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Overview

Episource’s Risk Adjustment Toolkit delivers a comprehensive set of tools for analyzing Medicare Advantage risk adjustment data. Powered by Risk Adjustment Toolkit, the industry’s leading Risk Adjustment Analytics engine, the Excel add-in empowers health plans and provider groups to better understand their members’ risk scores, identify DX/HCC gaps, and track risk program ROI.

Features:
  • Calculate member risk scores and forecast premiums based on demographic and diagnosis information
  • Perform analysis on DX codes and/or HCCs
  • Get descriptions and reference details about DX codes or HCCs without leaving Excel
  • Identify Year-over-Year HCC gaps and calculate their financial impacts
  • Calculate impact and ROI of incremental codes identified in risk adjustment programs
  • Full implementation of the CMS HCC Models, including hierarchies, age/sex edits, and interaction codes
  • Coverage of all risk factor types
Function Arguments
Function ParametersDescription
dx_array
Array of text cells. Each text cell can contain a single dx code or a comma separated list of dx codes. Any decimals in DX codes are stripped before processing.
cc_array
Array of text cells. Each text cell can contain a single HCC code or a comma separated list of HCC codes. HCC Codes can be in the string form HCCNNN(eg "HCC001"), or can be integer values. "+" or "-" values are accepted for the purposes of raf calculations: +HCC18 - HCC19 gives the net value of upgrading DM2
version
(CMS Model + DOS Year)*
Health Insurance Plans DOS Year
20172018201920202021202220232024
Medicare Part Cv22_2017v23_2018v24_2019v24_2020v24_2021v24_2022v24_2023
v28_2023
pace_v22_2023		v24_2024
v28_2024
pace_v22_2024
Medicare Part Dv05_2017v05_2018v05_2019v05_2020v05_2021v08_2022v08_2023
pace_v05_2023		v08_2024
pace_v05_2024
Affordable Care Act hhs_v05_2017hhs_v05_2018hhs_v05_2019hhs_v05_2020hhs_v05_2021hhs_v07_2022hhs_v07_2023hhs_v07_2024
Medicare Part E (ESRD) ---esrd_v21_2020esrd_v21_2021esrd_v24_2022esrd_v24_2023
pace_esrd_v21_2024		esrd_v24_2024
pace_esrd_v21_2023
model

Medicare Part - C

ModelDescription
CNCommunity Non-Dual
CPCommunity Partial Benefit
CFCommunity Full Benefit
IInstitutional
ENew Enrollee
SENew Enrollee Chronic Care SNP

Medicare Part - D

ModelDescription
D1Community Non-Low Income Continuing Enrollee
D2Community Low Income Continuing Enrollee
D3Institutional Continuing Enrollee
D4New Enrollee Community Non-Low Income Non-ESRD
D5New Enrollee Community Non-Low Income ESRD
D6New Enrollee Community Low Income Non-ESRD
D7New Enrollee Community Low Income ESRD
D8New Enrollee Institutional Non-ESRD
D9New Enrollee Institutional ESRD

Affordable Care Act

ModelDescription
ADULTage >= 21
CHILD2 <= age <= 20
INFANT0 <= age <= 1

Medicare Part - E (v21)

ModelDescription
C1Community Post Graft 4-9 (ESRD) (Adjustments before 2023)
C2Community Post Graft 10+ (ESRD) (Adjustments before 2023)
DDialysis (ESRD) (Adjustments before 2023)
I1Institutional Post Graft 4-9 (ESRD) (Adjustments before 2023)
I2Institutional Post Graft 10+ (ESRD) (Adjustments before 2023)
G1Graft I (ESRD)
G2Graft II (ESRD)
EDNew Enrollee Dialysis (ESRD)
E1New Enrollee Post Graft 4-9 (ESRD)
E2New Enrollee Post Graft 10+ (ESRD)

Medicare Part - E (v24)

