Continuous quality improvement plays a crucial role in promoting the quality of goods and services. By enhancing the quality of its goods or services, an organization is able to meet customer expectations, which translates into greater satisfaction and higher profits for the firm. Continuous quality improvement tools vary with regard to their underlying concepts, rigor, and application. This paper discusses five of the most widely used tools, namely, the PDCA, Donabedian model, ISO 9000, Lean methodology, and Six Sigma. It compares the key attributes of these methods and highlights their advantages and disadvantages. It also discusses a real-world application of the Donabedian model to improve the quality of preconception care in health care settings.
A continuous quality improvement is a useful approach for improving the production process in an organization. It entails a continuous, systematic, and iterative quality control method meant to improve “efficiency, effectiveness, performance, and outcomes” of a process (Keen, 1997, p. 12). In health care, process improvement tools such as the PDCA, Donabedian Model, ISO 9000, Lean Methodology, and Six Sigma, have been adopted to improve population health. The five quality improvement systems have different underlying concepts, origins, and applications. This paper provides a comparison of these quality improvement methodologies, illustrates their pros and cons, and examines an article applying one of these methods in a health care institution.
The PDCA cycle is one of the quality improvement processes adopted in various industries to improve and control the quality of products and services. Originally called PDSA (plan, do, study, and act) by Deming, PDCA entails continuous efforts to improve the quality, efficiency, and effectiveness of services and processes through an iterative process made up of four stages, namely, plan, do, check, and act (Keen, 1997). The aim of the initial phase (plan) is to examine a current issue scientifically to identify a problem and formulate an appropriate action plan. The “Do” phase is the implementation stage while the “Check” dimension entails an empirical study to assess the impact of the intervention. After testing the intervention, based on the results, one can decide to adopt, adapt, or abandon the process (act). Thus, PDCA is a straightforward, yet powerful quality improvement tool.
It is evident that the PDCA cycle is a scientific process; it entails formulating and testing hypotheses to determine the best intervention for a given problem. This ensures that the improvement process proceeds in a fashion that increases the likelihood of success. Another advantage of PDCA lies in its general nature that makes it adaptable to any industry. PDCA is also iterative, which allows one to adjust it continuously until a perfect improvement fit is attained. Local optimization is also possible in PDCA through repeated experimentation.
PDCA is a problem-solving process anchored in teamwork and collaboration. It requires one to set up a team with the right skill mix and training to effect the improvement sought. Thus, PDCA creates an inclusive learning environment and a knowledge pool gained from the problem resolution experiences. Besides its scientific rigor, PDCA is a simple process; the elements of its four phases are clear and unambiguous. However, compared to Six Sigma, PDCA is less rigorous in its analysis and thus, may not generate the required improvement fit. Moreover, although it is a faster process than Six Sigma, the limited rigor increases errors in the outcome. Since it is general in nature, it does not elaborate on the problem resolution process. This means that one has to complete the first iteration to determine its impact on a process.
The Donabedian Model
The Donabedian triad, which was put forward by Avedis Donabedian, considers health care quality as a three-faceted concept that consists of structure, process, and outcome (Keen, 1997). ‘Structure’ includes the resources, workforce, and facilities at an organization’s disposal. ‘Process’ covers the methods used in care provision, including surgeries and medical procedures. In contrast, outcome describes the effects or results of using a particular process or intervention on patient care. A particular intervention can produce positive or negative patient outcomes.
Unlike the other models, the Donabedian triad was developed in healthcare settings. The model includes process measures that take less measurement and analysis time compared to PDCA. ‘Process’ focuses on both technical and interpersonal aspects of an organization. Interpersonal processes measure the social interactions between the caregiver and the patient while technical ones focus on clinical factors that directly affect care provision. By focusing on the technical skills of the caregivers, the Donabedian triad fosters inter-specialty collaboration, which enhances the quality of care. Another advantage of this model is that it emphasizes structure as a crucial link between outcome and process. Structure determines a facility’s operational capability, as “leadership, human capital, information systems, and group dynamics” are key ingredients of a good care delivery system (Keen, 1997, p. 23).
