HEDIS (Healthcare Effectiveness Data and Information Set)
HEDIS -- Pros and Cons
When it comes to measuring the performance of American health plans, this is where HEDIS (Healthcare Effectiveness Data and Information Set) comes into use. It is widely used throughout America to assess the quality of health services and has 81 measures across 5 care domains. According to NCQA, HEDIS presents a reasonable comparing measure since it is used by so many plans to collect data and also because it is a very accurate measure.
Pros of HEDIS Measures:
HEDIS data is used by several health care plans to the employers as well as for self-assessment and improvement. It is also used by employers, consultants and consumers to help in finding the best health plans suitable for their requirements. Results produced by the HEDIS measures are double checked by the auditors who carefully examine the reports to ensure accuracy. The audit is done on the basis of method provided by National Committee for Quality Assurance.
It is also crucial that HEDIS is maintained up-to-date and does not consist of any obsolete data. To look after this issue, the NCQA's Committee on Performance Measurement, which is a group consisting of employers and consultants, organizes meetings and debates to decide which measures...
It measures whether the members are content with the care service under claims processing, customer care, and the time taken to care for a customer. It also enables a reasonable comparison of health plans on an "apple-to-apple" basis. The HEDIS results, which are extremely accurate are posted in the web-based Quality Compass and thus provides interactive comparison of results, additionally, it is easy to view. This also helps the members in competitor analysis, quality measurement, and benchmark plan performance.
Cons of HEDIS Measures:
However, there are also several downsides to using the HEDIS measure to calculate performance of health care. Since the data is not double-checked, it may be unfair to its competitors which are honest and audit their data. (Berman, 1999) Another problem may arise due to "distraction"; a newly discovered issue, which shows that the method of HEDIS may lower the quality scores due to the self-contradictory aspects of these measures. If more health-care measures…
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