Quality control in health care: an experiment in radiotherapy planning for breast cancer patients after mastectomy

Application and Challenges of Statistical Process Control in Radiation Therapy Quality Assurance

Quality assurance (QA) is important for ensuring precision in radiation therapy. The complexity and resource-intensive nature of QA has increased with the continual evolution of equipment and techniques. An effective approach is to improve the process control technology and resource optimization. Statistical process control is an economical and efficient tool that has been widely used to monitor, control, and improve quality management processes and is now being increasingly used for radiation therapy QA. This article reviews the development and methodology of statistical process control technology, evaluates its suitability in radiation therapy QA practices, and assesses its importance and challenges in optimizing radiation therapy QA processes.

Moving towards process-based radiotherapy quality assurance using statistical process control

Monitoring Radiotherapy Quality Assurance (QA) using Statistical Process Control (SPC) methods has gained wide acceptance. The significance of understanding the SPC methodologies has increased among the medical physics community with the release of Task Group (TG) reports from the American Association of Physicists in Medicine (AAPM) on patient-specific QA (PSQA) (TG-218) and Proton therapy QA (TG-224). Even though these reports recommend using SPC for QA analysis, physicists have ambiguities and doubts in choosing proper SPC tools and methodologies. This review article summarises the utilisation of SPC methods for different Radiotherapy QAs published in the literature, such as PSQA, routine Linac QA and patient positional verification. QA analysis using SPC could assist the user in distinguishing between 'special' and 'routine' sources of variations in the QA, which can aid in reducing actions on false positive QA results. For improved PSQA monitoring, machine-specific, site-specific, and technique-specific Tolerance Limits and Action Limits derived from a two-stage SPC-based approach can be used. Adopting a combination of Shewhart's control charts and time-weighted control charts for routine Linac QA monitoring could add more insights to the QA process. Incorporating SPC tools into existing image review modules or introducing new SPC software packages specifically designed for clinical use can significantly enhance the image review process. Proper selection and having adequate knowledge of SPC tools are essential for efficient QA monitoring, which is a function of the type of QA data available, and the magnitude of process drift to be monitored.

Preliminary Retrospective Analysis of Daily Tomotherapy Output Constancy Checks Using Statistical Process Control

The purpose of this study was to retrospectively evaluate the results from a Helical TomoTherapy Hi-Art treatment system relating to quality controls based on daily static and dynamic output checks using statistical process control methods. Individual value X-charts, exponentially weighted moving average charts, and process capability and acceptability indices were used to monitor the treatment system performance. Daily output values measured from January 2014 to January 2015 were considered. The results obtained showed that, although the process was in control, there was an out-of-control situation in the principal maintenance intervention for the treatment system. In particular, process capability indices showed a decreasing percentage of points in control which was, however, acceptable according to AAPM TG148 guidelines. Our findings underline the importance of restricting the acceptable range of daily output checks and suggest a future line of investigation for a detailed process control of daily output checks for the Helical TomoTherapy Hi-Art treatment system.

Retrospective analysis of linear accelerator output constancy checks using process control techniques

Shewhart control charts have previously been suggested as a process control tool for use in routine linear accelerator (linac) output verifications. However, a comprehensive approach to process control has not been investigated for linac output verifications. The purpose of this work is to investigate a comprehensive process control approach to linac output constancy quality assurance (QA). The RBA‐3 dose constancy check was used to verify outputs of photon beams and electron beams delivered by a Varian Clinac 21EX linac. The data were collected during 2009 to 2010. Shewhart‐type control charts, exponentially weighted moving average (EWMA) charts, and capability indices were applied to these processes. The Shewhart‐type individuals chart (X‐chart) was used and the number of data points used to calculate the control limits was varied. The parameters tested for the EWMA charts (smoothing parameter (λ) and the control limit width (L)) were λ=0.05, L=2.492; λ=0.10, L=2.703; and λ=0.20, L=2.860, as well as the number of points used to estimate the initial process mean and variation. Lastly, the number of in‐control data points used to determine process capability (Cp) and acceptability (Cpk) were investigated, comparing the first in‐control run to the longest in‐control run of the process data. Cp and Cpk values greater than 1.0 were considered acceptable. The 95% confidence intervals were reported. The X‐charts detected systematic errors (e.g., device setup errors). In‐control run lengths on the X‐charts varied from 5 to 30 output measurements (about one to seven months). EWMA charts showed in‐control runs ranging from 9 to 33 output measurements (about two to eight months). The Cp and Cpk ratios are higher than 1.0 for all energies, except 12 and 20 MeV. However, 10 MV and 6, 9, and 16 MeV were in question when considering the 95% confidence limits. The X‐chart should be calculated using 8–12 data points. For EWMA chart, using 4 data points is sufficient to calculate the initial mean and variance of the process. The EWMA limits should be calculated with λ=0.10, L=2.703. At least 25–30 in‐control data points should be used to calculate the Cp and Cpk indices.

