Read Case 13 in the Pruitt, Smith, & Perez-Ruberte text and answer the Discussion Questions associated with the case.

Week2-Assignment21-Case13-ReducingPatientFalls.pdf

Home >Business & Finance homework help >Operations Management homework help >Read Case 13 in the Pruitt, Smith, & Perez-Ruberte text and answer the Discussion Questions associated with the case.

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

238

Case 13: Reducing Patient Falls: The Sleuth Resident

OBJECTIVES

1. Describe how generating hypotheses can support the quality management process. 2. Examine collaboration among caregivers and quality management leaders. 3. Analyze patient safety data using quality management problem analysis tools. 4. Identify causes of variation in patient safety outcomes and relevant safety-enhancing technologies. 5. Evaluate efforts to overcome complacency with current patient safety performance.

INTRODUCTION

Patient falls are a leading Sentinel Event that are required to be reported by hospitals to The Joint Commission, the accreditation organization (The Joint Commission, 2019). Thousands of patients of acute care and rehabilitation hospitals are injured in falls that cause at least some sort of injury (Bouldin et al., 2013; Oliver, Healey, & Haines; 2010). The Centers for Medicare and Medicaid no longer pays hospitals for costs related to patient falls, which they consider preventable (Centers for Medicare and Medicaid Services; 2018). For these reasons, healthcare organizations seek to identify the root causes for patient falls and develop best practices for preventing them.

Red Valley Clinic is a large academic medical center that has served the Greater Red Valley metro area for 80 years. It has three large hospitals (300–500 beds each) and 28 medical group practices ranging from primary care to specialists, such as ophthalmologists, endocrinologists, orthopedic surgeons, and physical rehabilitation. Out of the three large hospitals, St. Xavier Memorial Hospital is the one that has been in operation the longest, and it is the flagship of Red Valley Clinic. Five years ago, Red Valley Clinic invested close to US$200 million to expand and update St. Xavier Memorial to modern standards. After the renovation, St. Xavier Memorial became a 340-bed hospital.

DATA FILE FOR CASE 13

Data files for students are available by accessing the following url: https://www.springerpub.com/hqm The data file for Case 13 provides summary data for 24 months of patient falls for one hospital by unit. Also includes total falls and averages for

five hypothesized root causes (patient age, bed age, acuity, RN years of experience, and average census) for each of the 15 patient units. Ideal data for creating scatterplots.

CASE SCENARIO

“Another month, another great review!” said Dr. Sanjeep Metha, a third-year resident at Red Valley Clinic as he came out of their monthly operations review. He high-fived his friend and colleague, Dr. Carson Stanley, another third-year resident at Red Valley who begrudgingly joined his friend’s hand in the air. Dr. Stanley was visibly troubled.

“What’s wrong?” inquired Dr. Metha. “Did you not like that glowing review of our units? In the past year, we almost eliminated infections, reduced length-of-stay, and increased revenue for the organization. Seven more months and we will be writing our own ticket, man! Cheer up!”

“Yes, I agree,” replied Dr. Stanley, “that our teams have done some great work on those fronts, but, does it not bother you how poorly we are doing on patient falls?”

“Oh, man, here we go! Why do you always insist on fixating on the negative?” asked Dr. Metha. “Well, for one, because that is a huge patient safety issue. Plus, I know we can do better,” Dr. Stanley answered. “Man, I can’t hang out with you when you are being Mr. Negative! I’ll catch up with you later, OK? We’ll celebrate!” said Dr. Metha as he bid farewell

to his friend and went down a different hallway. Dr. Stanley continued walking down the wide, well-lit, pristine clinic hallway, deep in thought. He did not notice the nurses coming and going, the

family who came out of one of the rooms full of joy, getting ready to get Dad home today, or the environmental services tech cleaning the spill into which he almost stepped. After a few minutes walking, he realized he had no idea how he got there. He then turned around and went back to his office to review the charts of the patients on whom he had to round.

The reason troubling Dr. Stanley was that over the 3 years he has been a resident, patient falls throughout St. Xavier Memorial have remained constant at between 30 and 40 every month. Not only is this number significantly higher than the national benchmark of 3.56 falls per 1,000 patient days (Bouldin et

https://www.springerpub.com/hqm

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

239

240

al., 2013), but for Dr. Stanley, one fall is too many. He needed to find a way to reduce falls. He set an ambitious goal to reduce patient falls by half over the next 18 months.

