WEBVTT 00:00:02.080 --> 00:00:06.810 The Dashwood screening is carried out daily by our disease at Westmead. 00:00:06.810 --> 00:00:12.330 We can have a range between 200 to 220 category one into patients. 00:00:13.200 --> 00:00:13.770 Per day. 00:00:14.300 --> 00:00:15.110 Out of this. 00:00:15.110 --> 00:00:17.250 It is expected that we see about 60 00:00:17.250 --> 00:00:21.060 to 70 Category 1 and 2 DEA patients. 00:00:21.990 --> 00:00:24.880 With the help of onsite health she dieticians. 00:00:24.900 --> 00:00:28.740 We have now managed to narrow down this criteria and are able 00:00:28.740 --> 00:00:32.310 to identify patients who will benefit most from a DEA visit. 00:00:32.970 --> 00:00:36.540 But due to feasibility issues we end up 00:00:36.570 --> 00:00:38.910 saying only about 5 patients per day. 00:00:39.750 --> 00:00:42.270 However when staffing levels are adequate 00:00:42.270 --> 00:00:44.760 at Westmead we will have a full day 00:00:44.760 --> 00:00:47.600 shift per week allocated to dashboards 00:00:48.420 --> 00:00:50.880 which can see about 40 to 50 patients. 00:00:53.790 --> 00:00:54.990 Most involved. 00:00:54.990 --> 00:00:56.880 Part of the screening process is. 00:00:57.390 --> 00:01:01.700 To identify the patients just see first taking you through the steps. 00:01:01.700 --> 00:01:02.410 Frankly. 00:01:03.000 --> 00:01:06.360 The DEA and 98 protocol patients are first filtered 00:01:06.420 --> 00:01:09.660 by transferring data onto an Excel spreadsheet. 00:01:09.960 --> 00:01:13.280 The clear fluids and fluids are excluded. 00:01:13.740 --> 00:01:17.820 Patients are then categorized into category one category two groups. 00:01:18.790 --> 00:01:21.570 Priority is given to Category 2 patients. 00:01:21.720 --> 00:01:23.700 Those having low intake first. 00:01:24.510 --> 00:01:27.870 And lastly long length of stay the longest days. 00:01:27.870 --> 00:01:31.500 Patients get priority. 00:01:34.410 --> 00:01:36.630 Once a spreadsheet is printed we go on to 00:01:36.630 --> 00:01:39.150 the wards and discuss with the patients about their 00:01:39.150 --> 00:01:43.230 particular low income low supply we preferences 00:01:43.230 --> 00:01:45.720 to see if the patient is consuming the extras. 00:01:46.110 --> 00:01:47.600 And if not make alternative. 00:01:49.190 --> 00:01:51.410 Their likes and dislikes are discussed. 00:01:52.450 --> 00:01:52.680 And. 00:01:53.590 --> 00:01:57.490 Moved from home or other sources get an ACIM pamphlet 00:01:57.520 --> 00:02:01.790 on nutrition in the New South Wales hospitals. 00:02:01.800 --> 00:02:04.030 We then returned to the office and amend 00:02:04.080 --> 00:02:06.970 the MFC notes and seaboard preferences. 00:02:07.660 --> 00:02:12.910 And finally notify the ward dietician. 00:02:13.210 --> 00:02:17.080 There are some limitations as to why the meal intake cannot 00:02:17.080 --> 00:02:20.860 be conducted by the food service assistance such as. 00:02:22.060 --> 00:02:24.550 If we have seaboard issues and the train tickets are 00:02:24.550 --> 00:02:27.910 printed on A4 paper instead of the automated printer. 00:02:28.990 --> 00:02:30.640 Or if the meal intake. 00:02:31.690 --> 00:02:34.900 Can only be done if it's been from properly promoted 00:02:34.900 --> 00:02:37.750 to the final stage of the life food choice process. 00:02:37.790 --> 00:02:39.580 So for instance when a train ticket is 00:02:39.580 --> 00:02:41.650 printed it needs to be pushed through to 00:02:42.080 --> 00:02:45.040 plating stage to reach those stage delivery 00:02:45.310 --> 00:02:47.330 and then finally the pick up stage. 00:02:47.950 --> 00:02:51.910 So if there is a place that's been missed the FSA 00:02:51.910 --> 00:02:55.580 is then counting the final intake for the patient. 00:02:55.600 --> 00:02:58.870 Recently we also found that the shortage of iPods and Wi-Fi 00:02:58.870 --> 00:03:02.050 connectivity issues caused a delay in data connection. 00:03:02.470 --> 00:03:03.130 Collection. 00:03:04.690 --> 00:03:08.490 Additionally we have found that once a day code has changed. 00:03:09.250 --> 00:03:11.230 Multiple meal intakes need to be carried 00:03:11.230 --> 00:03:13.580 out by the food services system. 00:03:13.690 --> 00:03:15.550 This leads to corrupted data. 00:03:15.940 --> 00:03:18.020 So I'll show you on the next slide. 00:03:22.170 --> 00:03:24.670 In room service you can see that this patient has 00:03:24.670 --> 00:03:26.950 changed giant codes after the cut off time. 00:03:27.800 --> 00:03:29.890 The train tickets were printed three times. 00:03:30.170 --> 00:03:30.490 That. 00:03:30.870 --> 00:03:34.600 10 0 6 eleven twenty two and eleven twenty five. 00:03:35.370 --> 00:03:37.540 And two of these tray tickets were identical 00:03:37.540 --> 00:03:40.560 as you can see on the bottom screenshots. 00:03:40.570 --> 00:03:41.940 This means that the moves to where 00:03:41.980 --> 00:03:43.990 the food service stack went to collect 00:03:43.990 --> 00:03:48.230 the meal tray they were required to take three separate meal intakes. 00:03:48.460 --> 00:03:51.970 The food service then conducted the meal intake on the first meal. 00:03:51.970 --> 00:03:54.280 As you can see by the green dots. 00:03:55.150 --> 00:03:55.540 And. 00:03:56.800 --> 00:03:59.430 For the old following meals placed in any 00:03:59.660 --> 00:04:02.620 or the recent code food or tray missing. 00:04:03.370 --> 00:04:05.560 We are still unsure how this data is 00:04:05.560 --> 00:04:07.570 then interpreted into the dashboard 00:04:07.630 --> 00:04:14.690 because there's two separate mailing texts for the same patient. 00:04:14.730 --> 00:04:17.520 Another feature of the document we're still unclear about 00:04:17.520 --> 00:04:20.970 is how the NH option affects the overall data quality. 