Calculating Measures of Comorbidity Using Administrative Data

1
Calculating Measures of Comorbidity Using
Administrative Data

• Vicki Stagg
• Statistical Programmer
• Department of Community Health Sciences
• Dr. Robert Hilsden
• Associate Professor
• Departments of Medicine and Community Health
  Sciences
• Dr. Hude Quan
• Associate Professor
• Centre for Health and Policy Studies (CHAPS)
• Department of Community Health Sciences
• University of Calgary
• Calgary, Alberta, Canada

2
Background

• Medical Administrative Data
• Inpatient hospital visit information
• Comorbidity
• Pre-existing diagnosis / additional complication
  of admitted patient
• Comorbidity Index
• For measurement of burden of disease and case-mix
  adjustment
• Allows for stratification or adjustment by
  severity of illness
• Two common tools Charlson and Elixhauser
• Clinical Conditions
• International Classification of Disease
• 9th Revision, Clinical Modification (ICD-9-CM
  codes)
• 10th Revision (ICD-10 codes)

3
Algorithms included in ado programs

• Charlson (17 comorbidity definitions)
• Presence/absence, weighted sum (Charlson index)
• Charlson index developed to predict risk of
  one-year mortality from comorbid illness
• (J Chron Dis, 198740(5)373-383)
• Deyo modification for ICD-9-CM
• (J Clin Epi, 199245(6)613-619)
• Quans Enhanced ICD-9-CM
• Quans ICD-10
• (Medical Care, 200543(11)1130-1139)
• Elixhauser (30 comorbidity definitions)
• Presence/absence, sum
• (Medical Care, 199836(1)8-27)
• Quans Enhanced ICD-9-CM

4
Algorithms development of ICD-10 enhanced
ICD-9-CM

• ICD-10 comorbidity coding algorithm
• Based on Charlson index
• Swiss, Australian, Canadian collaborative groups
• ICD-10 Canadian version (ICD-10-CA)
• Enhanced ICD-9-CM coding algorithm
• Back-translated from new ICD-10 coding algorithm
• To improve original Deyo (Charlson) and
  Elixhauser comorbidity classifications

5
Charlson Comorbidities with Corresponding
ICD-9-CM and ICD-10 Codes(Medical Care.
2005431130-1139)
6
Example coding algorithm
Comorbidity Deyo Enhanced ICD-10
Myocardial infarction 410.x, 412.x 410.x, 412.x I21.x, I22.x, I25.2
Congestive heart failure 428.x 398.91, 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 404.91, 404.93, 425.4-425.9, 428.x I09.9, I11.0, I13.0, I13.2, I12.5, I42.0, I42.5-I42.9, I43.x, I40.x, P29.0
(Medical Care, 200543(11)1130-1139)
7
Charlson Comorbidities Weights
CHARLSON COMORBIDITY ASSIGNED WEIGHTS
1. Myocardial infarction 1
2. Congestive heart failure 1
3. Peripheral vascular disease 1
4. Cerebrovascular disease 1
5. Dementia 1
6. Chronic pulmonary disease 1
7. Rheumatic disease 1
8. Peptic ulcer disease 1
9. Mild liver disease 1
10. Diabetes without chronic complication 1
11. Diabetes with end organ damage 2
12. Hemiplegia / paraplegia 2
13. Renal disease 2
14. Any malignancy/lymphoma/leukemia 2
15. Moderate or severe liver disease 3
16. Metastatic solid tumor 6
17. AIDS/HIV 6
8
Input data

• Patient demographic data
• ID variable (string) required if multiple visits
• Comorbidity diagnoses codes (strings)
• Charlson
• ICD-9-CM / ICD-10
• Elixhauser
• ICD-9-CM / ICD-10
• Additional medical information
• For subsequent modeling, if desired

9
Syntax

• Charlson
• charlson varlist if exp in range,
  index(string) idvar(varname) diagprfx(string)
  assign0 wtchrl cmorb noshow
• by may be used with charlson
• Elixhauser
• elixhauser varlist if exp in range,
  index(string) idvar(varname) diagprfx(string)
  smelix cmorb noshow
• by may be used with elixhauser

