Analysing Hospital Episode Statistics (HES)

Transcription

1 Analysing Hospital Episode Statistics (HES) Practical Session 3 - Looking at several diagnoses for each age - Merging data files and creating calculated fields Available to download from: Thursday, 30 August 2007 Written by: Robin Beaumont robin@organplayers.co.uk Status: V1.0 Contents 1. COMPARING DIFFERENT DIAGNOSES FOR EACH AGE - MERGING DATA FILES SPECIFYING THE DATA SET REQUIRED CREATING A DATA FILE CONTAINING ALL EPISODES FOR EACH AGE CREATING A DATA FILE CONTAINING ALL EPISODES FOR EACH AGE FOR EACH DIAGNOSIS MERGING DATA FILES TOGETHER REVIEW ANALYSING THE AGE SPECIFIC FREQUENCY OF DIAGNOSES CREATING A CALCULATED VARIABLE INVESTIGATING THE PROPORTIONS OF EPISODES FOR A PARTICULAR DIAGNOSIS VIEWING SEVERAL DIAGNOSES AT ONCE OPTIONAL EXERCISE APPENDIX...16

2 1. Comparing different diagnoses for each age - Merging data files In the previous sessions we investigated the incidence of diagnoses for particular ages. In this session we will take the investigation of diagnoses one stage further and consider the relative proportion of episodes for several diagnoses simultaneously for each age. The final exercise in this session will provide you with the skills to produce charts similar to the one below which shows the proportion of cases for two different conditions for each age..3 Proportion of episodes for age localised primary osteoarthritis intracranial injury nos no open intracranial wound Age at start of admission The above chart clearly shows the relationship between osteoarthritis and one type of head injury for each age. Also each diagnosis is shown as a percentage (proportion) of cases for each age. What conclusions can you draw from the above chart? Such information can be used to help guide the clinician to a possible diagnosis. Additionally by taking into account other factors a decision support system can be developed. We can use data like this to guide descions regarding the proably diagnosis given certain signs / symptoms and medical history etc. To produce the above chart from the tando1 data file we will need to manipulate the data. This involves producing several SPSS data files ('*.sav' files) and then merging them together to produce the necessary data file. There are several stages and we will work through each one carefully and this hopefully will stop getting lost on the way. C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 2

3 1.1 Specifying the data set required Analysing HES data session three I created the above chart by using the menu option Charts -> line -> multiple, values for individual cases. The dialogue boxes are reproduced below. Seeing what we need to end up with in terms of fields helps plan our data manipulation strategy.. To help further I have also included an extract from the final dataset as well. This will mean little to you at the moment. What you should notice is hat onely two of the above fields are within the tando.sav dataset so you can guess that it will take quite a bit of work to transform our current tando1.sav dataset into the one above. therefore have quite a lot of work to do to get the dataset in the required. We will begin by creating the first and fourth columns in the above diagram, that is obtain the total number of episodes for each age. C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 3

4 1.2 Creating a data file containing all episodes for each age We will begin by producing a file which contains the total number of episodes for each age. We will save this file on floppy disk and call it 'totfage.sav' being short in my mind for 'totals for ages'. We do this by what SPSS calls, aggregating the original data file (Tando1.sav). The exercise below explains how to do this. Aim to create a data file which has the total number of episodes for each age. 1 Make sure you have the 'tando1.sav' dataset open 2 Make sure you have the data window selected (to move to the correct window choose the menu option 'Window' and select the appropriate window). 3 Select the menu option Data -> Aggregate to aggregate the file. You should now be presented with the dialogue box shown opposite 4 Move the 'startage' variable into the 'Break Variables' box. This instructs SPSS to create a new case (record) in the new datafile for each unique age 5 Make sure the 'Number of cases' is chosen 6 Type on the box 'totage' This is my shorthand for 'total no. of records for each age' 7 Select the 'Write a new data file containing only the aggregated variables option 8 Click on the 'File' BUTTON. This will bring up the second dialogue box shown above: 10 Move to a sensible folder to store the file, in the 'File name' box type in 'totfage'. Don't type the quotes 11 Click the 'save' button to return you to the previous, Aggregate data, dialogue box 12 Click the OK button on the 'aggregate data' dialogue box to run the aggregation process. You now need to inspect to results of your work, that is open the new data file you have just created. 1 Choose the menu option file -> open -> data 2 Move to the folder you sorted the file in. 3 Select the 'totfage' data file you have just created. 4 If you are prompted to change any results choose 'No'. You should now be presented with a data window similar to the one opposite. For each start age ('startage' variable) the total number of records in the original file is given in the 'totage' variable. Comparing this data file structure with that which is eventually required we see that we have the first and third columns now. C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 4

