How to analyze potentially preventable complications in the inpatient setting

Healthcare organizations are increasingly using data analytics to better understand the impact of PPCs on patient outcomes, hospital costs and resource utilization. Recently, Solventum researchers published a study in Antimicrobial Stewardship & Healthcare Epidemiology examining differences in length of stay and cost for patients who experienced central catheter-related infections during an inpatient admission.

The study leveraged Solventum™ Potentially Preventable Complications Classification System not simply because the data were available, but because the methodology is particularly well suited for analyzing complications that develop during hospitalization

When evaluating hospital-acquired complications, it's critical to ensure the data are fit for purpose and that the patients being compared are truly comparable. This study demonstrates how PPC analytics can help healthcare organizations:

• Measure the impact of complications on length of stay and costs
• Account for patient severity and clinical complexity
• Differentiate hospital-acquired complications from conditions present on admission
• Identify opportunities for quality improvement and patient safety initiatives
• Better understand resource utilization across inpatient settings

Comparing patients who experience complications with those who do not may sound straightforward, but meaningful analysis requires careful consideration of patient acuity and clinical context.

The PPC methodology uses admission diagnosis-related groups (DRGs), discharge DRGs, and severity of illness levels to determine what occurred during a patient's hospital stay and to account for underlying clinical complexity. Additional clinical review is then applied to evaluate whether a complication could reasonably be considered potentially preventable based on factors such as:

• Time available for the complication to develop
• Relationship to services delivered during the hospitalization
• Existing comorbidities and clinical conditions

This approach helps create a more accurate framework for measuring potentially preventable complications and their impact on healthcare outcomes.

When evaluating the effect of complications on hospital length of stay and cost, admissions must be compared appropriately.

Patients who experience complications should be compared with similar patients who do not. This starts with comparing admissions involving the same procedures while accounting for severity of illness. Longer hospital stays or higher costs among clinically complex patients are not necessarily attributable to the care provided or to the complication itself.

The analysis also excluded community-acquired infections. Present-on-admission (POA) indicators played an important role in distinguishing infections that existed before hospitalization from those that likely developed during an inpatient stay.

Beyond POA status, patients also needed to remain hospitalized long enough for a complication to plausibly develop from a clinical perspective. With these safeguards in place, differences in outcomes can be more confidently associated with the complication being studied.

Using this methodology, the research team evaluated admissions that were at risk for central catheter-related infections and compared outcomes among patients who ultimately developed one.

The findings were significant.

On average, patients who acquired a central catheter-related infection:

• Stayed in the hospital approximately 40 days longer
• Incurred healthcare costs that were three to five times higher than comparable patients who did not experience the complication

The impact extends beyond financial considerations. Longer hospital stays can increase the burden on patients and families while consuming valuable clinical capacity and hospital resources.

While not every complication can be prevented, and some additional costs and days of care may be unavoidable, analyzing patterns and variation can help healthcare organizations identify meaningful opportunities for improvement.

This research highlights the importance of reducing central catheter-related infections and demonstrates how complication analytics can support patient safety efforts.

By examining the characteristics of patients who experience complications, healthcare organizations can identify procedures, departments or patient populations that may benefit from targeted quality improvement initiatives.

Although this study focused on a specific complication, the same analytical approach can be applied across a broad range of inpatient complications. Understanding where variation exists and how complications affect outcomes can help healthcare leaders:

• Improve patient safety
• Reduce unnecessary healthcare costs
• Optimize hospital resource utilization
• Increase capacity for patients who need care
• Support data-driven quality improvement programs

As healthcare organizations continue to focus on value-based care, leveraging robust complication analytics can help uncover actionable insights that lead to safer, smarter and more efficient care delivery.

Want to dive deeper? Read the study results here.

Shannon Garrison, MBA, MJ, is a health policy manager, clinical and economic research, at Solventum.

Laura Soloway, PhD, MPH, is a senior research scientist and data manager at Solventum.