Lean Transformation in Healthcare

Home » Best Practices

Category Archives: Best Practices

Excellence in Healthcare Delivery

Advertisements

The Heart of the Matter: Hospital’s Improved Diagnostic Process Saves Lives and Money

You expect to find many lifesaving techniques in hospitals—expensive medical research, groundbreaking procedures—but when it comes to treating patients with cardiovascular disease, the approach one Taiwanese hospital used might surprise you: data analysis.

Heart disease is one of the leading causes of death in Taiwan, so it’s no wonder the country’s healthcare professionals are looking for ways to improve treatment options.

That’s why a Lean Six Sigma project team at Cathay General Hospital in the city of Taipei examined the emergent angioplasty process for treating patients suffering from acute ST-elevation myocardial infarction (STEMI), a heart attack caused by coronary heart disease. Improving aspects such as the wait time between diagnosis and treatment could help to save many lives.

Doctors and quality managers from the hospital’s Quality Management Center used Minitab Statistical Software to assess the hospital’s process and confidently re-engineer both the diagnosis and treatment processes while increasing savings in medical resources.

The Challenge

A project team at Cathay General Hospital used Minitab Statistical Software to analyze data that would improve treatment for patients suffering from heart attacks. Above, the hospital is shown in its Taipei City, Taiwan, location.

Patients with STEMI are diagnosed through electrocardiogram findings and cardiac markers, and the recommended course of treatment for these patients is angioplasty completed within 90 minutes of arrival.

Medical professionals refer to this period as the door-to-balloon (D2B) time, because angioplasty involves inserting a small balloon inside the blocked blood vessel with a catheter. When inflated at the site of the blockage, the balloon enables blood flow to resume.

To maximize the patients’ chances for survival, the team needed to evaluate each step of the process. They needed to identify which variables were responsible for a D2B time that exceeded the recommended treatment time, and, more importantly, what adjustments could be made to minimize it.

How Minitab Helped

The team analyzed D2B time—which includes an electrocardiogram, the wait time before the operation, and the time for balloon inflation—using Minitab Statistical Software.

However, you can only trust the results of an analysis if you trust the data you’re analyzing. To ensure the data were trustworthy, the project team used Minitab to conduct a Gage R&R Study of their measurement system. This method evaluates a system’s precision, including its repeatability and reproducibility to ensure that measurements are consistent and reliable.

Minitab’s Assistant menu makes it easy to choose and use the right tool, even if you’re not a statistician. The dialog box above helps users create a data collection worksheet for a Gage R&R study.

Once they verified the precision of their measurements, the team analyzed D2B data from 40 STEMI cases that occurred over a nine-month period.

First, they tested the data to see if it followed a normal distribution, which is a key assumption in many types of analysis. The data were not normally distributed, but using Minitab the team easily applied a Box-Cox transformation to normalize it. The team then used the transformed data to create an I-MR control chart to evaluate if their process was stable over time. This type of control chart plots both individual observations (I) and the moving ranges (MR) to show how the mean and variation in the observations change over time.

The I-MR control chart above displays the normalized data from the Box-Cox transformation and identifies unusual sources of variation in the data.

The project team also used Minitab to conduct a process capability analysis to determine whether their process met performance specifications and provide insight into how they might improve their process. In this case, the upper specification limit for D2B time was 90 minutes. The results of the capability analysis confirmed that the hospital’s handling of STEMI cases had significant room for process improvement.

The team examined each step in handling a STEMI patient and identified several areas in which efficiency could be significantly enhanced, including confirming the diagnosis, medicating the patient, preparing for the operation, transferring the patient to the catheterization laboratory, and inflating the balloon.

Results

After assessing the STEMI process, the team implemented improvements such as sending patients who arrive with chest pain directly to an electrocardiogram test, printing treatment sheets automatically as opposed to writing them by hand, making a STEMI medication pack available in the emergency department, contacting the catheterization staff upon diagnosis confirmation, prepackaging all STEMI operation equipment in one box, and discontinuing the use of operation time as a forum to teach staff members who are not familiar with the procedure.

The team then collected additional data and reevaluated the process. Using Minitab to analyze the new data, the team demonstrated that the average D2B time dropped from 139.2 to 57.9 minutes—a 58.4% improvement. Furthermore, capability analysis showed that this new process could meet specifications.

