1 00:00:00,000 --> 00:00:02,430 The following content is provided under a Creative 2 00:00:02,430 --> 00:00:03,730 Commons license. 3 00:00:03,730 --> 00:00:06,060 Your support will help MIT OpenCourseWare 4 00:00:06,060 --> 00:00:10,090 continue to offer high-quality educational resources for free. 5 00:00:10,090 --> 00:00:12,690 To make a donation or to view additional materials 6 00:00:12,690 --> 00:00:16,560 from hundreds of MIT courses, visit MIT OpenCourseWare 7 00:00:16,560 --> 00:00:17,744 at ocw.mit.edu. 8 00:00:25,750 --> 00:00:28,410 BO MADSEN: Continuous process improvement-- 9 00:00:28,410 --> 00:00:30,160 we're going to need some improvement here. 10 00:00:30,160 --> 00:00:34,330 Can we agree on that, or did it flow seamlessly? 11 00:00:34,330 --> 00:00:37,510 You're happy? 12 00:00:37,510 --> 00:00:41,080 Maybe it feels like something you're already used to so hard 13 00:00:41,080 --> 00:00:43,450 to see the difference. 14 00:00:43,450 --> 00:00:46,960 So at the end of this, you should 15 00:00:46,960 --> 00:00:52,360 recognize the PDSA or PDCA-- 16 00:00:52,360 --> 00:00:54,860 Plan-Do-Study-Act some of your notes. 17 00:00:54,860 --> 00:00:56,710 I think say, Plan-Do-Check-Act. 18 00:00:59,370 --> 00:01:01,630 It really, it is the same. 19 00:01:01,630 --> 00:01:04,440 We just like the study better than the checking. 20 00:01:04,440 --> 00:01:06,870 And because you need to see-- 21 00:01:06,870 --> 00:01:10,000 follow up on what your changes they actually mean. 22 00:01:10,000 --> 00:01:11,460 We'll get to that. 23 00:01:11,460 --> 00:01:13,650 A bit about A3 thinking-- and there's 24 00:01:13,650 --> 00:01:16,200 a lot more about that tomorrow. 25 00:01:16,200 --> 00:01:23,190 But it is an effective improvement process approaches. 26 00:01:23,190 --> 00:01:27,510 And you should be able to use a framework, continuous process 27 00:01:27,510 --> 00:01:30,660 improvement framework for bettering your system. 28 00:01:30,660 --> 00:01:33,240 You should be able to apply the value stream 29 00:01:33,240 --> 00:01:36,240 mapping did a little bit about that yesterday. 30 00:01:36,240 --> 00:01:38,520 I know it was short, and you'll do some more now, 31 00:01:38,520 --> 00:01:43,290 so it should help you get that concept more under the skin. 32 00:01:43,290 --> 00:01:46,660 And then we'll do some root cause analysis as well. 33 00:01:46,660 --> 00:01:50,610 And we talked about the five whys yesterday. 34 00:01:50,610 --> 00:01:52,620 We'll get into that more now. 35 00:01:52,620 --> 00:01:56,160 So what is it this Plan-Do-Study-Act? 36 00:01:56,160 --> 00:02:01,620 Well, it's something that we use because for improvement. 37 00:02:01,620 --> 00:02:05,250 And you use it as a problem-solving tool. 38 00:02:05,250 --> 00:02:07,590 And you use it as something that will give you 39 00:02:07,590 --> 00:02:12,180 an overview of what you're doing now, how you plan your changes, 40 00:02:12,180 --> 00:02:14,880 and then actually doing those changes, 41 00:02:14,880 --> 00:02:18,080 and remembering to follow up on it. 42 00:02:18,080 --> 00:02:21,930 It's also so that we try to solve problems in the same way. 43 00:02:21,930 --> 00:02:25,590 Because that way, it's easier to integrate work 44 00:02:25,590 --> 00:02:26,830 in the organization. 45 00:02:26,830 --> 00:02:30,390 And instead of working in silos, you can work across everybody. 46 00:02:30,390 --> 00:02:32,560 It's using the same methodology. 47 00:02:32,560 --> 00:02:37,260 The A3 thinking is built on the same as well. 48 00:02:37,260 --> 00:02:42,510 So A3 thinking-- collaborative problem-solving approach-- 49 00:02:42,510 --> 00:02:46,170 and it gives us a logical approach 50 00:02:46,170 --> 00:02:49,540 to how to solve problems. 51 00:02:49,540 --> 00:02:53,250 It tells you something about where are we now? 52 00:02:53,250 --> 00:02:56,100 What is the strategy of our organization? 53 00:02:56,100 --> 00:02:58,620 Where is it that we want to go? 54 00:02:58,620 --> 00:03:00,600 And how do we plan to go there? 55 00:03:03,760 --> 00:03:06,850 Do you know what A3 stands for? 56 00:03:06,850 --> 00:03:07,790 AUDIENCE: Paper size. 57 00:03:07,790 --> 00:03:08,998 BO MADSEN: It's a paper size. 58 00:03:08,998 --> 00:03:11,940 Yeah, exactly-- you know A4 paper? 59 00:03:11,940 --> 00:03:14,360 So in Europe, we don't use the letter form. 60 00:03:14,360 --> 00:03:17,570 We have something called A4, double-size A4, 61 00:03:17,570 --> 00:03:21,560 it's double-size letter is an A3. 62 00:03:21,560 --> 00:03:27,620 So A3 thinking is your plan for improving something 63 00:03:27,620 --> 00:03:29,900 that fits within an A3 size. 64 00:03:29,900 --> 00:03:33,530 So it forces you to be very concise. 65 00:03:33,530 --> 00:03:38,090 You can't go on rambling about this, that, or the other. 66 00:03:38,090 --> 00:03:40,610 Because there's simply no room for it. 67 00:03:40,610 --> 00:03:44,160 And it does fit within that size-- 68 00:03:44,160 --> 00:03:46,380 takes a little bit of practice, maybe. 69 00:03:46,380 --> 00:03:47,460 But it does. 70 00:03:47,460 --> 00:03:52,870 And again, what is so important about it 71 00:03:52,870 --> 00:03:57,690 is is well, if everybody in your organization is using this, 72 00:03:57,690 --> 00:03:58,920 you can collaborate. 73 00:03:58,920 --> 00:04:01,140 Because that your partners-- 74 00:04:01,140 --> 00:04:03,750 they are thinking the same way as you 75 00:04:03,750 --> 00:04:08,120 are, which is really important. 76 00:04:08,120 --> 00:04:11,810 If you think about it, how it is now in many places, 77 00:04:11,810 --> 00:04:14,810 people-- they solve problems totally different. 78 00:04:14,810 --> 00:04:20,060 Some departments they have a chair, who's maybe a dictator. 79 00:04:20,060 --> 00:04:23,540 This is a problem, this is how you'll fix it. 80 00:04:23,540 --> 00:04:25,250 Others say OK, let's sit down. 81 00:04:25,250 --> 00:04:26,810 Let's think about how we can do this. 82 00:04:26,810 --> 00:04:29,192 And you brainstorm, and maybe you 83 00:04:29,192 --> 00:04:31,400 come up with who does what, or maybe you just come up 84 00:04:31,400 --> 00:04:33,775 with a lot of ideas that are sitting there and collecting 85 00:04:33,775 --> 00:04:35,510 dust. 86 00:04:35,510 --> 00:04:37,280 But this gives you really a platform 87 00:04:37,280 --> 00:04:39,410 to do it the same way-- 88 00:04:39,410 --> 00:04:42,080 everybody, which is nice. 89 00:04:42,080 --> 00:04:49,610 And part of that in this A3 thinking or your plan here is 90 00:04:49,610 --> 00:04:52,130 the Plan-Do-Study-Act. 91 00:04:52,130 --> 00:04:58,580 It is a piece of how you solve problems and improve processes. 92 00:04:58,580 --> 00:05:01,110 But it's only a piece of it. 93 00:05:01,110 --> 00:05:06,820 It is not the answer-all questions. 94 00:05:06,820 --> 00:05:08,570 So don't take it as such. 95 00:05:08,570 --> 00:05:15,580 So for the continuous process improvement, the framework 96 00:05:15,580 --> 00:05:17,350 here, there are a number of steps 97 00:05:17,350 --> 00:05:22,510 we will get through them as we go along here. 98 00:05:22,510 --> 00:05:26,970 But first, do we perceive the problem? 99 00:05:26,970 --> 00:05:30,050 Do we understand what the problem is? 100 00:05:30,050 --> 00:05:33,510 That's important before you start improving anything, 101 00:05:33,510 --> 00:05:35,040 you know what they say. 102 00:05:35,040 --> 00:05:41,880 So all improvement is a change, not all change is improvement. 103 00:05:41,880 --> 00:05:45,020 So you need to find out what your problem is 104 00:05:45,020 --> 00:05:47,450 to improve the right thing. 105 00:05:47,450 --> 00:05:53,210 So you need to grasp the current situation. 