Control Charts for Time In Between Asthma Events Control Charts for Time in Between Asthma Attacks By Farrokh Alemi, Ph.D. George Mason University College of Nursing and Health Science Tel: 703-993-4226 Fax: 509-756-1991 Email: [email protected] Version of Wednesday, November 06, 2002 Page 1 Control Charts for Time In Between Asthma Events Page 2 Abstract This paper provides a tutorial on use of time-in-between control charts for management of asthma. We provide the formulas needed for calculation and display of the chart. We also apply the method to 3 illustrative examples previously provided in the literature. Data show that the proposed chart describes patient conditions well and can detect important changes in patient environments. Additional research is needed to test the viability of the proposed tool in assisting asthmatic patients. Control Charts for Time In Between Asthma Events Page 3 Introduction The monitoring of Peak Expiratory Flow Rate (PEFR) is crucial to effective management of asthma. Recent national and international guidelines for care of patients recommend daily monitoring of PEFR.1 But the data collected, is rarely used by patients to help them understand their progress or by clinicians to modify treatment plans. Since neither the patient nor the clinician make extensive use of the data, it is not surprising that the effort to collect PEFR is often abandoned by the patients. To remedy this situation, a number of investigators have called for use of control charts in understanding PEFR data. 2, 3, 4, 5, 6 In a recent paper, Boggs and colleagues provide the steps for constructing an XmR chart for PEFR data.7 They provide examples of how PEFR can be charted by displaying data from three patients. We suggest an alternative method known as Timein-Between charts and which has been shown to be specially suited for monitoring rare events.8,9 In this approach, instead of directly displaying PEFR values, one measures and plots the time in between attacks. The clinician’s and the patient’s objective is to increase time until the next attack. Using the data provided by Boggs and colleagues, this paper shows how new insights is gained from patients’ management of asthma. Patient’s PEFR varies a great deal over time. Some of this variability is due to measurement errors and chance events that do not mark a change in the underlying lung function. Occasionally however, the PEFR values indicate a radical departure from usual patterns. In these circumstances, it is important to examine what might have caused the change. Control charts allow us to focus on occasions when changes in PEFR values indicate new disease patterns. Methods Patients are asked to record their PEFR value once a day. These data are used to construct the control chart. For the purposes of our study and in accordance with NHLBI suggestions, we define an asthma attack as a PEFR value that is lower than 80% of the personal best or predicted PEFR value. If the clinician wishes to monitor time to next severe attack, and in accordance with NHLBI suggestions they may define an attack as a value less than 60% of personal best or predicted PEFR value. In the control chart, we have a choice of either plotting length of well days or length of asthma attacks. The choice depends on which event is more rare. If the patient tends to have asthma attacks, then analyzing and plotting length of attack free days is best. In contrast, if patient has infrequent attacks, then analyzing and plotting length of asthma attacks is best. In either case, we are plotting the duration of the event which is relatively rare. We demonstrate the construction of the chart by examining the number of attack free days. In these charts, we plot the number of continuous days with no asthma attack against days since last visit. The steps in constructing the chart for number of attack free days are as follows: 1. Verify the chart assumptions. Check to see that attack free days are less common than asthma attack days. Check that length of attack free periods has a geometric distribution, meaning that longer periods are increasingly rare. Control Charts for Time In Between Asthma Events Page 4 2. Calculate the length of attack free periods. Score the length of attack free period. Table 1 shows how the number of continuous days with no asthma is estimated based on the values of two subsequent PEFR measurements. Table 1: Rules for counting days with no asthma attacks PEFR measure Number of days with Yesterday Today no asthma attack Start of data collection PEFR>=80% of best value 1 day Start of data collection PEFR<80% of best value 0 day PEFR>=80% of best value PEFR<80% of best value 0 day PEFR<80% of best value PEFR<80% of best value 0 day PEFR<80% of best value PEFR>80% of best value 1 day PEFR>=80% of best value PEFR>=80% of best value 1 + yesterday’s length of attack free days For example, during a week starting from Monday the client had values less than 80% of their best value on Wednesday and Thursday. In all other days, the client had normal values. In these circumstances, the count for Monday is 1 because there was no attack on this day. The count for Tuesday is 2 because it is two days without attack. The count for Wednesday and Thursday are both zero because of the attacks. The count for Friday, Saturday and Sunday are respectively 1, 2, and 3. Note that for each day of success, the number of attack free day increases until a day with an asthma attack occurs and returns the count to zero. The count remains at zero until another consecutive sequence of attack free days start. 3. Plot length of attack free periods against time. The Y-axis is the length of attack free periods. The x-axis is the time since last visit. 