Table 5 Catalogue of encountered problems

Data not available in

Data items required to compute many of the indicators, such as those contained in the pathology reports, were only

structured format

available in non-structured free text, and therefore not directly (re)usable. Also structured data to exclude patients based on

the exclusion criteria recurrent carcinoma and TEM-resection as well as ‘resection’ via colonoscopy was not available in our EMR

nor in the DSCA dataset. Non-recorded exclusion criteria can lead to lower indicator results, wrongly underestimating the

quality of care for indicators whose percentages are to be maximised [16, 17].

Incorrect data items

The double data entry in our case study helped us to discover incorrect data items. Furthermore, we identified imprecise

and/or incorrect diagnosis codes in our EMR.

Incomplete view of

Hospitals throughout the country refer patients to our hospital, which specialises in gastro-intestinal oncology. Some of

patient history

these patients are only treated for a short time, and then referred back. Likewise, our hospital maintains an alliance with a

nearby hospital. Referral letters are typically posted as physical letters, making a complete, consistent view on a patient’s

history difficult to obtain. For example, it is hard to retrace whether preoperative imaging of the colon has taken place in

another hospital.

Lack of relations

Our EMR does not store any relations between diagnoses and procedures, making it impossible to select the diagnosis that

between data items

was the underlying reason for a procedure. For example, the lymph node indicator should only select lymph node

examinations that have been carried out in the context of a primary colonic carcinoma, and not, for example, a previous

mamma carcinoma. As a partial solution, we imposed the constraint that the diagnosis should have been established before

the related operation was carried out, which resulted in some missed patients.

Lack of detail

None of the diagnoses in the EMR was detailed enough to meet the information required by the indicators, which include

patients with primary colonic and rectum carcinomas. The only relevant diagnoses in the EMR were malignant neoplasm

of colon, rectum and rectosigmoid junction. Therefore, the concepts employed in the queries to compute the indicators

had to be generalised. Furthermore, only the type of endoscopies is registered, such as colonoscopy, but not whether the

complete colon is affected.

Lack of standardisation

For example, the urgency of an operation is defined in the EMR according to 8 categories, but the DSCA dataset only

differentiates urgencies according to 4 categories. It was not clear how these categories should be mapped, as their

meaning was not unambiguously described (for example, one of the categories was called “extra”).