The Role of Statistical Process Control (SPC) in Healthcare

Statistical Process Control in Healthcare

The practices of quality improvement stands for a leading technique to the most challenging, and essential of controlling organizational change. Consequently, statistical process control is the main approach to quality improvement. SPC was created in the 1920s by Walter Shewhart, a physicist, with intention of enhancing industrial manufacturing. The approach was transferred to healthcare, initially in the laboratory environment and later applied into patient care, together with other QI approaches . This paper reviews the role of Statistical Process Control in non-technical application in this case focusing on healthcare organizations. Statistical Process Control is highly used in healthcare organizations for quality improvement. Therefore, the paper will center of the use of SPC in quality improvement in the healthcare environment.

Read also Appropriate Strategies for Administering the Quality Improvement and Risk-Management Processes within a Healthcare Delivery System

Definition Of Statistical Process Control With Regard To Quality Improvement

Statistical process control refers to a set of techniques, and a strategy for continuous improvement of outcomes, processes, and systems. The SPC technique is founded on learning via data and contains its foundation in the variation theory which involves understanding special and common causes. The strategy of SPC includes the concepts of prediction, analytic study, process thinking, capability, prevention, stability, stratification and prevention. SPC includes planned experimentation, methods of data collection, and analytic study. The basic tools employed in SPC include flow diagrams, control charts or Shewhart charts, scatter diagrams, run charts, pareto analysis, histograms and frequency plots. In healthcare environment, the phrases statistical quality control and statistical process control are frequently employed interchangeably. However, they former is employed to describe a wider organizational method of quality management which evolved into the total quality management concept.

Variations In Healthcare

Natural or inherent variation will always be identified in different production processes despite the effort employed to ensure consistency. Similarly, healthcare experiences these variation in its normal processes. Repeated evaluations of similar parameter frequently result to slight variation in healthcare organizations. Most variations demonstrated by these processes can be categorized into one of the two classes known as atypical or unnatural and natural or typical variation. The natural variability refers to systematic inherent variation as a regular portion of the process. The natural variability is regarded as the cumulative impact of a number of small, significant causes. These causes are known as common cause, such that a process working in the common cause presence is regarded to be in statistical control. Natural variability common causes instances in healthcare include varying patients behaviors, patients’ physical condition and weight, hospital census, appointment delay time and access satisfaction, re-measurement of blood sugar level of a patient, and waiting time of a department .

Nevertheless, there are other forms of variation that are generally huge and normally stand an unacceptable process performance degree in healthcare. These variations are not initiated by common causes, and thus, they act as a proposition that there is fundamental change in processes either negatively or positively because of distinctive unnatural variability which should be traced to its root cause to ensure quick intervention. These are referred to as unnatural variability occurring due to special causes. Process operation in special cause presence is considered to be out of statistical management. These unnatural variation as a result of special control include population demographic changes, equipment failure, physiology of a patient, new health personnel, degradation of skill, clinical procedures changes. SPC, similar to other statistical technique assists in teasing out inherent variation in different processes. This is attained via the use of SPC tools that include tally chart of check sheet, control chart, pareto diagram, flowchart, cause-and-effect diagram, and scatter diagram.

One SPC advantage over other statistical techniques such as classical approaches is that SPC technique integrate the classical statistical techniques rigor that are characteristically founded on ‘time static’ statistical evaluations with pragmatic improvement time sensitivity. By combining the statistical significance power tests with graphs chronological analysis of summary data as they are produced, SPC manages to detect trends and changes into moderately simple graphical and formulae displays which can be easily employed by non-statisticians [3].

Statistical Process Control Tools

The three most popular SPC tools employed in healthcare organization include the confidence chart, time chart and control chart. A time chart is employed when contrasting a single person, department or unit for varying periods. Confidence chart is highly applicable when contrasting different practices, units or individuals over a single period of time. Control chart on the other hand is employed for the control and study of repetitive processes.

Control Chart

Control chat contains two parts which include measurement series plotted in the template and time order. It contains three horizontal lines known as central line, characteristically median or mean, the lower line known as lower control limit (LCL), and the upper line known as the upper control limit (UCL). The LCL and UCL values are not arbitrarily set by the person making the chart, though they are normally computed from data inherent variation. For effective control charts application, a firm standard distributions understanding employed for the common variation causes is important. Control chart is of multivariate type and univariate type. Univariate chart is employed to monitor process using one quality aspect. Multivariate chart on the other hard is employed to monitor process containing two or more quality aspects which are normally correlated. Control chart has highly been employed in different manufacturing process due to their simplicity. This simplicity have made them to be frequently recommended in hospital performance improvement and monitoring. Their main advantage is that they provide a simple graphical manner used to display process outcomes and behavior, to evaluate fata chronologically as a series of time. There are various forms of control charts which include Shewhart Chart that contains u-chart, number defective chart-c-chart, np chart and proportion defective charts-p-chart . Below is a number defective chart C, demonstrating a cancer surgical case that is out of control:

 Confidence Charts

Confidence chart refers to an ordered data sequence with a center line, computed by use of the data mean, drawn horizontally across the chart. The lower and upper control limits are included in the chart, the impact being to draw a trombonogram that highlights special and common data variation cause. Confidence chart allows the process levels monitoring and variation type identification in a process at a given time period. Confidence chart has extra power for detecting healthcare data special cause variation. This power is obtained from extra rules related with control limits. Generally, these limits are agreed locally and are usually set at 3 x stigma. Thus confidence charts are very simple graphical instruments which allows the performance monitoring of the current process and are structured to identify the variation type existing in a process. Below is an example of a confidence chart demonstrating upper and lower confidence limit.

Time Chart

It contains timer-ordered data sequence with a horizontally drawn center line across the chart. It allows process level monitoring and variation type identification in processes at a given time period. A good example of time chart in hospital environment is provided below:


Statistical Process Control has been employed to improvement of healthcare in an extensive range of specialties and settings, at diverse organizations levels and unswervingly by patients, by use of different variable types. Based on various evaluations, SPC can be regarded as a versatile and powerful tool for controlling variation in healthcare via quality improvement. To enhance healthcare organization performance, individuals and organizations need the ability to design, improve, and control processes, and then monitor the impacts of this work improvement on the results. Statistical Process Control document and facilitate improvement of healthcare process, particularly in assisting to establish the interventions impacts intended to enhance care. It might permit early reporting on performance process, and might be employed to evaluate the requirement for a summative assessment prior to the evaluation process. However, its application in the healthcare sector also has some limitations. Some of these limitations include uncertainty about the methodological quality of various primary researches. Nevertheless, effective application of Statistical Process Control makes it a versatile toll that can permit stakeholders to enhance health of patients and manage healthcare changes.

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