Here is the promised list of extracted notes for each report.
–000. PERSON statistics
–100. OBSERVATION_PERIOD (joined to PERSON)
–200- VISIT_OCCURRENCE
–300- PROVIDER
–400- CONDITION_OCCURRENCE
–500- DEATH
–600- PROCEDURE_OCCURRENCE
–700- DRUG_EXPOSURE
–800- OBSERVATION
–900- DRUG_ERA
–1000- CONDITION_ERA
–1100- LOCATION
–1200- CARE_SITE
–1300- ORGANIZATION
–1400- PAYOR_PLAN_PERIOD
–1500- DRUG_COST
–1600- PROCEDURE_COST
–1700- COHORT
–{0
– 0 Number of persons
–{1
– 1 Number of persons
–{2
– 2 Number of persons by gender
–{3
– 3 Number of persons by year of birth
–{4
– 4 Number of persons by race
–{5
– 5 Number of persons by ethnicity
–{7
– 7 Number of persons with invalid provider_id
–{8
– 8 Number of persons with invalid location_id
–{9
– 9 Number of persons with invalid care_site_id
–{101
– 101 Number of persons by age, with age at first observation period
–{102
– 102 Number of persons by gender by age, with age at first observation period
–{103
– 103 Distribution of age at first observation period
–{104
– 104 Distribution of age at first observation period by gender
–{105
– 105 Length of observation (days) of first observation period
–{106
– 106 Length of observation (days) of first observation period by gender
–{107
– 107 Length of observation (days) of first observation period by age decile
–{108
– 108 Number of persons by length of observation period, in 30d increments
–{109
– 109 Number of persons with continuous observation in each year
– Note: using temp table instead of nested query because this gives vastly improved performance in Oracle
USE @results_schema; --Set to result schema so temp tables are created where user has write rights (Oracle)
IF OBJECT_ID(‘temp_dates’, ‘U’) IS NOT NULL --This should only do something in Oracle
–{110
– 110 Number of persons with continuous observation in each month
– Note: using temp table instead of nested query because this gives vastly improved performance in Oracle
USE @results_schema; --Set to result schema so temp tables are created where user has write rights (Oracle)
IF OBJECT_ID(‘temp_dates’, ‘U’) IS NOT NULL --This should only do something in Oracle
–{111
– 111 Number of persons by observation period start month
–{112
– 112 Number of persons by observation period end month
–{113
– 113 Number of persons by number of observation periods
–{114
– 114 Number of persons with observation period before year-of-birth
–{115
– 115 Number of persons with observation period end < start
–{116
– 116 Number of persons with at least one day of observation in each year by gender and age decile
–{117
– 117 Number of persons with at least one day of observation in each year by gender and age decile
–{200
– 200 Number of persons with at least one visit occurrence, by visit_concept_id
–{201
– 201 Number of visit occurrence records, by visit_concept_id
–{202
– 202 Number of persons by visit occurrence start month, by visit_concept_id
–{203
– 203 Number of distinct visit occurrence concepts per person
–{204
– 204 Number of persons with at least one visit occurrence, by visit_concept_id by calendar year by gender by age decile
–{206
– 206 Distribution of age by visit_concept_id
–{207
–207 Number of visit records with invalid person_id
–{208
–208 Number of visit records outside valid observation period
–{209
–209 Number of visit records with end date < start date
–{210
–210 Number of visit records with invalid care_site_id
–{211
– 211 Distribution of length of stay by visit_concept_id
–{220
– 220 Number of visit occurrence records by condition occurrence start month
–{300
– 300 Number of providers
–{301
– 301 Number of providers by specialty concept_id
–{302
– 302 Number of providers with invalid care site id
–{400
– 400 Number of persons with at least one condition occurrence, by condition_concept_id
–{401
– 401 Number of condition occurrence records, by condition_concept_id
–{402
– 402 Number of persons by condition occurrence start month, by condition_concept_id
–{403
– 403 Number of distinct condition occurrence concepts per person
–{404
– 404 Number of persons with at least one condition occurrence, by condition_concept_id by calendar year by gender by age decile
–{405
– 405 Number of condition occurrence records, by condition_concept_id by condition_type_concept_id
–{406
– 406 Distribution of age by condition_concept_id
–{409
– 409 Number of condition occurrence records with invalid person_id
–{410
– 410 Number of condition occurrence records outside valid observation period
–{411
– 411 Number of condition occurrence records with end date < start date
–{412
– 412 Number of condition occurrence records with invalid provider_id
–{413
– 413 Number of condition occurrence records with invalid visit_id
–{420
– 420 Number of condition occurrence records by condition occurrence start month
–{500
