Financial PMPM
Methods
The Financial PMPM data mart computes member months and stratifies population paid and allowed amounts by member months and service categories across various payers and plans.
Data Dictionary
pmpm_prep
A table that computes all the paid and allowed statistics for every patient_id and year_month combination.
Primary Keys:
- patient_id
- year_month
- plan
- data_source
Column | Data Type | Description | Terminology |
---|
pmpm_payer_plan
A table that computes per member per month statistics for every service category by aggregating across patients from pmpm_prep. This table is at the payer, plan grain.
Primary Keys:
- year_month
- payer
- plan
- data_source
Column | Data Type | Description | Terminology |
---|
pmpm_payer
A table that computes per member per month statistics for every service category by aggregating across patients from pmpm_prep. This table is at the payer grain.
Primary Keys:
- year_month
- payer
- data_source
Column | Data Type | Description | Terminology |
---|
Example SQL
Calculate Member Months and Total Medical Spend
select
data_source
, year_month
, cast(sum(medical_paid) as decimal(18,2)) as medical_paid
, count(*) as member_months
, cast(sum(medical_paid)/count(*) as decimal(18,2)) as pmpm
from financial_pmpm.pmpm_prep
group by
data_source
, year_month
order by
data_source
, year_month;
Trending PMPM by Service Category
The pmpm table already breaks out pmpm by service category and groups it at the member month level.
select *
from financial_pmpm.pmpm_payer
order by year_month;
Trending PMPM by Claim Type
Here we calculate PMPM manually by counting member months and joining payments by claim type to them.
with member_month as (
select
data_source
, year_month
, count(*) as member_months
from core.member_months
group by
data_source
, year_month
)
, medical_claims as (
select
mc.data_source
, to_char(mc.claim_start_date, 'yyyymm') as year_month
, mc.claim_type
, cast(sum(mc.paid_amount) as decimal(18, 2)) as paid_amount
from core.medical_claim as mc
inner join core.member_months as mm
on mc.patient_id = mm.patient_id
and mc.data_source = mm.data_source
and to_char(mc.claim_start_date, 'yyyymm') = mm.year_month
group by
mc.data_source
, to_char(mc.claim_start_date, 'yyyymm')
, mc.claim_type
)
select
mm.data_source
, mm.year_month
, mc.claim_type
, mc.paid_amount
, mm.member_months
, cast(mc.paid_amount / mm.member_months as decimal(18, 2)) as pmpm_claim_type
from member_month as mm
left join medical_claims as mc
on mm.data_source = mc.data_source
and mm.year_month = mc.year_month
order by
mm.data_source
, mm.year_month
, mc.claim_type;
PMPM by Chronic Condition
Here we calculate PMPM by chronic condition. Since members can and do have more than one chronic condition, payments and members months are duplicated. This is useful for comparing spend across chronic conditions, but should be used with caution given the duplication across conditions.
with chronic_condition_members as (
select distinct
patient_id
from chronic_conditions.tuva_chronic_conditions_long
)
, chronic_conditions as (
select
patient_id
, condition
from chronic_conditions.tuva_chronic_conditions_long
union
select
p.patient_id
, 'No Chronic Conditions' as condition
from core.patient as p
left join chronic_condition_members as ccm
on p.patient_id = ccm.patient_id
where ccm.patient_id is null
)
, medical_claims as (
select
mc.data_source
, mc.patient_id
, to_char(mc.claim_start_date, 'yyyymm') as year_month
, cast(sum(mc.paid_amount) as decimal(18, 2)) as paid_amount
from core.medical_claim as mc
inner join core.member_months as mm
on mc.patient_id = mm.patient_id
and mc.data_source = mm.data_source
and to_char(mc.claim_start_date, 'yyyymm') = mm.year_month
group by
mc.data_source
, mc.patient_id
, to_char(mc.claim_start_date, 'yyyymm')
)
select
mm.data_source
, cc.condition
, count(*) as member_months
, sum(mc.paid_amount) as paid_amount
, cast(sum(mc.paid_amount) / count(*) as decimal(18, 2)) as medical_pmpm
from core.member_months as mm
left join chronic_conditions as cc
on mm.patient_id = cc.patient_id
left join medical_claims as mc
on mm.patient_id = mc.patient_id
and mm.year_month = mc.year_month
and mm.data_source = mc.data_source
group by
mm.data_source
, cc.condition
order by
member_months desc;