Identifying high-risk geographic areas for cardiac arrest using three methods for cluster analysis

Identifying areas of Australia with high out-of-hospital cardiac arrest incidence and low bystander cardiopulmonary resuscitation rates: A retrospective, observational study

AIM

This study aims to explore regional variation and identify regions within Australia with high incidence of out-of-hospital cardiac arrest (OHCA) and low rates of bystander cardiopulmonary resuscitation (CPR).

METHOD

Adult OHCAs of presumed medical aetiology occurring across Australia between 2017 and 2019 were mapped onto local government areas (LGA) using the location of arrest coordinates. Bayesian spatial models were applied to provide "smoothed" estimates of OHCA incidence and bystander CPR rates (for bystander-witnessed OHCAs) for each LGA. For each state and territory, high-risk LGAs were defined as those with an incidence rate greater than the state or territory's 75th percentile and a bystander CPR rate less than the state or territory's 25th percentile.

RESULTS

A total of 62,579 OHCA cases attended by emergency medical services across 543 LGAs nationwide were included in the study. Nationally, the OHCA incidence rate across LGA ranged from 58.5 to 198.3 persons per 100,000, while bystander CPR rates ranged from 45% to 75%. We identified 60 high-risk LGAs, which were predominantly located in the state of New South Wales. Within each region, high-risk LGAs were typically located in regional and remote areas of the country, except for four metropolitan areas-two in Adelaide and two in Perth.

CONCLUSIONS

We have identified high-risk LGAs, characterised by high incidence and low bystander CPR rates, which are predominantly in regional and remote areas of Australia. Strategies for reducing OHCA and improving bystander response may be best targeted at these regions.

Spatiotemporal Analysis of Out-of-Hospital Cardiac Arrest Incidence and Survival Outcomes in Korea (2009-2021)

BACKGROUND

Out-of-hospital cardiac arrest is a major public health concern in Korea. Identifying spatiotemporal patterns of out-of-hospital cardiac arrest incidence and survival outcomes is crucial for effective resource allocation and targeted interventions. Thus, this study aimed to investigate the spatiotemporal epidemiology of out-of-hospital cardiac arrest in Korea, with a focus on identifying high-risk areas and populations and examining factors associated with prehospital outcomes.

METHODS

We conducted this population-based observational study using data from the Korean out-of-hospital cardiac arrest registry from January 2009 to December 2021. Using a Bayesian spatiotemporal model based on the Integrated Nested Laplace Approximation, we calculated the standardized incidence ratio and assessed the relative risk to compare the spatial and temporal distributions over time. The primary outcome was out-of-hospital cardiac arrest incidence, and the secondary outcomes included prehospital return of spontaneous circulation, survival to hospital admission and discharge, and good neurological outcomes.

RESULTS

Although the number of cases increased over time, the spatiotemporal analysis exhibited a discernible temporal pattern in the standardized incidence ratio of out-of-hospital cardiac arrest with a gradual decline over time (1.07; 95% credible interval [CrI], 1.04-1.09 in 2009 vs. 1.00; 95% CrI, 0.98-1.03 in 2021). The district-specific risk ratios of survival outcomes were more favorable in the metropolitan and major metropolitan areas. In particular, the neurological outcomes were significantly improved from relative risk 0.35 (0.31-0.39) in 2009 to 1.75 (1.65-1.86) in 2021.

CONCLUSION

This study emphasized the significance of small-area analyses in identifying high-risk regions and populations using spatiotemporal analyses. These findings have implications for public health planning efforts to alleviate the burden of out-of-hospital cardiac arrest in Korea.

Epidemic Characteristics, Spatiotemporal Pattern, and Risk Factors of Other Infectious Diarrhea in Fujian Province From 2005 to 2021: Retrospective Analysis

BACKGROUND

Other infectious diarrhea (OID) continues to pose a significant public health threat to all age groups in Fujian Province. There is a need for an in-depth analysis to understand the epidemiological pattern of OID and its associated risk factors in the region.

OBJECTIVE

In this study, we aimed to describe the overall epidemic characteristics and spatiotemporal pattern of OID in Fujian Province from 2005 to 2021 and explore the linkage between sociodemographic and environmental factors and the occurrence of OID within the study area.

METHODS

Notification data for OID in Fujian were extracted from the China Information System for Disease Control and Prevention. The spatiotemporal pattern of OID was analyzed using Moran index and Kulldorff scan statistics. The seasonality of and short-term impact of meteorological factors on OID were examined using an additive decomposition model and a generalized additive model. Geographical weighted regression and generalized linear mixed model were used to identify potential risk factors.

RESULTS

A total of 388,636 OID cases were recorded in Fujian Province from January 2005 to December 2021, with an average annual incidence of 60.3 (SD 16.7) per 100,000 population. Children aged <2 years accounted for 50.7% (196,905/388,636) of all cases. There was a steady increase in OID from 2005 to 2017 and a clear seasonal shift in OID cases from autumn to winter and spring between 2005 and 2020. Higher maximum temperature, atmospheric pressure, humidity, and precipitation were linked to a higher number of deseasonalized OID cases. The spatial and temporal aggregations were concentrated in Zhangzhou City and Xiamen City for 17 study years. Furthermore, the clustered areas exhibited a dynamic spreading trend, expanding from the southernmost Fujian to the southeast and then southward over time. Factors such as densely populated areas with a large <1-year-old population, less economically developed areas, and higher pollution levels contributed to OID cases in Fujian Province.

CONCLUSIONS

This study revealed a distinct distribution of OID incidence across different population groups, seasons, and regions in Fujian Province. Zhangzhou City and Xiamen City were identified as the major hot spots for OID. Therefore, prevention and control efforts should prioritize these specific hot spots and highly susceptible groups.

Impact of Receiving Hospital on Out-of-Hospital Cardiac Arrest Outcome: Racial and Ethnic Disparities in Texas

Background Factors associated with out-of-hospital cardiac arrest (OHCA) outcome disparities remain poorly understood. We evaluated the role of receiving hospital on OHCA outcome disparities. Methods and Results We studied people with OHCA who survived to hospital admission from TX-CARES (Texas Cardiac Arrest Registry to Enhance Survival), 2014 to 2021. Using census data, we stratified OHCAs into majority (>50%) strata: non-Hispanic White race and ethnicity, non-Hispanic Black race and ethnicity, and Hispanic or Latino ethnicity. We stratified hospitals into performance quartiles based on the primary outcome, survival with good neurologic outcome. We evaluated the association between race and ethnicity and care at higher-performance hospitals. We compared 3 models evaluating the association between race and ethnicity and outcome: (1) ignoring hospital, (2) adjusting for hospital as a random intercept, and (3) adjusting for hospital performance quartile. We adjusted models for possible confounders. We included 10 434 OHCAs. Hospital performance quartile outcome rates ranged from 11.3% (fourth) to 37.1% (first). Compared with OHCAs in neighborhoods of majority White race, those in neighborhoods of majority Black race (odds ratio [OR], 0.1 [95% CI, 0.1-0.1]) and Hispanic or Latino ethnicity (OR, 0.2 [95% CI, 0.2-0.2]) were less likely to be cared for at higher-performing hospitals. Compared with White neighborhoods (30.1%) and ignoring hospital, outcomes were worse in Black neighborhoods (15.4%; adjusted OR [aOR], 0.5 [95% CI, 0.4-0.5]) and Hispanic or Latino neighborhoods (19.2%; aOR, 0.6 [95% CI, 0.5-0.7]). Adjusting for hospital as a random intercept, outcomes improved for Black neighborhoods (aOR, 0.9 [95% CI, 0.7-1.05]) and Hispanic or Latino neighborhoods (aOR, 0.9 [95% CI, 0.8-0.99]). Adjusting for hospital performance quartile, outcomes improved for Black neighborhoods (aOR, 0.8 [95% CI, 0.7-1.01]) and Hispanic or Latino neighborhoods (aOR, 0.9 [95% CI, 0.8-0.996]). Conclusions In Black and Hispanic or Latino communities, OHCAs were less likely to be cared for at higher-performing hospitals, and adjusting for receiving hospital improved OHCA outcome disparities.