106 00:05:53,210 --> 00:05:55,360 How do you do that? 107 00:05:55,360 --> 00:05:59,802 How is it we find out what the current situation is? 108 00:05:59,802 --> 00:06:01,712 AUDIENCE: [INTERPOSING VOICES] 109 00:06:01,712 --> 00:06:02,670 BO MADSEN: You observe. 110 00:06:02,670 --> 00:06:03,833 Where do you observe? 111 00:06:03,833 --> 00:06:04,500 AUDIENCE: Gemba. 112 00:06:04,500 --> 00:06:06,840 BO MADSEN: In Gemba-- 113 00:06:06,840 --> 00:06:10,200 where the actual people do the actual work 114 00:06:10,200 --> 00:06:12,090 in the actual place. 115 00:06:12,090 --> 00:06:14,970 There you go-- the three actuals. 116 00:06:14,970 --> 00:06:17,290 Value stream mapping-- so I said, 117 00:06:17,290 --> 00:06:18,720 we did a little bit yesterday. 118 00:06:18,720 --> 00:06:21,090 So we need to find out what our value streams are. 119 00:06:21,090 --> 00:06:24,600 Have we mapped the end-to-end processes here-- 120 00:06:24,600 --> 00:06:26,370 the information flow? 121 00:06:26,370 --> 00:06:28,230 Do we know that right now? 122 00:06:28,230 --> 00:06:31,410 After our little simulation exercise here? 123 00:06:31,410 --> 00:06:33,300 We have an idea about it. 124 00:06:33,300 --> 00:06:36,450 My perspective sitting over at table three here 125 00:06:36,450 --> 00:06:39,090 was that the information flow was maybe 126 00:06:39,090 --> 00:06:44,110 what we had the most difficulty with finding out where-- 127 00:06:44,110 --> 00:06:45,240 how that is connected. 128 00:06:45,240 --> 00:06:48,810 I don't know how-- what was your experience here? 129 00:06:48,810 --> 00:06:52,290 Was it the physical flow of location? 130 00:06:52,290 --> 00:06:54,160 Or was it more information flow? 131 00:06:54,160 --> 00:06:55,530 AUDIENCE: Information flow. 132 00:06:55,530 --> 00:06:57,030 BO MADSEN: Yeah, so maybe that would 133 00:06:57,030 --> 00:06:59,580 be valuable to find out about that. 134 00:06:59,580 --> 00:07:03,420 And then, you add on the process data. 135 00:07:03,420 --> 00:07:05,700 Also, like we talked about yesterday, 136 00:07:05,700 --> 00:07:08,340 add on things that will give you valuable information. 137 00:07:08,340 --> 00:07:12,390 But don't clutter it with all information under the sun. 138 00:07:12,390 --> 00:07:13,890 Because it ain't going to be useful, 139 00:07:13,890 --> 00:07:16,182 and you won't have space for it if you do it on your A3 140 00:07:16,182 --> 00:07:17,220 as well. 141 00:07:17,220 --> 00:07:20,400 So you need to think about what metrics represent the system 142 00:07:20,400 --> 00:07:21,630 performance-- 143 00:07:21,630 --> 00:07:25,800 wait time, throughput time, financial performance. 144 00:07:25,800 --> 00:07:29,610 So not so much talking from here-- 145 00:07:29,610 --> 00:07:32,790 15-minute exercise. 146 00:07:32,790 --> 00:07:38,880 Develop your process map as it looks right now, 147 00:07:38,880 --> 00:07:41,460 not the anticipated future state. 148 00:07:41,460 --> 00:07:44,580 But what does it look like right now? 149 00:07:44,580 --> 00:07:47,460 Write your process steps on your Post-its. 150 00:07:47,460 --> 00:07:50,130 You have the easels that you can put them up on. 151 00:07:50,130 --> 00:07:52,530 And you can connect them. 152 00:07:52,530 --> 00:07:58,680 And just before you start, add the decisions-- 153 00:07:58,680 --> 00:08:02,730 the waits, the holds, and the inventories. 154 00:08:02,730 --> 00:08:03,960 Are there pileups? 155 00:08:03,960 --> 00:08:05,560 And look at this one. 156 00:08:05,560 --> 00:08:06,810 That's how you can look at it. 157 00:08:06,810 --> 00:08:11,790 Inventory or awaiting-- triangles, task, rectangles, 158 00:08:11,790 --> 00:08:12,330 burst-- 159 00:08:12,330 --> 00:08:13,740 if there are issues-- 160 00:08:13,740 --> 00:08:18,580 diamonds, decision points. 161 00:08:18,580 --> 00:08:19,650 Try to do that. 162 00:08:19,650 --> 00:08:22,350 You have 15 minutes so quarter past 11. 163 00:08:22,350 --> 00:08:25,110 HUGH MCMANUS: So this exercise is just like yesterday. 164 00:08:25,110 --> 00:08:29,670 You should be writing at kind of the exam 165 00:08:29,670 --> 00:08:36,210 or whatever the single sticky per process level on these. 166 00:08:36,210 --> 00:08:41,250 Do them first then the inventory and decisions. 167 00:08:41,250 --> 00:08:44,070 And when you're quite satisfied with all that on the stickies 168 00:08:44,070 --> 00:08:47,460 and you have [INAUDIBLE] then tie them together 169 00:08:47,460 --> 00:08:49,170 with the matches. 170 00:08:49,170 --> 00:08:54,892 [INTERPOSING VOICES] 171 00:08:54,892 --> 00:08:58,380 SPEAKER 1: The only reason it would go in a discharge 172 00:08:58,380 --> 00:09:00,162 is if they've already been to the lab. 173 00:09:00,162 --> 00:09:01,620 I guess put that there too, though. 174 00:09:01,620 --> 00:09:03,240 Because it's an option. 175 00:09:03,240 --> 00:09:05,052 SPEAKER 2: So make it a little different-- 176 00:09:05,052 --> 00:09:06,510 SPEAKER 3: Just make these in pink. 177 00:09:06,510 --> 00:09:09,240 SPEAKER 2: This has to come back here. 178 00:09:09,240 --> 00:09:11,010 SPEAKER 3: Right, But then failed 179 00:09:11,010 --> 00:09:12,577 has to go back there too. 180 00:09:12,577 --> 00:09:14,910 SPEAKER 4: I think we need another decision point here-- 181 00:09:14,910 --> 00:09:16,540 if previous tests. 182 00:09:16,540 --> 00:09:18,082 So if there was a failed test then it 183 00:09:18,082 --> 00:09:21,357 would have to go back to here because of [? positive ?] test. 184 00:09:21,357 --> 00:09:22,440 And they've already been-- 185 00:09:22,440 --> 00:09:22,950 SPEAKER 5: You can go like-- 186 00:09:22,950 --> 00:09:24,492 SPEAKER 4: they go back to discharge. 187 00:09:24,492 --> 00:09:26,310 SPEAKER 5: We can go test results here. 188 00:09:26,310 --> 00:09:31,140 HUGH MCMANUS: OK, So everybody's gotten pretty close. 189 00:09:31,140 --> 00:09:33,930 They're still tweaking some stuff and realizing that when 190 00:09:33,930 --> 00:09:36,900 you try to map out this process, although it seems fairly 191 00:09:36,900 --> 00:09:38,880 simple, it isn't. 192 00:09:38,880 --> 00:09:41,130 It's kind of complicated, and it's 193 00:09:41,130 --> 00:09:43,350 complicated a couple of different dimensions. 194 00:09:43,350 --> 00:09:46,110 What I'd like to start with is just to have-- 195 00:09:46,110 --> 00:09:49,403 why don't we start with you folks briefing your map, just 196 00:09:49,403 --> 00:09:50,820 real quick because everybody knows 197 00:09:50,820 --> 00:09:53,700 the process they've got the same one, just brief how 198 00:09:53,700 --> 00:09:55,080 you mapped it. 199 00:09:55,080 --> 00:09:57,342 If you could do that. 200 00:09:57,342 --> 00:09:58,290 SPEAKER 6: Go ahead. 201 00:09:58,290 --> 00:10:01,140 SPEAKER 1: OK. 202 00:10:01,140 --> 00:10:02,910 So we put our three big decision points 203 00:10:02,910 --> 00:10:06,960 made by triage, the MD, and lab as these green diamonds. 204 00:10:06,960 --> 00:10:08,730 And then instead of having a waiting room, 205 00:10:08,730 --> 00:10:11,310 we treated all of the wait times with 206 00:10:11,310 --> 00:10:14,250 these upside-down triangles. 207 00:10:14,250 --> 00:10:15,510 HUGH MCMANUS: So that's nice. 208 00:10:15,510 --> 00:10:16,875 It's functional. 209 00:10:16,875 --> 00:10:18,750 There's a couple-- there's one thing that you 210 00:10:18,750 --> 00:10:21,240 sort of abstracted, which is that issue of everything going 211 00:10:21,240 --> 00:10:24,690 back to the waiting room, which you distributed, which is fine. 212 00:10:24,690 --> 00:10:26,020 You have to make that decision. 213 00:10:26,020 --> 00:10:28,208 But you've sort of abstracted that. 214 00:10:28,208 --> 00:10:30,000 And the other thing, of course, is the fact 215 00:10:30,000 --> 00:10:32,730 that there's a dependency. 216 00:10:32,730 --> 00:10:37,230 The lab results often affect what the MD has to decide. 