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hcc.py
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hcc.py
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from enum import Enum,IntEnum
from functools import reduce
from datetime import datetime
from pyDatalog import pyDatalog
import os
pyDatalog.create_terms("""
output,Col,Val,score_em,Score,score,Scores,NE,INS,CE,institutional_score,age_range,
new_enrollee_score,community_score,Pair,Coef,coefficient,b,dc,overrides,wrap,
has_cc_that_overrides_this_one,beneficiary_has_hcc,Type,OT,beneficiary_has_cc,cc,CC,CC2,
ICD,edit,male,B,Diag,Ben,female,medicaid,age,A,old_age_entitled,new_enrollee,D,ben_hcc,
sepsis_card_resp_fail,cancer_immune,diabetes_chf,chf_copd,chf_renal,copd_card_resp_fail,
sepsis_pressure_ulcer, sepsis_artif_openings,art_openings_pressure_ulcer, diabetes_chf,
copd_asp_spec_bact_pneum,asp_spec_bact_pneum_pres_ulc, sepsis_asp_spec_bact_pneum,
schizophrenia_copd,schizophrenia_chf,schizophrenia_seizures,sex_age_range,U,L,disabled,
originally_disabled,ben_hcc,sex_age,MF,indicator,excised,beneficiary_icd,CC,B,
valid_community_variables,valid_institutional_variables,valid_new_enrollee_variables,indicator
""")
pyDatalog.create_terms("X,Y,Z")
def age_as_of(dob,date_as_of):
return date_as_of.year - dob.year - ((date_as_of.month, date_as_of.day) < (dob.month, dob.day))
class EntitlementReason(IntEnum):
OASI=0
DIB=1
ESRD=2
DIB_AND_ESRD = 3
class ICDType(IntEnum):
NINE = 9
TEN = 0
class Diagnosis(pyDatalog.Mixin):
def __init__(self,
beneficiary,
icdcode,
codetype=ICDType.NINE):
super().__init__()
self.beneficiary = beneficiary
self.icdcode = icdcode
self.codetype = codetype
def __repr__(self): # specifies how to display an Employee
return str(self.beneficiary) + str(self.icdcode) + str(self.codetype)
class Beneficiary(pyDatalog.Mixin):
def __init__(self,
hicno,sex,dob,
original_reason_entitlement=EntitlementReason.OASI,
medicaid=False,
newenrollee_medicaid=False,):
super().__init__()
self.hicno = hicno
self.sex = sex
self.dob = datetime.strptime(dob,"%Y%m%d")
self.age = age_as_of(self.dob,datetime.now())
self.medicaid = medicaid
self.newenrollee_medicaid = newenrollee_medicaid
self.original_reason_entitlement = original_reason_entitlement
self.diagnoses = []
def __repr__(self): # specifies how to display an Employee
return "ID:" + str(self.hicno) + ",DOB:" + str(self.dob)
def add_diagnosis(self,diag):
self.diagnoses.append(diag)
# lines 352 - 361
def load_diagnostic_category_facts():
diagnostic_categories = [
("cancer",["8","9","10","11","12"]),
("diabetes",["17","18","19"]),
("immune",["47"]),
("card_resp_fail",["82","83","84"]),
("chf",["85"]),
("copd",["110","111"]),
("renal",[str(x) for x in range(134,142)]),
("compl",["176"]),
("pressure_ulcer",["157","158","159","160"]),
("sepsis",["2"]) ]
for dcE, ccs in diagnostic_categories:
for ccE in ccs:
+ dc(dcE,ccE)
def load_coefficients(f):
dir = os.path.dirname(__file__)
