PEPFAR Quality Control and Method Validation Activity 3: Part 1

We use QC to monitor and alert us to changes, and we actually use QC rules to alert us when that Gaussian pattern has changed. Now many times we learn QC rules by having them presented to us on a PowerPoint slide. We briefly discussed the rule and then we move on to the next PowerPoint slide, but that's not the way we do it in SLAM to. And slam to. We're actually going to apply the QC rules. And we're going to be doing it in a game called match it up. It's a rule violation game, so for the next couple hours we're going to just be playing a game. But before we go on to that, let's just review. Yesterday we learned about how statistical quality control works. We have a single population an we have the past history of previous results and that gives us our mean in our SD. So there's our Gaussian distribution. We analyze a QC specimen an with today's observed value. If where we are today is where we expect it to be, the system is stable, however. If where we are today is not where we expected to be, the system has undergone a change and we are alerted to these changes with our rule violation. So all a rule violation is is just saying hello hi, you're too far from the mean of past results to be part of the same single population. A change has a curd. Now go look into it. That's all. A rule violation is telling us. So let's talk a little bit about terminology so that we can play the game effectively. First of all, we have a single rule and that single rule that control rule is just a criterion to determine if that run is acceptable or not. Is it in control or not? So we're using a criterion to determine is it good is the is it good enough to report out results? So that's a control rule. Then we have control limits on the Levy Jennings chart. Those are just the lines that we draw on the left. Jennings chart and typically when we exceed a certain control limit, that's when we stop and begin our troubleshooting, 'cause we've been alerted to a change, and Lastly, is the analytical run. The analytical run that analytical run is an interval an it can be an interval of either time or maybe numbered specimens, so maybe every eight hour will be an analytical run, or maybe every 50 patients will be an analytical run, but it's that time. Or number specimens that interval in which we use to determine if that run is acceptable or not with the criterion that we've selected. So. One of the things that we have to start thinking about with an analytical run is it's that time period where we expect the accuracy and precision to be stable, but but how long should that be? What? What kind of rule of thumb or guidelines are there for us to determine how long an analytical run should be? Well, there really aren't any. We have to actually start thinking about stability versus susceptibility an it's a balancing so you always have to start thinking about how well you can balance stability with susceptibility on the stability side. We already have a maximum length. The frequency of the calibration specified by the manufacturer. When the manufacturer says you have to calibrate every 24 hours there, they're saying. It can't be stable. They can't assure the accuracy or precision longer than that time period, so you could actually use the maximum calibration specified by the manufacturer as part of way to determine your analytical run. The other thing is post storage stability. You know how long are the analytes good? For me? If you find out that the results were not correct and you need to retest, you need to make sure that the specimen is still good enough. To retest so some of our issues with post storage stability, we need to start looking at, for example, many of our glucose is in potassium's are lying directly on the cells, so their stability is much shorter than if they would be separated off of the cells. So we always need to also think about stability. How long is it before I need to in can retest the specimen once alerted to a change? That's the stability side of it. Now, let's talk about this susceptibility. You know, anytime we introduce the possibility of change into the system, we need to really ensure that it hasn't truly changed. I mean, we are a high risk industry. We need to monitor the risk that we're involving. So the first thing is, anytime we introduce a change, we should start thinking about verifying that there hasn't been a significant change in the process. So the first one is known events. These are planned activities. We know when we have to calibrate. We know when. We have to do maintenance. We know when we're changing reagents, these are known possible changes to the analytical system and we should go out and verify that they are still acceptable. The other one though is the unknown events. Those aren't planned. Those sort of happen and we don't know it. And not only do we have to figure out what has changed, but we also have to figure out when it has changed when it