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Table 3 Summary of recommendations for designing QIT's

From: Quantitative data management in quality improvement collaboratives

Communication

Communicate on all levels, both management as care workers in the teams. Create a transparent design in which each person understands his purpose. Make sure that the QIT design is presented well before onset.

Data traffic

When there is data traffic make clear that it must be secured. Medical data must always be encrypted when it leaves the hospital even when it is anonymous.

Security

Data must be stored in a secure environment, preferably with a third party organization specialized in storing medical data. Ownership of the data must be subjected in a data management protocol.

Spreadsheet

Working with standardized spreadsheets leads to standardized data. Working with spreadsheets is not in line with the philosophy of the breakthrough method. In large QITs it is however inevitable to have at least part of the data standardized. By providing spreadsheets that are easy to extend with other variables it can even help promote additional data gathering.

Feedback

Central data management sometimes only seems to create demands for the teams working in QITs. It's therefore essential for data management to provide the teams with valuable feedback on different levels, both on their own teams, as their own hospital as the project they are involved in. Providing useful feedback encourages the teams to deliver their data to the central database.

Confidence

Quality improvement is about people and their positions. Their must be absolute confidence on how the data is trafficked, stored and on how the results are used. People will not cooperate in a process of which they think it might harm their position or institutions. A data management protocol with rules and regulations on handling the data and ownership of the data can be helpful in creating confidence.

Data management desk

Only a few of the hospitals involved in the FB p3 program had a tradition on standardized and large-scale data management. In the first cohort unfamiliarity with data management was an obstacle. The hospitals in the second cohort were advised to install a data management desk that could assist all participating teams within the hospital with their data traffic.