Case Study Of Central Medical

989 Words 4 Pages
Central Medical is a group practice consisting of 4 physicians’ offices. Central’s committee is trying to find a way to predict high risk patient groups. They want to take patients from these groups and apply intensive treatments. This paper will discuss process that Central used, additional processes that could be used, how data can be used to guide clinical practice, and the application of this case to another clinical environment.
Central’s Process The committee first makes a determination of what disease process they want to focus on. After this has been determined patients and families should be included in discussions. The patients that have the disease and their families can give firsthand knowledge as to if they would participate
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Health First is focused on profit and Central is focused on quality. More profit is a goal of Health first while Central’s goals are quality focused. By predicting areas of decreased resource consumption, an organization would then know where they may be saving money. If these areas are determined, then the more costly and time consuming areas can be focused on more easily.
In this case, the committee members themselves determined the criteria to be used for high risk patients. There is no mention of any research or other guidelines that were used to make the decision. Therefore, confidence in the criteria they selected is not high, meaning that since there is no data to prove that these are actually high-risk criteria there is a high risk of the criteria being incorrect. The decision on the criteria was made using collective
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However, they are often not in the correct format to be measured. Four challenges of using insurance claims for data reviews are: (1) conversion of claims into unique visits, (2) identification of incomplete claims data, (3) categorization of providers and locations of service, and (4) selecting the most useful measures of utilization and expenditures ("Quality of care," 2014). There is also a question of reliability and validity of the data. One study found only a 78.2% agreement between the principal diagnosis in a billing dataset and the principal diagnosis in the medical record ("Quality of care," 2014). Another study found that there was bias noted in coding comorbid condition on patients that died in the hospital, showing conditions that would be expected to increase the risk of death actually decreasing it ("Quality of care,"

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