Understanding Health Care Indexes

The data in this section is derived from surveys answered by website visitors, structured similarly to established scientific and governmental surveys. Individual responses are assigned a numerical value between -2 (indicating a strongly negative perception) and +2 (indicating a strongly positive perception).

To maintain data accuracy, we employ spam filtering algorithms that exclude inputs from users exhibiting suspicious behavior.

Survey results are then scaled from 0 to 100 for easier interpretation and comparison.

Our current index, updated continuously, is compiled from data within the past 5 years. 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 estimates the overall quality of a healthcare system by evaluating key factors such as medical 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 with greater emphasis on positive aspects through an exponential scale, while also amplifying the impact of negative aspects.

It is important to note that Numbeo’s Health Care Index is based on user-contributed data and perceptions, which may vary. While the data could be subject to biases, the index serves as a comparative tool for evaluating and comparing healthcare systems across different cities and countries, helping users understand healthcare quality globally.

The formulas used to calculate these indices are subject to change and are based on complex empirical models. The current calculation, implemented in Java, is as follows:

  // Assumes all input values range from -2 (very low) to 2 (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));
  }