Health info managers launch clinical coding AI adoption guide

An association of health information managers, clinical coders and clinical documentation specialists in Australia has published a guideline to adopt clinical coding solutions.

The directive developed by the Health Information Management Association of Australia (Himaa) emphasizes an approach based on principles to take AI technologies to generate clinically coded data. It is intended for health care organizations, clinical coding workforce, software companies, government agencies, coded data users and educators.

It describes seven key considerations: governance, risk management, confidentiality and security, ethical and safe use, improvement in quality, collaboration and partnership, and human expertise or humanity in the loop.

Why it matters

Himaa recognizes that AI offers “significant potential to improve the integrity of clinical documentation, allow autonomous coding, support clinical coding audits and improve health information management.”

He also sees how the evolution of the role of clinical coders, “requiring new skills in AI monitoring, management of exceptions and identification of algorithmic biases”.

“The adoption of this directive should lead to a safer adoption of AI by the sector, compliance with relevant legislation, standards and executives, and increased workforce of the workforce while confirming the role of clinical coding workforce in AI environments,” said Himaa, explaining its development of the Directorate of AI adoption.

The association urges health organizations to “go beyond technical deployment and to consider the broader ecosystem of governance, labor and regulatory expectations”.

“In the end, the successful application of clinical coding based on AI is based on the balance between automation and human surveillance, integration of governance into innovation and ensuring compliance while optimizing efficiency and precision,” said Himaa.

In addition, the association highlighted the need to invest in a “evolutionary IT infrastructure”, which includes processing and cybersecurity measures based on the cloud, to support long -term sustainability of the long -term AI.

Meanwhile, the Himaa directive does not provide specific advice on the adoption of AI for improving clinical documentation or technical specifications, computer infrastructure needs, interfacing specifications, AI products selection recommendations or other linked AI solutions such as ambient clinical documentation. However, its principles can be applicable to these areas.

The biggest trend

There are various advantages of the implementation of coding solutions assisted by AI; According to Himaa, AI can help solve coding shortages and code backwards and speed up the coding process. Technology can also be used to code a certain data subset and perform routine or low value tasks, so that coders can work on greater value tasks.

Northern health In Victoria, for example, recently went to a coding assisted by the AI ​​to mainly approach its coding labor in narrowing. Te Whatu Ora Health New Zealand, meanwhile, is trying to pilot a clinical coding solution assisted by AI for hospital admissions to improve the speed and precision of care.

However, Himaa noted that there was not yet published evidence of these potential advantages in the context of Australian health care.

The association has also noted common obstacles to the absorption of AI coding solutions. At the start of the adoption, these are in particular the challenges of integration, investment and cost, lack of confidence, risk appetites, capacity for change management, preparation of AI model, preparation and training, cybersecurity and confidentiality of data, the lack of digitized medical records and regulatory and governance considerations.