(a) High-level flowchart provides an overview of the body MR imaging examination process, from scheduling through image acquisition. Team discussions of the flowchart and review of background data indicated that MR imaging room availability was the limiting factor to increasing the daily volume of body MR imaging examinations. DI = diagnostic imaging scheduler, MRI = MR imaging staff, PSC = patient service coordinator, Radiology = non – MR imaging radiology staff requesting scheduling of services for a particular patient, Tech = technologist. (b) Low-level flowchart extracted from a detailed master chart of the entire process shows only the technologist’s work flow. The shape of each box on the chart has a specific meaning: Ovals indicate start- and end-points, squares and rectangles indicate steps, and diamonds indicate decision- making points. A careful review of flowcharts can reveal important information affecting a process: Our team learned that a single technologist typically performed nearly all the steps in a given examination, including setup, image acquisition, and quality verification. 

Contexts in source publication

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... implementations also facilitate training. To continue with the hypothetical example, technologists can be rotated to a small group of MR imaging systems for intensive tutoring in a new protocol. Those who have difficulty in mastering the new protocol can be identified and assisted. We have found such an approach useful in training technologists both in MR imaging and in CT. During this phase, it is important to collect regular measurements and to consider adding new types of measurements that may be necessary to incorporate lessons learned. However, sensitivity is required to avoid imposing excessively burden- some requirements on project participants. Multiple changes will be made throughout the course of a process improvement project, and the exact timing of each change may be difficult to recall later. It is therefore important to record the time point at which specific changes are made, either in a log (Table 1) or on a time line (Figs 9, 10). The information in these records can then be compared with the regularly updated control chart to identify the effects of particular changes (Figs 4, 10). A unique feature of process improvement is that the steps just described can be repeated in a potentially endless series of PDSA cycles until the aim has been fulfilled or the project has been terminated or reformulated with a new aim. The letters in PDSA refer to p lanning how to implement chosen changes, implementing or “ d oing” the plan, s tudying the results of the implementation (eg, control chart and time line) to identify beneficial changes and to brainstorm about new changes, and a cting on that information to choose which changes should be implemented next (20). During each cycle, certain questions should be addressed: Does the project aim need to be modified? Are the current resources, expertise, team make-up, and project time frame still adequate? Is the sponsor being kept informed and still satisfied with the direction and rate of progress? Are new measurements and new data sources needed? Is data collection adequate? Is there “data collection fatigue” among the process participants? Did the implemented change or changes move the relevant measure benefi- cially “out of control?” Do the data suggest that an implementation of a change should be scaled up or a different change should be considered? What was learned during the last implementation? Were there any unexpected benefits of change or unexpected obstacles to change? Was communication adequate among those involved? Are those involved still enthusiastic? It is crucial to maintain morale during PDSA cycles. Positive results should be communicated to all those involved to show the value of the project and demonstrate progress. Negative results and how they are being handled should also be shared, not only to allow learning among participants but also to indicate that even negative feedback is valued and used. A final question to be asked is whether the project has reached a stopping point (the aim has been met, or the aim is unachievable and the project should be terminated). If the aim has been met, measurements should continue to be obtained for monitoring during a follow-up period of appropriate duration to ensure that the aim continues to be met. If not, PDSA cycles can be reinitiated. If the aim continues to be met, then the project can be closed. A closer consideration of our body MR imaging project log (Table 1), time line (Fig 9), control charts (Fig 4), and flowcharts (Fig 5) reveals how our project evolved through successive PDSA cycles. Our initial PDSA cycles were focused on streamlining the work flow by having technologists complete as many steps as possible before the MR imaging examination began (eg, prefilling of syringes with intravenous contrast material). A review of measurements and observations showed that the steps we modified were all performed by the same technologist and that we had only changed the order in which the steps were completed and had not improved efficiency. During subsequent PDSA cycles, we created and modified a new part-time position for a technologist who would “float” between MR imaging rooms. Because there was no budget or time to hire and train additional technologists, this change was implemented in a limited way with existing staff. The questionnaire in Figure 2 was used to document the examinations in which the “floating” technologist had assisted. In cases in which the “floating” technologist was used, the total MR imaging room time decreased on average by 4–5 minutes. At the same time, a newly created body MR imaging protocol committee was implementing modified protocols. Despite these changes, the control chart showing the daily volume of body MR imaging examinations (Fig 4a) showed no increase from the baseline volume. The daily average MR imaging room time for body MR imaging examinations (Fig 4b) showed steady decreases over the six most recent data points, but this change was two data points shy of statistical significance. Because the completion of the project and a formal presentation of the results were course requirements, the project was subsequently ...