has changed. So let's go over to the board a little bit. And talk about analytical runs when we do an analytical run. We run a QC sample. And if that sample is good. Right, it's OK. Then we begin running our patients. And then we run a QC sample. And if that's good. Then we assume in this bracket. That the patients were also acceptable that the patients were giving out the correct results. The only problem here is in high automated systems. We run the QC. We report out the patients. And then we run the QC that brackets it. So no where are we assured that they are acceptable until we end the bracket. Now years ago when we did batch testing, that wasn't a problem. We started with the QC. We ran our batch. We ended with the QC and we reported out the patients. But now with that automated. Analyzer's an continuous throughput. It puts us into a whole different situation, so we need to start thinking about these unplanned events. So if I run patient after this. And my QC. Is good then. I know that these are fine as well. However, I've reported them out. Now I come to run. My patience. And my QC is not good. So not only do I have to find out why my QC has failed, why I no longer meeting the criterion that I selected. I have to find out when did it happen on this patient. Did it happen on this patient? It makes a difference about who I need to go back and retest, especially the magnitude of the error. Now we need to start thinking about what kind of risk we can assume in our organization. If, for example, in a 24 hour period you run 50 tests. And another lab does 200, then they may not want to do every 24 hours because they'd have to recover from 200 patients if they may want to do this in a shorter increment once every eight hours, or maybe after every 50 patients. But you still need to go back and relook at the patient since your last successful QC attempt. So what we want to do is reduce the amount of risk. Now that's when it's an unknown event. How about known events? How about known events? Well, again, we're going to start off with our QC. And it's OK, and we go on to our patients. And we end for the day and then we come the next morning and we do our maintenance. This is maintenance. And then we do our QC after our system checks. Now if the QC here fails. When did it fail? Did it fail at the maintenance or did it fail the day before? We don't know. We don't know. Not unless we bracketed out these patients. So if I did QC here and the QC was good, the QC was OK. Then I know the change occur that maintenance, but if I didn't do the QC before introducing a known change, I don't know when it a Kurd an. If these patients were affected. And this brings us to one of the issues with both ISO an on the slip to check list. So let's talk a little bit more about stability and susceptibility in the analytical run, because again, we're trying to determine how long these runs should be. Even I so tells us that the quality control material shall be periodically examined at a frequency the analytical interval that is based on stability and risk of harm. So even ISO is saying, hey, think about your analytical runs with stability and susceptibility. Goes on to say a couple more things that we want to be aware of. First of all, we need a procedure to prevent the release of patient results so the analytical run has to be deemed in control based on the criteria we used. Then we have to look to see when these rules are violated. If they contain a clinically significant error. Now ice is not saying to change, it's saying a significant error, and we're going to later in later activities, be able to determine is it a change or is it is significant change because we know we can have smaller changes throughout when we change reagent lot numbers or calibration. But here's the other thing. The laboratory shall evaluate results from patient samples that were examined after the last successful quality control event. I said was saying that if your QC fails here and you didn't bracket out your patience, your last successful QC event was yesterday morning and you need to start looking at all these patients. So one of the ways we can reduce risk is always bracketed out and the day. With QC, when you come in in the morning to do maintenance and run QC, you can identify where the problem happened. Something very simple to do, but we can start reducing the risk of releasing wrong results. An not only is I so saying since the last successful quality control event. But our slip to checklist is saying it is well in eight point 10 when we talk about QC results in B, does the laboratory evaluate the results from patient samples that were examined after the last successful quality control event? So everyone is saying you need to be able to assure that these results are correct? An again with that continuous flow of specimens through automated systems. It's very easy to release a large number of patients incorrectly, so we need to really start thinking about how much