IS WORK OVER?

Automation index

How much of a Health information technician’s job can AI already do?

An ICD-10 and a file come earlier. Coding it right and having the record when it is needed do not.

This percentage does not predict how many people will lose their jobs.

Task comparison

Health information technician

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Code ICD, the discharge set and the episode.
Estimate

No public source provides a precise figure. This is our estimate.

18%52%+9.4
Filing, scanning and the missing record.
Estimate

No public source provides a precise figure. This is our estimate.

16%48%+7.7
Loans, copies and the judge who wants the file.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Documentation emergencies and the discharge that will not close.
Estimate

No public source provides a precise figure. This is our estimate.

18%18%+3.2
Data quality, audits and billing.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
Confidentiality and not losing the record.
Estimate

No public source provides a precise figure. This is our estimate.

16%14%+2.2
Total100%31%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • code ICD-10
  • discharge dataset
  • file records
  • loan records
  • health documentation
  • scan reports
  • clinical data quality
  • confidentiality

Sources for this job· O*NET 29-2072.00· ESCO/ISCO 3252

Olive-oil miller

Where the time goes

Task weights are our estimates based on O*NET frequency data, not time shares published by O*NET.

The time saving for each task is estimated separately.

TaskShareAIPoints
Intake, yield and the mill log.
Estimate

No public source provides a precise figure. This is our estimate.

16%40%+6.4
Crush, malaxate and the decanter.
Estimate

No public source provides a precise figure. This is our estimate.

18%12%+2.2
Temperature, time and the fruitiness.
Estimate

No public source provides a precise figure. This is our estimate.

16%28%+4.5
Cellar, the batch and the one that goes rancid.
Estimate

No public source provides a precise figure. This is our estimate.

16%22%+3.5
The campaign, the tractor queue and not heating.
Estimate

No public source provides a precise figure. This is our estimate.

18%18%+3.2
Cold for real, and not painting the yield.
Estimate

No public source provides a precise figure. This is our estimate.

16%12%+1.9
Total100%22%

Modelled workweek: 100% · Public evidence: 0% · Estimate: 100% · Confidence: Low

Skills and activities

  • crush olives
  • malaxation
  • decanter
  • fruitiness
  • the campaign
  • mill yield
  • oil cellar
  • extraction temperature

Sources for this job· O*NET 51-3092.00· ESCO/ISCO 7514

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