file = open(os.path.join(dir,f), 'r')
for line in file:
vals = list(map(lambda s: s.strip(),line.split(",")))
label,coeff = vals
+ coefficient(label,float(coeff))
+ coefficient('starting',0.00)
def load_cc_facts(f,icdcodetype):
dir = os.path.dirname(__file__)
file = open(os.path.join(dir,f), 'r')
for line in file:
vals = line.split()
if len(vals) == 2:
icdE,ccE = vals
elif len(vals) == 3:
icdE,ccE,_ = vals
+ cc(icdE,ccE,icdcodetype)
def load_hcc_facts():
overriders = [
("8",["9","10","11","12" ]),
("9",["10","11","12" ]),
("10",["11","12" ]),
("11",["12" ]),
("17",["18","19" ]),
("18",["19" ]),
("27",["28","29","80" ]),
("28",["29" ]),
("46",["48" ]),
("51",["52" ]),
("54",["55" ]),
("57",["58" ]),
("70",["71","72","103","104","169" ]),
("71",["72","104","169" ]),
("72",["169" ]),
("82",["83","84" ]),
("83",["84" ]),
("86",["87","88" ]),
("87",["88" ]),
("99",["100" ]),
("103",["104" ]),
("106",["107","108","161","189" ]),
("107",["108" ]),
("110",["111","112" ]),
("111",["112" ]),
("114",["115" ]),
("134",["135","136","137","138","139","140","141"]),
("135",["136","137","138","139","140","141" ]),
("136",["137","138","139","140","141" ]),
("137",["138","139","140","141" ]),
("138",["139","140","141" ]),
("139",["140","141" ]),
("140",["141" ]),
("157",["158","159","160","161" ]),
("158",["159","160","161" ]),
("159",["160","161" ]),
("160",["161" ]),
("166",["80","167" ])
]
for overrider, overridees in overriders:
for overridee in overridees:
+ overrides(overrider,overridee)
def load_facts():
load_cc_facts("icd10.txt",0)
load_cc_facts("icd9.txt",9)
load_hcc_facts()
load_diagnostic_category_facts()
load_coefficients("coefficients.txt")
def community_regression():
# &COMM_REG
reg_vars = ["F0_34","F35_44", "F45_54", "F55_59", "F60_64", "F65_69",
"F70_74", "F75_79", "F80_84", "F85_89", "F90_94", "F95_GT",
"M0_34","M35_44", "M45_54", "M55_59", "M60_64", "M65_69",
"M70_74", "M75_79", "M80_84", "M85_89", "M90_94", "M95_GT",
"MCAID_Female_Aged","MCAID_Female_Disabled",
"MCAID_Male_Aged","MCAID_Male_Disabled",
"OriginallyDisabled_Female","OriginallyDisabled_Male",
"DISABLED_HCC6", "DISABLED_HCC34", "DISABLED_HCC46","DISABLED_HCC54",
"DISABLED_HCC55","DISABLED_HCC110", "DISABLED_HCC176", "SEPSIS_CARD_RESP_FAIL",
"CANCER_IMMUNE", "DIABETES_CHF", "CHF_COPD","CHF_RENAL", "COPD_CARD_RESP_FAIL",
"HCC1","HCC2","HCC6","HCC8","HCC9","HCC10", "HCC11", "HCC12",
"HCC17", "HCC18", "HCC19", "HCC21", "HCC22", "HCC23", "HCC27", "HCC28",
"HCC29", "HCC33", "HCC34", "HCC35", "HCC39", "HCC40", "HCC46", "HCC47",
"HCC48", "HCC51", "HCC52", "HCC54", "HCC55", "HCC57", "HCC58", "HCC70",
"HCC71", "HCC72", "HCC73", "HCC74", "HCC75", "HCC76", "HCC77", "HCC78",
"HCC79", "HCC80", "HCC82", "HCC83", "HCC84", "HCC85", "HCC86", "HCC87",
"HCC88", "HCC96", "HCC99", "HCC100","HCC103","HCC104","HCC106","HCC107",
"HCC108","HCC110","HCC111","HCC112","HCC114","HCC115","HCC122","HCC124",
