Ambulance use, distance and outcomes in patients with suspected cardiovascular disease: a registry-based geographic information system study

Prevalence and Predictors of Emergency Medical Service Use in Patients Undergoing Primary Percutaneous Coronary Intervention for ST-Elevation Myocardial Infarction

AIM

We aim to describe prevalence of Emergency Medical Service (EMS) use, investigate factors predictive of EMS use, and determine if EMS use predicts treatment delay and mortality in our ST-elevation myocardial infarction (STEMI) cohort.

METHOD

We prospectively collected data on 5,602 patients presenting with STEMI for primary percutaneous coronary intervention (PCI) transported to PCI-capable hospitals in Victoria, Australia, from 2013-2018 who were entered into the Victorian Cardiac Outcomes Registry (VCOR). We linked this dataset to the Ambulance Victoria and National Death Index (NDI) datasets. We excluded late presentation, thrombolysed, and in-hospital STEMI, as well as patients presenting with cardiogenic shock and out-of-hospital cardiac arrest.

RESULTS

In total, 74% of patients undergoing primary PCI for STEMI used EMS. Older age, female gender, higher socioeconomic status, and a history of prior ischaemic heart disease were independent predictors of using EMS. EMS use was associated with shorter adjusted door-to-balloon (53 vs 72 minutes, p<0.001) and symptom-to-balloon (183 vs 212 minutes, p<0.001) times. Mode of transport was not predictive of 30-day or 12-month mortality.

CONCLUSIONS

EMS use in Victoria is relatively high compared with internationally reported data. EMS use reduces treatment delay. Predictors of EMS use in our cohort are consistent with those prevalent in prior literature. Understanding the patients who are less likely to use EMS might inform more targeted education campaigns in the future.

Association between social support and ambulance use among older people in Japan: an empirical cross-sectional study

BACKGROUND

Ambulance service demand and utilization are increasing worldwide. To address this issue, the factors that affect ambulance use must be identified. Few studies have examined factors that can intervene and thus reduce the frequency of ambulance use. This study aimed to examine the association between social support and ambulance use among older adults in Japan. We hypothesize that social support is associated with reduced ambulance use.

METHODS

This cross-sectional study was conducted as part of the Japan Gerontological Evaluation Study. In December 2019 and January 2020, we collaborated with individuals aged 65 years or above with no long-term care needs. A total of 24,581 participants were included in the analysis. The objective and explanatory variables were ambulance use and social support, respectively. Binomial regression analysis was used to calculate the odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Social support was associated with ambulance use. People who had no one to listen to their complaints or worries were significantly more likely to use ambulance services than those who did (OR [95% CI] = 1.26 [1.03-1.53]). People with no one to take care of them when they were ill were also significantly more likely to use ambulance services than those who had someone to provide care (1.15 [1.01-1.31]). Moreover, the results of binomial logistic regression analysis indicated that individuals who called an ambulance but were not hospitalized had significantly lower social support compared to those who did not call an ambulance.

CONCLUSIONS

The results suggest that the presence and quality of social support play a significant role in ambulance use among older adults in Japan. Our findings can help policymakers to plan and implement strategies for reducing the burden on emergency medical care.

Geostatistical analysis from the clinical laboratory in cardiovascular prevention for primary care

INTRODUCTION AND OBJECTIVES

Cardiovascular diseases continue to lead the ranking of mortality in Spain. The implementation of geostatistical analysis techniques in the clinical laboratory are innovative tools that allow the design of new strategies in primary prevention of cardiovascular disease. The aim of this study was to study the prevalence and geolocation of severe dyslipidemia in the health areas under study in order to implement prevention strategies in primary care. A retrospective cohort study of low-density protein-bound cholesterol, triglyceride and lipoprotein (a) levels in the years 2019 and 2020 were carried out. In addition, a geostatistical analysis was performed including representation in choropleth maps and the detection of clustering clusters, using geographic information in zip code format included in the demographic data of each analytic.

RESULTS

The analytical data included in the study were triglycerides (n=365,384), low density protein-bound cholesterol (n=289,594) and lipoprotein to lipoprotein (a) (n=502). Areas with the highest and lowest percentage of cases were identified for the established cut-off points of LDL-C>190mg/dL and TG>150mg/dL. Two clustering clusters with statistical significance were detected for cLDL>190mg/dL and a total of 6 clusters for TG values>150mg/dL.

CONCLUSIONS

The detection of clusters, as well as the representation of choropleth maps, can be of great help in detecting geographic areas that require greater attention to intervene and improve cardiovascular risk.

