def __init__(self):
self.config = natus_config.NATUSConfig('ncqa')
self.log = natus_logging.NATUSLogging(self.__class__.__name__,
logging.INFO)
self.mmdf_file_glob = glob.glob(
self.config.read_value('setup', 'mmdf.input.filename.regex'))
self.mmdf = {}
def __init__(self):
self.log = natus_logging.NATUSLogging(self.__class__.__name__,
logging.INFO)
self.config = natus_config.NATUSConfig('ncqa')
self.db_con = connector.Connector()
self.member_filter = {}
# self.load_filter()
self.value_set_cache = {}
def __init__(self):
self.log = natus_logging.NATUSLogging(self.__class__.__name__, logging.INFO)
self.config = natus_config.NATUSConfig('ncqa')
self.dbname = self.config.read_value('db', 'mongodb.db.name')
self.url = self.config.read_value('db', 'mongodb.url')
self.log.info('Connecting to mongodb. db: ' + self.dbname + ', url: ' + self.url)
self.client = pymongo.MongoClient(self.url)
self.db = self.client[self.dbname]
def __init__(self):
self.log = natus_logging.NATUSLogging(self.__class__.__name__,
logging.INFO)
self.config = natus_config.NATUSConfig('ncqa')
self.db_connection = connector.Connector()
self.bulk_size = self.config.read_value('load', 'bulk.size')
self.input_file_name = self.config.read_value('load', 'input.filename')
self.documents = []
def __init__(self):
self.log = natus_logging.NATUSLogging(self.__class__.__name__,
logging.INFO)
self.config = natus_config.NATUSConfig('ncqa')
self.db_con = connector.Connector()
self.db_con.collection_name = 'measure_to_oid'
self.excel_sheetname = self.config.read_value(
'valueset', 'excel.measures.valuesets.sheet.name')
self.excel_filename = self.config.read_value('valueset',
'excel.filename')
def __init__(self, run_date: datetime):
config = natus_config.NATUSConfig('ncqa')
config_section_name = self.__class__.__name__
self.log = natus_logging.NATUSLogging(config_section_name,
logging.INFO)
self.run_date = run_date
measures = json.loads(
config.read_value(config_section_name, 'measures'))
self.db_con = connector.Connector()
self.measure_pipeline = self.init_measures(measures)
def __init__(self):
self.log = natus_logging.NATUSLogging(self.__class__.__name__,
logging.INFO)
self.config = natus_config.NATUSConfig('ncqa')
self.db_con = connector.Connector()
self.db_con.collection_name = 'code_to_description'
self.excel_sheetname = self.config.read_value('valueset',
'excel.sheetname')
self.excel_filename = self.config.read_value('valueset',
'excel.filename')
self.cpt_input_file = self.config.read_value('cms', 'cpt_input_file')
def __init__(self):
self.log = natus_logging.NATUSLogging(self.__class__.__name__, logging.INFO)
self.config = natus_config.NATUSConfig('ncqa')
self.merged_member_filename = self.config.read_value('merge', 'merged.member.filename')
self.members_input_filename = self.config.read_value('merge', 'members.input.filename')
self.filter_output_filename = self.config.read_value('merge', 'filter.output.filename')
self.run_date = datetime.now()
self.enrollments = {}
self.visits = {}
self.providers = {}
self.pharm = {}
self.mmdf = {}
def vs_to_codes():
from util import natus_config
import pandas as pd
from model.code import Code
from model.valueset import ValueSet
from db.mongo import connector
import json
config = natus_config.NATUSConfig('ncqa')
excel_filename = config.read_value('valueset', 'excel_filename')
sheet_name = config.read_value('valueset', 'excel_sheet_name')
print('Reading ' + excel_filename)
df = pd.read_excel(
excel_filename,
sheet_name=sheet_name
)
print('Processing ' + sheet_name)
value_set_info = None
codes_processed = set()
db_con = connector.Connector()
for index, row in df.iterrows():
vs_name = row['Value Set Name']
code = row['Code']
code_system = row['Code System']
code_system_oid = row['Code System OID']
code_info = Code(code, code_system, code_system_oid)
if vs_name not in codes_processed:
if len(codes_processed) > 0:
db_con.insert(vars(value_set_info), 'vs_to_codes')
codes_processed.add(vs_name)
vs_oid = row['Value Set OID']
value_set_info = ValueSet(vs_name, vs_oid, [vars(code_info)])
else:
value_set_info.codes.append(vars(code_info))
def __init__(self,
logger_name: str,
level: int,
destination: int = DESTINATION_PY_LOGGING):
from fluent import handler
self.config = natus_config.NATUSConfig('ncqa')
self.destination = destination
self.log = logging.getLogger(logger_name)
self.log.setLevel(level)
if self.destination == DESTINATION_PY_LOGGING:
ch = logging.StreamHandler()
formatter = logging.Formatter(
self.config.read_value('log', 'py.log.format'))
ch.setFormatter(formatter)
self.log.addHandler(ch)
elif self.destination == DESTINATION_FLUENTD_MONGODB:
self.handler = handler.FluentHandler(
logger_name,
host=self.config.read_value('log', 'fluentd.hostname'),
