Time to Adverse Events |
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This topic examines control charts that require only 1 observation per time period. These include time-between and Tukey control charts. Since there is one observation per time period, you can easily apply these methods to analysis of your own habits. Want to know if you have really lost weight or kept up with exercise, use the control charts this week to examine your own data. We continue as before to also look at real data from hospitals. Now we look at rare events such as wrong side surgery or medication errors. We also help you think through which chart is appropriate with what kind of data. Assigned Reading
Presentations
AssignmentsInstruction for Submission of Assignments: Assignments should be submitted directly on Blackboard. In rare situations assignments can be sent directly by email to the instructor. Submission should follow these rules:
Question 1: We have received a set of comments over time on the web. Check if we have improved? Please note that there are no pre- and post intervention periods and therefore control limits must be calculated from the entire period. Data► Answer► Ujwala's Teach One► Question 2: The following data show the speed with which Alabama Medical Center's Emergency Room provides a patient who has fractured long bone with pain medication. Examine if the organization has been able to reduce the response time to less than 73 minutes? Data► Answer► Aras's You Tube►
Question 3: A control chart requires independent repeated observations over time. In addition, based on other factors, different charts are appropriate. For each of the following conditions, select a measure in Hospital Compare and describe its denominator and numerator. You can find measure definitions under CMS's definition of measures. Select hospital compare program and focus on measures used in hospital compare program. Then, identify one or more control charts that are appropriate. If more than one control chart is appropriate, the usual approach is to try both charts and select the chart with tighter controls (i.e. control limits with smaller absolute difference): Which chart is right?► CMS's Measures►
Question 4: In the following data, we have tracked whether 352 infants in our pre-natal clinic eventually showed for various services in post-natal care. Each clinic is reporting if these 352 patients showed at their clinic and on what dates. Given these data, calculate the referral rate to each clinic. Has the rate of days-of-referrals to neurology clinic changed over time (does the control chart show points outside the limit)? In analyzing these data you may wish to use combination of if and match commands within excel. The command may look like =if(match(A2, C:C, 0), 1,0). This command says the value that should be matched is in A2, the look-up array is in column C, and 0 indicates that it should be exact match. The data provide dates of visits. Data► Answer► Question 5: Using the data from previous question, what is the daily probability of referrals to each of the ultrasound, neurology and combination of the two clinics. To calculate the daily probability of a visit follow these steps:
Here is what I calculated as the daily rates of referrals to neurology, ultrasound, and combination of the two clinics:
Question 6: In the past 3 years, there have been the following incidences of privacy violations: A disgruntled employees sold information on May 11 of year 1. Another disgruntled x-employee sold password to the system on Dec 12 of year 3. There have been four incidences of clinician discussing patient information in social gathering on the following dates: December 5 year 2, January 25 Year 3, May 27 year 3, and September 1 year 3. Days of incidences of any other types of privacy violations were May 11 year 1, Nov 22 year 2, Dec 27 year 3. Which types of privacy violations are more frequent? Use Excel formulas to calculate the average days to event and daily probability of the event. Answer► More |
Copyright © 1996 Farrokh Alemi, Ph.D. Most recent revision 01/08/2020. This page is part of the course on Statistical Process Improvement, this is the lecture on Introduction to the Course. |