Prevalence and Geographic Features of Patients Eligible for Extracorporeal Cardiopulmonary Resuscitation

OBJECTIVE

This study sought to identify Out of Hospital Cardiac Arrests (OHCA) eligible for Extracorporeal Cardiopulmonary Resuscitation (ECPR), use Geographic Information Systems (GIS) to investigate geographic patterns, and investigate if correlation between ECPR candidacy and Social Determinants of Health (SDoH) exist.

METHODS

This study is of emergency medical service (EMS) runs for OHCA to an urban medical center from January 1, 2016 to December 31, 2020. All runs were filtered to inclusion criteria for ECPR: age 18-65, initial shockable rhythm, and no return of spontaneous circulation within initial defibrillations. Address level data were mapped in a GIS. Cluster detection assessed for granular areas of high concentration. The Center for Disease Control and Prevention (CDC) Social Vulnerability Index (SVI) was overlaid. The SVI ranges from 0-1 with higher values indicating increasing social vulnerability.

RESULTS

There were 670 EMS transports for OHCA during the study period. 12.7% (85/670) met inclusion criteria for ECPR. 90% (77/85) had appropriate addresses for geocoding. Three geographic clusters of events were detected. Two were residential areas and one was concentrated over a public use area of downtown Cleveland. The SVI for these locations was 0.79, indicative of high social vulnerability. Nearly half (32/77, 41.5%) occurred in neighborhoods with the highest level of social vulnerability (SVI ≥0.9).

CONCLUSION

A significant proportion of OHCAs were eligible for ECPR based on prehospital criteria. Utilizing GIS to map and analyze ECPR patients provided insights into the locations of these events and the SDoH that may be driving risk in these places.

First Responder CPR and Survival Differences in Texas Minority and Lower Socioeconomic Status Neighborhoods

INTRODUCTION

First responder (FR) cardiopulmonary resuscitation (CPR) is an important component of out-of-hospital cardiac arrest (OHCA) care. However, little is known about FR CPR disparities.

METHODS

We linked the 2014-2021 Texas Cardiac Arrest Registry to Enhance Survival (TX-CARES) database to census tract data. We included non-traumatic OHCAs that were not witnessed by 9-1-1 responders and did not receive bystander CPR. We defined census tracts as having >50% of a race/ethnicity: White, Black, or Hispanic/Latino. We also stratified patients into quartiles based on socioeconomic status (SES): household income, high school graduation, and unemployment. We also combined race/ethnicity and income to create a total of five mixed strata, comparing lower income and minority census tracts to high income White census tracts. We created mixed model logistic regression models, adjusting for confounders and modeling census tract as a random intercept. Using the models, we compared FR CPR rates for census race/ethnicity (Black and Hispanic/Latino compared to White), and SES quartiles (2nd, 3rd, and 4th quartiles compared to 1st quartiles). Secondarily, we evaluated the association between FR CPR and survival for all strata.

RESULTS

We included 21,966 OHCAs, and 57.4% had FR CPR. Evaluating the association between census tract characteristic and FR CPR, majority Black (aOR 0.30, 95% CI 0.22-0.41) had a lower bystander CPR rate when compared to majority White. The lowest income quartile had a lower rate of bystander CPR (aOR 0.80, 95% CI 0.65-0.98). The worst unemployment quartile was also associated with a lower rate of FR CPR (aOR 0.75, 95% CI 0.61-0.92). Combining race/ethnicity and income, middle income majority Black (30.0%; aOR 0.27, 95% CI 0.17-0.46) and low income >80% Black (31.8%; aOR 0.27, 95% CI 0.10-0.68) had lower rates of FR CPR in comparison to high income majority White. There were no associations between Hispanic or lower high school graduation and lower rates of FR CPR. We found no association between FR CPR and survival for all three strata.

CONCLUSION

While we identified disparities in FR CPR in low SES and majority Black census tracts, we identified no association between FR CPR and survival in Texas.

Perpetuating Disparity: Failure of the Kidney Transplant System to Provide the Most Kidney Transplants to Communities With the Greatest Need

BACKGROUND

The burden of end-stage kidney disease (ESKD) and kidney transplant rates vary significantly across the United States. This study aims to examine the mismatch between ESKD burden and kidney transplant rates from a perspective of spatial epidemiology.

METHODS

US Renal Data System data from 2015 to 2017 on incident ESKD and kidney transplants per 1000 incident ESKD cases was analyzed. Clustering of ESKD burden and kidney transplant rates at the county level was determined using local Moran's I and correlated to county health scores. Higher percentile county health scores indicated worse overall community health.

RESULTS

Significant clusters of high-ESKD burden tended to coincide with clusters of low kidney transplant rates, and vice versa. The most common cluster type had high incident ESKD with low transplant rates (377 counties). Counties in these clusters had the lowest overall mean transplant rate (61.1), highest overall mean ESKD incidence (61.3), and highest mean county health scores percentile (80.9%, P <0.001 vs all other cluster types). By comparison, counties in clusters with low ESKD incidence and high transplant rates (n=359) had the highest mean transplant rate (110.6), the lowest mean ESKD incidence (28.9), and the lowest county health scores (20.2%). All comparisons to high-ESKD/low-transplant clusters were significant at P value <0.001.

CONCLUSION

There was a significant mismatch between kidney transplant rates and ESKD burden, where areas with the greatest need had the lowest transplant rates. This pattern exacerbates pre-existing disparities, as disadvantaged high-ESKD regions already suffer from worse access to care and overall community health, as evidenced by the highest county health scores in the study.

Are there socioeconomic disparities in geographic accessibility to community first responders to out-of-hospital cardiac arrest in Ireland?

Out-of-hospital cardiac arrest (OHCA) is a leading cause of death worldwide. Without appropriate early resuscitation interventions, the prospect of survival is limited. This means that an effective community response is a critical enabler of increasing the number of people who survive. However, while OHCA incidence is higher in more deprived areas, propensity to volunteer is, in general, associated with higher socioeconomic status. In this context, we consider whether there are socioeconomic disparities in geographic accessibility to volunteer community first responders (CFRs) in Ireland, where CFR groups have developed organically and communities self-select to participate. We use geographic information systems and propensity score matching to generate a set of control areas with which to compare established CFR catchment areas. Differences between CFRs and controls in terms of the distribution of catchment deprivation and social fragmentation scores are assessed using two-sided Kolmogorov-Smirnov tests. Overall we find that while CFR schemes are centred in more deprived and socially fragmented areas, beyond a catchment of 4 min there is no evidence of differences in area-level deprivation or social fragmentation. Our findings show that self-selection as a model of CFR recruitment does not lead to more deprived areas being disadvantaged in terms of access to CFR schemes. This means that community-led health interventions can develop to the benefit of community members across the socioeconomic spectrum and may be relevant for other countries and jurisdictions looking to support similar models within communities.

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Out-of-hospital cardiac arrest (OHCA) is a major cause of unexpected death.

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OHCA is more prevalent in deprived areas and community response is key for survival.

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Irish community first responders (CFRs) self-select to participate in CFR schemes.

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We consider if there are socioeconomic disparities in geographic access to CFRs.

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Self-selection does not result in deprived areas having worse access to CFR schemes.

Neighborhood-level out-of-hospital cardiac arrest risk and the impact of local CPR interventions

Introduction

Methods

Results

Conclusions

County-level Differences in Liver-related Mortality, Waitlisting, and Liver Transplantation in the United States

BACKGROUND

Much of our understanding regarding geographic issues in transplantation is based on statistical techniques that do not formally account for geography and is based on obsolete boundaries such as donation service area.

