives was conducted in scientific databases, search engines, and websites of the centers and scientific research organizations with publications and policy-making in this field. Consequently, 11 studies were selected for use in the second and third phases. In the second phase, to determine information needs, a researcher-developed questionnaire including 17 classes was given to 50 people under the cover of the family medicine plan in Shiraz city. By choosing one of the two options “Yes” or “No” by them, the necessary data classes were determined. In the third phase, the second researcher-developed questionnaire was designed and administered to 100 family physicians in Shiraz city. This questionnaire included the data elements corresponding to the data classes approved in the previous phase. The family physicians were asked to rate the importance of each data element using a Likert scale with five options, ranging from “very unimportant” to “very important.” The necessary data elements were determined based on these scores. RESULTS: In the first questionnaire, 16 of the 17 data classes received approval from individuals covered by the family medicine plan. Consequently, a questionnaire comprising 16 classes and 105 data elements was administered to the family physicians. Ultimately, the MDS was determined to include 16 classes and 72 data elements. CONCLUSIONS: Determining essential data elements, especially for patient/physician interaction in family medicine, should be such that they can be managed by the person while being comprehensive and providing sufficient help to the physician during the treatment process. This MDS can be used to interact with and refer PHRs to other physicians and specialists, as well as help interoperability between the PHR and other health systems, such as hospital information systems (HIS) and electronic health records (EHRs).

The Classification of Land Quality Index Using Minimum Data Set – Study in a Tropical Agroecosystem of East Java

The Classification of Land Quality Index Using Minimum Data Set – Study in a Tropical Agroecosystem of East Java

Health Profile Transitions and the Association With Cognitive Impairment in Older Nursing Home Residents With Suicidal Ideation.

In older U.S. nursing home residents with suicidal ideation (SI), limited studies have longitudinally investigated their health changes as related to cognitive function. This study aimed to identify the health profiles and the transitions between profiles at admission and 90-days and examine the associations with cognitive impairment. Using Minimum Data Set 3.0 (2011-15), we identified 10,079 older residents without severe cognitive impairment who reported SI on Patient Health Questionnaire-9. Health profile indicators included at-admission and 90-day post-admission depressive symptoms, frailty, and pain frequency and intensity. Using latent transition analysis, we identified distinct health profiles, examined the transitions between profiles over time, and estimated their associations with cognitive impairment. One third of residents continued to report SI at 90days. The five health profiles identified at admission were distinctive with varying levels of frailty, depressive symptoms, and pain, from the most severe Profile 1 characterized by frailty, all depressive symptoms, and horrible or frequent pain, to the least severe Profile 5 characterized by pre-frailty, depressed mood, and no pain. The 90-day profiles were mostly consistent. Most residents remained in a similar profile over time. Relative to residents with intact cognition/mild cognitive impairment, those with moderate impairment were less likely to belong to profiles characterized by more depressive symptoms and pain. Residents with SI had heterogeneous health profiles, which varied by cognitive impairment levels, but showed minimal changes despite being in a medically supervised setting. Findings highlighted the critical need for adequate recognition and management of SI in nursing homes.

Impacting trauma care in resource-limited settings: Lessons learned from Tanzania's web-based trauma registry initiatives.

Trauma significantly impacts Tanzanian healthcare. Lacking standardized hospital-based minimal trauma data sets places further challenges for policymakers. In other resource-limited countries, implementing trauma systems and registries has reduced injury mortalities. In 2013, we introduced an electronic trauma registry, iTRAUMATM at the Tanzanian Muhimbili Orthopedic Institute (MOI) but noted several drawbacks. In 2023, we introduced a robust web-based trauma registry platform. This study assesses the feasibility and utility of implementing the platform at MOI and summarizes challenges, lessons, and results compared to existing systems. This prospective observational study involved clinicians collecting data directly on the platform at the point-of-care, following specific training. Semi-structured interviews with local stakeholders identified challenges and areas for improvement. Data were reported from July to December 2023. Data from 2930 patients showed 59% of injuries were from road traffic collisions (RTCs), with 43% of patients arriving at MOI by non-ambulances. Our findings show that non-ambulance arrivals were associated with higher injury severity (p<0.026), mortalities (p<0.017), and delayed hospital arrival (p<0.004), underscoring the critical role of prompt transport in trauma management. The new platform identified trauma care gaps, with a mean arrival-to-care time of 29.89min, prompting trauma training at MOI to enhance clinician capacities. It also demonstrated superiority over existing systems by improving data completeness, timeliness, and usability. Challenges included gaining support for the platform's functionality, technology integration, and navigating administrative changes. With continued communication, stakeholder acceptance and support were achieved. The web-based platform has become MOI's standard trauma database, demonstrating its feasibility and utility. It overcame the existing challenges of data completeness, timeliness, and usability for policymaking. Positive feedback has prompted plans to expand the platform to other hospitals, benefiting clinical benchmarking and trauma preventive efforts. Ensuring sustainability requires involvement from the Ministry of Health, ongoing training, functionality enhancements, and strengthened global partnerships.