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
Fosse, N.A. du; Lashley, E.E.L.O.; Treurniet, T.T.; Lith, J.M.M. van; Cessie, S. le; Boosman, H.; Hoorn, M.L.P. van der 2021
Background International guidelines recommend to offer supportive care during a next pregnancy to couples affected by recurrent pregnancy loss (RPL). In previous research, several options for... Show moreBackground International guidelines recommend to offer supportive care during a next pregnancy to couples affected by recurrent pregnancy loss (RPL). In previous research, several options for supportive care have been identified and women's preferences have been quantified. Although it is known that RPL impacts the mental health of both partners, male preferences for supportive care have hardly been explored. Methods A cross-sectional study was conducted in couples who visited a specialized RPL clinic in the Netherlands between November 2018 and December 2019. Both members of the couples received a questionnaire that quantified their preferences for supportive care in a next pregnancy and they were asked to complete this independently from each other. Preferences for each supportive care option were analysed on a group level (by gender) and on a couple level, by comparing preferences of both partners. Results Ninety-two questionnaires (completed by 46 couples) were analysed. The overall need for supportive care indicated on a scale from 1 to 10 was 6.8 for men and 7.9 for women (P = 0.002). Both genders preferred to regularly see the same doctor with knowledge of their obstetric history, to make a plan for the first trimester and to have frequent ultrasound examinations. A lower proportion of men preferred a doctor that shows understanding (80% of men vs. 100% of women, P = 0.004) and a doctor that informs on wellbeing (72% vs. 100%, P = <= 0.000). Fewer men preferred support from friends (48% vs. 74%, P = 0.017). Thirty-seven percent of men requested more involvement of the male partner at the outpatient clinic, compared to 70% of women (P = 0.007). In 28% of couples, partners had opposing preferences regarding peer support. Conclusions While both women and men affected by RPL are in need of supportive care, their preferences may differ. Current supportive care services may not entirely address the needs of men. Health care professionals should focus on both partners and development of novel supportive care programs with specific attention for men should be considered. Show less
The number of clinician burnouts is increasing and has been linked to a high administrative burden. Automatic speech recognition (ASR) and natural language processing (NLP) techniques may address... Show moreThe number of clinician burnouts is increasing and has been linked to a high administrative burden. Automatic speech recognition (ASR) and natural language processing (NLP) techniques may address this issue by creating the possibility of automating clinical documentation with a "digital scribe". We reviewed the current status of the digital scribe in development towards clinical practice and present a scope for future research. We performed a literature search of four scientific databases (Medline, Web of Science, ACL, and Arxiv) and requested several companies that offer digital scribes to provide performance data. We included articles that described the use of models on clinical conversational data, either automatically or manually transcribed, to automate clinical documentation. Of 20 included articles, three described ASR models for clinical conversations. The other 17 articles presented models for entity extraction, classification, or summarization of clinical conversations. Two studies examined the system's clinical validity and usability, while the other 18 studies only assessed their model's technical validity on the specific NLP task. One company provided performance data. The most promising models use context-sensitive word embeddings in combination with attention-based neural networks. However, the studies on digital scribes only focus on technical validity, while companies offering digital scribes do not publish information on any of the research phases. Future research should focus on more extensive reporting, iteratively studying technical validity and clinical validity and usability, and investigating the clinical utility of digital scribes. Show less
Vos, M.S. de; Hamming, J.F.; Boosman, H.; Marang-van de Mheen, P.J. 2021
ObjectivesLinkage of safety data to patient experience data may provide information to improve surgical care. This retrospective observational study aimed to assess associations between... Show moreObjectivesLinkage of safety data to patient experience data may provide information to improve surgical care. This retrospective observational study aimed to assess associations between complications, incidents, patient-reported problems, and overall patient experience. MethodsRoutinely collected data from safety reporting on complications and incidents, as well as patient-reported problems and experience on the Picker Patient Experience Questionnaire 15, covering seven experience dimensions, were linked for 4236 surgical inpatients from an academic center (April 2014-December 2015, 41% response). Associations between complication and/or incident occurrence and patient-reported problems, regarding risk of nonpositive experience (i.e., grade of 1-5 of 10), were studied using multivariable logistic regression. ResultsPatient-reported problems were associated with occurrence of complications/incidents among patients with nonpositive experiences (odds ratio [OR] = 2.8, 95% confidence interval [CI] = 1.6-4.9), but not among patients with positive experiences (OR = 1.0, 95% CI = 0.6-1.5). For each experience dimension, presence of patient-reported problems increased risk of nonpositive experience (OR range = 2.7-4.4). Patients with complications or incidents without patient-reported problems were at lower risk of a nonpositive experience than patients with neither complications/incidents nor reported problems (OR = 0.5; 95% CI = 0.3-0.9). Occurrence of complications/incidents only increased risk of nonpositive experience when patients also had problems on "continuity and transition" or "respect for patient preferences" dimensions. ConclusionsLinking safety data to patient experience data can reveal ways to optimize care. Staff seem able to ensure positive patient experiences despite complications or incidents. Increased attention should be paid to respecting patient preferences, continuity, and transition, particularly when complications or incidents occur. Show less