5 1.3 Creating a data file containing all episodes for each age for each diagnosis dialogue box to run the aggregation process. diagnosis. 1 Open the Tando1 data file (Menu option file -> open ->Data) We will now create a data file which contains the total number of episodes for each age for each diagnosis. The resulting file, we will call 'totagedn.sav' being short in my mind for 'totals for each age for each diagnosis'. Aim to create a data file which has the total number of episodes for each age for each 2 Select the menu option Data -> Aggregate to aggregate the file 3 Move the 'startage' variable into the 'Break Variables' box. This instructs SPSS to create a new case (record) in the new datafile for each unique age 4 Move the 'diag_1' variable into the 'Break Variables' box. This instructs SPSS to create a new case (record) in the new datafile for each unique diagnosis as well 5 Make sure the Number of cases' is chosen 6 Type on the box 'totagedi' This is my shorthand for 'total no. of records for each age and diagnosis' 7 Select the 'Write a new data file containing only the aggregated variables option 8 Click on the 'File' BUTTON This will bring up the second dialogue box shown above: 10 Move to a sensible folder to store the file, in the 'File name' box type in ' totfdiagn'. Don't type the quotes 11 Click the 'save' button to return you to the previous, Aggregate data, dialogue box 12 Click the OK button on the 'aggregate data' As before when you created an aggregated data file you now need to inspect to results of your work. This is described in the exercise below: 1 Open the 'totfdiagn' data file you have just created (menu option file -> open ). If you are prompted to change any results first choose 'No'. You should then be presented with a data window which shows for each start age ('startage' variable) and each diagnosis the total number of records in the original file in the 'totagedi' variable. 1.4 Merging data files together C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 5

6 We now have three data files: tando1 totfage totfdiagn The original data file A data file containing the number of episodes for each age Analysing HES data session three A data file containing the number of episodes for each diagnosis for each age We will now merge the totfage and totfdiagn data files to get one step closer to the data we require. We do this by what SPSS calls merging the variables from each of the files. 1 Make sure the 'totfdiagn' data file is open if it is not open it now. 2 Choose the menu option Data -> Merge files -> add variables. (Note: don't choose the add cases option). You will then be presented with the dialogue box shown below. 3 Select the option An external SPSS data file and then click on the Browse button 4 Move to the correct folder and then choose the 'totfage' data file be clicking on it to make it highlighted. The name should now appear in the 'file name' box as shown opposite. 5 Click on the continue (may be OK ) button. You will now be presented with the 'Add variables' dialogue box shown below. 6 Select the 'startage' variable in the excluded variables box. It will become highlighted. 7 Click on the box beside 'Match cases on key variables in sorted files'. A tick sign should appear in it. 8 Click on the second option non active dataset is keyed table'. The button should then be grayed (i.e. selected). 9 Move the 'startage' variable into the 'Key variables' box by clicking on the button with the arrow sign on it beside the box. The dialogue box should now look like the one opposite. 10 Click on the OK button C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 6

7 12 The following dialogue box will appear. Because of the way we created the two files we know they are sorted on the relevant field. Therefore click the OK button. 13 IMPORTANT. You must now save the file under a different name. Previous versions of SPSS created a new merged file the current version added the new filed to the current open dataset. We therefore need to save this new dataset immediately with a new name. Select the menu option File -> Save As... Move, if necessary to a suitable folder, and give the new dataset the name diagage, which to me means diagnosis for each age The new dataset looks like this We now have four of the five variables specified in section 1.1 above. After getting this far making sure we have saved all three aggregated datasets is the first priority. Check that you have saved all the datasets. 2. Review At this point we will review what we have done so far in the form of a diagram: Aggregate original file TANDO1.SAV Totals for each age TOTFAGE.SAV Totals for each diagnosis for each age TOTFDIAGN.SAV Combined files DIAGAGE.SAV Although we have only merged two files you can merge large numbers of files together. For example you may have demographic details of subjects in one dataset and several separate datasets for each trial they may have participated in. I would suggest that you now take a break you deserve it! C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 7