"HCC134","HCC135","HCC136","HCC137","HCC138","HCC139","HCC140","HCC141",
"HCC157","HCC158","HCC159","HCC160","HCC161","HCC162","HCC166","HCC167",
"HCC169","HCC170","HCC173","HCC176","HCC186","HCC188","HCC189" ]
return reg_vars
def new_enrollee_regression():
reg_vars = ["NEF0_34","NEF35_44", "NEF45_54", "NEF55_59", "NEF60_64",
"NEF65","NEF66","NEF67","NEF68","NEF69",
"NEF70_74", "NEF75_79", "NEF80_84", "NEF85_89", "NEF90_94", "NEF95_GT",
"NEM0_34","NEM35_44", "NEM45_54", "NEM55_59", "NEM60_64",
"NEM65","NEM66","NEM67","NEM68","NEM69",
"NEM70_74", "NEM75_79", "NEM80_84", "NEM85_89", "NEM90_94", "NEM95_GT",
"MCAID_FEMALE0_64","MCAID_FEMALE65","MCAID_FEMALE66_69",
"MCAID_FEMALE70_74", "MCAID_FEMALE75_GT",
"MCAID_MALE0_64","MCAID_MALE65","MCAID_MALE66_69",
"MCAID_MALE70_74", "MCAID_MALE75_GT",
"Origdis_female65", "Origdis_female66_69",
"Origdis_female70_74","Origdis_female75_GT",
"Origdis_male65", "Origdis_male66_69",
"Origdis_male70_74","Origdis_male75_GT"]
return reg_vars
def institutional_regression():
reg_vars = ["F0_34","F35_44", "F45_54", "F55_59", "F60_64", "F65_69",
"F70_74", "F75_79", "F80_84", "F85_89", "F90_94", "F95_GT",
"M0_34","M35_44", "M45_54", "M55_59", "M60_64", "M65_69",
"M70_74", "M75_79", "M80_84", "M85_89", "M90_94", "M95_GT",
"MCAID","ORIGDS", "DISABLED_HCC85", "DISABLED_PRESSURE_ULCER",
"DISABLED_HCC161","DISABLED_HCC39", "DISABLED_HCC77", "DISABLED_HCC6",
"CHF_COPD", "COPD_CARD_RESP_FAIL", "SEPSIS_PRESSURE_ULCER", "SEPSIS_ARTIF_OPENINGS",
"ART_OPENINGS_PRESSURE_ULCER", "DIABETES_CHF", "COPD_ASP_SPEC_BACT_PNEUM", "ASP_SPEC_BACT_PNEUM_PRES_ULC",
"SEPSIS_ASP_SPEC_BACT_PNEUM", "SCHIZOPHRENIA_COPD", "SCHIZOPHRENIA_CHF", "SCHIZOPHRENIA_SEIZURES",
"HCC1","HCC2","HCC6","HCC8","HCC9","HCC10", "HCC11", "HCC12",
"HCC17", "HCC18", "HCC19", "HCC21", "HCC22", "HCC23", "HCC27", "HCC28",
"HCC29", "HCC33", "HCC34", "HCC35", "HCC39", "HCC40", "HCC46", "HCC47",
"HCC48", "HCC51", "HCC52", "HCC54", "HCC55", "HCC57", "HCC58", "HCC70",
"HCC71", "HCC72", "HCC73", "HCC74", "HCC75", "HCC76", "HCC77", "HCC78",
"HCC79", "HCC80", "HCC82", "HCC83", "HCC84", "HCC85", "HCC86", "HCC87",
"HCC88", "HCC96", "HCC99", "HCC100","HCC103","HCC104","HCC106","HCC107",
"HCC108","HCC110","HCC111","HCC112","HCC114","HCC115","HCC122","HCC124",
"HCC134","HCC135","HCC136","HCC137","HCC138","HCC139","HCC140","HCC141",
"HCC157","HCC158","HCC159","HCC160","HCC161","HCC162","HCC166","HCC167",
"HCC169","HCC170","HCC173","HCC176","HCC186","HCC188","HCC189" ]
return reg_vars
def load_rules():
Ben = Beneficiary
Diag = Diagnosis
male(B) <= (Ben.sex[B] == "male")
female(B) <= (Ben.sex[B] == "female")
medicaid(B) <= (Ben.medicaid[B] == True)
age(B,A) <= (Ben.age[B] == A)
old_age_entitled(B) <= (Ben.original_reason_entitlement[B] == EntitlementReason.OASI)
new_enrollee(B) <= (Ben.newenrollee_medicaid[B] == True)
# %* disabled;
# DISABL = (&AGEF < 65 & &OREC ne "0");
disabled(B) <= (Ben.age[B] < 65) & ~(old_age_entitled(B))
