Acute myocardial infarction--from territory to definitive treatment in an Italian province

Do acute myocardial infarction and stroke mortality vary by distance to hospitals in Switzerland? Results from the Swiss National Cohort Study

OBJECTIVE

Switzerland has mountains and valleys complicating the access to a hospital and critical care in case of emergencies. Treatment success for acute myocardial infarction (AMI) or stroke depends on timely treatment. We examined the relationship between distance to different hospital types and mortality from AMI or stroke in the Swiss National Cohort (SNC) Study.

DESIGN AND SETTING

The SNC is a longitudinal mortality study of the census 2000 population of Switzerland. For 4.5 million Swiss residents not living in a nursing home and older than 30 years in the year 2000, we calculated driving time and straight-line distance from their home to the nearest acute, acute with emergency room, central and university hospital (in total 173 hospitals). On the basis of quintiles, we used multivariable Cox proportional hazard models to estimate HRs of AMI and stroke mortality for driving time distance groups compared to the closest distance group.

RESULTS

Over 8 years, 19 301 AMI and 21 931 stroke deaths occurred. Mean driving time to the nearest acute hospital was 6.5 min (29.7 min to a university hospital). For AMI mortality, driving time to a university hospital showed the strongest association among the four types of hospitals with a hazard ratio (HR) of 1.19 (95% CI 1.10 to 1.30) and 1.10 (95% CI 1.01 to 1.20) for men and women aged 65+ years when comparing the highest quintile with the lowest quintile of driving time. For stroke mortality, the association with university hospital driving time was less pronounced than for AMI mortality and did not show a clear incremental pattern with increasing driving time. There was no association with driving time to the nearest hospital.

CONCLUSIONS

The increasing AMI mortality with increasing driving time to the nearest university hospital but not to any nearest hospital reflects a complex interplay of many factors along the care pathway.

System dynamics modeling in the evaluation of delays of care in ST-segment elevation myocardial infarction patients within a tiered health system

Background

Mortality rates amongst ST segment elevation myocardial infarction (STEMI) patients remain high, especially in developing countries. The aim of this study was to evaluate the factors related with delays in the treatment of STEMI patients to support a strategic plan toward structural and personnel modifications in a primary hospital aligning its process with international guidelines.

Methods and Findings

The study was conducted in a primary hospital localized in Foz do Iguaçu, Brazil. We utilized a qualitative and quantitative integrated analysis including on-site observations, interviews, medical records analysis, Qualitative Comparative Analysis (QCA) and System Dynamics Modeling (SD). Main cause of delays were categorized into three themes: a) professional, b) equipment and c) transportation logistics. QCA analysis confirmed four main stages of delay to STEMI patient’s care in relation to the ‘Door-in-Door-out’ time at the primary hospital. These stages and their average delays in minutes were: a) First Medical Contact (From Door-In to the first contact with the nurse and/or physician): 7 minutes; b) Electrocardiogram acquisition and review by a physician: 28 minutes; c) ECG transmission and Percutaneous Coronary Intervention Center team feedback time: 76 minutes; and d) Patient’s Transfer Waiting Time: 78 minutes. SD baseline model confirmed the system’s behavior with all occurring delays and the need of improvements. Moreover, after model validation and sensitivity analysis, results suggested that an overall improvement of 40% to 50% in each of these identified stages would reduce the delay.

Conclusions

This evaluation suggests that investment in health personnel training, diminution of bureaucracy, and management of guidelines might lead to important improvements decreasing the delay of STEMI patients’ care. In addition, this work provides evidence that SD modeling may highlight areas where health system managers can implement and evaluate the necessary changes in order to improve the process of care.

Regional disparities in mortality after ischemic heart disease in a Brazilian state from 2006 to 2010

Background

High technology in the field of interventional cardiology applied in tertiary hospitals has brought enormous benefits in the treatment of ischemic heart disease (IHD). However, IHD mortality rates remain high. We analyzed the relationship between IHD mortality rate and the socioeconomic, demographic, and geographic conditions in 399 cities in Parana state, Brazil, from 2006 to 2010.

Methods and Results

Data were obtained from the Mortality Information System and the Brazilian Institute of Geography and Statistics and evaluated through Exploratory Spatial Data Analysis. GeoDa™ was used to analyze 29.351 deaths across 399 cities. We found a positive spatial autocorrelation regarding IHD mortality (I = 0.5913, p = 0.001). There was a significant positive association between each of three socioeconomic and demographic indicators and IHD mortality rate: Population Elderly Index (I = 0.3436), Illiteracy Rate (I = 0.1873) and City Development Index (I = 0.0900). In addition, two indicators presented significant negative association with IHD mortality rate: Adjusted Population Size (I = −0.1216) and Gross Domestic Product (I = −0.0864). We also found a positive association between IHD mortality rates and the geographic distances between patients’ city of residence and their corresponding regional referral centers in interventional cardiology (I = 0.3368). Cities located within Regional Health Units with Reference Interventional Cardiology Center presented a significantly lower average specific mortality rate by IHD. The high mortality rate by IHD within the Regional Health Units was not restricted to socioeconomic and demographic variables, but dependent on the distance between each city and their reference interventional cardiology center.

Conclusions

We conclude that geographic factors play a significant role in IHD mortality within cities. These findings have important policy implications regarding the geographic distribution of cardiac health care networks in Latin America and in other emerging countries.