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(15) The database contains the number of cases treated, the number of deaths, and the EMRs for each of 10 IQIs for the years 2009-2013.
We computed the 5-year overall RAMR and UTP across all IQIs for 196 hospitals.
To check this possibility, we fit a linear regression model using EMR (computed for each hospital across all IQIs and all years) as the dependent variable and the number of cases (over all IQIs and years) as the independent variable.
Finally, we estimated our models with four additional IQIs.
IQIs and PSIs are risk-adjusted hospital rates of mortality and patient safety events obtained from software that identifies the events based on ICD9-CM diagnoses and procedures noted in the patient's discharge record (Elixhauser, Pancholi, and Clancy 2005; Laditka, Laditka, and Cornman 2005).
The composite IQIs and PSIs were constructed from individual indicators.
The PSI and IQIs came from the CMS's Reporting Hospital Quality Data for Annual Payment Update fdes.
We were not able to compute every IQI and PSI for every hospital because not every hospital provided every service, so the sample sizes for the individual IQIs and PSIs ranged from 366 to 913.
We estimated the association between the risk-adjusted rates of the IQIs and PSIs and the percentages of the hospital discharges for Asian, black, and Hispanic patients.
Using weighted least squares regression, we estimated the association between the percentages of Asian, black, and Hispanic discharges and individual IQIs and PSIs.
To maintain an adequate sample size, we selected the following risk-adjusted IQIs and PSIs, which had at least 1,400 nonmissing observations (out of a sample of 1,459 urban hospitals in the 20 HCUP states that had nonmissing observations for the AHA variables of interest): mortality rates for acute myocardial infarction (AMI), congestive heart failure (CHF), stroke, gastrointestinal hemorrhage, and pneumonia; failure to rescue rate; iatrogenic pneumothorax rate; infection due to medical care rate, and accidental puncture or laceration rate.
In order that we might include a subset of quality indicators from the application of the Inpatient Quality Indicator (IQI) and Patient Safety Indicator (PSI) modules of the AHRQ Quality Indicator (QI) software (2) to inpatient data from the Healthcare Cost and Utilization Project (HCUP), (3) we restricted our analysis to 20 states (4) for which HCUP State Inpatient Databases (SID) (5) were available.
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