In the wound care arena ways to better treat wounds based on data trends are nothing new. Currently, we measure length, width, and depth weekly to assess the effectiveness of treatments and interventions. The collection of this raw information is then analyzed utilizing a graft system to identify if the wounds are progressing, stalling, or not responding. A new trend emerging to help collect better quality data is the use of electronic measuring photo software. This software is readily available and most cell phones have the capability today. In any data collection process, the accuracy and quality of the information is key to gaining knowledge and transforming that into patient-directed interventions. “ ‘Garbage in – garbage out is a colloquial recognition of poor quality data entry leading to unreliable data output. The information collected needs to be highly accurate otherwise data analytics, applications or business process will be unreliable”(Kilkenny & Robinson, 2018, p. 1). The technology that is being developed will reduce human errors and lead to better outcoming and statistical data. “The latest smartphone cameras enable high-resolution videos that could be leveraged to reconstruct 3D models of wounds and accurately calculate the depth of a wound. In order to utilize this feature, the clinician takes a 5–15 second video of the wound in addition to the standard photo”(Madu, 2020, p. 26). The risk as with any protected health information is a breach of the data acquired. Although minimal information is used in the pictures there is still a chance of exposure and litigation if leaked or stolen. Therefore there must be strict policies in place to mitigate the risk. Such policies include removal of pictures daily, no stored data outside a secured server, staff education on proper identification with minimal use of health care patient information. This is one health care technology trend I think is promising and could see great benefit in the wound care field. The programs and systems need to be fully vetted and 2 integration efforts need to be made so that the information can easily flow into all medical records moving forward. Some challenges to this technology are the variability and training of staff on how to take pictures, taking pictures on rounded surfaces are challenging, software cost, and upgrades(Shetty et al., 2012, p. 1). I think the use of this new technology will absolutely improve patient outcomes and better direct patient treatments and interventions. This technology on a large scale and integrated with thousands of other patients’ measurements can help begin to trace trends in healing. This one data point can then be used with other data points including dressing selections, dietary control, offloading to predict treatments that can be used for evidence-based practice. Healthcare Information Technology Trends
Kilkenny, M. F., & Robinson, K. M. (2018). Data quality: “garbage in – garbage out”. Health Information Management Journal, 47(3), 103–105. https://doi.org/10.1177/1833358318774357
Madu, T. (2020). How Data Analytics Is Evolving. Todays Wound Clinic, 26–27. https://s3.amazonaws.com/HMP/hmp_ln/imported/2020-07/26-27_TWC0720_Madu.pdf
Shetty, R., Sreekar, H., Lamba, S., & Gupta, A. (2012). A novel and accurate technique of photographic wound measurement. Indian Journal of Plastic Surgery, 45(02), 425–429. https://doi.org/10.4103/0970-0358.101333
The use of infrared cameras to monitor and diagnose wounds has changed wound care as we know it. While wounds are not my thing, I do agree technology has come a long way in checking for tunneling, or wounds that re not visible to the naked eye. Point of care wound technology allow for data to be transmitted from an infrared camera into wound apps to better treat the patients. “The Swift Wound app provides highly reliable and accurate wound measurements. The FLIR™ infrared camera integrated into the Swift Wound app provides skin temperature readings equivalent to the clinically tested reference thermometer. Thus, the Swift Wound app has the advantage of being a non-contact, easy-to-use wound measurement tool that allows clinicians to image, measure, and track wound size and temperature from one visit to the next. In addition, this tool may also be used by patients and their caregivers for home monitoring.” (Wang, S. C., et. al.) My facility in the last year just started to use the infrared cameras and they are linked to our EMR to track data. But being able to use an application for in home health or to help monitor our patients seems like a great way to improve outcomes. Healthcare Information Technology Trends
Wang, S. C., Anderson, J. A. E., Evans, R., Woo, K., Beland, B., Sasseville, D., & Moreau, L. (n.d.). Point-of-care wound visioning technology: Reproducibility and accuracy of a wound measurement app. PLOS ONE. https://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0183139.
I haven’t heard of this technology yet, but it sounds awesome! Not that clinicians are making a large number of mistakes, but anytime that a software system can scan a wound and track and trend this data for progression, stalled, or regression of a wound would drastically eliminate human error. This greatly improves the accuracy of reporting. In completing research on this topic, I came across an article by Wang et al. (2017), that discussed the formation of a wound care application called Swift Wound app. This app performs the same functions that you spoke of, as well as assessing wound/peri-wound temperature. Like you stated, the company would need strict policies on this, but one option could be the company provides a phone with this capability to the wound care department. The phone would need to be docked every night and left within the department. This phone could be encrypted by the IT department as an added layer of protection. Bruce et al. (2014), notes that client devices are mostly poorly protected and could represent a weak-point to the corporate network. Healthcare Information Technology Trends
Bruce, N., Jang, W. T., & Lee, H. J. (2014). An embedded encryption protocol for healthcare networks security. International Journal of Security and Its Applications, 8(2), 139-144. https://dx.doi.org/10.14257/ijsia.2014.8.2.14.
Wang, S. C., Anderson, J. A. E., Evans, R., Woo, K. Beland, B., Sasseville, D., & Moreau, L. (2017). Point-of-care wound visioning technology: Reproducibility and accuracy of a wound measurement app. PloS One, 12(8), 1-14. https://doi.org/10.1371/journal.pome.0183139. Healthcare Information Technology Trends