1. The first is the case study ( Quantitative Analysis )

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I have attached the Case – “Burn Care.” This is the “quantitative analysis” case, “Burn Care” is the hardest or second hardest case in the set of case studies we use -– it just rolled to the top again for this semester. Lucky you :)

A few thoughts on Burn Care...

You are a VERY-WELL recompensed consultant, hired by Mr. Warden the hospital CEO, to develop and analyze alternative strategies regarding the situation. Mr. Warden is the target audience for the report and presentation. The presentation will be in the typical PowerPoint (mostly uninterrupted) format.

As specified in the Case, “The corporation has a perfect Management Information System (Ha! Ha!). I am providing you with the necessary data to solve the problems. Your job is to reduce operating expenses by $500,000 without reducing the quality of care or services to patients. You must also avert the nurses' strike and maintain their long-term job satisfaction. You can implement any change, use any strategy to reduce your expenses. If your strategy involves capital expenditure, then it must be paid for with interest within three years by the additional savings in operating expenses."

For the Burn Care case your report should be the typical comprehensive “Capstone” report (as long as necessary, but no longer)

Let’s Review the Case

Job One --> The hospital was given a goal of reducing operating expenses by $500,000 for the burn care unit. (p. 2), based on 1994 hourly rates.

This is Larry’s favorite case, and there are a lot of ways to approach finding the reduction. But you must keep sub-standard care to a  minimum , and you want to prevent a nursing strike. Also, remember, you should be concerned about your continued ability to attract and retain qualified nurses – unless, that is, you want to get all of them from the agency pool (but are agency nurses as good? what about quality and continuity??).

A couple of more observations and/or subtleties I am concerned you might miss:

       On page 2, the case says --> In May 1993 Mr. Adams, the regional vice-president of the corporation and an accountant by training, wrote a letter to Mr. Warden, the CEO, that he

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should discontinue the Baylor Plan as it was costing about $800,000 more in nursing payroll. Obviously,  IF  Mr. Adams is correct, finding $500,000 in savings will be easy… right??? Or, is Mr. Adams just a stupid budget weenie in administration who doesn’t understand or even have a clue??

       Remember, the “Budgeted Daily Staffing Pattern” (p. 4) is based on an assumption of 30 ADC (“average daily census”), but what happens when ADC is higher/lower? How does the pattern change? And, remember, the budget model is based on the staffing standard of 22 hours per patient per day.

       Pay attention to this paragraph --> The hospital's budgeted nurse-staffing standard in 1996 was 22 hours per patient per day (HPPD). The staff nurses on the unit, however, generally complained that the staffing levels were not sufficient to provide quality care to the burn patients. In December 1996, the hospital implemented Medicus patient acuity system for staffing and adopted 3.5 hours of direct care per acuity point as its worked nurse-staffing standard. (Bold emphasis supplied.)

       Make sure you understand the work sampling data on page 5  :)

       Make sure you understand the “Census and Acuity Data by Pay-Period” on page 3 :)

       From page 6 --> Here we are assuming that only the regular staff makes overtime under the Baylor Plan. The Flex staff is generally a part-time staff and works 8- or 12-hour shifts without overtime but they receive benefits. Agency nurses do not earn overtime or benefits from the hospital.

       Obviously, regular employees are paid OT at 1.5x for hours worked over 40 in a week. If you suggest something besides the Baylor staffing model, make sure you are explicit about how that schedule will work for “regular” employees – 24x7 staffing is very, very hard and is typically not easily divisible by 40.

       What about sick leave, annual leave, etc. for regular employees. How does that fit in?

       You can use their “Guideline for Estimating Labor Expenses,” or develop your own method of calculating labor expenses. I found their method confusing and developed my own exact method (relatively straightforward in a spreadsheet) – it wasn’t until after I developed my own that I understood how/why their’s was “close enough.” I found my

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“exact method” made it easier to evaluate alternative strategies. If you develop your own, make sure you include an explanation of your approach in an appendix.

       One more abbreviation – ALOS = average length of stay.

 In a prior semester a student asked ,

 

"In your message, you state "Obviously, regular employees are paid OT at 1.5x for hours worked over 40 in a week." The case states that that OT is paid at 1.25x regular pay. Am I misunderstanding or is 1.5x the OT to be paid in the solutions we offer?"

 

Professor replies -- >

 

On page 1 the case says, "During the week, nurses worked 12-hour shifts for five days (Monday-Friday), thus working 60 hours and getting paid for 70 hours (because of overtime policy) with full-time benefits." Thus, time and a half for over 40.

 

But I suspect the student was referring to the Guideline for Estimating Labor Expenses starting on page 5 (but I don't know, because the student did not reference the source of his/her 1.25x understanding). The Guideline works because it is dealing with an aggregate number, but it uses the term "overtime" somewhat differently than just hours worked over 40 in a week. So, both answers are correct.

