It was Yoshi’s first challenge as a #WOW coach this week, and it provided us with an opportunity to develop our data densification and date calculation skills. I will admit, this certainly was a challenge that made me have to think a lot and reference other content where I’d done similar things before.

Modelling the data

Yoshi provided us with an adapted data set of patient waiting times, based on the Healthcare dataset from the Real World Fake Data (#RWFD) site. This provides 1 row per patient with a wait start time and end time. The requirement was to understand how many patients were waiting in each 30 min time slot in a 24hr period, so if a patient waited over 30 mins, or the start & wait time spanned a 30 min time slot, then the data needed to be densified appropriately. Yoshi therefore provided an additional data set to use for this densification, and I have to be honest, it wasn’t quite what I was expecting.

So the first challenge was to understand how to relate the two sets of data together, and this took some testing before I got it right. Yoshi provided hints about using a DATEDIFF calculation to find the time difference between the wait start time (rounded to 30 mins) and the wait end time (rounded to 30 mins).

To work out the calculation required, I actually first connected to the Hospital ER data set and then spent time working out the various parts of the formula required. I wanted to work out what the waiting start time was ’rounded down’ to the previous 30 min time slot, and what the waiting end time was ’rounded up’ to the next 30 min time slot.

Date Start Round

//Rounding down the wait start time

IIF(DATEPART(‘minute’, [Date Start])<30 , DATETRUNC(‘hour’, [Date Start]) , DATEADD(‘minute’, 30, DATETRUNC(‘hour’, [Date Start])))

If the minute of Date Start is between 0 and 29, then return the date at the hour mark, otherwise (if the minute of Date Start is between 30-59) then find the date at the hour mark, and add on 30 minutes. So if Date Start is 23/04/2019 13:23:00 then return 23/04/2019 13:00:00, but if Date Start is 23/04/2019 13:47, then return 23/04/2019 13:30:00.

Date End Round

//Rounding up the wait end time

IIF(DATEPART(‘minute’, [Date End])<30 , DATEADD(‘minute’, 30, DATETRUNC(‘hour’, [Date End])) , DATEADD(‘hour’, 1,DATETRUNC(‘hour’, [Date End])))

If the minute of Date End is between 0 and 29, then find the date at the hour mark, and add on 30 minutes, otherwise (if the minute of Date End is between 30-59) then find the date at the hour mark, and add on 1 hour. So if Date End is 23/04/2019 13:23:00 then return 23/04/2019 13:30:00, but if Date End is 23/04/2019 13:47, then return 23/04/2019 14:00:00.

With this, I was then able to relate the Hospital ER data set to the dummy by 30 min data set by adding a relationship calculation to the Hospital ER data set of

DATEDIFF(‘minute’,
IIF(DATEPART(‘minute’, [Date Start])<30 , DATETRUNC(‘hour’, [Date Start]) , DATEADD(‘minute’, 30, DATETRUNC(‘hour’, [Date Start]))),
IIF( DATEPART(‘minute’, [Date End])<30 , DATEADD(‘minute’, 30, DATETRUNC(‘hour’, [Date End])) , DATEADD(‘hour’, 1,DATETRUNC(‘hour’, [Date End])))
)

(which returns the difference in minutes between the ’rounded down’ Date Start and the ’rounded up’ Date End – you can’t reference calculated fields in the relationship, so you have to recreate)

and set this to be >= to Range End from the dummy by 30 min data set

Let’s see what this has done to the data.

On a sheet add Patient ID. Date Start (as discrete exact date – blue pill), Date End (as discrete exact date – blue pill), Date Start Round (as discrete exact date – blue pill), Date End Round (as discrete exact date – blue pill) and Index (as discrete dimension – blue pill) to Rows and add Patient Waittime to Text.

Looking at the data for Patient Id 899-89-7946 : they started waiting at 06:18 and ended at 07:17. This meant they spanned three 30 min time slots: 06:00-06:30, 06:30-07:00 and 07:00-07:30, and consequently there are 3 rows displayed, and the ’rounded’ start & end dates go from 06:00 to 07:30.

Identifying the axis to plot the 24hr time period against

Having ‘densified’ the data, we now need to get a date against each row related to the 30 min time slot it represents. ie, for the example above we need to capture a date with the 06:00 time slot, the 06:30 time slot and the 07:00 time slot.

