Your facility needs to reduce the number of patient falls that occur in order to meet patient safety standards, such as the National Patient Safety Goals evaluated by the Joint Commission.
Conduct research about patient safety and preventing patient falls in the acute care setting.
Based on your findings, create a single guideline or procedure document (no more than 5-pages long) that your organization could implement to prevent falls for the general patient population. How would you extend your guideline/procedure to include these additional populations?
- The elderly and disabled
- Patients undergoing same-day surgery
Using Quality Measure Data to Identify Risks
The risk management function in health care organizations draws from the same sources of data, evaluation methodologies, and strategic goals as the quality improvement process. The American Society for Healthcare Risk Management is a resource that provides guidance and tools for assessing risk and preventing adverse incidents.
Clinical and administrative quality measure data are used to detect both the actual and potential risks to patient safety, and events that directly or indirectly cause harm. The evaluation of events lead to actions intended to educate staff, establish more efficient workflows, and improve communication so that errors or accidents are avoided. If an incident does occur, such as a “sentinel event” (defined by the Joint Commission as “an unexpected occurrence involving death or serious physical or psychological injury, or the risk thereof”) a detailed analysis is carried out to isolate the processes that were involved so that they can be redesigned. After processes are redesigned, quality and safety measure results are evaluated to determine if the actions taken were effective in reducing risks to patient safety.
Reducing medical errors and preventing serious reportable events are a major focus for external accrediting bodies (see the Joint Commission National Patient Safety Goals) and for value-based purchasing programs like CMS and other third-party payers. Some unexpected events, such as hospital-acquired infections, medication administration errors, and wrong-site surgeries can result in decreases in reimbursement if they occur in rates (or ratios) above established limits. Accrediting organizations and insurance companies require healthcare organizations to maintain specific patient safety measures or indicators to monitor rates of compliance with processes designed to prevent medical errors and detect patterns that could place certain populations at a higher risk for reportable events.
Primary data are the source of event reporting, since unexpected changes in a patient’s condition due to a health-care related injury or hazard is documented in the medical record. Health care facilities also use incident reporting forms to record the details of an event such as the time and place it occurred, the staff involved and the processes involved (such as medication administration or assisting a patient to a wheelchair). Some organizations utilize an automated surveillance program, where entries made into a computer application or electronic medical record module, trigger reviews by quality and risk management staff to determine if a serious reportable event occurred. The events can be reported electronically to external agencies that monitor patient safety. An example of an institution that is doing this type of reporting is the Florida Agency for Healthcare Administration.
- Excellent Website with resources discussing the relationship between patient safety, risk management, and quality improvement. https://www.ecri.org/Pages/default.aspx
Data vs. Information
Health care operations generate large amounts of primary and administrative data but often, the very authors (physicians, nurses, or mid-management) are not fully aware of the value of collecting and analyzing data beyond licensure and accreditation standards.
Data elements in themselves hold very little meaning until they are placed in context and relationships between data elements can be established. Through this process, the raw data is transformed into information from which conclusions are drawn. Doctors can learn about the effectiveness of using a certain cholesterol medication. The rehabilitation service can determine how quickly patients are scheduled for therapy after referrals are made. Department directors can submit budget proposals that demonstrate the need to add full time equivalents (FTEs) to handle the volume of patients. In other words, data needs to aid in making decisions and taking action.
Quality Measure Data
Quality measure data contributes to good decision-making and practical actions when it is transparent, or makes clear, what is being represented. This involves using statistical methods that aren’t too difficult to understand and won’t mislead the intended audience to draw incorrect conclusions. The data should also demonstrate a relationship between specific processes and outcomes, which is vital to informing and management about effectiveness and efficiency, and its impact on other organizational functions.
Process Measure Data
Process measure data provides the details on what is done and if it is appropriate for the situation. For example, compliance with the Acute Myocardial Infarction (AMI) clinical pathway will result in fewer patients experiencing complications requiring transfer to the intensive care unit. Following the pathway will also reduce the number of patients who suffer another MI within four weeks of discharge. The effectiveness of the process can be evaluated through process measures that monitor compliance at each step, or by the outcome (result). Process measures often represent the specific details needed to determine the cause and effects of certain actions.
Outcome Measure Data
Outcome measure data serves as a summary of processes, supporting the effectiveness or efficiency of processes. These data don’t provide as much detail, but the construct of the measures enables reviewers to “drill down,” or find the processes that contribute to the results. The outcomes data serve as a “snapshot” view of an organization’s performance and level of quality at a specific time, or can show trends over months or years. Outcomes data also helps organizations recognize when positive or negative patterns develop, so that corrective action is taken as quickly as possible. It should be noted that outcomes and process data are not analyzed separately, otherwise much of the meaning is lost and the true status of quality improvement cannot be readily determined.