claims_db/phclaims/stage/tables/load_stage.mcaid_mcare_claim_header.R

#### CODE TO LOAD & TABLE-LEVEL QA STAGE.MCAID_MCARE_claim_header
# Eli Kern, PHSKC (APDE), 2020-02
# Alastair Mathesonm PHSKC (APDE), 2020-01
#
# This code is designed to be run as part of the master Medicaid/Medicare script:
# https://github.com/PHSKC-APDE/claims_data/blob/master/claims_db/db_loader/mcaid/master_mcaid_mcare_analytic.R
#

#### Load script ####
load_stage.mcaid_mcare_claim_header_f <- function() {
  
  ### Run SQL query
  odbc::dbGetQuery(db_claims, glue::glue_sql(
    "--Code to load data to stage.mcare_claim_header table
    --Union of mcaid and mcare claim header tables
    --Eli Kern (PHSKC-APDE)
    --2020-02
    --Run time: X min
    
    
    ------------------
    --STEP 1: Union mcaid and mcare tables to prepare for re-assignment of unique IDs for health care event concepts
    -------------------
    
    if object_id('tempdb..#temp1') is not null drop table #temp1;
    
    --Medicaid claims
    select
    --top 100
    b.id_apde
    ,'mcaid' as source_desc
    ,cast(a.claim_header_id as varchar(255)) as claim_header_id --because mcare uses alpha characters
    ,a.clm_type_mcaid_id as claim_type_mcaid_id
    ,claim_type_mcare_id = null
    ,a.claim_type_id
    ,filetype_mcare = null
    ,a.first_service_date
    ,a.last_service_date
    ,a.patient_status
    ,patient_status_code = null
    ,a.place_of_service_code
    ,a.type_of_bill_code
    ,facility_type_code = null
    ,service_type_code = null
    ,a.clm_status_code as claim_status_code
    ,a.billing_provider_npi
    ,a.primary_diagnosis
    ,a.icdcm_version
    ,a.ed_perform_id
    ,a.ed_pophealth_id
    ,a.inpatient as inpatient_id
    ,a.admsn_source as admission_source
    ,admission_type = null
    ,a.admsn_date as admission_date
    ,a.admsn_time as admission_time
    ,a.dschrg_date as discharge_date
    ,a.drvd_drg_code as drg_code
    ,hospice_from_date = null
    ,a.pc_visit_id
    ,a.ccs
    ,a.ccs_description
    ,a.ccs_description_plain_lang
    ,a.ccs_mult1
    ,a.ccs_mult1_description
    ,a.ccs_mult2
    ,a.ccs_mult2_description
    ,a.ccs_mult2_plain_lang
    ,a.ccs_final_description
    ,a.ccs_final_plain_lang
    ,a.mental_dx1
    ,a.mental_dxany
    ,a.mental_dx_rda_any
    ,a.sud_dx_rda_any
    ,a.maternal_dx1
    ,a.maternal_broad_dx1
    ,a.newborn_dx1
    ,a.ipt_medsurg
    ,a.ipt_bh
    ,a.ipt_sdoh
    ,a.ed_sdoh
    ,a.sdoh_any
    ,a.intent
    ,a.mechanism
    into #temp1
    from PHClaims.final.mcaid_claim_header as a
    left join PHClaims.final.xwalk_apde_mcaid_mcare_pha as b
    on a.id_mcaid = b.id_mcaid
    