METHODS

We applied spatial epidemiological techniques to analyze liver-related mortality and access to liver transplant services at the county level using data from the Centers for Disease Control and Prevention and Scientific Registry of Transplant Recipients from 2010 to 2018.

RESULTS

There was a significant negative spatial correlation between transplant rates and liver-related mortality at the county level (Moran's I, -0.319; P  = 0.001). Significant clusters were identified with high transplant rates and low liver-related mortality. Counties in geographic clusters with high ratios of liver transplants to liver-related deaths had more liver transplant centers within 150 nautical miles (6.7 versus 3.6 centers; P  < 0.001) compared with all other counties, as did counties in geographic clusters with high ratios of waitlist additions to liver-related deaths (8.5 versus 2.5 centers; P  < 0.001). The spatial correlation between waitlist mortality and overall liver-related mortality was positive (Moran's I, 0.060; P  = 0.001) but weaker. Several areas with high waitlist mortality had some of the lowest overall liver-related mortality in the country.

CONCLUSIONS

These data suggest that high waitlist mortality and allocation model for end-stage liver disease do not necessarily correlate with decreased access to transplant, whereas local transplant center density is associated with better access to waitlisting and transplant.

Mapping local hot spots with routine tuberculosis data: A pragmatic approach to identify spatial variability

Objective

To use routinely collected data, with the addition of geographic information and census data, to identify local hot spots of rates of reported tuberculosis cases.

Design

Residential locations of tuberculosis cases identified from eight public health facilities in Lima, Peru (2013–2018) were linked to census data to calculate neighborhood-level annual case rates. Heat maps of tuberculosis case rates by neighborhood were created. Local indicators of spatial autocorrelation, Moran’s I, were used to identify where in the study area spatial clusters and outliers of tuberculosis case rates were occurring. Age- and sex-stratified case rates were also assessed.

Results

We identified reports of 1,295 TB cases across 74 neighborhoods during the five-year study period, for an average annual rate of 124.2 reported TB cases per 100,000 population. In evaluating case rates by individual neighborhood, we identified a median rate of reported cases of 123.6 and a range from 0 to 800 cases per 100,000 population. Individuals aged 15–44 years old and men had higher case rates than other age groups and women. Locations of both hot and cold spots overlapped across age- and gender-specific maps.

Conclusions

There is significant geographic heterogeneity in rates of reported TB cases and evident hot and cold spots within the study area. Characterization of the spatial distribution of these rates and local hot spots may be one practical tool to inform the work of local coalitions to target TB interventions in their zones.

A spatiotemporal data mining study to identify high-risk neighborhoods for out-of-hospital cardiac arrest (OHCA) incidents

Out-of-hospital cardiac arrest (OHCA) is a worldwide health problem. The aim of the study is to utilize the territorial-wide OHCA data of Hong Kong in 2012-2015 to examine its spatiotemporal pattern and high-risk neighborhoods. Three techniques for spatiotemporal data mining (SaTScan's spatial scan statistic, Local Moran's I, and Getis Ord Gi*) were used to extract high-risk neighborhoods of OHCA occurrence and identify local clusters/hotspots. By capitalizing on the strengths of these methods, the results were then triangulated to reveal "truly" high-risk OHCA clusters. The final clusters for all ages and the elderly 65+ groups exhibited relatively similar patterns. All ages groups were mainly distributed in the urbanized neighborhoods throughout Kowloon. More diverse distribution primarily in less accessible areas was observed among the elderly group. All outcomes were further converted into an index for easy interpretation by the general public. Noticing the spatial mismatches between hospitals and ambulance depots (representing supplies) and high-risk neighborhoods (representing demands), this setback should be addressed along with public education and strategic ambulance deployment plan to shorten response time and improve OHCA survival rate. This study offers policymakers and EMS providers essential spatial evidence to assist with emergency healthcare planning and informed decision-making.

Spatial and temporal analysis of myocardial infarction incidence in Zanjan province, Iran

Background

Myocardial Infarction (MI) is a major important public health concern and has huge burden on health system across the world. This study aimed to explore the spatial and temporal analysis of the incidence of MI to identify potential clusters of the incidence of MI patterns across rural areas in Zanjan province, Iran.

Materials & methods

This was a retrospective and geospatial analysis study of the incidence of MI data from nine hospitals during 2014–2018. Three different spatial analysis methods (Spatial autocorrelation, hot spot analysis and cluster and outlier analysis) were used to identify potential clusters and high-risk areas of the incidence of MI at the study area.

Results

Three thousand eight hundred twenty patients were registered at Zanjan hospitals due to MI during 2014–2018. The overall age-adjusted incidence rate of MI was 343 cases per 100,000 person which was raised from 88 cases in 2014 to 114 cases in 2018 per 100,000 person-year (a 30% increase, P < 0.001). Golabar region had the highest age-adjusted incidence rate of MI (515 cases per 100,000 person). Five hot spots and one high-high cluster were detected using spatial analysis methods.

Conclusion

This study showed that there is a great deal of spatial variations in the pattern of the incidence of MI in Zanjan province. The high incidence rate of MI in the study area compared to the national average, is a warning to local health authorities to determine the possible causes of disease incidence and potential drivers of high-risk areas. The spatial cluster analysis provides new evidence for policy-makers to design tailored interventions to reduce the incidence of MI and allocate health resource to unmet need areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11695-8.

Spatial-temporal analysis of cause-specific cardiovascular hospital admission in Beijing, China

BACKGROUND

The main aim of this study was to explore the spatial-temporal patterns of cause-specific CVD admission in Beijing using retrospective SaTScan analysis.

METHODS

A spatial-temporal analysis was conducted at the district level based on the rates of total and cause-specific CVD admissions, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF) from 2013 to 2017. We used joint point regression, Global Moran's I and Anselin's local Moran's I, together with Kulldorff's scan statistic.

RESULTS

Hospital admission trend decreased during the study period. Admission rates followed a spatially clustered pattern with differences occurring between cause-specific CVDs. Clusters were mainly identified in ecological preservation areas, with a more likely cluster found in Daxing, Fangshan, Xicheng district for total CVD, CHD, AF and HF, respectively.

CONCLUSIONS

Hospital admission of cause-specific CVD showed spatial clustered pattern, especially in ecological preservation areas.

Spatiotemporal analysis of out-of-hospital cardiac arrest in the City of Los Angeles, 2011-2019

OBJECTIVE

The goal of this analysis is to spatiotemporally identify and categorize areas in a large urban city according to Out-of-Hospital Cardiac Arrest (OHCA) rates and No Bystander CPR (NBCPR) risk levels.

STUDY AREA AND PARTICIPANTS

The study comprised all cardiac arrests within the administrative geographic boundary of the City of Los Angeles. The final sample included 15,904 cases that were geolocated within 985 census tracts.

MAIN OUTCOMES AND MEASURES

The primary outcome was stratification of census tracts into risk levels of OHCA and NBCPR by observed spatiotemporal patterns.

RESULTS

Of 985 census tracts in the analytical sample, 182 census tracts (18.5%) were identified as having higher risk of OHCA and NBCPR. This assessment resulted in 129 census tracts in Tier 3 (moderate risk), 36 in Tier 2 (moderate-high risk), and 17 in Tier 1 (highest risk). Census tracts in Tiers 2 and 3 had higher amounts incident OHCA, while those in tier 1 had more OHCA events with NBCPR. These areas were largely contiguous and located in the Central and South areas of Los Angeles.

CONCLUSIONS

Using a novel three-tiered neighborhood risk classification tool, specific neighborhoods have been identified in the second largest city in the U.S. with consistently high or accelerating rates of OHCA and low bystander CPR. Further study of bystander response and community-based public health campaigns are needed in these communities.

Community disparities in out of hospital cardiac arrest care and outcomes in Texas

BACKGROUND

Large racial and socioeconomic inequalities exist for out-of-hospital cardiac arrest (OHCA) care and outcomes. We sought to characterize racial, ethnic, and socioeconomic disparities in OHCA care and outcomes in Texas.

