refactor virtual wards

raw_data/inpatients_mitigators.py

@@ -10,6 +10,7 @@ def generate_inpatients_mitigators() -> None:
     """Generrate Inpatients Mitigators"""
     path = ["mitigators", "ip"]
 
+    import_errors = False
     for i in ["activity_avoidance", "efficiency"]:
         for j in sorted(os.listdir("/".join(path + [i]))):
             if j == "__init__.py":
@@ -18,23 +19,20 @@ def generate_inpatients_mitigators() -> None:
             try:
                 importlib.import_module(module)
             except:  # pylint: disable=bare-except
+                import_errors = True
                 print(f"Error: {module}")
 
+    if import_errors:
+        raise ImportError("Error importing modules")
+
     all_mitigators = [
         v2
         for v1 in mitigators.__registered_mitigators.values()  # pylint: disable=protected-access
         for v2 in v1.values()
     ]
 
-    errors = {}
-
     for m in all_mitigators:
-        try:
-            m.save()
-        except Exception as e:  # pylint: disable=broad-exception-caught
-            errors[str(m)] = e
-
-    print(errors)
+        m.save()
 
 
 if __name__ == "__main__":

raw_data/mitigators/ip/activity_avoidance/virtual_wards.py

@@ -3,59 +3,31 @@
 Virtual wards allow patients to receive the care they need at home, safely and conveniently rather
 than in hospital. They also provide systems with a significant opportunity to narrow the gap between
 demand and capacity for secondary care beds, by providing an alternative to admission and/or early
-discharge. 
+discharge.
 
 Whilst virtual wards may be beneficial for patients on a variety of clinical pathways, guidance has
 been produced relating to three pathways which represent the majority of patients who may be
 clinically suitable to benefit from a virtual ward. These pathways are Frailty, Acute Respiratory
-Infections (ARI) and Heart failure. 
+Infections (ARI) and Heart failure.
 
 This activity avoidance mitigator identifies patients who may be suitable for admission to an ARI or
-Heart Failure virtual ward. 
+Heart Failure virtual ward.
 
 ### Available breakdowns
 
 - Acute Respiratory Infection (IP-AA-030)
 - Heart Failure (IP-AA-031)
 """
 
-from pyspark.sql import functions as F
-
-from hes_datasets import nhp_apc, primary_diagnosis, procedures
 from raw_data.mitigators import activity_avoidance_mitigator
-
-
-def _virtual_wards_admissions(*args):
-    return (
-        nhp_apc.filter(F.col("admimeth").rlike("^2"))
-        .filter(F.col("dismeth").isin(["1", "2", "3"]))
-        .filter(F.col("age") >= 18)
-        .admission_has(primary_diagnosis, *args)
-        .select("epikey")
-        .withColumn("sample_rate", F.lit(1.0))
-    )
-
-
-# define these methods so they can be used for both activity avoidance and efficiencies
-
-
-def virtual_wards_ari():
-    """Virtual Wards: Acute Respiratory Infection (ARI)"""
-    return _virtual_wards_admissions("B(3[34]|97)", "J(0[6-9]|[1-9])", "U0[467]").join(
-        procedures, ["epikey"], "anti"
-    )
-
-
-def virtual_wards_heart_failure():
-    """Virtual Wards: Heart Failure"""
-    return _virtual_wards_admissions("I(110|255|42[09]|50[019])")
+from raw_data.mitigators.ip.shared import virtual_wards
 
 
 @activity_avoidance_mitigator()
 def _virtual_wards_activity_avoidance_ari():
-    return virtual_wards_ari()
+    return virtual_wards.ari()
 
 
 @activity_avoidance_mitigator()
 def _virtual_wards_activity_avoidance_heart_failure():
-    return virtual_wards_heart_failure()
+    return virtual_wards.heart_failure()

raw_data/mitigators/ip/efficiency/virtual_wards.py

@@ -3,31 +3,26 @@
 Virtual wards allow patients to receive the care they need at home, safely and conveniently rather
 than in hospital. They also provide systems with a significant opportunity to narrow the gap between
 demand and capacity for secondary care beds, by providing an alternative to admission and/or early
-discharge. 
+discharge.
 
 Whilst virtual wards may be beneficial for patients on a variety of clinical pathways guidance has
 been produced relating to three pathways which represent the majority of patients who may be
 clinically suitable to benefit from a virtual ward. These pathways are Frailty, Acute Respiratory
-Infections (ARI) and Heart failure. 
+Infections (ARI) and Heart failure.
 
 This efficiency mitigator identifies patients who may be suitable for earlier discharge through
-admission to step down ARI or Heart Failure virtual wards. 
+admission to step down ARI or Heart Failure virtual wards.
 """
 
 from raw_data.mitigators import efficiency_mitigator
-from raw_data.mitigators.ip.activity_avoidance.virtual_wards import (
-    virtual_wards_ari,
-    virtual_wards_heart_failure,
-)
-
-# use the definitions from activity avoidance
+from raw_data.mitigators.ip.shared import virtual_wards
 
 
 @efficiency_mitigator()
 def _virtual_wards_efficiencies_ari():
-    return virtual_wards_ari()
+    return virtual_wards.ari()
 
 
 @efficiency_mitigator()
 def _virtual_wards_efficiencies_heart_failure():
-    return virtual_wards_heart_failure()
+    return virtual_wards.heart_failure()

raw_data/mitigators/ip/shared/virtual_wards.py

@@ -0,0 +1,42 @@
+"""Virtual Wards
+
+Virtual wards allow patients to receive the care they need at home, safely and conveniently rather
+than in hospital. They also provide systems with a significant opportunity to narrow the gap between
+demand and capacity for secondary care beds, by providing an alternative to admission and/or early
+discharge.
+
+Whilst virtual wards may be beneficial for patients on a variety of clinical pathways, guidance has
+been produced relating to three pathways which represent the majority of patients who may be
+clinically suitable to benefit from a virtual ward. These pathways are Frailty, Acute Respiratory
+Infections (ARI) and Heart failure.
+"""
+
+from pyspark.sql import functions as F
+
+from hes_datasets import nhp_apc, primary_diagnosis, procedures
+
+
+def _virtual_wards_admissions(*args):
+    return (
+        nhp_apc.filter(F.col("admimeth").rlike("^2"))
+        .filter(F.col("dismeth").isin(["1", "2", "3"]))
+        .filter(F.col("age") >= 18)
+        .admission_has(primary_diagnosis, *args)
+        .select("epikey")
+        .withColumn("sample_rate", F.lit(1.0))
+    )
+
+
+# define these methods so they can be used for both activity avoidance and efficiencies
+
+
+def ari():
+    """Virtual Wards: Acute Respiratory Infection (ARI)"""
+    return _virtual_wards_admissions("B(3[34]|97)", "J(0[6-9]|[1-9])", "U0[467]").join(
+        procedures, ["epikey"], "anti"
+    )
+
+
+def heart_failure():
+    """Virtual Wards: Heart Failure"""
+    return _virtual_wards_admissions("I(110|255|42[09]|50[019])")