    union
    
    --Medicare claims
    select
    --top 100
    b.id_apde
    ,'mcare' as source_desc
    ,a.claim_header_id
    ,claim_type_mcaid_id = null
    ,a.claim_type_mcare_id
    ,a.claim_type_id
    ,a.filetype_mcare
    ,a.first_service_date
    ,a.last_service_date
    ,a.patient_status
    ,a.patient_status_code
    ,place_of_service_code = null
    ,type_of_bill_code = null
    ,a.facility_type_code 
    ,a.service_type_code
    ,claim_status_code = null
    ,billing_provider_npi = null
    ,a.primary_diagnosis
    ,a.icdcm_version
    ,a.ed_perform_id
    ,a.ed_pophealth_id
    ,a.inpatient_id
    ,a.ipt_admission_source as admission_source
    ,a.ipt_admission_type as admission_type
    ,a.admission_date
    ,admission_time = null
    ,a.discharge_date
    ,a.drg_code
    ,a.hospice_from_date
    ,a.pc_visit_id
    ,c.ccs
    ,c.ccs_description
    ,c.ccs_description_plain_lang
    ,c.multiccs_lv1 as ccs_mult1
    ,c.multiccs_lv1_description as ccs_mult1_description
    ,c.multiccs_lv2 as ccs_mult2
    ,c.multiccs_lv2_description as ccs_mult2_description
    ,c.multiccs_lv2_plain_lang as ccs_mult2_plain_lang
    ,c.ccs_final_description
    ,c.ccs_final_plain_lang
    ,mental_dx1 = null
    ,mental_dxany = null
    ,mental_dx_rda_any = null
    ,sud_dx_rda_any = null
    ,maternal_dx1 = null
    ,maternal_broad_dx1 = null
    ,newborn_dx1 = null
    ,ipt_medsurg = null
    ,ipt_bh = null
    ,ipt_sdoh = null
    ,ed_sdoh = null
    ,sdoh_any = null
    ,intent = null
    ,mechanism = null
    from PHClaims.final.mcare_claim_header as a
    left join PHClaims.final.xwalk_apde_mcaid_mcare_pha as b
    on a.id_mcare = b.id_mcare
    --join to ICD-CM lookup table to create some columns
    left join PHClaims.ref.dx_lookup as c
    on (a.primary_diagnosis = c.dx) and (a.icdcm_version = c.dx_ver);
    
    
    ----------------
    --STEP 2: Assign unique ID to healthcare utilization concepts that are grouped by person, service date
    -------------------
    if object_id('tempdb..#temp2') is not null drop table #temp2;
    select 
    id_apde
    ,source_desc
    ,claim_header_id collate SQL_Latin1_General_Cp1_CS_AS as claim_header_id
    ,claim_type_mcaid_id
    ,claim_type_mcare_id
    ,claim_type_id
    ,filetype_mcare
    ,first_service_date
    ,last_service_date
    ,patient_status
    ,patient_status_code
    ,place_of_service_code
    ,type_of_bill_code
    ,facility_type_code 
    ,service_type_code
    ,claim_status_code
    ,billing_provider_npi
    ,primary_diagnosis
    ,icdcm_version
    
    --ED performance (RDA measure)
    ,case when ed_perform_id is null then null
    else dense_rank() over
    	(order by case when ed_perform_id is null then 2 else 1 end, --sorts non-relevant claims to bottom
    	id_apde, first_service_date)
    end as ed_perform_id
    
    --Recreate Yale ED carrier, outpatient and inpatient flags
    ,case when ed_pophealth_id is not null and claim_type_id = 5 then 1 else 0 end as ed_yale_carrier
    ,case when ed_pophealth_id is not null and claim_type_id = 4 then 1 else 0 end as ed_yale_opt
    ,case when ed_pophealth_id is not null and claim_type_id = 1 then 1 else 0 end as ed_yale_ipt
    
    --inpatient stays
    ,case when (inpatient_id = 0 or inpatient_id is null) then null
    else dense_rank() over
    	(order by case when (inpatient_id = 0 or inpatient_id is null) then 2 else 1 end, --sorts non-relevant claims to bottom
    	id_apde, discharge_date)
    end as inpatient_id
    
    ,admission_source
    ,admission_type
    ,admission_date
    ,admission_time
    ,discharge_date
    ,drg_code
    ,hospice_from_date
    
    --primary care visits
    ,case when pc_visit_id is null then null
    else dense_rank() over
    	(order by case when pc_visit_id is null then 2 else 1 end, --sorts non-relevant claims to bottom
    	id_apde, first_service_date)
    end as pc_visit_id
    