METHODS

We analyzed 2014-2018 Texas-Cardiac Arrest Registry to Enhance Survival (CARES) data. Using census tracts, we defined race/ethnicity neighborhoods based on majority race/ethnicity composition: non-Hispanic/Latino white, non-Hispanic/Latino black, and Hispanic/Latino. We also stratified neighborhoods into socioeconomic categories: above and below the median for household income, employment rate, and high school graduation. We defined outcomes as bystander CPR rates, public bystander AED use, and survival to hospital discharge. Using mixed models, we analyzed the associations between outcomes and neighborhood (1) racial/ethnic categories and (2) socioeconomic categories.

RESULTS

We included data on 18,488 OHCAs. Relative to white neighborhoods, black neighborhoods had lower rates of AED use (OR 0.3, CI 0.2-0.4), and Hispanic/Latino neighborhoods had lower rates of bystander CPR (OR 0.7, CI 0.6-0.8), AED use (OR 0.4, CI 0.3-0.6), and survival (OR 0.8, CI 0.7-0.8). Lower income was associated with a lower rates of bystander CPR (OR 0.8, CI 0.7-0.8), AED use (OR 0.5, CI 0.4-0.8), and survival (OR 0.9, CI 0.9-0.98). Lower high school graduation was associated with a lower rate of bystander CPR (OR 0.8, CI 0.7-0.9) and AED use (OR 0.6, CI 0.4-0.9). Higher unemployment was associated with lower rates of bystander CPR (OR 0.9, CI 0.8-0.94) and AED use (OR 0.7, CI 0.5-0.99).

CONCLUSION

Minority and poor neighborhoods in Texas experience large and unacceptable disparities in OHCA bystander response and outcomes.

Despite Having Worse Risk Profiles, Northern Albertans Wait Longer for Specialist Follow-up After Emergency Department Visits for Atrial Fibrillation

Background

Atrial fibrillation and flutter (AFF) are common arrhythmias diagnosed in the emergency department (ED), and prompt follow-up with specialists may yield better outcomes. This study examines time to first specialist outpatient visit following ED discharge for AFF.

Methods

Alberta residents aged ≥ 35 years with ED presentations for AFF ending in discharge during 2017-2018 were extracted and linked with hospitalizations and physician claims. A spatial scan and multinomial logistic regression were performed. Regression model predictors included demographics, prior diagnoses, and prior health service use.

Results

ED presentations for 4387 patients (54% male; mean age 68 years) were analyzed. Two geographic areas were identified as clusters that had longer times than would be expected by chance: a north cluster of northern areas with an estimated median time of 98 days (95% confidence interval [CI] 82,139), and an east cluster of eastern areas with a median of 57 days (95% CI 47, 68). Patients in the north cluster were more likely to be younger (adjusted odds ratio [aOR] = 0.76 per 5 years, 95% CI 0.62, 0.93) and have prior histories of AFF (aOR = 1.45, 95% CI 1.11, 1.90), congestive heart failure (aOR=1.51, 95% CI 1.15, 1.98), chronic obstructive pulmonary disease (aOR = 2.03, 95% CI 1.55, 2.65), and diabetes (aOR = 1.30, 95% CI 1.00, 1.67). They were less likely to have prior general practitioner outpatient visits (aOR = 0.65 per 5 visits, 95% CI 0.53, 0.81) and specialist outpatient visits (aOR = 0.39, 95% CI 0.30, 0.50) than other patients.

Conclusions

Despite being at higher risk, patients in northern areas took longer to see a specialist after an ED presentation for AFF than those from other regions. Innovative strategies for promoting specialist follow-up should be explored.

Characterization of Regional Poison Center Utilization Through Geospatial Mapping

Introduction

Penetrance is the annual rate of human exposure calls per 1000 persons, a measure that historically describes poison center (PC) utilization. Penetrance varies by sociodemographic characteristics and by geography. Our goal in this study was to characterize the geospatial distribution of PC calls and describe the contribution of geospatial mapping to the understanding of PC utilization.

Methods

This was a single-center, retrospective study of closed, human, non-healthcare facility exposure calls to a regional PC over a five-year period. Exposure substance, gender, age, and zone improvement plan (ZIP) Code were geocoded to 2010 US Census data (household income, educational attainment, age, primary language) and spatially apportioned to US census tracts, and then analyzed with linear regression. Penetrance was geospatially mapped and qualitatively analyzed.

Results

From a total of 304,458 exposure calls during the study period, we identified 168,630 non-healthcare exposure calls. Of those records, 159,794 included ZIP Codes. After exclusions, we analyzed 156,805 records. Penetrance ranged from 0.081 – 38.47 calls/1000 population/year (median 5.74 calls/1000 persons/year). Regression revealed positive associations between >eighth-grade educational attainment (β = 5.05, p = 0.008), non-Hispanic Black (β = 1.18, p = 0.032) and American Indian (β = 3.10, p = 0.000) populations, suggesting that regions with higher proportions of these groups would display greater PC penetrance. Variability explained by regression modelling was low (R2 = 0.054), as anticipated. Geospatial mapping identified previously undocumented penetrance variability that was not evident in regression modeling.

Conclusion

PC calls vary substantially across sociodemographic strata. Higher proportions of non-Hispanic Black or American Indian residents and >eighth-grade educational attainment were associated with higher PC call penetrance. Geospatial mapping identified novel variations in penetrance that were not identified by regression modelling. Coupled with sociodemographic correlates, geospatial mapping may reveal disparities in PC access, identifying communities at which PC resources may be appropriately directed. Although the use of penetrance to describe PC utilization has fallen away, it may yet provide an important measure of disparity in healthcare access when coupled with geospatial mapping.

Spatial distribution and differences of stroke occurrence in the Rhone department of France (STROKE 69 cohort)

In France, 110,000 patients are admitted to hospital per year for stroke. Even though the relationship between stroke and risk factors such as low socio-economic status is well known, research in the spatial distribution (SD) of stroke as a contributing risk factor is less documented. Understanding the geographic differences of the disease may improve stroke prevention. In this study, a statistical spatial analysis was performed using a French cohort (STROKE 69) to describe spatial inequalities in the occurrence of stroke. STROKE 69 was a cohort study of 3,442 patients, conducted in the Rhône department of France, from November 2015 to December 2016. The cohort included all consecutive patients aged 18 years or older, with a likelihood of acute stroke within 24 hours of symptoms onset. Patients were geolocated, and incidence standardized rates ratio were estimated. SD models were identified using global spatial autocorrelation analysis and cluster detection methods. 2,179 patients were selected for analysis with spatial autocorrelation methods, including 1,467 patients with stroke, and 712 with a transient ischemic attack (TIA). Within both cluster detection methods, spatial inequalities were clearly visible, particularly in the northern region of the department and western part of the metropolitan area where rates were higher. Geographic methods for SD analysis were suitable tools to explain the spatial occurrence of stroke and identified potential spatial inequalities. This study was a first step towards understanding SD of stroke. Further research to explain SD using socio-economic data, care provision, risk factors and climate data is needed in the future.

Barriers to bystander CPR in deprived communities: Findings from a qualitative study

STUDY AIM

Rates of out of hospital cardiac arrest are higher in deprived communities. Bystander Cardiopulmonary Resuscitation (BCPR) can double the chance of survival but occurs less often in these communities in comparison to more affluent communities. People living in deprived communities are, therefore, doubly disadvantaged and there is limited evidence to explain why BCPR rates are lower. The aim of this paper is to examine the barriers to administering BCPR in deprived communities.

METHOD

Mixed method qualitative study with ten single sex focus groups (n = 61) conducted in deprived communities across central Scotland and 18 semi-structured interviews with stakeholders from the UK, Europe and the USA.

