Rejections, then detective work
Your data manager runs the submission and a batch of records comes back with errors. A date is missing here, a field inconsistent with another field there. Each one means going back through notes, finding who recorded what, and asking a busy clinician to confirm a detail from weeks ago.
Deadlines for submission are fixed, so this detective work always happens under time pressure.
Why errors are found so late
- Fields are filled in by many people across a treatment cycle.
- Nobody checks completeness until the data is being prepared for submission.
- Validation rules are applied by the receiving system, not at the point of entry.
- It is hard to see which treatments are ready to submit and which are not.
- Fixes are made in the submission rather than in the clinic system, so the same errors recur.
Clinic systems often allow a record to be saved with fields blank, because treatment cannot wait for paperwork. That is sensible at the time, but it means the gap is invisible until someone goes looking. By then the member of staff who knew the answer may be on a different rota, or may have left.
What the late-fixing costs
Data managers spend long periods chasing corrections. Clinicians are interrupted to confirm old details. The clinic risks missing deadlines, and repeated errors can become a concern when your data quality is reviewed.
| Approach | Checks at submission | Checks continuously |
|---|---|---|
| When errors appear | After rejection | Soon after the data is entered |
| Who fixes them | Data manager, chasing others | The person who entered it, prompted directly |
| Visibility | Unclear until the run | Ready and not-ready lists at any time |
| Recurring errors | Fixed each time | Traced to the form or process causing them |
How we build pre-submission checks
- We work with your data manager to write down the completeness and consistency rules they apply, based on your regulator's published requirements.
- A check runs daily against your clinic management system's data, through its reporting database, API or export.
- Each treatment gets a status: ready, missing information, or needs review, with the specific fields listed.
- Issues are assigned to the role that usually enters that data, and appear on their worklist.
- Your data manager sees an overall dashboard of readiness ahead of each deadline.
- A record is kept of what was submitted and when, and of any rejections and how they were resolved.
- A monthly report shows the most common error types, so forms or training can be adjusted.
We do not submit to the register on your behalf. The checks help your data manager prepare accurate data. What is submitted, and when, is their decision under your clinic's processes.
What your data manager gets
Fewer rejections, and far less detective work at deadline. Errors are fixed while the details are fresh, by the people who know them. The data manager can see readiness at a glance and spend their time on genuine questions rather than missing dates.
The monthly report on error types is often the most useful part. If the same field is missed repeatedly, the fix is usually a change to a form, a default or a training note, not more chasing. Over time the checks catch fewer problems because the causes have been dealt with.
Is this your data manager's life?
- Submissions come back with many errors.
- Errors are fixed by chasing clinicians about past treatments.
- Nobody can say which treatments are ready to submit.
- The same errors appear each time.
- The deadline period is dominated by data corrections.