A paper by R. N. Rodriguez (“Health Care Applications of Statistical Process Control: Examples Using the SAS® System,”, SAS Users Group International: Proceedings of the 21^st Annual Conference, 1996) illustrated several informative applications of control charts to the health care environment. One of these showed how a control chart was employed to analyze the number of office visits by health care plan members. The data for clinic E are shown in table 6E.17. The variable NVISITE is the number of visits to clinic E each month, and MMSE is the number of members enrolled in the health care plan each month, in units of member months. “Days” is the number of days in each month. The variable NYRSE converts MMSE to units of thousand members per year and is computed as follows: NYRSE represents the “area of opportunity.” The variable Phase separates the data into two time periods.

The variable can be thought of as an “inspection unit”, representing an identical “area of opportunity” for each “sample”. The “process characteristic” to be controlled is the rate of clinic visits. A u chart which monitors the average number clinic visits per is appropriate.

a. Use the data from P1 to construct a control chart for monitoring the rate of office visits performed at clinic E. Does this chart exhibit control?

b. Plot the data from P2 on the chart constructed in part (a). Is there a difference in the two phases?

c. Consider only the P2 data. Do these data exhibit control?

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Month Phase NVISITE NYRSE Days MMSE Jan. 94 1 Feb. 94 1 Mar 94 1 Apr. 94 1 May 94 1 Jun. 94 1 July 941 Aug. 94 1 Sep.94 2 Oct. 94 2 Nov. 94 2 Dec. 94 2 Jan. 95 2 Feb. 95 2 Mar. 95 2 1421 1303 1569 1576 1567 1450 1532 1694 1721 1762 1853 1770 2024 1975 2097 0.66099 37676 0.59718 28 7678 0.66219 317690 0.64608 30 7753 0.66779 7755 0.65575 307869 0.68105 317909 0.68820 317992 0.66717 308006 0.69612 318084 0.68233 30 8188 0.70809 318223 0.78215 319083 0.70684 28 9088 0.78947 319168