The data in this section is derived from surveys conducted by visitors to our website. Questions in these surveys are designed to be similar to many scientific and government surveys.
Each entry in the survey is assigned a number within the range of -2 to +2, where -2 represents a strongly negative perception and +2 represents a strongly positive perception.
To ensure data accuracy, we have implemented filtering measures to identify and exclude potential spam from our calculations. Our algorithms identify users who exhibit spam-like behavior and their inputs are not considered in the calculations. This helps maintain the integrity of the data and provide reliable results.
To make survey results easier to interpret for our users, we present them on a scale ranging from 0 to 100. This scale allows for a clear and straightforward understanding of the data, enhancing user experience and facilitating meaningful comparisons.
Our current index, which is continuously updated, is generated using data up to 36 months old. We carefully select cities for inclusion in the index based on a minimum number of contributors to ensure statistical significance. Additionally, our semiannual index is calculated twice a year by incorporating the latest data into the historical view.
Health Care Index is an estimation that evaluates the overall quality of the healthcare system, including factors such as healthcare professionals, equipment, staff, doctors, and costs. It provides an assessment of the healthcare infrastructure, services, and resources available in a specific location.
Health Care Exp Index is designed to reflect the quality of a healthcare system by emphasizing the positive aspects more significantly through an exponential increase while also emphasizing the native aspects more significantly.
It's important to note that the Health Care Index provided by Numbeo is based on user-contributed data and perceptions, which may vary. While it could be biased, the index is a comparative tool to evaluate and compare healthcare systems across different cities or countries, assisting in understanding the healthcare landscape.
Actual formulas to calculate indices are subject to change. At this moment, quite complex empirical formulas are used. Those formulas, as written in the Java programming language, are as follows:
//assumes all input values are in the range [-2 , 2], where -2 means very low and 2 means very high
@Override
protected void calculateIndex() {
index = new HealthCareIndex();
double overall = 0.0;
overall += getIndexPartPreCalc(skill_and_competency);
overall += getIndexPartPreCalc(speed);
overall += getIndexPartPreCalc(modern_equipment);
overall += getIndexPartPreCalc(accuracy_and_completeness);
overall += getIndexPartPreCalc(friendliness_and_courtesy);
overall += getIndexPartPreCalc(responsiveness_waitings);
overall += getIndexPartPreCalc(location);
overall += 2 * getIndexPartPreCalc(cost);
index.main = overall / 9;
double expScale = 0.0;
expScale += getIndexPartPreCalcExpScaleStandard(skill_and_competency);
expScale += getIndexPartPreCalcExpScaleStandard(speed);
expScale += getIndexPartPreCalcExpScaleStandard(modern_equipment);
expScale += getIndexPartPreCalcExpScaleStandard(accuracy_and_completeness);
expScale += getIndexPartPreCalcExpScaleStandard(friendliness_and_courtesy);
expScale += getIndexPartPreCalcExpScaleStandard(responsiveness_waitings);
expScale += getIndexPartPreCalcExpScaleStandard(location);
expScale += 2 * getIndexPartPreCalcExpScaleStandard(cost);
index.exp = calcScaleStandardIndexFromSum(expScale, 9);
}
protected double getIndexPartPreCalc(double internalValue) {
return (internalValue + 2) * 25;
}
protected double getIndexPartPreCalcExpScaleStandard(double internalValue) {
return getIndexPartPreCalcExpScale(internalValue, Math.E);
}
protected double getIndexPartPreCalcExpScale(double internalValue, double exp) {
return Math.pow((internalValue + 2) * 25, exp);
}
protected double calcScaleStandardIndexFromSum(double scaleSum, int elems) {
return Math.pow(scaleSum / elems, 1 / (Math.E * 8.8 / 10));
}