Whether for health reporting, evaluating disease management programmes (DMP), integrated health care and elective tariffs or for analysing diagnosis related groups (DRG) – prompt and reliable analyses of process data are indispensable nowadays. infas is very experienced in editing and analysing process data in public health service. infas can offer its clients prompt delivery of high quality results due to the routines and tools specifically developed for these purposes – even if several millions of data records out of different sources need to be checked, joined on individual level, and analysed. Sufficient technical resources are at hand, since infas routinely processes mass data.
Optimum timing of processes and proprietary tools for process data analysis lead to rapid delivery of results right upon receipt of actual customer data. The implementation of routines such as importing, checking, cleansing, editing, joining and analysing test data starts immediately at the project's outset. Therefore, these preparatory tasks ensure prompt data analysis upon receipt of the actual customer data.
infas uses specific software as professional output tool for complex reporting. Templates for reporting need to be determined in advance with the respective client so that the analyses' results can be transferred into reporting format without delay. A proprietary tool can alternatively transfer the analyses' results into MS Word-based format - even with highly complex tabular structures - so that the client itself can easily adapt the templates to its corporate design.
infas established a specific branch of quality assurance for data handling of process data, which determines additional specific instruments as required to back up base data. This means in particular:
- plausibility checks (per variable and cross-variable),
- control of duplicates (identical duplicates, quasi duplicates),
- merge ability check.
Early transfer of the respective test results to the client allows for - if need be - optimising the quality of the transferred raw data prior to starting analyses.