Heat Stress Illness Emergency Department Visits in National Environmental Public Health Tracking States, 2005-2010

Rescue service deployment data as an indicator of heat morbidity in Frankfurt / Main, Germany (2014-2022) - Trend association with various heat exposure indicators and considerations for outreach

Many publications dealt with the monitoring of heat-related mortality. Fewer analyses referred to indicators of heat-related morbidity. The aim of this work was to describe the heat-related morbidity using rescue service data from the city of Frankfurt/Main, Germany for the time period 2014-2022, with regard to the questions: 1) How do rescue service deployments develop over the years? Is there a trend identifiable towards a decrease in deployments over the years, e.g. as an effect of either (physiological) adaptation of the population or of the measures for prevention of heat-related morbidity? 2) Which heat parameters (days with a heat warning, heat days, heat weeks, heat waves) are most strongly associated with heat-related morbidity in terms of rescue service deployments and might therefore be additionally used as an easily communicable and understandable heat-warning indicator? Rescue service data were provided by the interdisciplinary medical supply compass system "IVENA" and adjusted for population development including age development. The effect of various indicators for heat exposure, such as days with a heat warning from the German meteorological service based on the scientific concept of "perceived heat", heat days, heat wave days and heat week days on different endpoints for heat morbidity (deployments in total as well as for heat associated diagnoses) was calculated using both difference-based (difference ± 95% CI) and ratio-based (ratio ± 95% CI) effect estimators. Rescue services deployments in summer months increased overall from 2014 to 2022 in all age groups over the years (2698 to 3517/100.000 population). However, there was a significant decrease in 2020, which could be explained by the special situation of the COVID-19 pandemic, probably caused by the absence of tourists and commuters from the city. In addition, no data are available on the actual implementation of the measures by the population. Therefore, an effect of the measures taken to prevent heat-associated morbidity in Frankfurt am Main could not be directly demonstrated, and our first question cannot be answered on the basis of these data. Almost all heat definitions used for exposure (day with a heat warning, heat day, heat wave day, heat week day) showed significant effects on heat-associated diagnoses in every year. When analysing the effect on all deployments, the effect was in part strongly dependent on individual years: Heat wave days and heat week days even showed negative effects in some years. The definition heat day led to a significant increase in rescue service deployments in all single years between 2014 and 2022 (ratio 2014-2022 1.09 (95CI 1.07-1.11); with a range of 1.05 (95CI 1.01-1.09) in 2020 and 1.14 (95CI 1.08-1.21) in 2014), this was not the case for days with a heat warning (ratio 2014-2022 1.04 (95CI1.02-1.05); with a range of 1.01 (95CI 0.97-1.05) in 2017 and 1.16 (95CI 1.10-1.23). Thus being not inferior to the heat warning day, the "heat day" defined as ≥32 °C maximum temperature, easily obtainable from the weather forecast, can be recommended for the activities of the public health authorities (warning, surveillance etc.) regarding heat health action planning.

Emergency Department Visits for Heat-Related Emergency Conditions in the United States from 2008-2020

Exposure to high temperatures is detrimental to human health. As climate change is expected to increase the frequency of extreme heat events, and raise ambient temperatures, an investigation into the trend of heat-related emergency department (ED) visits over the past decade is necessary to assess the human health impact of this growing public health crisis. ED visits were examined using the Nationwide Emergency Department Sample. Visits were included if the diagnostic field contained an ICD-9-CM or ICD-10-CM code specific to heat-related emergency conditions. Weighted counts were generated using the study design and weighting variables, to estimate the national burden of heat-related ED visits. A total of 1,078,432 weighted visits were included in this study. The annual incidence rate per 100,000 population increased by an average of 2.85% per year, ranging from 18.21 in 2009, to 32.34 in 2018. The total visit burden was greatest in the South (51.55%), with visits increasing to the greatest degree in the Midwest (8.52%). ED visit volume was greatest in July (29.79%), with visits increasing to the greatest degree in July (15.59%) and March (13.18%). An overall increase in heat-related ED visits for heat-related emergency conditions was found during the past decade across the United States, affecting patients in all regions and during all seasons.

Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions

Exposure to extreme heat is a known risk factor that is associated with increased heat-related illness (HRI) outcomes. The relevance of heat wave definitions (HWDs) could change across health conditions and geographies due to the heterogenous climate profile. This study compared the sensitivity of 28 HWDs associated with HRI emergency department visits over five summer seasons (2011−2016), stratified by two physiographic regions (Coastal and Piedmont) in North Carolina. The HRI rate ratios associated with heat waves were estimated using the generalized linear regression framework assuming a negative binomial distribution. We compared the Akaike Information Criterion (AIC) values across the HWDs to identify an optimal HWD. In the Coastal region, HWDs based on daily maximum temperature with a threshold > 90th percentile for two or more consecutive days had the optimal model fit. In the Piedmont region, HWD based on the daily minimum temperature with a threshold value > 90th percentile for two or more consecutive days was optimal. The HWDs with optimal model performance included in this study captured moderate and frequent heat episodes compared to the National Weather Service (NWS) heat products. This study compared the HRI morbidity risk associated with epidemiologic-based HWDs and with NWS heat products. Our findings could be used for public health education and suggest recalibrating NWS heat products.

Investigating age and regional effects on the relation between the incidence of heat-related ambulance transport and daily maximum temperature or WBGT

Background

Although age and regional climate are considered to have effects on the incidence ratio of heat-related illness, quantitative estimation of age or region on the effect of occurring temperature for heat stroke is limited.

Methods

By utilizing data on the number of daily heat-related ambulance transport (HAT) in each of three age groups (7–17, 18–64, 65 years old, or older) and 47 prefectures in Japan, and daily maximum temperature (DMT) or Wet Bulb Globe Temperature (DMW) of each prefecture for the summer season, the effects of age and region on heat-related illness were studied. Two-way ANOVA was used to analyze the significance of the effect of age and 10 regions in Japan on HAT. The population-weighted average of DMT or DMW measured at weather stations in each prefecture was used as DMT or DMW for each prefecture. DMT or DMW when HAT is one in 100,000 people (T₁ and W₁, respectively) was calculated for each age category and prefecture as an indicator of heat acclimatization. The relation between T₁ or W₁ and average DMT or DMW of each age category and prefecture were also analyzed.

Results

HAT of each age category and prefecture was plotted nearly on the exponential function of corresponding DMT or DMW. Average R² of the regression function in 47 prefectures in terms of DMW was 0.86, 0.93, and 0.94 for juveniles, adults, and elderly, respectively. The largest regional difference of W₁ in 47 prefectures was 4.5 and 4.8 °C for juveniles and adults, respectively between Hokkaido and Tokyo, 3.9 °C for elderly between Hokkaido and Okinawa. Estimated W₁ and average DMT or DMW during the summer season for 47 prefectures was linearly related. Regarding age difference, the regression line showed that W₁ of the prefecture for DMW at 30 °C of WBGT was 31.1 °C, 32.4 °C, and 29.8 °C for juveniles, adults, and elderly, respectively.

Conclusions

Age and regional differences affected the incidence of HAT. Thus, it is recommended that public prevention measures for heat-related disorders take into consideration age and regional variability.

Using social security number to identify sub-populations vulnerable to the health impacts from extreme heat in Florida, U.S

BACKGROUND

Some socioeconomically vulnerable groups may experience disproportionately higher risk of extreme heat illness than other groups, but no study has utilized the presence/absence of a social security number (SSN) as a proxy for vulnerable sub-populations.

METHODS

This study focused on the warm season from 2008 to 2012 in Florida, U.S. With a total number of 8,256,171 individual level health outcomes, we devised separate case-crossover models for five heat-sensitive health outcomes (cardiovascular disease, dehydration, heat-related illness, renal disease, and respiratory disease), type of health care visit (emergency department (ED) and hospitalization), and patients reporting/not reporting an SSN. Each stratified model also considered potential effect modification by sex, age, or race/ethnicity.