A more efficient process means patients receive angioplasty more quickly, which saves lives. Moreover, the average hospital stay for STEMI patients has decreased by three days since the new process was implemented, and the hospital has saved $4.4 million in medical resources. The project was recognized by the Taiwan Joint Commission of Hospital Accreditation, and was awarded the Symbol of National Quality by the Institute for Biotechnology and Medicine Industry.

Applying data analysis and Lean Six Sigma methods to the health care system doesn’t grab headlines like an experimental surgery might. But as more hospitals use data analysis to make procedures better, faster, and safer, its benefits will be seen every day in the faces of patients whose lives are saved.

Learn more about lean six sigma in healthcare :  Six Sigma Master Class – Improving Healthcare Processes

Advertisements

Patient Safety: Akron Children’s Hospital Uses Lean Six Sigma and Minitab in the NICU

Serious about Patient Safety: Akron Children’s Hospital Uses Lean Six Sigma and Minitab in the NICU

 Akron Children’s Hospital is serious about enhancing the patient experience, along with delivering quality healthcare in a timely, efficient manner. While the hospital formally established the Mark A. Watson Center for Operations Excellence in 2008, it has been performing quality improvement since its early beginnings 125 years ago. It’s no wonder the healthcare provider has consistently earned Best Children’s Hospitals rankings in 7 of the 10 specialties evaluated annually by U.S. News & World Report—including cancer, diabetes and endocrinology, pulmonology, neonatology, neurology and neurosurgery, and orthopedics.

The hospital encourages employees across all skill levels and departments to become involved in quality improvement, offering several levels of Lean Six Sigma training. As part of its green belt training and certification, employees learn to use Lean Six Sigma by leading and completing long-term projects with the guidance of experienced black belts.

One such green belt project, which began at the hospital’s Mahoning Valley, Ohio campus, had a goal to decrease one particular safety event—unplanned extubations in the hospital’s neonatal intensive care unit (NICU). To complete this project, the hospital improvement team relied on Lean Six Sigma tactics and the data analysis tools in Minitab Statistical Software.

The Challenge

Akron Children’s Hospital relies on Minitab Statistical Software to analyze their Lean Six Sigma project data. The hospital used Minitab to verify improvements made to the intubation process in the NICU.

An intubation is a medical procedure in which a breathing tube is placed into a patient’s trachea. This tube connects the patient to a machine called a ventilator, which helps the patient breathe. The procedure is common for both pediatric patients and adults in intensive care, but is most common for premature newborn babies residing in a hospital’s NICU. Babies born prematurely often have undeveloped lungs, which cause breathing problems and the need for the assistance of a ventilator.

Although this medical procedure is commonly performed, it is not without risk, and can cause trauma to or introduce an infection into the patient’s airway. Unplanned removal of the breathing tube, which is also known as an unplanned extubation, is a likely occurrence that can cause harm. Unplanned extubations are the fourth most common adverse event in NICUs across the U.S.

Akron Children’s Hospital’s Department of Respiratory Care had been collecting data on the rate of unplanned extubations in the Mahoning Valley NICU for well over a year, but had not had the capacity to investigate the occurrences further. Bonnie Powell, a Registered Respiratory Therapist and manager of respiratory services at Akron Children’s Hospital, was a green belt candidate during the time unplanned extubation data were collected. As part of her Lean Six Sigma training and certification, she set out to lead a project that would decrease the rate of unplanned extubations in the Mahoning Valley NICU.

“I knew this project was the perfect fit for me because as a respiratory therapist, I’ve been part of the frontline staff primarily responsible for intubating,” Powell says. “When you’re the one actually putting the tube into the patient, it just affects you more because you know the trauma that you could be causing to them.”

How Minitab Helped

While there’s not a true benchmark rate that NICUs should strive to stay below regarding unplanned extubations, the Vermont Oxford Network—a research collaboration of nearly 1,000 global NICUs including Akron Children’s—considers 2 in 100 intubated patient days to be the upper limit of acceptable. Previous data collected on the rate of unplanned extubations at the Mahoning Valley NICU revealed a rate of 3 in 100 intubated days.

