How to Control Your Blood Sugar Using Lean Six Sigma - GoLeanSixSigma.com

Whether at work or at home, Lean Six Sigma can help you solve problems efficiently and effectively. Here’s an example of a Lean Six Sigma project outside of work where blood sugar is reduced and controlled using the DMAIC methodology.

Operational Definition(s): What to Know Before Getting Started

A1C

A1C is the measure of the average blood glucose control over the past 3-4 months; the ideal range is <6%. Tests are conducted by a lab in conjunction with a health care provider.

Blood Glucose Level

Blood Glucose Level is the measure of the amount of glucose or sugar in the blood at the time of testing. They are usually self measured with a blood glucose meter. Normal pre-meal range is 70-130 mg/dl.

Here’s a chart from the American Diabetes Association which shows normal levels.

Control Blood Sugar Using Lean Six Sigma - A1C and Blood Glucose Levels

Comparison of A1C and Blood Glucose Levels

Exercise Calories

Exercise Calories are being defined as a measure of the calories expended in day in excess of a sedentary day. Although the measurement is subjective due to the various potential calorie calculators available on the internet, the data is being used to determine a daily or relative comparison and is not intended to be absolute.

The Glycemic Index

The glycemic index of food is a ranking of foods based on their immediate effect on blood glucose levels. Carbohydrate foods that breakdown quickly during digestion have the highest glycemic indexes. Their blood sugar response is fast and high. Carbohydrates that breakdown slowly, releasing glucose gradually into the blood stream, have low glycemic indexes.

Type II Diabetes

Type II Diabetes is a condition where either the body does not produce enough insulin or the cells ignore the insulin. Insulin is necessary for the body to be able to use glucose for energy. When you eat food, the body breaks down all of the sugars and starches into glucose. These are the basic fuel for the cells in the body. Insulin takes the sugar from the blood into the cells.

 

Desired Blood Sugar Levels

Desired Blood Sugar Levels

 

Project Results Summary: Controlling Blood Sugar

Project Wins

  • Improved daily average blood sugar from 205 mg/dl to 125 mg/dl.
  • There was a 10 lb weight loss, and a loss of 2” in pants size, but more significant is an overall increase in energy and an ability to slightly relax dietary restrictions.
  • The improved blood sugar measurements will not, due to statistical history, make a major change in the A1C reading for another 2 months; the measurement is a median of the past 120 days. A confirming A1C test is scheduled for the end of March. Baseline A1C was 8.1, the current is 7.6 and the desired is <6. Based upon current data and trends the expected result should be a measurement of 5.9.

DMAIC Approach

  • Reviewed Voice of Customer (VOC) and researched various methodologies on how to best control blood sugar with Type II diabetes.
  • Utilizing past A1C and glucose meter measurements; a baseline was established.
  • Analysis was performed on the data; the PM readings were generally lower than the AM readings.
  • Further research ensued with the determination that increased activity would be best method for Blood Sugar control.
  • The proposed solution was to specifically increase muscle activity by means of weight training.
  • To maintain the results it is necessary to continue the muscular activity of 20 minutes of training, 5 days per week. They do not need to be at gym weight training but could be at home exercises of pushups, lunges and crunches.

Context

It is critical to control high blood sugar levels to reduce the potential long term health risks. These can include; heart disease, kidney damage, nerve problems and loss of vision.

  • Project Timing: 60 day analysis
  • Start Date: 11/16/14
  • End Date: 1/15/15

Project Details (DMAIC Process): Controlling Blood Sugar

Define Phase

Business Case

Over the past year controlling Type II diabetes has been attempted with medications and changing diet, also by avoiding high glycemic index foods. These have been unsuccessful in controlling blood sugar levels to the acceptable range. Developing a long term alternative to increasing medications is highly desirable. Maintaining blood sugar levels is necessary to reduce long term health risks.

Problem Statement:

Current blood sugar levels range from 200-220, they should be less than 135

Goal Statement:

Increase physical activity to reduce average blood sugar levels to 100-135 or an A1C of <6 by the end of 2014.

Control Blood Sugar Using Lean Six Sigma - Threats & Opportunities Matrix - GoLeanSixSigma.com

 

In Scope

  • Increase daily activity by going to the gym regularly
  • Continue after meal walks
  • Continue to avoid high glycemic index foods
    • Include all data points, specifically Thanksgiving, Christmas and New Years

Out Of Scope

  • Increase medications
  • Additional and more strict dietary changes
    • Avoid holiday meals and parties

Control Blood Sugar Using Lean Six Sigma - SIPOC - GoLeanSixSigma.com

Measure Phase

  • Daily data for September 2014 was unavailable. The October 15th 2014 A1C test had a measurement of 8.1; indicating the prior 2-3 month Blood Sugar average to be 210. This average will be used as the baseline data for September 2014.
  • Blood Sugar Level data for October 2014 was obtained from the historical register of a glucose meter. The data was logged onto a data collection sheet to capture the blood sugar level along with the date and time of measurement.
  • Data was filtered by rounding to the nearest multiple of 5, this was necessary to create a baseline of meaningful data. The exact values were not critical as the data only needs to be relative to the desired goal.
  • Baseline measurements indicated the VOC goals were only being meet 8% of the time.
  • An A1C test was taken December 7th, the results were 8.3. After consultation with the doctor it was decided this test would be ignored due to the statistical nature of the A1C being a 120 day median. Not enough time or data would be available to offset the prior statistical median. It was decided a more accurate measurement of the process improvement would be available at the end of March 2015. The test result was a validation of the decision to use the October 15th test for the basis of the September data.