RESULTS

Mean temperature raised the odds of five heat-sensitive health outcomes with the highest odds ratios (ORs) for heat-related illness. Sex significantly modified heat exposure effects for dehydration ED visits (Males: 1.145, 95 % CI: 1.137-1.153; Females: 1.110, 95 % CI: 1.103-1.117) and hospitalization (Males: 1.116, 95 % CI: 1.110-1.121; Females: 1.100, 95 % CI: 1.095-1.105). Patients not reporting an SSN between 25 and 44 years (1.264, 95 % CI: 1.192-1.340) exhibited significantly higher dehydration ED ORs than those reporting an SSN (1.146, 95 % CI: 1.136-1.157). We also observed significantly higher ORs for cardiovascular disease hospitalization from the no SSN group (SSN: 1.089, 95 % CI: 1.088-1.090; no SSN: 1.100, 95 % CI: 1.091-1.110).

CONCLUSIONS

This paper partially supports the idea that individuals without an SSN could experience higher risks of dehydration (for those 25-45 years), renal disease, and cardiovascular disease than those with an SSN.

Heat-Related Illnesses Transported by United States Emergency Medical Services

Background and objectives: Heat-related illness (HRI) can have significant morbidity and mortality consequences. Research has predominately focused on HRI in the emergency department, yet health care leading up to hospital arrival can impact patient outcomes. Therefore, the purpose of this study was to describe HRI in the prehospital setting. Materials and Methods: A descriptive epidemiological design was utilized using data from the National Emergency Medical Services (EMS) Information System for the 2017-2018 calendar years. Variables of interest in this study were: patient demographics (age, gender, race), US census division, urbanicity, dispatch timestamp, incident disposition, primary provider impression, and regional temperatures. Results: There were 34,814 HRIs reported. The majority of patients were white (n = 10,878, 55.6%), males (n = 21,818, 62.7%), and in the 25 to 64 age group (n = 18,489, 53.1%). Most HRIs occurred in the South Atlantic US census division (n = 11,732, 33.7%), during the summer (n = 23,873, 68.6%), and in urban areas (n = 27,541, 83.5%). The hottest regions were East South Central, West South Central, and South Atlantic, with peak summer temperatures in excess of 30.0 °C. In the spring and summer, most regions had near normal temperatures within 0.5 °C of the long-term mean. EMS dispatch was called for an HRI predominately between the hours of 11:00 a.m.-6:59 p.m. (n = 26,344, 75.7%), with the majority (27,601, 79.3%) of HRIs considered heat exhaustion and requiring the patient to be treated and transported (n = 24,531, 70.5%). Conclusions: All age groups experienced HRI but particularly those 25 to 64 years old. Targeted education to increase public awareness of HRI in this age group may be needed. Region temperature most likely explains why certain divisions of the US have higher HRI frequency. Afternoons in the summer are when EMS agencies should be prepared for HRI activations. EMS units in high HRI frequency US divisions may need to carry additional treatment interventions for all HRI types.

Association Between Work-Related Hyperthermia Emergency Department Visits and Ambient Heat in Five Southeastern States, 2010-2012-A Case-Crossover Study

The objective of this study is to assess ambient temperatures' and extreme heat events' contribution to work-related emergency department (ED) visits for hyperthermia in the southeastern United States to inform prevention. Through a collaborative network and established data framework, work-related ED hyperthermia visits in five participating southeastern U.S. states were analyzed using a time stratified case-crossover design. For exposure metrics, day- and location-specific measures of ambient temperatures and county-specific identification of extreme heat events were used. From 2010 to 2012, 5,017 work-related hyperthermia ED visits were seen; 2,298 (~46%) of these visits occurred on days when the daily maximum heat index was at temperatures the Occupational Safety and Health Administration designates as having "lower" or "moderate" heat risk. A 14% increase in risk of ED visit was seen for a 1°F increase in average daily mean temperature, modeled as linear predictor across all temperatures. A 54% increase in risk was seen for work-related hyperthermia ED visits during extreme heat events (two or more consecutive days of unusually high temperatures) when controlling for average daily mean temperature. Despite ambient heat being a well-known risk to workers' health, this study's findings indicate ambient heat contributed to work-related ED hyperthermia visits in these five states. Used alone, existing OSHA heat-risk levels for ambient temperatures did not appear to successfully communicate workers' risk for hyperthermia in this study. Findings should inform future heat-alert communications and policies, heat prevention efforts, and heat-illness prevention research for workers in the southeastern United States.