ModelDescription
C3Community Post Graft 4-9 (ESRD) Full Dual
C4Community Post Graft 4-9 (ESRD) Partial Dual
C5Community Post Graft 4-9 (ESRD) Non-Dual
C6Community Post Graft 10+ (ESRD) Full Dual
C7Community Post Graft 10+ (ESRD) Partial Dual
C8Community Post Graft 10+ (ESRD) Non-Dual
D1Dialysis (ESRD) Full Dual
D2Dialysis (ESRD) Partial Dual or Non-dual
EDNew Enrollee Dialysis (ESRD)
E1New Enrollee Post Graft 4-9 (ESRD)
E2New Enrollee Post Graft 10+ (ESRD)
G1Graft I (ESRD)
G2Graft II (ESRD)
I3Institutional Dialysis (ESRD) Full Dual
I4Institutional Dialysis (ESRD) Partial or Non-Dual
I5Institutional Post Graft 4-9 (ESRD) Full Dual
I6Institutional Post Graft 4-9 (ESRD) Partial Dual
I7Institutional Post Graft 4-9 (ESRD) Non-Dual
I8Institutional Post Graft 10+ (ESRD) Full Dual
I9Institutional Post Graft 10+ (ESRD) Partial Dual
IAInstitutional Post Graft 10+ (ESRD) Non-Dual
age
Age of Member
sex
Sex of Member
plate
Enrollee's plan level

Plates provided by our Toolkit:

  • P - Platinum
  • G - Gold
  • S - Silver
  • B - Bronze
  • C - Catastrophic
baserate
Base reimbursement premium for a member. This number * RAF becomes the PMPM premium in US Dollars. Default baserate - $800
DOB
DOB of member to calculate age of the member given calculation year
orec
Original reason for entitlement. Indicates presence of ESRD or disability.
  • 0: Old age (OASI)
  • 1: Disability (DIB)
  • 2: End Stage Renal Disease (ESRD)
  • 3: Both DIB and ESRD
enrollmentDuration
Enrollee’s enrollment duration in months in benefit year; enrollment duration is not applicable to Child and Infant models; variable ignored
calculation_year
Used for calculating the current age of a member given DOB
disabl
Flag to indicate a member is on disability and should use a disabled demographic score
never_trump
Suppress trumping logic in the outputs such that both trumped and non-trumped codes are returned (This can be useful for suspecting)

