HTM data holds a treasure trove of information for hospital decision makers. To leverage it, you first have to clean up your CMMS
If you keep up with what is going on in the world of healthcare, you have no doubt heard the term “big data.” It generally refers to the massive amount of data stored in your facility’s electronic medical record (EMR) system—data amounts so massive that conventional database tools are not adequate to deal with the volume.
Healthcare technology management (HTM) departments have their own data systems, computerized maintenance management systems (CMMS), storing a seemingly infinitesimal amount of data compared to that of an EMR. However, we are storing way more data than we have ever had to deal with in the past. And the demand for HTM departments to produce meaningful information from our CMMS databases is rapidly growing.
We have always been professionals known for our technical skill and expertise. We must now more fully develop our skills to deal with our own big data. Effectively managing HTM inventory requires expanding our assumptions about how this data can be used while adopting new strategies to ensure accuracy and consistency.
The Capital Assets Inventory
“Inventory” refers to the assets held by the organization allowing the hospital to operate. Hospitals typically have a capital assets inventory managed by the finance department and a supply inventory managed by logistics. Most hospital departments have their own inventory of both fixed assets and supplies. HTM generally tracks its assets inventory in the CMMS, which is essentially a subset of the hospital’s capital asset inventory.
The hospital’s capital asset inventory is the one most important to executive management in your organization. It is used by the Centers for Medicare and Medicaid Services (CMS) to determine reimbursements for your hospital, and is closely monitored and governed by a number of specific guidelines and regulations too numerous to discuss in this article. The capital asset values and depreciation also show up on the hospital’s financial reports and can affect the hospital’s bond rating, which is used when a facility wants to borrow money for major expansion and renovation projects. It suffices to say that this inventory must be accurate.
In addition, The Joint Commission (TJC) requires hospitals to adhere to EC.02.04.01, EP2. which states, “The hospital maintains a written inventory of all medical equipment.” The inventory must therefore be periodically inventoried and audited to ensure its accuracy for patient safety and compliance purposes.
The Role of HTM Data
The CMMS is the key data system used by most HTM departments to manage their equipment assets. The HTM inventory has some general differences from the hospital’s overall capital asset inventory. First, we include all equipment regardless of its dollar value, while hospitals have a dollar threshold to define their capital. The minimum value for the hospital’s inventory could be anywhere from $500 to $10,000 or higher. Second, HTM would likely break down a device into its components for tracking, where the hospital inventory may only list the complete device.
HTM departments most commonly use this data to track preventive maintenance (PM) completion and open repair work orders. But an accurate, complete CMMS can—and should—serve as an important tool in several other ways.
Recall management. Patient safety is a major concern of all healthcare organizations. The book To Err is Human, published in March 2000, shone a bright light on how dangerous the hospital environment really is. The list of recalls and alerts produced by ECRI Institute gets longer each week. Technology has evolved to the point where we’re not just concerned with equipment hardware issues like we were in years past. Problematic software running on our equipment hardware has emerged as a major source of recalls and alerts. Being able to quickly identify whether or not you have affected hardware or software can be a real challenge for HTM departments. Keeping your CMMS up-to-date with accurate information can make locating these systems much easier.
Strategic equipment replacement planning and standardization. As hospitals’ capital funding gets tighter and tighter, making good, defensible investments in healthcare technology increases in importance. Forecasting when to replace or upgrade major systems is critical, as is undertaking efforts to better standardize existing equipment to improve patient safety and reduce expenses. HTM data is a vital source of information to help drive this process.
Decision Support. It should come as no surprise that hospital executive management requires the HTM department to provide good data to support any request for resources. The same goes for any other hospital department. HTM data can be used to support both short-term and long-range planning:
- Budget and staffing forecasting
- Department and individual training needs projections
- Alternate equipment maintenance strategies to meet TJC standards
- Disaster planning
- Service contract needs assessment and management
- Software upgrade management and forecasting
Keep It Clean
The HTM department may share its CMMS database with the central mobile equipment pool or other hospital functions with medical equipment assets. The more departments that share a common database, the less duplicate data entry required and the more consistent and accurate the data.
Data accuracy and completeness is absolutely vital in order to use the information for any of the previously mentioned functions. Imagine if you were asked by executive management for a list of equipment recommended for replacement, only to find out that some of the items on the list no longer existed in the organization. Apart from causing you embarrassment, it wouldn’t build confidence in the eyes of the executive team in your department’s ability to provide high-quality, actionable information from your data system. This could hamper your ability to be successful in any of the decision support scenarios listed above.
So how can you keep your data complete and accurate to prevent embarrassment? It’s not a task that comes without a good deal of forethought and work. The first step is to decide what data elements are truly necessary to generate the types of reports and information you need. In other words, don’t start out trying to solve world hunger if you only need to decide on what to eat for lunch. Making the project too big at the start may be frustrating and not meet your actual needs.
Your data set should include the following common data elements. (Note that this is not an exhaustive list.)
- Unique asset identification number
- Date of acquisition
- Acquisition cost
- Purchase order number
- Universal nomenclature
- Serial number
- Model number
- Model name
- Software revision
- Warranty expiration
- Owning department
- Estimated useful life
- Equipment location
Next, remember that lack of data consistency will result in “garbage in, garbage out.” Using multiple names or identifiers for the same item makes it impossible to generate comprehensive reports. Imagine that you want to generate a report on electric beds. But suppose the device descriptions found in the database included the following: Electric Bed; Bed, Electric; Elect Bed; Powered Bed; Bed, Elect, Powered; Patient Bed; Bed-Electric; Bed, Pat, Elect.