Impacts of climate change on the public health of the Mediterranean Basin population - Current situation, projections, preparedness and adaptation

The Mediterranean Basin is undergoing a warming trend with longer and warmer summers, an increase in the frequency and the severity of heat waves, changes in precipitation patterns and a reduction in rainfall amounts. In this unique populated region, which is characterized by significant gaps in the socio-economic levels particularly between the North (Europe) and South (Africa), parallel with population growth and migration, increased water demand and forest fires risk - the vulnerability of the Mediterranean population to human health risks increases significantly. Indeed, climatic changes impact the health of the Mediterranean population directly through extreme heat, drought or storms, or indirectly by changes in water availability, food provision and quality, air pollution and other stressors. The main health effects are related to extreme weather events (including extreme temperatures and floods), changes in the distribution of climate-sensitive diseases and changes in environmental and social conditions. The poorer countries, particularly in North Africa and the Levant, are at highest risk. Climate change affects the vulnerable sectors of the region, including an increasingly older population, with a larger percentage of those with chronic diseases, as well as poor people, which are therefore more susceptible to the effects of extreme temperatures. For those populations, a better surveillance and control systems are especially needed. In view of the climatic projections and the vulnerability of Mediterranean countries, climate change mitigation and adaptation become ever more imperative. It is important that prevention Health Action Plans will be implemented, particularly in those countries that currently have no prevention plans. Most adaptation measures are "win-win situation" from a health perspective, including reducing air pollution or providing shading solutions. Additionally, Mediterranean countries need to enhance cross-border collaboration, as adaptation to many of the health risks requires collaboration across borders and also across the different parts of the basin.

Age-Specific Associations of Ozone and Fine Particulate Matter with Respiratory Emergency Department Visits in the United States

RATIONALE

Whereas associations between air pollution and respiratory morbidity for adults 65 years and older are well documented in the United States, the evidence for people under 65 is less extensive. To address this gap, the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program collected respiratory emergency department (ED) data from 17 states.

OBJECTIVES

To estimate age-specific acute effects of ozone and fine particulate matter (particulate matter ≤2.5 mm in aerodynamic diameter [PM_2.5]) on respiratory ED visits.

METHODS

We conducted time-series analyses in 894 counties by linking daily respiratory ED visits with estimated ozone and PM_2.5 concentrations during the week before the date of the visit. Overall effect estimates were obtained with a Bayesian hierarchical model to combine county estimates for each pollutant by age group (children, 0-18; adults, 19-64; adults ≥ 65, and all ages) and by outcome group (acute respiratory infection, asthma, chronic obstructive pulmonary disease, pneumonia, and all respiratory ED visits).

MEASUREMENTS AND MAIN RESULTS

Rate ratios (95% credible interval) per 10-μg/m³ increase in PM_2.5 and all respiratory ED visits were 1.024 (1.018-1.029) among children, 1.008 (1.004-1.012) among adults younger than 65 years, and 1.002 (0.996-1.007) among adults 65 and older. Per 20-ppb increase in ozone, rate ratios were 1.017 (1.011-1.023) among children, 1.051 (1.046-1.056) among adults younger than 65, and 1.033 (1.026-1.040) among adults 65 and older. Associations varied in magnitude by age group for each outcome group.

CONCLUSIONS

These results address a gap in the evidence used to ensure adequate public health protection under national air pollution policies.