# %* originally disabled: CHANGED FIRST TIME FOR THIS SOFTWARE;
# ORIGDS = (&OREC = '1')*(DISABL = 0);
originally_disabled(B) <= (Ben.original_reason_entitlement[B] == EntitlementReason.DIB) & ~(disabled(B))
edit(ICD,9,B,"48") <= female(B) & (ICD.in_(["2860", "2861"]))
edit(ICD,9,B,"112") <= age(B,A) & (A < 18) & \
(ICD.in_(["4910", "4911", "49120", "49121", "49122",
"4918", "4919", "4920", "4928", "496",
"5181", "5182"]))
edit(ICD,0,B,"48") <= female(B) & (ICD.in_(["D66", "D67"]))
edit(ICD,0,B,"112") <= age(B,A) & (A < 18) & (ICD.in_(["J410",
"J411", "J418", "J42", "J430",
"J431", "J432", "J438", "J439", "J440",
"J441", "J449", "J982", "J983"]))
#IF &AGE < 18 AND &ICD9 IN ("49320", "49321", "49322")
# THEN CC="-1.0";
excised(ICD,9,B) <= age(B,A) & (A < 18) & (ICD.in_(["49320", "49321", "49322"]))
beneficiary_icd(B,ICD,Type) <= (Diag.beneficiary[D] == B) & (Diag.icdcode[D]==ICD) & (Diag.codetype[D]==Type)
beneficiary_has_cc(B,CC) <= beneficiary_icd(B,ICD,Type) & edit(ICD,Type,B,CC) & ~(excised(ICD,Type,B))
beneficiary_has_cc(B,CC) <= beneficiary_icd(B,ICD,Type) & \
cc(ICD,CC,Type) & ~(edit(ICD,Type,B,CC2)) & ~(excised(ICD,Type,B))
has_cc_that_overrides_this_one(B,CC) <= beneficiary_has_cc(B,OT) & overrides(OT,CC)
beneficiary_has_hcc(B,CC) <= beneficiary_has_cc(B,CC) & ~( has_cc_that_overrides_this_one(B,CC))
ben_hcc(B,CC) <= beneficiary_has_hcc(B,CC)
# lines 363 - 368
sepsis_card_resp_fail(CC,CC2) <= dc("sepsis",CC) & dc("card_resp_fail",CC2)
cancer_immune(CC,CC2) <= dc("cancer",CC) & dc("immune",CC2)
diabetes_chf(CC,CC2) <= dc("diabetes",CC) & dc("chf",CC2)
chf_copd(CC,CC2) <= dc("chf",CC) & dc("copd",CC2)
chf_renal(CC,CC2) <= dc("chf",CC) & dc("renal",CC2)
copd_card_resp_fail(CC,CC2) <= dc("copd",CC) & dc("card_resp_fail",CC2)
# PRESSURE_ULCER = MAX(HCC157, HCC158, HCC159, HCC160);
sepsis_pressure_ulcer(CC,CC2) <= dc("sepsis",CC) & dc("pressure_ulcer",CC2)
sepsis_artif_openings(CC,"188") <= dc("sepsis",CC)
art_openings_pressure_ulcer(CC,"188") <= dc("pressure_ulcer",CC)
diabetes_chf(CC,CC2) <= dc("diabetes",CC) & dc("chf",CC2)
copd_asp_spec_bact_pneum(CC,"114") <= dc("copd",CC)
asp_spec_bact_pneum_pres_ulc(CC,"114") <= dc("pressure_ulcer",CC)
sepsis_asp_spec_bact_pneum(CC,"114") <= dc("sepsis",CC)
schizophrenia_copd(CC,"57") <= dc("copd",CC)
schizophrenia_chf(CC,"57") <= dc("chf",CC)
schizophrenia_seizures("79",CC) <= (CC == "57")
# these predicates will be used to generate
# more specific predicates like "F0_34"
age_range(B,L,U) <= age(B,A) & (A <= U) & (A > L)
age_range(B,L,-1.0) <= age(B,A) & (A > L)
sex_age_range("male",B,L,U) <= male(B) & age_range(B,L,U)
sex_age_range("female",B,L,U) <= female(B) & age_range(B,L,U)
sex_age(MF,B,A) <= sex_age_range(MF,B,(A+1),A)
indicator(B,'ART_OPENINGS_PRESSURE_ULCER') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & art_openings_pressure_ulcer(CC,CC2)
indicator(B,'ASP_SPEC_BACT_PNEUM_PRES_ULC') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & asp_spec_bact_pneum_pres_ulc(CC,CC2)
