Mapping the Ecological Terrain of Stroke Prehospital Delay: A Nationwide Registry Study.

BACKGROUND: Delays in hospital presentation limit access to acute stroke treatments. While prior research has focused on patient-level factors, broader ecological and social determinants have not been well studied. We aimed to create a geospatial map of prehospital delay and examine the role of community-level social vulnerability. METHODS: We studied patients with ischemic stroke who arrived by emergency medical services in 2015 to 2017 from the American Heart Association Get With The Guidelines-Stroke registry. The primary outcome was time to hospital arrival after stroke (in minutes), beginning at last known well in most cases. Using Geographic Information System mapping, we displayed the geography of delay. We then used Cox proportional hazard models to study the relationship between community-level factors and arrival time (adjusted hazard ratios [aHR] <1.0 indicate delay). The primary exposure was the social vulnerability index (SVI), a metric of social vulnerability for every ZIP Code Tabulation Area ranging from 0.0 to 1.0. RESULTS: Of 750 336 patients, 149 145 met inclusion criteria. The mean age was 73 years, and 51% were female. The median time to hospital arrival was 140 minutes (Q1: 60 minutes, Q3: 458 minutes). The geospatial map revealed that many zones of delay overlapped with socially vulnerable areas (https://harvard-cga.maps.arcgis.com/apps/webappviewer/index.html?id=08f6e885c71b457f83cefc71013bcaa7). Cox models (aHR, 95% CI) confirmed that higher SVI, including quartiles 3 (aHR, 0.96 [95% CI, 0.93-0.98]) and 4 (aHR, 0.93 [95% CI, 0.91-0.95]), was associated with delay. Patients from SVI quartile 4 neighborhoods arrived 15.6 minutes [15-16.2] slower than patients from SVI quartile 1. Specific SVI themes associated with delay were a community's socioeconomic status (aHR, 0.80 [95% CI, 0.74-0.85]) and housing type and transportation (aHR, 0.89 [95% CI, 0.84-0.94]). CONCLUSIONS: This map of acute stroke presentation times shows areas with a high incidence of delay. Increased social vulnerability characterizes these areas. Such places should be systematically targeted to improve population-level stroke presentation times.

Spatial Patterning of Spontaneous and Medically Indicated Preterm Birth in Philadelphia.

Preterm birth (PTB) remains a key public health issue that disproportionately affects Black individuals. Since spontaneous PTB (sPTB) and medically indicated PTB (mPTB) may have different causes and interventions, we quantified racial disparities for sPTB and mPTB, and we characterized the geographic patterning of these phenotypes, overall and according to race/ethnicity. We examined a pregnancy cohort of 83,952 singleton births at 2 Philadelphia hospitals from 2008-2020, and classified each PTB as sPTB or mPTB. We used binomial regression to quantify the magnitude of racial disparities between non-Hispanic Black and non-Hispanic White individuals, then generated small area estimates by applying a Bayesian model that accounts for small numbers and smooths estimates of PTB risk by borrowing information from neighboring areas. Racial disparities in both sPTB and mPTB were significant (relative risk of sPTB = 1.83, 95% confidence interval: 1.70, 1.98; relative risk of mPTB = 2.20, 95% confidence interval: 2.00, 2.42). The disparity was 20% greater in mPTB than sPTB. There was substantial geographic variation in PTB, sPTB, and mPTB risks and racial disparity. Our findings underscore the importance of distinguishing PTB phenotypes within the context of public health and preventive medicine. Future work should consider social and environmental exposures that may explain geographic differences in PTB risk and disparities.

Association of travel time, patient characteristics, and hospital quality with patient mobility for breast cancer surgery: A national population-based study.

BACKGROUND: This national study investigated hospital quality and patient factors associated with treatment location for breast cancer surgery. METHODS: By using linked administrative data sets from the English National Health Service, the authors identified all women diagnosed between January 2, 2016, and December 31, 2018, who underwent breast-conserving surgery (BCS) or a mastectomy with or without immediate breast reconstruction. The extent to which patients bypassed their nearest hospital was investigated using a geographic information system (ArcGIS). Conditional logistic regressions were used to estimate the impact of travel time, hospital quality, and patient characteristics. RESULTS: 22,622 Of 69,153 patients undergoing BCS, 22,622 (32.7%) bypassed their nearest hospital; and, of 23,536 patients undergoing mastectomy, 7179 (30.5%) bypassed their nearest hospital. Women who were younger, without comorbidities, or from rural areas were more likely to travel to more distant hospitals (p < .05). Patients undergoing BCS (odds ratio [OR], 1.85; 95% confidence interval [CI], 1.36-2.50) or mastectomy (OR, 1.52; 95% CI, 1.14-2.02) were more likely to be treated at specialist breast reconstruction centers despite not undergoing the procedure. Patients receiving mastectomy and immediate breast reconstruction were more likely to travel to hospitals employing surgeons who had a media reputation (OR, 2.41; 95% CI, 1.28-4.52). Patients undergoing BCS were less likely to travel to hospitals with shorter surgical waiting times (OR, 0.65; 95% CI, 0.46-0.92). The authors did not observe a significant impact for research activity, hospital quality rating, breast re-excision rates, or the status as a multidisciplinary cancer center. CONCLUSIONS: Patient choice policies may drive inequalities in the health care system without improving patient outcomes.