Despite significant efforts, the COVID-19 pandemic has put enormous pressure on health care systems around the world, threatening the quality of patient care. Telemonitoring offers the opportunity... Show moreDespite significant efforts, the COVID-19 pandemic has put enormous pressure on health care systems around the world, threatening the quality of patient care. Telemonitoring offers the opportunity to carefully monitor patients with a confirmed or suspected case of COVID-19 from home and allows for the timely identification of worsening symptoms. Additionally, it may decrease the number of hospital visits and admissions, thereby reducing the use of scarce resources, optimizing health care capacity, and minimizing the risk of viral transmission. In this paper, we present a COVID-19 telemonitoring care pathway developed at a tertiary care hospital in the Netherlands, which combined the monitoring of vital parameters with video consultations for adequate clinical assessment. Additionally, we report a series of medical, scientific, organizational, and ethical recommendations that may be used as a guide for the design and implementation of telemonitoring pathways for COVID-19 and other diseases worldwide. Show less
Cammel, S.A.; Vos, M.S. de; Soest, D. van; Hettne, K.M.; Boer, F.; Steyerberg, E.W.; Boosman, H. 2020
Background Patient experience surveys often include free-text responses. Analysis of these responses is time-consuming and often underutilized. This study examined whether Natural Language... Show moreBackground Patient experience surveys often include free-text responses. Analysis of these responses is time-consuming and often underutilized. This study examined whether Natural Language Processing (NLP) techniques could provide a data-driven, hospital-independent solution to indicate points for quality improvement. Methods This retrospective study used routinely collected patient experience data from two hospitals. A data-driven NLP approach was used. Free-text responses were categorized into topics, subtopics (i.e. n-grams) and labelled with a sentiment score. The indicator 'impact', combining sentiment and frequency, was calculated to reveal topics to improve, monitor or celebrate. The topic modelling architecture was tested on data from a second hospital to examine whether the architecture is transferable to another hospital. Results A total of 38,664 survey responses from the first hospital resulted in 127 topics and 294 n-grams. The indicator 'impact' revealed n-grams to celebrate (15.3%), improve (8.8%), and monitor (16.7%). For hospital 2, a similar percentage of free-text responses could be labelled with a topic and n-grams. Between-hospitals, most topics (69.7%) were similar, but 32.2% of topics for hospital 1 and 29.0% of topics for hospital 2 were unique. Conclusions In both hospitals, NLP techniques could be used to categorize patient experience free-text responses into topics, sentiment labels and to define priorities for improvement. The model's architecture was shown to be hospital-specific as it was able to discover new topics for the second hospital. These methods should be considered for future patient experience analyses to make better use of this valuable source of information. Show less
Bastemeijer, C.M.; Boosman, H.; Ewijk, H. van; Verweij, L.M.; Voogt, L.; Hazelzet, J.A. 2019
Purpose: In the era of value-based healthcare, one strives for the most optimal outcomes and experiences from the perspective of the patient. So, patient experiences have become a key quality... Show morePurpose: In the era of value-based healthcare, one strives for the most optimal outcomes and experiences from the perspective of the patient. So, patient experiences have become a key quality indicator for healthcare. While these are supposed to drive quality improvement (QI), their use and effectiveness for this purpose has been questioned. The aim of this systematic review was to provide insight into QI interventions used in a hospital setting and their effects on improving patient experiences, and possible barriers and promoters for QI work.Methods: Prisma guidelines were used to design this review. International academic literature was searched in Embase, Medline OvidSP, Web of Science, Cochrane Central, PubMed Publisher, Scopus, PsycInfo, and Google Scholar. In total, 3,289 studies were retrieved and independently screened by the first two authors for eligibility and methodological quality. Data was extracted on the study purpose, setting, design, targeted patient experience domains, QI strategies, results of QI, barriers, and promotors for QI.Results: Twenty-one pre-post intervention studies were included for review. The methodological quality of the included studies was assessed using a Critical Appraisal Skills Program (CASP) Tool. QI strategies used were staff education, patient education, audit and feedback, clinician reminders, organizational change, and policy change. Twenty studies reported improvement in patient experience, 14 studies of the 21 included studies reported statistical significance. Most studies (n=17) reported data-related barriers (eg, questionnaire quality), professional, and/or organizational barriers (eg, skepticism among staff), and 14 studies mentioned specific promoters (eg, engaging staff and patients) for QI.Conclusions: Several patient experience domains are targeted for QI using diverse strategies and methodological approaches. Most studies reported at least one improvement and also barriers and promoters that may influence QI work. Future research should address these barriers and promoters in order to enhance methodological quality and improve patient experiences. Show less
