Uses of of Clinical Data

Structured Versus Free Text

For documentation and retrieval purposes, there is a dilemma if the clinical data should be structured (coded) or inaccessible text format. Medicine lacks uniform structured vocabulary and nomenclature, as do Physics and Chemistry. Structured data using some form of standardization can have a consistent representation and reduce documentation errors. However, structuring the data can reduce the “freedom of expression” in medical practice and losing the “art of medicine”. In a digital system, structured data is selecting codes from a given list of structured data.

When expressed in many ways, accessible text in the narrative format can be ambiguous and reduce uncertainty when the documents are read and used by different healthcare practitioners. In addition, narrative data can be represented using textual and numerical data.

Uses of Clinical Data

• Form the basis of the historical record – Clinical Data is collected during each encounter, and all data are accumulated to form the historical record.
• Provide a legal record – Clinical Data usually lies in different record systems in healthcare organizations. For example, within paper-based medical records, any observations, diagnoses, plans of treatment, and certificates of death can be used in court or any legal pursuit. It is formal documentation that is critical if needed to be used as evidence in a formal setting. Electronic documentation eases the process of retrieving data from multiple platforms if required to be used for court cases.
• Support communication among providers – Clinical Notes are shared from one provider to another provider to allow information are tallied across the chain. The exchange of information is crucial during handovers, referrals, and discharge to ensure the correct, accurate, and up-to-date data about the patients. Communication among providers also helps to reduce medical errors, to ensure the quality of care, and to allow two-way communication with patients.
• Anticipate future health problems – Once data is harnessed from the clinical encounters, data can be aggregated, and the analytical processes can be performed. Applying predictive analytics can help to anticipate future health problems. This process will reduce disease burden cost and mortality and morbidity among patients.
• Record standard preventive measures – Clinical data collection can be used as standard preventive measures using a dedicated registry. A Clinical Data analyst can process the data and conclude which variables can be used as preventative measures.
• Identify deviations from expected trends example, a growth chart By charting the data, healthcare providers can detect deviations by looking at individual trends.
• Coding and billing The clinical data can be coded into meaningful information that can be used for billing and insurance reimbursement purposes.