Data quality
Data quality in health care is crucial. The Data Quality Module is important as it ensures that all aspects of the data are gathered for. There are many aspects of data quality that has to be taken care of. The different features of data quality in health care are important. This model is important because it entails the entire process of handling data right from collection to the stage of warehousing. Data can be corrupted on in either of the stages. The model therefore takes care of each stage by giving what should be done to ensure that each stage is taken care of. The model not only takes care of the stages of data handling but also the different aspects of data features and characteristics. The data model is used a benchmark to measure the quality of data so that the process of testing the data is not biased. This model can be used by electronic health record (EHR) in managing electronic records. The shift from traditional method of recording data to electronic way will need that electronic data is as quality as much as possible.
Collaboration is important because it forms a basis for clinical diagnoses and documentation which has been created by various clinical staff and support personnel. There is therefore a need to have collaboration between these staff so that data accuracy and the correct terminology is adopted. This will help research to be carried out in a systematic way. The tools that can be used to encourage collaboration is through proper documentation, proper communication channels and proper structures. Other tools are ensuring that proper information systems be put in place to ensure that users can communicate and track documentation of other staff.
References
AHIMA coding products and services team. (2003). Managing and improving data quality. Journal of AHIMA, 74(7), 64A-C.
Merida, J. (1997). Information management of health professions. Albany, NY: Delmar Publishers.
