OnCo
ideasIdea

Double oncology capacity in low-resource settings with task-shifting and AI decision support

Many countries have one oncologist for millions of people. Train nurses and general doctors to deliver protocolised cancer care with software checks and remote specialist oversight.

Workforce shortages, not drugs, cap cancer treatment in much of Africa and South Asia. Task-shifting with decision support scaled HIV treatment; oncology has pilots (nurse-led chemotherapy, Botswana and Rwanda models, tele-oncology networks). The proposal is a package: protocol-driven regimens for the commonest cancers, a decision-support and safety-check tool validated for use by non-specialists, remote tumour board review, structured training and certification, and outcome registries to monitor safety and quality.

Hypothesis
Task-shifted, AI-supported care delivers guideline-concordant treatment with toxicity and survival outcomes non-inferior to specialist-delivered care and treats twice as many patients per oncologist.
Rationale
Most cancer care is protocolised and the risk lies in omissions and dose errors, which software and remote oversight catch reliably.
What would test it
Stepped-wedge implementation in district hospitals in two countries with treatment completion, protocol adherence, severe toxicity and one-year survival as endpoints compared with specialist centres.
Maturity
early clinical
Who has to act
policy
Cost to try
Large (over $50M)
Years to first evidence
5
Bottlenecks it attacks

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