Low-value chronic prescription of acid reducing medication among Dutch general practitioners: impact of a patient education intervention.

BACKGROUND: Dyspepsia is a commonly encountered clinical condition in Dutch general practice, which is often treated through the prescription of acid-reducing medication (ARM). However, recent studies indicate that the majority of chronic ARM users lack an indication for their use and that their long-term use is associated with adverse outcomes. We developed a patient-focussed educational intervention aiming to reduce low-value (chronic) use of ARM. METHODS: We conducted a randomized controlled study, and evaluated its effect on the low-value chronic prescription of ARM using data from a subset (n = 26) of practices from the Nivel Primary Care Database. The intervention involved distributing an educational waiting room posters and flyers informing both patients and general practitioners (GPs) regarding the appropriate indications for prescription of an ARM for dyspepsia, which also referred to an online decision aid. The interventions' effect was evaluated through calculation of the odds ratio of a patient receiving a low-value chronic ARM prescription over the second half of 2021 and 2022 (i.e. pre-intervention vs. post-intervention). RESULTS: In both the control and intervention groups, the proportion of patients receiving chronic low-value ARM prescriptions slightly increased. In the control group, it decreased from 50.3% in 2021 to 49.7% in 2022, and in the intervention group it increased from 51.3% in 2021 to 53.1% in 2022. Subsequent statistical analysis revealed no significant difference in low-value chronic prescriptions between the control and intervention groups (Odds ratio: 1.11 [0.84-1.47], p > 0.05). CONCLUSION: Our educational intervention did not result in a change in the low-value chronic prescription of ARM; approximately half of the patients of the intervention and control still received low-value chronic ARM prescriptions. The absence of effect might be explained by selection bias of participating practices, awareness on the topic of chronic AMR prescriptions and the relative low proportion of low-value chronic ARM prescribing in the intervention as well as the control group compared to an assessment conducted two years prior. TRIAL REGISTRATION: 10/31/2023 NCT06108817.

The implementation of a multidisciplinary, electronic health record embedded care pathway to improve structured data recording and decrease electronic health record burden.

INTRODUCTION: Theoretically, the added value of electronic health records (EHRs) is extensive. Reusable data capture in EHRs could lead to major improvements in quality measurement, scientific research, and decision support. To achieve these goals, structured and standardized recording of healthcare data is a prerequisite. However, time spent on EHRs by physicians is already high. This study evaluated the effect of implementing an EHR embedded care pathway with structured data recording on the EHR burden of physicians. MATERIALS AND METHODS: Before and six months after implementation, consultations were recorded and analyzed with video-analytic software. Main outcome measures were time spent on specific tasks within the EHR, total consultation duration, and usability indicators such as required mouse clicks and keystrokes. Additionally, a validated questionnaire was completed twice to evaluate changes in physician perception of EHR system factors and documentation process factors. RESULTS: Total EHR time in initial oncology consultations was significantly reduced by 3.7 min, a 27 % decrease. In contrast, although a decrease of 13 % in consultation duration was observed, no significant effect on EHR time was found in follow-up consultations. Additionally, perceptions of physicians regarding the EHR and documentation improved significantly. DISCUSSION: Our results have shown that it is possible to achieve structured data capture while simultaneously reducing the EHR burden, which is a decisive factor in end-user acceptance of documentation systems. Proper alignment of structured documentation with workflows is critical for success. CONCLUSION: Implementing an EHR embedded care pathway with structured documentation led to decreased EHR burden.

Trends in low-value GP care during the COVID-19 pandemic: a retrospective cohort study.