Cancer patterns in Iran: a gender-specific spatial modelling of cancer incidence during 2014-2017.

BACKGROUND: Cancer is a significant public health concern and the second leading cause of death. This study aims to visualize spatial patterns of top common cancer types and identify high-risk and low-risk counties for these cancers in Iran from 2014 to 2017. METHODS: In this study, we analyzed 482,229 newly diagnosed cancer cases recorded by the Iranian National Population-Based Cancer Registry from 2014 to 2017. We employed a purely spatial scanning model and local Moran I analysis to explore spatial patterns across Iran. RESULTS: Approximately 53% of all cases were male. The average age of cancer diagnosis was 62.58 ± 17.42 years for males and 56.11 ± 17.33years for females. Stomach cancer was the most common cancer in men. The northern and northwestern regions of Iran were identified as high-risk areas for stomach cancer in both genders, with a relative risk (RR) ranging from 1.26 to 2.64 in males and 1.19 to 3.32 in females. These areas recognized as high-risk areas for trachea, bronchus, and lung (TBL) cancer specifically in males (RR:1.15-2.02). Central regions of Iran were identified as high-risk areas for non-melanoma skin cancers in both genders, ranking as the second most common cancer (RR:1.18-5.93 in males and 1.24-5.38 in females). Furthermore, bladder cancer in males (RR:1.32-2.77) and thyroid cancer in females (RR:1.88-3.10) showed concentration in the central part of Iran. Breast cancer, being the most common cancer among women (RR:1.23-5.54), exhibited concentration in the northern regions of the country. Also, northern regions of Iran were identified as high-risk clusters for colon cancer (RR:1.31-3.31 in males and 1.33-4.13 in females), and prostate cancer in males (RR:1.22-2.31). Brain, nervous system cancer, ranked sixth among women (RR:1.26-5.25) in central areas. CONCLUSIONS: The study's revelations on the spatial patterns of common cancer incidence in Iran provide crucial insights into the distribution and trends of these diseases. The identification of high-risk areas equips policymakers with valuable information to tailor targeted screening programs, facilitating early diagnosis and effective disease control strategies.

Intake of Snacks and Sweets in a National Study of Built and Social Environments: the REasons for Geographic And Racial Differences in Stroke Study.

BACKGROUND: Few national studies across the United States' rural-urban continuum examine neighborhood effects on snacks and sweets intake among adults. OBJECTIVES: This study examines associations of urbanicity/rurality-tailored measures of food store availability and neighborhood socioeconomic status (NSES) with the intake of snacks and sweets in a national sample of middle and older age adults. METHODS: This cross-sectional study used food frequency questionnaire data collected in the REasons for Geographic And Racial Differences in Stroke study (N = 21,204). What We Eat in America food group categorizations guided outcome classification into 1 main category (total snacks and sweets) and 4 subcategories (savory snacks and crackers; sweet bakery products; candy and desserts; nutrition bars and low-fat snacks and sweets). NSES and food store availability were determined using geographic information systems. Food store availability was characterized as geographic access to primary food stores (e.g., supermarkets, supercenters, and select food retailers) in urbanicity/rurality-tailored neighborhood-based buffers. Multiple linear regression was used to predict each outcome. RESULTS: Living in neighborhoods with a high density of primary food stores was associated with 8.6%, 9.5%, and 5.8% lower intake of total snacks and sweets, sweet bakery products, and candy and desserts, respectively. Living in the highest NSES quartile was associated with 11.3%, 5.8%, and 18.9% lower intake of total snacks and sweets, savory snacks and crackers, and sweet bakery products, respectively. Depending on primary food store availability, higher household income was associated with significantly greater intake of nutrition bars and low-fat snacks and sweets. Living in a United States Department of Agriculture-defined food desert was not associated with intake. CONCLUSIONS: In a geographically diverse sample of middle and older age United States adults, living in neighborhoods with no primary food stores or neighborhoods of low-SES was associated with higher intake of total snacks and sweets and subgroups of snacks and sweets.

