Sources of Efficiency Gains

The IT platform enabled Saint Clare’s to enhance efficiency in the short run by mitigating the potential risk of lost information (e.g., paper documents, charts, reports), which often plagues paper-based environments. By storing existing documents and initiating the ongoing input of procedural data, Saint Clare’s created a more reliable method to organize, archive, and access information. Other gains include reducing the time for nursing staff to complete required paperwork, document vital treatment information for patients, and access past treatment information. The information download process has been enhanced by a user-friendly input interface, which also promotes a coherent, standardized database of treatment-related activities. Reduction in data access and downloading time from the previous paper report environment has increased the time available for nurses to concentrate on patient care. That is a classic case of increased productivity—accomplishing the same task in less time and increasing available employee time to address other tasks where the level of quality of each is increased.

“Patient Treatment” Intelligence

One of the most promising gains to efficiency lies in the ability to analyze the data that describe the treatment and care processes supported by the system. By transforming existing paper information into digital form and systematizing current and future procedure (treatment) information, Saint Clare’s is creating building blocks to perform more advanced analytics of patient care activities. Systematizing data enables users to analyze data elements more effectively in a logical, coherent manner. When compared to reading hundreds of paper reports and charts to formulate trends in patient response to treatments, the system effect provides the capability to identify and view trends over time. This applies to patient treatment outcomes and also to the effectiveness of treatment types across a variety of patients. The accessibility of more descriptive, coherent, and timely reports and graphics gives doctors, nurses, and hospital staff enhanced treatment intelligence.

Positive returns from business intelligence are generally achieved over time as data resources grow and develop and as new software applications augment data analysis. Increased usage of business intelligence enabled by higher quality information can assist treatment providers in better understanding treatment procedures, outcomes, and care for patients. With the establishment of an effective information management system and through the use of digital infrastructure, the implications for long-term efficiency gains through enhanced analytics and business (treatment) intelligence are far reaching.¹

Evaluation

When an electronic medical record system is implemented in an organization a process begins with a simple set of facts, and over time, a minimum of six months, a repository of workflow, treatment, and response information is established that, when put through a discriminating analysis, can be used to create a reliable and actionable set of information. This collection of facts will remain part of the database and be used to review charts on an as-needed basis for historical purposes. Data or the collection of facts provides the basis of creating information describing a multitude of activities in healthcare facilities. To accomplish this, a deep understanding of the processes, workflows, data capture, and regulatory requirements must be established. This is where a business strategy or process and performance evaluation methodologies such as Six Sigma come into play. Six Sigma can be viewed as either a business strategy tool that is effective at identifying the areas that require change or a performance evaluation methodology examining the effectiveness of process modification for a company. For an electronic medical record (EMR), it is important to understand how the data that underpin business intelligence and strategic methods such as Six Sigma are collected.

Reviewing a Workflow (Business Intelligence and Six Sigma)

One of the driving forces of customer or patient satisfaction is the effectiveness of a process or workflow in a healthcare organization. Any facility can claim it has policies and procedures that address those factors that lead to a positive patient experience; reality, however, indicates that what is dictated on paper may or may not be consistent with applications. Patients who visit facilities where they are able to navigate smoothly from one point in the process of registration to the next step generally have more positive feedback than those experiencing difficulty finding their way from one end of the building where they register to the other end, where radiology and the laboratory are located. A lack of clear workflow design (e.g., user-friendly directions for patients undergoing a process of events) can no doubt result in a negative patient experience. The application of business intelligence reporting coupled with a Six Sigma DMAIC project methodology review can identify how to improve the existing workflow. Clear directions on moving the patient from one area to the next that incorporate the activities of both patients and healthcare providers are critical to enhancing workflow efficiency and ultimately the patient experience.

The Six Sigma DMAIC project methodology is used for projects aimed at improving an existing business process. Each of the letters in the acronym identifies a phase of the project and was inspired by Deming’s plan–do–check–act cycle. The DMAIC project methodology is laid out as follows.

Define high-level project goals and the current process.

Measure key aspects of the current process and collect relevant data.

Analyze the data to verify cause-and-effect relationships. Deter-mine what the relationships are, and attempt to ensure that all factors have been considered.

Improve or optimize the process based on data analysis using techniques such as design of experiments.

Control to ensure that any deviations from the target are corrected before they result in defects. Set up pilot runs to establish process capability, move on to production, set up control mechanisms, and continuously monitor the process.

Given the preestablished processes that exist in the healthcare environment, business intelligence begins at the M phase of the project and continues through the final C phase. Each phase has distinct requirements that need to be accomplished before the process can move to the next phase. With the implementation of business intelligence, those taking part in the project can establish the goal, measure what currently exists, conduct analysis to identify key indicators, and produce information that can be acted on. Improving the process in the I phase is supported by visual representation to those responsible for executing the process, where the final stage of continually monitoring the process is accomplished by the timely updating of data resources and analysis of reports and graphics.

