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The Voice of the Patient

An Lean Six Sigma Excellence in Healthcare Delivery Excerpt:  The Voice of the Patient

 

Zero to 50,000 — The 20th Anniversary of the Hospitalist

Robert M. Wachter, M.D., and Lee Goldman, M.D., M.P.H.

Twenty years ago, we described the emergence of a new type of specialist that we called hospitalista “hospitalist.”1 Since then, the number of hospitalists has grown from a few hundred to more than 50,000 (see graph) — making this new field substantially larger than any subspecialty of internal medicine (the largest of which is cardiology, with 22,000 physicians), about the same size as pediatrics (55,000), and in fact larger than any specialty except general internal medicine (109,000) and family medicine (107,000). Approximately 75% of U.S. hospitals, including all highly ranked academic health centers, now have hospitalists. The field’s rapid growth has both reflected and contributed to the evolution of clinical practice over the past two decades.

In the mid-1990s, the combination of managed care for privately insured patients and Medicare’s diagnosis-related-group–based payment system for inpatients pushed hospitals to manage care more efficiently without sacrificing quality or alienating patients. Hospitalists emerged as one potential solution. Within a few years, evidence showed that using hospitalists could result in reduced costs, shortened lengths of stay, and preserved or even enhanced quality of care and patient satisfaction2,3 — in essence improving the value of care. The field was off and running.

For hospital medicine to grow as quickly as it has, many stars had to align, including a viable financial framework, a pool of qualified physicians, and enough force to overcome resistance to change. Remarkably, those stars did align.

The first issue was economic. By the mid-1990s, elective medical admissions had all but disappeared, but emergency admissions were increasing. Acutely ill patients needed rapid attention on admission and often multiple daily visits during hospitalization, regardless of whether that disrupted the flow of physicians’ outpatient practices. Moreover, the remuneration for nonprocedural inpatient care, especially given its growing complexity, was not high enough to make physicians who had historically been responsible for such care (primary care physicians in community settings and specialist and researcher attendings in academia) feel strongly about retaining their hospital roles. So most such physicians willingly turned inpatient care over to hospitalists.

How could hospitalists, then, fashion careers out of a role that was economically unattractive to their colleagues? Once evidence of substantial cost savings had accumulated, health care organizations found it advantageous to have hospitalist programs, and most provided financial support to create appealing jobs with reasonable salaries. Thanks to the value proposition and new duty-hour limits for residents, hospitalists also increasingly became responsible for staffing nonteaching services in teaching hospitals.

The second facilitator of hospitalist growth was the very large pool of general internists in the United States, most of whom were trained predominantly in inpatient settings. Many internists, whether newly minted or experienced, found the hospitalist role attractive, particularly given growing dissatisfaction with primary care internal medicine. In contrast, the small reservoirs of general internists in countries such as Canada and Britain have hindered efforts to build inpatient programs staffed by generalists.

Third, the quality, patient-safety, and value movements and widespread implementation of electronic health records all emerged just as the hospitalist field came of age. Hospitalists’ early emphasis on improving systems of care4 bolstered the field’s credibility and fostered the development of a cadre of young physicians who would ultimately assume local and national leadership roles. For example, the U.S. Surgeon General and the chief medical officer of the Centers for Medicare and Medicaid Services are hospitalists — an impressive validation of such a young field.

As the specialty grew in size and stature, the model spawned variations on its central theme. One obvious extension was pediatric hospitalists, who now account for approximately 10% of hospitalists. More creative variations include “hyphenated hospitalists,” such as surgical hospitalists (also called acute care surgeons), neuro-hospitalists, and obstetrical hospitalists. Medical hospitalists also often comanage care with surgeons or medical subspecialists, thereby reducing costs and allowing those specialists to concentrate on procedural tasks.5 Finally, financial penalties for readmissions have led many hospitalists to staff post–acute care facilities to improve coordination with colleagues at acute care hospitals.

Despite the hospitalist field’s unprecedented growth, there have been challenges. The model is based on the premise that the benefits of inpatient specialization and full-time hospital presence outweigh the disadvantages of a purposeful discontinuity of care. Although hospitalists have been leaders in developing systems (e.g., handoff protocols and post-discharge phone calls to patients) to mitigate harm from discontinuity, it remains the model’s Achilles’ heel.