PACS number: 89

Quality in radiation oncology

A modern approach to quality was developed in the United States at Bell Telephone Laboratories during the first part of the 20th century. Over the years, those quality techniques have been adopted and extended by almost every industry. Medicine in general and radiation oncology in particular have been slow to adopt modern quality techniques. This work contains a brief description of the history of research on quality that led to the development of organization-wide quality programs such as Six Sigma. The aim is to discuss the current approach to quality in radiation oncology as well as where quality should be in the future. A strategy is suggested with the goal to provide a threshold improvement in quality over the next 10 years.

Statistical process control for radiotherapy quality assurance

Every quality assurance process uncovers random and systematic errors. These errors typically consist of many small random errors and a very few number of large errors that dominate the result. Quality assurance practices in radiotherapy do not adequately differentiate between these two sources of error. The ability to separate these types of errors would allow the dominant source(s) of error to be efficiently detected and addressed. In this work, statistical process control is applied to quality assurance in radiotherapy for the purpose of setting action thresholds that differentiate between random and systematic errors. The theoretical development and implementation of process behavior charts are described. We report on a pilot project is which these techniques are applied to daily output and flatness/symmetry quality assurance for a 10 MV photon beam in our department. This clinical case was followed over 52 days. As part of our investigation, we found that action thresholds set using process behavior charts were able to identify systematic changes in our daily quality assurance process. This is in contrast to action thresholds set using the standard deviation, which did not identify the same systematic changes in the process. The process behavior thresholds calculated from a subset of the data detected a 2% change in the process whereas with a standard deviation calculation, no change was detected. Medical physicists must make decisions on quality assurance data as it is acquired. Process behavior charts help decide when to take action and when to acquire more data before making a change in the process.

Laryngeal recurrent nerve injury in surgery for benign thyroid diseases: effect of nerve dissection and impact of individual surgeon in more than 27,000 nerves at risk

OBJECTIVE

To evaluate the effect of recurrent nerve dissection on the incidence of recurrent laryngeal nerve injury (RLNI) and to analyze the performance of individual surgeons.

SUMMARY BACKGROUND DATA

Dissection of the recurrent nerve is mandatory in total thyroidectomy, but its relative merit in less extensive resections is not clear. The reported rates of RLNI differ widely; this may reflect a variation in the performance of individual surgeons.

METHODS

The authors studied the incidence of RLNI in primary surgery for benign thyroid disease during three periods in a single center. In period 1 (1979-1990; 9,385 consecutive patients, 15,865 nerves at risk), the recurrent nerve was not exposed. In period 2 (1991-1998; 6,128 patients, 10,548 nerves at risk), dissection of the recurrent nerve was the standard procedure. Global outcome and individual performance in these two periods were compared and presented to the surgeons. The effect of this quality control procedure was tested in 1999 (period 3; 930 patients, 1,561 nerves at risk).

RESULTS

Exposure of the recurrent nerve significantly reduced the global rate of postoperative and permanent RLNI. Some but not all surgeons improved their results by recurrent nerve dissection (e.g., permanent RLNI rates ranged from 0% to 1.1%). The documented significant differences in individual performances did not affect the outcome in period 3. The extent of nerve dissection was a source of variability; the rate of permanent RLNI averaged 0.9%, 0.3%, and 0.1% for surgeons who only localized, partially exposed, and completely dissected the recurrent nerve, respectively.

CONCLUSIONS

Recurrent nerve dissection significantly reduces the risk of RLNI. Extensive dissection facilitates visual control of nerve integrity during resection and is therefore superior to a more limited exposure of the nerve. Quality control can improve the global outcome and identify the variability in individual performance. This cannot be eliminated by merely confronting surgeons with comparative data; hence, it is important to search for the underlying causes.

Telemedicine and its impact on cancer management

The latest dramatic progress in the technologies of the computer industry is likely to increasingly influence the oncologist's daily routine. Besides well known and established telemedical services such as videoconferencing, the most influential trends are the spread of digital hospital infrastructures with unlimited, secured access to all relevant patient information. This article seeks to summarise the most imminent influences of telemedical developments on the future of the oncologist: the effects of telemedical services and electronic infrastructures on clinical workflow and on medical quality management. In addition, the history of telemedicine, recent technologies and the performance of electronic patient records are described.