00:04:21.370 --> 00:04:23.400 Says now had mentioned that we also have. 00:04:23.790 --> 00:04:27.230 Patients who have had a enter during meal intake. 00:04:28.350 --> 00:04:30.690 When you do do that it prompted you to put in a recent 00:04:30.690 --> 00:04:33.240 code and some of the recent codes are on the second. 00:04:33.990 --> 00:04:35.970 On the right so it can be due to diet 00:04:36.000 --> 00:04:39.160 change which is a popular one for us. 00:04:39.540 --> 00:04:43.650 If she kept tray or food or if the food items are missing. 00:04:44.790 --> 00:04:46.960 It is important that I mentioned that we all see 00:04:46.960 --> 00:04:50.160 the NRA as a reason for the UNC unaccounted data. 00:04:51.630 --> 00:04:52.320 At Wesley. 00:04:55.980 --> 00:04:58.830 Some of the challenges we face in the Indonesia shouldn't dash 00:04:58.950 --> 00:05:03.780 or daily the long list of category one patients each day. 00:05:03.780 --> 00:05:05.790 Approximately 200 patients. 00:05:05.940 --> 00:05:09.810 And since the dashboard has so much data in it it can be tedious 00:05:09.840 --> 00:05:14.030 and time consuming to be filtering out on a daily basis. 00:05:14.040 --> 00:05:16.350 We also find that the color coding the red 00:05:16.350 --> 00:05:20.640 and green is this in the analytical data section is 00:05:20.640 --> 00:05:23.640 the same for the reason code and the default 00:05:23.640 --> 00:05:26.580 meals so it can get a bit confusing at times. 00:05:28.290 --> 00:05:31.140 Lastly the risk category does not 00:05:31.140 --> 00:05:33.750 necessarily identify patients at risk. 00:05:33.750 --> 00:05:37.800 We found that most of our Category 1 and 2 patients indicate that 00:05:37.800 --> 00:05:41.640 they're consuming adequate meals from home or from other sources. 00:05:42.120 --> 00:05:44.490 However the intake does make account for this. 00:05:45.850 --> 00:05:47.580 >> Passing on so much. 00:05:47.580 --> 00:05:47.720 Thank. 00:05:47.880 --> 00:05:48.080 You. 00:05:50.400 --> 00:05:50.750 >> Thank you. 00:05:50.840 --> 00:05:51.130 So. 00:05:52.470 --> 00:05:54.990 I'll just speak about the some findings of 00:05:54.990 --> 00:05:57.330 the student project conducted last year. 00:05:57.450 --> 00:06:01.380 So there were specific errors that we had. The first was to 00:06:01.380 --> 00:06:04.820 review the quality of the nutrition additional data and display. 00:06:05.610 --> 00:06:07.340 Analyze the rate of missing data. 00:06:07.710 --> 00:06:10.350 And we also analyzed the rate of different news as 00:06:10.350 --> 00:06:13.050 was indicated by the nutrition dish at the time. 00:06:13.050 --> 00:06:16.800 The third aim was to assess the usability of 00:06:16.800 --> 00:06:19.400 nutrition dashboard data and clinical practice. 00:06:19.410 --> 00:06:20.640 And the third was to assist in 00:06:20.640 --> 00:06:23.930 the mobility and the relevance of nutrition. 00:06:32.070 --> 00:06:35.700 >> Meal data over three consecutive days or nine main meals were 00:06:35.710 --> 00:06:39.680 analyzed and then an average was calculated for each category. 00:07:03.390 --> 00:07:04.680 >> Was accounted for. 00:07:06.960 --> 00:07:09.450 >> So we discovered that nutrition Deshpande 00:07:09.450 --> 00:07:12.120 displayed many reasons for quality data. 00:07:12.120 --> 00:07:16.710 We knew about the first three reasons which were that patient kept tray 00:07:16.770 --> 00:07:22.190 of food item tray of food item was missing and patients refused meals. 00:07:22.200 --> 00:07:24.270 However we did know that. 00:07:25.810 --> 00:07:28.680 That poor quality data was also reflective of all 00:07:28.690 --> 00:07:32.340 the changes computer system errors and also where 00:07:32.340 --> 00:07:34.860 food service staff mentally entered reasons such as 00:07:34.860 --> 00:07:39.460 food item missing or when the tape was not done. 00:07:39.750 --> 00:07:40.110 So. 00:07:41.520 --> 00:07:45.240 What we found in in particular we found that the neuro gastro 00:07:45.240 --> 00:07:47.250 and surgical cardiothoracic wards 00:07:48.150 --> 00:07:51.160 averaged the highest poor quality data. 00:07:51.420 --> 00:07:53.190 And the reasons where their patients kept 00:07:53.190 --> 00:07:57.030 their tray of food item away and it was by 00:07:57.030 --> 00:07:59.760 choice the cardiology and the strong wards 00:07:59.760 --> 00:08:02.120 demonstrated the highest quality data. 00:08:02.160 --> 00:08:04.170 There were some computer system errors 00:08:04.200 --> 00:08:06.150 that contributed to the quality of data 00:08:06.210 --> 00:08:09.060 at the time and this was specifically 00:08:09.600 --> 00:08:12.160 specifically identified in three wards. 00:08:12.180 --> 00:08:17.250 This was reported to share for rectification at the time. 00:08:17.430 --> 00:08:20.100 Then we also looked at the range of different builds 00:08:20.250 --> 00:08:23.010 as was indicated by the nutrition dashboard. 00:08:23.040 --> 00:08:26.310 This time we studied the items selected in that. 00:08:26.790 --> 00:08:31.140 And where a rare segment indicated patients receiving default meals 00:08:31.440 --> 00:08:33.990 and the Green Square indicated no issues 00:08:34.570 --> 00:08:37.110 but to our discovery a blank section. 00:08:38.100 --> 00:08:39.030 Indicated. 00:08:39.810 --> 00:08:44.350 That patients did not select a meal but also did not get a default. 00:08:45.630 --> 00:08:48.090 This was not known prior to this study. 00:08:48.690 --> 00:08:51.470 And Hilscher was consulted for advice again. 00:08:52.740 --> 00:08:56.730 So we found that there was a default rate of 30 percent which was 00:08:56.730 --> 00:08:59.880 different to the health share report that we usually would get. 00:08:59.880 --> 00:09:05.280 And I think if it will agree with me we get about 15 to 16 percent of 00:09:05.280 --> 00:09:11.360 default after Michael choice was implemented for Westmead behind you. 00:09:11.360 --> 00:09:14.460 Neurology and the trauma wards have the highest default rate. 00:09:15.270 --> 00:09:18.060 Incidentally we also discovered that two out of. 00:09:18.780 --> 00:09:20.880 That two out of three study days are 00:09:20.880 --> 00:09:22.830 few wars according to the nutrition 00:09:22.830 --> 00:09:28.240 dashboard did not receive any meals nor did they make any selections. 