port=int(self.config.read_value('log',
'fluentd.forward.port')),
)
custom_format = {
'host': '%(hostname)s',
'where': '%(module)s.%(funcName)s',
'type': '%(levelname)s',
'stack_trace': '%(exc_text)s'
}
formatter = handler.FluentRecordFormatter(custom_format)
self.handler.setFormatter(formatter)
self.log.addHandler(self.handler)
else:
print('Unrecognized log destination')
raise ValueError
def __init__(self, run_date: datetime, connection: connector.Connector):
from util import natus_util
from pandas import date_range
config = natus_config.NATUSConfig('ncqa')
# shorthand notation
config_section_name = self.__class__.__name__
# self.codes = natus_util.measure_to_codes(config_section_name, connection)
self.anchor_date = eval(
config.read_value(config_section_name, 'anchor_date'))
continuous_enrollment_config = eval(
config.read_value(config_section_name, "continuous.enrollment"))
self.measurement_year_date_range = eval(
config.read_value(config_section_name,
'measurement_year_date_range'))
self.prior_measurement_year_date_range = eval(
config.read_value(config_section_name,
'prior_measurement_year_date_range'))
self.continuous_enrollment = natus_util.continuous_enrollment(
continuous_enrollment_config)
self.age_rule = config.read_value(config_section_name, 'age_rule')
self.eligible_date_range = eval(
config.read_value(config_section_name, 'date_range'))
self.ce_date_ranges = eval(
config.read_value(config_section_name, 'ce_date_ranges'))
self.ce_allowable_gaps = eval(
config.read_value(config_section_name, 'ce_allowable_gaps'))
self.ce_year_to_idx = eval(
config.read_value(config_section_name, 'ce_year_to_idx'))
self.outpatient = connection.find('vs_name', 'Outpatient',
'vs_to_codes')['codes']
# intersection with visit codes
self.outpatient_codes = set([x['code'] for x in self.outpatient])
self.observation = connection.find('vs_name', 'Observation',
'vs_to_codes')['codes']
self.observation_codes = set([x['code'] for x in self.observation])
self.frailty = connection.find('vs_name', 'Frailty',
'vs_to_codes')['codes']
self.frailty_codes = [x['code'] for x in self.frailty]
self.non_acute_inpatient = connection.find('vs_name',
'Nonacute Inpatient',
'vs_to_codes')['codes']
self.non_acute_inpatient_codes = set(
[x['code'] for x in self.non_acute_inpatient])
self.acute_inpatient = connection.find('vs_name', 'Acute Inpatient',
'vs_to_codes')['codes']
self.acute_inpatient_codes = set(
[x['code'] for x in self.acute_inpatient])
self.advanced_illness = connection.find('vs_name', 'Advanced Illness',
'vs_to_codes')['codes']
self.advanced_illness_codes = set(
[x['code'] for x in self.advanced_illness])
self.ed = connection.find('vs_name', 'ED', 'vs_to_codes')['codes']
self.ed_codes = set([x['code'] for x in self.ed])
self.bilateral_mastectomy = connection.find('vs_name',
'Bilateral Mastectomy',
'vs_to_codes')['codes']
self.bilateral_mastectomy_codes = [
x['code'] for x in self.bilateral_mastectomy
]
self.unilateral_mastectomy = connection.find('vs_name',
'Unilateral Mastectomy',
'vs_to_codes')['codes']
self.unilateral_mastectomy_codes = [
x['code'] for x in self.unilateral_mastectomy
]
self.bilateral_modifier = connection.find('vs_name',
'Bilateral Modifier',
'vs_to_codes')['codes']
self.right_modifier = connection.find('vs_name', 'Right Modifier',
'vs_to_codes')['codes']
self.left_modifier = connection.find('vs_name', 'Left Modifier',
'vs_to_codes')['codes']
self.history_of_bilateral_mastectomy = connection.find(
'vs_name', 'History of Bilateral Mastectomy',
'vs_to_codes')['codes']
self.history_of_bilateral_mastectomy_codes = [
x['code'] for x in self.history_of_bilateral_mastectomy
]
self.absence_of_right_breast = connection.find(
'vs_name', 'Absence of Right Breast', 'vs_to_codes')['codes']
self.absence_of_left_breast = connection.find(
'vs_name', 'Absence of Left Breast', 'vs_to_codes')['codes']
self.unilateral_mastectomy_right = connection.find(
'vs_name', 'Unilateral Mastectomy Right', 'vs_to_codes')['codes']
self.unilateral_mastectomy_right_codes = set(
[x['code'] for x in self.unilateral_mastectomy_right])
self.unilateral_mastectomy_left = connection.find(
'vs_name', 'Unilateral Mastectomy Left', 'vs_to_codes')['codes']
self.unilateral_mastectomy_left_codes = set(
[x['code'] for x in self.unilateral_mastectomy_left])
def __init__(self):
self.config = natus_config.NATUSConfig('ncqa')
self.log = natus_logging.NATUSLogging(self.__class__.__name__,
logging.INFO)
def __init__(self):
self.log = natus_logging.NATUSLogging(__class__.__name__, logging.INFO)
self.config = natus_config.NATUSConfig('ncqa')
self.db_con = connector.Connector()
self.input_filename = self.config.read_value('ndc',
'input.csv.filename')