8 The following assumes that you have the daigage.sav SPSS datafile open, if you don t open it now 2.1 Analysing the age specific frequency of diagnoses We will begin by looking at the relative frequency of one of the most common diseases in our dataset (see section 3 of the previous handout): 7151 Localised primary osteoarthritis We do this by setting up a filter for diag_1 = "7151-" 1 Choose the menu option Data -> select cases This brings up the 'Select cases' dialogue box 2 Click on the 'If condition is satisfied' option 3 Click on the 'If...' button to bring up the 'Select cases: if' dialogue box show below 4 Type into the box at the top right: diag_1 = "7151-" 5 Click the continue button 6 Click the OK button on the 'Select cases' dialogue box. We will now check our results by drawing a chart, this is the following exercise. 1 Choose the menu option Charts -> line 2 Select the Muliple option 3 Select the 'Values of individual cases' option 4 Click the 'define' button to bring up the next dialogue box 5 Move the 'Totage' variable into the 'Lines Represent' box 6 Move the 'Totagedi' variable into the 'Lines Represent' box 7 Select the 'Categories Labels - variable' by clicking on the option 8 Move the 'Startage' variable into the 'Variable' box 9 Click the OK button to obtain the graph. You should end up with a result similar to that shown below. C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 8

9 Unfortunately the x axis in the above chart is misleading, the x axis being unevenly spaced; to obtain a chart with a more sensible x axis we can use the scatter plot option: 1 Choose the menu option Graphs -> Scatter 2 Choose the 'overlay' option 3 Select the totage variable (it becomes highlighted) 4 Select the startage variable (both variables are now highlighted) 5 Click on the button with the arrow to move them both into the 'Y - X pair' box. You may need to click the Swap pair button so that you end up with totage startage 6 Select the totagedi variable (it becomes highlighted) 7 Select the select the startage variable (both variables are now highlighted) 8 Click on the button with the arrow to move them into the 'Y - X pair' box. Again you may need to click the Swap pair button to end up with totagedi startage The dialogue box should now look like the one below. 9 Click on the OK button to produce the chart shown below. You can now bring up the chart Editer by double clicking on the chart and edit it to produce the desired effect, what you need to do is insert lines between each of the values, called interpolation lines in SPSS. You need to do this for both the sets of points TOTAGEDI STARTAGE TOTAGE STARTAGE Total number for all diagnoses While the chart is useful for seeing the number of episodes for a particular diagnosis and how this roughly relates to the total for each age it would be nice to see the exact proportional value. To be able to do this we need to create a new variable described next. Number for selected diagnosis i.e C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 9

10 2.2 Creating a calculated variable Analysing HES data session three Age What we need to do now is add another variable to the data file representing the proportion of episodes for a particular diagnosis for a particular age. The data file will then be identical to that specified in section 1.1 above. 1 Make sure you have the diagage data file open. If not open it now. 2 Choose the menu option Transform -> compute The dialogue box is shown below. 3 Type in the 'Target Variable' box 'proption'. This stands for proportion in my mind. Don't type the quotes. 4 Type the following into the 'Numeric Expression' box: totagedi / totage These informs SPSS to compute a new variable from the 'totagedi' and 'totage' variables called 'proption'. The new variable takes the value of the 'totagedi' variable for each case divided by the corresponding 'totage' value. 5 Click on the OK button After a few seconds the new variable appears in the data editor window. We now have a data file containing the data in the correct format as specified in section 1.1 With this new variable we can obtain exact values for the proportions of episodes a particular diagnosis accounts for, for any age. This is demonstrated in the next section. Explain the meaning of the new 'proption' variable. C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 10

11 2.3 Investigating the proportions of episodes for a particular diagnosis We will do this by creating several charts. 1 Choose the menu option graphs -> line 2 The 'simple' option should be chosen be default 3 Select the 'Values of individual cases' option 4 Click the 'Define' button to bring up the next dialogue box 5 Move the 'Poption' variable into the 'Line Represents' box 6 Select the 'Categories Labels - variable' by clicking on the option 4 Move the 'Startage' variable into the 'Variable' box 5 Click the OK button to produce the chart shown below. From the graph opposite we can clearly see the peak around the 70 year age where episodes for Localised Primary Osteoarthritis account for nearly a third of all admissions. Optional exercise: Repeat the above exercise using the 'scatter' graph option to produce an appropriately spaced x axis..3.2 Value PROPTION While the above information is of some use it would be nice to compare several diagnoses at once, and this is our next, and final task. STARTAGE C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 11