*As available in the Risk Adjustment Toolkit

Functions
FunctionsArgumentsdescription
dx_descdx_array, versionReturns colon-separated list of descriptions of each DX Code from CMS crosswalk.
dx_rafdx_array, age, version, model, sex, disabl, verbose, never_trump, baserateReturns cc raf of associated dx codes after conversion to cc and trumping/interaction logic is applied (equivalent of cc_raf(dx2cc(dx_array))
dx2ccdx_array, age, version, model, sex, disabl, never_trump, verboseReturns a comma separated list of the ccs represented by a list of DX codes after trumping/interaction logic is applied
clean_cccc_array, versionGiven a list of ccs, return a list of deduped and untrumped ccs codes valid for the coding model
clean_dxdx_array, versionGiven a list of dx codes, return a list of deduped and untrumped dx codes valid for the coding model
cc_desccc_array, versionReturns a colon-separated list of descriptions of each HCC Code from CMS crosswalk.
cc_rafcc_array, version, model, age, sex, Returns cc raf (does not include demographic RAF) of cc codes after trumping/interaction logic is applied
cc_combinebase_cc_array, additional_cc_array, version, model, Returns a list of ccs after combining them and applying trumping/interaction logic;
cc_diffbase_cc_array, additional_cc_array, version, Compares a base list of ccs and additional ccs and returns an information block on the differences ; eg: "Adds: HCC001, HCC18; Deletes: HCC135; Upgraded: HCC019; Downgraded:"
cc_diff_rafbase_cc_array, additional_cc_array, [options]Returns net raf difference between baseline ccs and additional ccs
cc_diff_addsbase_cc_array, additional_cc_array, [options]Compares a base list of ccs and additional ccs and returns a list of ccs that are considered adds over the baseline
cc_diff_adds_rafbase_cc_array, additional_cc_array, [options]Returns the net raf value of ccs that are considered adds over the baseline
cc_diff_deletesbase_cc_array, additional_cc_array, [options]Compares a base list of ccs and additional ccs and returns a list of ccs that are deletes between the additional codes vs the baseline
cc_diff_deletes_rafbase_cc_array, additional_cc_array, [options]Returns the net raf value of ccs that are deletes between the additional codes vs the baseline
cc_diff_upgradedbase_cc_array, additional_cc_array, [options]Compares a base list of ccs and additional ccs and returns a list of ccs that are considered upgraded in the baseline
cc_diff_downgradedbase_cc_array, additional_cc_array, [options]Compares a base list of ccs and additional ccs and returns a list of ccs that are downgraded in the baseline compared to additional codes
cc_diff_downgrade_tobase_cc_array, additional_cc_array, [options]Compares a base list of ccs and additional ccs and returns a list of ccs that are downgraded_to in additional codes compared to the baseline
cc_incrementbase_cc_array, additional_cc_array, [options]Returns the net incremental change between cc_lists, for example for calculating the value of a coding project over claims. Equivalent of +Adds - Upgraded in the format("+HCC001, +HCC18, - HCC019")
cc_increment_rafbase_cc_array, additional_cc_array, [options]Returns the RAF of the net incremental change (+Adds - Upgraded) between cc_lists. Equivalent of cc_raf(cc_diff_increment)
cc_gapsbase_cc_array, additional_cc_array, [options]Compares a base list of ccs and additional ccs and returns a list of ccs that are deletes or downgrades between the additional codes vs the baseline
cc_gaps_rafbase_cc_array, additional_cc_array, [options]Compares a base list of ccs and additional ccs and returns raf of ccs that are deletes or downgrades between the additional codes vs the baseline
dx_incrementbase_dx_array, additional_dx_array, [options]Returns the net incremental change between dx_lists, for example for calculating the value of a coding project over claims. Equivalent of +Adds - Upgraded in the format("+dx001, +dx18, - dx019")
dx_increment_rafbase_dx_array, additional_dx_array, [options]Returns the RAF of the net incremental change (+Adds - Upgraded) between dx_lists. Equivalent of dx_raf(dx_diff_increment)
dx_gapsbase_dx_array, additional_dx_array, [options]Compares a base list of dxs and additional dxs and returns a list of dxs that are deletes or downgrades between the additional codes vs the baseline
dx_gaps_rafbase_dx_array, additional_dx_array, [options]dx_diff_deletes_raf focuses on YoY Chronic Gaps and downgrades (net raf of downgraded). Equivalent of dx_chronic(dx_diff_deletes).
dx_diffbase_dx_array, additional_dx_array, [options]Compares a base list of dx and additional dx and returns an information block on the differences ; eg: "Adds: E119, I2720; Deletes: I495; Upgraded: F10250; Downgraded:"
dx_diff_rafbase_dx_array, additional_dx_array, [options]Returns net raf difference between baseline ccs and additional ccs
cc_chroniccc_array, [options]Returns the subset of a cc list that pertain to chronic conditions
cc_acutecc_array, [options]Returns the subset of a cc list that pertain to acute conditions
cc_hybridcc_array, [options]Returns the subset of a cc list that pertain to hybrid (both acute and chronic) conditions
dx_chronicdx_array, [options]Returns the subset of a dx list that pertain to chronic conditions
dx_acutedx_array, [options]Returns the subset of a dx list that pertain to acute conditions
dx_hybriddx_array, [options]Returns the subset of a dx list that pertain to hybrid (both acute and chronic) conditions
memprofilememberid_column, dx_column_array, dos_column, sex, age, [options]This would be to process a received claims file. Consolidates data into a new sheet containing a table w/ 1 row per member containing for each dos year: unique DXs, their ccs, RAF value.
dx_profile_comparememberid_column, dx_column_array, dos_column, sex, age, [options]This would be a comparison between two raf_profile sheets. Consolidates data from both the sheet into a new sheet containing a table w/1 row per member containing Dx Codes from both the sheets. Run both dx_increment and dx_gaps to get the Dx difference between both the sheets and the corresponding RAF Value
Some Examples:
1. Conversion of DX to HCC, calculation of demo RAF, HCC RAF and total RAF:
ABCDEFGHIJK
1namedxversionraf_typeagesexhccsdemo_rafdx_rafhcc_raftotal_raf
2Bob JonesE119v24_2022CN67M=epi.DX2CC(B2,C2,D2,E2,F2)=epi.DEMO_RAF(,C2,D2,E2,F2,)=epi.DX_RAF(B2,C2,D2,E2,F2)=epi.CC_RAF(G2,C2,D2,E2,)=H2+I2
3Mark MathewsN183, N184hhs_v05_2021ADULT78M=epi.DX2CC(B3,C3,D3,E3,F3)=epi.DEMO_RAF(,C3,D3,E3,F3,)=epi.DX_RAF(B3,C3,D3,E3,F3)=epi.CC_RAF(G3,C3,D3,E3,)=H3+I3
Output for table (1):
GHIJK
1hccsdemo_rafdx_rafhcc_raftotal_raf
2HCC190.2570.0880.0880.345
3HHS_HCC188,ED_110.2380.8980.8981.136
2. Calculation of incremental HCC/DX, RAF change and ROI:
a) Calculation with incremental DX:
ABCDEFGHIJK
1nameclaims_dxchart_audit_resultsverraf_typeagesexbaserateincremental_dxraf_changechart_audit_roi
2John WilliamsE119E1151v24_2021CP40M800=epi.DX_INCREMENT(B2,C2,D2,E2,F2,G2)=epi.DX_INCREMENT_RAF(B2,C2,D2,E2,F2,G2,)=J2*H2
3Mathew JamesD330E1152v05_2021D370F880=epi.DX_INCREMENT(B3,C3,D3,E3,F3,G3)=epi.DX_INCREMENT_RAF(B3,C3,D3,E3,F3,G3,)=J3*H3
Output for table (2.a):
IJK
1incremental_dxraf_changechart_audit_roi
2E1151,-E1190.475380
3E11520.559491.92