Many hospitalists have added value as local leaders in quality improvement, safety, and innovation, but some have functioned more as shift workers. For example, many community hospitalists have a 7-days-on, 7-days-off schedule that focuses mainly on high-volume clinical work and sends an unspoken but clear message that, at the end of an intensive clinical “on” stint, one is “off” and uninvolved. Our impression is that hospitalist programs provide more value when hospitalists’ inpatient assignments (clinical “systole”) are complemented by a systems-oriented “diastole,” during which clinical activity is limited but they contribute to key institutional programs. Productive diastole is more likely when hospitalists have strong leadership, a robust professional-development curriculum, and a mutual hospital–hospitalist commitment to adding value during specified and structured nonclinical time.

Another problematic, though not unanticipated, consequence of the use of hospitalists has been a diminished role for specialists and researchers on teaching services. Because specialists are far less likely than they once were to serve as inpatient attendings, trainees have less contact with them and less exposure to basic and translational science.

Finally, the few academic hospitalist groups that have developed substantial research programs generally emphasize the implementation of quality- and systems-related initiatives. Hospitalists have been slow to pursue substantial inquiry into discovery related to the common inpatient diseases they see or to lead multicenter trials of new diagnostic or therapeutic approaches. This deficiency limits hospitalists’ credibility in academia and the advancement of the field.

Although we continue to believe that the hospitalist model is the best guarantor of high-quality, efficient inpatient care, it’s clear that today’s pressures require innovative approaches around this core. In addition to following patients in post–acute care facilities, another modified approach is to have a subgroup of hospitalists function as “comprehensivist” physicians who care for a small panel of the highest-risk, most frequently admitted outpatients and remain involved when hospitalization is required. This model aims to blend the advantages of the hospitalist model for the vast majority (>95%) of inpatients with the potential advantages of continuity for a small group of patients who are admitted repeatedly.

Hospitalist programs are innovating in other ways as well. Many are developing early-warning protocols in which electronic health record data are used to identify patients who are at risk for problems such as sepsis or falls. Others are implementing bedside ultrasonography for procedures and diagnosis, pioneering methods of making rounds more patient- and family-centric, implementing unit-based leadership teams, or applying process-improvement approaches such as the Toyota Production System to inpatient care.

Many academic programs are also experimenting with new ways of reconnecting specialists and scientists with trainees. Some have begun offering focused basic-science training to hospitalists, others have developed molecular medicine consult services, and still others have instituted dual attending programs, with a consultative teaching specialist joining a more hands-on teaching hospitalist. Such innovations are welcome and should be studied. In fact, the field’s greatest risk may well be complacency — failing to embrace the kinds of transformation and disruption that led to its birth, or being slow to address the inevitable side effects of even the best innovation.

When we described the hospitalist concept 20 years ago, we argued that it would become an important part of the health care landscape. Yet we couldn’t have predicted the growth and influence it has achieved. Today, hospital medicine is a respected field whose greatest legacies may be improvement of care and efficiency, injection of systems thinking into physician practice, and the vivid demonstration of our health care system’s capacity for massive change under the right conditions.

Latest Snapshot: Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU)

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Building A Culture of Nurse Excellence to Drive Patient Satisfaction

Driving nurse excellence and engagement will be essential to delivering on patient satisfaction and experience.

  By Sara Heath

– When it comes to nurse engagement, efforts must go a lot further than just driving good job satisfaction. In fact, nurse excellence isn’t entirely about the nurses at all, although they are important. Instead, nurse engagement is an essential means to yield an overall positive patient experience, connecting all of the key elements of healthcare into one cohesive picture.

The call for good patient experiences is not something new. Healthcare has long valued the patient, striving for excellent bedside manner and good clinical quality outcomes. But in an age where healthcare consumerism reigns supreme and CMS reimbursements hinge on good satisfaction scores, driving that positive hospital experience has become even more crucial.

But building that experience is extremely nuanced, most industry experts can appreciate. A good patient experience requires a balance of certain hospitality elements, patient safety, and meaningful interactions between patients and staff.