Towards malaria elimination: a reflection about digital notification modules to improve malaria cases notification speed and follow-up in the Brazilian Amazon region.

BACKGROUND: Health information systems (HIS) are a pivotal element in epidemiological surveillance. In Brazil, malaria persists as a public health challenge, with 99% of its occurrences concentrated in the Amazon region, where cases are reported through the HIS Sivep-Malaria. Recent technological advancements indicate that case notifications can be expedited through more efficient systems with broader coverage. The objective of this study is to analyse opportunities for notification within Sivep-Malaria and explore the implementation of mobile electronic devices and applications to enhance the performance of malaria case notifications and use. METHODS: This descriptive study analyses data on malaria-positive cases in the Brazilian Amazon from 2004 to 2022. Malaria Epidemiological Surveillance System (Sivep-Malaria) data were used. The Brazilian Amazon region area is approximately 5 million km2 across nine different states in Brazil. Data entry opportunities were assessed by considering the time difference between the 'date of data entry' and the 'date of notification.' Descriptive statistics, including analyses of means and medians, were conducted across the entire Amazon region, and for indigenous population villages and gold mining areas. RESULTS: Between 2004 and 2022, 6,176,878 new malaria cases were recorded in Brazil. The average data entry opportunity throughout the period was 17.9 days, with a median of 8 days. The most frequently occurring value was 1 day, and 99% of all notifications were entered within 138 days, with 75.0% entered within 20 days after notification. The states with the poorest data entry opportunities were Roraima and Tocantins, with averages of 31.3 and 31.0 days, respectively. For indigenous population villages and gold mining areas, the median data entry opportunities were 23 and 15 days, respectively. CONCLUSIONS: In malaria elimination, where surveillance is a primary strategy for evaluating each reported case, reducing notification time, enhancing data quality and being able to follow-up cases through computerized reports offer significant benefits for cases investigation. Technological improvements in Sivep-Malaria could yield substantial benefits for malaria control in Brazil, aiding the country in achieving disease elimination and fulfilling the Sustainable Development Goals.

The optimization of harm reduction services in Massachusetts through the use of GIS: Location-allocation analyses, 2019-2021.

BACKGROUND: Fatal opioid-related overdoses (OOD) continue to be a leading cause of preventable death across the US. Opioid Overdose Education and Naloxone Distribution programs (OENDs) play a vital role in addressing morbidity and mortality associated with opioid use, but access to such services is often inequitable. We utilized a geographic information system (GIS) and spatial analytical methods to inform prioritized placement of OEND services in Massachusetts. METHODS: We obtained addresses for OEND sites from the Massachusetts Department of Public Health and address-level fatal OOD data for January 2019 to December 2021 from the Massachusetts Registry of Vital Records and Statistics. Using location-allocation approaches in ArcGIS Pro, we created p-median models using locations of existing OEND sites and fatal OOD counts to identify areas that should be prioritized for future OEND placement. Variables included in our analysis were transportation mode, distance from public schools, race and ethnicity, and location feasibility. RESULTS: Three Massachusetts communities - Athol, Dorchester, and Fitchburg - were identified as priority sites for new OEND locations using location-allocation models based on capacity to maximize OOD prevention. Communities identified by the models for OEND placement had similar demographics and overdose rates (42.8 per 100,000 vs 40.1 per 100,000 population) to communities with existing OEND programs but lower naloxone kit distribution rates (2589 doses per 100,000 vs 3704 doses per 100,000). Further models demonstrated differential access based on location and transportation. CONCLUSION: Our analyses identified key areas of Massachusetts with greatest need for OEND services. Further, these results demonstrate the utility of using spatial epidemiological methods to inform public health recommendations.

Utilizing social determinants of health to identify most vulnerable neighborhoods-Latent class analysis and GIS map.