    ,ccs
    ,ccs_description
    ,ccs_description_plain_lang
    ,ccs_mult1
    ,ccs_mult1_description
    ,ccs_mult2
    ,ccs_mult2_description
    ,ccs_mult2_plain_lang
    ,ccs_final_description
    ,ccs_final_plain_lang
    ,mental_dx1
    ,mental_dxany
    ,mental_dx_rda_any
    ,sud_dx_rda_any
    ,maternal_dx1
    ,maternal_broad_dx1
    ,newborn_dx1
    ,ipt_medsurg
    ,ipt_bh
    ,ipt_sdoh
    ,ed_sdoh
    ,sdoh_any
    ,intent
    ,mechanism
    
    into #temp2
    from #temp1;
    
    --drop other temp tables to make space
    if object_id('tempdb..#temp1') is not null drop table #temp1;
    
    
    ------------------
    --STEP 3: Conduct overlap and clustering for ED population health measure (Yale measure)
    --Adaptation of Philip's Medicaid code, which is adaptation of Eli's original code
    -------------------
    
    -----
    --Union carrier, outpatient and inpatient ED visits
    -----
    --extract carrier ED visits and create left and right matching windows
    if object_id('tempdb..#ed_yale_1') is not null drop table #ed_yale_1;
    select id_apde,
    claim_header_id collate SQL_Latin1_General_Cp1_CS_AS as claim_header_id,
    first_service_date, last_service_date, 'Carrier' as ed_type
    into #ed_yale_1
    from #temp2
    where ed_yale_carrier = 1
    
    union
    select id_apde,
    claim_header_id collate SQL_Latin1_General_Cp1_CS_AS as claim_header_id,
    first_service_date, last_service_date, 'Outpatient' as ed_type
    from #temp2 where ed_yale_opt = 1
    
    union
    select id_apde,
    claim_header_id collate SQL_Latin1_General_Cp1_CS_AS as claim_header_id,
    first_service_date, last_service_date, 'Inpatient' as ed_type
    from #temp2 where ed_yale_ipt = 1;
    
    -----
    --label duplicate/adjacent visits with a single [ed_pophealth_id]
    -----
    
    --Set date of service matching window
    declare @match_window int;
    set @match_window = 1;
    
    if object_id('tempdb..#ed_yale_final') is not null 
    drop table #ed_yale_final;
    WITH [increment_stays_by_person] AS
    (
    SELECT
    id_apde
    ,claim_header_id collate SQL_Latin1_General_Cp1_CS_AS as claim_header_id
    -- If [prior_first_service_date] IS NULL, then it is the first chronological [first_service_date] for the person
    ,LAG([first_service_date]) OVER(PARTITION BY [id_apde] ORDER BY [first_service_date], [last_service_date], [claim_header_id]) AS [prior_first_service_date]
    ,[first_service_date]
    ,[last_service_date]
    ,[ed_type]
    -- Number of days between consecutive rows
    ,DATEDIFF(DAY, LAG([first_service_date]) OVER(PARTITION BY [id_apde] 
     ORDER BY [first_service_date], [last_service_date], [claim_header_id]), [first_service_date]) AS [date_diff]
    /*
    Create a chronological (0, 1) indicator column.
    If 0, it is the first ED visit for the person OR the ED visit appears to be a duplicate
    (overlapping service dates) of the prior visit.
    If 1, the prior ED visit appears to be distinct from the following stay.
    This indicator column will be summed to create an episode_id.
    */
    ,CASE WHEN ROW_NUMBER() OVER(PARTITION BY [id_apde] 
          ORDER BY [first_service_date], [last_service_date], [claim_header_id]) = 1 THEN 0
          WHEN DATEDIFF(DAY, LAG([first_service_date]) OVER(PARTITION BY [id_apde]
    	  ORDER BY [first_service_date], [last_service_date], [claim_header_id]), [first_service_date]) <= @match_window THEN 0
    	  WHEN DATEDIFF(DAY, LAG(first_service_date) OVER(PARTITION BY [id_apde]
    	  ORDER BY [first_service_date], [last_service_date], [claim_header_id]), [first_service_date]) > @match_window THEN 1
     END AS [increment]
    FROM #ed_yale_1
    --ORDER BY [id_apde], [first_service_date], [last_service_date], [claim_header_id]
    ),
    