 

I prefer to breakout the groups and calculate salary individually for the various schedules, but you can do it either way (my way or the Guideline) -- just make sure you specify your methodology and assumptions.

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Ramblings

Well, still some time to go before this VERY DIFFICULT case is due. You should already have started. But here’s a hint or two to make sure you didn’t get started by heading in the wrong direction.

In short, this is how I would have started my thought process. Warning: I haven’t double checked my analyses or spreadsheets; this is my first cut, so there may be errors.

Remember, you need to recommend changes that will save $500K/year. To do that you need to develop a baseline cost estimate (a model) for what things cost now, and then use the model to create strategic cost estimates for what the annual cost would be under various changes in policy. Somehow you need to get to $500K in annual savings using one or more strategies.

Explorations and Meanderings

OK, I call this spelunking around the data files. Just following my hunches to see if I can better understand the case. After I get done with that I’ll see about developing the baseline cost estimate.

First I thought I’d play a bit with understanding the Daily Staffing Pattern data. We must be careful of these numbers – they are budgeting data,

not actual data, and are based on the old staffing assumption of 22 hours per patient @ 30 patients.

Note: 55 staff per day @ 12 hours per day = 660 hours; 30 patients / day * 22 hours of staffing = 660. So, those calculations jibe. Rah!!!

But, the “new” standard, as of December 1996 is 3.5 hours of DIRECT care per day per patient acuity point. So, I wonder, how many hours of DIRECT care does the “Daily Staffing Pattern” provide. To figure that out I figured I would have to mix together the “Daily Staffing Pattern” data and the “Percent Time Distribution by Task and Level” data.

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Ramblings

First, I re‐entered the “Daily Staffing Pattern” data. I turned the data around, and then I re‐calculated the information in hours. Note that I took the time to make it “pretty.” Why you ask? Because I figure that a fair number of these tables will find there way into my final report, so I might as well make them pretty now. Note also I calculated the “skill mix” ratio with and without the Head Nurse and USs, and for the two shifts separately. I might want that info later

Note that I don’t know whether the shifts start at 6 or 7 or whatever, but I’m just assuming 6, and it really won’t matter to the analysis.

Daily Staffing Pattern (in hours, by shift)

(in headcount, by shift)

HNs

RNs

LPNs

NAs

USs

TOTAL

HNs

RNs

LPNs

NAs

USs

TOTAL

6 am ‐ 6 pm

12

228

48

48

24

360

1

19

4

4

2

30

skill mix

3.3%

63.3%

13.3%

13.3%

6.7%

100.0%

3.3%

63.3%

13.3%

13.3%

6.7%

100.0%

skill mix (no HN or US)

70.4%

14.8%

14.8%

100.0%

70.4%

14.8%

14.8%

100.0%

6 pm ‐ 6 am

0

228

48

0

24

300

0

19

4

0

2

25

skill mix

0.0%

76.0%

16.0%

0.0%

8.0%

100.0%

0.0%

76.0%

16.0%

0.0%

8.0%

100.0%

skill mix (no HN or US)

82.6%

17.4%

0.0%

100.0%

82.6%

17.4%

0.0%

100.0%

Daily

12

456

96

48

48

660

1

38

8

4

4

55

skill mix

1.8%

69.1%

14.5%

7.3%

7.3%

100.0%

1.8%

69.1%

14.5%

7.3%

7.3%

100.0%

skill mix (no HN or US)

76.0%

16.0%

8.0%

100.0%

76.0%

16.0%

8.0%

100.0%

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Ramblings

While working with the table I make note of a couple of things that may prove to be of future interest

· The hospital uses a lot more RNs than LPNs, although LPNs are cheaper.

· The hospital isn’t using any NAs (nursing assistants) on the overnight shift.

Nextmitewas ti to play with the “Percent Time Distribution by Task and Level.” I entered the data in a separate table in my spreadsheet, with

formulas (‘cuz I might need to change it later!), and I added a column for HNs, “guessing” at how they might spend their time.

Task Category (percent of time)

HNs RNs LPNs NAs USs

Direct:

0%

42%

58%

50%

0%

Professional

0%

22%

28%

10%

0%

Non‐Professional

0%

20%

30%

40%

0%

Indirect:

0%

32%

26%

35%

70%

Professional

0%

20%

16%

5%

0%

Non‐Professional

0%

12%

10%

30%

70%

Unit‐Based

92%

18%

7%

5%

20%

Personal

8%

8%

9%

10%

10%

Total

100%

100%

100%

100%

100%

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Ramblings

While working with the table I make note of a couple of things that may prove of future interest

· I don’t know what US stands for, but I note that they provide no Direct or Professional services. I guess I will think of them as clerical types – “un‐skilled” in the sense of nursing skills.