Dr. Stanley knew he first needed data to try to find some opportunities to reduce patient falls. He enlisted the help of Dan Stroman, a young, wide-eyed data analyst in the Process Excellence department to get him some data. “Sure thing, Dr. Stanley,” was Dan’s enthusiastic response. “Just let me know what you need.”

Dr. Stanley asked Dan to give him the falls data for the last 2 years by nursing unit for St. Xavier Memorial Hospital. He was delighted when, upon returning to his office that evening, he had an email from Dan Stroman with the subject, “Patient Falls data you requested.” Dr. Stanley thought, “Man this guy works fast,” as he smiled and opened the email (see Case 13 Data file provided in the Instructor’s and Student ancillary materials).

Upon studying the data, it was immediately obvious to Dr. Stanley that some nursing units were more prone to patient falls than others. He made the decision right then to find out the differences between nursing units and determine which, if any, of those differences could explain the higher numbers of falls for some units. Like a good quality improvement sleuth, Dr. Stanley knew that there is no substitute for “going and seeing for yourself.” So, the following day, he visited not only those units on which he normally rounded, but other units as well. He introduced himself and engaged with the staff there (nurses, transporters, techs). As part of his conversations with them, he always asked one of two questions, depending on the number of falls in that unit:

1. What do you think contributes to your low number of patient falls? 2. What do you think contributes to your high number of patient falls? He listened to their many theories and set out to test them with data. Dr. Stanley generated hypotheses that could be proved or disproved using the data

file. He was determined to get answers for his questions.

Hypothesis A: Older Patients Fall More Often

One day, while rounding on 4-West, Dr. Stanley asked the charge nurse, “What do you think contributes to your high number of patient falls?” “Oh, I know exactly why we have such a high number of falls every month,” she answered. “It’s because we have the oldest population of patients in the

whole hospital! Older patients are more prone to falls. It’s that simple.” Dr. Stanley went back to his office and called Dan Stroman. “Hello Dan! It’s Dr. Stanley!” “Hello, Dr. Stanley! How can I help you today?” Dan said with his usual excitement. “Could you pull the average age of the patients by unit for the last 2 years?” Dr. Stanley asked. He paused for a moment, and when Dan did not

immediately answer, he added, “It does not have to be by month, just an average for the whole year, by unit, for the last 2 years.” “Okay, let me see what I can do,” replied Dan as he started helping Dr. Stanley in his quest. The next morning, Dr. Stanley walked in to an email from Dan. He opened and studied the data. He wanted to find out if there was positive correlation

between patient age and number of falls by unit. He knew that an easy way to do that is by using a scatterplot, so he plotted the data and studied the result.

Hypothesis B: Older Beds Cause More Patient Falls

While rounding the Surgery floor another day, Dr. Stanley asked one of the staff nurses in 2-East, “What do you think contributes to your low number of patient falls?”

“Well, we have some really well-trained staff and everyone is on their toes and when there is a bed alarm, we hustle!” replied the nurse. “I think that the new beds have definitively had an impact.”

“New beds? What do you mean by that?” asked Dr. Stanley. “Yes, a few years ago, about 4 or 5 years ago, we got these new beds,” she started walking toward an empty room so she could show Dr. Stanley. “They

have a lot of nice features, and all the alarms work great! Bed alarms alert personnel when a patient at risk for a fall attempts to leave the bed without assistance. When I was upstairs in 4-North, half of those beds did not have alarms.”

“Really?” was Dr. Stanley’s response as he considered his next data request. Dr. Stanley went back to his office and got on the phone with Dan Stroman. “Hello Dan! This is Dr. Stanley, how are you?” “Doing great, Dr. Stanley,” replied Dan. “What can I do for you?” “Do you have any way to find out how old the beds are in each unit?” asked Dr. Stanley. “Hmm, that, hmm, that’s a new one!” replied Dan, sounding stumped. “Do you know of anyone who could have that kind of data, short of me having to go unit by unit asking the nurse managers?” Dr. Stanley kept the

conversation going. “Well, maybe Jan from facilities could help. You could ask her if they keep that information. Would you like her contact information?” Dan asked in an

attempt to get out of having to go trying to find these data. “Well, I don’t really know Jan,” replied Dr. Stanley. “Do you have a good working relationship with her?” “Man! This guy is going to make me go hunting for data for his little quest, isn’t he?” was Dan’s thought. He let out a sigh and responded, “Let me ask

her if they keep that information or if she can point me in the direction of someone who can. Give me a few hours, or maybe until tomorrow and I will let you know what I find,” Dan said.