b) Calculation with incremental HCC:
ABCDEFGHIJ
1nameclaims_dxchart_audit_resultsverraf_typeagebaserateincremental_dxraf_changechart_audit_roi
2John WilliamsHCC19HCC17v24_2021CP40800=epi.CC_INCREMENT(B2,C2,D2,E2,F2)=epi.CC_INCREMENT_RAF(B2,C2,D2,E2,F2)=I2*G2
3Mathew JamesHHS_HCC174, HHS_HCC4HHS_HCC3hhs_v07_2023CHILD10880=epi.CC_INCREMENT(B3,C3,D3,E3,F3,)=epi.CC_INCREMENT_RAF(B3,C3,D3,E3,F3,)=I3*G3
Output for table (2.b):
HIJ
1incremental_hccraf_changechart_audit_roi
2HCC17,-HCC190.211168.8
3HHS_HCC003,-HHS_HCC0042.1921928.96
3. HCC and DX Gaps YOY:
a) DX Gaps YOY:
ABCDEFGHI
1namebase_condnew_condversionmodelagesexdx_gapsdx_gaps_raf
2John WilliamsE1142E119v24_2022CN59M=epi.DX_GAPS(B2,C2,D2,E2,F2,G2,)=epi.DX_GAPS_RAF(B2,C2,D2,E2,F2,G2,)
3Sharin WingetF3181, G8220F603hhs_v07_2022CHILD12F=epi.DX_GAPS(B3,C3,D3,E3,F3,G3,)=epi.DX_GAPS_RAF(B3,C3,D3,E3,F3,G3,)
Output for table (3.a)
HI
1dx_gapsdx_gaps_raf
2E1142-0.189
3G8220,F3181-2.063

