A hidden solution to the hospital capacity crisis

As a physician and the chief medical officer at Solventum, I spend a lot of time thinking about the immense pressures facing our healthcare systems. We often hear about bed shortages and long waiting times in observation unit settings. Many systems are now discussing building more beds. But what if a powerful solution to the hospital capacity crisis isn't only about building more, but about improving the quality of care within the walls we already have?

For decades, we intentionally reduced the number of inpatient beds, driven by the shift toward effective outpatient care and shorter lengths of stay. This seemed manageable until the pandemic exposed deep vulnerabilities. We now face a functional shortage of staffed beds, worsened by workforce attrition and a projected 10% increase in hospitalizations over the next decade.

Many facilities are now approaching or have surpassed the 85% occupancy threshold – a critical point where efficiency drops and patient safety can be compromised. The common reaction is to call for building more, an expensive solution at roughly half a million dollars per new bed. But, our team at Solventum wanted to look deeper at excess utilization attributable to potentially preventable quality defects.

Uncovering preventable events in our busiest hospitals

To understand the nature of this demand, our research team embarked on a study. We focused on eight major U.S. cities with a high concentration of academic medical centers: DC, Baltimore, New York City, Boston, Cleveland, Philadelphia, Los Angeles, and Chicago. Bed shortage concerns have been particularly concentrated in cities with multiple academic health centers. Analyzing Medicare data from approximately 80 hospitals in these areas, we compared their performance against a risk-adjusted national average.

The results were revealing.

We found that these prominent medical centers had an 11% higher severity adjusted average length of stay than the national average. When we dug deeper, the story became even clearer. Forty percent of excess days were associated with potentially preventable events.

The leading drivers of inefficiency

What were these preventable events? Two factors accounted for 60% of these avoidable days:

1. Hospital readmissions: Patients returning to the hospital shortly after discharge were the single largest contributor.
2. In-hospital complications: These are events that occur during a patient's stay, such as a fall or a hospital-acquired infection, which prolong their time in the hospital.

These aren't just statistics; they represent real challenges for patients and massive strains on hospital resources. It suggests that by focusing on getting care right the first time, we can significantly improve hospital capacity, enhance patient safety and advance the goals of value-based care all at once. This isn't about discharging patients prematurely; it's about delivering care so effectively that they can go home safely and stay home.

Turning data into actionable healthcare analytics

Identifying a problem is one thing; solving it is another. Since you can't fix what you can't measure, using analytics to find where opportunities lie is critical. Three focus areas:

• Benchmark performance: To help you see how you're doing against anonymized peer groups. You can compare your performance to other urban, rural, or academic hospitals to set a realistic and meaningful baseline for quality improvement.
• Drill own to specifics: A hospital-wide readmission rate is too broad to be actionable. Consider tools that allow you to pinpoint opportunities with precision. Is the challenge in cardiology or orthopedics? Is it with a specific procedure or physician group? This level of detail helps you focus your quality improvement resources where they will have the greatest impact.
• Identify positive outliers: Analytics isn't just about finding problems. It’s also about finding successes. Perhaps your interventional radiology department has an outstandingly low complication rate. By understanding what they are doing differently – whether it’s their perioperative process or their discharge instructions – you can replicate that success across other service lines.

The growing role of AI in healthcare

Looking forward, AI in healthcare is making this process even more powerful. We are innovating with predictive analytics to help hospitals move from retrospective review to proactive intervention. AI can help answer critical questions like: Which patients are at the highest risk for readmission? What is the next best action to prevent a complication?

AI is also simplifying the analytics process itself. Instead of complex queries, leaders can ask natural language questions and get immediate, understandable reports. This democratizes data, putting powerful insights into the hands of the people who can use them to drive change on the front lines. It’s a key part of making benchmarking a dynamic, continuous process rather than a static annual report.

More nights at home, not in a hospital

A few years ago, the Minnesota Hospital Association ran a campaign with a simple, powerful goal: more nights for patients in their own beds, not hospital beds. This vision perfectly captures the human side of our work. Reducing hospital readmissions and preventable complications isn't just an operational goal. It's a win for patients who can recover in the comfort of their homes. It's a win for clinicians who can feel more confident in the care they provide. And it's a win for health systems which can serve more people effectively.

To dive deeper into this topic, check out this video interview with DOTmed.

For more information about the hospital bed capacity study referenced above, visit hfma.org. 

Sandeep Wadhwa is global chief medical officer for Solventum.