While he waited for the data, Dr. Stanley could not help but wonder what the data would tell him. Could it be that there was a correlation between the age of beds and patient falls?

Hypothesis C: Higher Acuity Patients Are More Prone to Falls

As Dr. Stanley rounded on 5-West, he found a group of team members at the nursing station. The group included the charge nurse, two staff nurses, and a patient care tech. He asked them how their day was going and engaged them in conversation. When he got to his question, “What do you think is causing your high number of patient falls?” the group fell silent for a brief moment. One of the staff nurses broke the silence. “We have really complex patients on this unit!” she said. The others nodded in confirmation. “We probably have some—if not the highest-acuity patients in this facility. Our patients are really, really sick, and sicker patients are harder to manage in all aspects, including falls.”

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

241

242

Dr. Stanley thanked them and went back to his office, pondering this along the way. In his office, he picked up the phone and called Sara Mullins, Chief Nursing Officer for St. Xavier. “Hello Ms. Mullins! It’s Dr. Stanley. How are you?”

“I’m doing great, Dr. Stanley,” replied Mullins. “What’s on your mind?” “As you may have heard, I am doing an in-depth study on patient falls in our hospital, and I have been gathering some data to try to pinpoint several

areas for opportunities. I have a question for you; it’s kind of a two-part question. How do we rate patient acuity? Does every patient get assigned an acuity rank? And, if so, are that data available retrospectively? I guess it was more of a three-part question” Dr. Stanley finished, smiling.

“Well, we use QuadraMed® scores,” responded Mullins. “Yes, every patient should get a score assigned, based on their current condition, their present illness and things like comorbidities, among others. And, for the third part of your question, yes, the data can be pulled from the EMR. We have reports we run routinely on this. What are you thinking?”

“This is great!” replied Dr. Stanley. “One of the hypotheses I am interested in testing is whether more complex, or higher acuity, patients are more prone to falls. This came up in my conversations with some of the nurses on one of those units that have historically struggled with patient falls. How can I get my hands on these data?”

“Lindsey McAllen in Nurse Informatics is the expert and owner of these data. She should be able to help you. By the way, I am very interested in knowing what you find out, so, please, keep me in the loop! I have my own opinions about this, but I will wait and see where the data take us. Please, do not hesitate to reach out if you need anything else.”

“Will do! Thank you, Ms. Mullins!” “Lindsey?” asked Dr. Stanley on the phone. “Yes …” answered Lindsey McAllen with a hint of a question. “Sorry, this is Dr. Stanley, one of the residents. Sara Mullins gave me your information for some data requests I have.” “Oh, yes, Dr. Stanley! How can I help you?” replied Lindsey. “Well, I am interested in getting the average patient acuity,” continued Dr. Stanley, “the QuadraMed score by nursing unit for the last 2 years. Is it

possible to pull an average for the whole year by unit?” “I’ve never done that, but I don’t see why it would not be possible. We can pull it weekly and monthly, so, it should be pretty straightforward to pull it

for the year. You just need one number for the whole year?” “Yes,” replied Dr. Stanley. “Well, one number for the whole year, by unit, for the last 2 years.” “Right, right!” replied Lindsey. “I’m in the middle of something right now, but let me play with it and I will get back to you.” “Great! Thank you, Lindsey!” said Dr. Stanley. As they hung up, Dr. Stanley pondered whether the data would corroborate or disprove the theory that

higher acuity patients are more vulnerable to falls.

Hypothesis D: Less Experienced Nurses Contribute to Higher Number of Patient Falls

Dr. Stanley’s investigation took him to the third floor. While on 3-West, he went to the nurse manager’s office, Rebecca Nieves, after he could not find anyone with whom to have a conversation and ask some questions. Her door was open. He peeked inside and, since she did not appear to notice him, he knocked on the door.

