Appendix I: Measure Sampling Introduction Sampling is a process of selecting a representative part of the population of interest in order to estimate the organization’s performance, without collecting data for its entire population. Using a statistically valid sample, an organization can measure its performance in an effective and efficient manner. Sampling is a particularly useful technique for performance measures that require primary data collection from a source such as the medical record. Sampling should not be used unless the organization has a large enough number of cases in the measure ’s initial eligible population because a fairly large number of sample cases are needed to accurately reflect the organization’s performance. Organizations with large patient volumes may perform data collection on a sample of the total population, but sampling is not required. To obtain statistically valid sample data, the sample size should be carefully determined and the sample cases should be randomly selected such that individual cases in the population have an equal chance of being selected. Only when the sample data truly represent the whole population can the sample-based performance measure data be meaningful and useful. Guidelines for effective sampling procedures follow. Sampling may be used for all measures in the Library of Measures except for I-HBIPS2, I-HBIPS-3, I-NCS-2, I-NSC-4 and I-NSC-5. These measures cannot be sampled because they are event-based measures.
Appendix I: Measure Sampling Sample Size Requirements Hospitals selecting sample cases for Library Measures should ensure that its measure ’s or measure set’s initial patient population(s) and sample size(s) meet the following conditions:
The number of discharged cases to be sampled on a monthly basis is determined in accordance with the following sampling table: Measure Sampling Table Total Monthly Initial Patient Population Size (N ) for the Selected Measure >= 59
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