Heat-health action plans in Europe: Challenges ahead and how to tackle them

High temperatures have periodically affected large areas in Europe and urban settings. In particular, the deadly 2003 summer heat waves precipitated a multitude of national and subnational health prevention and research efforts. Building on these and other international experiences the WHO Regional Office for Europe developed and published in 2008 a comprehensive framework for prevention, the heat-health action plans (HHAPs). This provided a blueprint used by several national and subnational authorities to design their prevention efforts. A decade after the publication of the WHO guidance, a wealth of new evidence and acquired implementation experience has emerged around HHAP effectiveness; heat exposure; acclimatization and adaptation; heat-health governance and stakeholder involvement; and the role of urban design and greening interventions in prevention. This evidence and experience can guide the strategies to tackle current and upcoming challenges in protecting health from heat under a warming climate.

Influence of the spatial resolution of the exposure estimate in determining the association between heat waves and adverse health outcomes

BACKGROUND

Area-level estimates of temperature may lead to exposure misclassification in studies examining associations between heat waves and health outcomes. Our study compared the association between heat waves and preterm birth (PTB) or non-accidental death (NAD) using exposure metrics at varying levels of spatial resolution: ZIP codes, 12.5 km, and 1 km.

METHOD

Using geocoded residential addresses on birth (1990-2010) and death (1997-2010) records from Alabama, USA, we implemented a time-stratified case-crossover design to examine the association between heat waves and PTB or NAD. ZIP code- and 12.5 km heat wave indices (HIs) were derived using air temperatures from Phase 2 of the North American Land Data Assimilation System (NLDAS-2). We downscaled NLDAS-2 data, using land surface temperatures (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) product, to estimate fine spatial resolution HIs (1 km).

RESULTS

The association between heat waves and PTB or NAD was significant and positive using ZIP code-, 12.5 km, and 1 km exposure metrics. Moreover, results show that these three-exposure metric analyses produced similar effect estimates. Urban heat islands were evident with the 1 km metric. When analyses were stratified by rurality, we found associations in urban areas were more positive than in rural areas.

CONCLUSIONS

Comparing results of models with a varying spatial resolution of the exposure metric allows for examination of potential bias associated with exposure misclassification.

Heat-Related Health Impacts under Scenarios of Climate and Population Change

Recent assessments have found that a warming climate, with associated increases in extreme heat events, could profoundly affect human health. This paper describes a new modeling and analysis framework, built around the Benefits Mapping and Analysis Program-Community Edition (BenMAP), for estimating heat-related mortality as a function of changes in key factors that determine the health impacts of extreme heat. This new framework has the flexibility to integrate these factors within health risk assessments, and to sample across the uncertainties in them, to provide a more comprehensive picture of total health risk from climate-driven increases in extreme heat. We illustrate the framework's potential with an updated set of projected heat-related mortality estimates for the United States. These projections combine downscaled Coupled Modeling Intercomparison Project 5 (CMIP5) climate model simulations for Representative Concentration Pathway (RCP)4.5 and RCP8.5, using the new Locating and Selecting Scenarios Online (LASSO) tool to select the most relevant downscaled climate realizations for the study, with new population projections from EPA's Integrated Climate and Land Use Scenarios (ICLUS) project. Results suggest that future changes in climate could cause approximately from 3000 to more than 16,000 heat-related deaths nationally on an annual basis. This work demonstrates that uncertainties associated with both future population and future climate strongly influence projected heat-related mortality. This framework can be used to systematically evaluate the sensitivity of projected future heat-related mortality to the key driving factors and major sources of methodological uncertainty inherent in such calculations, improving the scientific foundations of risk-based assessments of climate change and human health.

Evaluation of the Components of the North Carolina Syndromic Surveillance System Heat Syndrome Case Definition

OBJECTIVES

To improve heat-related illness surveillance, we evaluated and refined North Carolina's heat syndrome case definition.

METHODS

We analyzed North Carolina emergency department (ED) visits during 2012-2014. We evaluated the current heat syndrome case definition (ie, keywords in chief complaint/triage notes or International Classification of Diseases, Ninth Revision, Clinical Modification [ ICD-9-CM] codes) and additional heat-related inclusion and exclusion keywords. We calculated the positive predictive value and sensitivity of keyword-identified ED visits and manually reviewed ED visits to identify true positives and false positives.