But, as the chart we want to display is depicted over a 24hr timeframe, we need to align all the dates to the exact same day, while retaining the time period associated to each record. This technique to shift the dates to the same date, is described in this Tableau Knowledge Base article.

Date Start Baseline

DATEADD(‘day’, DATEDIFF(‘day’, [Date Start Round], #1990-01-01#), [Date Start Round])

Add this into the table, you can see what this data all looks like – note, I’m just choosing a arbitrary date of 01 Jan 1990, so my baseline dates are all on this date, but the time portions reflect that of the Date Start Round field.

With the day all aligned, we now want to get a time reflective of each 30 min timeslot. The logic took a bit of trial and error to get right, and there may well be a much better method than what I came up with. It became tricky as I had to handle what happens if the time is after 11pm (23:00) as I needed to make sure I didn’t end up returning dates on a different day (ie 2nd Jan 1990). I’ll describe my logic first.

If the Index is 0 then we just want the date time we’ve already adjusted – ie Date Start Baseline

If the Index is 1, then we need to shift the Date Start Baseline by 30 minutes. However, if Date Start Baseline is already 23:30, then we need to hardcode the date to be 01 Jan 1990 00:00:00, as ‘adding’ 30 mins will result in 02 Jan 1990 00:00:00.

If the Index is 2, then we need to shift the Date Start Baseline by 1 hour. However, if Date Start Baseline is already 23:30, then we need to hardcode the date to be 01 Jan 1990 00:30:00, as ‘adding’ 1 hour will result in 02 Jan 1990 00:30:00. Similarly, if Date Start Baseline is already 23:00, then we need to hardcode the date to 01 Jan 1990 00:00:00, otherwise we’ll end up with 02 Jan 1990 00:00:00.

As the relationship didn’t result in any instances of Index > 2, I stopped my logic there. This is all encapsulated within the calculation

Date to Plot

CASE [Index]
WHEN 0 THEN [Date Start Baseline ]
WHEN 1 THEN IIF(DATEPART(‘hour’, [Date Start Baseline ])=23 AND DATEPART(‘minute’, [Date Start Baseline ])=30, #1990-01-01 00:00:00#, DATEADD(‘minute’, 30, [Date Start Baseline ]))
WHEN 2 THEN IIF(DATEPART(‘hour’, [Date Start Baseline ])=23 AND DATEPART(‘minute’, [Date Start Baseline ])=30, #1990-01-01 00:30:00#, IIF(DATEPART(‘hour’, [Date Start Baseline ])=23 AND DATEPART(‘minute’, [Date Start Baseline ])=0, #1990-01-01 00:00:00#, DATEADD(‘hour’, 1, [Date Start Baseline ])))
END

Phew!

Add this to the table as a discrete exact date (blue pill), and you can see what’s happening.

For Patient Id 899-89-7946, we have the 3 timeslots we wanted: 06:00 (representing 06:00-06:30), 06:30 (representing 06:30 -07:00) and 07:00 (representing 07:00-07:30).

On a new sheet, add Date To Plot as a discrete exact date (blue pill) and then create

Count Patients

COUNT([Patient Id])

and add to Text and you have a list of the 48 30 min time slots that exist within a 24hr period, with the patient counts.

We need to be able to filter this based on a quarter, so create

Date Start Quarter

DATE(DATETRUNC(‘quarter’,[Date Start]))

and custom format this to yyyy-“Q”q

Add to the Filter shelf selecting individual dates and filter to 2019-Q2, and the results will adjust, and you should be able to reconcile against the solution.

Building the 30 minute time slot bar chart

On a new sheet, add Date Start Quarter to the Filter shelf and set to 2019-Q2. Then add Date to Plot as a continuous exact date (green pill) to Columns and Count Patients to Rows. Change the mark type to a bar and show mark labels.

Custom format Date To Plot to hh:nn.

We need to identify a selected bar in a different colour. We’ll use a parameter to capture the selected bar.

pSelectTimePeriod

date parameter defaulted to 01 Jan 1990 14:00 with a display format of hh:nn

Then create a calculated field

Is Selected Time Period

[Date to Plot] = [pSelectTimePeriod]

and add to the Colour shelf, adjusting colours to suit and setting the font on the labels to match mark colour.

