Post marketing surveillance is the process of monitoring the safety of a pharmaceutical drug or medical device after it has been released on the market and is an important part of the science of pharmacovigilance. The drugs and medical devices are generally approved on the basis of clinical trials, which involves relatively a number of people who have been selected for this purpose and they do not have other medical conditions. Post marketing surveillance of the drug can further be confirmed or denied of safety of the drug or device after it is used on the general population in large numbers with people who have a wide variety of medical conditions. Clinical data registries are very useful across many parts of the healthcare system. One of their most valuable purposes is the post-marketing surveillance of medicine.
How to Conduct Post-Market Surveillance?
It is generally divided into 3 parts
- Data Collection
- Data Analysis
- Data Interpretation
These are the steps which are done for conducting post-marketing surveillance on medical devices and drugs.
Step 1: Data Collection
Here the person needs the right data sources to work upon as well as the right technology so as to collect data efficiently, securely, and accurately for the post-marketing surveillance activities.
These data can be collected from several sources, such as:
- Medical record data that can be the electronic health record (EHR), clinical trials, lab results, imaging studies, and pharmacy prescriptions.
- Patient generated data which are got from patient-reported outcome (PRO) surveys or wearable biometric devices like smartwatches and smartphones.
- Payer and regulatory data that are collected from billing and insurance claims.
- Registry data from the industry, disease, patient, or medical specialty registries.
Step 2: Data Analysis
Once the data is collected for a given device or product, the next step is transforming them into real-world evidence. This generally involves combining, blending, validating, and analyzing the various data sources. These analyses can contain risk and reliability-adjusted according to the data which is collected and then presented to stakeholders in an interactive and interesting way.
Step 3: Data Interpretation
Once the data is collected and analyzed, there is need of a way to interpret the data easily and readily. Here are a few things that are considered here:
To ensure timely and accurate interpretation of data, a person needs statistically-adjusted reports that are available in the real-time. This helps to quickly and easily measure and understand the clinical outcomes, determine the patient’s quality of life, and understanding the total financial impact of the intervention.
Statistically-adjusted reports should always be built using key risk and reliability adjustment methods that are essential to achieve maximum data value.