    /*
    Sum [increment] column (Cumulative Sum) within person to create an stay_id that
    combines duplicate/overlapping ED visits.
    */
    [create_within_person_stay_id] AS
    (
    SELECT
    id_apde
    ,claim_header_id collate SQL_Latin1_General_Cp1_CS_AS as claim_header_id
    ,[prior_first_service_date]
    ,[first_service_date]
    ,[last_service_date]
    ,[ed_type]
    ,[date_diff]
    ,[increment]
    ,SUM([increment]) OVER(PARTITION BY [id_apde] ORDER BY [first_service_date], [last_service_date], [claim_header_id] ROWS UNBOUNDED PRECEDING) + 1 AS [within_person_stay_id]
    FROM [increment_stays_by_person]
    --ORDER BY [id_apde], [first_service_date], [last_service_date], [claim_header_id]
    )
    
    SELECT
    id_apde
    ,claim_header_id collate SQL_Latin1_General_Cp1_CS_AS as claim_header_id
    ,[prior_first_service_date]
    ,[first_service_date]
    ,[last_service_date]
    ,[ed_type]
    ,[date_diff]
    ,[increment]
    ,[within_person_stay_id]
    ,DENSE_RANK() OVER(ORDER BY [id_apde], [within_person_stay_id]) AS [ed_pophealth_id]
    
    ,FIRST_VALUE([first_service_date]) OVER(PARTITION BY [id_apde], [within_person_stay_id] 
     ORDER BY [id_apde], [within_person_stay_id] ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS [episode_first_service_date]
    ,LAST_VALUE([last_service_date]) OVER(PARTITION BY [id_apde], [within_person_stay_id] 
     ORDER BY [id_apde], [within_person_stay_id] ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS [episode_last_service_date]
    
    INTO #ed_yale_final
    FROM [create_within_person_stay_id]
    ORDER BY id_apde, [first_service_date], [last_service_date], [claim_header_id];
    
    --drop other temp tables to make space
    if object_id('tempdb..#ed_yale_1') is not null drop table #ed_yale_1;
    
    
    ------------------
    --STEP 9: Join back Yale table with header table on claim header ID
    -------------------
    insert into PHClaims.stage.mcaid_mcare_claim_header with (tablock)
    select distinct
    a.id_apde
    ,a.source_desc
    ,a.claim_header_id
    ,a.claim_type_mcaid_id
    ,a.claim_type_mcare_id
    ,a.claim_type_id
    ,a.filetype_mcare
    ,a.first_service_date
    ,a.last_service_date
    ,a.patient_status
    ,a.patient_status_code
    ,a.place_of_service_code
    ,a.type_of_bill_code
    ,a.facility_type_code
    ,a.service_type_code
    ,a.claim_status_code
    ,a.billing_provider_npi
    ,a.primary_diagnosis
    ,a.icdcm_version
    ,a.ed_perform_id
    ,b.ed_pophealth_id
    ,a.inpatient_id
    ,a.admission_source
    ,a.admission_type
    ,a.admission_date
    ,a.admission_time
    ,a.discharge_date
    ,a.drg_code
    ,a.hospice_from_date
    ,a.pc_visit_id
    ,a.ccs
    ,a.ccs_description
    ,a.ccs_description_plain_lang
    ,a.ccs_mult1
    ,a.ccs_mult1_description
    ,a.ccs_mult2
    ,a.ccs_mult2_description
    ,a.ccs_mult2_plain_lang
    ,a.ccs_final_description
    ,a.ccs_final_plain_lang
    ,a.mental_dx1
    ,a.mental_dxany
    ,a.mental_dx_rda_any
    ,a.sud_dx_rda_any
    ,a.maternal_dx1
    ,a.maternal_broad_dx1
    ,a.newborn_dx1
    ,a.ipt_medsurg
    ,a.ipt_bh
    ,a.ipt_sdoh
    ,a.ed_sdoh
    ,a.sdoh_any
    ,a.intent
    ,a.mechanism
    ,getdate() as last_run
    from #temp2 as a
    left join #ed_yale_final as b
    on a.claim_header_id = b.claim_header_id;",
    .con = db_claims))
}