217 00:10:37,230 --> 00:10:39,100 So there's an additional complication, 218 00:10:39,100 --> 00:10:41,310 which isn't captured at this level of detail. 219 00:10:41,310 --> 00:10:42,630 You could capture it. 220 00:10:42,630 --> 00:10:47,590 But it would essentially be more detail on the decision. 221 00:10:47,590 --> 00:10:49,470 [INTERPOSING VOICES] 222 00:10:51,330 --> 00:10:53,780 HUGH MCMANUS: We're just multiple decisions 223 00:10:53,780 --> 00:10:54,780 that the MD has to make. 224 00:10:54,780 --> 00:10:56,370 Has this patient been seen? 225 00:10:56,370 --> 00:10:59,097 Did they fail their lab tests, et cetera. 226 00:10:59,097 --> 00:11:00,930 Did they get a positive result, because that 227 00:11:00,930 --> 00:11:02,370 affects where things go. 228 00:11:02,370 --> 00:11:04,110 That's cool, so now let's have you 229 00:11:04,110 --> 00:11:09,351 folks just by way of contrast, tell us your strategy 230 00:11:09,351 --> 00:11:14,222 for plotting out the value [INAUDIBLE].. 231 00:11:14,222 --> 00:11:15,930 SPEAKER 7: So we have the different tasks 232 00:11:15,930 --> 00:11:17,347 that people have to do, which were 233 00:11:17,347 --> 00:11:21,770 all in green, so scheduling, registration, triage, 234 00:11:21,770 --> 00:11:22,780 et cetera. 235 00:11:22,780 --> 00:11:24,570 But what we represented the waiting 236 00:11:24,570 --> 00:11:26,910 room as a physical location. 237 00:11:26,910 --> 00:11:28,920 So it was like a mix between that spaghetti 238 00:11:28,920 --> 00:11:31,336 chart and the downstream map-- 239 00:11:31,336 --> 00:11:33,751 so basically in between every single task 240 00:11:33,751 --> 00:11:35,860 they have to go back to the waiting room. 241 00:11:35,860 --> 00:11:38,610 And so we are also didn't quite finish, 242 00:11:38,610 --> 00:11:42,210 but we try to have the dependency. 243 00:11:42,210 --> 00:11:44,220 If the test result is negative, you 244 00:11:44,220 --> 00:11:46,380 go back to the waiting room, and then discharge. 245 00:11:46,380 --> 00:11:49,080 If positive, then something else [INAUDIBLE].. 246 00:11:49,080 --> 00:11:53,280 And then the MD has to decide based on the previous test, 247 00:11:53,280 --> 00:11:54,060 what to do. 248 00:11:56,920 --> 00:11:59,742 AUDIENCE: They also start with times [INAUDIBLE].. 249 00:11:59,742 --> 00:12:01,950 HUGH MCMANUS: That's kind of our next step, actually, 250 00:12:01,950 --> 00:12:04,185 so they're ahead of the game as usual. 251 00:12:04,185 --> 00:12:05,310 This table is good at that. 252 00:12:05,310 --> 00:12:07,140 So you guys can finish up your traces. 253 00:12:07,140 --> 00:12:09,240 But here, they're taking a more physical approach. 254 00:12:09,240 --> 00:12:11,220 And the maps capture different things. 255 00:12:11,220 --> 00:12:14,547 This, it's sort of hard to see the flows and decisions. 256 00:12:14,547 --> 00:12:17,130 Because everything's going back and forth to the waiting room. 257 00:12:17,130 --> 00:12:20,100 So it provides a sort of a visual confusion factor. 258 00:12:20,100 --> 00:12:22,918 But maybe, the issue is that everything's 259 00:12:22,918 --> 00:12:24,210 going back to the waiting room. 260 00:12:24,210 --> 00:12:25,890 Maybe that's like an issue that we 261 00:12:25,890 --> 00:12:28,830 need to deal with, because that is obviously, confusing. 262 00:12:28,830 --> 00:12:31,770 It also has an awful lot of waste of motion in there 263 00:12:31,770 --> 00:12:35,430 with the poor patient and the potential for confusion 264 00:12:35,430 --> 00:12:37,090 that that engenders. 265 00:12:37,090 --> 00:12:39,540 And I can see your strategy although you didn't finish 266 00:12:39,540 --> 00:12:42,870 that there's actually individual paths here, which 267 00:12:42,870 --> 00:12:44,670 are going to get more complicated as we get 268 00:12:44,670 --> 00:12:46,830 the failed diagnostics, where maybe you could use 269 00:12:46,830 --> 00:12:51,790 a different color to trace the extra ones [? too. ?] 270 00:12:51,790 --> 00:12:54,840 So you can follow it, but it's a bit torturous, 271 00:12:54,840 --> 00:12:58,080 but it does capture certainly the chaos of the system 272 00:12:58,080 --> 00:12:59,040 quite nicely. 273 00:12:59,040 --> 00:13:04,122 So why don't we finish here and see what you guys have? 274 00:13:04,122 --> 00:13:05,580 You want to say something about it? 275 00:13:05,580 --> 00:13:08,520 [INTERPOSING VOICES] 276 00:13:08,520 --> 00:13:11,460 SPEAKER 8: We have each of the stations in the blue. 277 00:13:11,460 --> 00:13:13,390 I think the main source of chaos for us 278 00:13:13,390 --> 00:13:17,550 was what happens with the exam process and the decisions 279 00:13:17,550 --> 00:13:18,050 afterward. 280 00:13:18,050 --> 00:13:20,370 So that was our main point of contention 281 00:13:20,370 --> 00:13:22,170 at the end of this process is where 282 00:13:22,170 --> 00:13:25,230 do we put all these negative-positive failed test 283 00:13:25,230 --> 00:13:26,130 outcomes? 284 00:13:26,130 --> 00:13:27,720 And how do they eventually link back 285 00:13:27,720 --> 00:13:29,732 to the patient-to-start process. 286 00:13:29,732 --> 00:13:32,190 HUGH MCMANUS: And got some color going there to sort of try 287 00:13:32,190 --> 00:13:33,240 to chase that around. 288 00:13:36,332 --> 00:13:38,790 AUDIENCE: These are all value stream maps from the patient. 289 00:13:38,790 --> 00:13:40,483 But we don't have the information for-- 290 00:13:40,483 --> 00:13:42,900 HUGH MCMANUS: Right, there's some other [INAUDIBLE] there. 291 00:13:42,900 --> 00:13:44,580 AUDIENCE: There's charts and paperwork flying around. 292 00:13:44,580 --> 00:13:45,060 HUGH MCMANUS: That's right. 293 00:13:45,060 --> 00:13:47,477 And we did say we were following the patient value stream. 294 00:13:47,477 --> 00:13:51,388 But there are some other value streams up there-- the charts, 295 00:13:51,388 --> 00:13:53,430 the paperwork, which we actually could use pretty 296 00:13:53,430 --> 00:13:56,160 much the same map to chase. 297 00:13:56,160 --> 00:14:00,480 But they also have their own chart room and record room 298 00:14:00,480 --> 00:14:02,610 and to some extent, their own processes. 299 00:14:02,610 --> 00:14:07,320 They don't follow exactly the same path as the patient. 300 00:14:07,320 --> 00:14:08,220 So this is good. 301 00:14:08,220 --> 00:14:12,420 So why don't we continue with our exercise. 302 00:14:12,420 --> 00:14:15,810 BO MADSEN: Yes, so remember, yesterday we 303 00:14:15,810 --> 00:14:19,140 talked about different times. 304 00:14:19,140 --> 00:14:21,720 We talked about cycle time-- 305 00:14:21,720 --> 00:14:25,890 the time from the beginning to the end of the process. 306 00:14:25,890 --> 00:14:28,050 The touch time-- where the actual work 307 00:14:28,050 --> 00:14:32,340 is being done, where you exclude the wait times. 308 00:14:32,340 --> 00:14:37,240 And then again, value added non-value added time-- 309 00:14:37,240 --> 00:14:41,780 so we talk about some different types of time. 310 00:14:41,780 --> 00:14:45,130 And obviously, it is the value added time that we really want, 311 00:14:45,130 --> 00:14:48,640 and we prefer to get rid of the rest of it. 312 00:14:48,640 --> 00:14:52,450 So then there is also-- 313 00:14:52,450 --> 00:14:54,680 when we get to the capacity things as well, 314 00:14:54,680 --> 00:14:56,920 you need to think about failed tests. 315 00:14:56,920 --> 00:14:58,630 This is not 100% right. 316 00:14:58,630 --> 00:15:00,940 You have a certain amount of your test 317 00:15:00,940 --> 00:15:03,790 that just they're neither positive nor negative. 318 00:15:03,790 --> 00:15:05,530 They're just failed. 319 00:15:05,530 --> 00:15:07,390 Hospital systems for us-- 320 00:15:07,390 --> 00:15:13,220 what I have in my face every day is potassium. 