risk can we accept by the size of our analytical run, either in time or in numbers patients. So that's analytical run. So again, some of the common terms we learned about control rule decision criteria to assess whether the run these patients within the bracket is acceptable or not. Types of control rules, single rules, it's just a single criterion. Use such as a 13S or 12S. Then we can use a multi rule and here it uses a combination of criteria for each. Analytical run, so we're using more single rules together and we know that we're using more single rules together. We're applying them simultaneously with the nomenclature of the slash mark, but in this game that we're going to play today, we're only going to deal with single rules tomorrow will deal with multi roles. Again, just to review, the analytical run is that interval and the control limit or the lines the plus and minus one plus and minus two and so forth on the levy Jennings. So now we come to rule Nomenclature rule nomenclature can be written two different ways. The first one is the A. That's the number of control measurements involved. Then the L can either be a subscript or after a colon, and that's the control limits. Remember, I said control limits are those lines on the chart that plus and minus one plus and minus two. So the L refers to the control limit. That's rule nomenclature. So using this nomenclature that we just learned about, if I had something like a. 2. 2S. How many control measurements are involved? 2. And it exceeds what control limit? The plus or minus two, so that's rule nomenclature and all the rules go like that except for a few. And let's review those because they are part of the game as well. The other one would be the R. 4S now are can sometimes I've seen it written as random or range, but I like range because it's a range of four S so it differs. By 4S D. So it's a range of four SD, but it refers to a random. The other one would be a 7 T. Now how many data points are involved? 7. And the T stands for trend and the trend is also known as a drift and that can be seven data points that are increasing. Cecut, ifli or decreasing consecutively, and they may or may not cross the mean and then the last one we're going to just look at is the 10X. So when I have an XI always think of me. So this is how many data points on one side of the mean. 10 So ten data points, either above the mean or 10 data points below the mean, so these are the rules. They either follow this nomenclature, or we're going to work with the R4S70 and 10X. OK, so it's now time to play our game. The rule violation game and what the purpose is is to match the charts and histograms to the correct QC rule violation. Remember, I said we're not going to look at them on PowerPoint. We're actually going to apply them, so you'll need a rule violation packet and each table will have their own packet, so each table will have their own packet. You'll need a worksheet answer sheet and it's in your participants manual. I'll show you that in a minute, along with handouts to help with determining. Is it a rule violation or not. And also. Tape and scissors. And each area has that. And what we're going to do is, you're going to be working in groups, so you see around the classroom that there are postings of where each table will work. So table number one. And table #2 you're going to take your packet an actually work where the post it notes on the wall say you will be working, so everyone look around the wall and find out where their table will be working as we do this rule violation game and the way we're going to do it is you're going to cut apart the rule violation nomenclatures. So in your packet, the first page are nine single rules and you're going to cut them apart. And you're going to post them on the wall. Then you're going to match the charts with the appropriate heading. So each there's 19 charts in here. There is 19 charts in each packet, and there's a number on each chart. Some of them will be Gaussians, some of them are going to be Levy Jennings charts, but you're going to match these up to the nine headings that you've already cut out and posted on the wall. Once you're done that, you're going to populate the first 2 columns of your worksheet. Annual refer to the handouts to assist your group with matching. So let's work through this a little bit more before we go to the wall. OK, the first one is the handout. This is on page 17 and it's just up on the screen as well. But This is why the Gaussian curve looks like in regards to the distribution or the probability of a data point lying in this area based on randomness. On page 18. Is the same probability. Beginner Levy Jennings chart. So you can use these two handouts to determine are you looking at a rule violation or are you looking at just randomness? Because if it's not random then it's just telling us that it's not the same expected Gaussian. So either it's randomness or we have a problem. A new Gaussian is emerging so you can