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Reducing CAUTI Costs and Data Integration Systems

  • Category: CAUTI
  • Published: Thursday, 15 November 2018 19:22
  • Written by Health Pro
  • Hits: 705

Any discussion on Reducing CAUTI Costs must first include a summary of how to calculate CAUTI Costs in the first place. According to the Center for Disease Contro and Prevention (CDC), they define CAUTI rate as


The CAUTI rate per 1000 urinary catheter days is calculated by dividing the number of CAUTIs by the number of catheter days and multiplying the result by 1000. The Urinary Catheter Utilization Ratio is calculated by dividing the number of urinary catheter days by the number of patient days. DCenters for Disease Control and Prevention (CDC)


CAUTI Defined

Reducing CAUTI Costs Cauti stands for catheter-associated urinary tract infection. It is an infection that occurs in patients admitted in a hospital. It is one of the most common infections that patients can get from being in the hospital. It can be quite difficult to diagnose a CAUTI infection especially when the patient has been hospitalized for a while.

Its symptoms could be mistaken for symptoms of other illnesses the patient is suffering from. In elderly people, changes in their mental state or confusion can be signs of a CAUTI. There are a number of things that can lead to a CAUTI infection. It happens when fungi or bacteria enter the urinary tract via the catheter and then they multiply and leads to an infection.

According to Healthline, there are a number of ways infection can occur during catheterization. The symptoms of CAUTI and the ways the infection can occur are listed below

Symptoms of CAUTI

  • cloudy urine
  • blood in the urine
  • strong urine odor
  • urine leakage around your catheter
  • pressure, pain, or discomfort in your lower back or stomach
  • chills
  • fever
  • unexplained fatigue
  • vomiting


Ways CAUTI infection can occur

  • the catheter may become contaminated upon insertion
  • the drainage bag may not be emptied often enough
  • bacteria from a bowel movement may get on the catheter
  • urine in the catheter bag may flow backward into the bladder
  • the catheter may not be regularly cleaned
  • Clean insertion and removal techniques can help lower the risk of a CAUTI. Daily catheter care is required as well. Catheters shouldn’t be left in longer than needed, as longer use is associated with a higher risk of infection.


Data Integration and Calculating CAUTI Costs

Bi-Directional Sync Data Integration

Bi-directional sync data integration is the process of combining two data sets. There are many ways to combine data sets but in a bi-directional sync, the data is combined while still being allowed to exist in their different originating data sets. Using bi-directional data sync to share a dataset will enable healthcare organizations to use both systems while maintaining a consistent real-time view of the data in both systems. In a healthcare organization, a bi-directional data sync can enable them to run smoothly and calculate real-time costs for different items and that, of course, includes CAUTI costs.

With a bi-directional sync, a healthcare organization can have the data representations be much closer to reality in both systems and reduce the compound cost of having to manually address the inconsistencies, lack of data or the impact to your business from letting the inconsistencies exist. On the other hand, you can use bi-directional sync to take you from a suite of products that work well together but may not be the best at their own individual function. A bi-directional sync is useful for object representation in a comprehensive and consistent form.

For example, a doctor can have a single view of a patient's records even though they are a combination of data from two different departments or even hospitals. Or if a patient needs treatment in a small area and the nurse does not need to know about the patients' whole health history this system will help with that. It’s also what helps businesses display customer information without displaying some sensitive parts of it like their credit card number or date of birth. Even though the data is present, a bi-directional sync ensures that only data relevant to the user can be accessed.

Reducing CAUTI Costs

Correlation Data Integration

A data correlation system is one that identifies the intersections of two sets of data and automatically carries out a bi-directional synchronization of the data sets within its scope. This is similar to how the bi-directional pattern synchronizes the union of the scoped dataset, but instead, a correlation synchronizes the intersection. If a dataset exists in both systems and is a repetition a correlation system helps synchronize them. This kind of systems helps make away with redundancies which can have huge cost effect sometimes.

Imagine making the same purchase twice because data was entered more than once, it could lead to a dent in the operating cost of a healthcare organization. So a correlation system helps prevent errors like this from happening. The correlation pattern will not care where those objects came from; it will agnostically synchronize them as long as they are found in both systems. This system is also useful when two departments in a healthcare organization need to access the same data and also share data.

For example, a hospital group has two hospitals in the same city. You might like to share data between the two hospitals so if a patient uses either hospital, you will have an up to date record of what treatment they received at both locations. A correlation system makes do away with the need to maintain two systems and stores the data in one synchronized system. The correlation system is only valuable when it is only bi-directionally synchronizes the objects on a “Need to know” basis rather than always moving the full scope of the dataset in both directions. As already evident from the points above a correlation system helps to cut costs. This includes the cost of calculating CAUTI costs by making the cost of acquiring and storing the data cheaper. It saves a lot of effort that could be spent on integrating reports and data or separating them.