321 00:15:13,220 --> 00:15:14,900 Do you experience the same things? 322 00:15:14,900 --> 00:15:16,160 You get high potassium. 323 00:15:16,160 --> 00:15:17,270 Everybody gets scared. 324 00:15:17,270 --> 00:15:19,430 Because it is dangerous. 325 00:15:19,430 --> 00:15:21,200 You need redraws. 326 00:15:21,200 --> 00:15:24,300 And we used to be around 20%. 327 00:15:24,300 --> 00:15:27,950 And now, I think we're down to 7% through leaning it out. 328 00:15:27,950 --> 00:15:30,800 But 7% is still a lot. 329 00:15:30,800 --> 00:15:33,260 Because like you said, what does everybody 330 00:15:33,260 --> 00:15:34,910 do when they come to the hospital? 331 00:15:34,910 --> 00:15:36,840 They get lab tests. 332 00:15:36,840 --> 00:15:39,600 So we have probably a couple of patients every day 333 00:15:39,600 --> 00:15:43,200 referred to the emergency department for hyperkalemia 334 00:15:43,200 --> 00:15:45,270 that we redraw. 335 00:15:45,270 --> 00:15:47,410 And then it's negative-- normal. 336 00:15:47,410 --> 00:15:48,790 So that's expensive. 337 00:15:48,790 --> 00:15:50,700 HUGH MCMANUS: So why don't we-- 338 00:15:50,700 --> 00:15:54,150 because this group seems to have caught the basic issue, 339 00:15:54,150 --> 00:15:56,100 and some of them have already jumped ahead-- 340 00:15:56,100 --> 00:16:02,050 and what we want to do is add some time and reliability data 341 00:16:02,050 --> 00:16:03,960 to our map. 342 00:16:03,960 --> 00:16:08,100 The tricky thing is, of course, every patient 343 00:16:08,100 --> 00:16:10,350 is different based on the dice, right? 344 00:16:10,350 --> 00:16:14,640 So we have to pick some kind of unit of analysis-- an average, 345 00:16:14,640 --> 00:16:16,448 a median, something. 346 00:16:16,448 --> 00:16:17,740 BO MADSEN: A min and max maybe. 347 00:16:17,740 --> 00:16:19,740 HUGH MCMANUS: A min and max, right. 348 00:16:19,740 --> 00:16:22,740 So we need to decide what our unit of analysis is 349 00:16:22,740 --> 00:16:23,670 and be consistent. 350 00:16:23,670 --> 00:16:25,710 It almost doesn't matter what it is. 351 00:16:25,710 --> 00:16:27,400 Over long experience with these things, 352 00:16:27,400 --> 00:16:31,110 I found that doing a min-max average 353 00:16:31,110 --> 00:16:33,588 is easily enough detail. 354 00:16:33,588 --> 00:16:35,880 When you start putting min-max average on all of these, 355 00:16:35,880 --> 00:16:38,297 you suddenly realize, I got a whole bunch of numbers here. 356 00:16:38,297 --> 00:16:40,170 And it's enough to tell most of the story. 357 00:16:40,170 --> 00:16:42,090 So we don't need a deep statistical analysis 358 00:16:42,090 --> 00:16:42,930 of these numbers. 359 00:16:42,930 --> 00:16:46,560 But we need to decide what our unit of analysis 360 00:16:46,560 --> 00:16:48,630 is, put the times up. 361 00:16:48,630 --> 00:16:51,180 And the times can pretty much be the hourglass. 362 00:16:51,180 --> 00:16:53,730 If there's a little bit of non-value-added touch-time, 363 00:16:53,730 --> 00:16:56,400 if there's a little bit of futzing time or confusion time 364 00:16:56,400 --> 00:17:01,500 or waiting for supplies time, you can add that, as well. 365 00:17:01,500 --> 00:17:03,570 And put those times on our processes. 366 00:17:03,570 --> 00:17:09,480 And then the percentages of different decision outcomes, 367 00:17:09,480 --> 00:17:11,160 again, need to be estimated. 368 00:17:11,160 --> 00:17:13,839 Some of those are based on the dice. 369 00:17:13,839 --> 00:17:15,839 So you sort of have the numbers in front of you. 370 00:17:15,839 --> 00:17:17,317 Some of them aren't so much. 371 00:17:17,317 --> 00:17:18,650 When do they go to the hospital? 372 00:17:18,650 --> 00:17:20,220 Well, when the right-colored head shows up. 373 00:17:20,220 --> 00:17:21,137 When does that happen? 374 00:17:21,137 --> 00:17:22,140 You don't know. 375 00:17:22,140 --> 00:17:23,609 You just have to kind of estimate 376 00:17:23,609 --> 00:17:26,490 based on your experience, OK? 377 00:17:26,490 --> 00:17:27,970 So not too complicated. 378 00:17:27,970 --> 00:17:31,740 Let's take another 10-ish minutes to finish our maps 379 00:17:31,740 --> 00:17:34,000 and annotate them. 380 00:17:34,000 --> 00:17:35,633 EARLL MURMAN: I love that. 381 00:17:35,633 --> 00:17:37,800 AUDIENCE: So we're doing a weighted average to our-- 382 00:17:37,800 --> 00:17:38,592 EARLL MURMAN: Yeah. 383 00:17:38,592 --> 00:17:43,290 AUDIENCE: Yeah, so if there are two patients waiting, 384 00:17:43,290 --> 00:17:45,650 one will be waiting for this much. 385 00:17:45,650 --> 00:17:48,600 And the second will be waiting for two units of this. 386 00:17:48,600 --> 00:17:49,850 EARLL MURMAN: Excellent, yeah. 387 00:17:49,850 --> 00:17:50,912 AUDIENCE: Yeah. 388 00:17:50,912 --> 00:17:53,470 And if there's a third patient, the third patient 389 00:17:53,470 --> 00:17:55,020 will wait for three units of this. 390 00:17:55,020 --> 00:17:55,560 EARLL MURMAN: Yeah, OK. 391 00:17:55,560 --> 00:17:57,518 But we have to kind of average when we roll it. 392 00:17:57,518 --> 00:18:00,648 So on average, how many patients do you think were waiting? 393 00:18:00,648 --> 00:18:03,747 So treatment time is three times the dice roll. 394 00:18:03,747 --> 00:18:04,830 AUDIENCE: Yes, 40 seconds. 395 00:18:04,830 --> 00:18:08,760 EARLL MURMAN: OK, of which only 1/3 is value-added time and 2/3 396 00:18:08,760 --> 00:18:09,990 is waste. 397 00:18:09,990 --> 00:18:11,640 The average time a patient is in here 398 00:18:11,640 --> 00:18:16,200 is 80 times 3, which is 240, which is 240 seconds. 399 00:18:16,200 --> 00:18:18,618 AUDIENCE: OK, so should we just put 240? 400 00:18:18,618 --> 00:18:19,410 EARLL MURMAN: 240-- 401 00:18:19,410 --> 00:18:20,190 AUDIENCE: Yeah, you can do that. 402 00:18:20,190 --> 00:18:22,460 EARLL MURMAN: --of which 80 is value-added. 403 00:18:22,460 --> 00:18:25,950 AUDIENCE: So how about we put average time and value-added? 404 00:18:25,950 --> 00:18:27,330 EARLL MURMAN: Yeah, OK. 405 00:18:27,330 --> 00:18:28,180 AUDIENCE: OK. 406 00:18:28,180 --> 00:18:29,970 HUGH MCMANUS: There's basically two ways 407 00:18:29,970 --> 00:18:34,410 you could tackle the challenge of collecting data in the sim. 408 00:18:34,410 --> 00:18:35,865 And I think different teams did it 409 00:18:35,865 --> 00:18:37,740 different ways, which is an interesting thing 410 00:18:37,740 --> 00:18:38,448 about this group. 411 00:18:38,448 --> 00:18:40,380 It's a fairly sophisticated group. 412 00:18:40,380 --> 00:18:42,780 I think that people have grasped the issue 413 00:18:42,780 --> 00:18:45,330 and made different decisions about how to tackle it. 414 00:18:45,330 --> 00:18:48,570 You could go in, and you could say, well, OK. 415 00:18:48,570 --> 00:18:50,370 If I rolled an infinite number of dice, 416 00:18:50,370 --> 00:18:53,520 what would be the statistically likely outcome? 417 00:18:53,520 --> 00:18:55,620 What would be my weighted average time? 418 00:18:58,590 --> 00:19:02,310 What would be my weighted average of different outcomes 419 00:19:02,310 --> 00:19:03,610 through the system? 420 00:19:03,610 --> 00:19:05,137 So you could do it that way. 421 00:19:05,137 --> 00:19:06,720 And that's something in the real world 422 00:19:06,720 --> 00:19:10,410 you could do if you had profound knowledge of the system, 423 00:19:10,410 --> 00:19:14,010 if you just knew that 30% of this kind of patient 424 00:19:14,010 --> 00:19:15,300 went this way. 425 00:19:15,300 --> 00:19:20,580 Or other approach is you could use data, right? 426 00:19:20,580 --> 00:19:21,750 We have data. 427 00:19:21,750 --> 00:19:24,150 So you can just count them, right? 428 00:19:24,150 --> 00:19:25,710 Which ones went where? 429 00:19:25,710 --> 00:19:27,090 How many dots do we have to do? 430 00:19:27,090 --> 00:19:28,230 How much rework was there? 