00:09:28.260 --> 00:09:30.630 We later found that this was a system 00:09:30.630 --> 00:09:33.480 error and nominal indeed was conducted. 00:09:34.260 --> 00:09:36.220 For the mentioned wards. 00:09:36.220 --> 00:09:38.060 Now moving on to the staff survey. 00:09:38.070 --> 00:09:43.020 So we surveyed about eight dietitian assistants some open 00:09:43.020 --> 00:09:46.410 and close questions were asked such as whether the data used. 00:09:47.190 --> 00:09:48.990 Nutrition dashboard if they understood 00:09:48.990 --> 00:09:51.030 the nutrition dashboard functions 00:09:51.420 --> 00:09:53.880 the reasons why they used it and if standing 00:09:53.880 --> 00:09:57.160 of the risk category that was correct. 00:09:57.270 --> 00:10:01.890 We found that 100 percent of the dietician assistance used 00:10:01.890 --> 00:10:04.860 in nutrition dashboard as part of their work routine. 00:10:04.860 --> 00:10:09.480 However 30 percent misinterpreted the risk category. 00:10:09.480 --> 00:10:15.300 Similarly we surveyed the diet conditions and in addition 00:10:15.360 --> 00:10:19.080 we investigated if the dietitians correctly understood. 00:10:19.650 --> 00:10:20.700 The reason he. 00:10:21.280 --> 00:10:24.000 Will map at patients meal consumption. 00:10:26.100 --> 00:10:28.290 We found that almost 80 percent of 00:10:28.290 --> 00:10:31.470 the dietitians used a nutrition dashboard of which. 00:10:32.100 --> 00:10:33.180 80 percent. 00:10:33.990 --> 00:10:35.280 Viewed intake analysis. 00:10:35.280 --> 00:10:38.400 Seventy five percent looked at the data quality. 00:10:38.400 --> 00:10:40.890 Only 25 percent viewed meal selection. 00:10:41.190 --> 00:10:42.180 And 8 percent. 00:10:42.180 --> 00:10:46.380 Only 8 percent looked at the risk category. 00:10:46.380 --> 00:10:49.110 We also found that 50 percent indicated that nutrition 00:10:49.110 --> 00:10:52.590 dashboard assisted with identification of nutrition risk. 00:10:53.720 --> 00:10:56.040 50 percent did not find it to be a time 00:10:56.040 --> 00:10:59.520 consuming so time saving tool but I found 00:10:59.520 --> 00:11:01.690 it helpful for pictures from not picking 00:11:01.740 --> 00:11:04.230 the crown or the geriatric portions. 00:11:05.090 --> 00:11:08.380 Of 80 percent indicated that nutrition digital 00:11:08.610 --> 00:11:10.600 dashboard did not assist to prioritize 00:11:10.620 --> 00:11:13.830 debt and 75 per cent of the dietitians 00:11:13.830 --> 00:11:16.360 made incorrect interpretation of the meal. 00:11:16.400 --> 00:11:17.580 Indeed about. 00:11:20.970 --> 00:11:23.850 About 50 percent also did not refer to 00:11:23.850 --> 00:11:26.640 the reason he called Map and subsequently 00:11:26.700 --> 00:11:29.520 were unable to make an interpretation 00:11:29.520 --> 00:11:32.600 of the red amber and the green squares. 00:11:32.610 --> 00:11:36.660 There was some discussion that came out of this project and there 00:11:36.660 --> 00:11:40.530 were that milk consumption data quality is a complex issue. 00:11:40.530 --> 00:11:43.110 Energy and put in consumption on. 00:11:43.770 --> 00:11:47.280 Nutrition dashboard may be underestimated. High 00:11:47.280 --> 00:11:49.730 quality milk consumption data does not affect. 00:11:51.180 --> 00:11:52.510 Patient consumption. 00:11:52.530 --> 00:11:54.710 There may be some computer system around 00:11:55.170 --> 00:11:56.880 and it was difficult to decipher 00:11:56.880 --> 00:12:00.910 the reasons why a patient did not select a meal not provided with one. 00:12:02.280 --> 00:12:02.700 So. 00:12:03.030 --> 00:12:05.580 The recommendations that were made out of this project 00:12:05.640 --> 00:12:10.020 again was ongoing training for full service systems and. 00:12:11.520 --> 00:12:14.700 Communication of food consumption standards with patients. 00:12:16.290 --> 00:12:18.600 Integration of nutrition dashboard. 00:12:19.170 --> 00:12:20.750 Seaboard empowerment chart. 00:12:21.960 --> 00:12:25.110 For dietician assistance to be trained to include data 00:12:25.110 --> 00:12:28.980 collection to collect data on specific patients assigned 00:12:28.980 --> 00:12:34.290 by the dietitians maybe and some comprehensive education 00:12:34.380 --> 00:12:37.320 on all segments of nutrition dashboard for dietitian. 00:12:39.750 --> 00:12:42.030 And dietitian assistance. 00:12:42.060 --> 00:12:45.570 Again there were some limitations so not all the boards 00:12:45.570 --> 00:12:49.160 were included in this study due to the limited time frame. 00:12:49.770 --> 00:12:52.570 >> It was difficult to validate the results. 00:12:52.590 --> 00:12:55.050 It was also difficult to draw conclusions between 00:12:55.050 --> 00:12:59.010 rates of milk consumption data and specific boards. 00:13:00.230 --> 00:13:00.820 And. 00:13:03.090 --> 00:13:03.510 I've. 00:13:03.810 --> 00:13:04.410 >> With my time. 00:13:04.410 --> 00:13:07.350 So in conclusion the study results demonstrated some of 00:13:07.350 --> 00:13:10.710 the liability issues with the quality of data that was displayed. 00:13:12.450 --> 00:13:12.600 In. 00:13:14.400 --> 00:13:16.680 Training with particular focus on clinical practice 00:13:16.680 --> 00:13:19.980 and user visibility in large hospitals like Westmead. 00:13:20.670 --> 00:13:24.330 May put in shared some enhancement and improvement of patient outcomes. 00:13:24.930 --> 00:13:28.890 And I would like to say not blind our practices at 00:13:28.890 --> 00:13:33.200 Westmead should be considered as best practice. 