OBJECTIVES: Public Health officials are often challenged to effectively allocate limited resources. Social determinants of health (SDOH) may cluster in areas to cause unique profiles related to various adverse life events. The authors use the framework of unintended teen pregnancies to illustrate how to identify the most vulnerable neighborhoods. METHODS: This study used data from the U.S. American Community Survey, Princeton Eviction Lab, and Connecticut Office of Vital Records. Census tracts are small statistical subdivisions of a county. Latent class analysis (LCA) was employed to separate the 832 Connecticut census tracts into four distinct latent classes based on SDOH, and GIS mapping was utilized to visualize the distribution of the most vulnerable neighborhoods. GEE Poisson regression model was used to assess whether latent classes were related to the outcome. Data were analyzed in May 2021. RESULTS: LCA's results showed that class 1 (non-minority non-disadvantaged tracts) had the least diversity and lowest poverty of the four classes. Compared to class 1, class 2 (minority non-disadvantaged tracts) had more households with no health insurance and with single parents; and class 3 (non-minority disadvantaged tracts) had more households with no vehicle available, that had moved from another place in the past year, were low income, and living in renter-occupied housing. Class 4 (minority disadvantaged tracts) had the lowest socioeconomic characteristics. CONCLUSIONS: LCA can identify unique profiles for neighborhoods vulnerable to adverse events, setting up the potential for differential intervention strategies for communities with varying risk profiles. Our approach may be generalizable to other areas or other programs. KEY MESSAGES: What is already known on this topic Public health practitioners struggle to develop interventions that are universally effective. The teen birth rates vary tremendously by race and ethnicity. Unplanned teen pregnancy rates are related to multiple social determinants and behaviors. Latent class analysis has been applied successfully to address public health problems. What this study adds While it is the pregnancy that is not planned rather than the birth, access to pregnancy intention data is not available resulting in a dependency on teen birth data for developing public health strategies. Using teen birth rates to identify at-risk neighborhoods will not directly represent the teens at risk for pregnancy but rather those who delivered a live birth. Since teen birth rates often fluctuate due to small numbers, especially for small neighborhoods, LCA may avoid some of the limitations associated with direct rate comparisons. The authors illustrate how practitioners can use publicly available SDOH from the Census Bureau to identify distinct SDOH profiles for teen births at the census tract level. How this study might affect research, practice or policy These profiles of classes that are at heightened risk potentially can be used to tailor intervention plans for reducing unintended teen pregnancy. The approach may be adapted to other programs and other states to prioritize the allocation of limited resources.

Measuring Spatial Access of Vulnerable Population to HIV Testing Facilities in the Baton Rouge Metropolitan Statistical Area, Louisiana.

Ensuring adequate and equitable access to affordable HIV testing is a crucial step toward ending the HIV epidemic (EHE). Using the high-burden Baton Rouge Metropolitan Statistical Area (MSA) as an example, we measure spatial access to HIV testing facilities for vulnerable populations and assess whether their access would improve if eliminating a considerable barrier-costs. Locations and status (free, low-cost, and full cost) of HIV testing facilities are searched on the Internet and confirmed through a field survey. Vulnerable populations include the uninsured and people living with HIV (PLWH), disaggregated from county-level HIV prevalence data. Spatial access is computed by a normalized urban-rural two-step floating catchment area (NUR2SFCA) method. Our survey confirms that only 11% and 37% of the 103 Internet-searched HIV testing facilities are indeed free and low-cost. Making more facilities cheaper or free increases the average access of PLWH, the uninsured, and the entire population but their geographic patterns vary. Free testing facilities, clustered in Baton Rouge city, are highly accessible to 82.6%, 69.4%, and 70.2% of three population groups living in East and West Baton Rouge Parish. In comparison, making all low-cost facilities free increases access in most outlying parishes but at the cost of reducing access in East Baton Rouge Parish, leaving west Livingston, north Iberville, and east Pointe Coupee Parish with the poorest access. Making all full-cost facilities cheaper or free exhibits a similar pattern. The study has important policy implications for where and how to improve access to HIV testing for vulnerable populations.

RESUMEN: Medimos el acceso espacial a las instalaciones de pruebas de VIH para poblaciones vulnerables y evaluamos si su acceso mejoraría si se eliminaran las barreras de costos, utilizando como ejemplo el área estadística metropolitana de Baton Rouge, que tiene una alta carga. Nuestra encuesta confirma que el 11% y el 37% de los 103 centros de pruebas de VIH buscados en Internet son efectivamente gratuitos y de bajo costo. Hacer que más instalaciones sean más baratas o gratuitas aumenta el acceso promedio de las PLWH, las personas sin seguro y toda la población, pero sus patrones geográficos varían. Las instalaciones de pruebas gratuitas, agrupadas en la ciudad de Baton Rouge, son muy accesibles para el 82,6%, el 69,4% y el 70,2% de los tres grupos de población del este y oeste de Baton Rouge. En comparación, hacer que las instalaciones de bajo costo sean gratuitas aumenta el acceso en las parroquias periféricas, pero a costa de reducir el acceso en East Baton Rouge. Hacer que las instalaciones de costo total sean más baratas o gratuitas muestra un patrón similar. El estudio tiene importantes implicaciones políticas para mejorar el acceso a las pruebas del VIH para las poblaciones vulnerables.

Validating the Delone and Mclean's model in a developing country's infectious disease pandemic context.

