Received date: 22 April 2013; Accepted date: 30 April 2013
This is the second in a series of articles about the science of quality improvement. Many quality improvement initiatives are aimed at improving the process of care and ensuring that high-quality care is delivered reliably. In this article, we explain why it is important to understand healthcare processes in order to improve them and how this can be achieved. We explain the use of logic models todetermine what information to collect (from surveys, interviews, direct observations and other sources) and how to analyse this information (using techniques such as process maps, critical-to-quality trees, driver diagrams and cause-and-effect diagrams)to design more reliable and higher quality healthcare processes.
general practice, primary care, processes, quality improvement, reliability
This is the second in a series of articles on quality improvement tools and techniques, in our primer for quality improvement following on from the article in the previous issue on ‘Frameworks for improvement’. Many quality improvement methods in healthcare are directed at improving processes and increasing reliability in order to consistently deliver high-quality care. To some, the idea of ‘process’ may sound overly mechanistic; it may resemble the notion of industrial processes in manufacturing and the conveyor belt or a factory line. Linked to this is the implication that reliability and consistency means treating everyone the same, whatever their needs. These are basic misconceptions: a misunderstanding of what is meant by ‘process’ and by ‘reliability’.
If we look more deeply into these ideas we see that the underlying principles are the same whether for manufacturing or service industries, including health, an idea that Deming understood and explained over half a century ago. As we examine the idea of processes and reliability, we will draw on work from the intellectual giants of the quality improvement movement includingWEdwardsDeming, Joseph Juran and more recently Davis Balestracci.
There are some basic assumptions here which need to be clarified: quality healthcare is that which is effective, safe and improves patient experience. All work is a process and processes can be defined as a series of activities or inputs that lead to outputs: inputs include people, work methods, equipment, materials, environment andmeasurements. Understanding and improving processes can reduce inappropriate and unintended variation. We should examine these ideas in turn.
Everything we do involves a process. Healthcare processes are the steps that are taken or involve, either explicitly or implicitly, whether sequentially or in parallel, by people or machines, carrying out activities which are designed to improve or maintain health. For example, the process of a referral to hospital can involve the decision to refer (a cognitive process), following discussion with a patient of their needs or wants, a communication (e.g. letter) transferred to the hospital, an electronic appointment, letter (or call) to the patient to let them know a date or time, etc.
This example is relatively straightforward, compared with many health processes which are often more complex. They may involve many more steps, actors, equipment, materials, environments and interactions between these. The timing of the appointment (one possible output measure) can vary depending on how this is measured, as well as other inputs such as the content of the referral letter, the material used (paper vs. electronic), how it is sent (post vs. electronic) and all of this can affect patient experience of the referral. A delayed or lost referral can lead to a poor patient experience, waste (the patient calling the surgery to find out when the referral will be), rework (resending the referral), additional costs and poor outcomes including premature death, in the case of a patientwith cancer who has a referral delayed.
A better understanding of processes can make them more reliable and reduce inappropriate or unintended variation. In relation to health, this can improve effectiveness, safety and people’s experience of the healthcare they are receiving. Quality healthcare therefore meets patients’ needs by improving their health, increasing levels of satisfaction and reducing any errors. To understand how to improve care, we need to understand how to improve the processes involved, to understand how to reduce impropriate or unintended variation in these processes, and to understand how to make processes more consistent and reliable where this is required to improve outcomes of care. An important rider to applying these concepts in health systems is that some variation is inherent in the different presentations of disease, differences between patients and disparities of choice between individuals.
A number of conceptual and practical tools are available for understanding and improving processes and we will examine some of these. The range of tools considered in this article is not comprehensive but includes those we consider the most important and practically useful (Box 1).
A useful starting point for understanding and improving processes is the logic model. The logic model (Figure 1) defines what exactly we are trying to improve (the aims or priorities for improvement), describes who we are trying to improve it for (the population for which improvement is intended) and explains why we are trying to improve a particularly area of healthcare (the problem identified as in need of improvement). The model next describes the inputs which include people, work methods, equipment, materials, environment and measurements. It also describes how we will go about improving care in terms of who we will involve (the participants), what they will do to bring about improvement (the activities) and what we wish to achieve in terms of processes (the outputs) which are intended, or have been shown to lead to longer term benefits. Benefits are described in terms of health or wider gains as well as possible harms (the outcomes), whether intended or incidental and in the short, medium or longer term.
Various activities can help us understand the elements involved which can then be used to improve them (Box 1). For example, the problem, population of interest and priorities for improvement can be elucidated using interviews or surveys of patients and staff or direct observation.
Patients’ views ofwhat is important to them, how to meet their needs for better health, improve their experience and reduce harms can be discerned by asking them directly about these issues using interviews or focus groups, using surveys or direct observation of patients in their interactions with the health system (direct observation, written diaries or audio/ video diaries).
Often, it can be helpful to ask practitioners the same question, i.e. what constitutes good care and how can care be improved? Sometimes patients and practitioners agree but at other times their views may be discrepant. For example, patients and practitioners views on how to improve care of insomnia or acute pain, although broadly concordant, differ in some significant areas.
A process map is a tool to show pictorially the series of steps in a process of care. This can be constructed very simply by writing down the steps of a process on stick-it notes and connecting these on a (large) piece of paper using arrows. Often this exercise reveals a great many steps and complex interconnections between them, some of which are redundant or unhelpful. Process maps are sometimes called ‘spaghetti diagrams’ to convey intricate linkages between many steps. These processes can be confusing, conflicting, complex, chaotic and costly – what Balestracci refers to as the ‘five Cs.’
The process map can help us to identify which steps in a process are critical to quality. This enables unhelpful, wasteful or harmful steps to be removed. These measurable characteristics of a process, where standards need to be achieved to meet the quality requirements of the user, can be summarised using a critical-to-quality (CTQ) tree.
The inputs can be expanded, either as a whole or in specific areas to form a ‘cause-and-effect’ (sometimes called a fishbone or Ishikawa) diagram (Figure 2). The diagram helps elucidate the causes of a problem and is an aid to finding solutions. The central line represents the patient pathway leading to the outcome of interest and this is affected by various inputs, including patients themselves. The inputs include: people, both patients and healthcare providers; work methods and organisational processes; equipment such as machines and materials; and the environment which incorporates features such as policies, guidelines, protocols and organisational culture. Each in turn is influenced by various factors (represented by the subsidiary arrows).
The processes can also besummarised using a driver diagram. Driver diagrams enable a high-level improvement goal to be translated into a logical set of underpinning goals (‘primary drivers’) and specific actions (‘secondary drivers’) which can also be converted to measures. There are three stages to improving reliability as represented in a driver diagram in Figure 3.
The first stage involves preventing failure which can be achieved through standardisation of processes using guidelines and protocols checklists for practitioners, feedback to individual staff or groups, and education and training for staff. The next stage involves provider prompts and ‘forcing functions’ which prevent failure by ensuring that a (critical-toquality) process is completed before another can be undertaken. The final phase involves further redesign of the system to ensure that the process is as ‘lean’ as possible, minimising wasteful steps, reducing rework, reducing the chances of failure and maximising the efficient delivery of the process (Figure 3).
An example of this approach is shown for improving influenza vaccination rates in at-risk groups in primary care using a logic model (Figure 4) and case study (Box 2).
In the next article in the series we will go on to look at the important issue of measurement and the use of statistical process control in determining to what extent, if any, improvement has occurred as a consequence of change in processes.
Commissioned; not externally Peer Reviewed.
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