00:13:34.300 --> 00:13:37.960 >> So our final presenter today will be tracing Patrick's who's a hero. 00:13:37.970 --> 00:13:39.490 He's a head dietician of Coffs Harbour 00:13:39.490 --> 00:13:41.740 Hospital in the mid north coast LH day. 00:13:48.400 --> 00:13:50.890 >> Already unfortunately was on leave today so we were very 00:13:50.890 --> 00:13:53.960 appreciate appreciative of her preparing the slides. 00:13:53.990 --> 00:13:56.800 We're also very grateful to Tracy for agreeing to step in. 00:13:56.930 --> 00:14:01.510 Today for us she's up tracing presenting on how the train might 00:14:01.620 --> 00:14:05.650 and dashboard data is used a small city with limited dietitian 00:14:05.710 --> 00:14:10.090 hours against a different perspective on how it's used to benefit 00:14:10.150 --> 00:14:14.220 clinical practice and we say Tracey for joining us to do so. 00:14:14.230 --> 00:14:16.540 >> The nutrition dashboard and tray monitor are 00:14:16.540 --> 00:14:19.420 used routinely at Maxwell district hospital to 00:14:19.420 --> 00:14:21.700 assist with the management of the dietetic 00:14:21.700 --> 00:14:24.550 caseload and in the nutrition care of patients. 00:14:25.450 --> 00:14:28.690 I'll give an overview of their use and potential 00:14:28.690 --> 00:14:32.290 benefits that other sites so Mexico is one of 00:14:32.290 --> 00:14:34.540 our smaller facilities in the cost clinical 00:14:34.540 --> 00:14:37.150 network of Mid North Coast Local Health District. 00:14:38.080 --> 00:14:42.160 It's a level 3 48 bed facility about 60 K 00:14:42.160 --> 00:14:46.720 south of coffee so about a 40 minute drive. 00:14:46.750 --> 00:14:48.910 Today having a look at Maxwell today 00:14:48.940 --> 00:14:52.510 there's 36 patients in Macksville today 00:14:52.550 --> 00:14:55.960 so about 75 per cent capacity and two thirds 00:14:55.960 --> 00:15:00.750 of those patients over 65 years of age. 00:15:00.760 --> 00:15:03.310 The patients there there are a few acute 00:15:03.370 --> 00:15:06.910 but mostly they're subacute patients mostly rehab 00:15:07.350 --> 00:15:11.860 and recovering from surgery or complicated 00:15:11.860 --> 00:15:15.410 extended hospital stay hearing costs or waiting. 00:15:15.410 --> 00:15:17.650 Residential aged care facility placement 00:15:19.450 --> 00:15:22.300 Brody commenced at Macksville in 00:15:22.300 --> 00:15:24.580 the beginning of 2016 with the brand new 00:15:24.580 --> 00:15:26.740 position so she's built it from the ground 00:15:26.740 --> 00:15:30.340 up and done an amazing job and as we've 00:15:30.340 --> 00:15:32.710 seen on the wall has a wonderful 00:15:32.770 --> 00:15:34.660 close relationship with food services 00:15:34.690 --> 00:15:37.330 and they work extremely well together. 00:15:37.390 --> 00:15:38.540 Next slide please. 00:15:42.670 --> 00:15:49.120 Okay so the first My Free Choice Program and nutrition dashboard use 00:15:49.120 --> 00:15:53.800 at Macksville Brody uses that in a number of ways for triaging 00:15:54.100 --> 00:15:59.650 MSP patients for screening patients not referred via MSF T for 00:15:59.650 --> 00:16:06.490 nutrition risk and for triaging conventionally placed referrals. 00:16:06.490 --> 00:16:12.370 So for the three out of M S T patients like most places due to 00:16:12.370 --> 00:16:17.200 limited dietician hours we need to try out our patients and many 00:16:17.200 --> 00:16:21.430 of the patients referrals at Macksville are automatically generated 00:16:21.430 --> 00:16:26.250 referrals from an MSA team completed by the nursing staff. 00:16:26.500 --> 00:16:28.660 So the nutrition dashboard is helpful 00:16:29.110 --> 00:16:31.130 for Brody to filter through those M.S. 00:16:31.150 --> 00:16:35.800 to refer patients to see what else may be going on. 00:16:35.800 --> 00:16:43.780 So having a look at today's list there are three three new referrals 00:16:44.360 --> 00:16:54.010 three M S T two patients and of those three to have an M S T. 00:16:54.210 --> 00:16:54.830 Oh sorry. 00:16:54.880 --> 00:16:59.460 There are three Category 1 patients and 6 Category 4 patients. 00:16:59.680 --> 00:17:02.780 Nothing in between and two of those in 00:17:02.950 --> 00:17:07.600 those Category 1 patients are don't have 00:17:07.600 --> 00:17:10.600 any m t completed and one of those 00:17:10.900 --> 00:17:14.080 Category 1 patients have an M S T of 2. 00:17:14.110 --> 00:17:19.150 So Brody would you the nutrition dashboard to have a look at those Ms t 00:17:19.210 --> 00:17:24.370 patients particularly the two and use that further nutrition dashboard 00:17:24.370 --> 00:17:31.480 data to treat those patients for the screening of nutrition risk for 00:17:31.480 --> 00:17:36.860 patients that don't have any Misty referral or any other referral. 00:17:37.000 --> 00:17:38.860 Again Brody can have a look at the nutrition 00:17:38.860 --> 00:17:44.650 dashboard and see which again the risk category 00:17:44.650 --> 00:17:49.030 1 and 2 patients and place a referral herself 00:17:49.450 --> 00:17:52.330 and see those patients as time permits. 00:17:53.980 --> 00:17:57.380 >> For conventionally placed referrals. 00:17:57.430 --> 00:18:01.750 Again Brody can use the risk categories to 00:18:01.750 --> 00:18:04.660 determine who are the higher priority patients 00:18:05.680 --> 00:18:07.600 and who might be a little more complex 00:18:08.740 --> 00:18:13.220 and make time and try out those patients as well. 00:18:13.270 --> 00:18:17.740 Another way that Brody uses the nutrition dashboard is 00:18:17.770 --> 00:18:25.420 to use the estimated energy and protein intake again to 00:18:25.630 --> 00:18:31.330 help him form her nutrition assessment along with all 00:18:31.330 --> 00:18:37.000 of the other data collected from a variety of sources. 