431 00:19:28,230 --> 00:19:33,450 The problem with that is that it's small n, right? 432 00:19:33,450 --> 00:19:35,910 It's not going to give you the same answer 433 00:19:35,910 --> 00:19:40,650 as the statistical study unless you have a really large sample. 434 00:19:40,650 --> 00:19:46,230 Now, is that your world? 435 00:19:46,230 --> 00:19:48,140 Pretty much, right? 436 00:19:48,140 --> 00:19:51,840 In fact, medical studies tend to not really converge unless they 437 00:19:51,840 --> 00:19:54,900 have really large samples. 438 00:19:54,900 --> 00:19:56,130 But this is real. 439 00:19:56,130 --> 00:19:58,510 This is the reality on the ground. 440 00:19:58,510 --> 00:19:59,550 Which one do you trust? 441 00:19:59,550 --> 00:20:00,960 Which one do you believe? 442 00:20:00,960 --> 00:20:03,060 You have to choose, right? 443 00:20:03,060 --> 00:20:04,350 There's no absolute answer. 444 00:20:04,350 --> 00:20:07,710 BO MADSEN: It depends on what system you are in. 445 00:20:07,710 --> 00:20:11,070 So BI would probably have the most advanced medical records 446 00:20:11,070 --> 00:20:12,660 in this country. 447 00:20:12,660 --> 00:20:14,730 So we can pull everything out. 448 00:20:14,730 --> 00:20:18,780 And we can go 10 years back, 50,000 or 55,000 visits 449 00:20:18,780 --> 00:20:21,120 in the emergency department per year. 450 00:20:21,120 --> 00:20:23,820 And we could just pull all of that out. 451 00:20:23,820 --> 00:20:26,340 It's fairly easy, but that's because we have good people. 452 00:20:26,340 --> 00:20:28,380 But that's not the reality everywhere. 453 00:20:28,380 --> 00:20:30,300 So I worked with Iceland and with Denmark. 454 00:20:30,300 --> 00:20:33,390 And, well, they have fairly sophisticated 455 00:20:33,390 --> 00:20:35,230 electronic medical records. 456 00:20:35,230 --> 00:20:36,810 But a lot of it is still on paper. 457 00:20:36,810 --> 00:20:39,690 And you just need to go and look at the paper. 458 00:20:39,690 --> 00:20:43,260 And at BI, our record has limitations, too. 459 00:20:43,260 --> 00:20:45,600 Let's just say we want to study sepsis. 460 00:20:45,600 --> 00:20:48,810 We want to study the antibiotics that these patients got. 461 00:20:48,810 --> 00:20:52,500 I can electronically see what got pulled out of the Pyxis. 462 00:20:52,500 --> 00:20:54,600 You may be familiar with the Pyxis-- 463 00:20:54,600 --> 00:20:55,860 locked cabinet. 464 00:20:55,860 --> 00:20:58,140 You punch in the patient's medical record number 465 00:20:58,140 --> 00:21:00,000 and what you want to pull out. 466 00:21:00,000 --> 00:21:04,560 But I need to look at the paper to see what the nurse gave 467 00:21:04,560 --> 00:21:06,570 because one thing is that they pulled out 468 00:21:06,570 --> 00:21:10,560 4.5 grams of x, y, or z. 469 00:21:10,560 --> 00:21:14,820 But if they only gave 3 grams, that information 470 00:21:14,820 --> 00:21:17,880 is only available on paper as it is. 471 00:21:17,880 --> 00:21:21,567 All right, so, yes, you can go either way. 472 00:21:21,567 --> 00:21:22,650 HUGH MCMANUS: And that's-- 473 00:21:22,650 --> 00:21:27,000 BO MADSEN: Here, with the numbers that we added on, 474 00:21:27,000 --> 00:21:29,970 we had it a little bit fudged because, well, when you 475 00:21:29,970 --> 00:21:32,400 handle stuff, it takes time. 476 00:21:32,400 --> 00:21:35,700 15 seconds for just handling the patient to the waiting 477 00:21:35,700 --> 00:21:37,320 room, passing on the message. 478 00:21:37,320 --> 00:21:39,970 New patient takes time. 479 00:21:39,970 --> 00:21:43,830 There is a range of how long the different steps take, 480 00:21:43,830 --> 00:21:47,630 and the weighted average plus the fudge. 481 00:21:47,630 --> 00:21:51,810 OK, so it's hopefully pretty similar to what 482 00:21:51,810 --> 00:21:54,000 the different groups found. 483 00:21:54,000 --> 00:21:55,650 Maybe? 484 00:21:55,650 --> 00:21:56,342 Take a look. 485 00:21:56,342 --> 00:21:58,800 HUGH MCMANUS: Yeah, did you do something kind of innovative 486 00:21:58,800 --> 00:21:59,700 here instead of-- 487 00:22:02,290 --> 00:22:05,820 AUDIENCE: We calculated the actual waiting 488 00:22:05,820 --> 00:22:09,180 time for the patient in MD. 489 00:22:09,180 --> 00:22:14,810 So the process time-- so if it's 1 or 2 on a roll, 490 00:22:14,810 --> 00:22:18,400 then it's, what's their probability of 30 seconds? 491 00:22:18,400 --> 00:22:21,667 And if it's 3 to 4, it's, what's their probability of-- 492 00:22:21,667 --> 00:22:22,500 [INTERPOSING VOICES] 493 00:22:22,500 --> 00:22:26,010 And then I calculated all of them and summed them up. 494 00:22:26,010 --> 00:22:30,850 So for one patient, the [INAUDIBLE] average 495 00:22:30,850 --> 00:22:33,082 time is 80 seconds. 496 00:22:33,082 --> 00:22:34,290 HUGH MCMANUS: 80 seconds, OK. 497 00:22:34,290 --> 00:22:34,670 All right. 498 00:22:34,670 --> 00:22:35,010 So-- 499 00:22:35,010 --> 00:22:37,100 EARLL MURMAN: But then there's another important step-- 500 00:22:37,100 --> 00:22:37,530 HUGH MCMANUS: Yeah. 501 00:22:37,530 --> 00:22:37,860 AUDIENCE: Yeah. 502 00:22:37,860 --> 00:22:39,300 EARLL MURMAN: --is that she's got patients waiting. 503 00:22:39,300 --> 00:22:40,545 HUGH MCMANUS: Oh, OK. 504 00:22:40,545 --> 00:22:43,530 AUDIENCE: Yeah, so if one patient is waiting, 505 00:22:43,530 --> 00:22:47,326 and he probably will wait for the [INAUDIBLE] time that's 506 00:22:47,326 --> 00:22:48,180 80 seconds. 507 00:22:48,180 --> 00:22:50,040 And if two patients are waiting-- 508 00:22:50,040 --> 00:22:54,570 so this is 80 seconds-- this one will be 160 seconds. 509 00:22:54,570 --> 00:22:56,070 HUGH MCMANUS: OK, there's an issue. 510 00:22:56,070 --> 00:23:00,420 I noticed that we didn't even try [LAUGHS] to estimate 511 00:23:00,420 --> 00:23:01,990 the waiting times, right? 512 00:23:01,990 --> 00:23:04,260 So she's gotten extra sophisticated and said, 513 00:23:04,260 --> 00:23:07,500 the 80 is actually, we tacked on 15 seconds for paperwork. 514 00:23:07,500 --> 00:23:10,110 And so we're agreeing on that exactly. 515 00:23:10,110 --> 00:23:11,970 What she's doing, which is very clever-- 516 00:23:11,970 --> 00:23:15,370 and this, you probably do need to do database. 517 00:23:15,370 --> 00:23:18,030 How many patients did you have waiting typically? 518 00:23:18,030 --> 00:23:19,050 So yep. 519 00:23:19,050 --> 00:23:22,440 EARLL MURMAN: So she estimated that she has two patients 520 00:23:22,440 --> 00:23:23,295 on average waiting. 521 00:23:23,295 --> 00:23:24,060 HUGH MCMANUS: Waiting, OK. 522 00:23:24,060 --> 00:23:24,550 That's right. 523 00:23:24,550 --> 00:23:25,395 EARLL MURMAN: So the actual time in the MD 524 00:23:25,395 --> 00:23:27,395 was three times the actual treatment. 525 00:23:27,395 --> 00:23:28,530 HUGH MCMANUS: Right, right. 526 00:23:28,530 --> 00:23:29,010 So if we have-- 527 00:23:29,010 --> 00:23:29,760 BO MADSEN: So 240. 528 00:23:29,760 --> 00:23:30,872 HUGH MCMANUS: Yep, yeah. 529 00:23:30,872 --> 00:23:31,830 So that's great, right? 530 00:23:31,830 --> 00:23:34,470 That's going deeper than we did in our example. 531 00:23:34,470 --> 00:23:36,420 And that's right. 532 00:23:36,420 --> 00:23:40,020 Any time you have inventory in front of a process, yeah, 533 00:23:40,020 --> 00:23:41,280 it's going to have to-- 534 00:23:41,280 --> 00:23:43,110 something called Little's law, which 535 00:23:43,110 --> 00:23:45,270 we'll talk about next time. 536 00:23:45,270 --> 00:23:47,520 You're going to have to wait essentially 537 00:23:47,520 --> 00:23:51,580 that number of cycles to get through the process. 538 00:23:51,580 --> 00:23:55,380 So if there's two patients waiting and one in exam, 539 00:23:55,380 --> 00:23:57,600 it's going to, on average, take three cycles 540 00:23:57,600 --> 00:24:00,180 to clear a patient through there. 