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... our team created a paper-based questionnaire to collect detailed information from the MR imaging technologists (eg, the duration of occupancy of the MR imaging room, the time required for each sequential step performed during the MR imaging examination) (Fig 2). Problems that we encountered with this approach included missing, incomplete, or errone- ously completed questionnaires. Another alternative is to have a human observer monitor the process and record the results (16). In a time-motion study, a member of the project team shadows the technologist through every step in the MR imaging examination, tracking the time taken to complete each step and tallying the problems encountered. This method of data collection may result in higher data accuracy, but it is time and labor intensive and thus not suitable for con- tinuous monitoring. Before instituting changes in a process, it is important to clearly understand the current state (15). This means obtaining, charting, and analyzing baseline data collected over a sufficiently long period of time to avoid bias and to understand variations that are intrinsic to the process. Probably one of the most important tools for process improvement is the control chart (Figs 3, 4), which shows variation in a process over time. In the control chart, time is shown on the x-axis and a given measure on the y-axis. Beyond that basic structural principle, control charts may take many forms. One common form, the average and sigma (ie, SD) control chart (Figs 3, 4b), is used when the given measure charted per unit of time is an average. An example of such a measure would be the daily average duration of body MR imaging examinations. The control chart has a central horizontal line representing the overall mean, and “control” lines representing one, two, and three standard deviations above and below the mean. Another common type of control chart is the individual values and moving range chart, in which an individual value per unit of time and a moving range are shown simultaneously (Fig 4a). This type of control chart would be used to chart a single value (not an average) per unit of time. An example might be the total number of body MR imaging examinations performed in a given day (17–19). When analyzing a control chart, the goal is to determine whether the charted process is stable and in control (in which case variation is second- ary to chance) or out of control (in which case variation is secondary to assignable “special” or nonroutine causes) (19,20). An example of a special cause that might have decreased our daily volume of body MR imaging examinations would be downtime for repair of an MR imaging system. Similarly, in a project to improve the mammogra- phy ordering process, a telephone system upgrade might have caused the process to go out of control. Out-of-control variation in a process can be either beneficial or detrimental (19,20). However, at the start of a process improvement project, it is important that the process be in control. If it is not, then it must be brought into control before plans for process improvement are implemented, or it will be impossible to determine whether the measures implemented are responsible for subsequent variations in the process (17). There may be several signs that a process is out of control (Fig 3). Some examples include one data point more than 3 SDs above or below the mean, two of three successive points on the same side of the center line and more than 2 SDs above or below the mean, four of five successive points on the same side of the center line and more than 1 SD above or below the mean, and eight successive points on the same side of the center line (20). For our body MR imaging project, we created control charts (Fig 4) that were updated weekly. The charts showed the daily number of body MR imaging examinations (RIS data) and daily average MR imaging room time for body examinations (questionnaire data). These charts were disseminated by e-mail, discussed at weekly team meetings, and stored on a shared file server. The next step is to identify and prioritize opportunities for change by performing an in-depth evaluation of the specific process targeted for improvement. The purpose of process analysis is to obtain a thorough understanding of the process so as to identify the problems that inhibit achievement of the project aim. Three tools that are commonly used in process analysis are flowcharts, fishbone cause-and-effect diagrams, and tally sheets. We recommend that process analysis be performed at team meetings to best utilize the team members’ collective experience and special- ized knowledge about the process. Flowcharts are diagrams that show the steps in a process in their appropriate sequence (6,8–10,20). For complex processes, it may be necessary to create a “high-level,” simplified flowchart that can be supplemented by more detailed flowcharts of the individual stages, or groups of related steps, in the process (Fig 5). A thorough review of flowcharts by the project team can reveal rate-limiting steps and likely problems. Once a process is well understood, brainstorming may be useful to identify problems that may af- fect the success of the process improvement project. Cause-and-effect diagrams such as the fishbone diagram (Fig 6) can facilitate such brainstorming by helping conceptualize problems (6,10,20). Next, to facilitate decision making, data should be collected about the frequency of occurrence of each problem. Tally sheets are useful for recording instances of problems that are identified on a fishbone diagram (10,20). Problems described on the fishbone diagram can be listed and a tally taken of the instances of each problem over a given period of time. A centralized tally sheet maintained either as a digital shared file or as a paper-based master copy can be used by a technologist supervisor or a group of technologists to record instances of problems as they occur (Fig 7). Because our body MR imaging project involved scanners scattered throughout our institution, we instructed the technologists to record instances of problems by using the questionnaire shown in Figure 2. The results were then collated and tabulated. After opportunities for process change have been identified, the next step is to decide which changes should be made. The relative frequency of occurrence of each problem listed on the tally sheet may be calculated and the resultant percentages used to create a Pareto diagram to allow visualization of the most important problems (Figs 1, 7) (10,20). For example, our team’s review of a Pareto diagram indicated that issues affecting image quality (other than technologist error) and necessitating repeat imaging accounted for 73% of MR imaging examinations with a greatly prolonged duration (>2 SDs above the mean) (Fig 8). As an alternative, various list reduction techniques may be used. In brainstorming sessions, team members may be called on to identify which problems on the tally list are similar enough that they can be combined. Group multivoting techniques can then be used to further reduce the list so as to facilitate the selection of changes for implementation (6,20). Next, plans must be formulated to carry out the decisions that were made (8). During planning, the following questions must be answered: Who is in charge? What resources are available? Who can allocate additional resources if needed? What are the specific steps to be completed? Would an outline of steps (ie, a work breakdown struc- ture) be useful (21)? What is the time frame for project completion? Who should receive progress updates? Are there “stopping points” that might prevent the implementation of changes and doom the project to failure? When plans have been formulated, as many participants (eg, technologists, nurses) in the process as is reasonably possible should be in- vited to review them so as to assess the feasibil- ity of their implementation as well as to generate support for the project and allow learning about process change. How, then, should plans be implemented? We have found that small-scale pilot projects are useful initially to minimize risk (10,14,22). Lessons learned in these projects can be used to modify plans before scaling up, and plans that are clearly unsuccessful at the pilot project stage can be terminated quickly without a substantial waste of resources. For example, a new MR imaging protocol can be implemented initially on just one imaging system and the technologists authorized to switch to the old protocol if they encounter problems with the new one, with the stipulation that they provide information to the project team about the reason for the switch. This information can then be used to improve the protocol in a cyclical manner (through PDSA cycles) until it is sufficiently mature to be deployed more ...