BACKGROUND: This study aimed at validating the updated DeLone and McLean's information systems success model (D&MISS) in a developing country's infectious disease pandemic preparedness and response context. The findings from this study are relevant to inform policies and actions for enhancing developing countries' the Health Information System's (HIS) performance, and specifically to improve their future pandemic readiness and response. The study sought to respond to a key research question: to what extent can the D&MISS model provide evidence to enhance the HIS's infectious disease pandemic readiness and response in developing countries? METHOD: A cross-sectional study design that involved a multi-stage probability sampling approach to select eligible healthcare workers was applied. Conducted in Nigeria and Liberia, 576 primary healthcare workers, out of the proposed 600, participated, representing a response rate of 96%. The D&MISS model served as the theoretical underpinning for this study, and nine hypothesized relationships were stated before the study based on the interconnectedness of the model's six dimensions. Structural Equation Modelling (SEM) data analysis using the Partial Least Square approach was used to determine if hypothesized relationships were supported. RESULTS: 70% of the observed variance in the Net Benefit construct was explained by the predictive influence of the Use and User Satisfaction constructs. The Use construct had a slightly more substantial predictive influence than the User Satisfaction construct. Eight of the nine hypothesized relationships were supported, except for the relationship between Information Quality and Use. The relationships between System Quality and Use and User Satisfaction and Net Benefit had the highest beta coefficient, statistically significant at p < 0.05. CONCLUSION AND RELEVANCE: The D&MISS model demonstrated its relevance in providing evidence on the gaps of the HISs regarding future pandemic preparedness and response. However, from a future research opportunity, its enhancement and modifications with context-specific dimensions peculiar to developing countries will improve its ability to provide more context-specific evidence to improve pandemic preparedness and response for developing countries.

Trends in caesarean section rates in Europe from 2015 to 2019 using Robson's Ten Group Classification System: A Euro-Peristat study.

OBJECTIVE: To assess changes in caesarean section (CS) rates in Europe from 2015 to 2019 and utilise the Robson Ten Group Classification System (TGCS) to evaluate the contribution of different obstetric populations to overall CS rates and trends. DESIGN: Observational study utilising routine birth registry data. SETTING: A total of 28 European countries. POPULATION: Births at ≥22 weeks of gestation in 2015 and 2019. METHODS: Using a federated model, individual-level data from routine sources in each country were formatted to a common data model and transformed into anonymised, aggregated data. MAIN OUTCOME MEASURES: By country: overall CS rate. For TGCS groups (by country): CS rate, relative size, relative and absolute contribution to overall CS rate. RESULTS: Among the 28 European countries, both the CS rates (2015, 16.0%-55.9%; 2019, 16.0%-52.2%) and the trends varied (from -3.7% to +4.7%, with decreased rates in nine countries, maintained rates in seven countries (≤ ± 0.2) and with increasing rates in 12 countries). Using the TGCS (for 17 countries), in most countries labour induction increased (groups 2a and 4a), whereas multiple pregnancies (group 8) decreased. In countries with decreasing overall CS rates, CS tended to decrease across all TGCS groups, whereas in countries with increasing rates, CS tended to increase in most groups. In countries with the greatest increase in CS rates (>1%), the absolute contributions of groups 1 (nulliparous term cephalic singletons, spontaneous labour), 2a and 4a (induction of labour), 2b and 4b (prelabour CS) and 10 (preterm cephalic singletons) to the overall CS rate tended to increase. CONCLUSIONS: The TGCS shows varying CS trends and rates among countries of Europe. Comparisons between European countries, particularly those with differing trends, could provide insight into strategies to reduce CS without clinical indication.

Determinants of disparities of diabetes-related hospitalization rates in Florida: a retrospective ecological study using a multiscale geographically weighted regression approach.

BACKGROUND: Early diagnosis, control of blood glucose levels and cardiovascular risk factors, and regular screening are essential to prevent or delay complications of diabetes. However, most adults with diabetes do not meet recommended targets, and some populations have disproportionately high rates of potentially preventable diabetes-related hospitalizations. Understanding the factors that contribute to geographic disparities can guide resource allocation and help ensure that future interventions are designed to meet the specific needs of these communities. Therefore, the objectives of this study were (1) to identify determinants of diabetes-related hospitalization rates at the ZIP code tabulation area (ZCTA) level in Florida, and (2) assess if the strengths of these relationships vary by geographic location and at different spatial scales. METHODS: Diabetes-related hospitalization (DRH) rates were computed at the ZCTA level using data from 2016 to 2019. A global ordinary least squares regression model was fit to identify socioeconomic, demographic, healthcare-related, and built environment characteristics associated with log-transformed DRH rates. A multiscale geographically weighted regression (MGWR) model was then fit to investigate and describe spatial heterogeneity of regression coefficients. RESULTS: Populations of ZCTAs with high rates of diabetes-related hospitalizations tended to have higher proportions of older adults (p < 0.0001) and non-Hispanic Black residents (p = 0.003). In addition, DRH rates were associated with higher levels of unemployment (p = 0.001), uninsurance (p < 0.0001), and lack of access to a vehicle (p = 0.002). Population density and median household income had significant (p < 0.0001) negative associations with DRH rates. Non-stationary variables exhibited spatial heterogeneity at local (percent non-Hispanic Black, educational attainment), regional (age composition, unemployment, health insurance coverage), and statewide scales (population density, income, vehicle access). CONCLUSIONS: The findings of this study underscore the importance of socioeconomic resources and rurality in shaping population health. Understanding the spatial context of the observed relationships provides valuable insights to guide needs-based, locally-focused health planning to reduce disparities in the burden of potentially avoidable hospitalizations.