indicator(B,'CANCER_IMMUNE') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & cancer_immune(CC,CC2)
indicator(B,'CHF_COPD') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & chf_copd(CC,CC2)
indicator(B,'CHF_RENAL') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & chf_renal(CC,CC2)
indicator(B,'COPD_ASP_SPEC_BACT_PNEUM') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & copd_asp_spec_bact_pneum(CC,CC2)
indicator(B,'COPD_CARD_RESP_FAIL') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & copd_card_resp_fail(CC,CC2)
indicator(B,'DIABETES_CHF') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & diabetes_chf(CC,CC2)
indicator(B,'DISABLED_HCC110') <= ben_hcc(B,'110') & disabled(B)
indicator(B,'DISABLED_HCC161') <= ben_hcc(B,'161') & disabled(B)
indicator(B,'DISABLED_HCC176') <= ben_hcc(B,'176') & disabled(B)
indicator(B,'DISABLED_HCC34') <= ben_hcc(B,'34') & disabled(B)
indicator(B,'DISABLED_HCC39') <= ben_hcc(B,'39') & disabled(B)
indicator(B,'DISABLED_HCC46') <= ben_hcc(B,'46') & disabled(B)
indicator(B,'DISABLED_HCC54') <= ben_hcc(B,'54') & disabled(B)
indicator(B,'DISABLED_HCC55') <= ben_hcc(B,'55') & disabled(B)
indicator(B,'DISABLED_HCC6') <= ben_hcc(B,'6') & disabled(B)
indicator(B,'DISABLED_HCC77') <= ben_hcc(B,'77') & disabled(B)
indicator(B,'DISABLED_HCC85') <= ben_hcc(B,'85') & disabled(B)
indicator(B,'DISABLED_PRESSURE_ULCER') <= ben_hcc(B,CC) & dc(CC,'pressure_ulcer') & disabled(B)
indicator(B,'F0_34') <= sex_age_range('female',B,0,34)
indicator(B,'F35_44') <= sex_age_range('female',B,35,44)
indicator(B,'F45_54') <= sex_age_range('female',B,45,54)
indicator(B,'F55_59') <= sex_age_range('female',B,55,59)
indicator(B,'F60_64') <= sex_age_range('female',B,60,64)
indicator(B,'F65_69') <= sex_age_range('female',B,65,69)
indicator(B,'F70_74') <= sex_age_range('female',B,70,74)
indicator(B,'F75_79') <= sex_age_range('female',B,75,79)
indicator(B,'F80_84') <= sex_age_range('female',B,80,84)
indicator(B,'F85_89') <= sex_age_range('female',B,85,89)
indicator(B,'F90_94') <= sex_age_range('female',B,90,94)
indicator(B,'F95_GT') <= sex_age_range('female',B,95,-1.0)
hccees = [
'100', '103', '104', '106', '107', '108', '10', '110', '111', '112', '114', '115',
'11', '122', '124', '12', '134', '135', '136', '137', '138', '139', '140', '141',
'157', '158', '159', '160', '161', '162', '166', '167', '169', '170', '173', '176',
'17', '186', '188', '189', '18', '19', '1', '21', '22', '23', '27', '28', '29', '2',
'33', '34', '35', '39', '40', '46', '47', '48', '51', '52', '54', '55', '57', '58',
'6', '70', '71', '72', '73', '74', '75', '76', '77', '78', '79', '80', '82', '83',
'84', '85', '86', '87', '88', '8', '96', '99', '9']
for i in hccees:
indicator(B,'HCC' + i ) <= ben_hcc(B,i)
indicator(B,'M0_34') <= sex_age_range('male',B,0,34)
indicator(B,'M35_44') <= sex_age_range('male',B,35,44)
indicator(B,'M45_54') <= sex_age_range('male',B,45,54)