use these two handouts to figure out what is the probability of that data point lying there by randomness alone or. Maybe indicating the emergence of a new population. Now let's just practice a little bit before we go. When you look at Levy, Jennings charts or Gaussians, but particularly Levy Jennings charts. That's a lot of charts that you'll be reviewing in your laboratory. And there's several ways that you can quickly review it. The first one is to use the 12S rule as a scanning device. So when you're looking at these charts, trying to figure out if there's a rule violation, and if So what rule violation is it. Once we have the nomenclature, use the 12S as a scanning device. Just quickly go through and look for any data point above or below 2 SD. Stop and look around. Look around as to what happened earlier. Look around to what's happening in other levels. So use the 12S rule as a scanning device. The other thing you do is you start looking for clustering away from the mean. Remember if it's the normal Gaussian that predicted pattern, I should see half above and half below. But if I see them clustering somewhere else other than the mean on the levy Jennings chart, then I know there's a problem emerging that it's a new Gaussian starting to emerge, so we'll also look for abnormal clustering away from the mean. So these are two devices that we can use to detect rule violations quite easily because you are going to be looking at a lot of Levy Jennings charts over the years and this helps. So let's just try an example real quick. First of all, let's try the 12S scanning rule, so we're going to look for any data points above, and any data points below, and we see this one here. As soon as we see it, we want to stop and look around and what I'm seeing is that everything is fine, so this is just going to be that part of normal inherent random distribution. This is in that 95% area that exceeds that 60 eight 9599. So we're OK there now. We don't see any other 12S is. Let's look for abnormal clustering and all of a sudden I do. I see abnormal clustering here and it's not around the mean, it's away from the mean. So that's trying to tell me, wait, there's a maybe a new Gaussian emerging. So once we've identified that there is a new Gaussian emerging, now we have to label it. So how many data points are involved one? 234 so we have a four. And what is the control limit that exceeds? Well, it exceeds the 1S, so this is a called a four. 1S. OK, so that's the rule violation. This is why it starts to look like in a Gaussian when I'm having four data points fall here. This is not the Gaussian anymore. It's going to be a little bit more over here. It's shifted this way. I now have four data points here, so it's not the same Gaussian as before, and that's giving us an idea that the Gaussian is changing, so that's what you're going to use your going to use Gaussians. And you're going to use Levy Jennings chart and identify the nine rule violations in this packet. Now on page 19. Is your rule violation worksheet and we're only going to do part one for now. Part 2 will be later, so only focus on part one. You have 19 pieces of information in here and they're all labeled. 1 to 19 K. How many pieces of information go with each rule? Well, when I look at the 12S, I'm looking for two pieces or two numbers. When I go to the 13S, I'm looking for two pieces of information or two numbers. When I go down to the R4 S, I'm looking for three pieces of information, so use the worksheet to guide you as to how many pieces of information go with each rule violation. Are there any questions before we begin? Alright, then what we're going to do is take your packet your scissors anyer tape, go to the appropriate space on the wall an you have the next 30 minutes.

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Laborator) 2) Type num reviewed(including biases and Levy- reviewed(including bi Levy- The OF periodic Teview b) The achons ±ahen when resul+s b) The achons ±ahen when Quality b) when resul+s b) The achons when b) The achons +Q16en when resul+s b) The achons +Q6en when resul+s b) The achons ±Q6en when What will you n Goals The of periodic review For The 09 periodic review for of periodic review Quality The 09 petiodlC review 10 Results The of peviodlC review The of periodic review for Type and number of sompks ±esfed def The of periodic revtew for evalua+e Laborat01 defec+lnj and +rends 3) QC ased +0 q) The 09 peviodlC review for Goals Goals QC used • To match charts and histog,rarm To match charts and histogram Laboratory q) The 09 peviodic review for q) The of iew for q) The of q) The of peviodic q) The of viodic review q) The of peciodlC review q) The of peviodic review for q) The 09 peciodic review The of peciodiC review periodic review for QC ased +0 QC used +0 defec±inj an Labo Labc The OF periodic review and *rends fid s • To match charts and histogram • To mnatch charts and histograrr • match charts and To match charts and [o match charts and