b) HCC Gaps YOY:
ABCDEFGHI
1namebase_condnew_condversionmodelagesexhcc_gapshcc_gaps_raf
2John WilliamsHCC17, HCC1HCC18v24_2022CN59M=epi.CC_GAPS(B2,C2,D2,E2,F2,G2,)=epi.CC_GAPS_RAF(B2,C2,D2,E2,F2,G2,)
3Sharin WingetHHS_HCC1HHS_HCC2hhs_v07_2022CHILD12F=epi.CC_GAPS(B3,C3,D3,E3,F3,G3,)=epi.CC_GAPS_RAF(B3,C3,D3,E3,F3,G3,)
Output for table (3.b)
HI
1hcc_gapshcc_gaps_raf
2HCC1,HCC17-0.24
3HHS_HCC001-5.222
4. Member Profile:
Input Table:
ABCDEFGHIJKL
1namememidchartidagesexdosmodelEnrollment_durationPlateCalculation_YearDOBdx
2Erik11165M20183E119,i420,f330,d330
3Erik11285M2018CF4E1151
4Bob221421/14/2019CP4D330, F330
5Tom221423/19/2019CPF330
6Mark22390F6/29/2018CPE119
7Jane32459F5/3/2018CFi420
8Robert43174M9/4/2019ADULTE119
9Amy541F3/25/2019CFe119
10Jude643F4/25/2019ADULT7g20201/19/1970A0105
Command:
=epi.MEMPROFILE(InputTable!A1:A10,InputTable!B1:B10,InputTable!C1:C10,InputTable!D1:D10,InputTable!E1:E10,InputTable!F1:F10,InputTable!L1:L10,InputTable!G1:G10,InputTable!J1:J10,InputTable!K1:K10,InputTable!H1:H10,InputTable!I1:I10,1)

Output Table:
ABCDEFGHIJKLM
1namememiddosagesexmodelenrollmentDurationplatedxHCCsDemoRAFHCCRAFTotalRAF
2Erik1201885MCFE119,I420,F330,D330,E1151HCC12,HCC18,HCC59,HCC85,HCC108,DIABETES_CHF0.9231.482.403
3Bob2201942MCPD330, F330HCC12,HCC590.2410.2070.448
4Tom2201942MCPF330HCC590.2410.0480.289
5Mark2201890FCPE119HCC190.8170.0960.913
6Jane3201859FCFI420HCC85,DISABLED_HCC850.3920.4220.814
7Robert4201974MADULT11SE119HHS_HCC021,ED_110.3610.5190.88
8Amy5201980FCFE119HCC190.6390.090.729
9Jude6201950FADULT7GA0105HHS_HCC055,ED_70.5195.4926.011
5. DX Profile Compare:
Claims Input Table:
ABCDEFGH
1namememidchartidagesexdosmodeldx
2Erik111M1/1/2018E119,f330,d330
3Erik112M2/23/2018E119
4Bob221421/14/2019D330
5Bob22142F3/19/2019CFC770
6Bob223416/29/2018CPE119
7Tom32459F3/5/2018i420
8431744/9/2019IE119
9Jane54165F3/25/2019CFe119
10Jude64355F4/25/2019ADULTA0105
11Jack74568M4/13/2019D1E119,i420

Coding Input Table:
ABCDEFGHIJKL
1namememidchartidagesexdosmodelEnrollment_durationPlateCalculation_YearDOBdx
2Erik11185M1/1/20183E119,i420,f330,d330
3Erik11285M2/23/20184E1151
4Bob22142M1/14/2019CP4D330
5Bob22142M3/19/2019CPF330
6Bob22341F6/29/2018CPE119
7Tom32459F3/5/2018CFA0105
8Mark43174M4/9/2019IE119
9Jane565F3/25/2019CFe119
10Jude64355F4/25/2019ADULTE1111
11Jack74568M4/13/2019D1E089
Command:
=epi.DX_PROFILE_COMPARE(Claims!A1:A11,Claims!B1:B11,Claims!C1:C11,Claims!D1:D11,Claims!E1:E11,Claims!F1:F11,Claims!H1:H11,Claims!G1:G11,,,,,Coding!A1:A11,Coding!B1:B11,Coding!C1:C11,Coding!D1:D11,Coding!E1:E11,Coding!F1:F11,Coding!L1:L11,Coding!G1:G11,Coding!J1:J11,Coding!K1:K11,Coding!H1:H11,Coding!I1:I11,1,0)