RESULTS

Two key themes related to confidence and environmental factors were identified to summarise the perceived barriers to administering BCPR in deprived communities. Barriers related to confidence included: self-efficacy; knowledge and awareness of how, and when, to administer CPR; accessing CPR training; having previous experience of administering BCPR; who required CPR; and whether the bystander was physically fit to give CPR. Environmental barriers focused on the safety of the physical environment in which people lived, and fear of reprisal from gangs or the police.

CONCLUSIONS

Barriers to administering BCPR identified in the general population are relevant to people living in deprived communities but are exacerbated by a range of contextual, individual and environmental factors. A one-size-fits-all approach is not sufficient to promote 'CPR readiness' in deprived communities. Future approaches to working with disadvantaged communities should be tailored to the local community.

The influence of past experiences on future willingness to perform bystander cardiopulmonary resuscitation

Background

The influence of past familial experiences of receiving cardiopulmonary resuscitation (CPR) and medical help in various cardiac arrest and nonfatal cardiac events toward willingness to “pay it forward” by helping the next cardiac arrest victim was explored.

Methods

Using a validated questionnaire, 6248 participants were asked to rate their willingness to perform bystander chest compression with mouth-to-mouth ventilation and chest compression-only CPR. Their past familial experiences of receiving cardiopulmonary resuscitation (CPR) and medical help in various cardiac arrest and nonfatal cardiac events were also recorded.

Results

Kruskal-Wallis test with post hoc Dunn’s pairwise comparisons showed that the following were significantly more willing to perform CPR with mouth-to-mouth ventilation: familial experience of “nonfatal cardiac events” (mean rank = 447) vs “out-of-hospital cardiac arrest with no CPR” (mean rank = 177), U = 35442.5, z = −2.055, p = 0.04; “in-hospital cardiac arrest and successful CPR” (mean rank = 2955.79) vs “none of these experiences” (mean rank = 2468.38), U = 111903, z = −2.60, p = 0.01; and “in-hospital cardiac arrest with successful CPR” (mean rank = 133.45) vs “out-of-hospital arrest with no CPR” (mean rank = 112.36), U = 4135.5, z = −2.06, p = 0.04. For compression-only CPR, Kruskal-Wallis test with multiple runs of Mann-Whitney U tests showed that “nonfatal cardiac events” group was statistically higher than the group with “none of these experiences” (mean rank = 3061.43 vs 2859.91), U = 1194658, z = −2.588, p = 0.01. The groups of “in-hospital cardiac arrest with successful CPR” and “in-hospital cardiac arrest with transient return of spontaneous circulation” were the most willing groups to perform compression-only CPR.

Conclusion

Prior familial experiences of receiving CPR and medical help, particularly among those with successful outcomes in a hospital setting, seem to increase the willingness to perform bystander CPR.

Patient, Neighborhood, and Spatial Determinants of Out-of-Hospital Cardiac Arrest Outcomes Throughout the Chain of Survival: A Community-Oriented Multilevel Analysis

Objective: Global and national trends of out-of-hospital cardiac arrest (OHCA) have been examined; however, geographic variation and socioeconomic disparities of OHCA outcomes in the community setting are less understood. We developed and tested a replicable, community-oriented assessment strategy aimed to identify spatial variations in OHCA outcomes using socioeconomic, prehospital, and in-hospital factors. Methods: Emergency medical service (EMS) records of adult, non-traumatic OHCA within Alachua County, FL (2012-2017) were retrospectively reviewed and matched to corresponding medical records at the University of Florida (UF). Incidence of cardiac arrest was geocoded to census tracts and connected to U.S. census socioeconomic attribute data. Primary outcomes include survival to emergency department (ED), hospital admission, discharge, and discharge to home. Multilevel mixed-effects logistic regression models were developed to assess sub-county geographic variance, probabilities of survival, and prehospital risk factors. Getis-Ord Gi statistic and Moran's I-test was applied to assess spatial clustering in outcome survival rates. Results: Of the 1562 OHCA cases extracted from EMS records, 1,335 (85.5%) were included with 372 transported to study site. Predicted probability of survival to ED was 57.0% (95CI: 51.3-62.3%). Of transported cases to study site ED, predicted probabilities of survival was to 41.7% (95CI: 36.1-47.6%) for hospital admission, 16.1% (95CI: 10.7-23.5%) for hospital discharge, and 7.1% (95CI: 3.7-13.3%) for home discharge. Census tracts accounted for significant variability in survival to ED (p < 0.001), discharge (p = 0.031), and home discharge outcomes (p = 0.036). There was no significant geographic variation in survival to admission outcome. Neighborhood-level factors significantly improved model fit for survival to ED, discharge, and discharge home outcomes. Multiple modifiable patient- and neighborhood-level variables of interest were identified, including rural-urban differences. Conclusion: We identified important geographic disparities that exist in OHCA outcomes at the community level. By using a replicable schematic, this variation can be explained through community-oriented modifiable socioeconomic and prehospital factors.

Hands-Only Cardiopulmonary Resuscitation Education: A Comparison of On-Screen With Compression Feedback, Classroom, and Video Education

STUDY OBJECTIVE

We compare 3 methods of hands-only cardiopulmonary resuscitation (CPR) education, using performance scores. A paucity of research exists on the comparative effectiveness of different types of hands-only CPR education. This study also includes a novel kiosk approach that has not previously been studied, to our knowledge.

METHODS

A randomized, controlled study compared participant scores on 4 hands-only CPR outcome measures after education with a 25- to 45-minute practice-while-watching classroom session (classroom), 4-minute on-screen feedback and practice session (kiosk), and 1-minute video viewing (video only). Participants took a 30-second compression test after initial training and again after 3 months.

RESULTS

After the initial education session, the video-only group had a lower total score (compressions correct on hand placement, rate, and depth) (-9.7; 95% confidence interval [CI] -16.5 to -3.0) than the classroom group. There were no significant differences on total score between classroom and kiosk participants. Additional outcome scores help explain which components negatively affect total score for each education method. The video-only group had lower compression depth scores (-9.9; 95% CI -14.0 to -5.7) than the classroom group. The kiosk group outperformed the classroom group on hand position score (4.9; 95% CI 1.3 to 8.6) but scored lower on compression depth score (-5.6; 95% CI -9.5 to -1.8). The change in 4 outcome variables was not significantly different across education type at 3-month follow-up.

CONCLUSION

Participants exposed to the kiosk session and those exposed to classroom education performed hands-only CPR similarly, and both groups showed skill performance superior to that of participants watching only a video. With regular retraining to prevent skills decay, the efficient and free hands-only CPR training kiosk has the potential to increase bystander intervention and improve survival from out-of-hospital cardiac arrest.

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

BACKGROUND

Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

METHODS

We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

RESULTS

We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

CONCLUSIONS

A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.

Temperature and age–gender effects on out-of-hospital cardiac arrest cases

Introduction:

Temperature is a key factor influencing the occurrence of out-of-hospital cardiac arrest, yet there is no equivalent study in Hong Kong. This study reports results involving a large-scale territory-wide investigation on the impacts of ambient temperature and age–gender differences on out-of-hospital cardiac arrest outcome in Hong Kong.

Methods:

This study included 25,467 out-of-hospital cardiac arrest cases treated by the Hong Kong Fire Services Department between December 2011 and November 2016 inclusive. Simple correlation and regression analyses were used to examine the relationships between out-of-hospital cardiac arrest cases and temperature, age and gender. Calendar charts were used to visualise temporal patterns of pre-hospital emergency medical services related to out-of-hospital cardiac arrest cases.

Results:

A strong negative curvilinear relationship was found between out-of-hospital cardiac arrest and daily temperature (r2 > 0.9) with prominent effects on elderly people aged ≥85 years. For each unit decrease in mean temperature in °C, there was a maximum of 5.6% increase in out-of-hospital cardiac arrest cases among all age groups and 7.3% increase in the ≥85 years elderly age group. Men were slightly more at risk of out-of-hospital cardiac arrest compared with women. The demand for out-of-hospital cardiac arrest–related emergency medical services was highest between 06:00 and 11:00 in the wintertime.