– 500 Number of persons with death, by cause_of_death_concept_id
–{501
– 501 Number of records of death, by cause_of_death_concept_id
–{502
– 502 Number of persons by condition occurrence start month
–{504
– 504 Number of persons with a death, by calendar year by gender by age decile
–{505
– 505 Number of death records, by death_type_concept_id
–{506
– 506 Distribution of age by condition_concept_id
–{509
– 509 Number of death records with invalid person_id
–{510
– 510 Number of death records outside valid observation period
–{511
– 511 Distribution of time from death to last condition
–{512
– 512 Distribution of time from death to last drug
–{513
– 513 Distribution of time from death to last visit
–{514
– 514 Distribution of time from death to last procedure
–{515
– 515 Distribution of time from death to last observation
–{600
– 600 Number of persons with at least one procedure occurrence, by procedure_concept_id
–{601
– 601 Number of procedure occurrence records, by procedure_concept_id
–{602
– 602 Number of persons by procedure occurrence start month, by procedure_concept_id
–{603
– 603 Number of distinct procedure occurrence concepts per person
–{604
– 604 Number of persons with at least one procedure occurrence, by procedure_concept_id by calendar year by gender by age decile
–{605
– 605 Number of procedure occurrence records, by procedure_concept_id by procedure_type_concept_id
–{606
– 606 Distribution of age by procedure_concept_id
–{609
– 609 Number of procedure occurrence records with invalid person_id
–{610
– 610 Number of procedure occurrence records outside valid observation period
–{612
– 612 Number of procedure occurrence records with invalid provider_id
–{613
– 613 Number of procedure occurrence records with invalid visit_id
–{620
– 620 Number of procedure occurrence records by condition occurrence start month
–{700
– 700 Number of persons with at least one drug occurrence, by drug_concept_id
–{701
– 701 Number of drug occurrence records, by drug_concept_id
–{702
– 702 Number of persons by drug occurrence start month, by drug_concept_id
–{703
– 703 Number of distinct drug exposure concepts per person
–{704
– 704 Number of persons with at least one drug occurrence, by drug_concept_id by calendar year by gender by age decile
–{705
– 705 Number of drug occurrence records, by drug_concept_id by drug_type_concept_id
–{706
– 706 Distribution of age by drug_concept_id
–{709
– 709 Number of drug exposure records with invalid person_id
–{710
– 710 Number of drug exposure records outside valid observation period
–{711
– 711 Number of drug exposure records with end date < start date
–{712
– 712 Number of drug exposure records with invalid provider_id
–{713
– 713 Number of drug exposure records with invalid visit_id
–{715
– 715 Distribution of days_supply by drug_concept_id
–{716
– 716 Distribution of refills by drug_concept_id
–{717
– 717 Distribution of quantity by drug_concept_id
–{720
– 720 Number of drug exposure records by condition occurrence start month
–{800
– 800 Number of persons with at least one observation occurrence, by observation_concept_id
–{801
– 801 Number of observation occurrence records, by observation_concept_id
–{802
– 802 Number of persons by observation occurrence start month, by observation_concept_id
–{803
– 803 Number of distinct observation occurrence concepts per person
–{804
– 804 Number of persons with at least one observation occurrence, by observation_concept_id by calendar year by gender by age decile
–{805
– 805 Number of observation occurrence records, by observation_concept_id by observation_type_concept_id
–{806
– 806 Distribution of age by observation_concept_id
–{807
– 807 Number of observation occurrence records, by observation_concept_id and unit_concept_id
–{809
– 809 Number of observation records with invalid person_id
–{810
– 810 Number of observation records outside valid observation period
–{812
– 812 Number of observation records with invalid provider_id
–{813
– 813 Number of observation records with invalid visit_id
–{814
– 814 Number of observation records with no value (numeric, string, or concept)
–{815
– 815 Distribution of numeric values, by observation_concept_id and unit_concept_id
–{816
– 816 Distribution of low range, by observation_concept_id and unit_concept_id
–{817
– 817 Distribution of high range, by observation_concept_id and unit_concept_id
–{818
– 818 Number of observation records below/within/above normal range, by observation_concept_id and unit_concept_id
–{820
– 820 Number of observation records by condition occurrence start month
–{900
– 900 Number of persons with at least one drug occurrence, by drug_concept_id
–{901
– 901 Number of drug occurrence records, by drug_concept_id
–{902
– 902 Number of persons by drug occurrence start month, by drug_concept_id
–{903
– 903 Number of distinct drug era concepts per person
