As both the battalion chief of my local ambulance and rescue squad and a business intelligence consultant, you can imagine that healthcare analytics are near and dear to me. Plus, living in the Philadelphia region, it's impossible to escape the news of numerous hospital closures every year. So at arcplan, I love working with hospitals and healthcare organizations to build reports and dashboards that track the metrics critical to their survival. All the way back in 2001, Paul Mango and Louis Shapiro of McKinsey & Company argued that hospitals are essentially a commodity business and therefore need to compete on the basis of operational efficiency. This sentiment rings true more than 10 years later, with skyrocketing medical costs, declining insurance reimbursements, and increased utilization by an aging population. Giving hospital executives (and physicians!) access to real-time data has never been more critical to hospital operations.
Hospital executives often report on financial, operational and clinical system metrics which are crucial to ongoing operations and management. The hospitals we've worked with often have an overarching goal to provide efficient, quality care to patients, and they need access to their existing data to make sure they are achieving that goal. Important metrics that roll up to the goal of "efficiency" include the average wait time for a hospital bed, physician productivity, nurse turnover rates and the cost per discharge. Metrics that roll up to a "quality" goal include average length of stay, re-admission rates and patient satisfaction. The only way to improve the quality and efficiency of care is to analyze current performance and identify areas for improvement.
One of arcplan's customers, the largest private operator of healthcare facilities in the world, came to us when they were focusing on efficiency. For more than 5 years, they have used an arcplan-powered business intelligence system (with data from Oracle Essbase and Teradata) to track key metrics and make decisions that improve efficiency of care – specifically in emergency rooms. All of their ERs needed to reduce wait times, shorten lengths of stay, and avoid people leaving the ER without care and treatment. The goal became to have every ER patient seen by a doctor within 45 minutes of arrival.
So what metrics do they track to achieve this goal? Here are a few examples:
- Patient Arrival: days and times patients arrive in the ER (good for pattern recognition, not necessarily real-time analysis)
- Provider Productivity: patient volume by physician; average time spent with patients
- Turnaround: turnaround time of CT exams, MRIs, and ancillary services; lab result wait times
- Bed Tracking: system to track which beds are vacated and when, so ER staff can prep patients for admission when rooms are about to open up
Lab results and CT exam turnaround are critical metrics to help hospitals avoid bottlenecks. If results take too long, then delays are experienced down the line – the waiting room fills up, patients wait longer – and it becomes difficult to catch up. Taking a look at the metrics tells hospital administrators, for example, to increase lab staff during peak periods to avoid delays. The same is true for patient arrival days and times – that information is tracked because ER arrivals can be somewhat predictable and should be staffed accordingly. One urban hospital may see maximum patient arrivals at 7:30am and 6:00 pm – equating to rush hour traffic – or an even number of patients from 11am to 11pm on Saturdays and Sundays. Administrators can plan for this and increase the efficiency of each ER department.
Critical to achieving our customer's goal was access to real-time data – what good would 2-month old data be to managing the current patient flow? This is something to keep in mind when deploying a BI system at your facility.
But what is efficient care without quality? Patient satisfaction is an important metric for our customer, as satisfied patients are more likely to return in the future (though the hope is that they don’t have to!), tell a friend or family member about their experience, etc. But it's important to recognize what the previously mentioned McKinsey report calls out:
“If medical care is largely a commodity, quality of care will only rarely distinguish a particular hospital, at least within a class of competing institutions in a given region…It is benefits such as short waiting times and fast turnarounds that can distinguish one hospital from another."
- Hospitals Get Serious About Operations, 2001
As costs rise and reimbursements do not, the volume of patients it takes to break even grows every year. Remaining efficient takes work and analysis as well as changes to staff behavior and mindsets, which can be encouraged by using objective data every day to make decisions about patient care and hospital operations.
Have questions or want to discuss your own hospital business intelligence initiative? Leave a comment!