“Any unplanned extubation has the potential to cause harm to the patient and negatively impact overall patient satisfaction,” says Powell. “We wanted to improve our performance on this metric.”

Powell’s Lean Six Sigma project team included a multidisciplinary group of nurses, respiratory therapists, a neonatal nurse practitioner, and a neonatologist.

The team began by using Lean Six Sigma tools to brainstorm reasons why unplanned extubations were occurring, as well as solutions for stopping them. “The fishbone diagram and cause maps were among the most helpful tools we used,” Powell says. “We looked at the highest impact solutions, as well as how easy they would be to implement, and prioritized solutions from there.

“This step helped us to organize and roll out our seven improvements into two phases,” she says.

Along with more frequent communication between nurses and respiratory therapists before, during, and after an intubation, as well as educational information distributed in meetings and via email, one improvement implemented was the “two to turn” rule. “Anytime an intubated patient is repositioned, one caregiver is turning the patient and another is holding the tube at the patient’s mouth,” Powell explains.

The team applied the improvements for several months, as collecting enough data to meet the required 100 intubated days for pre- and post-improvement comparison proved difficult for many reasons.

“There is a continuing trend in neonatal care to use devices such as masks and nasal prongs to connect the patient to the ventilator to help with breathing. When these devices are used, there is no need for a breathing tube, which reduces the number of intubated days and lengthened our post-improvement data collection period,” Powell says. “That, coupled with greater attention to our weaning protocol, which focused on shortening the time babies need ventilator support of their breathing, contributed to why we saw a reduced amount of intubated days.

“Of course, fewer intubated days was a good thing in this case, and supported the idea that our improvements were working,” adds Powell.

To compare unplanned extubations, pre- and post-improvement, the team visualized their data using control charts in Minitab Statistical Software.

Minitab graphs clearly reveal the impact of improvement efforts. This control chart displays the reduction in unplanned extubations after Lean Six Sigma improvements were implemented.

To verify their results statistically, the team ran a 2 proportions test in Minitab to see if their unplanned extubation rates decreased after improvements were put into place.

Hypothesis testing in Minitab makes it easy to determine if there is enough evidence in a sample of data to infer that a certain condition is true for an entire population.

The analysis showed the team that after improvements were implemented, the unplanned extubation rate had indeed decreased.

The team also used Minitab to perform process capability analysis both pre- and post-improvement. This tool provided another before-and-after comparison of unplanned extubation rates, and aided the project team in assessing whether the new process was capable and in statistical control.

“I have never taken a statistics course and have no background in this type of work,” Powell notes, “but Minitab, coupled with the instruction I received from the Center for Operations Excellence, made it easy for me to analyze and understand my data.”

Trauda Gilbert, deployment leader for the Center for Operations Excellence at Akron Children’s, echoes Powell. “To be able to use Minitab to visually demonstrate the before and after effect with a control chart, which you can then share with your team and champion is really valuable. Minitab also makes it easy for front-line staff to document that they have made a statistically significant difference. To be able to do that without having to interact with a biostatistician or one of the other very rarely found statistical resources in our organization, is very beneficial,” she notes.

“Healthcare quality is a little different than manufacturing because we can’t just run a DOE and tweak a process line,” says Gilbert. “Even though we’re different, Minitab still helps us out.”

Results

The data revealed a dramatic reduction in intubated days after the improvements were made, as well as a considerable reduction in the rate of unplanned extubations at the Mahoning Valley campus. The reductions brought their rates in line with the Vermont Oxford Network’s suggestion of 2 unplanned extubations in 100 intubated patient days.

“This project showed us that simple improvements can create real change,” says Powell. “The cultural change this project instilled in our team was exciting—the recognition that even they could make a difference is huge.”

Cost savings resulting from the reduction in supplies and staff time needed to care for unplanned extubations can be calculated, but the overall financial impacts are hard to quantify. “The larger costs of unplanned extubations—such as a longer NICU length of stay, ventilator-associated pneumonia, and other setbacks that the patient can experience from the event—can be difficult to tease out,” Powell says.

“Neonatal patients are some of our key customers here,” she continues. “Due to the fact that they were born early, they come back to our institution for care frequently, especially initially. Making sure they have a safe experience early is critical, because the results of good care at this stage can have exponential benefits for patients in the future.”