00:18:37.560 --> 00:18:40.230 The other system that Brody uses is 00:18:40.230 --> 00:18:42.800 the train monitor a wall crime monitor 00:18:42.800 --> 00:18:46.920 is conventionally used by food service staff to manage workflow. 00:18:46.920 --> 00:18:48.390 It can be a really valuable source of 00:18:48.390 --> 00:18:50.740 information for the dietitian as well. 00:18:51.800 --> 00:18:55.470 So there's two applications in train monitor that proteins will use at 00:18:55.470 --> 00:19:02.340 Macksville and that includes the mobile intake data and export control. 00:19:02.340 --> 00:19:03.030 >> The next slide. 00:19:12.150 --> 00:19:16.940 >> Yeah so you can see there with a monitor which we have a 00:19:16.940 --> 00:19:20.180 link to connect to which I'm sure everyone's familiar with. 00:19:20.930 --> 00:19:22.460 We can have a look at the reports 00:19:22.550 --> 00:19:28.400 and the mobile intake data so the mobile intake data. 00:19:28.400 --> 00:19:32.510 First up on the next slide is used to 00:19:32.600 --> 00:19:34.970 check me or Camille what patients are 00:19:35.090 --> 00:19:39.080 ordering to check if patients are consuming 00:19:39.530 --> 00:19:44.630 supplements or other nutritious food 00:19:44.630 --> 00:19:46.520 or drink items that the dietician might 00:19:46.520 --> 00:19:50.690 have implemented and to see which patients 00:19:50.690 --> 00:19:53.450 are declining meals or if meal choices are 00:19:53.450 --> 00:19:56.790 being made without the patient's input. 00:19:57.290 --> 00:20:00.170 So I find it useful to cross-check this 00:20:00.170 --> 00:20:03.680 data also with 24 hour recalls with 00:20:03.680 --> 00:20:07.040 patients particularly those who may be 00:20:07.040 --> 00:20:12.800 poor historians or a little confused. 00:20:12.800 --> 00:20:20.510 Also we use that here it costs to check on consumption meal by 00:20:20.510 --> 00:20:27.110 meal to make sure that items that the patient enjoys has been 00:20:27.110 --> 00:20:32.000 chosen and two to check that patients are consuming those 00:20:32.000 --> 00:20:37.240 items that we might have discussed and implemented with them. 00:20:37.250 --> 00:20:42.230 Another thing that we use to try and take data for was to do 00:20:42.230 --> 00:20:45.560 an intake data audit which students conducted for us last year 00:20:45.590 --> 00:20:51.920 so they gained access to the to their train take data and use 00:20:51.920 --> 00:20:57.230 that within their audit which I'll discuss in a little while. 00:20:57.890 --> 00:21:01.310 So they monitor reports are often run at Macksville to assess 00:21:01.310 --> 00:21:04.550 the intake of patients that have been admitted for less than three days. 00:21:04.550 --> 00:21:07.760 As we know the nutrition dashboard kicked in after 00:21:07.760 --> 00:21:11.120 patients have had data collected for three days. 00:21:11.630 --> 00:21:16.520 So for both patients who are in the first three days 00:21:16.520 --> 00:21:19.610 of their admission and the majority of patients 00:21:20.000 --> 00:21:22.340 at Macksville are in for greater than three days 00:21:22.370 --> 00:21:25.880 they have an average length of stay of 13 days. 00:21:26.300 --> 00:21:30.910 So because BART is only there two days a week. 00:21:31.400 --> 00:21:32.930 Often you know she'll be referred 00:21:32.930 --> 00:21:34.840 patients within those first three days. 00:21:34.850 --> 00:21:39.110 So the thing the train modelling data is really useful 00:21:39.950 --> 00:21:42.720 until the nutrition dashboard information kicks in. 00:21:44.090 --> 00:21:49.100 So those reports are really useful to evaluate not just in a GM protein 00:21:49.880 --> 00:21:54.500 but to also look at any other nutrients that you might want to consider 00:21:54.830 --> 00:21:59.260 for patients whether that be carbohydrate distribution or fiber intake 00:21:59.270 --> 00:22:07.030 fluid exchanges or any of the electrolytes or vitamin intake as well. 00:22:07.200 --> 00:22:07.820 >> Next slide. 00:22:07.820 --> 00:22:08.340 Thanks. 00:22:10.460 --> 00:22:15.350 >> So we very interested as well to have a look at thin accuracy 00:22:15.350 --> 00:22:18.890 and the reliability of the data within 00:22:19.680 --> 00:22:21.950 tray monitor and the nutrition dashboard. 00:22:22.880 --> 00:22:28.370 So last year we asked our food service students from Newcastle uni 00:22:28.430 --> 00:22:34.320 to do an audit for us and have a look at the accuracy of the data. 00:22:34.660 --> 00:22:36.560 The guys have my fair choice. 00:22:36.560 --> 00:22:42.980 Of course Brad was hesitant to rely too much on the data as we were 00:22:42.980 --> 00:22:49.490 unsure of the accuracy being in the early days of my food choice. 00:22:49.700 --> 00:22:52.910 So we were really keen to get a bit of a 00:22:52.910 --> 00:22:57.300 reflection of how accurate that data is. 00:22:57.380 --> 00:23:01.250 So that said last year students from Newcastle uni conducted 00:23:02.180 --> 00:23:10.240 an intake data audit for us and Macksville got the gold star. 00:23:10.340 --> 00:23:14.560 They were rated at 80 per cent 86 per cent reliability. 00:23:15.050 --> 00:23:18.380 So above the 80 per cent benchmark set 00:23:18.380 --> 00:23:25.340 by health share the overall reliability 00:23:25.370 --> 00:23:30.950 of the data for cost clinical network was 81 per cent but I think Matt 00:23:31.040 --> 00:23:32.720 Max feels good data pushed this up a 00:23:32.720 --> 00:23:36.020 little bit because costs was overall 00:23:36.020 --> 00:23:39.940 seventy seven per cent Burlington or so a very commendable 80 per cent. 00:23:40.700 --> 00:23:46.880 And as I said gold star to Macksville 86 per cent so that improved. 00:23:46.880 --> 00:23:52.200 Di dietician confidence in in the data. 00:23:52.430 --> 00:23:54.620 But of course you know it's it's part of 00:23:55.010 --> 00:23:59.540 a lot of different data that we use for 00:23:59.960 --> 00:24:02.480 assessment and monitoring and evaluation 00:24:02.570 --> 00:24:06.270 not just ourselves source of data. 00:24:06.530 --> 00:24:09.750 So how was that good result achieved. 