class MedicalDiagnosesRuleGroup(CrfRuleGroup):
"""Allows the heartattack, cancer, tb forms to be made available
whether or not the participant has a record. see redmine 314.
"""
heart_attack_record = CrfRule(
predicate=P('heart_attack_record', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.heartattack'])
cancer_record = CrfRule(
predicate=P('cancer_record', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.cancer'])
tb_record_tuberculosis = CrfRule(
predicate=P('tb_record', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.tuberculosis'])
class Meta:
app_label = app_label
source_model = f'{app_label}.medicaldiagnoses'
class ReviewPositiveRuleGroup(CrfRuleGroup):
recorded_hiv_result = CrfRule(
predicate=pc.func_requires_todays_hiv_result,
consequence=NOT_REQUIRED,
alternative=REQUIRED,
target_models=[f'{app_label}.hivcareadherence',
f'{app_label}.hivmedicalcare',
f'{app_label}.positiveparticipant'])
recorded_hivresult = CrfRule(
predicate=P('recorded_hiv_result', 'eq', NEG),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.stigma', f'{app_label}.stigmaopinion'])
require_todays_hiv_result = CrfRule(
predicate=pc.func_requires_todays_hiv_result,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hivresult'])
class Meta:
app_label = app_label
source_model = f'{app_label}.hivtestreview'
class SexualBehaviourRuleGroup(CrfRuleGroup):
partners = CrfRule(
predicate=pc.func_requires_recent_partner,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.recentpartner'])
last_year_partners = CrfRule(
predicate=pc.func_requires_second_partner_forms,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.secondpartner'])
more_partners = CrfRule(
predicate=pc.func_requires_third_partner_forms,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.thirdpartner'])
ever_sex = CrfRule(
predicate=PF(
'ever_sex', 'gender',
func=lambda x, y: True if x == YES and y == FEMALE else False),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.reproductivehealth',
f'{app_label}.pregnancy',
f'{app_label}.nonpregnancy'])
class Meta:
app_label = app_label
source_model = f'{app_label}.sexualbehaviour'
class ChildSocioDemographicRuleGroup(CrfRuleGroup):
attend_school = CrfRule(predicate=P('attend_school', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.academicperformance'])
working_status = CrfRule(predicate=P('working', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.childworkingstatus'])
class Meta:
app_label = app_label
source_model = f'{app_label}.childsociodemographic'
class BaseCrfRuleGroup(CrfRuleGroup):
pima_cd4 = CrfRule(
predicate=pc.func_requires_pima_cd4,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.pimacd4'])
hic_enrollment = CrfRule(
predicate=pc.func_requires_hic_enrollment,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hicenrollment'])
class Meta:
abstract = True
class CrfRuleGroup1(BaseCrfRuleGroup):
serve_sti_form = CrfRule(
predicate=pc.func_hiv_positive,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hivrelatedillness'])
elisa_result = CrfRule(
predicate=P('hiv_result', 'eq', IND),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.elisahivresult'])
class Meta:
app_label = app_label
source_model = f'{app_label}.hivresult'
class CircumcisionRuleGroup(CrfRuleGroup):
circumcised = CrfRule(
predicate=P('circumcised', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.circumcised'])
uncircumcised = CrfRule(
predicate=P('circumcised', 'eq', NO),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.uncircumcised'])
class Meta:
app_label = app_label
source_model = f'{app_label}.circumcision'
class ResourceUtilizationRuleGroup(CrfRuleGroup):
out_patient = CrfRule(
predicate=P('out_patient', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.outpatientcare'])
hospitalized = CrfRule(
predicate=P('hospitalized', 'eq', 0),
consequence=NOT_REQUIRED,
alternative=REQUIRED,
target_models=[f'{app_label}.hospitaladmission'])
class Meta:
app_label = app_label
source_model = f'{app_label}.resourceutilization'
class MaternalSrhServicesRuleGroup(CrfRuleGroup):
srh_services = CrfRule(predicate=pc.func_show_srh_services_utilization,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[(f'{app_label}.maternalsrh')])
class Meta:
app_label = app_label
source_model = f'{app_label}.maternalvisit'
class InfantBirthArvRuleGroup(CrfRuleGroup):
birth_arv = CrfRule(predicate=pc.func_infant_heu,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[(f'{app_label}.infantbirtharv')])
class Meta:
app_label = app_label
source_model = f'{app_label}.infantvisit'
class InfantArvProphRuleGroup(CrfRuleGroup):
arv_proph = CrfRule(predicate=pc.func_show_infant_arv_proph,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[(f'{app_label}.infantarvproph')])
class Meta:
app_label = app_label
source_model = f'{app_label}.infantvisit'
class InfantFuDxRuleGroup(CrfRuleGroup):
has_dx_yes = CrfRule(predicate=P('has_dx', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[(f'{app_label}.infantfudx')])
class Meta:
app_label = app_label
source_model = f'{app_label}.infantfu'
class KaraboOffstudyRuleGroup(CrfRuleGroup):
show_offstudy = CrfRule(predicate=pc.show_karabo_offstudy,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[(f'{app_label}.karabooffstudy')])
class Meta:
app_label = app_label
source_model = f'{app_label}.karabotuberculosishistory'
class InfantNvpDispensingRuleGroup(CrfRuleGroup):
infant_nvp_dispensing = CrfRule(
predicate=pc.func_show_infant_nvp_dispensing,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[(f'{app_label}.infantnvpdispensing')])
class Meta:
app_label = app_label
source_model = f'{app_label}.infantvisit'
class RapidTestResultGroup(CrfRuleGroup):
rapid_test_result = CrfRule(
