ChatGPT. Certainly! Below is a SAS code that performs the steps outlined in Part A for the year 2013. Afterward, it merges the state means and standard deviations into the aha2013 dataset and determines the safety net status for each hospital, saving the result as aha_SN_2013 . The SAS macro %calcSN is also provided:
data aha2013;
/* Your code to read in the aha2013 data file */
set aha2013;
/* Step 1: Generate the variable 'year' */
year = year(dtbeg);
/* Step 2: Generate the variable 'TOTBDS' */
totbds = sum(genbd, pedbd, obbd, msicbd, cicbd, nicbd, nintbd, pedicbd,
brnbd, spcicbd, rehabbd, alchbd, psybd, snbd88, icfbd88, othlbd94, othbd94);
/* Step 3: Classify hospital size */
if totbds <= 200 then size = '0-200';
else if totbds <= 400 then size = '201-400';
else if totbds <= 600 then size = '401-600';
else if totbds <= 800 then size = '601-800';
else size = '801+';
/* Step 4: Classify hospitals into Hospital or Medical Center */
if index(upcase(mname), 'HOSPITAL') then type = 'Hospital';
else if index(upcase(mname), 'CENTER') then type = 'Medical Center';
/* Step 5: Generate the required variables */
prcntCharity = netcharity_ir / grsinprev_ir;
prcntMCdCharges = grsinpatmcd / grsinprev_ir;
prcntMCdDischarge = admmcd / admts;
run;
/* Step 6: Calculate state mean and standard deviation */
proc means data=aha2013 mean std;
var prcntCharity prcntMCdCharges prcntMCdDischarge;
where state = 'VA' and year = 2013;
output out=state_stats mean= state_mean std= state_std;
run;
/* Step 7: Merge state means and standard deviations into aha2013 */
data aha2013;
merge aha2013 state_stats;
by state year;
run;
/* Step 8-11: Determine safety net status */
data aha_SN_2013;
set aha2013;
array prcnt(*) prcntCharity prcntMCdCharges prcntMCdDischarge;
array std(*) state_mean_prcntCharity state_mean_prcntMCdCharges state_mean_prcntMCdDischarge;
array std_dev(*) state_std_prcntCharity state_std_prcntMCdCharges state_std_prcntMCdDischarge;
/* Step 12: Assign safety net status */
sn = 3; /* Default value for not safety net */
do i = 1 to dim(prcnt);
if prcnt[i] > (state_mean[i] + state_std[i]) then sn = 1;
else if prcnt[i] > state_mean[i] then sn = 2;
end;
drop i;
run;
%macro calcSN(datasetName);
data &datasetName;
set &datasetName;
/* Insert the code from Part A here */
run;
%mend;
/* Example of using the macro */
%calcSN(aha2013);
This code assumes that you have loaded the AHA data into the aha2013 dataset. Adjust the dataset name and variable names as needed based on the actual structure of your data. Additionally, make sure to customize the file paths for input and output as per your system configuration.
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