In addition to improving the patient experience, the project helped Powell obtain her Lean Six Sigma belt certification. “I did get my green belt as a result, and we’ve also rolled out selected improvements to the NICU at our Akron campus,” she says. “We’re in the process of collecting data there as well, so this project didn’t just stop in Mahoning Valley.”

Powell’s project is just one example of an estimated 300 documented projects that have been completed throughout the Akron Children’s organization. The total financial savings of the hospital’s operations excellence program is estimated to be more than $25 million since its official beginnings in 2008.

Learn more about lean six sigma in healthcare :  Six Sigma Master Class – Improving Healthcare Processes

Using Six Sigma to Reduce Pressure Ulcers at a Hospital

Since 2001, Thibodaux Regional Medical Center (TRMC) in Louisiana has applied Six Sigma and change management methods to a range of clinical and operational issues. One project that clearly aligned with the hospital’s strategic plan was an initiative to reduce nosocomial or hospital-acquired pressure ulcers, because this is one of the key performance metrics indicating quality of care.

Although the pressure ulcer rate at the medical center was much better than the industry average, the continuous quality improvement data detected an increase between the last quarter of 2003 and the second quarter of 2004.

In October 2004, a Six Sigma project to address this issue was approved by the hospital’s senior executives. A team began to clarify the problem statement. Their vision was to be the “Skin Savers” by resolving issues leading to the development of nosocomial pressure ulcers. The project team included a Black Belt, enterostomal therapy registered nurse (ETRN), medical surgical RN, ICU RN, rehab RN and RN educator.

Scoping the Project

Through the scoping process, the team determined that inpatients with a length of stay longer than 72 hours would be included, while pediatric patients would be excluded. The project Y was defined as the nosocomial rate of Stage 2, 3 and 4 pressure ulcers calculated per 1,000 patient days. Targets were established to eliminate nosocomial Stage 3 and Stage 4 pressure ulcers and reduce Stage 2 pressure ulcers from 4.0 to less than 1.6 skin breaks per 1,000 patient days by the end of the second quarter of 2005.

The team developed a threats and opportunities matrix to help validate the need for change (Table 1). They encountered some initial resistance from staff, but were able to build acceptance as the project began to unfold.

Table 1: Threats and Opportunities Matrix
Threat Opportunity
Short Term Increase length of stay Improve quality of care
Increase costs Decrease medical complications to patient
Increase medical complications to patient
Long Term Decrease patient satisfaction Improve preventative care measures
Increase morbidity rate Improve hospital status/image
Decrease physician satisfaction Increase profitability
Increase number of lawsuits Improve customer satisfaction
Decrease reimbursement
Loss of accreditation

Measurement and Analysis

During the Measure phase, the team detailed the current process, including inputs and outputs. Using cause and effect tools, process steps having the greatest impact on the customer were identified as opportunities for improvement. The team also reviewed historical data and determined that overall process capability was acceptable, but that the sub-processes had a great deal of room for improvement. Improving these sub-processes would positively affect the overall process and further improve quality of care.

Measurement system analysis on the interpretation of the Braden Scale was performed to verify that results obtained by staff RNs were consistent with the results obtained by the enterostomal therapy RN, because this is the tool used to identify patients at risk of developing a pressure ulcer. This analysis indicated that the current process of individual interpretation was unreliable and would need to be standardized and re-evaluated during the course of the project.

A cause and effect matrix was constructed to rate the outputs of the process based on customer priorities and to rate the effect of the inputs on each output (Figure 1). The matrix identified areas in the process that have the most effect on the overall outcome, and consequently the areas that need to be focused on for improvement (Table 2).

The team identified several critical Xs affecting the process:

  • Frequency of the Braden Scale – The Braden Scale is an assessment tool used to identify patients at risk of developing pressure ulcers. Policy dictates how frequently this assessment is performed.
  • Heel protectors in use – Heel protectors are one of the basic preventative treatment measures taken to prevent pressure ulcers.
  • Incontinence protocol followed – Protocol must be followed to prevent against constant moisture on the patient’s skin that can lead to a pressure ulcer.
  • Proper bed – Special beds to relieve pressure on various parts of the body are used for high-risk patients as a preventative measure.
  • Q2H (every two hours) turning – Rotating the patient’s body position every two hours is done to prevent development of pressure ulcers.