00:24:09.860 --> 00:24:12.700 As I said borrowed the dietician down 00:24:12.700 --> 00:24:15.160 at Macksville since then instigation 00:24:15.160 --> 00:24:20.170 of the position in the beginning in 2016 and has a great relationship 00:24:20.170 --> 00:24:25.690 with food services down there and she conducts regular in services 00:24:25.810 --> 00:24:33.700 and consults you know weekly where food services staff she made 00:24:33.700 --> 00:24:38.680 sure that that the that the good results of this particular audit were 00:24:38.680 --> 00:24:44.350 relayed back to food service staff and so food services staff you 00:24:44.350 --> 00:24:48.670 know they know the importance of being accurate with this data and they 00:24:48.670 --> 00:24:53.460 understand that they're also an integral part of great patient care. 00:24:53.460 --> 00:24:54.280 Dan Maxfield. 00:24:55.090 --> 00:24:57.760 >> Great nutrition care and having that 00:24:59.590 --> 00:25:01.720 understanding of the importance of the role 00:25:01.720 --> 00:25:07.780 that they play and that they have a very 00:25:07.780 --> 00:25:09.960 important part to play in nutrition care 00:25:10.030 --> 00:25:13.660 >> I think he has continued not only the great relationship 00:25:13.680 --> 00:25:20.280 road has vested services but the reliability of that data. 00:25:20.290 --> 00:25:21.040 Next slide please. 00:25:25.650 --> 00:25:29.520 So yeah we see hospital wide benefits of 00:25:30.340 --> 00:25:38.540 the tray monitor and nutrition dashboard data. 00:25:38.670 --> 00:25:45.250 It allows folks limited time to be efficiently used in the third to 00:25:45.560 --> 00:25:51.690 to trash priority patients by having a look and cross checking with 00:25:51.690 --> 00:25:56.160 the key referrals the regular referrals and those patients are not 00:25:56.160 --> 00:26:00.690 referred at all by cross checking with nutrition dashboard data. 00:26:00.990 --> 00:26:03.900 We can zero in on those patients in most 00:26:03.900 --> 00:26:06.240 need within a limited time and limited 00:26:06.240 --> 00:26:13.360 FTE it assists with estimating oral intake of the patients and gives a 00:26:13.680 --> 00:26:16.680 quantitative methods that perhaps we haven't 00:26:16.680 --> 00:26:20.160 had the intensity of that information 00:26:20.190 --> 00:26:23.370 before and it decreases their reliance 00:26:23.370 --> 00:26:26.040 on nursing staff to complete C chart. 00:26:26.790 --> 00:26:30.750 There's a pretty high nurse to patient ratio down at Macksville 00:26:30.780 --> 00:26:35.730 so anything that we can do to assist in alleviating 00:26:36.300 --> 00:26:40.620 their workload demand to also help to improve working 00:26:40.620 --> 00:26:44.910 relationships between dietetics and nursing staff. 00:26:45.090 --> 00:26:47.480 So lastly I think. 00:26:49.320 --> 00:26:52.030 It's ongoing. 00:26:52.290 --> 00:26:54.990 Party continues to work very closely both with food 00:26:54.990 --> 00:26:59.460 services staff and ward staff and ensure that 00:26:59.820 --> 00:27:03.720 the kitchen staff are empowered and feel that they 00:27:03.720 --> 00:27:08.820 have an important role in the care of patients. 00:27:09.360 --> 00:27:14.340 And we would like to properly implement annual audits to 00:27:14.340 --> 00:27:19.050 ensure that the accuracy of the data remains as high 00:27:19.080 --> 00:27:23.280 and perhaps to set a benchmark for the rest of 00:27:23.280 --> 00:27:28.100 the cost clinical network to run to meet Maxfield results. 00:27:28.110 --> 00:27:30.570 So putting a bit of a challenge out there between 00:27:30.570 --> 00:27:35.920 our facility and even if the data isn't accurate. 00:27:36.300 --> 00:27:39.120 What we can consider is is using train monitor 00:27:39.180 --> 00:27:41.750 to check what the patients are ordering. 00:27:42.340 --> 00:27:44.400 If nothing else to better inform our 00:27:44.400 --> 00:27:48.510 nutrition assessments and to also use 00:27:48.510 --> 00:27:55.530 the nutrition dashboard to flag those patients who are on the ordering. 00:27:55.550 --> 00:27:56.550 That's it for me. 00:27:57.750 --> 00:27:58.290 >> Thank you. 00:27:58.950 --> 00:27:59.960 Thank you Tracy. 00:27:59.970 --> 00:28:02.420 Appreciate that. 00:28:02.420 --> 00:28:05.260 >> Please say thank you to all that for this. 00:28:05.270 --> 00:28:06.750 Well that's the end of our presentation 00:28:06.750 --> 00:28:09.390 session today and I'm sure you'll agree 00:28:09.390 --> 00:28:11.160 that there was lots of different 00:28:11.160 --> 00:28:15.900 perspectives provided and I think that demonstrates that the data from 00:28:15.900 --> 00:28:18.450 the dashboard and from tray monitor is just 00:28:18.450 --> 00:28:20.530 not one solution as to how you can use it. 00:28:20.550 --> 00:28:24.120 >> You can customize it to your own facility. You 00:28:24.120 --> 00:28:26.760 can make it fit your workflow as you think 00:28:26.880 --> 00:28:28.890 is most appropriate and most practical 00:28:29.400 --> 00:28:32.460 and sometimes implementation is quite challenging. 00:28:32.460 --> 00:28:34.230 So there's some hurdles you need to get over 00:28:34.920 --> 00:28:37.740 but I think it's also really reassuring 00:28:37.740 --> 00:28:40.380 that we've got lots of departments in 00:28:40.380 --> 00:28:42.930 the state now who have who are utilizing it. 00:28:42.930 --> 00:28:46.270 You've had experience and I'm sure would always be very well. 00:28:46.310 --> 00:28:50.790 >> JJ any tips or tricks or advice or or you would just 00:28:50.790 --> 00:28:54.000 be a shoulder to cry on if you need it so reach out 00:28:54.000 --> 00:28:55.950 and talk to your colleagues especially our presenters 00:28:55.950 --> 00:28:58.130 today I'm sure that I'll be happy to contact you. 00:28:58.890 --> 00:29:02.180 >> So after some pressure we still got 10 minutes left. 00:29:02.190 --> 00:29:04.320 I've received a couple of questions through 00:29:04.320 --> 00:29:06.390 slideshow and email which I can lead with. 00:29:06.390 --> 00:29:08.290 So if you've got any questions I'd like to share. 