Essay on data quality

The Quality of Data provided by patients is to healthcare practitioners is very important as this can lead to disastrous situations. Several studies have been done by different research institutions in the attempt to improve the quality of data healthcare practitioners generate from the patients and other data providers. However, despite all of the studies, the problem has not been completely eradicated. Reliable and valid data are prerequisites to the achievement of right decisions and diagnosis of health care practioners.
There are several real and fictitious data entry issues that could compromise data quality gathered. One of these is the simple distraction of the holder of data. If a health practioner is tasked to monitor the breathing pattern of a patient every 30 seconds and he gets distracted by something or someone. (American Academy of Orthopeic Surgeons, 2014) A single miss could be the key to finding the correct diagnosis but the health practioner failed to do his task. If a patient with high blood comes to a health facility feeling nauseous and is suspecting that his blood pressure has risen. However, the health practioner got distracted by a police siren while taking the patients blood pressure he read the wrong blood pressure. So instead of helping the patient by providing appropriate medicine to decrease his blood pressure, no medicine was given. The life of the patient can be compromised.
Another data entry issue is relevant to patient identification errors. The integrity of documents are put at risk when an information is documented on a wrong patient health record. The clinical decisions are affected by the errors committed in the identification of patients. This can compromise the safety of the patient as wrong diagnosis can lead to wrong clinical and laboratory tests and wrong medicines. This in turn can lead to not only increasing cost but also compromising the life of the patient.(AHIMA)
With the increasing popularity of Electronic Health Information Systems, increasing errors related to the use of clinical support systems also arises. These errors are brought about by several factors like “ software design flaws, system performance issues, poor decision support rules, inadequate user training, human error, disruption of system use because of interruptions by colleagues, or use of the system in ways not intended by the system developer” (Bowman, 2013) Users of the support systems might miss to notice or provide important data that affects the result provided by the decision support system simply because these are not emphasize by the system. Data entry errors can also lead to the wrong advice provided by the system. A small error in the combinations of conditions in the programming level of the system can also lead to disastrous advices that can be adapted by the health care practitioner. Some suggested ways to reduce the errors brought about by the systems are to improve the design of the systems in such a way that important and sensitive data are emphasized, improving the proper use and usability of the system by providing proper orientation and documentation, and improve documentation capture processes.

References

AHIMA. “ EHRs as the Business and Legal Records of Healthcare Organizations (Updated).” (Updated November 2010) Retrieved from http://library. ahima. org/xpedio/groups/public/documents/ahima/bok1_050286. hcsp? dDocName= bok1_050286
American Academy of Orthopeic Surgeons (2014). Prevention of Medication Errors. Retrieved from http://www. aaos. org/about/papers/advistmt/1026. asp
Arts, Danielle G. T. (2002). Defining and Improving Data Quality in Medical Registries: A Literature Review, Case Study, and Generic Framework. J Am Med Inform Assoc. 2002 Nov-Dec; 9(6): 600–611. Retrieved from http://www. ncbi. nlm. nih. gov/pmc/articles/PMC349377/
Bowman, Sue (October 2013). Impact of Electronic Health Record Systems on Information Integrity: Quality and Safety Implications. Perspect Health Inf Manag. 2013 Fall; 10(Fall): 1c. Retrieved from http://www. ncbi. nlm. nih. gov/pmc/articles/PMC3797550/