defec+inj and +1 nornenclature to create 9 h Laborator Results Frequency of AC +es+ Goals 1:2S or Goals Results Quality Quaceptibility Qua it Laborator q) The of review for q) The of review Goals appropriate heacling. Use Worksheet Frequency so Results b) The achons ±Qhen when 2) Type and number of QC used +0 11ts b) The achons +ahen What Will you need? Results defec Rule used +3 SD -1 SD -3 SD The of periodic review q) The 09 peviodiC review q) The of petiodlC review The of periodic review q) The of petiodic review The of ic review The of petiodic review The Desi review for The of periodic review- The 09 peviodic review The of petiodlC review for The of periodic +3 SD -2 SD of peviodic review of peciodic review Laborator defecflnj and *rends The of peviodic review The of peciodic revie.w The of periodic for ID The of periodic review The of review The viodiC review for The of peciodic review and *rends Results System Goals The of review for The of petiodlC review System The veview b) The and +cends used Laborator b) The achons b) b) The achons. of pevtodlC review defec+inj and *rends Res when resul+s The 09 periodic review of review Results b) Is IS b) The achons +a6en and fid *fends -view for exceed defecfinj and *rends Laborator Frequency q) The 09 peviodiC revtew q) The of periodic review for q) The of periodic review The periodic review for q) The periodic review for The of periodic review q) The periodic review acceptability (in«ontrc Laboratory The of pevtodtc revtew and *rends Labor Quality efec+inj and +rends *ec+inj and *rends Introducing a change *fiends Laboratorix • Control Rule - a decision criteria to assess d +cends Its and +rends WIIat Will you need? exceed QQCep+Qåle and +cends and +cends exceed acceptable I evalaaVe evaluaVe periodic review and +rends Quality exceed accep+Q61e to the correct QC rule vtolat:ior• to the correct QC rule violation [D periodic review b) b) n when resul+s to the correct QC rule to the correct QC rule violatior +hen • not acceptc peviod'C revaew en resul+s SD Laborator Laboratory review and *rends clinically Sl clinically s clinically fid +rends Type and number Of and *rends Laborator q) The of peviodtc review number b) The achons +Qhen susceptibility to change 09 review when resul+s Qhen when resul+s Goals Resu defecfinj and *rends Results The OF peviodtc review for The of periodic revtew The OF review WHERE WE EXPECT ro BE ' Quality q) The of pevicdrc review when resul+s Match up t Match up The periodic review Match Match t Goal evalua+e achons when resul+s Fvequency of frequency Quality The 09 pevtcdtc review What Will you need? What you need? What Will vou need? Laborato Goals release of patient results in the event of quality control Results defec+inj and not acceptable or react to the examining system in a manner as close as The periodic review for Match up the charts With Quality defect b) The achons wh defec+'lnj and +Qhen when resul+s hen when resul+s Ken when resul+s iaboratory Ions +Q6en when resul+s + QhKen when resul+s a) Is th defec+inj and ' *rends number defec+lnj {Q hen when resul+s Mean exceed qccep+üåle exceed exceed acceptable exceed accep+aåle limi+s b) The achons +Q6en when resul+s Laborator Goals and exceed accep±üle Rule Violations and *rends The of periodic review for and *rends/ Laboratory 13 s ruu 13 s ruli de defeci-inj and +rends defec.•hnj defec-hnj and Laborator 13 s rul< '13 s rul< b) The achons — b) The achons ±ahen b) When b) The when s and *rends Goals Laboratory Goals Results The Fretuency of periodic review The OF pevicd'C review The achons ±Q6en when Jennings charts for quantitative tests)? ua It Laborator) q) q) The revtew and +rends OF periodic review defec.f-inj and and +rervis Goals defec+iny *rends defec+lnj and *rends defec.±inj and *rends ichons ±Qhen when resul+s Ions +Qhen when resul+s achons ±Q6en when resul+s achons +Q6en when resul+s ±Qhen when ed QQCep+QåIe defec+inj d&ecfinj and *rends defec+inj and *rends d±ec+inj defec+inj an defec±inj and - +rends The OF periodic review for is take defecåinj a defeciinj q) of pevicdlC review for q) The of pericdtc review exceed QQQep+±Ie b) The achons Laborator z' numbec Laborator Laborator Goals exceed acceptable l, defec+irw What will you dop d*ec+inj and d±ec+inj and +rends a) Is there dc appropriate app r upriat€ 3s Results Goals aben when resul+s defec+inj and *rends defec+inj and +rends defectinj and *rends exceed C(QQep+Q61e 23.5% and +cends and +ce Kh6en when resul+s • Types of Cor 2.5% number exceed exceed accep+aåle and *rends ions when ons when resul+s when Rule and *rends your group b) The achons when b) The achons wahen rhen exceed accep+oåle exceed occep+oåle and +cends b) The achons ±aKen when Purpose The Fretxenc.y OF periodic review Quality q) The of periodic review The of periodic review b) when resul+s +cends fids to the viola Results Laborator Laboratory rends OF periodic review for of periodic review The of peviodlC review q) The of peciodlC review The of review The of