A ‘bonus’ requirement is to make each bar ’30 mins’ wide. For this we need

Size – 30 Mins

//number of seconds in 30 mins divided by number of seconds in a day (24hrs)
(30 * 60) / 86400

Add this to the Size shelf, change it to be a dimension (so no longer aggregated to SUM), then click on the Size shelf, and set it to be fixed width, left aligned.

Via the Colour shelf, change the border of the mark to white.

Next, we need to get the tooltip to reflect the ‘current’ time slot, as well as the next time slot. For this I created

Next Time Period

IIF(LAST()=0, #1990-01-01 00:00:00#, LOOKUP(MIN([Date to Plot]),1))

This is a table calculation. If it’s the last record (ie 01 Jan 1990 23:30), then set the time slot to be 1st Jan 1990 00:00, otherwise return the next time slot (lookup the next (+1) record). Custom format this to hh:nn and add to the Tooltip shelf. Set the table calculation to compute by Date to Plot and Is Selected Time Period.

Update the Tooltip as required.

The final part of this bar chart is another ‘bonus’ requirement – to add 2 hr time interval ‘bandings’. For this I created another calculated field

2hr Time Period to Plot

IIF(DATEPART(‘hour’, MIN([Date to Plot]))%4 = 0 AND DATEPART(‘minute’, MIN([Date to Plot]))=0,WINDOW_MAX([Count Patients])*1.1,NULL)

If the hour part of the date is divisible by 4 (ie 0, 4, 8,12,16, 20), and we’re at the hour mark (minute of date is 0), then get the value of highest patient count displayed in the chart, and uplift it by 10%, otherwise return nothing.

Add this to Rows. On the 2nd marks card created, remove Is Selected Time Period from Colour and Next Time Period from Tooltip. Adjust the table calculation of the 2hr Time Period to Plot to compute by Date to Plot only. Remove labels from displaying.

The bars are currently showing all at the same height (as required) but at a width of 30 minutes. We want this to be 2 hrs instead, so create

Size – 2 Hrs

//number of seconds in 2hrs / number of seconds in a day (24 hrs)
(60*60*2)/86400

Add this to the Size shelf instead (fixing it to left again). Adjust the colour to a pale grey, and delete all the text from the Tooltip.

Hide the nulls indicator. Make the chart dual axis and synchronise the axis. Right click on the 2hr Time Period Plot axis (the right hand axis) and move marks to back.

Tidy up the chart by removing row & column dividers, hiding the right hand axis, removing the titles from the other axes. Update the title accordingly.

Building the Patient Detail bar chart

On a new sheet, add Is Selected Time Period to Filter and set to True. Then go back to the other bar chart, and set the Date Start Quarter Filter to Apply to Worksheets -> Selected Worksheets and select the new one being built.

Add Department Referral, Patient Id, Date Start (as discrete exact date – blue pill) and Date End (as discrete exact date – blue pill) to Rows and Patient Waittime to Columns. Manually drag the None Department Referral option to the top of the chart. Add Patient Waittime to Colour and adjust to use the grey colour palette. Remove column dividers.

The title of this chart needs to display the number of patients in the selection, as well as the timeframe of the 30 min period. We already have the start of this captured in the parameter pSelectTimePeriod. We can use parameters to capture the other values too.

pNumberPatients

integer parameter defaulted to 0

pNextTimePeriod

date parameter, defaulted to 01 Jan 1990 14:30:00, with a custom display format of hh:nn

Update the title of the Patient Detail bar chart to reference these parameters (don’t worry about the count not being right at this point).

Capturing the selections

Add the sheets onto a dashboard. Then create the following dashboard parameter actions.

Set Selected Start

On select of the 30 Min bar chart, set the pSelectTimePeriod parameter passing in the value from the Date To Plot field.

Set Selected End

On select of the 30 Min bar chart, set the pNextTimePeriod parameter passing in the value from the Next Time Period field.

Set Count of Patients

On select of the 30 Min bar chart, set the pNumberPatients parameter passing in the value from the Count Patients field, aggregated at the SUM level.

With these all set, you should find you can click on a bar in the 30 minute chart and filter the list of patients below, with the title reflecting the bar chosen.

The basic viz itself wasn’t overly tricky, once you get over the hurdle of the calculations needed for the relationship and identifying the relevant 30 min time periods.

My published viz is here. Enjoy!

Happy vizzin’!

Donna