Preventative IT Care for Healthcare Companies: 3 Strategies to Minimize Outages

IT is the backbone of any healthcare organization, and maintaining uptime is critical to all business and clinical processes. Yet, system degradations and outages still occur frequently, which not only affects business operations but could also impact the quality of patient care.

Despite vigilant healthcare, IT teams identifying and remedying issues efficiently continue to be a struggle. In a recent ServiceNow survey done in partnership with Healthcare Dive’s studioID, 64% of IT healthcare professionals said it had been somewhat to extremely difficult to manage system degradation and outages over the past two years.

A major part of the challenge with system outages is having the visibility to find and remedy issues. The majority of IT healthcare professionals surveyed (60%) indicated that it was somewhat to extremely difficult to identify where the problem was when something went wrong in their system. In addition, they noted that the primary remediation challenge was diagnosing the root cause of a service issue (54%).

However, healthcare organizations can’t afford to continue on with the status quo. The effect of having critical (and even lifesaving) technology down because of unplanned outages is simply too costly…

Understanding the cost of system degradations and outages

Many healthcare organizations have not (or can not) measure the cost of a system outage or degradation. According to the Ponemon Institute, the average total cost of unplanned outages for healthcare is $918,000.

Of course, your organization’s situation is unique, which is all the more reason it’s important to better understand how issues with your system affect the organization. Because once you understand exactly how much of an effect the issue is having, you may see that it’s not only worth investing in fixing the issue, but you’ll also have the data to help get stakeholder approval to do so.

How to measure the cost of system degradations and outages

The cost of system interruptions can be calculated in a number of ways. A few examples of common metrics are:

  • Medical staff downtime
  • IT hours expended
  • Loss of patient revenue

One of the primary reasons medical staff downtime is so important to measure when calculating cost, is that it’s often the most expensive resource, and they are also the ones most affected by the downtime.

“There are so many things healthcare professionals do within the EMR, and if it is an unplanned downtime issue, usually that is where a lot of frustration and unhappiness comes into play because they wouldn’t be able to work on what they’re trying to do. If they’re trying to look at the patient’s vital signs or order medication or see what medication their patients are on right now, or if they want to do a transfer or discharge or admit a patient, they can’t do any of those things.” – Dr. Noreen Butte, Physician Executive at Cerner Corporation

While you can use any of these metrics or a combination of metrics to measure the cost of system outages, you may also want to measure other factors to identify how severe an outage is. Respondents in the ServiceNow survey cited the number of users affected (78%), the amount of time a system is down (76%), and the number of locations affected (48%) as the main ways to determine how severe an issue is.

How to reduce costly outages

Ultimately, reducing the cost of outages is dependent on reducing the amount of time your system is down and the amount of time your staff and clinicians are unable to work because of the outage. Even in the case of planned downtime, some organizations fail to properly prepare.

Besides better preparing for planned and unplanned downtime, the cost of downtime can be reduced by limiting how often and for how long outages occur. Here are three strategies to help.

1. Use a single platform to monitor and manage your network

One of the main reasons it’s challenging to identify system issues or to diagnosis the root cause of an issue is that different parts of your IT are likely siloed in different domains. Even when a command center approach is taken to try to identify and remedy an issue, it can still take longer than it should.

Picture, for example, a technician doing routine maintenance on a CT scanner inadvertently introduced a misconfiguration. Over time, the device began to generate more and more network traffic until the entire network for that facility becomes nonfunctioning. While the organization had lots of disparate tools and data to help diagnose the issue, it will become overwhelming to sort through it all to isolate the problem. The technician and the part of the organization that was doing the maintenance had also never logged a change order.

2. Apply predictive intelligence to identify and remedy problems

A platform with built-in, predictive intelligence can also significantly reduce the number of outages and the time it takes to diagnose and remedy those that you do have.

With predictive intelligence, you can detect abnormalities as they occur, which allows you to automatically create an incident ticket or notify the right person to investigate the problem, helping resolve issues faster. And, over time, as you collect more and more data, you can apply predictive intelligence to automatically suggest articles or workarounds based on the trends or patterns you’re seeing. And, in some cases, the platform may even automate remedying some issues.

3. Leverage built-in dashboards

Besides bringing all your system data into a centralized location, you need a comprehensive dashboard that serves as an insights hub and provides your IT staff real-time visibility into your entire network, applications, and services.

A comprehensive dashboard should provide visibility in the following areas:

  • Service availability
  • Mean time to resolution for major and high-priority incidents
  • Duration and frequency of downtimes
  • The effect of the downtime on productivity
  • Normal operation versus abnormal

You should also ensure that your dashboard can incorporate predictive intelligence and is pre-configured to suggest knowledge articles and workarounds based on the issue.

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