Healthcare databases with a focus on electronic health records

What is it?

Healthcare databases are systems into which healthcare providers routinely enter clinical and laboratory data. One of the most commonly used forms of healthcare databases are electronic health records (EHRs). Practitioners enter routine clinical and laboratory data into EHRs during usual practice as a record of the patient’s care. Other healthcare databases include claims databases, which are maintained by payers for reimbursement purposes, pharmacist databases and patient registries. Healthcare databases can be used as data sources for the generation of real-world evidence (RWE).

Examples of initiatives for healthcare databases

The Medicines & Healthcare products Regulatory Agency (MHRA) has published a position paper on compliance issues and user requirements for EHRs. This paper could be used as a basis EHR quality checks. In addition, the following initiatives aim to improve routinely collected data for use in research:

  • The TRANSFoRm project aims to develop a ‘rapid learning healthcare system’ that can improve both patient safety and the conduct and volume of clinical research in Europe.
  • The Electronic Health Records for Clinical Research (EHR4CR) project of the EU’s Innovative Medicines Initiative (IMI) has developed a technological platform that combines hospital data across countries, to identify sites and patients for trials.
  • An EHRCR tool will allow doctors to evaluate the quality and security of their EHR systems and provide study teams with this information.
  • The Sentinel Initiative is a linked system developed by the US Food and Drug Administration (FDA) that will draw on existing healthcare data from multiple databases to actively monitor the safety of medical products in real time and help to address the heterogeneity of data collection that currently exists.

Why is it useful?

  • Real-world data on risks and benefits: the use of routinely collected data, such as data from EHRs, allows assessment of the benefits and risks of different medical treatments, as well as the relative effectiveness of medicines in the real world.
  • Studies can be carried out quickly: studies based on real-world data (RWD) are faster to conduct than randomised controlled trials (RCTs).

What are its limitations?

  • Data is not collected for research purposes: practitioners and healthcare professionals are not trained to collect data. Data collection process may not be clear and may result in imprecise, incorrect or incomplete data entry. By training staff this limitation may be avoided. However, this may interfere with the usual care provided to patients, for example by altering treatment decisions. This could result in a decrease in the generalisability of study results.
  • Invalid, inaccurate or incomplete data: routinely collected data may lack detailed information on indications, patient characteristics, treatments and events, and may be less structured (van Staa et al 2014). In addition, data are typically obtained during clinical visits, which may be infrequent or irregular.
  • Quality and completeness of data varies within and among databases: routinely used healthcare databases are varied and heterogeneous. Data quality checks within the data collection system that detect incorrect or missing data, and specify procedures for correction, may ensure that differences within and among databases are detected and accounted for.
  • Variable quality and completeness: EHR systems include patient data beyond that needed for a study. Access to this data (rather than study-specific data) raises right-to-privacy concerns.

What do stakeholders say?

Advantages of EHRs from a patient-perspective:

  • Collecting and storing patient health information in electronic databases enables clinicians to keep track of patients’ conditions over time.
  • Information can quickly be accessed anywhere at any time, and all the relevant information is kept in one place.
  • Using EHRs can help clinicians to give patients treatment that is more effective and better aligned to patients’ needs.
    Appropriate measures to safeguard patients’ data are necessary. Additional security features should be used when necessary, and patients should be provided with clear information on how the data will be stored, used and protected.

Key contributors

Rachel Kalf, Zorginstituut Nederland (ZIN)
Anna-Katharina Meinecke, Bayer