periodic review for Results Goals Results We Expect Expect ao b) The achons when to the violation. exceed QCCep+Qhole Results Sheet b) b) The when resul+s b) The achons faHen when resul+s b) The achonsz- b) The achons +ahen when resul+s b) The achons b) The achons åQhen when resu14s q) The of periodic review for answer Sheet Laborator b) The achons wQhen Where when resul+s Results Results b) The achons +QKen - en when resul+s S +aHen when resul+s Rule Violations Packet (one b) The achons when W b) The achons +Q6en when and +rends achons ±Qhen when resul+s Rule Violations Packet (one set Rule Violations Packet Laborator b) The achons ±ahen when b) The achons ±Qhen b) The achons +ahen when Results ua it b) The achons +Qhen Goals when Goals -Is periodic review 2. 2:2S or 2:2s 1:2S or Use the Hons +QKen when Quality and releva whether an analytical run is: hetheT*h8nalytical run is: b) The achons when resu14s b) The ad-tons +ahen when Quality b) The achons when S when The Accuracy Quality Laborator exceed QQQep+oh,Ie Results 4 consecutive b) The achons ±Qhen when We Are Laborator xceed QCQep+QåIe licni+s b) The when b) The achons when resql+s +Qhen when resul+s b) The when resql+s b) The when resul+s hen when resul+s .n when resul+s b) The Hen when resul+s when resu14s b) The achons when b) The achons ±a6en when b) The faKen when resul+s Laborator Results SD obs b) The achons ±QKen b) The ach z b) The achons ±Q6en when resul+s b) The achons +Q6e b) The achons +Q6ene b) The achons ±Q16en b) The achons ±QKen whee- b) The achons +Q6en b) The acho b) The achonse-• and 1) Known events —planned -Is exceed b) The achons +ahen b) The achons ±Qhen when* b) The b) The achons ±Q6en when b) b) The hen when resul+s exceed occep+üle exceed QQQep+QloIe -2s Resuits b) The achons +Qhen when b) The achons ±Qhen • Goals en resu14s en resul+s Goals Hen when resul+s -3s Is ua It Results to Goals exceed exceed What Will you need? What you need? defec+inj achons +aKen and *rends and +rends defec+' and when resul+s Laboratory Control taken wher Quality and +rends per group) your group ceed accep+oåle b) The achons wh b) The achons w ins ±Q6en when resul+s +Q6en when resul+s Results Results b) ach exceed b) The ad-tons when ua it hen resul+s Ealytical Accuracy PEPFAR QC Workshop øeed exceed b) The achons uall€ per possible to patient samples. b) The achons ±ahen when re QCQep+Q61e qccep+üåle Goals Q6en when resul+s QQQep+QåIe acceptable Qua it failure. ua it Q16en when resul+s hen when resu14s fen when resul+s Laboratory Goals violation violatio Results Precision exceed n resul+s hen resul+s Attach both heading and charts to defec+ino and -hen resu14s expect Analytical Laborator Laborator The error cond The OF review Results + 2 SD + 1 SD - 2 SD en resul+s Results Vs and +cends Resul+s Quality The revtew ±Qhen when resul+s defec+inc +Qhen when resul+s WHERE WE EXPECT ro WHERE WE ARE Laborator Quality Quality Quality to the wola to the viola ua It . ions fa16en when res +s s and and +cends and WHERE WE EXPECT mo BE WHERE WE ARE Goals to the Laborator exceed occep%ble exceed occepfüIe b) The achons fahen when resul+s the Goals Use the Soens when resul+s MEAN obs Laboratory ex The achons when resul+s error to Results WHERE we EXPECT ro WHERE WE ARE 2 SD b) The ach b) WHERE WE WHERE WE ARE WHERE WE EXPECT ro BE WHERE WE ARE WHERE we EXPECr ro WHERE WE ARE WHERE WE ro WHERE WE ARE exceed SD Working in groups, you will: WHERE WE EXPEcr ro WHERE WE A RE Results . 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WHERE WE EXPECT ro BE • b) The achons whKen rhe: b) The achons when resul+s b) The when resul+s Laborator Goals exceed qccep±üle • Rule Violations Packet (one Rule Violations Packet Rule Violations b) The achons +a6en Goals b) The Quality exceed accep+Q61e limi+s exceed accep+Q61e exceed QQCep+Q61e 5) The ac+tons +Q6en ua t WHERE WE ro BE WHERE WE ARE WHERE WE EXPECT TO WHERE WE ARE WHERE WE expecr WHERE WE ARE WHERE WE ARE when resul+s b) The exceed exceed ac exceed acceptable exceed accep+aåle exceed QQcep+Q61e ltmi+s b) The achor b) The achons exceed QQQep+Q61e WHERE WE EXPECT ro BE WHERE exceed QQcep+Q61e WHERE WE expecr ro BE WHERE Goals WHERE WE EXPECT ro BE ' Results detec±inj Results Susceptibility Frequency ro WHERE WE EXPECT ro , acceptable e ad-ions fQ6en when resul+s Laborator Results WHERE EXPECT the wall board. Quality WHERE WE EXPECr ro The achons exceed the wall board, \ons ±Q6en when resul+s Quality and conf exceed accep+061e review *rends WHERE WE EXPECT ro WHERE m WHERE WE ARE Matach Attach both WHERE WE EXPECr ro BE e) System exceed OCCep+nh exceed accep+oble exceed QQQep+a exceed , exceed exceed QQQep+061e exceed QQQep+o exceed acceptable li ed when resul+s ( Control Limit) Control exceed QCQcep+061e exceed QQCep+a61e exceed QCcep+Q61e ahen when resul+s en when resql+s Control acceptable (in-control) en whet when Labe Syste= .d +QKen when resul+s System 1:3S or 1. 