And that’s hard, experts say. Hospitals only have so many resources to dedicate to facility amenities and clinicians are strapped for time, seriously hindering their ability to connect with patients on a personal level. Patient safety, although essential to clinical quality outcomes, can falter to human error in the most unfortunate cases, despite best efforts. Communicating those lapses then present a whole new challenge.

But those challenges aren’t insurmountable, especially when nurses are engaged. These clinicians are on the frontlines of everything ranging from patient interactions to medical care. So, when nurses thrive, everything else thrives, too, according to Christy Dempsey, DNP, MSN, MBA, CNOR, CENP, FAAN, the chief nursing officer at healthcare consulting firm, Press Ganey.

READ MORE: Pushing for Nurse Engagement to Drive Better Patient Experience

“A culture of nursing excellence really does impact everything,” Dempsey said in a recent interview with PatientEngagementHIT. “If you have a good culture of nursing excellence, then you’re more likely to have better physician engagement. You’re more likely to see that patient experience of their physicians, not just of the nurses, is better. Clinical quality is better. It’s the rising tide that lifts all boats in healthcare.”

As noted above, nursing excellence looks like a lot more than just good job perks and satisfaction, although those factors can be important. Instead, nursing excellence is about developing and advancing strong nurse leaders, who are then able to advocate for their patients and nurse peers.

“Nursing excellence requires a structure within the organization that supports shared governance so that nurses at every level are helping and involved in making decisions, measuring transparency of data, and establishing performance benchmarks and promoting autonomy for nurses inside that shared governance framework,” Dempsey explained.

Nurturing a culture of provider teamwork and implementing care frameworks that emphasize not just clinical quality, but safety and patient experience as well, is another key hallmark of nursing excellence.

But although the industry has a good model of what nursing excellence is – strong team-based care that gives all stakeholders the tools to succeed – it isn’t always happening.

READ MORE: Supporting Nurses to Address the Social Determinants of Health

“We are in an environment that is constantly changing. It’s complex in terms of the patients and the venues, the continuum of care,” Dempsey said. “There are a lot of pressures within healthcare today.”

But it’s those very factors that hamper efforts for nurse excellence that nurse engagement and empowerment can solve. When nurses are empowered, Dempsey maintained, the patient can thrive because the team can thrive.

“Even in today’s complex, constantly changing healthcare environment, that culture of nursing excellence can be fostered, promoted, and then impact everything else that happens in healthcare,” Dempsey asserted.

Healthcare organizations on a journey to nurse excellence need to start where they are today. Understanding their current competency in patient safety, nurse experience, and clinical quality and experience will be important for understanding the root causes of any underperformance they see in their facility, Dempsey instructed.

From there, organizations can design a path forward.

READ MORE: Nurse-Led Education Program Boosts Older Patient Experience

“Define what the nursing professional practice model in your practice is,” Dempsey said. “Once you have determined that, you’ve got to make sure that you have CEO and board support for that model and that the chief nursing officers and nursing leadership are involved in executive level decision making at the C suite and the board level.”

A nursing shared governance that included nurse managers and engages bedside nurses will help organizations build their accountability structure, leading nurses and other stakeholders to take ownership of the process. Stakeholders should also play a hand in writing out job descriptions, performance reviews, and standards for clinical practice.

After that, teams must scale that plan organization-wide.

“You need to establish a communication plan so that you are able to disseminate information and initiatives that help you drive towards nursing excellence,” Dempsey said. “You must have an organizational strategy for data transparency in how you talk about the data. You can’t just post it on the wall. How do you talk about the data and wrap stories around that data to make it come to life? Then, look at the specific work unit information and communication strategies.”

All of this must lead to an optimized work environment, Dempsey continued. Work environment, or the factors that make a job doable and even enjoyable, is even more important that staffing levels, Dempsey reported.

“Optimizing that nursing work environment is so important,” she said. “That includes the leadership development plan, how you are engaging nurses and fostering their development, and how you are providing incentives for professional development.”

Organizations must also assess how they are assuring they have the appropriate resources – both human and material – and emotional support for nurses. This will allow nurses to continue efforts for patient-centered care.

“Make sure that you’re optimizing staffing so that you have the right people taking care of the right patients in the right place at the right time,” Dempsey stated.

