We observed a lack of consistency in the application of methods for computing MID or MCID for generic and disease-specific HRQoL measures .
The anchor-based method yields conservative estimates of MID or MCID , compared to the distribution-based method .
OBJECTIVES The objective of the study was to assess the usability of minimal important difference ( MID ) and minimal clinical ly important difference ( MCID ) for measuring meaningful changes in disease-specific and generic health-related quality -of-life ( HRQoL ) outcomes in patient-centered care .
Effect Sizes for Interpreting Changes in Health Status
Health status measures are being used with increasing frequency in clinical research . Up to now the emphasis has been on the reliability and validity of these measures . Less attention has been given to the sensitivity of these measures for detecting clinical change . As health status measures are applied more frequently in the clinical setting , we need a useful way to estimate and communicate whether particular changes in health status are clinical ly relevant . This report considers effect sizes as a useful way to interpret changes in health status . Effect sizes are defined as the mean change found in a variable divided by the st and ard deviation of that variable . Effect sizes are used to translate “ the before and after changes ” in a “ one group ” situation into a st and ard unit of measurement that will provide a clearer underst and ing of health status results . The utility of effect sizes is demonstrated from four different perspectives using three health status data sets derived from arthritis population s administered the Arthritis Impact Measurement Scales ( AIMS ) . The first perspective shows how general and instrument-specific benchmarks can be developed and how they can be used to translate the meaning of clinical change . The second perspective shows how effect sizes can be used to compare traditional clinical measures with health status measures in a st and ard clinical drug trial . The third application demonstrates the use of effect sizes when comparing two drugs tested in separate drug trials and shows how they can facilitate this type of comparison . Finally , our health status results show how effect sizes can supplement st and ard statistical testing to give a more complete and clinical ly relevant picture of health status change . We conclude that effect sizes are an important tool that will facilitate the use and interpretation of health status measures in clinical research in arthritis and other chronic diseases
We observed a lack of consistency in the application of methods for computing MID or MCID for generic and disease-specific HRQoL measures .
The anchor-based method yields conservative estimates of MID or MCID , compared to the distribution-based method .
OBJECTIVES The objective of the study was to assess the usability of minimal important difference ( MID ) and minimal clinical ly important difference ( MCID ) for measuring meaningful changes in disease-specific and generic health-related quality -of-life ( HRQoL ) outcomes in patient-centered care .