RESULTS

The current heat syndrome case definition identified 8928 ED visits; additional inclusion keywords identified another 598 ED visits. Of 4006 keyword-identified ED visits, 3216 (80.3%) were captured by 4 phrases: "heat ex" (n = 1674, 41.8%), "overheat" (n = 646, 16.1%), "too hot" (n = 594, 14.8%), and "heatstroke" (n = 302, 7.5%). Among the 267 ED visits identified by keyword only, a burn diagnosis or the following keywords resulted in a false-positive rate >95%: "burn," "grease," "liquid," "oil," "radiator," "antifreeze," "hot tub," "hot spring," and "sauna." After applying the revised inclusion and exclusion criteria, we identified 9132 heat-related ED visits: 2157 by keyword only, 5493 by ICD-9-CM code only, and 1482 by both (sensitivity = 27.0%, positive predictive value = 40.7%). Cases identified by keywords were strongly correlated with cases identified by ICD-9-CM codes (rho = .94, P < .001).

CONCLUSIONS

Revising the heat syndrome case definition through the use of additional inclusion and exclusion criteria substantially improved the accuracy of the surveillance system. Other jurisdictions may benefit from refining their heat syndrome case definition.

Evaluation of a Novel Syndromic Surveillance Query for Heat-Related Illness Using Hospital Data From Maricopa County, Arizona, 2015

OBJECTIVES

We evaluated a novel syndromic surveillance query, developed by the Council of State and Territorial Epidemiologists (CSTE) Heat Syndrome Workgroup, for identifying heat-related illness cases in near real time, using emergency department and inpatient hospital data from Maricopa County, Arizona, in 2015.

METHODS

The Maricopa County Department of Public Health applied 2 queries for heat-related illness to area hospital data transmitted to the National Syndromic Surveillance Program BioSense Platform: the BioSense "heat, excessive" query and the novel CSTE query. We reviewed the line lists generated by each query and used the diagnosis code and chief complaint text fields to find probable cases of heat-related illness. For each query, we calculated positive predictive values (PPVs) for heat-related illness.

RESULTS

The CSTE query identified 674 records, of which 591 were categorized as probable heat-related illness, demonstrating a PPV of 88% for heat-related illness. The BioSense query identified 791 patient records, of which 589 were probable heat-related illness, demonstrating a PPV of 74% for heat-related illness. The PPV was substantially higher for the CSTE novel and BioSense queries during the heat season (May 1 to September 30; 92% and 85%, respectively) than during the cooler seasons (55% and 29%, respectively).

CONCLUSION

A novel query for heat-related illness that combined diagnosis codes, chief complaint text terms, and exclusion criteria had a high PPV for heat-related illness, particularly during the heat season. Public health departments can use this query to meet local needs; however, use of this novel query to substantially improve public health heat-related illness prevention remains to be seen.

Hospitalizations for heat-stress illness varies between rural and urban areas: an analysis of Illinois data, 1987-2014

BACKGROUND

The disease burden due to heat-stress illness (HSI), which can result in significant morbidity and mortality, is expected to increase as the climate continues to warm. In the United States (U.S.) much of what is known about HSI epidemiology is from analyses of urban heat waves. There is limited research addressing whether HSI hospitalization risk varies between urban and rural areas, nor is much known about additional diagnoses of patients hospitalized for HSI.

METHODS

Hospitalizations in Illinois for HSI (ICD-9-CM codes 992.x or E900) in the months of May through September from 1987 to 2014 (n = 8667) were examined. Age-adjusted mean monthly hospitalization rates were calculated for each county using U.S. Census population data. Counties were categorized into five urban-rural strata using Rural Urban Continuum Codes (RUCC) (RUCC1, most urbanized to RUCC5, thinly populated). Average maximum monthly temperature (°C) was calculated for each county using daily data. Multi-level linear regression models were used, with county as the fixed effect and temperature as random effect, to model monthly hospitalization rates, adjusting for the percent of county population below the poverty line, percent of population that is Non-Hispanic Black, and percent of the population that is Hispanic. All analyses were stratified by county RUCC. Additional diagnoses of patients hospitalized for HSI and charges for hospitalization were summarized.