00:29:08.310 --> 00:29:11.130 By the way I can I can raise that. 00:29:11.130 --> 00:29:13.440 So the first question I received by e-mail. 00:29:14.880 --> 00:29:15.630 Was. 00:29:18.290 --> 00:29:19.110 From Caitlin. 00:29:19.620 --> 00:29:24.660 So a question if no one else is us is there any concerns regarding 00:29:24.660 --> 00:29:28.440 the quality of the per cent consumed data being entered. 00:29:29.110 --> 00:29:32.780 If there have been concerns that this may not be accurate estimates. 00:29:32.790 --> 00:29:35.010 Have you had any strategies to manage this. 00:29:35.430 --> 00:29:37.680 And I feel that this is a large barrier 00:29:37.680 --> 00:29:39.870 to using the dashboard so I might 00:29:39.930 --> 00:29:43.350 open that up to one of our presenters to contribute to that response. 00:29:43.350 --> 00:29:44.880 If you have something to say. 00:29:48.870 --> 00:29:51.530 I guess with us that's something that we want to work with. 00:29:52.840 --> 00:29:53.090 So. 00:29:53.510 --> 00:29:58.650 That we sort of continue doing ongoing training and ongoing. 00:29:59.570 --> 00:30:02.060 >> Compliance checks because there is a lot of 00:30:02.060 --> 00:30:05.380 interpretation when you actually go to pick up the food. 00:30:05.540 --> 00:30:07.850 It's all well and good when it's in the prepackaged meals 00:30:07.850 --> 00:30:11.580 and all the protein and the veggies and everything all set up. 00:30:11.870 --> 00:30:14.060 But once you actually go to collect the meals 00:30:14.060 --> 00:30:17.090 and all the food is sort of mashed up together it's 00:30:17.090 --> 00:30:19.970 hard to sort of determine which portion of 00:30:19.970 --> 00:30:22.620 the veg which portion of the protein has been eaten. 00:30:22.640 --> 00:30:25.250 So there's a lot up to interpretation 00:30:25.970 --> 00:30:28.900 and that's why we kind of take the dashboard 00:30:28.900 --> 00:30:30.890 as face value and then go into our own 00:30:30.890 --> 00:30:33.290 investigation to find out whether that is. 00:30:34.130 --> 00:30:35.090 Accurate or not. 00:30:37.150 --> 00:30:38.860 Any other presenters like to add to that. 00:30:41.130 --> 00:30:41.670 I think. 00:30:41.790 --> 00:30:43.050 >> Like to do it. 00:30:43.080 --> 00:30:44.760 It's definitely a concern and it's something 00:30:44.760 --> 00:30:46.950 that we're looking into investigating 00:30:47.130 --> 00:30:49.960 as a project because I wouldn't think 00:30:49.970 --> 00:30:51.680 it is a lot of work that can be done. 00:30:51.720 --> 00:30:52.870 So nothing that we've done yet. 00:30:52.890 --> 00:30:53.130 But. 00:30:53.460 --> 00:30:54.820 We have our eyes on it. 00:30:56.750 --> 00:30:59.010 >> So if I could just reflect on the presentation 00:30:59.010 --> 00:31:00.770 from Tracey it sounds like Brody's done 00:31:00.770 --> 00:31:03.320 a lot of work in that space to try to 00:31:03.320 --> 00:31:05.540 assure the quality of the data is accurate. 00:31:05.780 --> 00:31:08.690 And I know that he'll share in-house training programs 00:31:08.690 --> 00:31:11.720 for their staff to do that but also keep in mind. 00:31:12.050 --> 00:31:15.280 What did nursing staff do before when they recorded a food chart. 00:31:15.290 --> 00:31:18.810 They've been having different challenges or the same challenges. 00:31:18.830 --> 00:31:21.110 So I think it's great that we've. 00:31:21.710 --> 00:31:23.780 >> This process in place and yes it could be 00:31:23.780 --> 00:31:26.560 improvement strategies that going forward. 00:31:26.590 --> 00:31:26.910 But. 00:31:27.600 --> 00:31:27.960 Great. 00:31:28.070 --> 00:31:29.520 Thank you. 00:31:29.640 --> 00:31:31.320 The next question we have is that if. 00:31:31.860 --> 00:31:32.010 We're. 00:31:32.250 --> 00:31:34.010 Providing a supplement to the patient 00:31:34.190 --> 00:31:36.650 and they move out of categories Category 1 00:31:37.190 --> 00:31:38.810 is there any evidence to show that 00:31:38.810 --> 00:31:41.480 consuming more and not just ordering more. 00:31:42.890 --> 00:31:43.210 >> Yes. 00:31:43.220 --> 00:31:46.570 So on the dashboard at the bottom this some options. 00:31:46.580 --> 00:31:48.800 And one of them is intake analysis. 00:31:48.890 --> 00:31:50.500 So when you open that up on. 00:31:50.650 --> 00:31:50.850 My. 00:31:51.570 --> 00:31:51.980 Side. 00:31:54.920 --> 00:31:55.050 I. 00:31:55.220 --> 00:32:01.150 Just pull the sign up so I can talk you. 00:32:07.550 --> 00:32:08.090 Kept. 00:32:08.500 --> 00:32:08.730 Coming. 00:32:09.780 --> 00:32:11.310 Up. 00:32:12.900 --> 00:32:13.240 Well. 00:32:13.750 --> 00:32:14.590 Yeah. 00:32:15.140 --> 00:32:17.430 So looking at that side there. 00:32:17.630 --> 00:32:18.470 So that's the. 00:32:19.070 --> 00:32:24.040 Protein and energy contribution the red part of the bars is the. 00:32:24.500 --> 00:32:26.420 Contribution from the supplement. 00:32:26.420 --> 00:32:29.270 So if you open up the patient's file you can actually 00:32:29.270 --> 00:32:31.560 see how much of the supplement they are consuming. 00:32:31.970 --> 00:32:35.540 So for that particular example that I had the day I did 00:32:35.570 --> 00:32:40.220 offer the sausage and it did provide more nutrition which. 00:32:41.630 --> 00:32:42.050 Had. 00:32:42.470 --> 00:32:45.230 Allowed the patient to move out a Category 1 but what had actually 00:32:45.560 --> 00:32:49.040 happened is they were then Category 2 because they weren't 00:32:49.040 --> 00:32:52.670 actually eating enough of energy and protein but these other 00:32:52.880 --> 00:32:56.720 processes in place like embassy screening and the dieticians using. 