12 2.4 Viewing several diagnoses at once. Analysing HES data session three This can be done several ways. The way described below has been chosen to demonstrate the use of the 'If' option in SPSS. This allows you to place a set of values for a particular diagnosis in a separate variable. We will compare the proportion of episodes for Ostearthritis (7151) against those for Intracranial injury (8540) for each age. Draw very roughly what you would expect to see on the chart. 1 Remove any filter you have on the data file by choosing the menu option Choose the menu option Data -> Select cases Click on the 'Select all cases' option then Click the OK button. 2 Select the menu option Transform -> Compute 3 Type the new variable name 'd8540' in the 'Target Variable' box This new variable is going to contain only values for those episodes which have a diagnosis of Type or, select and move, the 'proption' variable into the 'Numeric Expression' box 5 Click on the 'if' button lower down in the dialogue box. This will allow you to specify that only those episodes which have a diagnosis of 8540 will be copied into the new variable. 6 The 'Compute Variable: if Cases' dialogue box now appears, as shown below 7 Select the 'Include if cases satisfy condition' option. 8 Type the following into the text box: diag_1 = "8540-" 9 Click the 'continue' button. 10 Click the 'OK' button in the 'compute variable' dialogue box. You should now have a new variable in the data file called 'd8540' which only contains values when the diag_1 is Intracranial injury. C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 12

13 Repeat the above steps to produce another variable which contains only values for diagnosis 7151 by substituting the value 7151 for 8540 in each of the above steps. The picture opposite summerises the steps. You should now have a data file identical to the one below, the two extra calculated fields providing details for the diagnoses we are interested in. We will now produce a graph of the combined results. 1 Choose the menu option Graphs-> Line 2 Select Multiple 3 Select 'values for individual cases' 4 Click the 'Define' button You will now be presented with the following dialogue box. 5 Move the two new variables into the 'Lines Represent' box, as shown above 6 Select the 'Category labels' option 7 Move the 'startage ' variable into the 'Variable' box. 8 Click the OK button 9 You will now be presented with the following graph. C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 13

14 Value D7151 D8540 Unfortunately the points have not been jointed up for you. To do this you need to edit the chart and unselect the 'Break line at missing' which is a menu item in the 'Format' menu (Note: this may be different for version 6 of SPSS). The final result should look like something like the chart below STARTAGE Because we used the Line type graph the X axis is rather misleading for example the sharp rise where the chart indicates 88 is actually the set of values for the under one year olds (the 7001 etc. Age values, see the previous handout for details). It would have been more appropriate to use the scatter chart, with the age filter, with the overlay option described earlier in this handout. This is left as a final exercise for you to do. Clearly you can add as many diagnoses as you want to the charts to provide interesting comparisons. Value STARTAGE D7151 D8540 Common problem Blank Graphs! C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 14

15 3. Optional exercise 1 Produce a scatter chart with the overlay option of the above data. Hint 1: You need to apply the filter to exclude those startage values above 7000 first. Hint 2. When in the 'Overlay Scatterplot' dialogue box you need to click on the 'Options' button to set the 'Missing values' option to 'Exclude cases variable by variable'. Otherwise you will end up with a blank chart. The final result, with some additional editing is given opposite Select several diagnoses, from the list provided in the session two handout, Section 3, and repeat the exercise localised primary osteoarthritis 8540 intracranial injury nos no open intracranial wound 3 Re-run the aggregate commands to find out the proportion of deaths for each diagnosis regardless of age. 4 Re-run the aggregate commands to find out the proportion of deaths for each diagnosis for each age. C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 15

16 4. Appendix A similar result to some of the charts produced during this session could have been created directly from the original Tando1 data file DIAG_1 Count STARTAGE The chart abve was produced by: 1 Setting a filter to: (diag_1 = "8540-" or diag_1 = "7151-") and startage < Selecting the menu option Graphs -> line and the 'multiple' and 'Summaries for groups of cases' option. 3 Clicking on the defin button produces the dialogue box below. Set up the options as indicated. Note that the '% of cases' option is chossen. Finally click the OK button. End of handout. C:\HIcourseweb new\hes\ses3\hes_ses3.doc Robin Beaumont robin@organplayers.co.uk page 16