“Then, finally, track integrated metrics, so reducing silos both in terms of operations, but also in terms of the way we look at data,” she continued. “Integrate that data so that you can see things and how things move together — or don’t. This will help you draw insights from that integrated data and then build improvement plans, and accountability and ownership plans based on that integrated data.”

All of this will hinge on a culture of team-based care. The organizations that Dempsey sees fully committed to a culture of excellence are already deploying strong team-based care strategies, fostering collaboration, communication, and support across the team. This is a symbiotic relationship, she said, because the culture of excellence also draws on the whole hospital team.

And at the end of the day, that is what will help organizations push to the next level in value-based and patient-centered care.

“Driving nursing excellence is not just a good idea, it makes good fiscal sense,” Dempsey concluded. “It makes good sense to recruit and retain the best and the brightest. It is the rising tide that will help health care. We need to really promote that.”

Case Study: Surmounting Staff Scheduling at Valley Baptist Health System

By Carolyn Pexton and Blake Hubbard

Case Study: Surmounting Staff Scheduling at Valley Baptist Health System

Located in Harlingen, Texas, Valley Baptist Health System is a full-service, not-for-profit community health network ably serving the population of south Texas and beyond. The system is comprised of multiple organizations including Valley Baptist Medical Center, a 611-bed acute care hospital providing the number one rated orthopedics service in Texas, a state of the art children’s center and a lead level III trauma facility. The organization also serves as a teaching facility for The University of Texas Health Science Center.

In 2002, Valley Baptist Health System began to implement GE’s Six Sigma approach as a rigorous methodology for process improvement and a philosophy for organizational transformation. The adoption of Six Sigma at Valley Baptist fostered a revitalized culture that embraces the voice of the customer, breaks down barriers to change and raises the bar on performance expectations. Through this initiative, the team at Valley Baptist began to examine the most critical opportunities for improvement and select projects that would align with strategic objectives and produce measurable results.

As with most healthcare providers today, maintaining appropriate staffing levels and improving productivity are among the top concerns at Valley Baptist. During the initial wave of Six Sigma training projects, the team at Valley Baptist launched an effort to review and improve the staff scheduling process for one nursing unit in orthopedics. Within this particular unit, there had been a history of overtime and use of agency hours that did not seem to correlate with changes in patient volume. Patient census would fluctuate while staffing levels remained the same, and the higher hourly wage for overtime and agencies had begun to strain the overall labor budget.

The primary focus for this project was to improve the unit’s ability to responsibly meet staffing targets while protecting the quality of patient care. It is a challenge to reach that optimal level – avoiding overstaffing yet appropriately meeting daily needs. Paramount in this effort was the notion that targets would be met without adversely impacting customers. Patient satisfaction scores had to remain constant or increase, and this mandate was built into the project and measured through the use of upper and lower specification limits.

A cross functional project team was assembled including the chief nursing officer as sponsor, the assistant vice president from human resources, the nursing house supervisor, the nurse manager from the cardiac care unit, a representative from IT and a charge nurse. The introduction of any new change initiative can elicit skepticism, but since Six Sigma concentrates on fixing the process rather than assigning blame, once the approach was understood much of the skepticism subsided. Stakeholder analysis and other CAP (change acceleration process) tools helped to surface concerns and improve communication.

Also supporting this project were metrics to measure productivity for nurses and managers that had been introduced through the adoption of Six Sigma. The dual emphasis on productivity and quality provides a framework for offering cost effective care and aligns with the customer-centered mission at Valley Baptist.

Defining the Goal

During the Define phase of the project, the team concentrated on clearly identifying the problem and establishing goals. The nursing units in general had struggled to meet their staffing targets and were over budget on labor costs. For this project, the team decided to focus on one orthopedics nursing unit based on three criteria: the unit was not extremely specialized or unique so it offered the best representation of nursing as a whole; the manager was very supportive of the initiative; and this unit offered clear opportunity for improvement and results.

To understand the current scheduling process, the project team used the SIPOC tool to develop a high-level process map. SIPOC stands for suppliers, inputs, process, output and customers. Inputs are obtained from suppliers, value is added through your process, and an output is provided that meets or exceeds your customer’s requirements. SIPOC is extremely useful during process mapping.

