SQL consolidate overlapping dates based on criteria - sql

Question

I'm trying to merge overlapping dates between Admit and discharge dates of patients. There are a few edge cases which I couldn't cover in the query.
Input
+----+------------+--------------+
| ID | Admit_Dt | Discharge_Dt |
+----+------------+--------------+
| 1 | 12/30/2020 | 07/14/2021 |
+----+------------+--------------+
| 1 | 01/02/2021 | 07/14/2021 |
+----+------------+--------------+
| 1 | 06/16/2021 | 07/14/2021 |
+----+------------+--------------+
| 2 | 03/04/2021 | 03/25/2021 |
+----+------------+--------------+
| 2 | 05/01/2021 | 05/10/2021 |
+----+------------+--------------+
| 3 | 06/01/2021 | 06/05/2021 |
+----+------------+--------------+
Expected Output
+----+------------+--------------+
| ID | Admit_dt | Discharge_dt |
+----+------------+--------------+
| 1 | 12/30/2020 | 07/14/2021 |
+----+------------+--------------+
| 2 | 03/04/2021 | 03/25/2021 |
+----+------------+--------------+
| 2 | 05/01/2021 | 05/10/2021 |
+----+------------+--------------+
| 3 | 06/01/2021 | 06/05/2021 |
+----+------------+--------------+
Query I used the logic that was here But this doesn't cover the edge case for ID 2 and 3. Also the subquery is slower when the data is huge. Is it possible to tackle this problem using LAG?
SELECT dr1.* FROM Member_Discharges dr1
INNER JOIN Member_Discharges dr2
ON dr2.ADMIT_DT> dr1.ADMIT_DT
and dr2.ADMIT_DT< dr1.DISCHARGE_DT

Answer 1

This is a type of gaps-and-islands problem. I would suggest using a cumulative max to determine when an "island" starts and then aggregate:
select id, min(admit_dt), max(discharge_dt)
from (select t.*,
sum(case when prev_Discharge_dt >= Admit_Dt then 0 else 1 end) over (partition by id order by admit_dt, discharge_dt) as grp
from (select t.*,
max(Discharge_dt) over (partition by id
order by Admit_Dt, Discharge_dt
rows between unbounded preceding and 1 preceding) as prev_Discharge_dt
from t
) t
) t
group by id, grp;
Here is a db<>fiddle.
The innermost subquery is retrieving the maximum discharge date before each row. This allows you to check for an overlap. The middle subquery counts up the number of times there is no overlap -- the beginning of a group. And the outer query aggregates.

Answer 2

Here is another "gaps-and-islands" solution
Use LAG to determine if the previous Discharge_Dt is earlier than the current Admit_Dt, if so we have a starting point
Number the islands using COUNT OVER
Group by the ID and the new grouping number, and take the min and max dates
WITH StartPoints AS (
SELECT *,
IsStart = CASE WHEN LAG(Discharge_Dt, 1, '19000101')
OVER (PARTITION BY ID ORDER BY Admit_Dt)
< Admit_Dt THEN 1 END
FROM YourTable t
),
Groupings AS (
SELECT *,
GroupId = COUNT(IsStart) OVER (PARTITION BY ID
ORDER BY Admit_Dt ROWS UNBOUNDED PRECEDING)
FROM StartPoints
)
SELECT ID, Admit_Dt = MIN(Admit_Dt), Discharge_Dt = MAX(Discharge_Dt)
FROM Groupings
GROUP BY ID, GroupId
ORDER BY ID, GroupId;
db<>fiddle