Health Data Collection: Concept and Methods


Health data collection is a crucial part of public health analytics, and it involves the gathering and organization of information related to individuals’ health and healthcare. There are two main types of health data; primary data and secondary data. Primary data is collected directly from individuals through methods such as surveys, medical examinations, and focus groups. In contrast, secondary data is collected from sources that have already collected data, such as electronic health records, disease surveillance systems, and administrative records.

Some of the health data collection methods are described below:

  1. Survey: It is used to collect information on a wide range of health-related topics, such as disease prevalence, risk factors, and healthcare access.
  2. Medical examinations: It involves the collection of clinical data such as blood pressure, weight, and blood tests.
  3. Focus groups: It is useful for understanding attitudes, beliefs, and behaviors of a group of people in relation to health.
  4. Electronic Health Records (EHRs): EHRs are electronic records of patients’ medical history, diagnoses, medications, and treatment plans.
  5. Disease Surveillance Systems: Disease surveillance systems collect data on the occurrence and distribution of infectious diseases.
  6. Administrative Records: Administrative records include data on healthcare utilization, such as hospital admissions, emergency room visits, and insurance claims.

Health data collected can be used to monitor trends in health, identify risk factors, and evaluate the effectiveness of interventions. What other health data collection methods are you aware of?



The depth, range, and scope of data collected in health is diverse and complex, so it cannot be considered in detail here. Research on fields as diverse as biochemistry, psychology, genetics, and sports physiology have usefully illuminated aspects of population health, but the problem of central collection and collation and of making valid generalizations reduces the usefulness of most data from health-related research for the purpose of delineating aspects of national health.

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You are absolutely right. There is the need to collate the diverse health datasets from different areas of the health systems to be useful in effective policy making and implementation of interventions.