Let’s know what Clinical Documents are.
Clinical Documents are written records or reports documenting various aspects of patient care and medical encounters. With a crucial role in the healthcare domain, including communication, legal or regulatory purposes, research, etc, these clinical documents can take various forms.
The clinical documents can be study templates, protocols, discharge summaries, or reports, along with other documents. However, it is highly crucial to maintain accuracy and comprehensive information. These documents should be legible, timely, and adhere to privacy and confidentiality regulations.
Where does Artificial Intelligence fit in all this?
Since years now, these documents have been created and reviewed manually. With a lot of efforts and expertise from Medical Writers, these documents go with multiple cycles of reviews, to ensure that the information shared is highly accurate and proven.
But in the recent years, Artificial Intelligence (AI) has grown tremendously. Not in a specific field, but AI has made its jump into a variety of sectors, Healthcare being another sector highly benefited. From spending days on reviewing the clinical documents, now AI has come with its algorithms to reduce the time, to just mere few hours.
Now we know the basics, so let’s get into how AI is able to achieve such complexities.
Artificial intelligence is the development of computer systems that can perform tasks that typically require human intelligence. In the context of clinical document review, AI algorithms are employed to analyse and extract meaningful data from vast amounts of information. These algorithms are trained on large datasets of interpreted clinical documents, enabling them to recognize patterns, identify key information, and make predictions. Since being trained on variety of clinical documents, AI is able to understand new patterns and analyse them into meaningful reports.
Finally collaborating AI and Clinical Review
- AI can process and review clinical documents at a much faster rate that humans. They can analyse large volumes of data in a short period, allowing healthcare professionals to access critical information promptly. This efficiency leads to improved decision-making and better patient care.
- AI algorithms can accurately extract relevant information from clinical documents. This automated extraction reduces the risk of manual errors and ensures the completeness and accuracy of the information captured.
- AI algorithms can be trained to follow predefined rules and guidelines consistently. This helps in maintaining standardized documentation practices across different healthcare providers and reduces variations in the way information is recorded, ensuring uniformity and clarity in clinical documents.
- By analysing large datasets and recognizing patterns, AI tools can identify trends, highlight potential risks, and suggest appropriate treatment options based on evidence-based guidelines.
- With AI handling the initial review and extraction of information from clinical documents, healthcare professionals can focus more on direct patient care and spend less time on administrative tasks. This improves workflow efficiency and allows clinicians to allocate their time and expertise where it is most needed.
- AI-enabled clinical document review facilitates research and population health studies by providing access to large amounts of data. Researchers can leverage this data to identify cohorts, study disease patterns, monitor treatment outcomes, and contribute to evidence-based medicine.
Now, GENINVO offers a variety of innovative solutions, keeping in minds the medical writers hard-work. With expert subject matter experts and technological leaders, we offer tools to leverage the burden for medical writers and help them shift their focus more towards leveraging their critical thinking and factual interpretations.
To help with the review of clinical documents, DocQC does it, merely within few working hours. You can just create your project, upload the documents waiting to be reviewed, and be ready to review. With different quality control checks in DocQC, you can select which section of study report you want to QC, and also select whether to review in the moment, or later with downloaded offline report. With just few minutes to generate reports, DocQC save medical writer’s time, and also reduces potential errors that might be overseen by human eye.
In Conclusion,
Artificial Intelligence has transformed the field of medical writing, particularly in the automation of clinical reviews. By leveraging AI algorithms and NLP techniques, medical writers can streamline the quality control review process, from data extraction and literature screening to data synthesis and language processing. AI-powered automation enhances efficiency, accuracy, and collaboration, saving time and effort while producing high-quality clinical documents. As AI continues to evolve, it holds great promise for further revolutionizing medical writing and advancing evidence-based medicine. With continued advancements and proper oversight, AI will play an increasingly vital role in improving patient care and healthcare outcomes.
By Hargun Kaur Sethi
Software Development and Business Growth, GENINVO
