如何从SQL中的历史住院患者数据计算每月30天的再入院率？

我想根据5年60个月的住院数据计算每月再住院率。一些住院患者在这段时间内再次入院超过10次，而其他患者只有一次

数据表如下所示。例如，身份证号为201的住院患者五年内仅入院一次，但身份证号为212的住院患者有四次，其中两人在三天内再次入院

如何使用SQL中的此类数据计算医院每月30天的再入院率？30天再入院是指住院患者在上次出院后30天内再次入院 谢谢大家!

  ID   | SN    | Admdate     | Disdate       |
+------+-------+-------------+---------------+
|**212 | 1     | 2014-01-01  | 2014-01-12**  |
|201   | 2     | 2014-01-01  | 2014-01-10    |
|**212 | 598   | 2014-01-28  | 2014-02-12**  |
|**212 | 10000 | 2016-12-23  | 2016-12-29 ** |
| **212| 15112 | 2017-06-10  | 2017-06-21 ** |
|*401  | 20101 | 2018-01-01 | 2018-01-11     |*
|*401  | 21101 | 2018-02-01 | 2018-02-13     |*
|401   | 22101 | 2018-10-01  | 2018-10-11    |

为此：

with cte as (
  select 
    t.admdate,
    case when exists (
      select 1 from tablename
      where id = t.id and sn <> t.sn and datediff(day, disdate, t.admdate) <= 30
    ) then 1 else 0 end readmission
  from tablename t
  where datediff(month, t.admdate, getdate()) <= 60
)
select 
  year(admdate) year, 
  month(admdate) month,
  100.0 * sum(readmission) / count(*) readmissionrate
from cte
group by year(admdate), month(admdate) 
order by year(admdate), month(admdate)

如果表的该行是重新读取，则CTE返回值为1的列重新读取，否则返回值为0。 然后通过使用group by YEARDAMDATE、monthadmdate，您可以通过SUMREADDISION获得重新读取的总数，并除以总行数。

---

请看。

看起来，我有点晚了，但尽管如此-以下是我的建议：

WITH mnths AS (
  select cast(1 as int) m 
  UNION ALL select m+1 FROM mnths WHERE m<60 
), admdis AS (
  SELECT *, 12*(year(admdate)-2014)+month(admdate)a, 12*(year(disdate)-2014)+month(disdate) d 
  FROM tbl t
  WHERE exists (SELECT 1 FROM tbl WHERE id=t.id AND disdate>DATEADD(day, -30, t.admdate) and sn<t.sn) 
)
SELECT (m-1)/12+2014 yr, 1+(m-1)%12 mn,m, count(id) readm 
FROM mnths LEFT JOIN admdis ON a=m
GROUP BY m 