Conclusion:

This study provides the first local evidence linking weather and demographic effects with out-of-hospital cardiac arrest in Hong Kong. It offers empirical evidence to policymakers in support of strengthening existing emergency medical services to deal with the expected increase in out-of-hospital cardiac arrest in the wintertime and in regions with a large number of elderly population.

A comparison of spatial heterogeneity with local cluster detection methods for chronic respiratory diseases in Thailand

Background: The Centers for Disease Control and Prevention reported that deaths from chronic respiratory diseases (CRDs) in Thailand increased by almost 13% in 2010, along with an increased burden related to the disease. Evaluating the geographical heterogeneity of CRDs is important for surveillance. Previous studies have indicated that socioeconomic status has an effect on disease, and that this can be measured with variables such as night-time lights (NTLs) and industrial density (ID). However, there is no understanding of how NTLs and ID correlate with CRDs. We compared spatial heterogeneity obtained by using local cluster detection methods for CRDs and by correlating NTLs and ID with CRDs.

Methods: We applied the spatial scan statistic in SaTScan, as well as local indices of spatial association (LISA), Getis and Ord’s local Gi*(d) statistic, and Pearson correlation. In our analysis, data were collected on gender, age, household income, education, family size, occupation, region, residential area, housing construction materials, cooking fuels, smoking status and previously diagnosed CRDs by a physician from the National Socioeconomic Survey, which is a cross-sectional study conducted by the National Statistical Office of Thailand in 2010.

Results: According to our findings, the spatial scan statistic, LISA, and the local Gi*(d) statistic revealed similar results for areas with the highest clustering of CRDs. However, the hotspots for the spatial scan statistic covered a wider area than LISA and the local Gi*(d) statistic. In addition, there were persistent hotspots in Bangkok and the perimeter provinces. NTLs and ID have a positive correlation with CRDs.

Conclusions: This study demonstrates that all the statistical methods used could detect spatial heterogeneity of CRDs. NTLs and ID can serve as new parameters for determining disease hotspots by representing the population and industrial boom that typically contributes to epidemics.

The Effect of Rurality on Out-of-Hospital Cardiac Arrest Resuscitation Incidence: An Exploratory Study of a National Registry Utilizing a Categorical Approach

PURPOSE

Variation in incidence is a universal feature of out-of-hospital cardiac arrest (OHCA). One potential source of variation is the rurality of the location where the OHCA incident occurs. While previous work has used a simple binary approach to define rurality, the purpose of this study was to use a categorical approach to quantify the impact of urban-rural classification on OHCA incidence in the Republic of Ireland.

METHODS

The observed versus expected ratio of OHCA incidence where resuscitation was attempted for the period January 1, 2012, to December 31, 2014, was calculated for each of the 3,408 electoral divisions (ED). EDs were then classified into 1 of 6 urban-rural classes. Multilevel modeling was used to test for variation in incidence ratios (IR) across the urban-rural classes.

FINDINGS

A total of 4,755 cases of adult OHCA, not witnessed by Emergency Medical Services, where resuscitation was attempted were included in the study. The number of EDs in each category was as follows: city (n = 477); town (n = 293); near village (n = 182); remote village (n = 84); near rural (n = 1,479); remote rural (n = 893). The IR per ED varied from 0 to 18.38 (EDs, n = 3,408). Multilevel modeling showed that 2.36% of variation in IR was due to urban-rural classification. This dropped to 0.45% when adjusted for ED deprivation score and median distance to an ambulance station. The addition of other explanatory variables did not improve the model.

CONCLUSION

OHCA variation in Ireland is limited and almost fully explained by area-level deprivation and proximity to ambulance stations.

Spatio-temporal analysis of the incidence of colorectal cancer in Guangzhou, 2010-2014

INTRODUCTION

Colorectal cancer (CRC) is a common type of neoplasm. This study examined the spatio-temporal distribution of the CRC incidence in Guangzhou during 2010-2014.

METHODS

Colorectal cancer incidence data were obtained from the Guangzhou Cancer Registry System. Spatial autocorrelation analysis and a retrospective spatio-temporal scan were used to assess the spatio-temporal cluster distribution of CRC cases.

RESULTS

A total of 14,618 CRC cases were registered in Guangzhou during 2010-2014, with a crude incidence of 35.56/100,000 and an age-standardized rate of incidence by the world standard population (ASRIW) of 23.58/100,000. The crude incidence increased by 19.70% from 2010 (32.88/100,000) to 2014 (39.36/100,000) with an average annual percentage change (AAPC) of 4.33%. The AAPC of ASRIW was not statistically significant. The spatial autocorrelation analysis revealed a CRC incidence hot spot in central urban areas in Guangzhou City, which included 25 streets in southwestern Baiyun District, northwestern Haizhu District, and the border region between Liwan and Yuexiu Districts. Three high- and five low-incidence clusters were identified according to spatio-temporal scan of CRC incidence clusters. The high-incidence clusters were located in central urban areas including the border regions between Baiyun, Haizhu, Liwan, and Yuexiu Districts.

CONCLUSIONS

This study revealed the spatio-temporal cluster pattern of the incidence of CRC in Guangzhou. This information can inform allocation of health resources for CRC screening.

Geographic clustering of emergency department presentations for acute coronary syndromes and heart failure in Alberta: a population-based study

BACKGROUND

Collectively, the most common acute cardiac presentations to emergency departments are acute coronary syndromes (ACSs) and heart failure. We examined geographic variation and clustering in emergency department presentations by adults for ACS or heart failure in Alberta in 2010/11.

METHODS

All emergency department presentations for ACS or heart failure made by Alberta residents aged 35 years or more during 2010/11 were extracted from 5 linked population-based Alberta administrative health databases. Data extracted included demographic characteristics, hospital admissions and physician claims. Spatial scan tests and logistic regression analyses were performed.

RESULTS

There were 6342 patients with ACS (mean age 65.9 yr, 63.1% male) and 4780 patients with heart failure (mean age 76.6 yr, 49.9% male). For both ACS and heart failure, a primary cluster and 2 secondary clusters were identified. Different clusters were identified for the 2 conditions. For both conditions, patients living in the clusters had more primary care physician claims, prior emergency department visits and prior hospital admissions than did patients living outside the clusters. However, they were less likely to have had a specialist claim in the prior 2 years (odds ratio 0.64 [95% confidence interval 0.56-0.73] for ACS and 0.51 [95% confidence interval 0.43-0.61] for heart failure).

INTERPRETATION

Geographic areas were identified with higher numbers than expected of patients presenting to the emergency department for ACS or heart failure. Lower specialist access in these areas was associated with increased emergency department use.

Disparities in telephone CPR access and timing during out-of-hospital cardiac arrest

AIM

Spanish-only speaking residents in the United States face barriers to receiving potentially life-saving 911 interventions such as Telephone -cardiopulmonary resuscitation (TCPR) instructions. Since 2015, 911 dispatchers have placed an increased emphasis on rapid identification of potential cardiac arrest. The purpose of this study was to describe the utilization and timing of the 911 system during suspected out-of-hospital cardiac arrest (OHCA) by Spanish-speaking callers in Metropolitan Phoenix, Arizona.

METHODS

The dataset consisted of suspected OHCA from 911 centers from October 10, 2010 through December 31, 2013. Review of audio TCPR process data included whether the need for CPR was recognized by telecommunicators, whether CPR instructions were provided, and the time elements from call receipt to initiation of compressions.

RESULTS

A total of 3398 calls were made to 911 for suspected OHCA where CPR was indicated. A total of 39 (1.2%) were determined to have a Spanish language barrier. This averages to 18 calls per year with a Spanish language barrier during the study period, compared with 286 OHCAs expected per year among this population. The average time until telecommunicators recognized CPR need was 87.4s for the no language barrier group compared to 160.6s for the Spanish-language barrier group (p<0.001).Time to CPR instructions started was significantly different between these groups (144.4s vs 231.3s, respectively) (p<0.001), as was time to first compression, (174.4s vs. 290.9s, respectively) (p<0.001).