Measuring and Analyzing the Issues

As they moved through the Measure and Analyze phases, the project team focused on data collection and the identification of the critical “Xs” that were impacting staff scheduling. Historical data was gathered from the payroll system to analyze regular time, overtime, agency use, sick time, vacation, jury, funeral leave and FMLA. They examined 24 pay periods for each data point. Fortunately, the team was able to extract the data they needed from existing systems and avoid manual data collection, which is more labor intensive and can increase the project timeline.

Given the availability of continuous data for the “Y” or effect and the potential Xs or causes, regression analysis was the tool chosen to help the team understand the relationship between variation from the staffing goals and vacation, FMLA, sick leave, overtime, agency nurse usage, and so on. Through regression analysis, they were able to determine that three critical Xs could explain 95 percent of the variation: agency use, overtime and census. The next step would be to understand underlying factors – data would point the team to interesting findings that disputed their original theories.

The Improve Phase

During the Improve phase, the team used many of the CAP and Work-out tools. Such acceptance-building techniques are key to success, since improvements introduce changes in process and human behavior. The team conducted a Work-out session to develop new standard operating procedures for better management of overtime and agency usage – critical drivers in staffing.

The chief nursing officer attended the sessions to underscore the importance of this initiative from a leadership perspective. The project team used the process map to indicate where they might have opportunities for improvement, and then conducted separate Work-outs on each area. They brought in nursing staff, house supervisors and other stakeholders to participate in the search for solutions.

This project translates to $460,000 in potential savings for one unit. Conservatively, if it were spread across the health system the savings could exceed $5 million.

Never Assume

This project furnished a classic example as to how Six Sigma can be used to either corroborate or dispel original theories. Management at Valley Baptist had initially assumed they were over budget on labor costs due to sick leave, FMLA, vacation and people not showing up, which would have naturally necessitated the additional overtime and agency hours. The data and analysis proved those assumptions to be incorrect.

It turns out there were several factors contributing to the staff scheduling challenges. One illuminating aspect to come from the Work-outs was the realization that nurses didn’t like floating in and out of units – this came up in every session. There were also issues with the staffing matrix which attempted to set parameters based on volume. Compliance was not ideal, and the matrix itself was based on data that was not completely current. Another complication was that maintaining information in the matrix involved labor intensive, manual processes that were difficult to control.

The team discovered the use of overtime was not always need-based. Units would regularly schedule 48 hours for each nurse, with the extra eight hours of overtime built-in as “traditional” usage. This became an accepted practice and although in theory, adjustments are supposed to be made when the patient flow is lighter, this was not happening. On the form used to submit data the nurses would have to guess what hours they might actually work. The matrix might indicate compliance, but the payroll data actually showed them clocked in for 14-15 hours instead of 12.

Another critical issue is that the nursing unit lacked appropriate mechanisms for shift coordination and handoff. There were two fully independent teams between the day and night shifts, and there was not a smooth transition between them. Part of the problem stemmed from a lack of written guidelines governing the overtime between shifts. Nurses would finish their regular 12-hour shift and stay on overtime to complete tasks rather than pass them on to the next shift.

The central metric of this Six Sigma initiative was worked hours divided by equivalent patient days. Valley Baptist Health System defines worked hours as those hours during which an employee was actually working – including regular time and overtime, and excluding non-productive hours such as sick and vacation time. Equivalent patient days is the volume statistic utilized within the Orthopedics Unit. It is the typical patient days number adjusted to reflect short-term observation (STO) patient volume.

Results and the Control Phase

The development of new standard operating procedures has clearly had a positive impact on the organization. This gave staff a plan they can follow and established accountability. The unit began a process for transition meetings between shifts. The outgoing nurse now takes the incoming nurse to the patient’s room, introduces them and provides a report on the current status and whether there are outstanding orders. In addition to improving operations for the hospital, this change has also been well received by patients, as reflected in rising satisfaction scores during the pilot.

The project on staff scheduling has led to an overall reduction in the higher hourly cost of overtime and agency use, and has translated to $460 thousand in potential savings for this one unit. Conservatively, if this project were spread across the health system the savings could exceed $5 million. It is also important to note that this project started at the 0 sigma level and increased to Six Sigma for nine consecutive pay periods.