Hospital-level characteristics of the standardised mortality ratio for ischemic heart disease: a retrospective observational study using Japanese administrative claim data from 2012 to 2019

Background

Ischemic heart disease (IHD) is one of the leading causes of mortality worldwide and imposes a heavy burden on patients. Previous studies have indicated that the optimal care for IHD during hospitalisation may reduce the risk of in-hospital mortality. The standardised mortality ratio (SMR) is an indicator for assessing the risk-adjusted in-hospital mortality ratio based on case-mix. This indicator can crucially identify hospitals that can be changed to improve patient safety and the quality of care. This study aimed to determine the hospital-level characteristics of the SMR for IHD in Japan.

Methods

This study was designed as a retrospective observational study using the Japanese administrative claim data from 2012 to 2019. The data of all hospital admissions with a primary diagnosis of IHD (ICD-10, I20-I25) were used. Patients with complete variables data were included in this study. Hospitals with less than 200 IHD inpatients in each 2-year period were excluded. The SMR was defined as the ratio of the observed number of in-hospital deaths to the expected number of in-hospital deaths multiplied by 100.The observed number of in-hospital deaths was the sum of the actual number of in-hospital deaths at that hospital, and the expected number of in-hospital deaths was the sum of the probabilities of in-hospital deaths. Ratios of in-hospital mortality was risk-adjusted using multivariable logistic regression analyses. The c-statistic and Hosmer-Lemeshow test were used to evaluate the predictive accuracy of the logistic models. Changes in SMRs in each consecutive period were assessed using Spearman's correlation coefficient.

Results

A total of 64,831 were admitted patients with IHD in 27 hospitals as complete submission data. The SMRs showed wide variation among hospitals, ranging from 35.4 to 197.6, and analysis models indicated good predictive ability with a c-statistic of 0.93 (95% CI [0.92-0.94]) and Hosmer-Lemeshow test of 0.30. The results of chi-square tests and t-tests for all variables to assess the association with in-hospital mortality were P < 0.001. In the analysis of trends in each consecutive period, the SMRs showed positive correlations.

Conclusions

This study denoted that the SMRs for IHD could be calculated using Japanese administrative claim data. The SMR for IHD might contribute to the development of more appropriate benchmarking systems for hospitals to improve quality of care.

The potential of new prediction models for emergency medical dispatch prioritisation of patients with chest pain: a cohort study

Objectives

To develop emergency medical dispatch (EMD) centre prediction models with high sensitivity and satisfying specificity to identify high-priority patients and patients suitable for non-emergency care respectively, when assessing patients with chest pain.

Methods

Observational cohort study of 2917 unselected patients with chest pain who contacted an EMD centre in Sweden due to chest pain during 2018. Multivariate logistic regression was applied to develop models predicting low-risk or high-risk condition, that is, occurrence of time-sensitive diagnosis on hospital discharge.

Results

Prediction models were developed for the identification of patients suitable for high- and low-priority dispatch, using 11 and 10 variables respectively. The area under the receiver-operating characteristic curve (AUROC) for the high-risk prediction model was 0.79 and for the low-risk model it was 0.74. When applying the high-risk prediction model, 56% of the EMS missions were given highest priority, compared with 65% with the current standard. When applying the low-risk model, 7% were given the lowest priority compared to 1% for the current standard. The new prediction models outperformed today’s dispatch priority accuracy in terms of sensitivity as well as positive and negative predictive value in both high- and low-risk prediction. The low-risk model predicted almost six times as many patients as having low-risk conditions compared with today’s standard. This was done without increasing the number of high-risk patients wrongly assessed as low-risk.

Conclusions

By introducing prediction models, based on logistic regression analyses, using variables obtained by standard EMD-questions on age, sex, medical history and symptomology, EMD prioritisation can be improved compared with using current criteria index-based ones. This will allow a more efficient emergency medical services resource allocation.

Travel time to emergency care not by geographic time, but by optimal time: A nationwide cross-sectional study for establishing optimal hospital access time to emergency medical care in South Korea