4. Calculate the Upper Control Limit. A patient’s lung function has improved, if number of days with no asthma attacks is higher than an upper control limit (UCL). To calculate the UCL, we need R, the ratio of days without an attack to days with an attack R= Number of days without asthma attack Number of days with asthma attack If we assume that time to the next attack has a geometric distribution (meaning that most attacks are short and longer attacks are increasingly rare), then the UCL can be calculated as: UCL = R + 3 [R * (1+R)] 0.5 5. If the duration of attack free days exceed the UCL, then the patient is getting better. The duration is beyond what can be expected from chance alone. The clinician and the patient explore what brought about these prolonged recovery with the objective of finding the cause and repeating the success. Control Charts for Time In Between Asthma Events Page 5 Source of data Data were collected from three illustrative cases reported by Boggs and colleagues. The first patient was a “36 year old female who had asthma since age 10 as a result of both allergic and non allergic causal and trigger agents.” Her care included avoiding dust mite, and cigarette smoke. She was asthmatic only once in the last 3 months and that was secondary to exertion. Table 2 provides PEFR data for 14 consecutive observation days for patient one. Her personal best was 468 L/minute during this period. Table 2: Data for Three Illustrative Patients First patient Second patient Third patient Asthma Asthma Asthma Day since visit PEFR attack? PEFR attack? PEFR attack? 1 430 No 314 Yes 120 Yes 2 380 No 411 Yes 140 Yes 3 410 No 426 Yes 100 Yes 4 400 No 432 Yes 150 Yes 5 420 No 411 Yes 260 No 6 410 No 401 Yes 150 Yes 7 460 No 371 Yes 100 Yes 8 420 No 346 Yes 120 Yes 9 460 No 361 Yes 160 Yes 10 440 No 391 Yes 300 No 11 420 No 371 Yes 300 No 12 460 No 356 Yes 275 No 13 470 No 450 No 300 No 14 460 No 396 Yes 200 No 15 529 140 Yes 16 516 170 Yes 17 536 150 Yes 18 543 150 Yes 19 543 190 No 20 536 21 550 22 520 23 516 24 521 25 557 26 550 27 506 28 529 Personal best 468 554 310 80% of the best 374 443 248 Asthma attack is defined as 80% of best personal value. Second patient care was changed after 14th day. Control Charts for Time In Between Asthma Events Page 6 The second patient was “22 years old female with a history of chronic, severe, life threatening asthma since early childhood.” She had a wide range of allergies. Table 2 shows 14 consecutive observation days for the second patient. Her personal best was 554 L/minute. After these 14 days, the patient’s medication and care changed. An additional 14 days were observed post treatment change. The third patient was 11 years old and being seen for the first time. She had asthma for 8 years and had required hospitalization 3 times in the past 12 months. Her personal best was 310 L/minute. Results Table 3 shows the calculation of the attack free periods for second and third patient. The calculation for the first patient is trivial as the patient was always attack free. Table 3: Calculation of attack free periods Days since visit 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Second Patient Attack Asthma free PEFR attack? period 314 Yes 0 411 Yes 0 426 Yes 0 432 Yes 0 411 Yes 0 401 Yes 0 371 Yes 0 346 Yes 0 361 Yes 0 391 Yes 0 371 Yes 0 356 Yes 0 450 No 1 396 Yes 0 529 No 1 516 No 2 536 No 3 543 No 4 543 No 5 536 No 6 550 No 7 520 No 8 516 No 9 521 No 10 557 No 11 550 No 12 506 No 13 Third Patient PEFR 120 140 100 150 260 150 100 120 160 300 300 275 300 200 140 170 150 150 190 Asthma attack? Yes Yes Yes Yes No Yes Yes Yes Yes No No No No No Yes Yes Yes Yes No Attack free period 0 0 0 0 1 0 0 0 0 1 2 3 4 5 0 0 0 0 1 Control Charts for Time In Between Asthma Events 28 Personal best 80% of the best 529 554 443 No Page 7 14 310 248 For the first patient, all PEFR values were above 80% of her personal best. This patient had no asthma attacks during this observation period and therefore no change in patient’s care is indicated. For this patient because attack days are more rare than well days, one would plot the number of consecutive asthma attack days. The second patient is a different story. During the first 14 days, the patient had numerous days where his PEFR was below 80% of personal best. For this patient an attack free day is quite rare. Therefore we plot the number of attack free days against days since office visit. Figure 1 provides the findings. Consecutive attack free days Figure 1: Observation of Second Patient for 14 days 2 1 Upper control limit 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Days since office visit Consecutive attack free days Note that there are no days until the 13th day in which the patient does not have a mild asthma attack. The control limit is calculated from the ratio of attack free days to attack days. For the second patient’s first 14 days, this ratio is 1/13 = 0.08. The UCL is calculated as 0.08 + 3 * (0.08*1.08)^0.5 = 0.94. Note that the single day in which the client does not have an attack is a statistical Figure 2: Recovery of Second Patient significant event. The after intervention clinician and the patient need to review why on this 16 day the patient did not have 14 Before an attack. After 12 intervention intervention After 14 10 observation days, the 8 6 second patient’s care was 4 modified significantly. 