How Accurate Mortality Risk Measurement Improves Quality and Value

By more accurately reflecting a patient’s mortality risk, healthcare organizations can improve quality scores and drive greater value-based reimbursement.

Risk-adjusted mortality rates (RAMRs) are the metric that highlights the relationship between illness severity and death. Payers, providers, and patients have historically used these publicly reported performance measures to assess a healthcare organization’s care quality.

As the industry shifts from volume to value, the Centers for Medicare & Medicaid Services (CMS), as well as a number of commercial payers, are starting to consider RAMRs—along with other key quality measures, such as 30-day readmission rates and length of stay—when determining reimbursement. Depending on the payment arrangement, organizations that have low RAMRs can receive bonus payments and organizations having higher RAMRs may incur fines.

“Keeping RAMRs low is an essential step when pursuing risk-based payment arrangements,” says Brett Senor, MD, a practicing internal medicine hospitalist for Mission Health in Asheville, N.C. “Not only will a low rate demonstrate high quality but it can also enhance an organization’s chances for greater reimbursement and incentives. Plus, it can make an organization a more attractive partner in value-based models, such as accountable care organizations and patient-centered medical homes.”

Moving the Needle on RAMRs

While CMS and other payers use slightly different methodologies to calculate RAMRs, the basic concept is the same, and hospitals as well as physician practices can figure this metric on their own. “Basically, RAMRs take into consideration the relationship between observed and expected mortality—otherwise known as the O/E ratio,” says Senor. “If the O/E ratio is greater than one, it communicates the hospital has had more deaths than expected. Conversely, if the ratio is less than one, it means the hospital has had fewer deaths than expected.”

To keep RAMRs low, organizations can approach the O/E measure from both sides. First, they can address observed mortality by limiting the number of deaths that occur due to insufficient or inappropriate treatment. “Although this is important, the reality is that only about 5 percent of hospital mortality is due to poor patient care,” says Senor. “So, while organizations can and should pull together an assessment team to review incidents and make sure there is nothing that could have been done differently, this effort will most likely not have a  meaningful impact on RAMRs. To see greater change, organizations must review and fine-tune their expected mortality.”

Expected mortality predicts the amount of deaths based on patients’ illness severity. Items that can affect this metric include a patient’s primary diagnosis, acuity plus comorbidities, admit source, demographics, and secondary diagnoses.

“To generate the truest expected mortality rate, a healthcare organization has to fully describe and quantify illness severity and treatment,” Senor says. “Otherwise, the indicator can tell a misleading story, underrepresenting how sick the patient population is and what treatment is occurring to address that level of illness. Eventually, an imprecise expected mortality rate can put an organization at risk for lesser reimbursement and possible penalties.”

Senor highlighted the example of a hospital that has an O/E ratio of 12.0. “On first pass, this would appear to be a poor quality institution because the organization has a much higher mortality than expected,” Senor says. “However, when you look deeper, the organization has an observed mortality rate of 2—which is fairly standard—but an expected mortality of .167, which is extremely low given the acuity of the organization’s patients. After the hospital improves documentation specificity and pays more attention to possible comorbidities that could influence the primary diagnosis, the organization significantly increases its expected mortality and brings the O/E ratio down to less than one—demonstrating that its observed mortality is less than expected and highlighting the quality of care the organization provides.”

Strategies for Better Capturing Expected Mortality

While the secret to accurate RAMRs involves more precisely describing expected mortality, this process is often easier said than done. There are a few strategies to better describe expected mortality:

Establish a robust CDI program. As organizations plan for ICD-10 and other large-scale initiatives, they are starting to fine-tune their clinical documentation improvement (CDI) efforts. Any increase in accuracy and specificity should positively impact the verity of expected mortality. Strong leadership commitment as well as interactive, hands-on training and frequent auditing are required to drive a CDI program. “Organizations should also look at embedding tools within the electronic health record that encourage a high-level of detail and prompt physicians to consider all contributing factors,” Senor says.

Engage a physician champion. Underpinning any documentation improvement is the need for a strong physician leader to help promote the project and explain the benefits in terms physicians can appreciate. “Doctors often respond best to their peers and if there is an advocate that can effectively communicate the importance of better documentation and compel doctors to change their habits, the effort will be more successful.”

Stay vigilant on contributing secondary diagnoses. Organizations also should ensure they are aware of high-risk secondary diagnoses that can make a big difference in expected mortality. “Sepsis is probably the biggest one, as it is often missed in both diagnosis and documentation,” Senor says. “To impact observed mortality, clinicians need to learn to recognize sepsis earlier and begin treatment faster to prevent mortality. One way to do this is to employ a sepsis alert tool that outlines the signs and symptoms, allowing physicians to more reliably identify sepsis and proactively manage it. To affect expected mortality, organizations need to begin documenting sepsis as soon as it is diagnosed to accurately capture the severity of illness.”

Other frequently overlooked conditions that can also amp up patient acuity include protein calorie malnutrition, dementia, and diabetes complications.

Access related tool: Common Mortality Risk Variables

One Step Closer to Value-Based Care

While there are many things organizations can do to lay the groundwork for quality-driven payment models, getting a handle on the  RAMR rate and making sure it correctly reflects your organization’s quality is key to painting the best picture, communicating your value, and readying yourself for new payment opportunities.

Kathleen B. Vega is a freelance healthcare writer and editor who contributes regularly to HFMA Forums.

Interviewed for this article: Brett Senor, MD, is an internal medicine hospitalist as well as ICD-10 chair/advisor for Mission Health in Asheville, North Carolina.

Discussion Starters

Forum members: What do you think? Please share your thoughts in the comments section below.

• How do you monitor your RAMR rates?
• Have you made any changes in your CDI program to improve identification of mortality risk?