541 00:24:00,180 --> 00:24:01,560 So that's very good. 542 00:24:01,560 --> 00:24:02,060 OK. 543 00:24:02,060 --> 00:24:05,430 BO MADSEN: And then if you look at your 544 00:24:05,430 --> 00:24:08,220 how long time things [? they ?] take, 545 00:24:08,220 --> 00:24:11,580 you should also get a sense of what the rate-limiting steps 546 00:24:11,580 --> 00:24:12,150 are here. 547 00:24:14,910 --> 00:24:18,120 What would you say? 548 00:24:18,120 --> 00:24:19,560 [LAUGHTER] 549 00:24:19,560 --> 00:24:23,230 When you look at it, who's the limiting step? 550 00:24:23,230 --> 00:24:24,837 AUDIENCE: MD and the lab. 551 00:24:24,837 --> 00:24:25,920 BO MADSEN: MD and the lab. 552 00:24:25,920 --> 00:24:26,545 AUDIENCE: Yeah. 553 00:24:26,545 --> 00:24:30,570 BO MADSEN: What's the difference between the MD and the lab? 554 00:24:30,570 --> 00:24:32,327 The MD is-- 555 00:24:32,327 --> 00:24:32,910 AUDIENCE: One. 556 00:24:32,910 --> 00:24:33,910 BO MADSEN: --one person. 557 00:24:33,910 --> 00:24:35,700 And the lab can do, how much at a time? 558 00:24:35,700 --> 00:24:36,076 AUDIENCE: Three. 559 00:24:36,076 --> 00:24:36,452 AUDIENCE: Potentially. 560 00:24:36,452 --> 00:24:38,560 BO MADSEN: Three with a little bit of good luck, 561 00:24:38,560 --> 00:24:43,250 right, because they can do three different things at a time. 562 00:24:43,250 --> 00:24:47,940 But if you look at the times of the lab, well, 45 to 205. 563 00:24:47,940 --> 00:24:49,380 The same for the lab. 564 00:24:49,380 --> 00:24:51,570 But the MD is really only one and can only 565 00:24:51,570 --> 00:24:57,920 be in one place at a time, so OK. 566 00:24:57,920 --> 00:25:00,630 And then there's some rework. 567 00:25:00,630 --> 00:25:02,630 HUGH MCMANUS: And that, too, we have essentially 568 00:25:02,630 --> 00:25:03,547 the same issue, right? 569 00:25:03,547 --> 00:25:08,630 People can look at the dice and guesstimate. 570 00:25:08,630 --> 00:25:11,360 Or they can look at their data and figure out 571 00:25:11,360 --> 00:25:13,910 what the rework rates are. 572 00:25:13,910 --> 00:25:17,510 The thing that actually you can't 573 00:25:17,510 --> 00:25:20,810 do there is that some of that depends on the patient color, 574 00:25:20,810 --> 00:25:22,238 which you don't know, right? 575 00:25:22,238 --> 00:25:23,780 There's an externality there that you 576 00:25:23,780 --> 00:25:25,370 don't have any control over. 577 00:25:25,370 --> 00:25:28,115 And if that's true, all you can do is look at your data, right? 578 00:25:28,115 --> 00:25:29,990 You don't know what the big world looks like. 579 00:25:29,990 --> 00:25:32,720 You only know what your data looks like. 580 00:25:32,720 --> 00:25:37,670 So based on that, you should have something on this order. 581 00:25:37,670 --> 00:25:42,650 Something on the order of half of the tests don't go so well. 582 00:25:42,650 --> 00:25:46,025 So that's another major detractor. 583 00:25:46,025 --> 00:25:50,190 BO MADSEN: All right, so diagnosing root causes. 584 00:25:50,190 --> 00:25:53,130 You need to find out, what are the causes here? 585 00:25:53,130 --> 00:25:54,660 What's the effect? 586 00:25:54,660 --> 00:25:55,860 What's the cause? 587 00:25:55,860 --> 00:26:00,240 It's nice to separate those out because the root causes, 588 00:26:00,240 --> 00:26:03,060 if you can find an effect of those, 589 00:26:03,060 --> 00:26:05,730 you have a better chance of improving your system. 590 00:26:05,730 --> 00:26:10,290 We haven't talked much about workaround. 591 00:26:10,290 --> 00:26:15,360 But it's very prominent in the medical field. 592 00:26:15,360 --> 00:26:18,570 So the medical field and the engineering field, 593 00:26:18,570 --> 00:26:20,940 I think that we have some of the same attributes. 594 00:26:20,940 --> 00:26:23,180 It is that we fix problems, right? 595 00:26:23,180 --> 00:26:26,010 We see a problem, we fix it. 596 00:26:26,010 --> 00:26:28,630 So I have a problem at work, I just fix it. 597 00:26:28,630 --> 00:26:31,830 I don't go back and say, all right, why is it that it takes 598 00:26:31,830 --> 00:26:36,260 15 minutes to do a lumbar puncture? 599 00:26:36,260 --> 00:26:38,550 It's not that it's the 11 minutes 600 00:26:38,550 --> 00:26:42,470 that it takes to find the stuff and get everything ready. 601 00:26:42,470 --> 00:26:44,240 I just go ahead, and I do it. 602 00:26:44,240 --> 00:26:47,570 Or if it's a new resident, I'll help them and collect the stuff 603 00:26:47,570 --> 00:26:51,620 for them, instead of saying, OK, we need kits. 604 00:26:51,620 --> 00:26:54,350 We need the stuff to be available in the area 605 00:26:54,350 --> 00:26:57,152 where we use it because that's a long process. 606 00:26:57,152 --> 00:26:58,610 It involves our nursing leadership, 607 00:26:58,610 --> 00:27:01,460 physician leadership, and restocking guys. 608 00:27:01,460 --> 00:27:04,530 And it's someone else's area of responsibility. 609 00:27:04,530 --> 00:27:07,590 And they're going to be upset if I say this is all wrong. 610 00:27:07,590 --> 00:27:11,440 And so we just do workarounds. 611 00:27:11,440 --> 00:27:13,030 That's not a good way of doing it. 612 00:27:13,030 --> 00:27:17,960 You can analyze the root-cause analysis in different ways-- 613 00:27:17,960 --> 00:27:21,610 the 5 Whys we talked about with the Jefferson Monument. 614 00:27:21,610 --> 00:27:22,700 It's very interesting. 615 00:27:22,700 --> 00:27:24,940 It's really useful. 616 00:27:24,940 --> 00:27:26,860 If you think about a medical system 617 00:27:26,860 --> 00:27:31,750 and say, we do too many joint replacements, 618 00:27:31,750 --> 00:27:33,850 why do we do too many joint replacements? 619 00:27:33,850 --> 00:27:35,440 Well, because the joints are worn. 620 00:27:35,440 --> 00:27:38,220 Why are the joints worn? 621 00:27:38,220 --> 00:27:39,510 Chime in here. 622 00:27:39,510 --> 00:27:41,700 Why do people get joint replacements in the US? 623 00:27:41,700 --> 00:27:42,450 AUDIENCE: Obesity. 624 00:27:42,450 --> 00:27:44,010 BO MADSEN: Yes, obesity. 625 00:27:44,010 --> 00:27:45,300 Why are people obese? 626 00:27:45,300 --> 00:27:46,758 AUDIENCE: McDonald's [INAUDIBLE] 627 00:27:46,758 --> 00:27:48,220 [LAUGHTER] 628 00:27:48,220 --> 00:27:49,010 BO MADSEN: No, no. 629 00:27:49,010 --> 00:27:53,110 And again, these things are being answered 630 00:27:53,110 --> 00:27:54,610 in a personal manner, right? 631 00:27:54,610 --> 00:27:56,290 So you can end up with different things. 632 00:27:56,290 --> 00:27:58,105 But I think you're right on. 633 00:27:58,105 --> 00:28:02,780 Pre-processed food is cheaper than making your own food, 634 00:28:02,780 --> 00:28:03,670 right? 635 00:28:03,670 --> 00:28:05,930 And then it gets into, who earns what? 636 00:28:05,930 --> 00:28:07,240 So you do, why? 637 00:28:07,240 --> 00:28:09,670 Pre-processed food is cheaper than the other. 638 00:28:09,670 --> 00:28:10,930 Why is it? 639 00:28:10,930 --> 00:28:13,270 Because we put garbage in the food. 640 00:28:13,270 --> 00:28:14,530 And why is that? 641 00:28:14,530 --> 00:28:15,490 Blah, blah, blah. 642 00:28:15,490 --> 00:28:19,300 OK, so 5 Whys really work. 643 00:28:19,300 --> 00:28:21,320 And it works on many different things. 644 00:28:21,320 --> 00:28:24,730 It's not only the Jefferson Monument, which is nice, too. 645 00:28:24,730 --> 00:28:26,470 We can do capacity analysis. 646 00:28:26,470 --> 00:28:29,170 We looked at that yesterday. 647 00:28:29,170 --> 00:28:31,870 Remember, how much time is available? 648 00:28:31,870 --> 00:28:34,530 What is our cycle time-- 649 00:28:34,530 --> 00:28:41,760 again, limited by the slowest steps in this process. 