To illustrate the Six Sigma business intelligence approach, let us turn to a hypothetical healthcare application. In this case, an emergency room was honored with a national award for having the highest customer satisfaction rating of all the facilities participating in the survey. Although this is a very prestigious award, this kind of recognition means further scrutiny by those visiting that see the award prominently displayed on the wall of the waiting area. To maintain these performance achievements, analysis of what is currently in place, including time frames from each point in the process, is required, where considering the time it takes to move the patient between each point in the process is essential. A brief review by the project initiators identifies that the average wait time for a patient is more than 45 minutes before he or she has a medical service exam (MSE) by a physician. This identifies the area of workflow improvement that must be addressed. In parallel with the workflow, policy, and procedure evaluation, all current workflow points need to be identified in the system. The ability to extract these points should be available because a typical EMR would have the ability to add tasks, markers, or events in the system to identify when you have reached a point in the workflow or process. Event elements of the workflow process can be analyzed because informatics applications have the ability to time-stamp these events that indicate start and completion times. In an ideal situation the identified points in the workflow would be created and completed automatically by the software as personnel move the patient through the emergency department and complete the tasks or events previously defined. This prevents missing data from personnel overlooking the need to enter any time stamp information. The ultimate result is a data resource that enables decision makers to identify bottlenecks in the workflow, investigate causes of delays, and if feasible, introduce guidelines to address the issues at hand.

Initial review of data includes a column for every step in the process that contains the time to complete that task. In this facility the patient arrives, which is the starting time stamp of the process, and then moves into triage with a nurse, and is assigned and moved into a bed in the emergency department. Nurse evaluation and a medical history review are then conducted and completed. Next, a medical service exam is performed by the physician, which may be followed by testing, procedures, medication administration, and treatment. Disposition of the patient is performed to indicate if the patient is going home after treatment or being admitted. These are just some of the initial steps that can be identified for tracking purposes, and the time frame between each step indicates where potential bottlenecks exist in the process. Identification of the areas between the arrival and the MSE become visible as extended time frames from arrival to the triage occur, and the time from the MSE being requested to when it was completed by the physician may become elevated. The next step is to look at what personnel are involved with moving the patient through the process, or perhaps personnel staffing levels at those times versus the number of patients coming to the facility for treatment. By doing this we complete the M and A phases of the project through measurement and analysis of what is currently in place by business intelligence tools available within the EMR. Further detail and alternate representation of the data would be needed to drive the changes in the I phase of the project. The timing of workflows is imperative to the successful treatment of a patient because the feeling of adequate care can generally be linked to the timeliness of movement of the patient through the emergency room, or any other department in a facility. However, one step that makes the largest impact is that of the physician coming in to see the patient. Of the data that have been collected to this point, the arrival time of the patient is available and it is known when the physician starts the MSE, or first visits the patient in the room, because there is a time stamp associated with the event and the physicians have agreed to log in to the computer and start the event prior to visiting with the patient. This agreement can be easily acquired from the physician since he or she will typically log in to the computer to gather the data that have been collected during triage and initial nurse evaluation. On the completion of the shift the system is left with time stamps and events from every patient and every physician, and the business intelligence system can now run automatically to produce the chart seen in Figure 12.2. What is immediately seen is that some physicians are adequate at arriving to see the patient and begin their exam in under 30 minutes, and typically those physicians have a lighter load than others. The physician who stands out is physician 6 because he had one of the lightest loads for the shift but was unable to meet the required 30-minute time frame. Now the administration can delve deeper into why this was occurring and sit down with the physician after reviewing the data to see if there was an outlier that caused the physician to fall outside the acceptable range. Whatever the reason, by simply having the data in place and available for them to see how well they are performing, the physicians will typically strive to meet the goal because they do not want to be the outlier in meeting the needs of both the patients and the facilities. Any administrator would love to be able to create an environment where personnel strive to increase performance and patient satisfaction without any monetary output to the physicians themselves.

Figure 12.2 Bubble chart to identify physicians with average door to MSE times greater than 30 minutes.

Improvement may be needed in the specific areas that have been identified as a source of process delays. This can be accomplished through the analysis of process-related information via reports and graphics that depict excessive lag times for certain procedures beyond normal and acceptable levels. Initiatives such as increasing labor resources (e.g., specific healthcare personnel) to areas where bottlenecks occur, or systematizing procedures that cause undue delays in patient care activity (e.g., administrative) can be implemented. Applications of charts and graphics that report on daily performance metrics involve the C phase, which enables decision makers to quickly view on a daily basis, at a high level, reports indicating trends in process performance rates. Robust business intelligence technology enables users to drill into the low-level reports to see where incidents are causing delays and inhibiting process performance. This allows personnel to address problems as they are occurring to alleviate negative patient experiences in the pipeline. As an example of how you can identify causes in disruption of workflow, a Pareto chart was utilized to determine the potential causes of patients being delayed in movement from the emergency department to the nursing units (see Figure 12.3). Again, we can rapidly identify the areas that need improvement, where it is understood that to make the largest improvement in process, you need to identify the causes of delay that happen 80% of the time. With a review of the chart the three main problems are the areas of the emergency department physician and the admitting physician exchanging their reports with each other, and the delay in the nursing staff giving a report to the admitting nurse on the unit. The directors of the organization now have a clear path to alleviate patients waiting excessive times before being taken to their beds. A new methodology for handling patient needs to be evaluated is required. Once that methodology is put in place, the same evaluation of data can be run again to see the results of time frames and the causes for delay. With enough data collected over time, trending can then be added to identify points in time and the changes that were put in place at that time to produce the effect on the statistical measures.

Figure 12.3 Factors for patient delays.