· I also note that LPNs provide a fair amount more direct service than RNs, but, as we know from above, the hospital isn’t using LPNs very much.

At last I can get back to my earlier question – How many hours of DIRECT care does the “Daily Staffing Pattern” provide. When I use the info in the two tables above together (multiplying number of hours per day by % of time spent on direct care for each category), I discover

Daily Direct Service Hours

HNs

RNs

LPNs

NAs

USs

TOTAL

0.0

191.5

55.7

24.0

0.0

271.2

daily service hours per patient =

direct service supports this average acuity

level per patient =

9.04

2.58

Recall, the budget staffing plan was based on 30 patients, so 9.04=271.2/30.

And, the “new” worked nurse‐staffing standard calls for 3.5 hours of direct care per patient acuity points, so this staffing pattern can cover 30 patients with an average acuity level of 2.58 (9.04/3.5).

Now, I wonder, what is the “average acuity level” per patient... Guess I ought to play with that next.

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A student question (below) and my answer.

As suggested in class, you will want to understand the differences between RNs and LPNs, so I deliberately do not address that aspect of your question.

 

Re: the NAs and USs, I could give you examples, but they would be a guess, and your guess is probably as good as mine. I’m not sure that however you answer your question, it will lead you in a useful direction; I could be wrong.

 

Another Hint:   yesterday a student asked about using technology to make the nurses, etc., more productive. The student referred to my typical “today’s technology at today’s prices” case instructions. Hmmm, note that this instruction was NOT included in Burn Care. That’s because the case already includes a technology-based option for increasing nurses’ direct care productivity – the TSS. That is the only technology option that should be considered.

 

Yet Another Hint : In a prior semester, a student proposed trying to reduce costs by trying to negotiate prescription drug prices with the Big Pharmas. While such WAY, WAY “out of the box” suggestions can certainly be included in the list of alternatives you add in at the end [and I’ve got a couple of more viable/plausible ones in mind that you probably should have thought of yourself], don’t rely on them to replace a thorough analysis of the possible staffing solutions/strategies. Remember, there are no silver bullets and you can’t assume you will win the lottery: )  [Heh, if the Feds and Medicare can’t twist the arm of Big Pharmas, do you think one hospital can???]

 

From:  a student Subject: Question re Task categories

 

I had a question about the "professional" and "non-professional" subcategories. Could you give an example of what a "non-professional" task might be in both the "direct" and "Indirect" categories? 

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Answer to second question – What are you adding together to get the 236K? Check your worked hours by class by type against my page 6 table – do they match. If I had to guess I would suspect your formulas for the Regular nursing staff were somehow a little bit wrong, but it also could be with your formulas for Flex and Agency.

From: a student Subject: Re: Probably a fatal error

A follow-up...if the total hours worked by source is 234,004.0, shouldn't the annual total hours for each of the by-source-by-type (bottom row of regular HN through Agency NA) equal 234,004? It currently totals to around 236k. When you subtract out the 168+672 in the formulas for Agency and Flex, then the totals equal out. Is this significant, or am I just down an unnecessary rabbit hole?

OK, now back to your first question.

1. Columns 5-8 of the page 6 table show Worked Hours by Type based on the reported FTEs.

2. Since there were no HN or US hours for Flex or Agency why would I subtract them out?

3. Note that 0.76 + 0.16 + 0.08 = 1.0 (100%).

From: a student Subject: Probably a fatal error

Hello and Happy Saturday, 

I'm rethinking most of my numbers after receiving Ramblings 3. I think I have most of my formulas straight, but there's one thing I can't wrap my mind around. Perhaps you can't answer, but I figured I would try...

In the "Census and Acuity Data by Pay-Period" table, the way I have my formula set up for regular employees is basically: [the fraction of total hours worked by regular employees in that period, or "regular/total"] * [the percentage of the type (RN, LPN, NA)] * [total hours - hours worked by HNs and USs (168+672 without formulas)]. All my numbers came out the same as yours in that section. 

However in the Flex-Pool and Agency sections, it seems like your numbers don't subtract out that 168+672. I understand that the Flex and Agency Pools are not providing HNs or USs, but why wouldn't we still account for the HN and US contribution to total hours? To get to those 76, 16, 8 percent of hours worked in a given shift by RNs, LPNs, and NAs, (as I understand it), we subtract the hours worked by HNs and USs from the total in the formula...so I'm having a hard time understanding why we wouldn't use that same pattern when we're talking about total annual hours. 

 

Any clues you can give would be more than welcome. Thanks and have a good weekend.

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