RESULTS

Highest rates of HSI hospitalizations were seen in the most rural, thinly populated stratum (mean annual summer hospitalization rate of 1.16 hospitalizations per 100,000 population in the thinly populated strata vs. 0.45 per 100,000 in the metropolitan urban strata). A one-degree Celsius increase in maximum monthly average temperature was associated with a 0.34 increase in HSI hospitalization rate per 100,000 population in the thinly populated counties compared with 0.02 per 100,000 in highly urbanized counties. The most common additional diagnoses of patients hospitalized with HSI were dehydration, electrolyte abnormalities, and acute renal disorders. Total and mean hospital charges for HSI cases were $167.7 million and $20,500 (in 2014 US dollars).

CONCLUSION

Elevated temperatures appear to have different impacts on HSI hospitalization rates as function of urbanization. The most rural and the most urbanized counties of Illinois had the largest increases in monthly hospitalization rates for HSI per unit increase in the average monthly maximum temperature. This suggests that vulnerability of communities to heat is complex and strategies to reduce HSI may need to be tailored to the degree of urbanization of a county.

Evaluation of Diagnostic Codes in Morbidity and Mortality Data Sources for Heat-Related Illness Surveillance

OBJECTIVES

The primary objective of this study was to identify patients with heat-related illness (HRI) using codes for heat-related injury diagnosis and external cause of injury in 3 administrative data sets: emergency department (ED) visit records, hospital discharge records, and death certificates.

METHODS

We obtained data on ED visits, hospitalizations, and deaths for Florida residents for May 1 through October 31, 2005-2012. To identify patients with HRI, we used codes from the International Classification of Diseases, Ninth Revision, Clinical Modification ( ICD-9-CM) to search data on ED visits and hospitalizations and codes from the International Classification of Diseases, Tenth Revision ( ICD-10) to search data on deaths. We stratified the results by data source and whether the HRI was work related.

RESULTS

We identified 23 981 ED visits, 4816 hospitalizations, and 140 deaths in patients with non-work-related HRI and 2979 ED visits, 415 hospitalizations, and 23 deaths in patients with work-related HRI. The most common diagnosis codes among patients were for severe HRI (heat exhaustion or heatstroke). The proportion of patients with a severe HRI diagnosis increased with data source severity. If ICD-9-CM code E900.1 and ICD-10 code W92 (excessive heat of man-made origin) were used as exclusion criteria for HRI, 5.0% of patients with non-work-related deaths, 3.0% of patients with work-related ED visits, and 1.7% of patients with work-related hospitalizations would have been removed.

CONCLUSIONS

Using multiple data sources and all diagnosis fields may improve the sensitivity of HRI surveillance. Future studies should evaluate the impact of converting ICD-9-CM to ICD-10-CM codes on HRI surveillance of ED visits and hospitalizations.

A Comprehensive Evaluation of the Burden of Heat-Related Illness and Death within the Florida Population

The failure of the human body to thermoregulate can lead to severe outcomes (e.g., death) and lasting physiological damage. However, heat-related illness (HRI) is highly preventable via individual- and community-level modification. A thorough understanding of the burden is necessary for effective intervention. This paper describes the burden of severe HRI morbidity and mortality among residents of a humid subtropical climate. Work-related and non-work-related HRI emergency department (ED) visits, hospitalizations, and deaths among Florida residents during May to October (2005–2012) were examined. Sub-groups susceptible to HRI were identified. The age-adjusted rates/100,000 person-years for non-work-related HRI were 33.1 ED visits, 5.9 hospitalizations, and 0.2 deaths, while for work-related HRI/100,000 worker-years there were 8.5 ED visits, 1.1 hospitalizations, and 0.1 deaths. The rates of HRI varied by county, data source, and work-related status, with the highest rates observed in the panhandle and south central Florida. The sub-groups with the highest relative rates regardless of data source or work-relatedness were males, minorities, and rural residents. Those aged 15–35 years had the highest ED visit rates, while for non-work-related hospitalizations and deaths the rates increased with age. The results of this study can be used for targeted interventions and evaluating changes in the HRI burden over time.