There are many more options, including simple misspellings, that would cause a search or report to produce incomplete data. I’ve always been a firm believer in one and only one person reviewing and managing all data input into the system. Imagine if you had 10 people in the department all entering information the way they think it should appear. The result would be absolute chaos!
Maintaining Data Accuracy
Once you’ve established a clean database, the next issue is how to you keep data accurate. Your database is not static; it’s constantly changing. If you’re in a large organization, equipment may be coming and going weekly, if not daily. Your hospital finance department has very tight control over the capital asset inventory it manages. There are typically strict processes that must be followed to remove old equipment from circulation. These processes should, but may not always, include HTM. You should review your hospital’s policy to ensure that notifying your department is among the required steps. If not, work with you finance department to make sure HTM is included so that any changes to equipment status can be updated in the CMMS.
One additional problem to consider is how to handle noncapital items (those with a cost below the hospital’s capital equipment threshold), which do not undergo the same level of scrutiny as capital items. These noncapital devices typically account for about 33% of your total inventory. They require you to have a close relationship with each department you support to ensure you are made aware when these items are disposed of. In my experience, this process isn’t as effective as it needs to be.
From time to time, you may need to conduct a physical inventory to ensure information on these noncapital items is up-to-date. This can be a time-consuming, challenging endeavor. Many of these devices are small, highly mobile, and can hide in desk drawers. I have found that reviewing your CMMS to determine the last time a device was physically handled by the department can provide some assurance the item still exists. If it hasn’t been seen in years, further investigation with the owning department is definitely warranted.
If your department is fortunate enough to have either an active or passive real-time locating system (RTLS) implemented, you are way ahead of most. In simple terms, the RTLS provides the current location or last-seen location of a device. That data can then be integrated into the CMMS. Whatever methods you use will require extensive communication with all your customers, hospital finance, and the department at your facility that manages disposal of equipment—typically, your logistics group.
Once your CMMS inventory is updated, you will need to regularly review the data for inconsistencies to ensure all data shows up in a query or report. As noted earlier, having multiple names or spelling for the same item will allow data to be missed, which jeopardizes the credibility of the information you’re trying to convey.
Now, how can we keep the data accurate as items continue to come in or out of the inventory? I’d first have a discussion with your CMMS vendor to see if options exist to integrate data from the CMMS and finance systems. This approach should reduce the amount of technician time spent performing inventory management and reduce the possibility of human error during data input. It also establishes a closed-loop system that will help ensure all your work wasn’t for nothing.
Finally, work with your CMMS vendor, hospital finance, and logistics to establish agreed-upon policies, procedures, and processes to ensure the integrity of your data and to protect the investment of time made by the HTM department staff.
Get to Know Your Vendor
All HTM departments large and small are feeling the pressure to maintain accurate inventory data to comply with TJC standards, help with forecasting capital plans, or answer other questions within their organization. The attention you have given data input and data management in the past will be a measure of how much work and effort you have ahead of you.
My recommendation is to start with your CMMS vendor to help determine what tools it has available to help you with this journey. I recently spoke to Hank Goddard, chairman and CEO of Mainspring Healthcare Solutions, to see what was on the horizon. He said that new features are being developed every day to support customers, from analyzing existing data to correcting and standardizing the data to maintaining it once all the work is complete. These reporting tools can provide better information to help you be a successful HTM department.
Developing your own tool set and skills—as an individual and a department—is necessary in this era of big data. Successful departments will reap the rewards of meeting or exceeding TJC requirements and will increase their visibility and influence in the eyes of hospital leadership. Good luck in your journey!
Dennis Minsent is president of Healthcare Technology Management Solutions. For more information, contact chief editor Jenny Lower at [email protected].
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Dennis makes a number of excellent points on the wealth of information hidden and lying dormant within many a CMMS. While the HTM community does indeed have a treasure trove and decades of potentially useful data – data does not become information – or better yet knowledge – without analysis. In and throughout science, such analysis typically involves the appropriate and correct use of classic inferential statistical tools, e.g., analysis of variance (ANOVA), multiple and logistic regression, etc. In contrast to simple descriptive statistics, i.e., those that are limited to the use of means and standard deviations, the inferential statistics allow us to test hypotheses, look for relationships, and most importantly ask questions; the answers to which may then lead us to new knowledge. Despite our collective volume of data, the HTM literature has very few, if any, studies that have rigorously and appropriately applied these inferential tools to the analysis of CMMS data. Let’s try to start changing this. The knowledge to be gained may be just what the community needs in order to take back dominion of how healthcare technology should be managed.
Dennis makes a number of excellent points on the wealth of information hidden and lying dormant within many a CMMS. While the HTM community does indeed have a treasure trove and decades of potentially useful data – data does not become information – or better yet knowledge – without analysis. In and throughout science, such analysis typically involves the appropriate and correct use of classic inferential statistical tools, e.g., analysis of variance (ANOVA), multiple and logistic regression, etc. In contrast to simple descriptive statistics, i.e., those that are limited to the use of means and standard deviations, the inferential statistics allow us to test hypotheses, look for relationships, and most importantly answer questions; the answers to which may then lead us to new knowledge. Despite our collective volume of data, the HTM literature has very few, if any, studies that have rigorously and appropriately applied these inferential tools to the analysis of CMMS data. Let’s try to start changing this. The knowledge to be gained may be just what the community needs in order to take back dominion of how healthcare technology should be managed.