Figure 1: Cause-and-Effect Matrix

Table 2: Data Analysis

Process

Defects

Opportunities

% Defective

Z Score

Overall Process

64

16,311

0.39

2.66

Braden Scale Frequency

10

76

13.16

1.12

Proper Bed

24

76

31.58

0.48

Q2H Turning

49

76

64.47

-0.37

Data analysis revealed that the bed type was not a critical factor in the process, but the use of heel protectors, incontinence protocol compliance, and Q2H turning were critical to the process of preventing nosocomial pressure ulcers. The impact of the Braden Scale frequency of performance was not identified until further analysis was performed (Figure 2).

Figure 2: One-Way Analysis of Means for Sub-Process Defects

Evaluating data specific to at-risk patients, the team separated populations who developed nosocomial pressure ulcers from those who did not have skin breakdowns. The Braden Scale result at the time of inpatient admission from each population was analyzed to see the effect on development of a nosocomial pressure ulcer. One unexpected finding was that the admit Braden Scale result was higher for patients who develop nosocomial pressure ulcers than for those who do not develop them, showing that patients at risk are not being identified in a timely manner, thus delaying the initiation of necessary preventative measures.

The team then looked at defects for Braden Scale frequency of performance for each population of patients using a chi square test. They found the frequency of Braden Scale performance did have an effect on the development of nosocomial pressure ulcers. This was confirmed with binary logistic regression analysis (Table 3).

Table 3: Binary Logistic Regression Analysis
Process

Coefficient

Odds

Probability

Odds Ratio

No Defects

–0.5222

0.59

0.37

N/A

Braden Scale Defects

2.54322

7.55

0.88

12.72

Bed Defects

1.56220

2.83

0.74

4.77

Q2 Turn Defects

–2.16870

0.07

0.07

0.11

The most significant X is the Braden Scale frequency of performance. This analysis confirmed the need to increase the frequency of Braden Scale performance to identify at-risk patients.

Recommendations for Improvement

During the Improve phase, recommended changes were identified for each cause of failure on the FMEA with a risk priority number of greater than 200. Some of the recommendations include:

  • Frequency of Braden Scale performance to be increased to every five days
  • Braden Scale assessment in hospital information system (HIS) to include descriptions for each response
  • Global competency test on interpretation of Braden Scale to be repeated annually
  • Prompts to be added in HIS to initiate prevention/treatment protocols
  • ET Accountability Tracking Tool to be issued for non-compliance with prevention and treatment protocols as needed

The Braden Scale R&R was repeated after improvements were made on the interpretation of results. The data revealed an exact match between RNs and the ETRN 40 percent of the time, and RNs were within the acceptable limits (+/– 2) 80 percent of the time. Standard deviation was 1.9, placing the results within the specification limits. The data indicated that the RNs tend to interpret results slightly lower than the ETRN, which is a better side to err on because lower Braden Scale results identify patients at risk of developing pressure ulcers.

The Control Phase

Another round of data collection began during the Control phase to demonstrate the impact of the improvements that had been implemented. A formal control plan was developed to ensure that improvements would be sustained over time, and the project was turned over to the process owner with follow-up issues documented in the Project Transition Action Plan.

The team implemented multiple improvements, including compilation of a document concerning expectations for skin assessment with input from nursing and staff. They also gave a global competency test on interpretation of the Braden Scale, which will be repeated annually. The Braden Scale frequency was increased to five days, and they corrected the HIS calculation to trigger clinical alerts for repeat of the Braden Scale. Prompts were added for initiating the Braden Scale, and monthly chart audits were developed for documentation of Q2H turning. A turning schedule was posted in patient rooms to identify need and document results of Q2H turning of patient. Additional solutions included the following:

  • ETRN to attend RN orientation to discuss skin issues
  • Revise treatment protocol to be more detailed
  • Wound care products to be reorganized on units
  • Unit educators to address skin issues during annual competency testing
  • CNA and RN to report at shift change to identify patients with skin issues
  • Task list to be created for CNAs
  • ET accountability tracking tool to be issued for non-compliance with prevention and treatment protocols as needed

Results and Recognition

Since this was a quality-focused project, the benefits are measured in cost avoidance and an overall improved quality of care. A 60 percent reduction in the overall nosocomial pressure ulcer rate resulted in an annual cost avoidance of approximately $300,000.

