Software Company CEO Believes AI Will End Healthcare's Labor-Intensive Paper Chase

According to DataLink Software CEO Ashish Kachru, the healthcare industry can learn valuable lessons from other sectors that have embraced technology to streamline processes.

Kachru believes that leveraging artificial intelligence (AI), large language models (LLM), machine learning (ML), natural language processing (NLP), and robotic process automation (RPA) can revolutionize healthcare administration, compliance, and care delivery.

Labor-intensive "Chart-chasing"

Kachru specifically highlights the labor-intensive practice of "chart-chasing" as an area in need of transformation. Chart-chasing involves manually reviewing paper-based medical charts, placing burdens on healthcare plans and providers. Compliance with regulatory or third-party deadlines further complicates this process.

Drawing a parallel to traditional financial audits conducted on-site, Kachru explains how the majority of financial audits have transitioned to electronic methods.

However, some industries, like construction and manufacturing, still rely on paper audits for their tangible assets. Kachru emphasizes that digitizing data from paper documents is a priority, as few organizations opt for expensive and cumbersome manual audits.

In healthcare, chart-chasing occurs when health insurance teams audit medical records for coding errors and omissions during visits to provider organizations. Regulatory and financial imperatives drive these audits, often taking place at year-end and presenting significant challenges.

The healthcare industry's use of the International Classification of Diseases (ICD-10) further adds complexity, with its extensive set of 75,000 codes developed by the World Health Organization, according to Kachru. The tech CEO acknowledges that expecting providers to master and apply every code is unrealistic.

To capture a comprehensive view of patient health, Kachru suggested that healthcare providers must capture both structured and unstructured data during patient encounters.

While structured data, such as electronically inputted ICD-10 codes, hold value, unstructured data, including CAT scans, free text notes, spoken evaluations, and faxed documents, provide crucial insights that are difficult to standardize.

Leveraging NLP and ML

Kachru advocates for leveraging natural language processing (NLP) and ML algorithms to extract meaning from spoken and written words during patient visits. By decoding and converting unstructured inputs into intelligible information, technology can enhance data capture speed and accuracy.

Kachru acknowledges that changing healthcare practices requires a shift in industry culture. Educating stakeholders about the benefits to patients and the greater good is crucial. Technologists must develop user-friendly solutions that inspire confidence and make data sharing the natural course of action.

"Leading technology players are already deploying sophisticated tech capabilities to drive proactive, data-rich methods to the "next best step" in the patient treatment trajectory. Just as fewer people today write checks in their daily lives, payers and providers are edging closer to the day they can enjoy a truly standardized free flow of data in many new ways," the tech executive wrote in a Forbes article.