Output Table:
ABCDEFGHIJKLMNOPQRSTUVW
1namememiddosagesexmodelenrollmentDurationplatedx_1dx_2verHCCs_1DemoRAF_1HCCRAF_1TotalRAF_1HCCs_2DemoRAF_2HCCRAF_2TotalRAF_2dx_incrementRAF_incrementdx_gapsRAF_gaps
2Erik1201885MCPE119,F330,D330E119,I420,F330,D330,E1151v23_2018HCC12,HCC19,HCC590.6790.3381.017HCC12,HCC18,HCC59,HCC85,HCC108,DIABETES_CHF0.6791.3912.07I420,E1151,-E1191.0530
3Bob2201942FCFD330,C770D330,F330v24_2019HCC80.2882.4442.732HCC12,HCC590.2880.2320.52F3300.056C770-2.268
4Bob2201841FCPE119E119v23_2018HCC190.3840.1330.517HCC190.3840.1330.51700
5Tom3201859FCFI420A0105v23_2018HCC85,DISABLED_HCC850.3920.4220.814HCC39,DISABLED_HCC390.3920.7241.116A01050.724I420-0.422
6Mark4201974MIE119E119v24_2019HCC191.1640.1481.312HCC191.1640.1481.31200
7Jane5201965FCFE119E119v24_2019HCC190.380.090.47HCC190.380.090.4700
8Jude6201955FADULT11SA0105E1111hhs_v05_2019HHS_HCC055,ED_110.3825.2525.634HHS_HCC019,ED_110.3820.5190.901E11110.462A0105-5.252
9Jack7201968MD1E119,I420E089v05_2019RXHCC31,RXHCC1860.2610.4370.698RXHCC310.2610.270.5310I420-0.167
6. HCC Profile Compare:
Claims Input Table:
ABCDEFGH
1namememidchartidagesexdosmodelhcc
2Jane541F3/25/2019CFHCC19
3Jude64355F4/25/2019ADULTHHS_HCC055
4Jack74568M4/13/2019D1RXHCC186,RXHCC31
5Robert852F4/25/2022ADULTHHS_HCC21
6Mike95568M4/13/2023D1RXHCC186,RXHCC31
7Jerry105759F3/5/202285
8Bruno1160852/23/2023HCC38

Coding Input Table:
ABCDEFGHIJKL
1namememidchartidagesexdosmodelEnrollment_durationPlateCalculation_YearDOBhcc
2Jane541F3/25/2019CFHCC19
3Jude64355F4/25/2019AdultHHS_HCC019
4Jack74568M4/13/2019D1RXHCC31
5Robert852F4/25/2022ADULT7G20221/19/1960HHS_HCC008
6Mike95568M4/13/2023D1RXHCC31
7Jerry105759F3/5/2022CFHCC39
8Bruno1160M2/23/2023437
Command:
=epi.HCC_PROFILE_COMPARE(Claims!A1:A8,Claims!B1:B8,Claims!C1:C8,Claims!D1:D8,Claims!E1:E8,Claims!F1:F8,Claims!H1:H8,Claims!G1:G8,,,,,Coding!A1:A8,Coding!B1:B8,Coding!C1:C8,Coding!D1:D8,Coding!E1:E8,Coding!F1:F8,Coding!L1:L8,Coding!G1:G8,Coding!J1:J8,Coding!K1:K8,Coding!H1:H8,Coding!I1:I8,1,0)

