Window functions and calculating averages with tricky data manipulation - sql

Question

I have a SQL Server programming challenge involving some manipulations of healthcare patient pulse readings.
The goal is to do an average of readings within a certain time period and to only include the latest pulse reading of the day.
As an example, times are appt_time:
PATIENT 1 PATIENT 2
‘1/1/2019 80 ‘1/3/2019 90
‘1/4/2019 85
‘1/2/2019 10 am 78
‘1/2/2019 1 pm 85
‘1/3/2019 90
A patient may or may not have a second reading in a day. Only the last 3 latest chronological readings are used for the average. If less than 3 readings are available, an average is computed for 2 readings, or 1 reading is chosen as average.
Can this be done with the SQL window functions? This is a little more efficient than using a subquery.
I have used first_VALUE desc statements successfully to pick the last pulse in a day. I then have tried various row_number commands to exclude the marked off row (first pulse of the day when 2 readings are present). I cannot seem to correctly calculate the average. I have used row_number in select and from clauses.
with CTEBPI3
AS (
SELECT pat_id
,appt_time
,bp_pulse
,first_VALUE (bp_pulse) over(partition by appt_time order by appt_time desc ) fv
,ROW_NUMBER() OVER (PARTITION BY appt_time ORDER BY APPT_time DESC)RN1
,,Round(Sum(bp_pulse) OVER (PARTITION BY Pat_id) / COUNT (appt_time) OVER (PARTITION BY Pat_id), 0) AS adJAVGSYS3
FROM
pat_enc
WHERE appt_time > '07/15/2018'
)
select *,
WHEN rn=1
Average for pat1 should be 85
Average for pat2 should be 87.5

Answer 1

You can do this with two window functions:
MAX(appt_time) OVER ... to get the latest time per day
DENSE_RANK() OVER ... to get the last three days
You get the date part from your datetime with CONVERT(DATE, appt_time). The average function AVGis already built in :-)
The complete query:
select pat_id, avg(bp_pulse) as average_pulse
from
(
select
pat_id, appt_time, bp_pulse,
max(appt_time) over (partition by pat_id, convert(date, appt_time)) as max_time,
dense_rank() over (partition by pat_id order by convert(date, appt_time) desc) as rn
from pat_enc
) evaluated
where appt_time = max_time -- last row per day
and rn <= 3 -- last three days
group by pat_id
order by pat_id;
If the column bp_pulse is defined as an integer, you must convert it to a decimal to avoid integer arithmetic:
select pat_id, avg(convert(decimal, bp_pulse)) as average_pulse
Demo: https://dbfiddle.uk/?rdbms=sqlserver_2017&fiddle=3df744fcf2af89cdfd8b3cd8b6546d89

Answer 2

Actually, window functions are not necessarily more efficient. It is worth comparing:
select p.pat_id, avg(p.bp_pulse)
from pat_enc p
where -- appt_time > '2018-07-15' and -- don't know if this is necessary
p.appt_time >= (select distinct convert(date, appt_time)
from pat_enc p2
where p2.pat_id = p.pat_id
order by distinct convert(date, appt_time)
offset 2 row fetch first 1 row only
) and
p.appt_time = (select max(p2.appt_time)
from pat_enc p2
where p2.pat_id = p.pat_id and
convert(date, p2.appt_time) = convert(date, p.appt_time)
);
This wants an index on pat_enc(pat_id, appt_time).
In fact, there are a variety of ways to write this logic, with different mixes of subqueries and window functions (this is one extreme).
Which performs the best will depend on the nature of your data. In particular:
The number of appointments on the same day -- is this normally 1 or a large number?
The overall number of days with appointments -- is this right around three or are there hundreds?
You need to test on your data, but I think window function will work best when relatively few rows are filtered out (~1 appointment/day, ~3 days with appointments). Subqueries will be helpful when more rows are being filtered.