Patient X reduces his chances of a second heart attack using change analysis

Mr Christopher Ude Mr Christopher Ude

Cardiovascular disease (CVD) is one of the leading causes of death in Australia. In 2015, CVD resulted in 490,000 Australians being hospitalized. In 2016, CVD claimed the lives of 43,963 Australians, many of which could have possibly been prevented.

High blood pressure (hypertension), is one of the main causes for CVD. Given that hypertension generally has no symptoms, diagnosing and managing it, is somewhat difficult. In 2014/15, 34% of Australians were diagnosed with hypertension, out of which 68% had uncontrolled or unmanaged hypertension.

How can one measure hypertension when there’s no symptoms? Feeling well is no indicator! Blood pressure readings vary substantially (even minute to minute), hence an ‘occasional’ blood pressure reading at the medical clinic ‘may not’ accurately depict the true picture.

The answer is self-monitoring! Whilst many argue it can create a degree of anxiety, others argue that by knowing, one is in a better position to react, thereby potentially improving state of health, which could just prove to be ‘life-saving’.

Self-monitoring requires taking blood pressure readings and then using statistical analysis to intepret meaning

Whenever data is collected, statistical analysis is used for extracting the knowledge required to formulate decisions, an approach adopted by the manufacturing industry. Hypertension management is no exception. After all, when stripped down, a typical blood pressure reading is data.

Blood pressure is measured in ‘numeric’ values, displaying 3 readings: Systolic, Diastolic and Pulse. Systolic and diastolic have boundary limits in which blood pressure needs to be controlled within, otherwise health could be compromised. Once there is enough data over time, SPC (statistical process control) can be applied to uncover trends, detect changes, identify causes for changes, and more.

The best way to describe the effectiveness of SPC in hypertension management and demonstrate how it can used as a health warning, is through a case study.


The following is about a 62-year-old heart patient, whom was alerted to dangerously high blood pressure (despite taking BP medication) using Change Analysis, and how these insights were used in conjunction with the assistance of his doctor to identify a medication in-efficiency.

From here-on, the patient will be known as Patient X.

In 2009, Patient X endured a heart attack, requiring a double by-pass surgery along with a couple of heart valve replacements. Medical practitioners concluded that severe hypertension was a contributing factor to his heart attack, amongst others.

Patient X was put on BP medication and was asked to make significant lifestyle adjustments. Patient X took his medication, adopted a healthier lifestyle and was back to living again.

A visit to the local pharmacist however changed things. The pharmacist was offering FREE blood pressure checks to customers. Out of curiosity, Patient X checked his blood pressure. It was 180/110. Patient X was advised by the pharmacist to visit his doctor, which when he did, the doctor obtained a reading of 145/90. The doctor was not concerned and said just continue with the medication.

Being conscientious, Patient X purchased a blood pressure unit. He took readings everyday for 2 weeks and noticed his blood pressure was variable. One minute it was high, next it was low. He could not make ‘heads or tails’ out of it. His son-in-law who works in quality assurance suggested Patient X use Change Analysis to interpret his readings. The intent was for Change Analysis to provide a statistically significant profile of Patient X’s blood pressure, generating an underlying trend in the form of a step, taking BP variability into account.

Referring to Figure 1, it was confirmed through Change Analysis, that Patient X’s blood pressure was dangerously high, even with medication. The Change Analysis also showed the variability of the individual results.

Shewhart chart demonstrating the issues with spc theory Figure 1: Patient X's Systolic and Diastolic readings plotted on a change analysis

Patient X visited his doctor and shared his Change Analysis profile. The doctor examined the Change Analysis and concluded it could be due to Patient X’s medication dosage. The doctor changed the medication dosage and asked Patient X to re-visit with the Change Analysis a week later.

Referring to Figure 2, the underlying step reduced, reflecting the change in dosage. However, it was not significant enough. The doctor examined the change and concluded that the medication may be incorrect. Patient X was prescribed new BP medication.

Shewhart chart demonstrating the issues with spc theory Figure 2: Decrease in blood pressure due to medication dosage change

Referring to Figure 3, the new medication had the desired effect. Within a few days, a further reduction in blood pressure was depicted, which continued to lower again (evident in step 3) to acceptable levels.

Shewhart chart demonstrating the issues with spc theory Figure 3: Decrease in blood pressure due to new medication

Through Change Analysis Patient X and his doctor were able to detect a medication in-efficiency which was failing Patient X. Through a change in medication, Change Analysis confirmed the desired effect, thereby reducing the risk of a second heart attack. Today Patient X is living a healthy life and has his hypertension under control using Change Analysis as his tool of insight. He regularly visits his doctor with his Change Analysis profile.

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