Health Care Quality Assessment

Inpatient Quality Indicators (IQIs) are a set of measures developed at the national level by the Agency for Health Care Research and Quality (AHRQ) to provide a perspective on the quality of patient care given by hospitals. Quality of care is measured using: 1) in-hospital mortality for certain procedures and medical conditions; 2) utilization of procedures for which there are questions of overuse, underuse, or misuse; and 3) volume of procedures for which there is some evidence that a higher volume of procedures is associated with lower mortality. AHRQ spent years of research and analysis to define these indicators as measures of healthcare quality.

The quality of care indicators reported in this web site, are those IQIs that are measured using in-hospital mortality. Specifically, this web site focuses on the IQIs: Acute Myocardial Infarction (AMI), Pneumonia, Heart Failure and Acute Stroke - indicators that are used to measure hospital performance by taking into account the number of in-hospital deaths (mortality) from these conditions. Hospital specific mortality rates reported in this section show the number of deaths per 100 patients for each condition during hospitalization. Mortality is considered an Outcome of Care Measure.

Since 2009, the Department has been reporting on heart attack, pneumonia, heart failure and acute stroke mortality levels as part of the Outcome of Care Measurers. These indicators were recommended by the “The Governor's Commission on Rationalizing Health Care Resources” to create the “Hospital Performance Dashboard”.

The data comes from the New Jersey hospital discharge database also known as the Uniform Bill (UB) data. Hospitals submit these data to the State. Hospital discharge data provides patient level information that includes demographics characteristics, ICD-10 diagnosis and procedure codes, severity of illness, pre-existing conditions or comorbidities, length of hospital stays, outcome or status of patients upon discharge, insurance coverages, etc.

The IQIs Mortality rates in this report are calculated by applying the AHRQ IQIs Software to the hospital discharge (UB) data. The software is known for its strength in performing “risk-adjustment”. Risk-adjusted mortality rates are calculated by comparing the number of deaths expected in a particular hospital, and how many patients actually experienced death. Hospitals that treat sicker or older patients may be unfairly compared to other hospitals that treat patients in relatively better conditions. It is very important to make adjustments for differences in patient characteristics such age, sex, comorbidities, severity of illness, etc. so that hospitals may be compared fairly. For example, if a patient has a pre-existing chronic illness before admission to the hospital, this condition may increase the likelihood or risk of that patient not surviving the procedure or treatment. Advanced age is another example of a characteristic that may increase the risk of death.

The data in this web site shows hospital specific mortality rates for heart attack, heart failure, pneumonia, and stroke in all 71 hospitals in New Jersey. Statewide average mortality rates as well as national rates are also reported for purposes of comparison. The mortality rates presented in the table show the rate at which patients in a given hospital are likely to die from that condition. A rate is expressed as the number of deaths per 100 eligible patients.

Since 2008, hospitals have been reporting data on Present on Admission (POA) for each patient on their UB forms. Patients may have other illnesses and conditions (comorbidities) upon admission in addition to the health problem for which they were admitted. The POA indicator identifies these pre-existing conditions and those that occur during the hospital stay. This way, patients with the POA can be excluded from the rate calculation, when appropriate, so that performance comparison remains fair and balanced.

For details such as the total number of deaths (numerator), the total number of eligible discharges (denominator), observed and expected mortality rates and the 95% confidence intervals for the risk-adjusted rates, go to www.nj.gov/health/healthcarequality/health-care-professionals/quality-indicators/iqi.shtml and refer to Reports listed under IQI Supplements to the Hospital Performance Report. For more information on technical specifications and how rates are calculated, go to: www.qualityindicators.ahrq.gov/Modules/iqi_resources.aspx.

Note that for IQIs, lower numbers are better because they mean fewer deaths.

You can use this information to assess the quality of care inside a hospital, which is useful when making decisions about where to go for treatment. This information, however, is not intended to be used alone when making these decisions. Consider the results of all the different data sources that measure quality of care within a hospital. Most importantly, hospitals can use their IQIs rates to identify areas within the hospital that need improvement.

The footnote labels, "better than statewide average” and “worse than statewide average”, shown at the top of the table describe the interpretation of the IQI mortality rates in a meaningful way. These labels help identify hospitals that have better than average, average, or worse than average performances compared to the statewide performance, which is shown on the top row of the table and labeled “Statewide Rate.”

When a hospital’s rate is marked by a single asterisk, it means the hospital’s performance is better than the statewide average, meaning fewer deaths than the statewide average deaths for a given condition. Likewise, when a hospital’s rate is marked by double asterisks, it means the hospital’s performance is worse than the statewide average, meaning more deaths than the statewide average. When a hospital’s rate is not marked by an asterisk, it means the hospital’s performance is the same as or, similar to the statewide rate.

Hospital rates are determined after adjusting for the risk factors of their patients. A hospital’s rate is ‘worse than average’ if its 95% confidence interval falls completely above the statewide rate. By comparison, a hospital’s rate is ‘better than average’ if its 95% confidence interval falls completely below the statewide rate.

Some rates that appear very large are not marked as ‘worse than average’ while others that appear very small are not marked as ‘better than average’. The reason for such cases may be, that rates calculated from small numbers of events tend to have wider confidence intervals that make the statewide rate fall within the interval, giving the appearance of good performance by that hospital compared to a hospital whose rate is based on a higher volume.

[1] Centers for Disease Control and Prevention. Underlying Cause of Death, 1999–2018. CDC WONDER Online Database. Atlanta, GA: Centers for Disease Control and Prevention; 2018. Accessed March 12, 2020.