Background Evaluating patients' experiences is essential when incorporating the patients' perspective in improving healthcare. Experiences are mainly collected using closed-ended questions,... Show moreBackground Evaluating patients' experiences is essential when incorporating the patients' perspective in improving healthcare. Experiences are mainly collected using closed-ended questions, although the value of open-ended questions is widely recognized. Natural language processing (NLP) can automate the analysis of open-ended questions for an efficient approach to patient-centeredness. Methods We developed the Artificial Intelligence Patient-Reported Experience Measures (AI-PREM) tool, consisting of a new, open-ended questionnaire, an NLP pipeline to analyze the answers using sentiment analysis and topic modeling, and a visualization to guide physicians through the results. The questionnaire and NLP pipeline were iteratively developed and validated in a clinical context. Results The final AI-PREM consisted of five open-ended questions about the provided information, personal approach, collaboration between healthcare professionals, organization of care, and other experiences. The AI-PREM was sent to 867 vestibular schwannoma patients, 534 of which responded. The sentiment analysis model attained an F1 score of 0.97 for positive texts and 0.63 for negative texts. There was a 90% overlap between automatically and manually extracted topics. The visualization was hierarchically structured into three stages: the sentiment per question, the topics per sentiment and question, and the original patient responses per topic. Conclusions The AI-PREM tool is a comprehensive method that combines a validated, open-ended questionnaire with a well-performing NLP pipeline and visualization. Thematically organizing and quantifying patient feedback reduces the time invested by healthcare professionals to evaluate and prioritize patient experiences without being confined to the limited answer options of closed-ended questions. Show less
Patients with Parkinson's Disease may be eligible for Deep Brain Stimulation (DBS) in case of severe motor complications. This thesis provides indications for improving patient selection for DBS,... Show morePatients with Parkinson's Disease may be eligible for Deep Brain Stimulation (DBS) in case of severe motor complications. This thesis provides indications for improving patient selection for DBS, as well as describing new biomarkers based on Electroencephalography (EEG) to aid during the DBS selection process. Show less
Care for older persons is changing. A new primary health care concept is called ‘person-centred, integrated care’ involving changing roles for General Practitioners (GPs) and other... Show moreCare for older persons is changing. A new primary health care concept is called ‘person-centred, integrated care’ involving changing roles for General Practitioners (GPs) and other professionals. The inclusion of the personal values of the patients in the changing care is essential but vulnerable. This thesis links the process of innovating care and the values of the older persons involved, by studying patient satisfaction as an expression of personal value in two care innovation and implementation projects. Key findings are: The level of patient satisfaction is related to complexity of health problems and is related more to the care organization than to the condition of the patient. Modifiable communicative aspects of GP behavior are related to patient satisfaction. Patients and GPs, show different satisfaction about aspects of care reflecting different values. In a real-life implementation strategy, patient satisfaction and engagement is feasible and valuable. Conclusions are that patient satisfaction can be used in innovating care but must be interpreted with caution. Also older patients need a role in the implementation process in order to assure that their values are expressed in the care innovation. A combination of individual shared decision making, satisfaction investigation and procedural engagement is proposed. Show less
Lutjeboer, J.; Burgmans, M.C.; Chung, K.; Erkel, A.R. van 2015