indicator(B,'M55_59') <= sex_age_range('male',B,55,59)
indicator(B,'M60_64') <= sex_age_range('male',B,60,64)
indicator(B,'M65_69') <= sex_age_range('male',B,65,69)
indicator(B,'M70_74') <= sex_age_range('male',B,70,74)
indicator(B,'M75_79') <= sex_age_range('male',B,75,79)
indicator(B,'M80_84') <= sex_age_range('male',B,80,84)
indicator(B,'M85_89') <= sex_age_range('male',B,85,89)
indicator(B,'M90_94') <= sex_age_range('male',B,90,94)
indicator(B,'M95_GT') <= sex_age_range('male',B,95,-1.0)
# THESE NEED TO CHANGE
indicator(B,'MCAID_FEMALE0_64') <= medicaid(B) & sex_age_range('female',B,0,64)
indicator(B,'MCAID_FEMALE65') <= medicaid(B) & sex_age('female',B,65)
indicator(B,'MCAID_FEMALE66_69') <= medicaid(B) & sex_age_range('female',B,66,69)
indicator(B,'MCAID_FEMALE70_74') <= medicaid(B) & sex_age_range('female',B,70,74)
indicator(B,'MCAID_FEMALE75_GT') <= medicaid(B) & sex_age_range('female',B,75,-1.0)
indicator(B,'MCAID_Female_Aged') <= medicaid(B) & ~disabled(B) & female(B)
indicator(B,'MCAID_Female_Disabled') <= medicaid(B) & disabled(B) & female(B)
indicator(B,'MCAID') <= medicaid(B)
indicator(B,'MCAID_MALE0_64') <= medicaid(B) & sex_age_range('male',B,0,64)
indicator(B,'MCAID_MALE65') <= medicaid(B) & sex_age('male',B,65)
indicator(B,'MCAID_MALE66_69') <= medicaid(B) & sex_age_range('male',B,66,69)
indicator(B,'MCAID_MALE70_74') <= medicaid(B) & sex_age_range('male',B,70,74)
indicator(B,'MCAID_MALE75_GT') <= medicaid(B) & sex_age_range('male',B,75,-1.0)
indicator(B,'MCAID_Male_Aged') <= medicaid(B) & ~disabled(B) & male(B)
indicator(B,'MCAID_Male_Disabled') <= medicaid(B) & disabled(B) & male(B)
# -- UNTIL HERE... need to add NEF65 indicator stuff instead of sex_age_range
indicator(B,'NEM0_34') <= sex_age_range("male",B,0,34)
indicator(B,'NEM35_44') <= sex_age_range("male",B,35,44)
indicator(B,'NEM45_54') <= sex_age_range("male",B,45,54)
indicator(B,'NEM55_59') <= sex_age_range("male",B,55,59)
indicator(B,'NEM60_64') <= sex_age_range("male",B,60,63)
# WHEN(&SEX='2' & &AGEF=64 & &OREC NE '0') NE_AGESEX = 5;
# WHEN(&SEX='2' & &AGEF=64 & &OREC='0') NE_AGESEX = 6;
indicator(B,'NEM60_64') <= sex_age("male",B,64) & ~(old_age_entitled(B))
indicator(B,'NEM65') <= sex_age("male",B,64) & old_age_entitled(B)
indicator(B,'NEM65') <= sex_age("male",B,65)
indicator(B,'NEM66') <= sex_age("male",B,66)
indicator(B,'NEM67') <= sex_age("male",B,67)
indicator(B,'NEM68') <= sex_age("male",B,68)
indicator(B,'NEM69') <= sex_age("male",B,69)
indicator(B,'NEM70_74') <= sex_age_range("male",B,70,74)
indicator(B,'NEM75_79') <= sex_age_range("male",B,75,79)
indicator(B,'NEM80_84') <= sex_age_range("male",B,80,84)
indicator(B,'NEM85_89') <= sex_age_range("male",B,85,89)
indicator(B,'NEM90_94') <= sex_age_range("male",B,90,94)
indicator(B,'NEM95_GT') <= sex_age_range("male",B,95,-1.0)
indicator(B,'NEF0_34') <= sex_age_range("female",B,0,34)
indicator(B,'NEF35_44') <= sex_age_range("female",B,35,44)
