Stalis
 

Data management - a priority for healthcare systems

Most of the attention in healthcare IT focuses on new systems and the networks that connect them; worryingly, we hear much less about the quality of data that is destined to flow around them. This feature, produced with Stalis Ltd, seeks to redress the balance. The articles argue that healthcare organisations not only need to look long and hard at the quality of the data they propose to migrate into the new, integrated systems, but that they also need to speed up their plans and allow more time for the complex process of data cleansing.

The first article makes the case for paying far greater attention to data cleansing and, in effect, issues a wake-up call to trusts that have not yet addressed the issue or believe that the work can be done quickly and easily just before new systems arrive. The second article offers advice from Stalis' experts on the best ways to approach data cleaning and in the final article we look at how Sheffield Children's NHS Trust succeeded with its data cleansing, integration and migration.

Case Studies
Technician Data cleanliness - a pressing issue for trusts

With patient data being migrated from myriad local systems to the National Care Records System (NCRS), data cleanliness is fast becoming a serious, pressing issue for NHS trusts in England.

Doctor Migrate in haste... repent at leisure

The quality of data migration is fundamental to the success of the National Programme for IT. How do you ensure that your project will be successful and cause minimal disruption to your trust's day to day business of healthcare provision?

Baby Sheffield Children's NHS Trust: data cleansing, integration and migration

Sheffield Children’s NHS Trust is one of a handful of dedicated children’s hospitals in the UK, a regional centre of excellence with national and international specialties. This case study shows how the trust worked with Stalis to unlock, access and clean the data in its systems and provide ongoing support to maintain and improve data quality.

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