10 the data pc Control Results Work wall Laboratorw, • Handout l: Bell with Handout Bell Curve With • Handout l: Bell Curve with • Handout l: dell Curve with Handout IIÆ Bell Curve With Handout l: Bell with Handout l: Bell ua ity ua it ua it WHERE WE EXPECT ro BE WHERE WE ARE Goals ed exceed WHERE WE A RE lit WHERE WE per group) WHERE WE acceptable Control; specifi sceptibi/ity WHERE WE EXPECT ro BE' calibration, reagent charm calibration, reagent chamges, b) when b) The WHERE WE EXPECT roE •xceed ARE ua It WHERE we A Re ua It -2 SD, -2 SD 13.5% Results WHERE WE ARE • to the correct QC rule violation. to the correct QC rule violation WHERE WE ARE —WHERE ua WHERE WE EXPECr ro WHERE WEARE WHERE WE WHERE Quality ua it Qua it Control WHERE WE WE ARE ua It WHERE Go WHERE we WHERE WHERE WE EXPECT ro WHERE WE ARE Tick for each item as Yes (Y), the wall wall we WHERE WE ARE we expecr Yo we WE we WHERE WHERE WE WHERE WE ARE the b) The when ; •4 WHERE WE ARE exceed exceed Control ua It WE WHERE wc Re ua t ua it ME EXPECT ro BE WHERE WE ARE Cut apart the rule violation WHERE WE EXPECT ro BE 4 ua exceed occepiüle Control Results When the quality control rules are violated and Quality ua it conformities In ti WHERE WE rWHERE RE WE ARE WHERE WE EXPECT ua It acceptability (in-control or out-of-control) is WHERE WHERE WE EXPEcr ro BE W WHERE WE EXPECr ro Quality WHERE WE ARE conformities , ro BE WHERE WE EXPECT ro BE Distributions .2 Control ro we exceed exceed OCQep±oåi ex ro WHERE WE ARE HERE WE ARE ua it we expecr ro ' RE WEARE ME ARE WHERE WHERE we ro De ua It ro ' specificati( device WHERE expecr ro we we expecr ro we . we expeer ro BE expect to expecr TO WE ARE WHERE WE ro WHERE WHERE WE WHERE WE ARE occep+ohole ro WHERE WE EXPECT ro BE ' ua ua lty b) The achons whKen r WHERE WE ARE WHERE WE EXPECT WHERE WE with WHERE WE EXPECT TO WHERE WE EXPECT ro Use the WHERE WE EXPECT ro BE ' WHERE WE EXPECT ro BE WHERE WE a scanning WHERE WE EXPECT ro BE' E WHERE WE A RE WHERE WE EXPECT ro WHERE WE Control; Use the ua it WHERE WE ro BE ua 1 WHERE WE EXPECT ro BE'• Quallty Controli Control, Controle WHERE WE EXPEcr ro BE WHERE WE ro BE WHERE WE EXPECr ro B WHERE WE EXPEcr ro WHERE WE EXPECr ro • Handout 2: Chart WIth Worksheet: Answer Sheet •1:2s rule as WHERE wr WHERE WE RE • Worksheet: Answer Sheet — number of cont -3 SD WHERE WE EXPECT ro WHERE WE ro : ua It yste vste we WE RE ro we ARE ro WHERE WE RE WHERE WE ARE we ARE WHERE we we ro we we ro ee we ro WHERE we ARE latit achons ARE Control vystem ualit exceed Control! ua DE WHERE WE ARE WHERE WE EXPECT ro WHERE WE , WHERE WE EXPECT ro BE ua 1 Control and maintenance WHERE wr EXPECT WHERE WE EXPECT ro B beyo WHERE b) we ua It exceed System ua It Cont?ol irol Control Control ontrol Control Partial (P) or NO(N) WHERE WE EXPECT ro BE' • populate fir Populate fir fir System WHERE WHERE WE EXPECr ro BE ' WHERE WE WHERE WHERE WE EXPECT ro WHERE WE WHERE WE EXPECT ro WHERE WE • Handout Chart with • Handout 2: Chart with • Handout 2: L_-J Chart with • Handout 2: 1--1 Chart With 1:3S or 13 s 1:3s or 13 s 1:2s or 1:3s or WHERE WE EXPCCF ro WHERE WE We • Handout 2: IA—J Chart with • Handout 2: I.-J Chart With ua i Quality HERE R:4s or R ua it exceed l, yste_ 4:2s rule as exceed WHERE we ARE WHERE we WHERE WE ARE WHERE we we ARE ARE RE WHERE WE uahit Qua it WHERE WE ARE Control- Control uali WHERE WE ARE Control WHERE WE ua t Control ua It not acceptable (out-of-control). WHERE WE WHERE ua it +1 SD WHERE WE EXPECT ro WHERE WE , WE ARE WHERE WE EXPECT ro BE WHERE WE ARE WE ro WHERE WE ARE Iuality WHERE WRE Control Multirule System WHERE WE EXPEC rol Quality Quality WHERE WE WHERE WE ARE, ua WHERE WE ARE WE Handout ': Bell Curve With 1:2s rule as WHeRE Control WHERE we weRe we -2 SD) Handout Bell Curve With Distributions nomenclature to create 9 headings. re b) Does the laboratc ystem WHERE WE EXPECT ro DE' • Handout l: Bell with • Handout ': Bell Curve With Handout 'l: Bell Curve With WHERE rube as 'WHERE WE ARE we SD _ l: Bell Curve WHERE WE EXPEC WHERE WE ro BE WHERE WHERE WEAR WHERE WE AHERE WHERE WE EXPECr ro BE WHERE WE WHERE WE ro BE WHERE WE ARE WHERE WE EXPECr ro BE WHERE WE ARE Laboratory WHERE WC EXPEcr ro WHERE WC ro WHERE we expccr TO or expecr ro ' Quality ua it so. (Cont WHERE WE EXPECr ro WHERE WE ARE WHERE EXPEcr ro BE WHERE WE ARE WHERE WE EXPECT ro WHERE WE ARE WHERE WE EXPECT WHERE WE ro BE WHERE WE ARE,' WHERE WE EXPECT WHERE WE ARE WHERE WE EXPECT ro WHERE WE EXPECr ro BE WHERE ro BE WHERE WE ARE WHERE WE ro WHERE WE ARE —'WHERE WE EXPECT WHERE we WHERE WE WHERE we ro WHERE WE ARE WHERE WHERE WE ro WHERE WE WHERE WE E WHERE WE TO BE ua WHERE wr a it WHERE we ARE WHERE WE WHERE , WHERE WE EXPECT TO BE WHERE WE ARE WHERE WE EXPECT roE WHERE WE rWHERE WHERE WE EXPECT ro BE WHERE WE WHERE WE EXPECT ro BE ' WHERE WE TO WHERE WE ARE WHERE WHERE WEARE WHERE we EXE Quality we expecr WHERE WE exprcr ro BE WHERE WE expecr ro WHERE WE ARE ua 1 Quality ua it WHERE wr WHERE WE EXPECT TO BE we ARE 4:1S or WHERE WE _RE WHERE WE ARE • we AR' RE WE EXPECT ro BE 4. WHERE