This contains 20,000+ records. Columns in file are: case id, country, province, district, sex, age, specialty, icd-10, diagnosis, date of visit, date of treatment,treatment details, and medication details. A file with 500,000 records can also be extracted for purchase (the whole database currently has over 3 million cases). Highly beneficial for the following analysis: Health Disparities Analysis: By examining healthcare data in conjunction with demographic information such as age, gender, race, ethnicity, income, and education level, you can identify disparities in healthcare access, utilization, and outcomes across different demographic groups. This analysis can help in addressing inequities and designing targeted interventions to improve healthcare outcomes for marginalized populations. Epidemiological Analysis: By correlating healthcare data with demographic factors, you can study disease prevalence and incidence rates among different population segments. This analysis can provide insights into the distribution and determinants of health conditions, helping public health agencies and researchers understand the impact of demographic factors on disease patterns. Access to Care Analysis: By combining healthcare and demographic data, you can assess the accessibility of healthcare services across different demographic groups. This analysis can involve examining factors such as distance to healthcare facilities, health insurance coverage, and socioeconomic status to identify areas with limited access to care and inform policy decisions and resource allocation. Health Behavior Analysis: By analyzing healthcare data alongside demographic information, you can study health behaviors and lifestyle factors that contribute to health outcomes. This can include analyzing factors such as smoking rates, physical activity levels, dietary habits, and preventive care utilization. The findings can guide targeted health promotion initiatives and interventions. Predictive Modeling: Integrating healthcare and demographic data allows for predictive analytics to forecast health outcomes, resource needs, and disease prevalence. By combining historical healthcare data with demographic variables, predictive models can be developed to estimate future healthcare demands, identify high-risk populations, and optimize resource allocation and preventive interventions. Public Health Planning: Analyzing healthcare and demographic data together helps in effective public health planning. By considering demographic characteristics, health needs, and healthcare utilization patterns, public health agencies can design interventions, allocate resources, and tailor programs to meet the specific needs of different population groups. Social Determinants of Health Analysis: Demographic data plays a crucial role in understanding social determinants of health. By integrating demographic factors such as income, education, employment, housing, and social support with healthcare data, you can analyze the impact of these determinants on health outcomes. This analysis can inform policies and interventions aimed at addressing social determinants and improving health equity.