CoRPS

Projects We Care 2021

Published: 10th November 2021 Last updated: 16th September 2022

We Care makes funds available annually for research projects in which physicians and scientists work together. Ten projects were awarded funding in 2021.

Summary of the We Care 2021 projects

PREPARE study

prof. dr. Steffen Pauws PDEng, TSHD

dr. Guus Schoonman, neurology (ETZ)

For successful shared decision-making, it is important that health care providers understand the patient's perspective on his/her medical problem. After a visit to the family physician, patients receive a referral to the hospital via a digital message. This referral letter is the starting point of a clinical pathway. The central idea of this project is to ask patients to add comments to the referral letter so that their opinions, values, preferences and expectations can be recorded in the electronic patient record (EPR). These are then brought to the attention of hospital health care providers. Next, this study looks at the impact of these comments on patients' decision-making.

Researchers are conducting a randomized study in at least four clinical departments. For two months, patients digitally comment on the referral letter from their primary care physician. For a two-month control period, the referral letter is not added to the patient's comments. Within a week of the initial consultation at the hospital, patient and caregiver are asked to complete questionnaires that address:

1. The effort required to prepare for the consultation;
2. the degree of involvement on the patient perspective during the consultation;
3. patient confidence and satisfaction with respect to shared decision-making;
4.  caregiver satisfaction.

Implementation of an optimized AI model for the detection and monitoring of osteolytic bone lesions

dr. Sharon Ong, TSHD

dr. Gorkem Saygili, TSHD

dr. Maarten Heres

During the project in We Care Round 1, a deep learning model was developed for detection and segmentation of osteolytic lesions in CT scans.  These lesions are characteristic of multiple myeloma (Kahler's disease). The results of this first small-scale project were sufficiently motivating to investigate further optimization of this Artificial Intelligence (AI) tool.

In the follow-up project, this model will be further developed with more advanced and efficient algorithms and additional CT datasets. By applying automatic segmentation and identification of the skeleton, the researchers aim to create a detailed anatomical map of the locations of the lesions. In addition, an automated recording tool is being developed to monitor lesions on follow-up scans. This would allow the evaluation of treatment for patients with Kahler disease.

The improved model should then be validated and integrated into the hospital's work process. Radiologists and physician assistants will be involved in the evaluation of the algorithm. Deep-learning algorithms can lead to false detections and therefore need to learn from experts. Therefore, we will develop a hybrid Physician-AI framework to allow the algorithm to learn from corrections made by the radiologists.

Evaluation study on use of E-health application for rehabilitation pathway of bone fracture patients

Tineke Broer, TLS
dr. Koen Lansink, trauma surgery

In this study, researchers evaluated the decision aid 'Recovery from a broken bone', which is used in the ETZ and Amphia. The decision aid contains information on what a bone fracture is, the healing process, possible complications, various treatment options during admission, the recovery process and what patients themselves can contribute to recovery. In addition, the patient is asked to provide information about his/her situation before the accident and how the patient is doing at the time of completion (shortly before a check-up visit to the treating specialist).

The aim of this project is to use in-depth research to find out how and to what extent a decision aid can help patients to make their own decisions and what the subjective experience of patients is in relation to a decision aid. For the study, researchers use interviews with patients and care providers and observations of outpatient clinic discussions. They look at the psychological experience, the impact on social relationships and the doctor-patient relationship. The researchers also asked patients about their perception of privacy in relation to the decision aid. In addition, the experiences of health care providers with the decision aid were investigated.

Preventive medicine through the prediction of individual blood values

prof. dr. Maurits Kaptein, TSHD

dr. Remco van Horssen, Clinical Chemical Hematology Laboratory en Trombosis Service

Within this project, researchers use predictive models and algorithms to compare a measured blood value with predicted values. This prediction is individual and based on previously measured values. With this they look for trends within normal values, in order to predict an abnormal value before it has been measured. This prevents unnecessary blood draws. Lifestyle recommendations can even prevent the occurrence of an abnormal value. After the data models have been developed and tested, this direct form of preventive medicine is being tested in this project for a targeted set of blood values in collaboration with a general practice. By combining the experience from clinical chemistry in the ETZ with the data research knowledge of Tilburg University, the ultimate goal is that people do not become patients, by coaching them individually and digitally.

We record it for YOU! How does the consultation work if it can be framed back by the patient?

prof. dr. Emiel Krahmer, TSHD

dr. Jan Erik Bunt, pediatrics

This project investigates information transfer and communication between doctor and patient. Because the patient forgets a lot of information from an outpatient consultation, this scientific study makes an audio recording of the consultation available to the patient. The conversation can be listened to again, which can help to make choices in consultation with the doctor. Subsequently, it will be studied whether making an audio recording has an influence on the course of the consultation (time for emotions, information transfer, time for small talk, etc.) and how the patient and the doctor perceive a conversation. The study is a collaboration between the ETZ and the TiU and will be conducted in an open RCT form at 200 consultations in various specialties.