Health information management systems and practices in conflict-affected settings: the case of northwest Syria.

BACKGROUND: In conflict settings, as it is the case in Syria, it is crucial to enhance health information management to facilitate an effective and sustainable approach to strengthening health systems in such contexts. In this study, we aim to provide a baseline understanding of the present state of health information management in Northwest Syria (NWS) to better plan for strengthening the health information system of the area that is transitioning to an early-recovery stage. METHODS: A combination of questionnaires and subsequent interviews was used for data collection. Purposive sampling was used to select twenty-one respondents directly involved in managing and directing different domains of health information in the NWS who worked with local NGOs, INGOs, UN-agencies, or part of the Health Working Group. A scoring system for each public health domain was constructed based on the number and quality of the available datasets for these domains, which were established by Checci and others. RESULTS & CONCLUSIONS: Reliable and aggregate health information in the NWS is limited, despite some improvements made over the past decade. The conflict restricted and challenged efforts to establish a concentrated and harmonized HIS in the NWS, which led to a lack of leadership, poor coordination, and duplication of key activities. Although the UN established the EWARN and HeRAMS as common data collection systems in the NWS, they are directed toward advocacy and managed by external experts with little participation or access from local stakeholders to these datasets. RECOMMENDATIONS: There is a need for participatory approaches and the empowerment of local actors and local NGOs, cooperation between local and international stakeholders to increase access to data, and a central domain for planning, organization, and harmonizing the process. To enhance the humanitarian health response in Syria and other crisis areas, it is imperative to invest in data collection and utilisation, mHealth and eHealth technologies, capacity building, and robust technical and autonomous leadership.

Managing hemolysis in serum neuron-specific enolase measurements - an automated algorithm for routine practice.

Neuron-specific enolase (NSE) derived from neurons and peripheral neuroendocrine cells is a biomarker for neuroendocrine tumors and for prognostication in comatose cardiac arrest survivors. However, as platelets and erythrocytes contain NSE, hemolysis causes falsely elevated NSE. We used native serum and hemolysate derived from the same patients to make serial dilutions, and subsequently measured NSE (mNSE) and hemolytic index (HI) in each dilution. An algorithm suitable for the laboratory information system was developed based on the mNSE, HI and the estimated gradient of hemolytic interference from 30 patients. We estimated the associated uncertainty of the corrected NSE (cNSE) results based on the observed range of the gradient and derived an equation for cNSE for samples with limited hemolysis (i.e. 5 < HI ≤ 30): cNSE = mNSE - HI × (0.34 ± 0.23) µg/L. By semi-quantitatively grading the contribution from limited hemolysis, a texted result noting the hemolysis-associated degree of uncertainty can accompany the cNSE result. The major challenge of hemolysis when using serum NSE as a biomarker can be managed using an automated algorithm for correction of NSE results based on degree of hemolysis. However, laboratorians and clinicians should be aware of the limitations associated with in vivo hemolysis.

Access to urban green spaces and use of social services and institutional long-term care among older people in Malmö, Sweden: a longitudinal register study.

BACKGROUND: Finding ways to prolong independence in daily life among older people would be beneficial for both individuals and society. Urban green spaces have been found to improve health, but only a few studies have evaluated the association between urban green spaces and independence in daily life. The aim of this study was to assess the long-term effect of urban green spaces on independence in daily life, using social services and support, mobility aids, and relocation to institutional long-term care as proxies, among community dwelling people 65 + years. METHODS: We identified 40 357 people 65 + years living in the city of Malmö, Sweden in 2010. Using geographical information systems (GIS), we determined the amount of urban green spaces (total, public, and quiet) within 300 m of each person's residence. All three measures were categorized based on their respective percentiles, so that the first quartile represented the 25% with the least access and the fourth quartile the 25% with the most access. In 2015 and 2019, we assessed the outcomes minor assistance (non-personal support), major assistance (personal support), and relocation into institutional long-term care. These three outcome measures were used as proxies for independence in daily life. The effect of amount of urban green spaces in 2010 on the three outcomes in 2015 and 2019, respectively, was assessed by pairwise comparing the three highest quartiles to the lowest. RESULTS: Compared to the lowest quartile, those in the highest quartile of quiet green spaces in 2010 were less likely to receive minor assistance in both 2015 and 2019. Besides this, there were no indications that any of the measures of urban green space affected independence in daily life at the five- and nine-year follow-up, respectively. CONCLUSION: Although urban green spaces are known to have positive impact on health, physical activity, and social cohesion among older people, we found no effect of total, public, or quiet green spaces on independence in daily life. This could possibly be a result of the choice of measures of urban green spaces, including spatial and temporal aspects, an inability to capture important qualitative aspects of the green spaces, or the proxy measures used to assess independence in daily life.