00:32:57.860 --> 00:33:00.800 The dashboard for what screening was also being present 00:33:00.800 --> 00:33:04.610 in empty ts in hope that they will pick up a patient 00:33:04.610 --> 00:33:07.600 like this to do further intervention and investigation 00:33:07.700 --> 00:33:11.170 but yet generally can investigate how much they drink. 00:33:11.290 --> 00:33:11.530 So. 00:33:13.020 --> 00:33:14.710 >> Thanks. 00:33:14.950 --> 00:33:17.220 We have a comment from Shannon Singh from he'll share 00:33:17.630 --> 00:33:19.930 that it was interesting learnings from all sides. 00:33:19.930 --> 00:33:23.000 And thanks so much for sharing everyone. 00:33:23.100 --> 00:33:25.880 It's great to see that the dashboard is being used. 00:33:26.340 --> 00:33:26.850 I agree. 00:33:26.850 --> 00:33:28.110 That is good news. 00:33:28.110 --> 00:33:30.690 >> I haven't received any other question. 00:33:31.120 --> 00:33:33.510 A question I want to throw out there. 00:33:40.920 --> 00:33:44.370 >> Making it easy or easier or better 00:33:44.400 --> 00:33:54.650 or enhancing your bill be a clinician. 00:33:55.520 --> 00:33:59.630 >> I think it's definitely enhanced our workflows. 00:33:59.630 --> 00:34:03.020 I think previously you know if we wanted 00:34:03.020 --> 00:34:05.570 some detailed information around patient 00:34:06.020 --> 00:34:08.690 consumption you would have to implement some 00:34:08.690 --> 00:34:13.620 food chart for the nursing staff to to do. 00:34:14.090 --> 00:34:21.440 And I was always a fan of using the escapes 00:34:21.440 --> 00:34:23.390 me in Cebu and you could turn on. 00:34:25.760 --> 00:34:25.920 A. 00:34:27.170 --> 00:34:28.220 Calorie count that's it. 00:34:28.280 --> 00:34:28.570 Sorry. 00:34:28.610 --> 00:34:29.090 Thank you. 00:34:30.700 --> 00:34:32.900 But then you would need to bring the food cart 00:34:32.900 --> 00:34:37.070 back from the board and input the percentages. 00:34:37.400 --> 00:34:41.120 And you could print some reports out doing that if you wanted to 00:34:41.120 --> 00:34:46.070 get you know I think called report around patient consumption. 00:34:46.070 --> 00:34:49.010 But again you know you were relying on nursing 00:34:49.010 --> 00:34:51.230 staff to be accurate and we all know that 00:34:51.230 --> 00:34:54.590 the food the food charts by nursing staff were 00:34:54.590 --> 00:34:58.010 rarely completed the way we would like them to. 00:34:58.010 --> 00:35:02.720 So I think it's just really handy to be able to have access to that 00:35:02.720 --> 00:35:07.230 data through either train monitor or the nutrition dashboard. 00:35:07.400 --> 00:35:12.800 And I guess it's helped workflows and workload from that 00:35:12.800 --> 00:35:16.190 perspective for both nursing staff not having to keep 00:35:16.240 --> 00:35:20.780 the the food carts and the dietician not having to come back 00:35:20.780 --> 00:35:25.280 and put those those percentages into the calorie counts. 00:35:25.640 --> 00:35:27.920 So that's a bit of an advantage I see. 00:35:28.460 --> 00:35:30.560 So malamute with me I would say that it 00:35:30.560 --> 00:35:33.380 doesn't help all of them but as I said. 00:35:34.430 --> 00:35:35.750 Some dieticians to. 00:35:39.570 --> 00:35:41.480 >> Jewish patients. 00:35:42.090 --> 00:35:43.620 So someone just. 00:35:45.440 --> 00:35:49.970 >> Thinks that to me I as a clinician I have found it very valuable 00:35:49.970 --> 00:35:52.400 and useful because you can use trained 00:35:52.400 --> 00:35:54.130 well I tend to get that intake data 00:35:54.170 --> 00:35:56.320 but myself I'm quite a visual person 00:35:56.330 --> 00:35:59.960 so I like the the graphs and the picture 00:36:00.080 --> 00:36:02.300 tutorial patients with the intake to 00:36:02.300 --> 00:36:03.650 investigate the trainings of what's 00:36:03.650 --> 00:36:09.020 happening and I think workflow wise maybe it hasn't completely helped 00:36:09.020 --> 00:36:13.580 me because it does take more time talking but like I'm quite enjoying 00:36:13.580 --> 00:36:15.590 investigating the point of what's happening 00:36:15.590 --> 00:36:16.940 and trying to understand what's 00:36:16.940 --> 00:36:18.570 happening with this admission and just 00:36:18.580 --> 00:36:20.420 do a more comprehensive assessment. 00:36:22.940 --> 00:36:23.500 >> Thank you. 00:36:23.660 --> 00:36:26.930 I think just from my past experience and using it 00:36:27.350 --> 00:36:29.930 it's not providing you all the information that's 00:36:29.960 --> 00:36:31.910 providing a part of the puzzle to start a 00:36:31.910 --> 00:36:34.760 conversation to look maybe in a different direction. 00:36:34.940 --> 00:36:35.850 And I think anything you. 00:36:36.170 --> 00:36:38.510 Add to that making the assessment more 00:36:38.510 --> 00:36:41.310 comprehensive I think is valuable. 00:36:41.660 --> 00:36:45.290 Just up on the screen now is the contact details 00:36:45.290 --> 00:36:48.170 of the position so we're coming up to the time. 00:36:48.500 --> 00:36:51.930 So I really like to thank again every presenters for their talk. 00:36:51.970 --> 00:36:55.390 If it is apparent today I'd also like to thank all of 00:36:55.400 --> 00:36:58.440 these innovations or practices that you'd like to share. 00:36:58.460 --> 00:37:01.400 Please be in touch with me and we can work out a way of disseminating 00:37:01.400 --> 00:37:04.370 it through the network because I think there's lots of gold 00:37:04.490 --> 00:37:08.330 everywhere out there and what you would do it might really help some 00:37:08.330 --> 00:37:12.380 colleagues improve a process or do something better somewhere else. 00:37:12.380 --> 00:37:14.150 So thank you to everybody.