The triad measures the outcome of an initiative, which helps determine its effects on patient care. The key elements of outcome measures fall into four categories, namely, “behavioral, experiential, clinical, and financial” (Keen, 1997, p. 224). These clusters are comprehensive and thus, offer valid measurements of the outcomes of organizational processes and structures. Although the model gives a general framework for measuring quality improvement initiatives, it leaves out some important factors. First, it does not capture the cost and efficiency of an improvement initiative. Second, the triad does not include culture as a process measure. It only focuses on technical skills and excludes patient safety culture and systems, which are important quality improvement measures in healthcare settings.
ISO 9000 is a group of global quality standards that are adaptable to any industry or sector (Anderson, Daly, Johnson & Johnson, 1999). Unlike the other models, this methodology is not a quality system, but a category of standards. An international body, ISO/TC 176, develops and revises these standards periodically to help institutions manage quality. The formulation of the ISO-9000 standards entails collaboration among specialists drawn from various sectors. The intention is to develop quality standards that ensure that consumer goods and services have the desired characteristics. ISO 9000 only gives guidelines to firms regarding quality management and does not require them to adhere to specific quality standards or procedures.
One advantage of ISO 9000 is that it is anchored on quality management principles. The eight principles guide an organization towards a path of improved performance. Anderson et al. (1999) outline these principles as leadership, customer focus, involvement/inclusivity, process approach, system management strategy, continual improvement, fact-based decision-making and efficient supply chains. ISO 9000, like PDCA, is general and thus, adaptable to any organization or sector. It is also consistent in terms of data and design control (Anderson et al., 1999). This helps control each function during the production process, which yields quality products or services.
ISO 9000’s process approach also fosters efficient resource management. It entails ascertaining the current processes, determining what is needed (based on the ISO 9000 standard), and changing the operations to conform to the standards. This facilitates continual quality improvement. Thus, since it uses a process approach, ISO 9000 is an important indicator of quality improvement in an organization. The process approach relies on the PDCA methodology to control all processes to increase operational efficiency and meet client needs. Thus, ISO 9000 enhances the quality of products or services, which raises customer satisfaction.
However, as aforementioned, ISO 9000 only outlines the quality management requirements that organizations should meet; it does not provide guidelines on how organizations can achieve them. The reasoning behind this approach is that once an organization has its own quality management system, it will begin to produce quality goods or services. Moreover, some variants of ISO 9000 (those published in 1994) are strict and thus, inflexible. Additionally, while ISO 9000 outlines the quality management requirements, certification only follows the ISO 9001 methodology.
The Lean Methodology
Lean methodology is a quality management model that has its origins in the production environment. Lean production or Toyota manufacturing model is a continuous improvement approach that centers on waste reduction to enhance effectiveness (Blind, 2004). The wastes present in non-lean environments include overproduction, waiting, transportation, excess inventory, surplus motion, underutilized workforce, non-value-added production, and defects (Blind, 2004). ‘Lean’ firms use ‘lean building blocks’ to do away with the eight wastes. Some of the lean building blocks include the pull system, whereby the production rate depends on customer demand, Kanban cards, work cells, total quality management (TQM), and total production maintenance (TPM), among others.
Adopting lean production brings many benefits to an organization. The first benefit is operational improvement. According to Blind (2004), removing the ‘eight wastes’ leads to reduction in lead-time, space utilization, and work-in-process inventory and improvement in quality and productivity. Organizations can use the low lead-time to gain a strategic advantage in the industry by producing goods at a faster rate than rivals produce. Lean production also results in administrative improvements characterized by low production errors, better customer service, and lower staffing requirements.
However, the implementation of lean production has little effect on some continuous production processes. In particular, implementing this methodology in heavy-volume firms may not yield much improvement due to “insignificant opportunities in the production areas” (Blind, 2004, p. 56). In addition, failure of the suppliers to implement the methodology would affect timely delivery of products and increase inventory volume. This would significantly reduce the benefits of the methodology. Lean methodology also has a significant impact on the organizational culture and thus, its implementation may encounter resistance.
