AI-based coding the only way for Registries to handle increasing loads and CTR shortages

I have spoken at a number of conferences in the past few years and attended even more as a delegate. One perennial topic raised in conversations is the worrying shortage of CTRs and its impact on the efficiency of registries and the need to stretch budgets further than ever.

The shortages and shortcomings are mostly due to factors outside the control of registries and has resulted in increasing reports of growing backlogs, staff burnout, and a reduction in registry efficiency.

Recruitment of new staff has proven problematic with the cohort of senior CTRs moving into retirement age, exacerbated by the introduction of more and more coding requirements. Young potential staff have more work and eduction opportunities available to them so they find clinical coding a less attractive occupation. The higher mobility of these young staff makes it all the more difficult to retain them even once they are recruited

Delays in recruiting new staff have their own knock on effects by increasing backlogs and making it more difficult to provide timely statistics on the distribution and growth of disease cohorts.

The value of Registries has been increasing in that they have been able to provide valuable information for health planning authorities, but the registries themselves are looking for more ways in which they can contribute to the care of cancer patients. As the most comprehensive source of information about a patient they represent a valuable resource for clinical carers when they are making decisions for patients. The efforts made by Registries to extend their capabilities has led to further pressure to make more information available. The expansion in medical investigations, especially in the imaging and pathology technologies has also increased the demand on registries to collect and analyse even more data.

Large pharmaceutical organisations and other medical research groups are increasingly wanting a larger the range of data made available to them and this puts even further demand on registries.

The question for all registry directors is how to cope with:

  • decreasing staff availability;
  • increased data volumes;
  • increased data requests;
  • faster turnaround requirements; and,
  • diversification of their functions.

The popular answer in today’s medical technology enthusiasm is for Artificial Intelligence (AI), but can it really help? And what can it actually do? Here are some suggestions with their advantages:

Suggestions

  • Sort out reportable cancer reports from non-cancer reports and non-reportables;
  • Extract the five core attributes of {Site, Histology, Grade, Behaviour, Laterality} from the cancer reports;
  • Codify the five core attributes to ICD O3.

The advantages of these functions for a cancer registry would be highly significant. The first function would remove a serious and substantial bottleneck to fulfilling the main task of Case Identification and Coding . In some states the amount of unuseful reports can reach as high as 60%, so in a state like California this can represent about 600,000 reports that are unwanted and a nuisance that clutters up the principal work of the registry.

The second function should be designed to process simple reports automatically and move the cryptic reports to a Manual processing workflow stream. In this way the mundane work would be removed off the registrar’s desktop and they could spend additional time on the more difficult cases.

The third function is important in semi-automating the coding of reports. This requires sophisticated AI as there are over 800 histology codes in ICD-O3 and many of them are defined by complex combinations of content and rules. This labyrinthine standard is better served by a strong AI solution that makes fewer mistakes, with mechanism for identifying the most difficult to be passed to Manual Processing.

AI holds out a promise of increasing the efficiency of cancer registries by releasing staff to do the most difficult work. It is not self evident that this use of AI will cause disruption to the workforce. It should act as a support mechanism for staff who are already surrounded by a shrinking workforce, increasing demands, and flooding data lake that they cannot escape.

I would welcome the chance to hear of your particular challenges and explore ways we could work together to enhance the productivity of your registry.

Cross-posted to LinkedIn.

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