Create hes_apc_diagnosis.md

Author: anna-stevenson

docs/curated_assets/hes_apc_diagnosis.md

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+---
+layout: default
+title: HES APC - Diagnosis
+parent: HES APC
+grand_parent: Curated Assets
+nav_order: 1
+permalink: /curated_assets/hes_apc/hes_apc_diagnosis
+---
+
+# HES APC - Diagnosis
+
+<a href="https://github.com/BHFDSC/hds_curated_assets/blob/main/D08-hes_apc.py" class="btn btn-primary fs-5 mb-4 mb-md-0 mr-2" target="_blank">View code on GitHub</a>
+
+The *hes_apc_diagnosis* table is curated from the latest archived version of the HES APC table (hes_apc_all_years_archive). The output is a long format table where each row represents an individual three-digit (DIAG_3_01,…, DIAG_3_20) or four-digit (DIAG_4_01,…, DIAG_4_20) ICD-9 or ICD-10 diagnosis code associated with a specific individual and hospital episode. Non-alphanumeric characters and trailing Xs are removed from the diagnosis codes, and rows where codes are null, or an empty string, are removed ensuring only valid codes are retained. The resulting table includes 10 columns: 6 identifier columns (person ID, episode key, episode start date, episode end date, admission date and discharge date) and 4 columns capturing the diagnosis code and position (diag_column, code, diag_digits, diag_position).
+
+-	**diag_column**: the name of the original diagnosis column (eg., DIAG_3_01)
+-	**code**: the actual ICD diagnosis code
+-	**diag_digits**: indicates whether the ICD code is the three- or four-digit version
+-	**diag_position**: indicates the position of the diagnosis code (eg., 1-20)
+
+
+## Example
+
+| person_id | epikey | epistart | epiend | admidate | disdate | diag_column | code | diag_digits | diag_position |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| A | 178954263574 | 2021-06-24 | 2021-06-24 | 2021-06-24 | 2021-06-24 | DIAG_3_01 | H25 | 3 | 1 |
+| A | 178954263574 | 2021-06-24 | 2021-06-24 | 2021-06-24 | 2021-06-24 | DIAG_3_02 | H40 | 3 | 2 |
+| A | 178954263574 | 2021-06-24 | 2021-06-24 | 2021-06-24 | 2021-06-24 | DIAG_3_03 | H53 | 3 | 3 |
+| A | 178954263574 | 2021-06-24 | 2021-06-24 | 2021-06-24 | 2021-06-24 | DIAG_4_01 | H258 | 4 | 1 |
+| A | 178954263574 | 2021-06-24 | 2021-06-24 | 2021-06-24 | 2021-06-24 | DIAG_4_02 | H402 | 4 | 2 |
+| A | 178954263574 | 2021-06-24 | 2021-06-24 | 2021-06-24 | 2021-06-24 | DIAG_4_03 | H533 | 4 | 3 |
+| B | 559478246553 | 2020-10-07 | 2020-10-08 | 2020-10-07 | 2020-10-08 | DIAG_3_01 | T85 | 3 | 1 |
+| B | 559478246553 | 2020-10-07 | 2020-10-08 | 2020-10-07 | 2020-10-08 | DIAG_3_02 | Y84 | 3 | 2 |
+
+
+
+The table is saved to the DSA schema **dsa_391419_j3w9t_collab**. The archived_on_date is in the format **YYYY_MM_DD**.
+
+{: .highlight-title }
+> Table Name
+>
+> >
+> hds_curated_assets__hes_apc_diagnosis_archived_on_date
+
+The below code will load the hes_apc_diagnosis table as at October 2024 using PySpark:
+
+{% highlight markdown %}
+```python
+import pyspark.sql.functions as f
+dsa = f'dsa_391419_j3w9t_collab'
+demographics_table = spark.table(f'{dsa}.hds_curated_assets__hes_apc_diagnosis_2024_10_01')
+```
+{% endhighlight %}