CONCLUSIONS

Our study suggests that Hispanic callers under-utilize the 911 system, and when they do call 911, there are significant delays in initiating CPR.

Socioeconomic status and survival from ventricular fibrillation out-of-hospital cardiac arrest

PURPOSE

Out-of-hospital cardiac arrest (OHCA) is a major cause of death in the United States. How individual-level socioeconomic status (SES) influences survival is uncertain.

METHODS

The investigation is a retrospective cohort study of adults who suffered OHCA and presented with a shockable rhythm in a metropolitan county from January 1, 1999-December 31, 2005. Individual-level measures of SES were obtained from vital records and surveys. SES measures included education and occupation. We used multivariable logistic regression to assess the independent association between SES measures and survival to hospital discharge.

RESULTS

Of the 1390 eligible OHCA patients, 374 (27%) survived to hospital discharge. Compared to those with less than high school diploma, the multivariable-adjusted odds ratio of survival was 1.36 (95% confidence interval [CI], 0.87-2.14) for high school graduates, 1.54 (95% CI, 0.95-2.48) for those with some college, and 1.96 (95% CI, 1.17-3.27) for those with college degrees (test for trend across the categories P < .001). We did not observe an independent association between occupation and survival.

CONCLUSIONS

Higher education was associated with greater survival after OHCA. This relationship was not explained by key demographic or clinical characteristics. A better understanding of the mechanism by which individual-level SES characteristics influence prognosis may provide opportunities to improve survival.

Identification of factors integral to designing community-based CPR interventions for high-risk neighborhood residents

BACKGROUND

High-risk neighborhoods can be identified as census tracts in which cardiac arrest incidence is high and bystander cardiopulmonary resuscitation (CPR) prevalence is low. However, little is known about how best to tailor community CPR training to high-risk neighborhood residents. The objective of this study was to identify factors integral to the design and implementation of community-based CPR intervention programs targeted to these areas.

METHODS

Using qualitative methods, six focus groups with 42 participants were conducted in high-risk neighborhoods in Columbus, Ohio during January and February 2011 to elicit resident views on how best to design community-based CPR educational programs for these neighborhoods. Snowball and purposeful sampling by community liaisons was used to recruit participants. Three reviewers analyzed the data in an iterative process to identify recurrent and unifying themes.

RESULTS

Focus group participants identified four principal considerations for the design of community-based CPR interventions: 1) identifying lay people to serve as motivated leaders while targeting both senior citizens and school children to increase reach, 2) finding appropriate community-based locations to hold CPR training, 3) providing incentives to encourage more people to participate, and 4) identifying and addressing barriers to participation.

CONCLUSION

Out-of-hospital cardiac arrest is a particular risk for minority and low-income communities. By working together with the community key factors integral to designing community-based CPR within these high-risk communities can be identified and implemented.

Spatial Pattern Detection of Tuberculosis: A Case Study of Si Sa Ket Province, Thailand

This retrospective population-based study was conducted to analyze spatial patterns of tuberculosis (TB) incidence in Si Sa Ket province, Thailand. TB notification data from 2004 to 2008 collected from TB clinics throughout the province was used along with population data to reveal a descriptive epidemiology of TB incidences. Global clustering patterns of the occurrence were assessed by using global spatial autocorrelation techniques. Additionally, local spatial pattern detection was performed by using local spatial autocorrelation and spatial scan statistic methods. The findings indicated clusters of the disease occurred in the study area. More specifically, significantly high-rate clusters were mostly detected in Mueang Si Sa Ket and Khukhan districts, which are located in the northwestern part of the province, while significantly low-rate clusters were persistent in Kantharalak and Benchalak districts, which are located at the southeastern area.

Regions of High Out-Of-Hospital Cardiac Arrest Incidence and Low Bystander CPR Rates in Victoria, Australia

Background

Out-of-hospital cardiac arrest (OHCA) remains a major public health issue and research has shown that large regional variation in outcomes exists. Of the interventions associated with survival, the provision of bystander CPR is one of the most important modifiable factors. The aim of this study is to identify census areas with high incidence of OHCA and low rates of bystander CPR in Victoria, Australia

Methods

We conducted an observational study using prospectively collected population-based OHCA data from the state of Victoria in Australia. Using ArcGIS (ArcMap 10.0), we linked the location of the arrest using the dispatch coordinates (longitude and latitude) to Victorian Local Government Areas (LGAs). We used Bayesian hierarchical models with random effects on each LGA to provide shrunken estimates of the rates of bystander CPR and the incidence rates.

Results

Over the study period there were 31,019 adult OHCA attended, of which 21,436 (69.1%) cases were of presumed cardiac etiology. Significant variation in the incidence of OHCA among LGAs was observed. There was a 3 fold difference in the incidence rate between the lowest and highest LGAs, ranging from 38.5 to 115.1 cases per 100,000 person-years. The overall rate of bystander CPR for bystander witnessed OHCAs was 62.4%, with the rate increasing from 56.4% in 2008–2010 to 68.6% in 2010–2013. There was a 25.1% absolute difference in bystander CPR rates between the highest and lowest LGAs.

Conclusion

Significant regional variation in OHCA incidence and bystander CPR rates exists throughout Victoria. Regions with high incidence and low bystander CPR participation can be identified and would make suitable targets for interventions to improve CPR participation rates.

Presumed Regional Incidence Rate of Out-of-Hospital Cardiac Arrest in Korea

The regional incidence rates of out-of-hospital cardiac arrest (OHCA) were traditionally calculated with the residential population as the denominator. The aim of this study was to estimate the true incidence rate of OHCA and to investigate characteristics of regions with overestimated and underestimated OHCA incidence rates. We used the national OHCA database from 2006 to 2010. The nighttime residential and daytime transient populations were investigated from the 2010 Census. The daytime population was calculated by adding the daytime influx of population to, and subtracting the daytime outflow from, the nighttime residential population. Conventional age-standardized incidence rates (CASRs) and daytime corrected age-standardized incidence rates (DASRs) for OHCA per 100,000 person-years were calculated in each county. A total of 97,291 OHCAs were eligible. The age-standardized incidence rates of OHCAs per 100,000 person-years were 34.6 (95% CI: 34.3-35.0) in the daytime and 24.8 (95% CI: 24.5-25.1) in the nighttime among males, and 14.9 (95% CI: 14.7-15.1) in the daytime, and 10.4 (95% CI: 10.2-10.6) in the nighttime among females. The difference between the CASR and DASR ranged from 35.4 to -11.6 in males and from 6.1 to -1.0 in females. Through the Bland-Altman plot analysis, we found the difference between the CASR and DASR increased as the average CASR and DASR increased as well as with the larger daytime transient population. The conventional incidence rate was overestimated in counties with many OHCA cases and in metropolitan cities with large daytime population influx and nighttime outflow, while it was underestimated in residential counties around metropolitan cities.

Geographic clustering of emergency department presentations for atrial fibrillation and flutter in Alberta, Canada

OBJECTIVES

Atrial fibrillation and flutter (AFF) are the most common arrhythmias seen in the outpatient setting, and they affect more than 300,000 adult Canadians. The aims of this study were to examine temporal and geographic trends in emergency department (ED) presentations made by adults (age ≥ 35 years) for AFF in Alberta, Canada, from 1999 to 2011. Statistical disease cluster detection techniques were used to identify geographic areas with higher numbers of individuals presenting with AFF and higher numbers of ED presentations for AFF than expected by chance alone. Geographic clusters of individuals with stroke or heart failure follow-up within 365 days of ED presentations for AFF were also identified.

METHODS

All ED presentations for AFF made by individuals aged ≥35 years were extracted from Alberta's Ambulatory Care Classification System. The Alberta Health Care Insurance Plan provided population counts and demographics for the patients presenting (age, sex, year, geographic unit). The Physician Claims File provided non-ED physician claims data after a patient's ED presentation. Statistical analyses included numerical and graphical summaries, directly standardized rates, and statistical disease cluster detection tests.