Rebecca turned her head down and looked at him over her glasses. “Yes, Dr. Stanley! What brings you around to this side of the tracks?” she asked, while keeping her fingers on her keyboard.

“Hello, Rebecca. How are you?” asked Dr. Stanley. “Argh! I am working on this serious event report I have to file and the amount of data and information I need to type in is so much!” Rebecca said while

her eyes went back to her computer screen. “Oh, then, maybe I should come back when it is a better time for you,” said Dr. Stanley genuinely understanding her situation. “No, no, no, no!” replied Rebecca, taking her glasses off and motioning him to stay and come closer. “Come! Tell me. What’s on your mind?” “Thanks,” added Dr. Stanley. “I’ll try not to take too much of your time. I am doing an investigation into patient falls and trying to find some

opportunities on which we can improve. So, I just have one simple question for you. What do you think contributes to your high number of patient falls?”

“Wow! You went straight for the jugular on that one!” said Rebecca with a smile. “No, in all seriousness, you are right. We do have a high number of falls and while there are several things we have tried with some mixed results, I think it all comes down to experience. I mean, I have one of the youngest staff in this hospital. Don’t get me wrong! I love my staff, and they are all trying as hard as they can, but sometimes there is something to be said about being an old fox, like me. More experienced nurses have seen it all and can plan better and, in my opinion, are better prepared to handle different situations, including preventing patient falls. There are things that the chart does not tell you. If you just go by the fall risk score from the chart, you may miss a few things, and this is where experience comes in handy.”

“I knew you would have some insight! Thank you Rebecca!” said Dr. Stanley as he left Rebecca’s office. He made a few notes in his tablet and continued with his rounds.

When he came back to his office that afternoon, Dr. Stanley picked up the phone and called Sara Mullins, Chief Nursing Officer for St. Xavier. “Hello Ms. Mullins! It’s Dr. Stanley. Do you have a few minutes?”

“Sure thing, Dr. Stanley!” replied Mullins. “What’s on your mind?” “I have been interviewing some more staff and had another idea. Do we track anywhere how many years of experience our nursing staff has?” “Ooh, that’s a good one!” replied Mullins with an air of mystery and a smile Dr. Stanley could feel over the phone. “You can probably start with Kevin

Stanton, Director of Team Resources. They keep all those records, although I am not sure how easy it is to pull the data. Kevin can definitively tell you.” “Thank you very much, Ms. Mullins!” replied Dr. Stanley. Dr. Stanley immediately dialed Kevin Stanton expecting to leave a message, given how late in the day it was. To his surprise, Kevin Stanton picked up

the phone. “Oh, um, Mr. Stanton! I’m sorry I was expecting to leave a message on your voicemail. This is Dr. Stanley, one of the residents here at St. Xavier. May I trouble you for a few minutes, sir?”

Kevin Stanton was literally already packed up and leaving the office when the phone rang, so, he placed his laptop bag on top of the desk and sat back down. “I have a few minutes, sure!” he said with a grunt, as he sat down.

“Thank you, I will be brief. As you may have heard, I am doing a study on patient falls in our hospital, and I have been gathering some data to try to pinpoint several areas for opportunities. My latest investigations have pointed me in the direction of looking into the years of experience of our nursing staff.

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

243

244

Do we track anywhere how many years of experience our nursing staff has? I would like to get, if possible, the average years of experience of the nursing staff on our hospital, by unit, for the last 2 years.”

Kevin had both elbows on his desk, holding the phone on his left ear and stroking his forehead with his right hand. Since there was silence, which Dr. Stanley interpreted as hesitation or confusion, he added, “Basically, I am just looking for one number by unit (the

average years of experience of the nursing staff) for the last 2 years, just one number by year for each individual unit.” “Yeah, yeah …” responded Kevin. “I am thinking about this … hmm. Listen; let me have a word with Alberto, our analyst. Alberto …” (Kevin

was trying to remember his last name) “Rodríguez! I’ll try to talk to him tomorrow to explain what you are looking for, and I’ll put him in touch with you. How’s that?”

As they hung up, Dr. Stanley was excited at the prospect of getting his hands on the data and trying to find some clues as to whether nursing experience really has an impact on patient falls. He had to wait a little bit more than 24 hours to get it, however. Two days later, when he checked his email first thing in the morning, Dr. Stanley found an email from Alberto Rodríguez.