2 Figure 2 shows the UCL 0 resulting recovery of the 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 patient. As can be seen, the Days since visit patient had no attack for Control Charts for Time In Between Asthma Events Page 8 the next 15 days post treatment. Throughout the time period after the intervention, the length of attack free days exceeded the UCL. Therefore, after the intervention that patient had improved beyond what could be expected by mere chance. The third patient illustrates a mix of well days and asthma attacks. The patient had asthma attacks the first four days. Recovery started on the 5th day but the length of recovery was not statistically significant and therefore could have been due to random chance events. The recovery was statistically significant from 9th through the 13th day. The patient and the clinician explored what brought about this success. During this period the patient was visiting her aunt and was away from dog, mite and smoke irritants in her home environment. After the 13th day, the patient returns home and so do the asthma attacks. 5 4 3 Upper control limit 2 1 19 17 15 13 11 9 7 5 3 0 1 Consecutive attack free days Figure 3: Recovery of Third Patient Days since visit Conclusions This paper provides a brief tutorial on use of time-in-between control charts in monitoring asthma attacks. The approach provided here provides a viable method of analyzing PEFR values. It has the advantage of providing a visual display of data. The control limit allows the clinicians and the patients to ignore random variations and focus on periods of time when real changes in underlying patterns of asthma attacks are occurring. The rules for construction of the control chart are relatively simple and can be taught to patients. In addition, web based and medical record based tools are also available for analyzing control charts (see for example http://www.rapidimprovements.com). Finally, clinical laboratories can construct control charts for patients. These possibilities encourage additional work on the use of control chart for asthmatic patients. Additional research is needed to compare the proposed approach to XmR charts both in terms of accuracy in detecting changes in patient outcomes as well as ease of use and understanding by patients. It is important to study whether patients who use control Control Charts for Time In Between Asthma Events Page 9 chart methodologies have more effective communications with their clinicians and can more easily get to root environmental causes of their asthma. But perhaps most important, research is needed to verify that patients who use control charts obtain greater relief from asthma attacks than those who do not use control charts. Appendix A: Data Collection Tool Patients often need a well-structured task for collecting and charting the data. The following are two forms for data collection and charting. Control Charts for Time In Between Asthma Events Page 10 Form for Patients with Infrequent Asthma Attacks Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Mild Attack? Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No PEFR Attack length Duration of asthma attacks 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 1 2 Best PEFR = 80% of best PEFR = 3 4 5 6 7 8 9 1 0 Days since last office visit 1 1 1 2 Rules for scoring: Score each PEFR less than 80% of your best personal value or predicted value as an attack. Put a zero for the length of attacks whenever a well day occurs. When attacks occur over consecutive days, add “1” to previous day’s total until a well day occurs, in which case you start the count back at zero. Following table shows how to score the length of attacks: Yesterday No data No data No Attack Attack No Attack Attack Today Attack No Attack No Attack No Attack Attack Attack Duration of attack 1 day 0 day 0 day 0 day 1 day 1 + yesterday’s length of attack Plot the duration of attack in the chart area to the right. To set your upper control limit, calculate the ratio of attack days to well days. The control limit is calculated as: Limit = Ratio + 3 * SQRT [Ratio *(1+ Ratio)] Values that exceed the control limit indicate significant deterioration of your asthma. When this occurs explore what may have caused this change. Bring this chart to your next clinic visit. Bring this chart to your next clinic visit. 1 3 1 4 Control Charts for Time In Between Asthma Events Page 11 Form for Patients with Frequent Asthma Attacks Day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 PEFR Mild Attack? Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Yes | No Consecutive well days # of well days 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0 1 2 Personal best PEFR = 80% of personal best = 3 4 5 6 7 8 9 1 0 1 1 Days since last office visit Rules for scoring: Score each PEFR less than 80% of your best personal value or predicted value as an attack. Put a zero for the number of well days whenever an attack occurs. When a well day occurs, add “1” to previous days number until an attack occurs, in which case you start the count back at zero. Following table shows how to score the number of days between attacks: Yesterday No data No data No Attack Today Attack No Attack No Attack Attack No Attack Attack No Attack Attack Attack Number of well days 0 day 1 day 1 + yesterday’s length of well days 1 day 0 day 0 day Plot the number of days between attacks (well days), in the chart area to the right. To set your limits, calculate the ratio of well days to attack days. The control limit is calculated as: Limit = Ratio + 3 * SQRT [Ratio *(1+ Ratio)] Values that exceed the control limit indicate significant improvement in your asthma. When this occurs explore what has changed to cause such an improvement. 1 2 1 3 1 4 Control Charts for Time In Between Asthma Events Page 12 References 1 2 3 4 5 6 7 8 9 Expert Panel Report. 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