indicator(B,'NEF45_54') <= sex_age_range("female",B,45,54)
indicator(B,'NEF55_59') <= sex_age_range("female",B,55,59)
indicator(B,'NEF60_64') <= sex_age_range("female",B,60,63)
# WHEN(&SEX='2' & &AGEF=64 & &OREC NE '0') NE_AGESEX = 5;
# WHEN(&SEX='2' & &AGEF=64 & &OREC='0') NE_AGESEX = 6;
indicator(B,'NEF60_64') <= sex_age("female",B,64) & ~(old_age_entitled(B))
indicator(B,'NEF65') <= sex_age("female",B,64) & old_age_entitled(B)
indicator(B,'NEF65') <= sex_age("female",B,65)
indicator(B,'NEF66') <= sex_age("female",B,66)
indicator(B,'NEF67') <= sex_age("female",B,67)
indicator(B,'NEF68') <= sex_age("female",B,68)
indicator(B,'NEF69') <= sex_age("female",B,69)
indicator(B,'NEF70_74') <= sex_age_range("female",B,70,74)
indicator(B,'NEF75_79') <= sex_age_range("female",B,75,79)
indicator(B,'NEF80_84') <= sex_age_range("female",B,80,84)
indicator(B,'NEF85_89') <= sex_age_range("female",B,85,89)
indicator(B,'NEF90_94') <= sex_age_range("female",B,90,94)
indicator(B,'NEF95_GT') <= sex_age_range("female",B,95,-1.0)
indicator(B,'Origdis_female65') <= originally_disabled(B) & indicator(B, 'NEF65')
indicator(B,'Origdis_female66_69') <= originally_disabled(B) & indicator(B, 'NEF66')
indicator(B,'Origdis_female66_69') <= originally_disabled(B) & indicator(B, 'NEF67')
indicator(B,'Origdis_female66_69') <= originally_disabled(B) & indicator(B, 'NEF68')
indicator(B,'Origdis_female66_69') <= originally_disabled(B) & indicator(B, 'NEF69')
indicator(B,'Origdis_female70_74') <= originally_disabled(B) & indicator(B, 'NEF70_74')
indicator(B,'Origdis_female75_GT') <= originally_disabled(B) & sex_age_range("female",B,74,-1.0)
indicator(B,'Origdis_male65') <= originally_disabled(B) & indicator(B, 'NEM65')
indicator(B,'Origdis_male66_69') <= originally_disabled(B) & indicator(B, 'NEM66')
indicator(B,'Origdis_male66_69') <= originally_disabled(B) & indicator(B, 'NEM67')
indicator(B,'Origdis_male66_69') <= originally_disabled(B) & indicator(B, 'NEM68')
indicator(B,'Origdis_male66_69') <= originally_disabled(B) & indicator(B, 'NEM69')
indicator(B,'Origdis_male70_74') <= originally_disabled(B) & indicator(B, 'NEM70_74')
indicator(B,'Origdis_male75_GT') <= originally_disabled(B) & sex_age_range("male",B,74,-1.0)
indicator(B,'ORIGDS') <= originally_disabled(B)
indicator(B,'OriginallyDisabled_Female') <= originally_disabled(B) & female(B)
indicator(B,'OriginallyDisabled_Male') <= originally_disabled(B) & male(B)
indicator(B,'SCHIZOPHRENIA_CHF') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & schizophrenia_chf(CC,CC2)
indicator(B,'SCHIZOPHRENIA_COPD') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & schizophrenia_copd(CC,CC2)
indicator(B,'SCHIZOPHRENIA_SEIZURES') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & schizophrenia_seizures(CC,CC2)
indicator(B,'SEPSIS_ARTIF_OPENINGS') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & sepsis_artif_openings(CC,CC2)