RESULTS

During 12 years, there were 63,395 ED presentations for AFF made by 32,101 individuals. Standardized rates remained relatively stable over time, at about two per 1,000 for individuals presenting to the ED for AFF and about three per 1,000 for ED presentations for AFF. The northern and southeastern parts of the province were identified as clusters of individuals presenting for AFF, and ED presentations for AFF, and several of the areas demonstrated clusters in multiple years. Further, several of the geographic clusters were also identified as potential clusters for stroke or heart failure within 365 days after the ED presentations for AFF.

CONCLUSIONS

This population-based study spanned 12 fiscal years and showed variations in the number of people presenting to EDs for AFF and the number of ED presentations for AFF over geography. The potential clusters identified may represent geographic areas with higher disease severity or a lower availability of non-ED health services. The clusters are not all likely to have occurred by chance, and further investigation and intervention could occur to reduce ED presentations for AFF.

Barriers to calling 911 and learning and performing cardiopulmonary resuscitation for residents of primarily Latino, high-risk neighborhoods in Denver, Colorado

STUDY OBJECTIVE

Individuals in neighborhoods composed of minority and lower socioeconomic status populations are more likely to have an out-of-hospital cardiac arrest event, less likely to have bystander cardiopulmonary resuscitation (CPR) performed, and less likely to survive. Latino cardiac arrest victims are 30% less likely than whites to have bystander CPR performed. The goal of this study is to identify barriers and facilitators to calling 911, and learning and performing CPR in 5 low-income, Latino neighborhoods in Denver, CO.

METHODS

Six focus groups and 9 key informant interviews were conducted in Denver during the summer of 2012. Purposeful and snowball sampling, conducted by community liaisons, was used to recruit participants. Two reviewers analyzed the data to identify recurrent and unifying themes. A qualitative content analysis was used with a 5-stage iterative process to analyze each transcript.

RESULTS

Six key barriers to calling 911 were identified: fear of becoming involved because of distrust of law enforcement, financial, immigration status, lack of recognition of cardiac arrest event, language, and violence. Seven cultural barriers were identified that may preclude performance of bystander CPR: age, sex, immigration status, language, racism, strangers, and fear of touching someone. Participants suggested that increasing availability of tailored education in Spanish, increasing the number of bilingual 911 dispatchers, and policy-level changes, including CPR as a requirement for graduation and strengthening Good Samaritan laws, may serve as potential facilitators in increasing the provision of bystander CPR.

CONCLUSION

Distrust of law enforcement, language concerns, lack of recognition of cardiac arrest, and financial issues must be addressed when community-based CPR educational programs for Latinos are implemented.

Multiple cluster analysis for the identification of high-risk census tracts for out-of-hospital cardiac arrest (OHCA) in Denver, Colorado

BACKGROUND

Prior research has shown that high-risk census tracts for out-of-hospital cardiac arrest (OHCA) can be identified. High-risk neighborhoods are defined as having a high incidence of OHCA and a low prevalence of bystander cardiopulmonary resuscitation (CPR). However, there is no consensus regarding the process for identifying high-risk neighborhoods.

OBJECTIVE

We propose a novel summary approach to identify high-risk neighborhoods through three separate spatial analysis methods: Empirical Bayes (EB), Local Moran's I (LISA), and Getis Ord Gi* (Gi*) in Denver, Colorado.

METHODS

We conducted a secondary analysis of prospectively collected Emergency Medical Services data of OHCA from January 1, 2009 to December 31, 2011 from the City and County of Denver, Colorado. OHCA incidents were restricted to those of cardiac etiology in adults ≥18 years. The OHCA incident locations were geocoded using Centrus. EB smoothed incidence rates were calculated for OHCA using Geoda and LISA and Gi* calculated using ArcGIS 10.

RESULTS

A total of 1102 arrests in 142 census tracts occurred during the study period, with 887 arrests included in the final sample. Maps of clusters of high OHCA incidence were overlaid with maps identifying census tracts in the below the Denver County mean for bystander CPR prevalence. Five census tracts identified were designated as Tier 1 high-risk tracts, while an additional 7 census tracts where designated as Tier 2 high-risk tracts.

CONCLUSION

This is the first study to use these three spatial cluster analysis methods for the detection of high-risk census tracts. These census tracts are possible sites for targeted community-based interventions to improve both cardiovascular health education and CPR training.

Accuracy of prehospital transport time estimation

OBJECTIVES

Estimates of prehospital transport times are an important part of emergency care system research and planning; however, the accuracy of these estimates is unknown. The authors examined the accuracy of three estimation methods against observed transport times in a large cohort of prehospital patient transports.

METHODS

This was a validation study using prehospital records in King County, Washington, and southwestern Pennsylvania from 2002 to 2006 and 2005 to 2011, respectively. Transport time estimates were generated using three methods: linear arc distance, Google Maps, and ArcGIS Network Analyst. Estimation error, defined as the absolute difference between observed and estimated transport time, was assessed, as well as the proportion of estimated times that were within specified error thresholds. Based on the primary results, a regression estimate was used that incorporated population density, time of day, and season to assess improved accuracy. Finally, hospital catchment areas were compared using each method with a fixed drive time.

RESULTS

The authors analyzed 29,935 prehospital transports to 44 hospitals. The mean (± standard deviation [±SD]) absolute error was 4.8 (±7.3) minutes using linear arc, 3.5 (±5.4) minutes using Google Maps, and 4.4 (±5.7) minutes using ArcGIS. All pairwise comparisons were statistically significant (p < 0.01). Estimation accuracy was lower for each method among transports more than 20 minutes (mean [±SD] absolute error was 12.7 [±11.7] minutes for linear arc, 9.8 [±10.5] minutes for Google Maps, and 11.6 [±10.9] minutes for ArcGIS). Estimates were within 5 minutes of observed transport time for 79% of linear arc estimates, 86.6% of Google Maps estimates, and 81.3% of ArcGIS estimates. The regression-based approach did not substantially improve estimation. There were large differences in hospital catchment areas estimated by each method.

CONCLUSIONS

Route-based transport time estimates demonstrate moderate accuracy. These methods can be valuable for informing a host of decisions related to the system organization and patient access to emergency medical care; however, they should be employed with sensitivity to their limitations.

Barriers and facilitators to learning and performing cardiopulmonary resuscitation in neighborhoods with low bystander cardiopulmonary resuscitation prevalence and high rates of cardiac arrest in Columbus, OH

BACKGROUND

Residents who live in neighborhoods that are primarily black, Latino, or poor are more likely to have an out-of-hospital cardiac arrest, less likely to receive cardiopulmonary resuscitation (CPR), and less likely to survive. No prior studies have been conducted to understand the contributing factors that may decrease the likelihood of residents learning and performing CPR in these neighborhoods. The goal of this study was to identify barriers and facilitators to learning and performing CPR in 3 low-income, high-risk, and predominantly black neighborhoods in Columbus, OH.

METHODS AND RESULTS

Community-Based Participatory Research approaches were used to develop and conduct 6 focus groups in conjunction with community partners in 3 target high-risk neighborhoods in Columbus, OH, in January to February 2011. Snowball and purposeful sampling, done by community liaisons, was used to recruit participants. Three reviewers analyzed the data in an iterative process to identify recurrent and unifying themes. Three major barriers to learning CPR were identified and included financial, informational, and motivational factors. Four major barriers were identified for performing CPR and included fear of legal consequences, emotional issues, knowledge, and situational concerns. Participants suggested that family/self-preservation, emotional, and economic factors may serve as potential facilitators in increasing the provision of bystander CPR.

CONCLUSIONS

The financial cost of CPR training, lack of information, and the fear of risking one's own life must be addressed when designing a community-based CPR educational program. Using data from the community can facilitate improved design and implementation of CPR programs.