Laboratory-based surveillance of chronic kidney disease in people with private health coverage in Brazil.

BACKGROUND: Although approximately 25% of Brazilians have private health coverage (PHC), studies on the surveillance of chronic kidney disease (CKD) in this population are scarce. The objective of this study was to estimate the prevalence of CKD in individuals under two PHC regimes in Brazil, who total 8,335,724 beneficiaries. METHODS: Outpatient serum creatinine and proteinuria results of individuals from all five regions of Brazil, ≥ 18 years of age, and performed between 10/01/2021 and 10/31/2022, were analyzed through the own laboratory network database. People with serum creatinine measurements were evaluated for the prevalence and staging of CKD, and those with simultaneous measurements of serum creatinine and proteinuria were evaluated for the risk category of the disease. CKD was classified according to current guidelines and was defined as a glomerular filtration rate (GFR) < 60 ml/min/1.73 m² estimated by the 2021 CKD-EPI equation. RESULTS: The number of adults with serum creatinine results was 1,508,766 (age 44.0 [IQR, 33.9-56.8] years, 62.3% female). The estimated prevalence of CKD was 3.8% (2.6%, 0.8%, 0.2% and 0.2% in CKD stages 3a, 3b, 4 and 5, respectively), and it was higher in males than females (4.0% vs. 3.7%, p < 0.001, respectively) and in older age groups (0.2% among 18-29-year-olds, 0.5% among 30-44-year-olds, 2.0% among 45-59-year-olds, 9.4% among 60-74-year-olds, and 32.4% among ≥ 75-year-olds, p < 0.001) Adults with simultaneous results of creatinine and proteinuria were 64,178 (age 57.0 [IQR, 44.8-67.3] years, 58.1% female). After adjusting for age and gender, 70.1% were in the low-risk category of CKD, 20.0% were in the moderate-risk category, 5.8% were in the high-risk category, and 4.1% were in the very high-risk category. CONCLUSION: The estimated prevalence of CKD was 3.8%, and approximately 10% of the participants were in the categories of high or very high-risk of the disease. While almost 20% of beneficiaries with PHC had serum creatinine data, fewer than 1% underwent tests for proteinuria. This study was one of the largest ever conducted in Brazil and the first one to use the 2021 CKD-EPI equation to estimate the prevalence of CKD.

Does circle priming improve smart infusion pump and electronic health record interoperability for chemotherapy in a pediatric hematology/oncology setting?

INTRODUCTION: The objective of this project was to assess the percentage of interoperability compliance within our pediatric hematology/oncology patient care areas for intravenous chemotherapy medications before and after the implementation of circle priming. METHODS: We conducted a retrospective quality improvement project at an inpatient pediatric hematology/oncology floor and outpatient pediatric infusion center before and after implementation of circle priming. RESULTS: There was a statistically significant increase in percent interoperability compliance for the inpatient pediatric hematology/oncology floor from 4.1% prior to implementation of circle priming to 35.6% after (odds ratio 13.1 (95% CI, 3.96-43.1), p < 0.001), as well as for the outpatient pediatric infusion center from 18.5% to 47.3%, respectively (odds ratio 3.9 (95% CI, 2.7-5.9), p < 0.001). CONCLUSION: Implementation of circle priming has significantly increased the percentage of interoperability compliance for intravenous chemotherapy medications in our pediatric hematology/oncology patient care areas.

Concordance analysis of two databases to search for potential drug interactions in onco-hematologic patients.

