Clinical data management has the capacity to simplify micro-tasks that can be cumbersome for staff members. Nurses need to place their emphasis on patient comfort and review, and not on the technical details that can meddle with their ability to work effectively. Administrative agents oversee these processes, and Human Resources reps and technicians can confirm that the system is properly maintained. Data management relies on cooperation through the entire chain. The constant pursuit of quality improvement in healthcare runs into a few expected obstacles. Even if every person is collaborating to the highest degree, some issues are unavoidable. Below are two main reasons for inaccurate reporting.
E-Measures Skip and Misappropriate Data
An e-measure is a formal report of a certain selection of data points. The e-measures from healthcare quality improvement only arise from data points collected into the certified EHR technology. Data not added to this filing will not be present in the e-measure. There are two common results in this scenario. The first is that the report will simply have a missing data point. It will acknowledge that data should be there, but it does not have the provisions to provide that data. The second likely scenario is that the e-measure will omit any mention of that non-structured data. It continues on as if it did not exist. The latter of the two scenarios can cause inaccurate reporting, especially because it does not alert the person reviewing the measure that data is missing.
Data Source Problems
Data cannot be gathered in a subjective way. Improving healthcare quality works on a very detailed process. For example, the system is collecting data on how often patients show up late. The goal is to determine the patient spread and clinical quality measures patient flow for the future. If some patient's do not sign in immediately, the data will be off. Furthermore, some staff members may state the arrival time as the time the paperwork is submitted (which could create discrepancies of 15 or more minutes). The data could be thrown off due to ground floor practices and the lack of consistent data integrity.
For the most part, these issues can be minimized but never rid of entirely. There will always be the potential for inaccurate reports due to human error and system interruption. The task of quality improvement healthcare never ends, and that is the way it probably should be. When complacency sets in, systems fall slack and irresponsible.