Using statistical process control charts for the continual improvement of asthma care.

BACKGROUND: Home monitoring of lung function using simple, inexpensive tools to measure peak expiratory flow rate (PEFR) has been possible since the 1970s. Yet although current national and international guidelines recommend monitoring of PEFRs via traditional run charts, their use by both patients and physicians remains low. The role of statistical process control (SPC) theory and charts in the serial monitoring of lung function at home were explored and applied to the direct care of patients with asthma. The method represents an integration of collective professional and improvement knowledge with the related disciplines of continual improvement, SPC, system thinking/system dynamics, paradigms, and the learning community/organization. CASE STUDIES: Use of PEFR control charts for four patients cared for at the Asthma-Allergy Clinic and Research Center (Shreveport, La) is described. The key to good asthma control is the ability to optimize lung function by reducing the variation between serial lung function measurements and thereby generate a safe range of function. Knowledge of the type of variation (special cause or common cause) in the system helps in focusing clinical decision making. Case 4, an 11-year-old boy, for example, shows how control charts were used to learn the effects of a new inhaled corticosteroid. Comparison of the last 14 days of baseline and the last 14 days of open label use of the inhaled corticosteroid showed an obvious improvement in actual PEFR values--which a run chart or comparison of means would have easily demonstrated. The control chart showed that this child's care process at baseline was functionally at risk for severe asthma (46% personal best) and that the effect of the new medication not only elevated the mean function but shifted the range of function from 46%-72% personal best to 78%-102% personal best. At this new range of function the patient's system of care was not capable of delivering values that are at risk for severe asthma. Unless the range of function the change in care is capable of producing is specifically quantitated, misinterpretation of improvement data can occur. DISCUSSION: Developing the concept of the PEFR control chart involved examining and challenging traditional mental models for monitoring PEFR at home in the care of asthma, acquiring a better understanding of the workings of dynamic systems and with system thinking, and sharing what was learned with patients and seeking their input.
CONCLUSIONS: The PEFR control chart employs an interesting statistical platform that enables the integration of knowledge of serial measurements and knowledge of the variation between those measurements into a tool with which to better assess the asthma care process being followed. This tool provides clinical insights, practical knowledge, and opportunities unavailable to patients and physicians via traditional PEFR charting.