INTRODUCTION: Potential drug interactions exert a significant impact on patient safety, especially within intricate onco-hematological treatments, potentially resulting in toxicity or treatment failures. Despite the availability of databases for potential drug interaction investigation, persistent heterogeneity in concordance rates and classifications exists. The additional variability in database agreement poses further complexity, notably in critical contexts like onco-hematology. AIM: To analyze the concordance of two databases for researching potential drug interaction in prescriptions for hematological patients at a University Hospital in the Midwest region of Brazil. METHOD: Cross-sectional study developed in a Brazilian hospital. The search for potential drug interaction was conducted in Micromedex® and UpToDate®. The variables were: the presence of potential drug interaction, severity, mechanism, management, and documentation. Data was analyzed in terms of frequency (absolute and relative), Cohen's kappa, and Fleiss kappa. RESULTS: The presence of potential drug interaction, showed a lack of concordance between the databases (k = -0.115 [95% CI: 0.361-0.532], p = 0.003). Regarding the mechanism, a strong agreement was observed (k = 0.805, p < 0.001 [95% CI: 0.550-0.941]). The management concordance showed a fair agreement, 46.8% (k = 0.22, p < 0.001 [95% CI: 0.099-0.341]). Stratifying the categories, significant concordance was observed in "Adjustment of dose + Monitoring" (k = 0.302, p = 0.018) and "Monitoring" (k = 0.417, p = 0.001), while other categories did not reach statistical significance. CONCLUSION: Our study emphasizes the variability in potential drug interaction research, revealing disparities in severity classification, management recommendations, and documentation practices across databases.

Examining rehabilitation access disparities: an integrated analysis of electronic health record data and population characteristics through bivariate choropleth mapping.

BACKGROUND: Despite efforts to view electronic health records (EHR) data through an equity lens, crucial contextual information regarding patients' social environments remains limited. Integrating EHR data and Geographic Information Systems (GIS) technology can give deeper insights into the relationships between patients' social environments, health outcomes, and geographic factors. This study aims to identify regions with the fastest and slowest access to outpatient physical therapy services using bivariate choropleth maps to provide contextual insights that may contribute to health disparity in access. METHODS: This was a retrospective cohort study of patients' access timelines for the first visit to outpatient physical therapy services (n = 10,363). The three timelines evaluated were (1) referral-to-scheduled appointment time, (2) scheduled appointment to first visit time, and (3) referral to first visit time. Hot and coldspot analyses (CI 95%) determined the fastest and slowest access times with patient-level characteristics and bivariate choropleth maps that were developed to visualize associations between access patterns and disadvantaged areas using Area Deprivation Index scores. Data were collected between January 1, 2016 and January 1, 2020. EHR data were geocoded via GIS technology to calculate geospatial statistics (Gi∗ statistic from ArcGIS Pro) in an urban area. RESULTS: Statistically significant differences were found for all three access timelines between coldspot (i.e., fast access group) and hotspot (i.e., slow access group) comparisons (p < .05). The hotspot regions had higher deprivation scores; higher proportions of residents who were older, privately insured, female, lived further from clinics; and a higher proportion of Black patients with orthopaedic diagnoses compared to the coldspot regions. CONCLUSIONS: Our study identified and described local areas with higher densities of patients that experienced longer access times to outpatient physical therapy services. Integration of EHR and GIS data is a more robust method to identify health disparities in access to care. With this approach, we can better understand the intricate interplay between social, economic, and environmental factors contributing to health disparities in access to care.

Surgical waiting lists and queue management in a Brazilian tertiary public hospital.

BACKGROUND: Centralized management of queues helps to reduce the surgical waiting time in the publicly funded healthcare system, but this is not a reality in the Brazilian Unified Healthcare System (BUHS). We describe the implementation of the "Patients with Surgical Indication" (PSI) in a Brazilian public tertiary hospital, the impact on waiting time, and its use in rationing oncological surgeries during the COVID-19 Pandemic. METHODS: Retrospective observational study of elective surgical requests (2016-2022) in a Brazilian general, public, tertiary university hospital. We recovered information regarding the inflows (indications), outflows and their reasons, the number of patients, and waiting time in queue. RESULTS: We enrolled 82,844 indications in the PSI (2016-2022). The waiting time (median and interquartile range) in days decreased from 98(48;168) in 2016 to 14(3;152) in 2022 (p < 0.01). The same occurred with the backlog that ranged from 6,884 in 2016 to 844 in 2022 (p < 001). During the Pandemic, there was a reduction in the number of non-oncological surgeries per month (95% confidence interval) of -10.9(-18.0;-3.8) during Phase I (January 2019-March 2020), maintenance in Phase II (April 2020-August 2021) 0.1(-10.0;10.4) and increment in Phase III (September 2021-December 2022) of 23.0(15.3;30.8). In the oncological conditions, these numbers were 0.6(-2.1;3.3) for Phase I, an increase of 3.2(0.7;5.6) in Phase II and 3.9(1,4;6,4) in Phase III. CONCLUSION: Implementing a centralized list of surgical indications and developing queue management principles proved feasible, with effective rationing. It unprecedentedly demonstrated the decrease in the median waiting time in Brazil.