Purpose. There are many reasons to conduct chart reviews such a required by a regulatory agency, justification of billing, and research. Another frequently used purpose of a chart review is to assist in measuring quality of care. This measurement is then used to help determine if a change in process is needed to improvement patient outcomes. There are several models used in process improvement including Juran’s Universal Sequence for Quality Improvement, the Seven-step problem-solving model, FOCUS-PDCA and Six-Sigma DMAIC (Langley, Moen, Nolan, Nolan, Norman & Provost, 2009). Chart reviews can be an integral step in all of these models in gleaning data to measure the depth of the problem or if it even exists. This paper will
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Data obtained from chart review is also beneficial in laying the groundwork to help decide if a more involved or any project is needed (Connelly, 2008). Chart review may also unearth an opportunity that was previously unknown (Connelly, 2008). For example, doing a chart review on patients that had a Rapid Response Team called, could unearth a trend that was completely unlooked before. One disadvantage of chart review is that data gleaned from is noted to be, at times, inaccurate (Nagurney, Brown, Sane, Weiner, Wang & Chang, 2005) and incomplete (Wu & Ashton, 1997). Also, different clinicians have different charting styles and may even document in different places in the chart, which can cause misinterpretation or inability to locate needed information (Wong, 2009).
Considerations. The steps involved in performing a chart review vary due to organizational factors such as the number of people involved, the amount of data needed, the type of charting system used, and how the data will be recorded. Some data, such as demographics, is much easier to get and record than data that may need to be obtained from narrative information. If the data is complex enough, it may need a clinician with the appropriate expertise (Aaronson & Burman, 1994).
Data Accuracy. Steps must be taken to ensure validity and reliability of the data collected. Validity refers to the accuracy with which the data reflects what it is supposed to measure. Reliability is the