predicate=pc.func_show_rapid_test_form,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[(f'{app_label}.rapidtestresult')])
class Meta:
app_label = app_label
source_model = f'{app_label}.maternalvisit'
class InfantBirthDataRuleGroup(CrfRuleGroup):
solid_foods = CrfRule(
predicate=P('congenital_anomalities', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[(f'{app_label}.infantcongenitalanomalies')])
class Meta:
app_label = app_label
source_model = f'{app_label}.infantbirthdata'
class ViralLoadTrackingCrfRuleGroup(CrfRuleGroup):
is_drawn = CrfRule(predicate=P('is_drawn', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.vlresult'])
class Meta:
source_model = f'{app_label}.viralloadtracking'
app_label = app_label
class EducationQuestionnaireRuleGroup(CrfRuleGroup):
work_status = CrfRule(
predicate=P('work_status', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.communityquestionnaire'])
class Meta:
app_label = 'trainee_subject'
source_model = f'{app_label}.educationquestionnaire'
class InfantNvpAdjustmentRuleGroup(CrfRuleGroup):
nvp_adjustment = CrfRule(predicate=pc.func_show_nvp_adjustment_2010,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[
(f'{app_label}.infantnvpadjustment')
])
class Meta:
app_label = app_label
source_model = f'{app_label}.infantvisit'
class GAD7AnxietyScreeningRuleGroup(CrfRuleGroup):
gad_anxiety_referral = CrfRule(
predicate=P('anxiety_score', 'gte', 10),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.caregivergadreferral'])
class Meta:
app_label = app_label
source_model = f'{app_label}.caregivergadanxietyscreening'
class MaternalUltrasoundInitialRuleGroup(CrfRuleGroup):
maternal_ultrasound = CrfRule(
predicate=pc.func_show_ultrasound_form,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.maternalultrasoundinitial'])
class Meta:
app_label = app_label
source_model = f'{app_label}.maternalvisit'
class QuestionnaireCrfRuleGroup(CrfRuleGroup):
viralloadtracking = CrfRule(
predicate=P('registration_type', 'eq', MASA_VL_SCHEDULED),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.viralloadtracking'])
class Meta:
source_model = f'{app_label}.questionnaire'
app_label = app_label
class HivTestingHistoryRuleGroup(CrfRuleGroup):
has_record = CrfRule(
predicate=pc.func_requires_hivtestreview,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hivtestreview'])
has_tested = CrfRule(
predicate=P('has_tested', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hivtested'])
hiv_untested = CrfRule(
predicate=pc.func_requires_hivuntested,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hivuntested'])
other_record = CrfRule(
predicate=PF(
'has_tested', 'other_record',
func=lambda x, y: True if x == YES and y == YES else False),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hivresultdocumentation'])
require_todays_hiv_result = CrfRule(
predicate=pc.func_requires_todays_hiv_result,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hivresult'])
verbal_hiv_result_hiv_care_baseline = CrfRule(
predicate=P('verbal_hiv_result', 'eq', POS),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hivcareadherence',
f'{app_label}.positiveparticipant',
f'{app_label}.hivmedicalcare',
f'{app_label}.hivhealthcarecosts'])
verbal_response = CrfRule(
predicate=P('verbal_hiv_result', 'eq', NEG),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.stigma',
f'{app_label}.stigmaopinion'])
def method_result(self):
return True
class Meta:
app_label = app_label
source_model = f'{app_label}.hivtestinghistory'
class FollowupRuleGroup(CrfRuleGroup):
death_report = CrfRule(
predicate=P("alive", "eq", NO),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=["deathreport"],
)
class Meta:
app_label = "mapitio_subject"
source_model = "followup"
class MedicalExpensesCrfRuleGroup(CrfRuleGroup):
medical_expenses = CrfRule(
predicate=P("care_before_hospital", "eq", YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f"{app_label}.medicalexpensestwo"],
)
class Meta:
app_label = app_label
source_model = f"{app_label}.medicalexpenses"
class CongenitalAnomaliesRuleGroup(CrfRuleGroup):
congenital_anomalies = CrfRule(
predicate=P('congenital_anomalities', 'eq', YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.infantcongenitalanomalies']
)
class Meta:
app_label = app_label
source_model = f'{app_label}.birthdata'
class InfantFuPhysicalRuleGroup(CrfRuleGroup):
physical_assessment_yes = CrfRule(predicate=P('physical_assessment', 'eq',
YES),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[
(f'{app_label}.infantfuphysical')
])
class Meta:
app_label = app_label
source_model = f'{app_label}.infantfu'
class KaraboTbRuleGroup(CrfRuleGroup):
require_tb_form = CrfRule(predicate=pc.func_show_karabo_tb_form,
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[
(f'{app_label}.karabotuberculosishistory')
])
class Meta:
app_label = app_label
source_model = f'{app_label}.infantvisit'
class ReproductiveRuleGroup(CrfRuleGroup):
currently_pregnant = CrfRule(
predicate=PF(
'currently_pregnant', 'menopause',
func=lambda x, y: True if x == YES or x == NOT_SURE and y == NO else False),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.pregnancy'])
non_pregnant = CrfRule(
predicate=PF(
'currently_pregnant', 'menopause',
func=lambda x, y: True if x == NO and y == NO else False),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.nonpregnancy'])
class Meta:
app_label = app_label
source_model = f'{app_label}.reproductivehealth'
class CrfRuleGroup2(BaseCrfRuleGroup):
serve_hiv_care_adherence = CrfRule(
predicate=P('verbal_hiv_result', 'eq', POS),
consequence=REQUIRED,
alternative=NOT_REQUIRED,
target_models=[f'{app_label}.hivcareadherence',
f'{app_label}.hivmedicalcare'])
class Meta:
app_label = app_label
source_model = f'{app_label}.hivtestinghistory'