Scheduling is not a workflow one normally associates with medical device connectivity. In some applications, scheduling is handled by software separate from the connectivity solution. Sometimes, scheduling is not done at all. In other applications, as we shall see, scheduling is so much a part of the broader workflow, that it’s hard to recognize as a scheduling task. Two illustrative aspects of scheduling will be discussed, scheduling for diagnostic modalities and scheduling for routine patient care tasks. Because it’s less understood (and frankly more interesting) we will look at scheduling for routine patient care tasks first.
Patient Care Task Scheduling
Patient care tasks encompass routine activities carried out by caregivers and/or aids. Examples of these routine tasks include vital signs collection, medication administration, bed turns (to avoid hospital acquired pressure ulcers, or HAPU), and respiratory circuit flushing (to avoid ventilator acquired pneumonia, VAP). These tasks must be completed at a predetermined frequency on a reliable basis or adverse events – including patient death – can result.Read More
Connectivity enabled medical devices send patient data right out of the medical device to a network, be it a body area network, cellular broadband network, home or enterprise network. The network then conveys this medical device data to databases and applications that store, display and manipulate the data. When a medical device is directly attached to a patient, there is no question as to which patient the device data belongs. As soon as the data leaves the actual medical device via the serial port or a network connection, the association of that data with a particular patient is no longer obvious.
Much of the data used in establishing and maintaining patient association or patient context comes from, or is stored in, the patient management database. Patient management workflow is an important enabling component in the overall connectivity solution and key to patient context management.
It is critical to reliably know that the data from a medical device belongs to a particular patient. If the data is not associated with any patient it’s worthless; should the data be associated with the wrong patient it could be deadly. When patient data from patient A is misidentified as belonging to patient B, patient A can miss out on a life saving clinical intervention that is mistakenly applied to patient B. In this example, patient A may die due to a lack of care, and patient B may be injured or die as a consequence of receiving some clinical intervention that is not needed and could be contraindicated. Consequently, safe and reliable patient association or patient context management is a foundational capability for virtually any medical device connectivity or interoperability solution.Read More
In a few short weeks, TCBI will be holding their 5th annual Medical Device Connectivity Conference in Herndon, VA (the Washington DC metro area), November 21-22. It seems like the first conference was only a year or two ago.
Medical device connectivity, or the more fashionable (and some might say, more descriptive) term interoperability, has both changed significantly and remained the same over these past 5 years. Lots has changed on the regulatory and HIT governance front. The FDA has issued guidance on mobile medical apps, wireless medical devices, and cyber security – just this year. The FDASIA report on regulating HIT was presented to the ONC, FDA and FCC.Read More
A key feature of all connectivity solutions is a database that includes all of the patients associated with the system’s medical devices. This is called a “patient census” or ADT (admission, transfer and discharge), much like the way a hospital’s ADT system manages patient demographics for the hospital information system or EMR. Also referred to as patient management data, these data often include: patient name and ID number (permanent medical record number, episode of care number, or both), current assigned location of the patient, and the device associated with the patient. Depending on the application, these data can also include more operational or clinical things like assigned caregivers, admitting and/or attending physician, admitting diagnosis and service unit. It is also possible that this operational or clinical data may be stored in a different file, separate from patient management.
Some workflows or systems queue up patient information prior to arrival or application of the medical device, while others capture or generate patient demographics when the medical device is first applied to the patient. In any event, the connectivity solution must capture patient demographics that are sufficient to ensure correct patient identification and possibly additional information that relates to the use of the medical device (e.g., body surface area – or the data to calculate it, weight, etc.) Common methods to capture patient demographics are an ADT interface and a method of manual data entry. In some cases, it may be practical to capture patient demographics at the same time the medical device is associated with a patient.
This workflow is being tackled first in this series of blog posts because it is a foundation used by most connectivity workflows. Patient management workflow should be one of the last set of requirements completed because it must support all the workflows to be included in the product. What follows, in no particular order, are a number of issues and considerations that fall under the patient management category.Read More
One of the biggest challenges for medical device makers developing connectivity solutions is to look beyond the connection itself and design an overall solution that provides good workflow. Medical device connectivity is workflow automation through the integration of medical devices and information systems. It is the scope and quality of the workflow automation in a connectivity solution that impacts users, and not just how the connections are technically implemented.
Besides meeting a growing list of market requirements, connectivity aims to deliver certain features and benefits. Typical examples include:
- Reduced user error by automating previously manual tasks – this can improve patient safety and outcomes
- Automating certain tasks make the resulting data available as it’s generated, rather than when users can get around to manually documenting it (if they don’t forget)
- Automated oversight, where the connectivity solution monitors and reports on the episode of care associated with the medical device can also improve patient safety and outcomes as well as improve staff productivity
- Making it efficient and simple to review retrospective and current medical device data to better make a diagnosis or gauge the efficacy of a therapeutic intervention