“At Valley Baptist, we continually seek opportunities to improve productivity,” said Jim Springfield, President and CEO. “This focus is critical for our future success and ability to meet patient needs.”

To ensure results are maintained, managers use control charts and trend reports with data from HR, time and attendance and payroll systems. This provides real time information on productivity, tracking worked hours versus patient days to show alignment with targets on an ongoing basis.

Organizational and Customer Impact

The bottom line is that nurses, management and patients are all happier as a result of this project. With the pilot in the Control phase, Valley Baptist has held Work-outs to determine how they might broaden the SOPs and implement this approach across the system in all nursing units.

“Staff has become much more flexible. We initially encountered some resistance, but using the CAP tools and working through the process helped to create a shared need and vision.”

Leadership involvement and support turned out to be a significant factor in the overall success of the project. This initiative represented a major culture change from previous CQI and TQM approaches to quality improvement. All previous efforts had involved hard work and good intentions, but prior to Six Sigma, they lacked the framework and rigor to institute statistically valid long-term results.

The health system is moving toward autonomy through additional Green Belt and Black Belt training with projects, and through participation in a Master Black Belt course at GE’s Healthcare Institute in Waukesha, Wisconsin. This experience provides instruction and interaction that prepares the MBB to come back and teach within the organization.

“Coming from the HR side, it’s important for organizations to know it’s possible to change the way you’ve always done things, and that employees will adapt to a new approach. If you can overcome the stress surrounding change you can realize increased efficiency. This is a positive way to control staffing without employing slash and burn techniques.”

Irma Pye, senior vice president at Valley Baptist, attended a conference in Utah with other healthcare executives. When the issue of performance improvement and staffing came up, someone mentioned they’d attempted to do a project on this and it had failed because they couldn’t afford to alienate and potentially lose good employees. Irma spoke up and let them know that based on her own recent experience, you can indeed address this issue and it can work if it is approached in the right way using the right techniques.

“Usually, when you ask the department manager to trim labor costs they think it can’t be done because it will antagonize employees . . . they’ll either take a job somewhere else, or stay there with negative feelings which impacts morale. This approach was able to affect change, while avoiding issues of layoffs or pay cuts.”

Using Predictive Analytics to Help Seniors Maintain Their Independence

Evan McLaughlin 09 September, 2019

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We might not be able to observe the progressive loss of cognitive and intellectual abilities someone with dementia is experiencing from the outside, but healthcare clinicians can detect it when they observe their ability to bathe, groom or dress themselves deteriorate. Minitab consultant  and Insights 2019 speaker David Patrishkoff is researching how to help with the aid of Minitab software.

Activities of Daily Living (ADLs)

The healthcare industry calls basic self-care tasks like one’s ability to properly feed themselves, move around or go to the bathroom “Activities of Daily Living,” or ADLs. Since the 1950s, healthcare professionals have scored ADLs with pre-set criteria (see this worksheet from the National Palliative Care Research Center for example).

After populating a worksheet like this, a healthcare professional can flag the functional capabilities of older adults and use the results to assess their ability to live independently.

What if symptoms could be caught earlier?
Enter Machine Learning and Predictive Analytics

David Patrishkoff

 

David Patrishkoff

There is evidence that deterioration of ADL scores are preventable. Screening can greatly help as the first step in the process too. For example, preventing elderly patients from falling has been shown to reduce the use of home healthcare, and the associated costs.

Building off of related research, Minitab consultant David Patrishkoff set out to use Machine Learning to help detect ADL deterioration earlier in the process and address it accordingly.

In healthcare, interventions are activities or strategies (such as screenings or vaccinations) to assess, improve, maintain, promote or modify health of individuals or groups. David uses Minitab Statistical Software and Salford Predictive Modeler (SPM) to examine 1,200+ interventions and therapies that nurses and home care workers provide to people across the country, and select the best ones to maintain or improve their independence and their ADLs.

“I start in Minitab with data visualizations and clean up the data, then jump into SPM for the really heavy lifting of very complex data sets,” David said. “I have columns of data where I have one of any 83,000 prescriptions that are prescribed to people. There are 43,000 diagnosis codes too. The algorithms in SPM can deal with highly dimensional data.”

