Risk-adjusted outcomes in Medicare inpatient nephrectomy patients

Risk-adjusted outcomes of inpatient medicare medical admissions

It is important that actual outcomes of care and not surrogate markers, such as process measures, be used to evaluate the quality of inpatient care. Because of the heterogenous composition of patients, risk-adjustment is essential for the objective evaluation of outcomes following inpatient care. Comparative evaluation of risk-adjusted outcomes can be used to identify suboptimal performance and can provide direction for care improvement initiatives.We studied the risk-adjusted outcomes of 6 medical conditions during the inpatient and 90-day post-discharge period to identify the opportunities for care improvement. The Medicare Limited Dataset for 2012 to 2014 was used to identify acute myocardial infarction (AMI), chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), pneumonia (PNEU), cerebrovascular accidents (CVA), and gastrointestinal hemorrhage (GIH). Stepwise logistic predictive models were developed for the adverse outcomes (AOs) of inpatient deaths, 3-sigma prolonged length-of-stay outliers, 90-day post-discharge deaths, and 90-day readmissions after unrelated events were excluded. Observed and predicted AOs were determined for each hospital with ≥75 cases for each of the 6 medical conditions. Z-scores and risk-adjusted AO rates for each hospital permitted comparative analysis of outcomes after adjusting for covariance among the medical conditions.There were a total of 1,811,749 patients from 973 acute care hospitals with the 6 medical conditions. A total of 41% of all patients had ≥1 AO events. One or more readmissions were identified in 29.8% of patients. A total of 64 hospitals (6.4%) were 2 standard deviations better than the mean for risk-adjusted outcomes, and 72 (7.4%) were 2 standard deviations poorer. The best performing decile of hospitals had mean AO rates of 35.1% (odds ratio = 0.766; 95% confidence interval (CI) CI: 0.762-0.771) and the poorest performing decile a mean AO rate of 48.5% (odds ratio = 1.357; 95% CI: 1.346-1.369). Volume of qualifying cases ranged from 670 to 9314; no association was identified for increased volume of patients (P < .40).Risk-adjusted AO rates demonstrated nearly a 14% opportunity for care improvement between top and suboptimal performing hospitals. Hospitals must be able to benchmark objective measurement of outcomes to inform quality initiatives.

Inpatient and 90-day post-discharge outcomes in elective Medicare spine fusion surgery

BACKGROUND CONTEXT

Elective spine surgery is a commonly performed operative procedure, that requires knowledge of risk-adjusted results to improve outcomes and reduce costs.

PURPOSE

To develop risk-adjusted models to predict the adverse outcomes (AOs) of care during the inpatient and 90-day post-discharge period for spine fusion surgery.

STUDY DESIGN/SETTING

To identify the significant risk factors associated with AOs and to develop risk models that measure performance.

PATIENT SAMPLE

Hospitals that met minimum criteria of both 20 elective cervical and 20 elective non-cervical spine fusion operations in the 2012-2014 Medicare limited dataset.

OUTCOME MEASURES

The risk-adjusted AOs of inpatient deaths, prolonged length-of-stay for the index hospitalization, 90-day post-discharge deaths, and 90-day post-discharge readmissions were dependent variables in predictive risk models.

METHODS

Over 500 candidate risk factors were used for logistic regression models to predict the AOs. Models were then used to predicted risk-adjusted AO rates by hospitals.

RESULTS

There were 874 hospitals with a minimum of both 20 cervical and 20 non-cervical spine fusion patients. There were 167,395 total cases. A total of 7,981 (15.9%) of cervical fusion patients and 17,481 (14.9%) of non-cervical fusion patients had one or more AOs for an overall AO rate of 15.2%. A total of 54 hospitals (6.2%) had z-scores that were 2.0 better than predicted with a median risk adjusted AO rate of 9.2%, and 75 hospitals (8.6%) were 2.0 z-scores poorer than predicted with a median risk-adjusted AO rate of 23.2%.

CONCLUSIONS

Differences among hospitals defines opportunities for care improvement.