在计算比率时，我必须确保我没有被零除，因此，在那些没有入学的月份，比率被假定为零，但没有实际计算

演示：

下面是生成的结果：

yr    mn totl readm rate
2014    1   3   1   0.333333333333
2014    2   0   0   0.000000000000
2014    3   0   0   0.000000000000
2014    4   0   0   0.000000000000
2014    5   0   0   0.000000000000
2014    6   0   0   0.000000000000
2014    7   0   0   0.000000000000
2014    8   0   0   0.000000000000
2014    9   0   0   0.000000000000
2014    10  0   0   0.000000000000
2014    11  0   0   0.000000000000
2014    12  0   0   0.000000000000
2015    1   0   0   0.000000000000
2015    2   0   0   0.000000000000
2015    3   0   0   0.000000000000
2015    4   0   0   0.000000000000
2015    5   0   0   0.000000000000
2015    6   0   0   0.000000000000
2015    7   0   0   0.000000000000
2015    8   0   0   0.000000000000
2015    9   0   0   0.000000000000
2015    10  0   0   0.000000000000
2015    11  0   0   0.000000000000
2015    12  0   0   0.000000000000
2016    1   0   0   0.000000000000
2016    2   0   0   0.000000000000
2016    3   0   0   0.000000000000
2016    4   0   0   0.000000000000
2016    5   0   0   0.000000000000
2016    6   0   0   0.000000000000
2016    7   0   0   0.000000000000
2016    8   0   0   0.000000000000
2016    9   0   0   0.000000000000
2016    10  0   0   0.000000000000
2016    11  0   0   0.000000000000
2016    12  1   0   0.000000000000
2017    1   0   0   0.000000000000
2017    2   0   0   0.000000000000
2017    3   0   0   0.000000000000
2017    4   0   0   0.000000000000
2017    5   0   0   0.000000000000
2017    6   1   0   0.000000000000
2017    7   0   0   0.000000000000
2017    8   0   0   0.000000000000
2017    9   0   0   0.000000000000
2017    10  0   0   0.000000000000
2017    11  0   0   0.000000000000
2017    12  0   0   0.000000000000
2018    1   1   0   0.000000000000
2018    2   1   1   1.000000000000
2018    3   0   0   0.000000000000
2018    4   0   0   0.000000000000
2018    5   0   0   0.000000000000
2018    6   0   0   0.000000000000
2018    7   0   0   0.000000000000
2018    8   0   0   0.000000000000
2018    9   0   0   0.000000000000
2018    10  1   0   0.000000000000
2018    11  0   0   0.000000000000
2018    12  0   0   0.000000000000

---

totl列包含该期间的总入院人数，readm再入院人数和比率是readm/totl的比率，如果totl为0，则为0。

您期望的输出是什么？我使用的是SQL Server版本17。

yr    mn totl readm rate
2014    1   3   1   0.333333333333
2014    2   0   0   0.000000000000
2014    3   0   0   0.000000000000
2014    4   0   0   0.000000000000
2014    5   0   0   0.000000000000
2014    6   0   0   0.000000000000
2014    7   0   0   0.000000000000
2014    8   0   0   0.000000000000
2014    9   0   0   0.000000000000
2014    10  0   0   0.000000000000
2014    11  0   0   0.000000000000
2014    12  0   0   0.000000000000
2015    1   0   0   0.000000000000
2015    2   0   0   0.000000000000
2015    3   0   0   0.000000000000
2015    4   0   0   0.000000000000
2015    5   0   0   0.000000000000
2015    6   0   0   0.000000000000
2015    7   0   0   0.000000000000
2015    8   0   0   0.000000000000
2015    9   0   0   0.000000000000
2015    10  0   0   0.000000000000
2015    11  0   0   0.000000000000
2015    12  0   0   0.000000000000
2016    1   0   0   0.000000000000
2016    2   0   0   0.000000000000
2016    3   0   0   0.000000000000
2016    4   0   0   0.000000000000
2016    5   0   0   0.000000000000
2016    6   0   0   0.000000000000
2016    7   0   0   0.000000000000
2016    8   0   0   0.000000000000
2016    9   0   0   0.000000000000
2016    10  0   0   0.000000000000
2016    11  0   0   0.000000000000
2016    12  1   0   0.000000000000
2017    1   0   0   0.000000000000
2017    2   0   0   0.000000000000
2017    3   0   0   0.000000000000
2017    4   0   0   0.000000000000
2017    5   0   0   0.000000000000
2017    6   1   0   0.000000000000
2017    7   0   0   0.000000000000
2017    8   0   0   0.000000000000
2017    9   0   0   0.000000000000
2017    10  0   0   0.000000000000
2017    11  0   0   0.000000000000
2017    12  0   0   0.000000000000
2018    1   1   0   0.000000000000
2018    2   1   1   1.000000000000
2018    3   0   0   0.000000000000
2018    4   0   0   0.000000000000
2018    5   0   0   0.000000000000
2018    6   0   0   0.000000000000
2018    7   0   0   0.000000000000
2018    8   0   0   0.000000000000
2018    9   0   0   0.000000000000
2018    10  1   0   0.000000000000
2018    11  0   0   0.000000000000
2018    12  0   0   0.000000000000