Increase in travel time, beyond a critical point, to emergency care may lead to a residential disparity in the outcome of patients with acute conditions. However, few studies have evaluated the evidence of travel time benchmarks in view of the association between travel time and outcome. Thus, this study aimed to establish the optimal hospital access time (OHAT) for emergency care in South Korea. We used nationwide healthcare claims data collected by the National Health Insurance System database of South Korea. Claims data of 445,548 patients who had visited emergency centers between January 1, 2006 and December 31, 2014 were analyzed. Travel time, by vehicle from the residence of the patient, to the emergency center was calculated. Thirteen emergency care-sensitive conditions (ECSCs) were selected by a multidisciplinary expert panel. The 30-day mortality after discharge was set as the outcome measure of emergency care. A change-point analysis was performed to identify the threshold where the mortality of ECSCs changed significantly. The differences in risk-adjusted mortality between patients living outside of OHAT and those living inside OHAT were evaluated. Five ECSCs showed a significant threshold where the mortality changed according to their OHAT. These were intracranial injury, acute myocardial infarction, other acute ischemic heart disease, fracture of the femur, and sepsis. The calculated OHAT were 71-80 min, 31-40 min, 70-80 min, 41-50 min, and 61-70 min, respectively. Those who lived outside the OHAT had higher risks of death, even after adjustment (adjusted OR: 1.04-7.21; 95% CI: 1.03-26.34). In conclusion, the OHAT for emergency care with no significant increase in mortality is in the 31-80 min range. Optimal travel time to hospital should be established by optimal time for outcomes, and not by geographic time, to resolve the disparities in geographical accessibility to emergency care.

The use of geographical analysis in assessing the impact of patients' home addresses on their participation in outpatient cardiac rehabilitation: a prospective cohort study

Purpose

Geographical analysis is becoming a powerful tool for evaluating the quality of medical services and acquiring fundamental data for medical decision-making. Using geographical analysis, we evaluated the impact of the distance from patients’ homes to the hospital on their participation in outpatient cardiac rehabilitation (OCR).

Methods

All patients hospitalized for percutaneous coronary intervention, coronary artery bypass grafting, valvular surgery, congestive heart failure, and aortic diseases were advised to participate in an OCR program after discharge. Using the dataset of our cohort study of OCR from 2004 to 2015 (n = 9,019), we used geographical analysis to investigate the impact of the distance from patients’ homes to hospital on their participation in our OCR program.

Results

Patients whose road distance from home to hospital was 0–10 km, 10–20 km, and 20–30 km participated more in OCR than those whose road distance was ≧ 30 km (OR 4.34, 95% CI 3.80–4.96; OR 2.98, 95% CI 2.61–3.40; and OR 1.90, 95% CI 1.61–2.23, respectively). Especially in patients with heart failure, the longer the distance, the lesser the participation rate (P < .001).

Conclusions

Using geographical analysis, we successfully evaluated the factors influencing patients’ participation in OCR. This illustrates the importance of using geographical analysis in future epidemiological and clinical studies.

Trial registration

UMIN000028435.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12199-020-00917-x.

Ambulance Transport of Patients with Mild Conditions in Hokkaido, Japan

Understanding the epidemiological distributions of ambulance transport for patients with mild conditions according to age, disease, and geographic region could help in achieving optimal use of ambulance services. In the present study, we explored the descriptive epidemiology of ambulance transports in Hokkaido, the northernmost prefecture of Japan, identifying potential factors that determine the frequency of transports for mild diseases. Of the total 153,667 ambulance transports in Hokkaido during 2016, we found that two-thirds were for older people, of which about 60% resulted in hospital admission. There were 74,485 transports for mild cases, which were most commonly for psychiatric disorders among working-age adults (n = 4805), heart diseases among older people (n = 4246), and sensory organ diseases among older people (n = 3589). Examining the ecological correlations over 58 geographic units of ambulance services, the total unemployment rate and distance to the nearest tertiary care hospital were, respectively, positively and negatively correlated with the standardized transport ratio for multiple mild diseases. The proportion of working-age adults was uniquely identified as a possible positive predictor in mild cases of psychiatric disorders. As the identified potential predictors could be helpful in considering countermeasures, the causal links should be examined in future studies.

Characteristics of the Spanish Older People in the Use of Accidents and Emergency Unit Services (2014-2017)

The aim of this study was to determine which factors are related to Accidents and Emergency Unit (AEU) use by the elderly Spanish population. Observational analysis of the 2014 European Survey of Health in Spain (ESHS-2014; N = 6,520) and the 2017 Spanish Health Survey (SHS-2017; N = 7,024) was employed. About one third (4,095, 30.2%) of the sample used the AEU, and they were primarily women (32.6%). Comorbidity (p = .01), presence of physical limitation in the prior 6 months to the survey, and a history of several diseases (p < .001)-as in diabetes (p < .001), osteoarthritis (p < .001), and chronic bronchitis, emphysema, or chronic obstructive pulmonary disease (p < .001)-were associated with AEU visits in both surveys. Female sex and several cardiovascular diseases were only significant in the ESHS-2014. In the SHS-2017, depressive status was an independent risk factor. This epidemiological data allow a better understanding of the use of AEU, suggesting indications for the care process.