To make sure their initiatives are producing a positive impact on the patient care environment, the hospital continuously measures patient and employee satisfaction through Press Ganey. Inpatient satisfaction is consistently ranked in the 99th percentile and employee satisfaction in the 97th percentile. TRMC also has received recognition in the industry for their achievements, including the Louisiana Performance Excellence Award for Quality Leadership (Baldrige criteria), Studer Firestarter Award and Press Ganey Excellence Award.

“This project is a perfect example of the need to verify underlying causes using valid data, rather than trusting your instincts alone,” said Sheri Eschete, Black Belt and leader of the pressure ulcer project at TRMC. “Six Sigma provided us with the tools to get to the real problem so that we could make the right improvements. There had been a perception that not turning the patients often enough was the issue, but the data revealed that it was really the frequency of the Braden Scale. Leveraging the data helped us to convince others and implement appropriate changes.”

The nosocomial pressure ulcer rate is monitored monthly as one of the patient-focused outcome indicators of quality care. The results are maintained on the performance improvement dashboard (Figures 3 and 4).

Figure 3: Stage 3 and 4 Nosocomial Ulcers

Figure 4: Stage 2 Nosocomial Ulcers

Learn more about lean six sigma in healthcare :  Six Sigma Master Class – Improving Healthcare Processes

Lean Six Sigma in Healthcare: Improving Patient Satisfaction

Riverview Hospital Association
For providers like Riverview Hospital Association, serving Wisconsin Rapids, Wis. and surrounding areas, recent changes in the U.S. healthcare system have placed more emphasis on improving the quality of care and increasing patient satisfaction. “In this era of healthcare reform, it is even more essential for providers to have a systematic method to improve the way care is delivered,” says Christopher Spranger, director of Lean Six Sigma and Quality Improvement at Riverview Hospital Association. “We have had a Lean Six Sigma program in place for four years, and we are continuously working on ways to make our hospital safer and more efficient.

The Challenge

Under what is known as Hospital Inpatient Value-Based Purchasing (VBP), a portion of the Medicare payments hospitals receive are tied directly to patient satisfaction metrics and the quality of care, rather than entirely on the volume of Medicare patients treated. A new rule from the Centers for Medicare and Medicaid Services (CMS) grants Medicare incentive payments to hospitals that are meeting high quality of care standards, or have shown sufficient improvements. Hospitals that do not meet these standards are subject to a reduction in Medicare payments. “Nearly all hospitals treat a sufficiently large percentage of Medicare patients,” says Spranger, “so this rule presents a significant challenge with substantial financial implications for us—and for many other hospitals.”

Incentive payments are determined by how well hospitals score on two point-based domains. One domain takes into account the clinical process of care, where the hospital is judged on its performance in meeting twelve predefined clinical measures. The second domain is based upon the overall patient experience and measured through a survey called the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). HCAHPS scores depend on the percentage of positive responses received for each question within each specific ”dimension,“ or category. Dimensions include communication with doctors and nurses, clarity of discharge information, overall hospital rating and more.

When Spranger and the Lean Six Sigma team at Riverview discovered that the hospital’s overall HCAHPS survey scores were lower than desired for the discharge information dimension, they set out to improve scores with Lean Six Sigma techniques and data analysis.

How Data Analysis Helped

The Lean Six Sigma team’s goal was to increase the percentage of “yes” responses for the following yes/no HCAHPS survey question: “During this hospital stay, did doctors, nurses, or other hospital staff talk to you about whether you would have the help you needed when you left the hospital?” To start, the team assessed their baseline performance by plotting outcomes from the previous 24 months with a Minitab control chart. The chart revealed a stable process and a current average positive monthly response rate of 85 percent. The goal was to improve positive monthly responses and exceed the preset benchmark of 91 percent.

Minitab Control Chart

To determine underlying factors that could be causing low scores, Spranger and the team chose to analyze data the hospital already had on-hand about the patient, which was collected as part of the HCAHPS survey. They had access to the responder’s age, gender, length of stay, primary language, education level, hospital unit visited and more. With Minitab charts, histograms and plots, they were able to explore the variables and responses graphically.