#### Table-level QA script ####
qa_stage.mcaid_mcare_claim_header_qa_f <- function() {
  
  #confirm that claim row counts match as expected for union
  res1 <- dbGetQuery(conn = db_claims, glue_sql(
    "select 'stage.mcaid_mcare_claim_header' as 'table', 'row count, expect match with sum of mcaid and mcare' as qa_type,
    count(*) as qa1, qa2 = null
    from stage.mcaid_mcare_claim_header;",
    .con = db_claims))
  
  res2 <- dbGetQuery(conn = db_claims, glue_sql(
    "select 'stage.mcaid_claim_header' as 'table', 'row count' as qa_type,
    count(*) as qa1, qa2 = null
    from final.mcaid_claim_header;",
    .con = db_claims))
  
  res3 <- dbGetQuery(conn = db_claims, glue_sql(
    "select 'stage.mcare_claim_header' as 'table', 'row count' as qa_type,
    count(*) as qa1, qa2 = null
    from final.mcare_claim_header;",
    .con = db_claims))
  
  #verify that all inpatient stays have discharge date
  res4 <- dbGetQuery(conn = db_claims, glue_sql(
    "select 'stage.mcaid_mcare_claim_header' as 'table', '# of ipt stays with no discharge date, expect 0' as qa_type,
    count(*) as qa1, qa2 = null
    from PHClaims.stage.mcaid_mcare_claim_header
    where inpatient_id is not null and discharge_date is null;",
    .con = db_claims))
  
  #verify that no ed_pophealth_id value is used for more than one person
  res5 <- dbGetQuery(conn = db_claims, glue_sql(
    "select 'stage.mcaid_mcare_claim_header' as 'table', '# of ed_pophealth_id values used for >1 person, expect 0' as qa_type,
    count(a.ed_pophealth_id) as qa1, qa2 = null
    from (
      select ed_pophealth_id, count(distinct id_apde) as id_dcount
      from PHClaims.stage.mcaid_mcare_claim_header
      group by ed_pophealth_id
    ) as a
    where a.id_dcount > 1;",
    .con = db_claims))
  
  #verify that ed_pophealth_id does not skip any values
  res6 <- dbGetQuery(conn = db_claims, glue_sql(
    "select 'stage.mcaid_mcare_claim_header' as 'table', 'qa1 = distinct ed_pophealth_id, qa2 = max - min + 1' as qa_type,
    count(distinct ed_pophealth_id) as qa1, cast(max(ed_pophealth_id) - min(ed_pophealth_id) + 1 as int) as qa2
    from PHClaims.stage.mcaid_mcare_claim_header;",
    .con = db_claims))
  
  #verify that there are no rows with ed_perform_id without ed_pophealth_id
  res7 <- dbGetQuery(conn = db_claims, glue_sql(
    "select 'stage.mcaid_mcare_claim_header' as 'table', '# of ed_perform rows with no ed_pophealth, expect 0' as qa_type,
    count(*) as qa1, qa2 = null
    from PHClaims.stage.mcaid_mcare_claim_header
    where ed_perform_id is not null and ed_pophealth_id is null;",
    .con = db_claims))
  
  #verify that 1-day overlap window was implemented correctly with ed_pophealth_id
  res8 <- dbGetQuery(conn = db_claims, glue_sql(
    "with cte as
    (
    select * 
    ,lag(ed_pophealth_id) over(partition by id_apde, ed_pophealth_id order by first_service_date) as lag_ed_pophealth_id
    ,lag(first_service_date) over(partition by id_apde, ed_pophealth_id order by first_service_date) as lag_first_service_date
    from PHClaims.stage.mcaid_mcare_claim_header
    where [ed_pophealth_id] is not null
    )
    select 'stage.mcaid_mcare_claim_header' as 'table', '# of ed_pophealth visits where the overlap date is greater than 1 day, expect 0' as 'qa_type',
      count(*) as qa1, qa2 = null
    from PHClaims.stage.mcaid_mcare_claim_header
    where [ed_pophealth_id] in (select ed_pophealth_id from cte where abs(datediff(day, lag_first_service_date, first_service_date)) > 1);",
    .con = db_claims))
  
  res_final <- mget(ls(pattern="^res")) %>% bind_rows()
}
PHSKC-APDE/Medicaid documentation built on April 3, 2020, 5:32 p.m.