10
Input options

• index (string)
• ICD-9-CM (charlson) c
• Enhanced ICD-9-CM (charlson/elixhauser) e
• ICD-10 (charlson/elixhauser) 10
• idvar(varname)
• Required when multiple records per patient
• diagprfx(string)
• Gives common root of the comorbidity variables
• Necessary only when varlist not used
• assign0
• Only applicable to charlson
• Flag to apply hierarchical method

11
Output options

• wtchrl (charlson command)
• Presents summary of Charlson Index (frequencies
  of weighted sums)
• wtelix (elixhauser command)
• Displays frequencies of sum of elixhauser
  comorbidities
• cmorb
• Displays frequencies of individual comorbidities
• noshow
• Controls display of chosen options

12
Sample program 1 charlson (Enhanced
ICD-9-CM Algorithm)

• Input data (ICD-9-CM codes) -

Small Sample Data Small Sample Data Small Sample Data Small Sample Data
patientid diag1 diag2 diag3
id1 39891 5834 342
id2 0930
id3 2500 2507
id4 342 2500 3441
id5 3441 342
id6 2500 5722
id7 5722 196
id8 042
id9 V427 4561
id10 176 197 V427
13
Sample program 1 charlson

• Command
• . charlson, index(e) diagprfx(diag) wtchrl cmorb

14
Sample program 1 charlson Output (part 1)

• (Option noshow omitted)

(0 observations deleted) COMORBIDITY INDEX
MACRO Providing COMORBIDITY INDEX Summary OPTIONS
SELECTED INPUT DATA Enhanced
ICD-9 OBSERVATIONAL UNIT Visits ID VARIABLE NAME
(Given only if Unit is Patients) PREFIX of
COMORBIDITY VARIABLES diag HIERARCHY METHOD
APPLIED NO SUMMARIZE CHARLSON INDEX and WEIGHTS
YES SUMMARIZE INDIVIDUAL COMORBIDITIES
YES Please wait. Thank you! Program takes a few
minutes - there are up to 3 ICD codes per
subject. Iteration 1 of 3 - Program is running -
Please wait Iteration 2 of 3 - Program is running
- Please wait Iteration 3 of 3 - Program is
running - Please wait Total Number of
Observational Units (Visits OR Patients) 10
15
Sample program 1 charlson Output (part 2)
CHARLSON INDEX Freq.
Percent Cum. -----------------------------
------------------ 1 1
10.00 10.00 2 1
10.00 20.00 3 2
20.00 40.00 4 2
20.00 60.00 5 1
10.00 70.00 6 1
10.00 80.00 9 2
20.00 100.00 -------------------------------
---------------- Total 10
100.00 GROUPED CHARLSON INDEX
Freq. Percent Cum. --------------
--------------------------------- 1
1 10.00 10.00 2
9 90.00 100.00 -----------------
------------------------------ Total
10 100.00 Variable Obs
Mean Std. Dev. Min
Max ---------------------------------------------
------------------------ charlindex 10
4.6 2.716207 1 9

• (option wtchrl)

16
Sample program 1 charlson Output (part 3)

• (option cmorb)
• selected comorbidities displayed

Diabetes Freq. Percent
Cum. --------------------------------------------
--- Absent 7 70.00
70.00 Present 3 30.00
100.00 ------------------------------------------
----- Total 10 100.00
Diabetes Complicatio ns
Freq. Percent Cum. -------------------
---------------------------- Absent
9 90.00 90.00 Present
1 10.00 100.00 ----------------------
------------------------- Total
10 100.00
17
Output dataset describe
obs 10
vars 41 17
Oct 2007 1008 size 1,880 (99.9 of
memory free) -------------------------------------
------------------------------------------
storage display value variable name
type format label variable
label --------------------------------------------
----------------------------------- id
str23 23s diag1
str5 9s diag2
str4 9s diag3
str4 9s ynch1
float 9.0g ynlab AMI (Acute
Myocardial) ynch2 float 9.0g
ynlab CHF (Congestive Heart) ynch3
float 9.0g ynlab PVD (Peripheral
Vascular) ynch4 float 9.0g
ynlab CEVD (Cerebrovascular ynch5
float 9.0g ynlab Dementia ynch6
float 9.0g ynlab COPD (Chronic
Obstructive
Pulmonary) ynch7 float 9.0g
ynlab Rheumatoid Disease ynch8
float 9.0g ynlab PUD (Peptic
Ulcer) ynch9 float 9.0g ynlab
Mild LD (Liver) ynch10 float 9.0g
ynlab Diabetes ynch11 float
9.0g ynlab Diabetes
Complications ynch12 float 9.0g
ynlab HP/PAPL (Hemiplegia or
Paraplegia)
18
Output dataset describe continued
ynch13 float 9.0g ynlab RD
(Renal) ynch14 float 9.0g ynlab
Cancer ynch15 float 9.0g
ynlab Moderate/Severe LD (Liver) ynch16
float 9.0g ynlab Metastic
Cancer ynch17 float 9.0g ynlab
AIDS weightch1 float 9.0g
weightch2 float 9.0g
weightch3 float 9.0g
weightch4 float 9.0g
weightch5 float 9.0g
weightch6 float 9.0g
weightch7 float 9.0g
weightch8 float 9.0g
weightch9 float 9.0g
weightch10 float 9.0g
weightch11 float 9.0g
weightch12 float 9.0g
weightch13 float 9.0g
weightch14 float 9.0g
weightch15 float 9.0g
weightch16 float 9.0g
weightch17 float 9.0g
charlindex float 9.0g
CHARLSON INDEX grpci float 9.0g
GROUPED CHARLSON INDEX ----------------
--------------------------------------------------
------------- Sorted by Note dataset
has changed since last saved
19
Output dataset selected variables
. list id ynch10 ynch11 ynch15
------------------------------------
id ynch10 ynch11 ynch15
------------------------------------ 1.
id1 Absent Absent Absent 2. id2
Absent Absent Absent 3. id3
Present Present Absent 4. id4
Present Absent Absent 5. id5
Absent Absent Absent
------------------------------------ 6.
id6 Present Absent Present 7. id7
Absent Absent Present 8. id8
Absent Absent Absent 9. id9
Absent Absent Present 10. id10
Absent Absent Absent
------------------------------------
. list id weightch10 weightch11 weightch15, c
------------------------------ id
we10 we11 we15 --------------------
---------- 1. id1 0 0 0
2. id2 0 0 0 3.
id3 1 2 0 4. id4 1
0 0 5. id5 0 0
0 ------------------------------ 6.
id6 1 0 3 7. id7
0 0 3 8. id8 0 0
0 9. id9 0 0 3
10. id10 0 0 0
------------------------------
20
Output dataset Charlson index grouped
Charlson index
. list id charlindex grpci
------------------------- id
charlix grpci -------------------------
1. id1 5 2 2. id2
1 1 3. id3 3 2
4. id4 3 2 5. id5
2 2 -------------------------
6. id6 4 2 7. id7
9 2 8. id8 6 2
9. id9 4 2 10. id10
9 2 -------------------------
21
Program rerun with assign0 option (changes
frequencies)

• . comorbid, index(e) diagprfx(diag) wtchrl cmorb
  assign0

CHARLSON INDEX Freq.
Percent Cum. -----------------------------
------------------ 1 1
10.00 10.00 2 2
20.00 30.00 3 2
20.00 50.00 4 1
10.00 60.00 5 1
10.00 70.00 6 1
10.00 80.00 7 1
10.00 90.00 9 1
10.00 100.00 -------------------------------
---------------- Total 10
100.00 GROUPED CHARLSON INDEX
Freq. Percent Cum. --------------
--------------------------------- 1
1 10.00 10.00 2
9 90.00 100.00 -----------------
------------------------------ Total
10 100.00
------------------------- id
charlix grpci -------------------------
1. id1 5 2 2. id2
1 1 3. id3 2 2
4. id4 3 2 5. id5
2 2 -------------------------
6. id6 4 2 7. id7
9 2 8. id8 6 2
9. id9 3 2 10. id10
7 2 -------------------------

22
Selected comorbidities revisited-
Diabetes Freq. Percent
Cum. --------------------------------------------
--- Absent 8 80.00
80.00 Present 2 20.00
100.00 ------------------------------------------
----- Total 10 100.00
Diabetes Complicatio ns
Freq. Percent Cum. -------------------
---------------------------- Absent
9 90.00 90.00 Present
1 10.00 100.00 ----------------------
------------------------- Total
10 100.00
23
Sample program 2 elixhauser (ICD-10
Algorithm)

• Input - real inpatient data -

obs 2,987
vars 43 18
Oct 2007 1018 size 1,000,645 (90.5 of
memory free) -------------------------------------
------------------------------------------
storage display value variable name
type format label variable
label --------------------------------------------
----------------------------------- dx1
str6 9s DIAG1 dx2
str6 9s DIAG2 . . .
dx24 str6 9s
DIAG24 dx25 str6 9s
DIAG25 cdr_keyforqshe long 12.0g
CDR_KEY (for QSHI use) admitdate
str20 20s Admit
Date dischargedate str20 20s
Discharge Date acutelosdays int 8.0g
ACUTE LOS (days) birthdate
str11 11s Birth Date age
int 8.0g AGE pc
str6 9s PC residence
str7 9s
RESIDENCE entrycodetohol str61 61s
ENTRY CODE to hospital strokediagtypa
str25 25s Stroke Diag Type
when Stroke
not the Main Diag gender long
8.0g gender gender site
long 8.0g site site stroketype
long 13.0g stroke Stroke
type disposition long 60.0g disp
discharge disposition cohort float
9.0g cohort cohort --------------------
--------------------------------------------------
---------
24
Sample program 2 elixhauser

• Command
• . elixhauser dx1-dx25, index(10) smelix cmorb

25
Sample program 2 elixhauserOutput
ELIX COMORBIDITY SUM
Freq. Percent Cum. -------------------
---------------------------- 0
402 13.46 13.46 1
715 23.94 37.40 2
751 25.14 62.54 3
529 17.71 80.25 4
303 10.14 90.39 5
174 5.83 96.22 6
71 2.38 98.59 7
30 1.00 99.60 8
10 0.33 99.93 9
1 0.03 99.97 10
1 0.03 100.00 -----------------------
------------------------ Total 2,987
100.00 Variable Obs
Mean Std. Dev. Min
Max ---------------------------------------------
------------------------ elixsum 2987
2.216605 1.621281 0 10
26
ELIXHAUSER COMORBIDITY PERCENT
Congestive Heart Failure 8.20
Cardiac Arrhythmias 22.23
Valvular Disease 4.49
Pulmonary Circulation Disorders 1.77
Peripheral Vascular Disorders 5.49
Hypertension, Uncomplicated 58.49
Paralysis 25.68
Other Neurological Disorders 23.84
Chronic Pulmonary Disease 7.20
Diabetes, Uncomplicated 15.80
Diabetes, Complicated 4.08
Hypothyroidism 3.85
Renal Failure 4.69
Liver Disease 0.77
Peptic Ulcer Disease Excluding Bleeding 0.40
AIDS/HIV 0.13
27
continued
ELIXHAUSER COMORBIDITY PERCENT
Lymphoma 0.57
Metastatic Cancer 1.61
Solid Tumor Without Metastasis 2.98
Rheumatoid Arthritis/Collagen Vascular 1.47
Coagulopathy 2.68
Obesity 3.31
Weight Loss 0.67
Fluid and Electrolyte Disorders 6.46
Blood Loss Anemia 0.50
Deficiency Anemia 1.31
Alcohol Abuse 3.35
Drug Abuse 0.74
Psychoses 0.50
Depression 4.59
Hypertension, Complicated 3.82
28
Acknowledgements

• I would like to express sincere gratitude to
• Dr. Robert Hilsden
• Depts. of Medicine/ Community Health Sciences, U
  of Calgary
• For supervising this work and for all his advice
  and support.
• Dr. Hude Quan
• Centre for Health and Policy Studies
• Dept. of Community Health Sciences, U of
  Calgary
• For providing the SAS code and databases and for
  his support.
• Haifeng Zhu
• MSc Graduate Student
• Dept. of Community Health Sciences
• For her assistance with converting the
  Elixhauser algorithms to Stata.
• Malcolm Stagg
• Student, Vista Virtual School, Calgary AB
• My son, for his help with preparing this
  PowerPoint presentation and all his
  encouragement.

29
SUGGESTIONS / COMMENTSWELCOME

• vlstagg_at_ucalgary.ca
• Thank you!