The Six-Sigma Model
Six-Sigma is a quality improvement approach introduced by Motorola to optimize its production processes and necessitate cultural transformation (Raisinghani, Ette, Pierce, Cannon & Daripaly, 2005). Compared to PDCA, Six-Sigma uses more rigorous techniques and statistical methods to determine the results of a production process. One of these methods is the measurement system analysis (MSA), which is used to measure the key product attributes that need optimization. Another tool is statistical process control, which measures the departures from the normal variation in the quality of products. The Six-Sigma model also uses design of experiments (DOE) as a tool for process optimization. Raisinghani et al. (2005) write that DOE is necessary in a process that involves many inputs to predict output variables. ‘Failure mode and effects analysis’ or FMEA is another quality methodology used in the Six-Sigma model. It entails a liaison with key stakeholders to determine potential pitfalls and their remedies. A quality control and capability analysis follow the FMEA procedure. It provides a final mark of quality for a process or product.
The scientific inquiry of Six-Sigma reduces the number of defects that come out of a process. Since Six-Sigma is a rigorous process, identifying opportunities for process improvement is possible. Additionally, through systematic measurement the pitfalls in a process can be minimized resulting in better quality production. High quality products increase customer satisfaction. The reduction in defects also cuts down production costs. Six-Sigma also allows tracking of results, which helps identify opportunities for process improvement. However, Six Sigma only provides tools for monitoring production. It does not focus on the product design stage, which affects its success. Additionally, the Six-Sigma model, despite being rigorous, is difficult to understand compared to other models.
Sardasht, Shourab, Jafarnejad, Esmaily (2013) used the Donabedian model to evaluate the quality of care given to mothers planning to conceive. This descriptive study relied on obstetric data and the demographics of women receiving preconception care at Iranian health care centers (Sardasht et al., 2013). It involved 30 subjects (women of reproductive age) sampled using the multi-stage sampling technique. The researchers used questionnaires to collect data about the subjects’ satisfaction and knowledge of the care received. The authors used the outcome aspect of the model to assess the quality of the preconception care. The outcome variables included “monitoring the subjects’ health status, their knowledge level, and satisfaction rate” and relating them to health care changes in the facilities (Sardasht et al., 2013, p. 54). The results indicated a satisfaction rate of 76% and a knowledge level of 15%. From these results, the researchers concluded that continuous medical education initiatives could enhance preconception outcomes, such as knowledge and patient satisfaction.
The five models discussed vary with regard to origin, underlying concepts, application, and rigor. Six-Sigma is the most rigorous one while the lean model affects all structures of an organization. The Donabedian methodology centers on three variables, namely, process, structure, and outcome. In contrast, ISO 9000 sets standards that dictate quality improvement in an industry. The PDCA cycle has the advantage of being easy to follow, adaptable, and rigorous. In the healthcare sector, successful implementation of any continuous improvement method depends on the context of the institution.
Anderson, W., Daly, D., Johnson, M., & Johnson, F. (1999). Why firms seek ISO 9000 certification: regulatory compliance or competitive advantage? Production and Operations Management, 8(1), 28–43.
Blind, K. (2004). The economics of standards: theory, evidence, policy. Cheltenham: Edward Elgar Publishing.
Keen, P. (1997). The Process Edge: Creating Value where it Counts. Boston, MA: Harvard Business School Press.
Raisinghani, M., Ette, H., Pierce, R., Cannon, G., & Daripaly, P. (2005). Six Sigma: concepts, tools, and applications. Industrial Management & Data Systems, 105(4), 491-505.
Sardasht, G., Shourab, J., Jafarnejad, F., & Esmaily, H. (2014). Application of Donabedian Quality-of-Care Framework to Assess the Outcomes of Preconception Care in Urban Health Centers, Mashhad, Iran in 2012. Journal of Midwifery and Reproductive Health, 2(1), 50-59.