–{904
– 904 Number of persons with at least one drug occurrence, by drug_concept_id by calendar year by gender by age decile
–{906
– 906 Distribution of age by drug_concept_id
–{907
– 907 Distribution of drug era length, by drug_concept_id
–{908
– 908 Number of drug eras with invalid person
–{909
– 909 Number of drug eras outside valid observation period
–{910
– 910 Number of drug eras with end date < start date
–{920
– 920 Number of drug era records by drug era start month
–{1000
– 1000 Number of persons with at least one condition occurrence, by condition_concept_id
–{1001
– 1001 Number of condition occurrence records, by condition_concept_id
–{1002
– 1002 Number of persons by condition occurrence start month, by condition_concept_id
–{1003
– 1003 Number of distinct condition era concepts per person
–{1004
– 1004 Number of persons with at least one condition occurrence, by condition_concept_id by calendar year by gender by age decile
–{1006
– 1006 Distribution of age by condition_concept_id
–{1007
– 1007 Distribution of condition era length, by condition_concept_id
–{1008
– 1008 Number of condition eras with invalid person
–{1009
– 1009 Number of condition eras outside valid observation period
–{1010
– 1010 Number of condition eras with end date < start date
–{1020
– 1020 Number of drug era records by drug era start month
–{1100
– 1100 Number of persons by location 3-digit zip
–{1101
– 1101 Number of persons by location state
–{1102
– 1102 Number of care sites by location 3-digit zip
–{1103
– 1103 Number of care sites by location state
–{1200
– 1200 Number of persons by place of service
–{1201
– 1201 Number of visits by place of service
–{1202
– 1202 Number of care sites by place of service
–{1300
– 1300 Number of organizations by place of service
–{1406
– 1406 Length of payer plan (days) of first payer plan period by gender
–{1407
– 1407 Length of payer plan (days) of first payer plan period by age decile
–{1408
– 1408 Number of persons by length of payer plan period, in 30d increments
–{1409
– 1409 Number of persons with continuous payer plan in each year
– Note: using temp table instead of nested query because this gives vastly improved
USE @results_schema; --Set to result schema so temp tables are created where user has write rights (Oracle)
IF OBJECT_ID(‘temp_dates’, ‘U’) IS NOT NULL --This should only do something in Oracle
–{1410
– 1410 Number of persons with continuous payer plan in each month
– Note: using temp table instead of nested query because this gives vastly improved performance in Oracle
USE @results_schema; --Set to result schema so temp tables are created where user has write rights (Oracle)
IF OBJECT_ID(‘temp_dates’, ‘U’) IS NOT NULL --This should only do something in Oracle
–{1411
– 1411 Number of persons by payer plan period start month
–{1412
– 1412 Number of persons by payer plan period end month
–{1413
– 1413 Number of persons by number of payer plan periods
–{1414
– 1414 Number of persons with payer plan period before year-of-birth
–{1415
– 1415 Number of persons with payer plan period end < start
–{1500
– 1500 Number of drug cost records with invalid drug exposure id
–{1501
– 1501 Number of drug cost records with invalid payer plan period id
–{1502
– 1502 Distribution of paid copay, by drug_concept_id
–{1503
– 1503 Distribution of paid coinsurance, by drug_concept_id
–{1504
– 1504 Distribution of paid toward deductible, by drug_concept_id
–{1505
– 1505 Distribution of paid by payer, by drug_concept_id
–{1506
– 1506 Distribution of paid by coordination of benefit, by drug_concept_id
–{1507
– 1507 Distribution of total out-of-pocket, by drug_concept_id
–{1508
– 1508 Distribution of total paid, by drug_concept_id
–{1509
– 1509 Distribution of ingredient_cost, by drug_concept_id
–{1510
– 1510 Distribution of dispensing fee, by drug_concept_id
–{1511
– 1511 Distribution of average wholesale price, by drug_concept_id
–{1600
– 1600 Number of procedure cost records with invalid procedure exposure id
–{1601
– 1601 Number of procedure cost records with invalid payer plan period id
–{1602
– 1602 Distribution of paid copay, by procedure_concept_id
–{1603
– 1603 Distribution of paid coinsurance, by procedure_concept_id
–{1604
– 1604 Distribution of paid toward deductible, by procedure_concept_id
–{1605
– 1605 Distribution of paid by payer, by procedure_concept_id
–{1606
– 1606 Distribution of paid by coordination of benefit, by procedure_concept_id
–{1607
– 1607 Distribution of total out-of-pocket, by procedure_concept_id
–{1608
– 1608 Distribution of total paid, by procedure_concept_id
–{1609
– 1609 Number of records by disease_class_concept_id
–{1610
– 1610 Number of records by revenue_code_concept_id
–{1700
– 1700 Number of records by cohort_concept_id
–{1701
– 1701 Number of records with cohort end date < cohort start date