A Master Black Belt who began his career in the automotive industry, David has consulted in about 60 different industries worldwide and trained nearly 30,000 professionals in Lean Six Sigma and patient safety.

Applying Predictive Analytics to Problem-solving

David first began using TreeNet in SPM to enhance his research into causes of traffic accident injuries and deaths, and he is applying some of the same methods now to ADLs and home care.

There is a belief that you have to be a data scientist coding in Python and R to handle these kinds of problems, he notes, but that’s not necessarily true. David recommends learning to use predictive analytics software like SPM to see how you can do better root cause analysis.

David also credits the 64-bit version of Minitab 19 with helping him with larger data sets he was unable to work with in previous versions.

“It helped me tremendously,” he said. “I had old files that were too big and then with the 64-bit Minitab 19 it further helped my analysis.”

What’s Next?

David has been speaking at conferences about his research and how classic Six Sigma and operational excellence practitioners can build on their knowledge of statistical methods to take the next step into the data science revolution. He plans to present and publish further findings next year on how to provide home healthcare clinicians a stable methodology to improve patient outcomes.

Fewer X-Ray Errors Reduce Cancer Risk, Wait Time and Costs Evan McLaughlin 27

Evan McLaughlin 27 November, 2019

Clinicians examining a radiograph

In hospital and clinic settings, making the right decisions doesn’t just reduce costs from duplicative work and process inefficiencies — it results in better outcomes for patients. Think about needing to take an extra X-ray because the first captured the wrong foot. Even if it’s the right limb, what if they captured it from the wrong angle?

Over the 14 years he worked in healthcare quality improvement, Art Wheeler saw this and many other process improvement scenarios. Most recently, as decision support manager for quality improvement services at one of the country’s largest not-for-profit freestanding pediatric healthcare networks, he was the primary statistician, as well as a mentor and coach for Six Sigma Black Belts and Green Belts, program managers and project leaders for 8 1/2 years.

An expert in statistical quality control, one of his key responsibilities was ensuring data was collected in a way that was sound and ensured the best chances for detecting statistical significance of any reported improvements. He also developed the charts and writeups for the analysis sections of corresponding published articles and responded to reviewer questions or comments to help ensure acceptance.

Remember that extra X-ray scenario we mentioned earlier? Art served as a consultant on a duplicate X-ray study, which found each unnecessary scan cost facilities an extra $150 to $300 and overall patients were waiting longer. One study of 18 US pediatric emergency departments showed radiology errors are the third most common event in pediatric emergency research networks and human errors rather than equipment issues caused 87% of them.

Besides reducing errors, the team were also motivated to achieve their goal of zero errors at two clinics so they could also reduce lifetime radiation exposure for individuals, which in turn diminishes their risk of developing cancer. Efforts like this were part of the hospital’s “Zero Hero” program – they would measure the time period and the number of cases involved, aim to reduce incidents to zero and record how long they maintained zero incidents.

It wasn’t all black and white though. They needed to understand the context behind the duplicate X-rays to truly make improvements. With a retrospective review of a 14-month period at two facilities, they knew there were good and bad reasons behind the 170+ duplicate X-rays that were recorded, for a duplicate radiograph. Each duplicate radiograph was classified as …

  1. No error, where they intentionally studied from multiple views;
  2. Incorrect location, when the patient’s initial complaint did not match the initial radiograph (e.g. the aforementioned wrong foot);
  3. Incorrect laterality, when it’s the wrong side; or
  4. Unnecessary radiograph, a known issue when a clinical athletic trainer preordered multiple radiographs without physician evaluation and assessment.

The Pareto chart below shows the most common error during the 14-month period was incorrect location.

pareto-chart-radiograph-error-classification-resize

The quality improvement team took steps to meet their zero percent goal in both clinics, which included issuing surveys to patients and families during registration to help document where they needed to be X-rayed and if they had been X-rayed in the past.

The unnecessary radiograph was also a known issue when a clinical athletic trainer preordered multiple radiographs without physician evaluation and assessment. An intervention was made to fix this, making physicians responsible for putting their own radiograph orders in the Electronic Medical Record.

Overall these steps improved communication between physicians, clinical athletic trainers, radiology technologists, patients and families, and greatly contributed to better outcomes for everyone involved.

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