WE ARE ua It ua 1 WHERE WE EXPEC WE ARE we ua It WE EXPECr ro WHERE WE device WHERE V E WE ARE ARE cr ro WHERE we WHERE WHERE WE WHERE WHERE m E WHERE WE ARE we a scanning Distributions Distribution (Control, (Control r! (Control (COntrol r! Control? Control Rule Worksheet. WHERE WE WHERE WE AR ua i Ma ua yste b) Does the I WHERE WHERE WE ro WHERE WE ARE WHERE WE EXPECT ro BE WHERE WEARE WHERE WE EXPECT ro BE' WHERE WE EXPECT BE WHERE WE ARE wr ro Quality control materials shall be rol WHER - WHERE WE EXPECr ro BE WHERE WE EXPECr ro WHERE WE EXPECr WHERE HERE WE EXPECT ro 'HERE WE EXPECr ro BE RE WE EXPECT ro BE :HERE WE EXPECT ro BE WHERE WE ro BE WE EXPECr ro BE WHERE PE ro BE EXPECr ro BE cr ro BE ro BE o BE WHERE WE EXP'Cr WHERE WE - EXPECT ro BE BE WHERE we WHERE WE EXPECT ro BE WHERE WHERE WE EXPECT ro BE' ua it 7 Goals Match th WHERE WE WHERE we ARE WHERE wr WHERE WE ARE WHERE we ro Be WHERE WE ARE. we WHERE WE EXPECT WHERE WE ARE WHERE WE ARE Goals WHERE WE ARE WHERE WE WHERE WE EXPECT ro BE WHERE WE ARE iol indicate that examination results are likely to contain WHERE WE WHERE we ARE WE ARE e did expect this System ro WHERE Systey WHERE we System • nape involved The labora -2 Syste Control, yste is Is we made. WHERE WE WHERE PE ro BE WHERE we ro WHERE WE expecr ro BE Match t S ste WHERE WE EXPEcr ro WHERE WHERE WE A Re WHERE RE WHERE we ARE WHERE WE A RE WHERE WE roE WHERE WHERE WE EXPECr ro 'E E we ARE ro Control we ARC TESTING vystem System WHERE WE system Syste Introducing a change System WHERE WE ARE Systen WHERE Control Control • Tape Tape -1 Control Match Refer to WHERE WE ro BE WHERE ARE Results _yste yste Control Control Refer Syestem WHERE mE WHERE we ARE WHERE WHERE WE ARE WHERE WE" WHERE WE ARE Control? Control; Control! WHERE yste Control Look for ua It PROFICIENC from System use WHERE WE ua it ste WHERE 2) Unknown events— not WHERE WHERE we Syste WHERE WE'ARE WHERE WE ARE WHERE WE ARE WHERE WE BRE RE WE ARE E WE ARE - ARE ARE from the a scanning WHERE WE. WHERE WEARE S WHERE WE ARE ERE WE ARE WE ARE WHERE Control WHERE WE ARE What will you need? What Will you need? What will you need* -nat you neb n device -3 so Match up the charts with the Irv -3SD -2SD WHERE WE rWHERE a scanning +3 SD • Handout 2: IA Chart with • Handout 2: 1.0J Chart with • Types of Control Rules ; WHERE RE system WE ARE -3SD • Handout 2: Chart with • Handout 2: 1.0 Chart with Handout 2: Chart With Handout 2: I.-J Chart with Handout 2: IA Chart with yste WHERE WHERE we ARE ARE Mean WHERE WE ARE WHERE WE ARE System device Susceptibility • Scissors Scissors -2 SD after Quaceptibility PA Distribution -4SD -3SD -3SD -2SD your group IS QUALITY PROFICIENCY WHERE WE • Scissors PROFICI TESTING (1 WHERE WE ARE 13s rule WHERE abnormal PROFICIENCY WH TESTING so point patient san PROFICIENCY 2 of 3:2s or 2 of 3 ACTI must determine not only 13 123 TESTING Control ua it TESTING (l Distributions System L = control limits o Syste System PROFICIENCY Syste= SAMPLE Syster Systen system SING ( Activity 3: QUALITY PROFICIENCY YSte PROFICIENCY ACT after th clinically significant errors, the results shall be rejected after the IN Y-axis after PATIENT TESTING (PT) TESTING 99.7% R:4s QUALITY PATIENT appropriate heading. Use Worksheet L = control limits of cot. abnormal TESTING (PT) periodically examined with a frequency TESTING (PT) TESTING ( TESTING PROFICIEN the mean CONTROL PROFICIE' CONTROL 1-1 PATIENT PROFI QUALITY PROFICIENCY SAN ING (PT) • Tape SAMPLE Rule Violations Packe • Rule Violations Packet (one set Rule Violations Packet Rule Violations Packet (one —j Me ua ity • Control Limit -the QC chart's defined limits or Messages . Tape has changed but also whe Tape TESTING (PT) Look for QU -Is QUALI SAMPLE QUALITY Quality a) Is there documentation of corrective action (QC) PATIENT SA QUALITY TESTING (PT) 1) Known events —planned Single-rule successful QUA System -3SD -3 SD -4 SD ROL QUALITY TESTING (PT) (QC) Look for TESTIC SAMPLE PROFICIENCY PROFICIENCY QUALITY QUALITY TESTING (PT) Control CIENCY PROFICIENCY SAMPLE PROFICIEN.Y PROFICIENCY PROFICIENCY clustering TESTING (PT) QUALITY PROFICIENCY PROFICIENCY = essayes P,ROFICIENCY PROFICIENCY (QC) Scissors TESTING PROF PROFICI IS015189:20 QUALITY CONTROL to determine how many charts match Look for :ROFICIENCY PATIENT • Scissors Scissors TESTING ( PATIENT PATIENT, 34% CONTROL TESTING (PT) violation QUALITY TESTING PATIENT change occurred as part SAMPLE CONTROL the mean ± a mu co TESTING (PTY 3:1S PROFICIENCY PATIENT per group) your group QUALITY 30 minutes SAMPLE CONT TESTING TESTING (PT) SAMPLE and relevant patient samples re-examined after the TESTING (PT) PATIENT SAMPLE SAMPLE CONTROL away from Look for CONTROL QUALITY PATI abnormal • -STING (PT) PROFICIENCY CONTROL TESTING TESTING TESTING (PT) (QC) TESTING (PT) TESTING essayes essages PATIENT TESTING (PT) SAMPLE NG (PT) PATIENT TESTING PROFICIENCY (QC) CONTROL TESTING (5 PROFICIENCY PATIENT SQC. 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