Monitoring patients using control charts

Interesting collection of studies using control charts to monitor measures from individual patients.


Tennant, R., Mohammed, M. A., Coleman, J. J., & Martin, U. (2007). Monitoring patients using control charts: a systematic review. international journal for quality in health care, 19(4), 187-194.


Authors/Year/Sample size Results
Hayati et al. [18], 2006 (n = 45) Control charts, based on peak flow readings taken at work had a sensitivity of 86% and specificity of 88% compared with a gold standard measure (Specific Inhalation Challenge, SIC). 2/3 individuals with a positive diagnosis based on SIC had lower peak flow readings at work than at home, suggesting potential errors with the gold standard measure
Alemi and Neuhauser [19], 2004 (n = 3) Control charts for all three asthmatic patients in the study showed special cause variation on at least one occasion. One patient showed no attacks after changes in their asthma care regime. One patient showed special cause variation (a decrease in attacks), which was associated with a reduction to exposure to irritants at home
Boggs et al. [20], 1998 (n = 3) Patient 1: Peak flow readings ranged between 92% and 76% of personal best. The patient’s control chart was in statistical control: future peak flow readings likely to continue to fall within a safe range Patient 2: Peak flow readings ranged between 86% and 54% of personal best, indicating that the patient was at high risk of severe asthma. Changes in the patient’s treatment regime brought readings into statistical control Patient 3: Peak flow readings ranged between 17% and 101% of personal best, indicating that peak flow readings were not in statistical control. Changes in the patient’s treatment regime brought readings into statistical control
Gibson et al. [21], 1995 (n = 35) Exacerbations identified using 9 action points for identifying exacerbations (3 based on control chart exceedences, 6 based on action points taken from published guidelines) were compared with exacerbations identified by clinical assessment (using retrospective data collected by patients). The two methods with the highest sensitivity and specificity (peak flow rate < 80% of personal best, 2/3 successive measures between 2 and 3 lower sigma) were compared. True positive rate: peak flow rate < 80% = 88%, control chart (2/3 successive measures 2–3 lower sigma) = 91% (P = NS). False positive rate: peak flow rate < 80% = 47%, control chart (2/3 successive measures two- to three-sigma) = 23%. (P = 0.002). An action point of a single measure > 3 lower sigma detected 72% of exacerbations before they were clinically identified. An action point of 2/3 points 2–3 lower sigma identified 19% of exacerbations earlier. An action point of 4/5 points between 1 and 2 lower sigma identified 60% of exacerbations earlier
Hebert and Neuhauser [22], 2004 (n = 1) Patient 1: In the first period of observation, mean systolic blood pressure was 131.1 mmHg (Upper and Lower control limits 146.3 and 115.9 mmHg, respectively). In the second period of observation, the control chart indicated a significant drop in blood pressure (mean = 126.1 mmHg) (Upper and Lower control limits 143.3 and 109, respectively). Qualitative interviews showed a high level of patient acceptability (satisfaction in observing improvements in blood pressure, improved knowledge of own blood pressure measurements)
Solodky et al. [23], 1998 (n = 3) Case-series: In both patients, all seven systolic blood pressure readings taken after treatment fell below the mean for the seven pre-treatment values Case-study: The control chart for the period before treatment showed a mean blood sugar level of 130 mg/dL: upper control limits were exceeded on two occasions. The control chart for the period after treatment showed a drop in mean blood sugar levels to 97: upper control limits were exceeded on two occasions
Piccoli et al. [24], 1987 (n = 38) CUSUM charts of serum creatinine following kidney transplant had a sensitivity of 85% and a specificity of 94% in identifying positive or negative changes in renal function compared with gold standard measures (full clinical assessment). There was no significant difference in the time take to detect a change in renal function using either detection method