650 00:28:41,760 --> 00:28:43,410 All right, so tomorrow you're going 651 00:28:43,410 --> 00:28:46,680 to look at cause-and-effect diagrams and some Pareto 652 00:28:46,680 --> 00:28:47,940 charts, too. 653 00:28:47,940 --> 00:28:49,830 This we're just going to stop. 654 00:28:49,830 --> 00:28:54,650 And pitfalls, they can be answered differently. 655 00:28:54,650 --> 00:28:58,540 Some are based on values and on opinions. 656 00:28:58,540 --> 00:29:01,770 If there's too much difference, then maybe 657 00:29:01,770 --> 00:29:03,570 you need a more sophisticated tool 658 00:29:03,570 --> 00:29:06,050 for that particular problem. 659 00:29:06,050 --> 00:29:10,170 But in general, it's going to work well on many problems. 660 00:29:10,170 --> 00:29:11,370 Good place to start. 661 00:29:11,370 --> 00:29:15,670 Yeah, it's difficult to identify all the possible causes. 662 00:29:15,670 --> 00:29:20,365 If you have input that's higher than your capacity, 663 00:29:20,365 --> 00:29:21,990 then you're going to have a bottleneck. 664 00:29:21,990 --> 00:29:24,630 And then you're just going to have a build-up of things 665 00:29:24,630 --> 00:29:26,420 that are waiting. 666 00:29:26,420 --> 00:29:29,460 Example from Denmark-- pardon me again-- 667 00:29:29,460 --> 00:29:31,820 so there is a plan that says, for instance, 668 00:29:31,820 --> 00:29:33,920 pancreatic cancer patients, they should 669 00:29:33,920 --> 00:29:36,050 be able to have surgery within, I 670 00:29:36,050 --> 00:29:38,570 don't remember if it's two or four weeks. 671 00:29:38,570 --> 00:29:40,190 One would hope that it's tomorrow. 672 00:29:40,190 --> 00:29:41,750 But it's two or four weeks. 673 00:29:41,750 --> 00:29:45,840 Nonetheless, they don't have the capacity to do that. 674 00:29:45,840 --> 00:29:47,930 And then you have a build-up of patients. 675 00:29:47,930 --> 00:29:50,720 And some of them, they get surgery two months later, 676 00:29:50,720 --> 00:29:52,250 maybe three months later. 677 00:29:52,250 --> 00:29:54,110 Others, what happened to them? 678 00:29:54,110 --> 00:29:55,770 Well, when it's cancer, you know what? 679 00:29:55,770 --> 00:29:58,040 It becomes inoperable, right? 680 00:29:58,040 --> 00:30:01,630 And then they drop off the list. 681 00:30:01,630 --> 00:30:05,980 So when capacity and supply is mismatched, 682 00:30:05,980 --> 00:30:07,720 you're going to have a build-up. 683 00:30:07,720 --> 00:30:13,540 Theoretical capacity, so this is a very cool field. 684 00:30:13,540 --> 00:30:15,410 You'll have more about that tomorrow. 685 00:30:15,410 --> 00:30:19,960 So maximum capacity is, well, the maximum sustainable flow 686 00:30:19,960 --> 00:30:20,620 rate. 687 00:30:20,620 --> 00:30:23,878 Any activity, we like to think about 100%. 688 00:30:23,878 --> 00:30:26,170 Hugh is going to tell you tomorrow that that's actually 689 00:30:26,170 --> 00:30:28,330 not really attainable. 690 00:30:28,330 --> 00:30:34,288 And it's not an attractive goal because it will not function. 691 00:30:34,288 --> 00:30:36,580 It will lead to longer wait times and things like that. 692 00:30:36,580 --> 00:30:39,400 Effective capacity takes into account 693 00:30:39,400 --> 00:30:43,840 the errors, the distracters, the reworks, 694 00:30:43,840 --> 00:30:45,880 what you can actually achieve. 695 00:30:45,880 --> 00:30:47,930 And we can look at that. 696 00:30:47,930 --> 00:30:50,230 So if you can see five patients per hour 697 00:30:50,230 --> 00:30:53,860 but you have an error rate of 20%, 698 00:30:53,860 --> 00:30:56,140 then in reality you're only going 699 00:30:56,140 --> 00:30:59,270 to see four patients per hour, right? 700 00:30:59,270 --> 00:31:04,370 OK, so that's your effective capacity, not your maximum. 701 00:31:04,370 --> 00:31:05,480 All right, let's see. 702 00:31:05,480 --> 00:31:07,040 We can look at this one here. 703 00:31:07,040 --> 00:31:10,310 Capacity calculation, time available-- we know that. 704 00:31:10,310 --> 00:31:14,300 And then the cycle time, the time per unit, time per round, 705 00:31:14,300 --> 00:31:16,370 the number of resources that you have. 706 00:31:16,370 --> 00:31:18,980 But you're not always available, are you? 707 00:31:18,980 --> 00:31:21,170 You're not available 100% of the time. 708 00:31:21,170 --> 00:31:22,550 People, they go to eat. 709 00:31:22,550 --> 00:31:24,710 They have bathroom breaks. 710 00:31:24,710 --> 00:31:26,390 In Europe, they smoke. 711 00:31:26,390 --> 00:31:29,780 And some places, that is being taken out of your work time 712 00:31:29,780 --> 00:31:30,350 now. 713 00:31:30,350 --> 00:31:31,340 I'm not kidding. 714 00:31:31,340 --> 00:31:32,870 But that's a new concept. 715 00:31:32,870 --> 00:31:35,320 It never used to be. 716 00:31:35,320 --> 00:31:37,080 So I think smoking will go down with that. 717 00:31:37,080 --> 00:31:38,310 I think it's an excellent step. 718 00:31:38,310 --> 00:31:38,580 [LAUGHTER] 719 00:31:38,580 --> 00:31:40,020 No, I mean-- and I'm not kidding. 720 00:31:40,020 --> 00:31:43,470 [LAUGHS] The actual touch time, where you're doing something 721 00:31:43,470 --> 00:31:45,390 that is useful for the patient. 722 00:31:45,390 --> 00:31:49,410 And then the number of repeats, the failed test or the, 723 00:31:49,410 --> 00:31:52,620 I had a positive test, I need to go back to the MD, 724 00:31:52,620 --> 00:31:54,490 as in our simulation here. 725 00:31:54,490 --> 00:31:56,050 So you put that in your equation. 726 00:31:56,050 --> 00:31:58,013 And then you get your real capacity. 727 00:31:58,013 --> 00:31:59,430 The green ones are the good stuff. 728 00:31:59,430 --> 00:32:01,440 And the red ones are the detractors. 729 00:32:01,440 --> 00:32:05,345 So this is basic concepts. 730 00:32:05,345 --> 00:32:07,220 People, if you go back to your organizations, 731 00:32:07,220 --> 00:32:09,500 they might be confused by the words that you're using. 732 00:32:09,500 --> 00:32:13,080 But if you talk about this as a concept, 733 00:32:13,080 --> 00:32:17,550 then you should all be on the same page. 734 00:32:17,550 --> 00:32:22,430 So now we have 10 minutes to do a root-cause analysis 735 00:32:22,430 --> 00:32:25,380 for your clinic operation here. 736 00:32:25,380 --> 00:32:28,460 So identify causes that can be remedied 737 00:32:28,460 --> 00:32:32,900 using lean principles and tools that you heard about yesterday. 738 00:32:32,900 --> 00:32:34,910 Try to put it on your easel. 739 00:32:34,910 --> 00:32:37,600 And let's talk about it. 740 00:32:37,600 --> 00:32:40,100 HUGH MCMANUS: So think a little bit more about what's wrong. 741 00:32:40,100 --> 00:32:43,850 You can finish up your value stream map. 742 00:32:43,850 --> 00:32:48,170 Rather than do a separate easel chart display, 743 00:32:48,170 --> 00:32:53,450 why don't you go ahead and put your suspected root causes 744 00:32:53,450 --> 00:32:55,460 right there on the chart, you know? 745 00:32:55,460 --> 00:32:59,698 Is this the problem, chaos in the waiting room? 746 00:32:59,698 --> 00:33:01,490 I don't know whether that's the root cause. 747 00:33:01,490 --> 00:33:06,410 That may actually be a symptom. 748 00:33:06,410 --> 00:33:08,300 But we'll put that right on the chart. 749 00:33:08,300 --> 00:33:12,350 So we'll finish the morning with an annotated chart 750 00:33:12,350 --> 00:33:14,150 of the things that you want to fix. 751 00:33:14,150 --> 00:33:16,808 And after lunch, we're going to proceed to fix them. 752 00:33:16,808 --> 00:33:18,350 EARLL MURMAN: So it sounds like we've 753 00:33:18,350 --> 00:33:21,140 identified two major problems. 754 00:33:21,140 --> 00:33:22,570 We have the bottleneck here. 755 00:33:22,570 --> 00:33:25,490 And there's a solution to get the [INAUDIBLE].. 