Output Table:
ABCDEFGHIJKLMNOPQRS
1namememiddosagesexmodelverHCCs_1DemoRAF_1HCCRAF_1TotalRAF_1HCCs_2DemoRAF_2HCCRAF_2TotalRAF_2hcc_incrementhcc_increment_rafhcc_gapshcc_gaps_raf
2Jane5201965FCFv24_2019HCC190.380.090.47HCC190.380.090.4700
3Jude6201955FADULThhs_v05_2019HHS_HCC0550.3825.2525.634HHS_HCC0190.3820.5190.901HHS_HCC0190.462HHS_HCC055-5.252
4Jack7201968MD1v05_2019RXHCC186,RXHCC310.2610.4370.698RXHCC310.2610.270.5310RXHCC186-0.167
5Robert8202262FADULThhs_v07_2022HHS_HCC0210.3370.1010.438HHS_HCC0080.33722.66122.998HHS_HCC00822.661HHS_HCC021-0.101
6Mike9202368MD1v08_2023RXHCC186,RXHCC310.190.4530.643RXHCC310.190.2430.4330RXHCC186-0.21
7Jerry10202259FCFv24_2022HCC850.3620.4060.768HCC390.3620.5690.931HCC39,DISABLED_HCC390.569HCC85,DISABLED_HCC85-0.406
8Bruno11202385MCNv28_2023HCC380.6160.1540.77HCC370.6160.1540.77HCC37,-HCC3800
7. Disease Duration:
a) Disease Duration with DX:
ABCD
1dxveracutechronic
2F23, E1142, E1100v23_2018=epi.DX_ACUTE(A2, B2)=epi.DX_CHRONIC(A2, B2)
3F330, C770v24_2021=epi.dx_acute(A3, B3)=epi.dx_chronic(A3, B3)
Output for table (7.a)
CD
1acutechronic
2F23E1142,E1100
3J683F330,C770

b) Disease Duration with HCC:
ABCDE
1hccveracutechronichybrid
2HCC18, HCC169, HCC138v24_2019=epi.CC_ACUTE(A2, B2)=epi.CC_CHRONIC(A2, B2)=epi.CC_HYBRID(A2, B2)
3HCC19, HCC1v24_2022=epi.CC_ACUTE(A3, B3)=epi.CC_CHRONIC(A3, B3)=epi.CC_HYBRID(A3, B3)
Output for table (7.b)
CDE
1acutechronichybrid
2HCC169HCC138HCC18
3HCC1HCC19
8. Some more examples:
AB
1functionoutput
2=epi.CLEAN_DX("e11.9", "v24_2022")E119
3=epi.CC_DESC("HCC18")HCC18:Diabetes with Chronic Complications
4=epi.DX_DESC("E1111", "hhs_v07_2023")E1111:Type 2 diabetes mellitus with ketoacidosis with coma
5=epi.DX2CC("E1142", "hhs_v05_2021")HHS_HCC020,ED_11
6=epi.CC_RAF("HCC19", "V24_2019")0.092
7=epi.DEMO_RAF(,"v28_2023", "CN", 65, "F" )0.306
8=epi.CC_INFO("HCC17", ,"CF", 30)desc: Diabetes with Acute Complications; children: HCC18,HCC19; parents: ; RAF: 0.353
9=epi.CC_COMBINE("HCC56, HCC57", "v24_2022")HCC56,HCC57,gSubstanceUseDisorder_gPsych
10=epi.CC_DIFF("HCC19, HCC56","HCC17, HCC18, HCC55")adds: HCC17,HCC55; upgraded: HCC19,HCC56; downgraded: ; downgraded_to: ; deletes:
11=epi.CC_DIFF_RAF("HCC19, HCC56", "HCC17, HCC18, HCC55", "v24_2021","CPD",)0.211
12=epi.DX_INCREMENT("E119", "E1111")E1111,-E119
13=epi.CC_INCREMENT_RAF("HCC19, HCC56", "HCC17, HCC18, HCC55", "v23_2018","CPD",,,,)0.455
14=epi.CC_GAPS("HCC19, HCC85", "HCC55",,,,,,)HCC19,HCC85,DIABETES_CHF
15=epi.CC_GAPS_RAF("HCC19, HCC85", "HCC55",,"CF",18,)-0.563
16=epi.DX_INCREMENT("E119, F1110", "E1111, E1042, F1020")E1111,F1020,-E119,-F1110
17=epi.DX_INCREMENT_RAF("E119", "F10.14, E1151", "v28_2023", "CP", 10)0.147
18=epi.DX_GAPS("E119, I281", "E1111, E1042, F1020")I281
19=epi.DX_GAPS_RAF("E119, I281", "E1111, E1042, F1020", "v24_2020", "CP", 18)-0.35
20=epi.DX_DIFF("E119, F1110", "E1111, E1042, F1020")adds: E1111,F1020; upgraded: E119,F1110; downgraded: ; downgraded_to: ; deletes:
21=epi.DX_DIFF_RAF("E119", "E1111", "V24_2022", "CF", 70)0.195