Virtual Reality as pain management in the emergency room

dr. Wendy Powell, TSHD

dr. Maite Huis in ‘t Veld, Emergency Medicine

Is Virtual Reality (VR) a safe and effective non-drug alternative to the use of medicated pain management during painful procedures in the emergency department? For this project, experts in Immersive Technology and Emergency Medicine are working together to investigate whether Virtual Reality (VR) is a non-drug alternative to pain management during painful procedures in the emergency department (ED). Using qualitative and quantitative outcome measures, researchers will gain a better understanding of the efficacy and effectiveness of using VR for pain relief in the emergency department. Researchers use "off-the-shelf" VR technology to provide distraction from pain during painful procedures in the emergency room. The analgesic effect of VR is compared to the analgesia provided by regularly used medication by using qualitative pharmacological outcome measures as well as subjective observations and patient experience.

Toward an e-health solution to return to work after injury

dr. Margot Joosen Tranzo, TSB

dr. Ruth Geuze, orthopedic surgery / trauma department

When patients receive personalized information after suffering an injury, they may have unrealistic expectations. In this study, a module for an E-health application is developed with personalized information about (sustainable) return to work. This project has several study methods; continuous quantitative data collection, focus groups and semi-structured interviews to gather in-depth, qualitative information about return to work. Data-driven texts to support the interpretation of predicted outcomes are developed and tested. The personalized prediction models and testimonials will be integrated into an existing E-health application 'the patient journey app for trauma patients'.

Medication verification by the patient: A case study of the use of a digital assistant to prepare for the medication verification interview

dr. Karin Slegers, TSHD

dr. Barbara Maat, Hospital Pharmacy

Before a patient undergoes treatment at the hospital, he or she is given a medication verification interview. During this interview, a pharmacy assistant checks with the patient whether the data the hospital has on medication use is correct and complete. Such interviews are labor intensive and patients do not always remember all the details correctly.

This project examines whether patients can have a check carried out at home in preparation for the interview. To this end, the researchers are developing and evaluating a digital assistant that supports patients in checking and completing their medication. The researchers are looking at how such a digital assistant can be designed to optimally match the skills, motivations, barriers and values of patients and care providers. Furthermore, in a field experiment, they will evaluate the impact of a digital assistant on the patient's and pharmacy assistant's experiences during the medication verification interview.

Artificial intelligence-driven augmented reality in the operating room: Surgical applicability and effectiveness of holograms

prof.dr. Max Louwerse, TSHD

dr. Jan Heyligers, surgery

Can surgeries be performed more efficiently with augmented reality? With "smart" augmented reality glasses, a 3D hologram can be projected over a body part. The hologram shows the internal anatomy of a specific patient. This allows a surgeon to see what the body looks like on the inside before starting surgery. What is groundbreaking about this PhD project is that the holograms can be applied without the use of markers. The project has several goals:

1. perfecting the precision and operation of the technique we have already developed for clinical applications;
2. evaluation of how augmented reality can be used efficiently in surgery;
3. measuring the benefits of the developed technique in surgery in terms of complication risk, ease of use and radiation dose during operations.

By combining surgery and artificial intelligence, the project thus offers new insights into more efficient and better care.

Blood, sweat and fear: Implementing AI driven E-health solution to help overcome needlefear

dr. Elisabeth Huis in 't Veld, TSHD

dr. Bachtiar Buhari, neurosurgery

20 to 50 percent of people suffer from fear of needles. This can lead to severe reactions such as panic, avoidance of punctures, palpitations, nausea, dizziness or fainting. These reactions often arise well before the puncture itself. Sometimes they also occur unconsciously, making them difficult to prevent and cure. A fear of needles is not only distressing for the patient, but also for the nurses and doctors who treat the patient. It is often impossible to reassure someone when they enter the treatment room already very scared or dizzy.

That's why we are developing a game app, AINAR, which uses Artificial Intelligence (AI) to see if you are going to get scared or dizzy before you even realize it. Then the app playfully teaches you to avoid these reactions before the shot takes place. In this project, researchers, doctors and nurses are working together to further develop, improve and test AINAR. The knowledge and insights of patients and healthcare staff are very important in this process. The researchers are looking at when the anxiety and physical reactions start, using innovative imaging techniques and AI to see what happens in the face then. For example, does someone pull away pale or does that person start sweating? Then the researchers will test the effectiveness of AINAR and whether it improves the lancing experience for patient and caregiver.