Baseline Data Collection Form

Control Blood Sugar Using Lean Six Sigma - Baseline Data Collection Form - GoLeanSixSigma.com

Analyze Phase

Data Analysis indicated a completely random pattern when compared by days. Delving deeper into the data it was discovered the AM readings were more consistent, but with a higher average reading of 199. The PM readings averaged 167, but the spread was very inconsistent. There was enough evidence to show that daily activity did lower the PM Blood Sugar Level.

The following charts were used to analyze the data and support the described tendencies:

  • The histogram indicates the process essentially out of control.
  • A scatter plot of the “data by day” displayed no apparent trend or relationship.
  • A scatter plot of the “data by the hour of the day” indicated some trends.
  • A Box and Whisker plot of the data comparing the AM and PM readings revealed the AM readings were more consistent. The PM plot indicated there was a potential for a successful improvement plan.

Baseline Data Charts

October 1 to November 15
Control Blood Sugar Using Lean Six Sigma - Baseline Data Charts (Histogram & Scatter Plot) - GoLeanSixSigma.com

Histogram & Scatter Plot

Control Blood Sugar Using Lean Six Sigma - Baseline Data Charts (Scatter Plot & Box and Whisker Plot) - GoLeanSixSigma.com

Scatter Plot & Box Whisker Plot

 

Improve

A simple root cause analysis on the differences between the AM and PM readings indicated that activity, or more specifically the amount and type of activity, had a direct effect on the Blood Sugar Level, and therefore activity would be the best and most measurable option in improving the process.

Description of the process change:

  • The Blood Sugar Levels were measured in the AM and PM prior to meals, thus eliminating the variable effects the type of meals could impart on the measurements.
  • Increasing the daily activity by 400-500 calories per day, this equates to approximately 30-40 minutes of exercise, exercise included 20-30 minutes on a bike, treadmill or elliptical with a heart rate of at least 150 BPM, plus 10- 20 minutes of resistance weight training.

SIPOC – Process Improvement

Control Blood Sugar Using Lean Six Sigma - SIPOC Process Improvement - GoLeanSixSigma.com

Improvement Data Charts

Control Blood Sugar Using Lean Six Sigma - Improvement Data Charts Process Improvement - GoLeanSixSigma.com

Control Phase

After the initial 30 days there was a trending towards the goal. A decrease in the amount of exercise was attempted to determine if the trend would be maintained with less effort. After this initial test, it was determined that 5 days of exercise per week was required, allowing for two days of rest to maintain the blood sugar levels at the desired range. The rest days should not be back to back.

  • The initial 30 days were inconsistent in terms of results, but a trend of lowered blood sugar was noticed on days following when the activity included weight training.
  • The second 30 days show a significant improvement in terms of trends and consistency in the lowering of the blood sugar levels.
  • There was one data point outside the desired range, Jan 10th PM reading. It was due to a late afternoon meal that did not follow the requirement of being low glycemic.
  • Specific habitual changes needed to be altered.
  • Exercise sessions were most beneficial if they were later in the day, either before or after the evening meal.
  • Exercise sessions needed to include 20 minutes of strength training, either weights or at home resistance training, i.e. pushups, sit-ups. These need to follow some type of cardio to increase the heat rate to the “target” level.
  • The need to continue a glycemic appropriate diet is still crucial to maintain the desired results.
  • Days with high activity can replace a day’s exercise session: such as walking a round of golf, extended periods of yard work, heavy house/garage cleaning or similar activities.

Next Steps

  • There are various methods to control Blood Sugar Levels. The most common are the types of food consumed, exercise and medication. The simplest option is with medications. The problem with this method is it takes a long period of time to determine the correct medications and doses. The dependence on medications is undesirable and can be costly. A combination of medications and diet are very effective but these lead to lifestyle changes that are at times difficult to maintain. Fast food and quick meals are not often glycemic appropriate meals. The most difficult and perhaps the best method is a program that includes medications, diet and exercise. The inclusion of exercise allows the body to transfer sugar from the blood to the muscles, increasing the body’s insulin-sensitivity. This could potentially allow for the reduction in medications and dietary restrictions.
  • The next steps in the process are to maintain the plan and obtain a desired result to the March 2011 A1C test. It is the goal to continue the effort to remove the need for dietary restrictions and medications. The viability and level of these reductions will not be known for another 4 months.

Are you taking control of your health with Lean Six Sigma? We want to hear how! Tell us in the comments below.

Maintain your good health! Register for Green Belt Training & Certification today to get all the tools you need to improve and control your health! 

Tracy O'Rourke

Tracy is a Managing Partner & Executive Advisor at GoLeanSixSigma.com. She is also a Lean Six Sigma Green Belt Instructor at University of California San Diego and teaches in San Diego State University’s Lean Enterprise Program. For almost 20 years, she has helped leading organizations like Washington State, Charles Schwab and GE build problem-solving muscles.