Practice Brief: Designing a Data Collection Process In any healthcare organization, data is collected in numerous ways for an ever-increasing number of reasons. Data may be collected by a monitoring device directly connected to the patient, or by providers as they make observations or record treatments. Quality improvement activities often call for data collection where observations of activities, timeliness, or satisfaction indicators are gathered. Data may be abstracted from primary sources and collected for unique reporting requirements, such as specialized registries or claims transactions. With the various types of data collected in many different methods for varied purposes, it is not surprising that data collection may have escaped management in the past. Why Is It Important?Data collection should be carefully managed in healthcare organizations. Time spent collecting data can consume huge portions of a provider's day -- taking him or her away from more direct patient care activities. Other employees may spend their entire day collecting data. When you consider the cost of data collection equipment, software, employee time, benefits, and other overhead, the price of data collection can add up quickly. And what are you getting for your money? Is the data collected reliable? Is it comprehensive? Does it provide the necessary detail to answer important clinical and business decisions? For the price your facility is paying, the answers to these questions must be yes. AHIMA's data quality management model depicts data collection as one of the four primary data functions. The others are application, warehousing, and analysis. All characteristics of data quality management should be applied to data collection processes, including: Accuracy Accessibility Comprehensiveness Consistency Currency Definition Granularity Precision Relevancy Timeliness Design ProcessWhen faced with a new application (or use) of data, the following factors sh...