The team analyzed the variables further, and used the Minitab Assistant to guide their statistical analysis. They followed interactive decision trees to determine which analysis to use, and selected Analysis of Variance (ANOVA) to compare sample means and to look for significant differences within variables that could be impacting the HCAHPS survey question.

Minitab Assistant

The Riverview team began this project with a preset assumption that differences in the education level or the primary language of the respondent might offer insight into the low scores, but their analyses of these variables revealed no statistical significance. However, analysis of other variables uncovered statistically significant differences within respondent age groups and the hospital unit visited.

Surpassing the Benchmark

The Riverview Lean Six Sigma team was able to narrow the project scope and use the insights they gathered to improve patient satisfaction for groups identified as scoring the lowest. “Historically, health organizations try to increase patient satisfaction through staff training and other large-scale solutions,” says Spranger. “Now, with a data-driven approach, we are able to better target improvements.” The improvements for this project targeted low-scoring patient groups from specific age ranges, as well as patients who stayed in specific hospital units.

The team also used the improvement effort to solve key problems identified in the current process for handling patient discharges, which included timing of education, ensuring the involvement of a family caregiver, and clarifying outcomes with the patient. They redesigned the discharge education process into three phases to address previous issues with timing, collaborated with primary care physician clinics to ensure consistency, created a process to ensure that a primary family caregiver was identified to engage in care management after discharge, and clarified terminology in discharge documentation that was considered vague.

After implementing these improvement strategies, the team compared the current proportion of “yes” responses to responses before the project began. They achieved an impressive gain in the proportion of “yes” responses and met their goal to surpass the 91 percent benchmark for average positive monthly responses.

Learn more about lean six sigma in healthcare :  Six Sigma Master Class – Improving Healthcare Processes

How to Use Value Stream Maps in Healthcare

Carly Barry 27 February, 2013

While value stream mapping, or VSM, is a key tool used in many Lean Six Sigma projects for manufacturing, it’s also widely used in healthcare.

Value stream mapping can help you map, visualize, and understand the flow of patients, materials (e.g., bags of screened blood or plasma), and information. The “value stream” is all of the actions required to complete a particular process, and the goal of VSM is to identify improvements that can be made to reduce waste (e.g., patient wait times).

Value Stream Map - example from manufacturing

How is VSM applied to healthcare?

When used within healthcare, one obvious application for VSM is mapping a patient’s path to treatment to improve service and minimize delays.

To accurately map a system, obtaining high-quality, reliable data about the flow of information and the time a patient spends at or between steps is key. Accurately timing process steps and using multi-departmental teams is essential to obtain a true picture of what’s going on.

To map a patient’s path to treatment, a current state map can be created in a VSM tool (we offer a powerful one in Companion by Minitab) to act as a baseline and to identify areas for improvement:

Current State Value Stream Map

In this example, the first step a patient takes is to visit his general physician (abbrev. “GP” above), and this is represented as a rectangular process shape in the VSM. The time the patient spends at this step can be broken down into value-added (“VA”) and non value-added (“NVA”) cycle times. VA is time the customer is willing to pay for: that is, the 20 minutes spent consulting with the GP. NVA is the time the customer is not willing to pay for, i.e., the 20 minutes spent in the waiting room before the appointment.

The dotted line arrow between process steps is called a push arrow. This shows that once a patient completes a step, they are “pushed” to the next step. This is inefficient, and a more efficient process can be designed by changing push steps to continuous flow or “pull” steps. The yellow triangles indicate the time a patient spends waiting for the next process. These steps are a non-value added action for the patient.

While VSM can certainly be done by-hand on paper, using computer-based tools like those in Quality Companion makes the process a lot easier. For example, Quality Companion automatically calculates and displays a timeline underneath the VSM, which adds up the total time to go through the entire system (aka “lead time”) and displays summary information.

By identifying all of the steps, you can start to map the whole process out, moving from left to right. Once you have mapped out the entire system, an ideal future state map can be created, and possibly a series of future states in between. These can identify areas for improvement, and once implemented, they can become the “new” current state map as part of an iterative quality improvement process.

How do you improve the current state map?

