Welcome to part three of this learning activity module, CAF PCI registry metric 39, PCI in-hospital risk-adjusted acute kidney injury, all patients. My name is John Giroud and I will be narrating this lesson. Acute kidney injury after PCI is a common and serious complication of the procedure. It is associated with an increased risk of myocardial infarction, dialysis, and death. Even small increases in serum creatinine have been associated with increased hospital length of stay. Acute kidney injury prediction and prevention should be a priority for participants because therapeutic options are limited once AKI develops. Metric 39 is helpful in providing risk-adjusted feedback on AKI, informing clinical decision-making and directing the use of strategies to avoid AKI and improve the safety of PCI procedures. The objectives for this learning module are to discuss and define what is post-PCI acute kidney injury, analyze and apply a systematic approach in understanding metric 39 and utilize the e-reports dashboard metric feedback. In lesson three, we will utilize the e-reports dashboard, which provides a detailed analysis of a hospital's individual performance and gives insight into care variations and quality improvement opportunities. We will then apply this information through a case scenario. The e-reports dashboard provides a streamlined centralized location to assess the facility's metric performance. It provides the user the ability to view metric details and the ability to drill down into the metric. The dashboard also provides patient detail information to evaluate individual patients and evaluate the procedure details. The dashboard allows the ability to filter data for a better understanding of the patient and procedure characteristics, as well as provider treatment patterns and facility processes. When reviewing facility performance and metric performance is worse than expected, don't immediately assume that it is a problem with the quality of your program or with a specific operator. We recommend not looking at only one year or one quarter of data. Rather, metric performance that reveals a durable undesirable trend may be more indicative of an area that is deserving of additional focus of quality improvement efforts and initiatives. When reviewing facility performance, assess the quality of data submitted to the registry and ask yourself the following two questions. Has data for all of the reporting periods been submitted? Was a green benchmark inclusion status achieved for all reporting periods? This is important because green status is necessary in order for the data to be included in the benchmark and comparison group statistics. We encourage you to look at the patient level detail report on the dashboard as it provides important feedback on individual patients. The patient level detail report or drill down provides feedback on individual patients eligibility for inclusion or exclusion in the metric. The drill down also provides feedback on each patient's predicted probability of AKI and displays each individual patient risk factor utilized by the model. When performance in the metric isn't as expected, the facility should review the patient detail report and ask the following questions. Is there a high number of patients who did not meet the risk model eligibility? If so, it may make sense to review. Is data being captured consistently and accurately when multiple people are coding? If multiple people are coding, do the coders all have the same understanding of the coding instructions and target value of the data elements used by the risk model? The risk model expects some patients to have AKI. The goal of a risk model is not simply to exclude patients but to accurately predict their risk of AKI. Eligible patients are assigned a predicted probability of having AKI based on patient variables. Each eligible patient's predicted probability then provides the facility overall expected AKI rate. Because the metric only looks at eligible patients, when there are a high number of patients who did not meet model eligibility, this may impact the facility's overall expected AKI rate. Remember that detail line 4880, expected AKI, represents what the model predicted as the AKI rate for the facility. Based on risk factors for each eligible patient's predicted probability of AKI. When metric performance is not as expected, it is important to consider if the patient's risk profile on the patient drill down matches the risk profile in the medical record accordingly. If it does not, there may be opportunities to improve either abstract or understanding of the data elements and target values, provider documentation, or both. As discussed in lesson one, the patient level drill down provides feedback on eligible patients. Eligible patients will receive a predicted probability of AKI value based on the coding and capturing of patient variables used by the risk model. This is the patient's risk profile of the patient's condition prior to the start of the PCI procedure. The drill down should be reviewed to ensure that data is being captured accurately and consistently. Let's now move on to our case scenario for this lesson. The registry site manager notes an increasing AKI rate pattern. The facility is having more AKI than the model and metric is expecting. And the question is, should the registry site manager consider performing a self-audit to ensure that the data is being captured consistently? Number one, no. Or number two, yes. And the answer is number two, yes. The registry site manager should perform a self-audit to ensure that data is being captured accurately and correctly. The value of a self-audit in this circumstance is that it might indicate that there is inconsistent coding, either under or over coding of a patient's risk variables. Education to improve precise data capture is encouraged. This concludes lesson three of CAPPS V2. This concludes lesson three of CAPPCI Registry Metric 39 PCI in Hospital Risk-Adjusted Acute Kidney Injury All Patients. Thank you for your participation.

acute kidney injury

percutaneous coronary intervention

cardiovascular risk

CAF PCI registry

e-reports dashboard