indicator(B,'SEPSIS_ASP_SPEC_BACT_PNEUM') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & sepsis_asp_spec_bact_pneum(CC,CC2)
indicator(B,'SEPSIS_CARD_RESP_FAIL') <= ben_hcc(B,CC) & ben_hcc(B,CC2) & sepsis_card_resp_fail(CC,CC2)
# the following 3 lines are plain python
cvars = community_regression()
ivars = institutional_regression()
nevars = new_enrollee_regression()
allvars = list(set().union(cvars,ivars,nevars))
(valid_community_variables[B] == concat_(CC,key=CC,sep=',')) <= indicator(B,CC) & CC.in_(cvars)
(valid_institutional_variables[B] == concat_(CC,key=CC,sep=',')) <= indicator(B,CC) & CC.in_(ivars)
(valid_new_enrollee_variables[B] == concat_(CC,key=CC,sep=',')) <= indicator(B,CC) & CC.in_(nevars)
(new_enrollee_score[B] == sum_(Coef,key=Coef)) <= indicator(B,CC) \
& CC.in_(nevars) & coefficient("NE_"+CC,Coef)
(institutional_score[B] == sum_(Coef,key=Coef)) <= indicator(B,CC) \
& CC.in_(ivars) & coefficient("INS_"+CC,Coef)
(community_score[B] == sum_(Coef,key=Coef)) <= indicator(B,CC) \
& CC.in_(cvars) & coefficient("CE_"+CC,Coef)
score(B,"community",Score) <= (community_score[B] == Score)
score(B,"institutional",Score) <= (institutional_score[B] == Score)
score(B,"new_enrollee",Score) <= (new_enrollee_score[B] == Score)
output(B,Col,Val) <= score(B,Col,Val)
output(B,Col,0) <= Col.in_(allvars) & ~(indicator(B,Col))
output(B,Col,1) <= indicator(B,Col)
output(B,"sex",Val) <= (Ben.sex[B]==Val)
output(B,"age",Val) <= age(B,Val)
load_facts()
load_rules()
####################################################
jane = Beneficiary(2,"female","19740824",EntitlementReason.DIB,True)
jane.add_diagnosis(Diagnosis(jane,"D66",ICDType.TEN))
jane.add_diagnosis(Diagnosis(jane,"C182",ICDType.TEN))
daniel = Beneficiary(1,"male","19740824",EntitlementReason.DIB)
daniel.add_diagnosis(Diagnosis(daniel,"A0223",ICDType.TEN)) # 51
daniel.add_diagnosis(Diagnosis(daniel,"A0224",ICDType.TEN)) # 52
daniel.add_diagnosis(Diagnosis(daniel,"D66",ICDType.TEN))
daniel.add_diagnosis(Diagnosis(daniel,"C163",ICDType.TEN))
daniel.add_diagnosis(Diagnosis(daniel,"C163",ICDType.TEN))
daniel.add_diagnosis(Diagnosis(daniel,"C182",ICDType.TEN))
daniel.add_diagnosis(Diagnosis(daniel,"C800",ICDType.TEN))
daniel.add_diagnosis(Diagnosis(daniel,"A072",ICDType.TEN))
bob = Beneficiary(3,"male","20040824",EntitlementReason.DIB,True)
bob.add_diagnosis(Diagnosis(bob,"A0223",ICDType.TEN))
bob.add_diagnosis(Diagnosis(bob,"A0224",ICDType.TEN))
jacob = Beneficiary(4,"male","1940824",EntitlementReason.DIB,True)
antonio = Beneficiary(3,"male","20040824",EntitlementReason.DIB,True)
antonio.add_diagnosis(Diagnosis(antonio,"A0223",ICDType.TEN))
antonio.add_diagnosis(Diagnosis(antonio,"49320",ICDType.NINE))
john = Beneficiary(5,"male","19920824",EntitlementReason.DIB,True)
john.add_diagnosis(Diagnosis(john,"A0223",ICDType.TEN))
john.add_diagnosis(Diagnosis(john,"49320",ICDType.NINE))
####################################################