When looking for areas of improvement, try to focus on changes to improve the flow of patients through the process. Continuous flow is the ideal and moves patients through the system without them having to wait. However, continuous flow is not always possible, so instead other changes might be introduced—such as first-in first-out (FIFO).

Also be sure to take a look at the takt time, which can help you decipher the pace of customer demand. In this case, takt time can be interpreted as the number of patients that can be treated per unit of time. Quality Companion will calculate takt time automatically.

Once you have completed the current and future state maps, you can compare the two, quantify improvement opportunities, and look at how to implement the changes. In this example, the triage and sort/appointment steps might be combined so that fewer visits to the hospital were required by the patient and they receive treatment faster.

To see another example value stream mapping, check out this video that features a scenario from Companion’s extensive help system:

Learn more about lean six sigma in healthcare :  Six Sigma Master Class – Improving Healthcare Processes

Congratulations Michael Cossiart on Becoming a Certified Lean Six Sigma Black Belt!

7/7/2017 For Immediate Release – Phoenix, Arizona * United States

TPMG would like to congratulate Michael Cossiart for successfully completing the Lean Six Sigma Excellence in Healthcare Delivery Black Belt Certification program and earning his lean six sigma black belt!  He successfully completed the rigorous 16 unit – 65 lesson online blended lean six sigma black belt workshop by passing the certification examination with distinction.  The goal of Michael’s lean six sigma black belt certification project was to improve the throughput and productive capacity of his hospital’s radiology department.   His black belt project successfully eliminated 80 hours of non-productive wait time per month, decreased overtime by 44% ($245k annual savings) and increased the capacity to serve 22 more patients per month.  Congratulations Michael!

Michael Cossiart serves as a Program Manager in Performance Improvement at PeaceHealth.  He has more than 14 years professional experience in healthcare and served as an industrial engineer for 3 years at the Boeing Corporation.

Michael earned his Masters in Business Administration  from Western Washington University and holds a Bachelors Degree in Industrial Engineering from the Oregon Institute of Technology.

The Performance Management Group’s Lean Six Sigma Excellence in Healthcare Delivery Black Belt Certification Program is specifically designed for professionals who work for healthcare clinics, hospitals and systems. TPMG has been certifying green belts and black belts for more than 15 years. The company provides lean six sigma certification on-site, online, and on-campus (at the University of Phoenix) nationwide. For more information regarding lean six sigma training, certification and consulting – contact TPMG llc at 623.643.9837 or logon to www.helpingmakeithappen.com.

Congratulations Aleksandra Stolic on Becoming a Certified Lean Six Sigma Green Belt!

7/27/2017 For Immediate Release – Phoenix, Arizona * United States

TPMG would like to congratulate Aleksandra Stolic for successfully completing the Lean Six Sigma Excellence in Healthcare Delivery Green Belt Certification program and earning her lean six sigma green belt!  Aleksandra successfully completed a rigorous 10 unit – 45 lesson online lean six sigma green belt workshop by passing the certification examination with distinction.  This accomplishment acknowledges she has fulfilled the requirements for the green belt program of study and, from this day forward, is certified as a Lean Six Sigma Green Belt.  By completing this distinctive course, she is qualified and authorized to implement lean applications and performance management systems.  Congratulations Aleksandra!

Aleksandra is currently a well qualified Project Manager of Independent Medical Education and Medical External Affairs at Takeda Pharmaceuticals.  She has more than 18 years experience in the healthcare industry 14 of which with the American Academy of Pediatrics.  She holds a Master of Public Health from Northern Illinois University and a Bachelors of Arts in English from University of Belgrade.  In addition to her Lean Six Sigma Green Belt Certification,  Alexandra is a Certified Scrum Master and is a member in good standing with Alliance for Continuing Education in the Health Professions.

The Performance Management Group’s Lean Six Sigma Excellence in Healthcare Delivery Green Belt Certification Program is specifically designed for professionals who work for healthcare clinics, hospitals and systems. TPMG has been certifying green belts and black belts for more than 15 years. The company provides lean six sigma certification on-site, online, and on-campus (at the University of Phoenix) nationwide. For more information regarding lean six sigma training, certification and consulting – contact TPMG llc at 623.643.9837 or logon to www.helpingmakeithappen.com.

%d bloggers like this: