A Microcomputer Program (sf36.exe) that Generates SAS Code for Scoring the SF-36 Health Survey

Dixon DRU-1437-PI AbstractThis paper describes a microcomputer that can be used to generate SAS code that for scoring SF-36 Health Survey, one of the most widely used measures of health-

A Microcomputer Program (sf36.exe) that Generates

SAS Code for Scoring the SF-36 Health Survey

Ron D Hays, Cathy D Sherbourne, Karen L Spritzer, Wil J Dixon

DRU-1437-PI

AbstractThis paper describes a microcomputer that can be used to generate SAS code that for scoring SF-36 Health Survey, one of the most widely used measures of health-related quality of life today The generated SAS code scores the 8 SF-36 scales as well as the SF-36 physical and mental health composite scores In addition, the program produces code that provides US general population normative scores, age and gender adjusted to one’s sample The significance of the difference between the sample and the general population on each SF-36 scale score is also generated Example input and output files are included Selected SF-36 publications are cited The SF-36 Health Survey items are given in the Appendix

A Microcomputer Program (sf36.exe) that Generates

SAS Code for Scoring the SF-36 Health Survey

The SF-36 taps eight health concepts: physical functioning, bodilypain, role limitations due to physical health problems, role limitationsdue to personal or emotional problems, emotional well-being, socialfunctioning, energy/fatigue, and general health perceptions It alsoincludes a single item that provides an indication of perceived change

in health These 36 items were adapted from longer instruments

completed by patients participating in the Medical Outcomes Study (MOS),

an observational study of variations in physician practice styles andpatient outcomes in different systems of health care delivery (Hays &Shapiro, 1992; Stewart, Sherbourne, Hays, et al., 1992)

Scoring the Eight SF-36 Scales

We recommend that responses be scored as described below (the RAND method) A somewhat different scoring procedure for the pain and general health scales was advocated by New England Medical Center (NEMC)

investigators (Ware, Snow, Kosinski,, & Gandek, 1993) Although only our scoring recommendations for these scales are described here, the SAS program generator we provide scores these two scales both ways.Pain scale scores scored the RAND versus NEMC way correlated 0.99 inthe MOS, with a mean difference of 3.33 (NEMC scoring yields lower pain scores on average) General health perception scale scores also correlated 0.99 in the MOS, with a mean difference of -1.37 (NEMC scoring yields higher general health scores on average) For further information about the scoring differences, see Hays, Sherbourne, and Mazel (1993)

Scoring the SF-36 is a two-step process First, pre-coded numericvalues are recoded per the scoring key given in Table 1 Note that allitems are scored so that a high score defines a more favorable healthstate In addition, each item is scored on a 0 to 100 range so that thelowest and highest possible scores are set at 0 and 100, respectively.Scores represent the percentage of total possible score achieved Instep 2, items in the same scale are averaged together to create the 8scale scores Table 2 lists the items averaged together to create eachscale Items that are left blank (missing data) are not taken into

account when calculating the scale scores Hence, scale scores

represent the average for all items in the scale that the respondentanswered If all items in a scale are missing, then the scale score is also missing

Example: Items 20 and 32 are used to score the measure of social

functioning Each of the two items has 5 response choices However, a

high score (response choice 5) on item 20 indicates extreme

limitations in

social functioning, while a high score (response choice 5) on item 32indicates the absence of limitations in social functioning To score bothitems in the same direction, Table 1 shows that responses 1 through 5 for

item 20 should be recoded to values of 100, 75, 50, 25, and 0,

respectively Responses 1 through 5 for item 32 should be recoded tovalues of 0, 25, 50, 75, and 100, respectively Table 2 shows that thesetwo recoded items should be averaged together to form the socialfunctioning scale If the respondent is missing one of the two items, the

person's score will be equal to that of the nonmissing item

Table 3 presents information on the reliability, central tendencyand variability of the scales in the MOS when scored using this

method

To use the enclosed programs, it is necessary to have a SAS datasetwith

the SF-36 items in it The program, sf36.exe, is used in combination

with your SAS file of SF-36 items to create SAS code for scoring theSF-36 scales

In addition to having a SAS dataset with SF-36 items, you need tocreate an ASCII file that specifies the variable names you have

assigned to

the 36 SF-36 items in your study When sf36.exe is executed, you will

be asked for the name of the input file: WHAT FILE CONTAINS THE INPUT SETUP?

Notice that the input file (sf36.in) consists of a list of 36 variable

names, each entered on a separate row beginning in column one (see Table 4) The variable names need to be listed to correspond with the order of items presented in the Appendix For example, the first item reads "In general, would you say your health is: Excellent, Very good, Good, Fair, Poor?" On the first row of the input file, you should list the variable name you assigned to this item You need to list the actual SAS names used for your data set so that the generated SAS code will include rename statements linking your SAS names to the SAS names used in the generated code (the generated code uses names I1

through I36 following the order of items in the Appendix)

If you use the same SAS names as assumed in the program (I1 through

I36), you can use the sf36.in file (see Table 4) as the input file when you execute sf36.exe If you use different SAS names, you will have to

create a

file that reflects these differences (see sf36.ex, Table 5, for an example

of a

different input file) Note that you should not use the variable names I1 through I36 for variables other than the SF-36 items or SAS will not

be able to distinguish the SF-36 items from these other variables

The program assumes that your dataset includes a continuous measure

of AGE (named "AGE") and a gender variable called "MALE" (coded 0

=

female, 1 = male)

The sf36.exe program produces a file, sf36.sas, that contains SAS

code for scoring the sf-36 scales For the pain and general health scales, both the RAND and NEMC scoring are provided Scale scores are created for persons that answer any of the items in a scale (Note that NEMC only creates scores for person who answer half or more of the items in a scale.)

The SAS code in sf36.sas assumes that the name of the SAS

dataset

that includes the SF-36 items is "TEMP" (see SET TEMP in the

generated

SAS code) If your file has a different name, you should change this

part of the sf36.sas file to reflect that Note that a raw data file,

sf36.raw, is also produced and that this file is read by sf36.sas when

it is run This raw data file includes information about US general

population means and standard deviations (Ware et al., 1993)

Example of Using sf36.exe

Table 5 provides an example of an input file, sf36.in2, for sf36.exe

In this example, the SF-36 items were assigned the SAS names T1 through T36 in the study in which they were used The input file is read by sf36.exe and this information is used in creating the file,

sf36.sas, shown in Table 6

Scoring the SF-36 Physical and Mental Health Composite

Scores

Running sf36b.exe will produce SAS code, saved as sf36add.sas,

that will create T-scores for the 8 SF-36 scales (using the US general population norms) In addition, physical and mental health composite scores for the SF-36 (Ware, Kosinkski, & Keller, 1994) and the SF-12

(Ware, Kosinski, & Keller, 1995, 1996) are produced The sf36add.sas

file

can be appended to sf36.sas for analyses of the SF-36 scales and composite scores Running the resulting sf36.sas file yields the output

shown for the sample data shown in Table 7

The output includes descriptive statistics for the 8 SF-36 scales and

US general population norms, age and gender adjusted to your

sample The SF-36 SAS names used are as follows:

PHYFUN10 Physical functioning in your sample

PFISFM Physical functioning in general population

ROLEP4 Role limitations physical in your sample

RPSFM Role limitations physical in general population

PAIN2 Pain in your sample RAND scoring

SFPAIN Pain in your sample NEMC scoring

BPSFM Pain in general population

GENH5 General health in your sample RAND scoring

SFGENH5 General health in your sample NEMC scoring

GENSFM General health in general population

EMOT5 Emotional well-being in your sample

MHSFM Emotional well-being in general population

ROLEE3 Role limitations emotional in your sample

RESFM Role limitations emotional in general population

ENFAT4 Energy in your sample

ENFTSFM Energy in general population

SOCFUN2 Social function in your sample

SFSFM Social function in general population

Table 7 illustrates the output of means, standard deviations,

minimum and maximum values for each of these scales Note that only the mean values are provided for the general population values (PFISFM, RPSFM, BPSFM, GENSFM, MHSFM, RESFM, ENFTSFM, SFSFM), because the standard deviations and ranges produced by SAS for these scales are not relevant (i.e., These variances and ranges

because they are based on mean scores derived from age and gender subgroups of the general population, and are not the general

population estimates of these statistics)

In addition to the descriptive statistics, sf36.sas provides t-statistics

(asymptotically z-statistics) for the significance of the difference

between

SF-36 scores in the sample compared to the US general population

(ZPHY10, ZRP, ZBP, ZGENH, ZENFT, ZSF, ZRE, ZMHI) Finally, sf36.sas

outputs SF-36 scale scores for the sample, corresponding T-scores for each scale, and the physical (AGG_PHYS) and mental health

(AGG_MENT) composite T-scores The sample size and descriptive statistics provided here may differ from the prior output, because in the prior output respondents are omitted if they have missing data on age or gender (these variables are needed to adjust the general

population values to one’s sample)

For further information please contact either:

Ron D Hays or Cathy D Sherbourne

RAND RAND

1700 Main Street 1700 Main Street

P.O Box 2138 P.O Box 2138

Santa Monica, CA 90407-2138 Santa Monica, CA 90407-2138

(310) 393-0411 Ext.7581 (Voice) (310) 393-0411 Ext 7216 (Voice) (310) 393-4818 (FAX) (310) 393-4818 (FAX)

Ronald_Hays@rand.org Cathy_Sherbourne@rand.org

Selected SF-36 Publications (Including Those Cited Above)

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Table 1 STEP 1: RECODING ITEMS ITEM NUMBERS Change original response category

2 - > 50

3 - > 100 13,14,15,16,17,18,19 1 - > 0

Table 2 STEP 2: AVERAGING ITEMS TO FORM SCALES

Scale Number Of After Recoding Per Table 1, Average The

Following Items:

Physical functioning 10 3 4 5 6 7 8 9 10 11 12 Role limitations due to physical health 4 13 14 15 16

Role limitations due to emotional

Table 3 RELIABILITY, CENTRAL TENDENCY AND VARIABILITY OF SCALES

IN THE MEDICAL OUTCOMES STUDY

Role Functioning/physical 4 0.84 52.97 40.78 Role Functioning/emotional 3 0.83 65.78 40.71

Note Data is from baseline of the Medical Outcomes Study (N = 2471), except for

Health change, which was obtained one-year later.