756 00:33:25,490 --> 00:33:27,350 And then the failing [INAUDIBLE],, 757 00:33:27,350 --> 00:33:29,155 we got to find some solution for that. 758 00:33:29,155 --> 00:33:29,780 AUDIENCE: Yeah. 759 00:33:29,780 --> 00:33:32,340 EARLL MURMAN: And then those are the two main long poles 760 00:33:32,340 --> 00:33:32,840 in the tent. 761 00:33:32,840 --> 00:33:35,450 And then next level down is stream-lining 762 00:33:35,450 --> 00:33:41,660 the ordering system and this, just, 763 00:33:41,660 --> 00:33:43,305 flow through the waiting room. 764 00:33:43,305 --> 00:33:45,440 AUDIENCE: Also optimizing the order 765 00:33:45,440 --> 00:33:48,410 that we get patients from the MD to the diagnostics 766 00:33:48,410 --> 00:33:50,090 so that I can run a couple at a time. 767 00:33:50,090 --> 00:33:50,960 AUDIENCE: So we're doing that. 768 00:33:50,960 --> 00:33:51,390 AUDIENCE: Yeah, because-- 769 00:33:51,390 --> 00:33:52,070 EARLL MURMAN: Oh, OK. 770 00:33:52,070 --> 00:33:54,410 So we actually want to have this distributed waiting room 771 00:33:54,410 --> 00:33:54,993 type of thing? 772 00:33:54,993 --> 00:33:56,902 AUDIENCE: No, that is just so she doesn't-- 773 00:33:56,902 --> 00:33:59,360 like, she has to pick which order she sees the patients in. 774 00:33:59,360 --> 00:34:01,130 AUDIENCE: Right, if I'm treating a gray patient 775 00:34:01,130 --> 00:34:03,170 and she's got a gray patient and blue patient that she's 776 00:34:03,170 --> 00:34:04,640 trying to decide who to treat next, 777 00:34:04,640 --> 00:34:06,840 pick the blue one so that I can run it at the same time. 778 00:34:06,840 --> 00:34:07,010 EARLL MURMAN: Ah, wow. 779 00:34:07,010 --> 00:34:07,880 So this is a visual control. 780 00:34:07,880 --> 00:34:08,505 AUDIENCE: Yeah. 781 00:34:08,505 --> 00:34:09,290 EARLL MURMAN: OK. 782 00:34:09,290 --> 00:34:10,380 OK, cool. 783 00:34:10,380 --> 00:34:14,360 HUGH MCMANUS: Let's talk about the conclusions 784 00:34:14,360 --> 00:34:17,210 you guys came to on your root-cause exercises. 785 00:34:17,210 --> 00:34:19,670 If we could just go around and just tell me 786 00:34:19,670 --> 00:34:23,540 two things that you think are the biggest problems 787 00:34:23,540 --> 00:34:29,719 with your processes from a root-cause perspective. 788 00:34:29,719 --> 00:34:30,919 Let's start back here. 789 00:34:30,919 --> 00:34:33,620 AUDIENCE: So our main problem was the bottleneck 790 00:34:33,620 --> 00:34:34,471 in the exam room. 791 00:34:34,471 --> 00:34:35,179 HUGH MCMANUS: OK. 792 00:34:35,179 --> 00:34:37,670 AUDIENCE: So when it boiled down to the root causes, 793 00:34:37,670 --> 00:34:41,989 we thought it was due to triage failure, potentially 794 00:34:41,989 --> 00:34:44,210 due to inadequate training here in triage-- 795 00:34:44,210 --> 00:34:45,110 HUGH MCMANUS: OK. 796 00:34:45,110 --> 00:34:47,600 AUDIENCE: --as well as test failure 797 00:34:47,600 --> 00:34:52,370 due to equipment issues, for example lack of maintenance, 798 00:34:52,370 --> 00:34:55,850 more training required, and a protocol 799 00:34:55,850 --> 00:35:00,750 that just would make the process less efficient. 800 00:35:00,750 --> 00:35:01,760 HUGH MCMANUS: Right. 801 00:35:01,760 --> 00:35:06,860 So the rework issue from diagnostics 802 00:35:06,860 --> 00:35:08,690 is easy to understand. 803 00:35:08,690 --> 00:35:12,200 What was the issue with triage? 804 00:35:12,200 --> 00:35:14,630 AUDIENCE: So we potentially were thinking 805 00:35:14,630 --> 00:35:18,170 that we could start cross-training staff 806 00:35:18,170 --> 00:35:21,320 between registration and triage because this might just 807 00:35:21,320 --> 00:35:23,255 be a step that we don't need necessarily. 808 00:35:23,255 --> 00:35:24,160 HUGH MCMANUS: OK, so you think there's 809 00:35:24,160 --> 00:35:25,310 some inefficiency there. 810 00:35:25,310 --> 00:35:27,020 AUDIENCE: Well, in triage, the doctor 811 00:35:27,020 --> 00:35:29,840 was seeing levels of care that were either too easy, 812 00:35:29,840 --> 00:35:32,750 they could have been managed by triage to either discharged 813 00:35:32,750 --> 00:35:35,630 to home or sent to the hospital without ever seeing the doctor. 814 00:35:35,630 --> 00:35:38,360 So he could have seen fewer patients if triage was-- 815 00:35:38,360 --> 00:35:43,160 HUGH MCMANUS: OK, so triage was feeding unnecessary work 816 00:35:43,160 --> 00:35:44,700 to the doctor. 817 00:35:44,700 --> 00:35:46,160 OK. 818 00:35:46,160 --> 00:35:47,600 You folks? 819 00:35:47,600 --> 00:35:50,390 What's your top two? 820 00:35:50,390 --> 00:35:55,340 AUDIENCE: We think one of them is too much patient movement, 821 00:35:55,340 --> 00:35:58,090 having them shuttle back and forth to the waiting room. 822 00:35:58,090 --> 00:36:03,140 It created a lot of confusion for all areas 823 00:36:03,140 --> 00:36:06,810 in that we didn't know where they were supposed to go next. 824 00:36:06,810 --> 00:36:09,900 So that kind of covered actually a couple of them. 825 00:36:09,900 --> 00:36:14,610 We also have the inefficient registration triage system 826 00:36:14,610 --> 00:36:18,460 and also the [INAUDIBLE] information flow, 827 00:36:18,460 --> 00:36:22,020 where the chart was getting separated from the patient 828 00:36:22,020 --> 00:36:26,470 and going to the chartroom in between each time. 829 00:36:26,470 --> 00:36:29,615 And really one way to solve that would 830 00:36:29,615 --> 00:36:31,705 be keep the chart with the patient 831 00:36:31,705 --> 00:36:33,190 as they move through the system. 832 00:36:33,190 --> 00:36:35,470 HUGH MCMANUS: So you focused more 833 00:36:35,470 --> 00:36:38,080 on the detractors for the bottleneck, 834 00:36:38,080 --> 00:36:41,860 while you guys are focusing more on the overall process 835 00:36:41,860 --> 00:36:45,690 issues of the confusion of having the patient moving. 836 00:36:45,690 --> 00:36:47,050 These are both valid. 837 00:36:47,050 --> 00:36:51,240 It's interesting that folks are getting kind of different-- 838 00:36:51,240 --> 00:36:52,930 so who wants to speak for this table? 839 00:36:52,930 --> 00:36:55,027 AUDIENCE: So we also agreed with them, 840 00:36:55,027 --> 00:36:56,360 so I won't reiterate that point. 841 00:36:56,360 --> 00:36:57,818 But one minor thing that we noticed 842 00:36:57,818 --> 00:36:59,901 is we had a lot of unused capacity in diagnostics. 843 00:36:59,901 --> 00:37:00,610 HUGH MCMANUS: OK. 844 00:37:00,610 --> 00:37:02,690 AUDIENCE: And we had a backup with the physician. 845 00:37:02,690 --> 00:37:04,340 And the physician didn't have a method 846 00:37:04,340 --> 00:37:05,923 of choosing which patient to see next. 847 00:37:05,923 --> 00:37:11,660 So we set up a signal system whereby any unused device 848 00:37:11,660 --> 00:37:14,363 would be set in front of the eyes of the physician 849 00:37:14,363 --> 00:37:16,530 so that she could pick the right patient to see next 850 00:37:16,530 --> 00:37:18,363 instead of running back over to diagnostics. 851 00:37:18,363 --> 00:37:19,370 HUGH MCMANUS: Yeah, OK. 852 00:37:19,370 --> 00:37:20,410 AUDIENCE: [INAUDIBLE] 853 00:37:20,410 --> 00:37:25,370 HUGH MCMANUS: So looking at the outflow from the physician, 854 00:37:25,370 --> 00:37:28,070 making sure that patients didn't have to wait on the other end, 855 00:37:28,070 --> 00:37:28,890 as well. 856 00:37:28,890 --> 00:37:29,390 Yeah? 857 00:37:29,390 --> 00:37:31,900 EARLL MURMAN: That's a really good instance of pull. 858 00:37:31,900 --> 00:37:33,020 HUGH MCMANUS: Yes, yep. 859 00:37:33,020 --> 00:37:37,340 EARLL MURMAN: OK, you can see what the diagnostics could use. 860 00:37:37,340 --> 00:37:39,780 And they really have something set up almost 861 00:37:39,780 --> 00:37:40,655 like a [? combine. ?] 862 00:37:40,655 --> 00:37:43,280 HUGH MCMANUS: It's almost like a [? pull ?] [? combine, ?] yep, 863 00:37:43,280 --> 00:37:45,920 that, yeah, the patient is pulled into diagnostic based 864 00:37:45,920 --> 00:37:48,250 on the availability.