Dr. Stanley, I hope this is the data you need. If it is not, or if you need a different pull or slice of the data, please, let me know. Thank you very much! Alberto Rodríguez Dr. Stanley opened the attachment and went to work on this latest data gold mine.

Hypothesis E: Units With Higher Daily Census Are More Vulnerable to Patient Falls

Dr. Stanley went up to the sixth floor, to round the neuro units. While there, he talked to the nurse manager, the staff nurses, case managers, and patient care techs, always finding a way to ask about patient falls. When he asked, “What do you think contributes to your low number of patient falls?” he heard that floor nurses on that floor had it “relatively easy.” When he continued probing, one staff nurse offered, “Well, I know in most of the floors below, the nurse- to-patient ratio could be as high as 1:5 or even 1:6 sometimes. They have units with really high daily census downstairs. Up here, it is rare if we ever get close to 20 patients, and we have five staff nurses. I would be willing to bet that those units with higher census probably have more falls, don’t you think?”

“Actually, I know of a great way we can find out,” he replied, already planning his next data request for Dan Stroman. “Dr. Stanley, how can I help you now, sir? You still acting like a patient falls detective?” asked Dan with a hint of cynicism. “Darn it! I thought I was

done with this guy. I’m pretty sure he thinks I work for him,” is what he was really thinking. “Hi Dan! Yes, I am still on my search. I know I have made many requests from you, and I appreciate your help very much. Let’s hope this is the last one.

Could you get me the average daily census by unit for the last 2 years?” Dr. Stanley asked. “Ah! I see where you are going with that, Doctor! Listen, I am working on a large simulation project for the Emergency Department. Is it okay if I get

you your data by Friday this week?” “Sure thing, Dan! I appreciate it a lot!” said Dr. Stanley, already pondering what the data would tell him. Would it corroborate or disprove the theory that

higher census units are more vulnerable to patient falls? He could not wait to see the data and play with it! As Dr. Stanley waited for the data, he could not help but notice he followed a repetitive process every time he was testing a hypothesis (Figure C13.1).

He noted everything started with a theory, the hypothesis that needed to be tested. How did he test it? Gathering and analyzing data, mostly through the use of scatterplots. In the end, he was able to make conclusions about each of the hypotheses with respect to their validity and identify potential interventions to attack those root causes that were uncovered as some of his hypotheses were proven correct.

Figure C13.1 Hypothesis-testing process.

DISCUSSION QUESTIONS

1. What other potential root causes might influence patient falls?

2. Equipped with the data, what would you do about the hypotheses that proved to be unsupported?

3. Based on the correctly identified hypothesis in the case scenario, what would be your course of action if you were the CEO/president of St. Xavier Memorial Hospital?

4. What do you think of the CNO’s (Sara Mullins) position of “waiting and seeing what the data tell us” instead of immediately jumping to conclusions?

PODCAST FOR CASE 13

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

Persona l use on

ly, do no t reprodu

ce.

2020-11 -07

jennifer. naegele

18@gm ail.com

245

246

247

Listen to how experts approach the topic (you can access the podcast by following this url to Springer Publishing Company Connect™: https://connect.springerpub.com/content/book/978-0-8261-4514-7/front-matter/fmatter2)

REFERENCES

Bouldin, E. D., Andresen, E. M., Dunton, N. E., Simon, M., Waters, T. M., Liu, M.,…Shorr, R. I. (2013). Falls among adult patients hospitalized in the United States: Prevalence and trends. Journal of Patient Safety, 9(1), 13–17. doi:10.1097/PTS.0b013e3182699b64

Centers for Medicare and Medicaid Services. (2018). Hospital-acquired conditions. Retrieved from https://www.cms.gov/Medicare/Medicare-Fee-for- Service-Payment/HospitalAcqCond/Hospital-Acquired_Conditions.html

The Joint Commission. (2019). Sentinel event data summary. Retrieved from https://www.jointcommission.org/assets/1/6/Summary_4Q_2018.pdf Oliver, D., Healey, F., & Haines, T. P. (2010). Preventing falls and fall-related injuries in hospitals. Clinics in Geriatric Medicine, 26(4), 645–692.

doi:10.1016/j.cger.2010.06.005