BACKGROUND: Several studies showed that during the pandemic patients have refrained from visiting their general practitioner (GP). This resulted in medical care being delayed, postponed or completely forgone. The provision of low-value care, i.e. care which offers no net benefit for the patient, also could have been affected. We therefore assessed the impact of the COVID-19 restrictions on three types of low-value GP care: 1) imaging for back or knee problems, 2) antibiotics for otitis media acuta (OMA), and 3) repeated opioid prescriptions, without a prior GP visit. METHODS: We performed a retrospective cohort study using registration data from GPs part of an academic GP network over the period 2017-2022. The COVID-19 period was defined as the period between April 2020 to December 2021. The periods before (January 2017 to April 2020) and after the COVID-19 period (January 2022 to December 2022) are the pre- and post-restrictions periods. The three clinical practices examined were selected by two practicing GPs from a top 30 of recommendations originating from the Dutch GP guidelines, based on their perceived prevalence and relevance in practice (van Dulmen et al., BMC Primary Care 23:141, 2022). Multilevel Poisson regression models were built to examine changes in the incidence rates (IR) of both registered episodes and episodes receiving low-value treatment. RESULTS: During the COVID-19 restrictions period, the IRs of episodes of all three types of GP care decreased significantly. The IR of episodes of back or knee pain decreased by 12%, OMA episodes by 54% and opioid prescription rate by 13%. Only the IR of OMA episodes remained significantly lower (22%) during the post-restrictions period. The provision of low-value care also changed. The IR of imaging for back or knee pain and low-value prescription of antibiotics for OMA both decreased significantly during the COVID-restrictions period (by 21% and 78%), but only the low-value prescription rate of antibiotics for OMA remained significantly lower (by 63%) during the post-restrictions period. The IR of inappropriately repeated opioid prescriptions remained unchanged over all three periods. CONCLUSIONS: This study shows that both the rate of episodes as well as the rate at which low-value care was provided have generally been affected by the COVID-19 restrictions. Furthermore, it shows that the magnitude of the impact of the restrictions varies depending on the type of low-value care. This indicates that deimplementation of low-value care requires tailored (multiple) interventions and may not be achieved through a single disruption or intervention alone.

Development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard.

Objective: To describe the development and validation of automated electronic health record data reuse for a multidisciplinary quality dashboard. Materials and methods: Comparative study analyzing a manually extracted and an automatically extracted dataset with 262 patients treated for HNC cancer in a tertiary oncology center in the Netherlands in 2020. The primary outcome measures were the percentage of agreement on data elements required for calculating quality indicators and the difference between indicators results calculated using manually collected and indicators that used automatically extracted data. Results: The results of this study demonstrate high agreement between manual and automatically collected variables, reaching up to 99.0% agreement. However, some variables demonstrate lower levels of agreement, with one variable showing only a 20.0% agreement rate. The indicator results obtained through manual collection and automatic extraction show high agreement in most cases, with discrepancy rates ranging from 0.3% to 3.5%. One indicator is identified as a negative outlier, with a discrepancy rate of nearly 25%. Conclusions: This study shows that it is possible to use routinely collected structured data to reliably measure the quality of care in real-time, which could render manual data collection for quality measurement obsolete. To achieve reliable data reuse, it is important that relevant data is recorded as structured data during the care process. Furthermore, the results also imply that data validation is conditional to development of a reliable dashboard.

What are Effective Strategies to Reduce Low-Value Care? An Analysis of 121 Randomized Deimplementation Studies.

BACKGROUND: Low-value care is healthcare leading to no or little clinical benefit for the patient. The best (combinations of) interventions to reduce low-value care are unclear. PURPOSE: To provide an overview of randomized controlled trials (RCTs) evaluating deimplementation strategies, to quantify the effectiveness and describe different combinations of strategies. METHODS: Analysis of 121 RCTs (1990-2019) evaluating a strategy to reduce low-value care, identified by a systematic review. Deimplementation strategies were described and associations between strategy characteristics and effectiveness explored. RESULTS: Of 109 trials comparing deimplementation to usual care, 75 (69%) reported a significant reduction of low-value healthcare practices. Seventy-three trials included in a quantitative analysis showed a median relative reduction of 17% (IQR 7%-42%). The effectiveness of deimplementation strategies was not associated with the number and types of interventions applied. CONCLUSIONS AND IMPLICATIONS: Most deimplementation strategies achieved a considerable reduction of low-value care. We found no signs that a particular type or number of interventions works best for deimplementation. Future deimplementation studies should map relevant contextual factors, such as the workplace culture or economic factors. Interventions should be tailored to these factors and provide details regarding sustainability of the effect.

Low-value wound care: Are nurses and physicians choosing wisely? A mixed methods study.

BACKGROUND: Choosing Wisely is an international movement that stimulates conversations about unnecessary care. The campaign created five recommendations including a statement that less wound care is sometimes better. AIMS: The study aims to evaluate nurses' and physicians' adherence to the Choosing Wisely recommendations for acute wound care in the Netherlands and the barriers and facilitators to improve this. DESIGN: This is a mixed methods study using a survey and interviews. METHODS: The survey was completed by 171 nurses and 71 physicians from November 2017 to February 2018. A total of 17 nurses and 6 physicians were interviewed. RESULTS: Awareness of the five recommendations ranged from 62% to 89% for nurses and 46% to 85% for physicians. However, up to 15% of the nurses and 28% of physicians were aware but did not adhere to the recommendations. Barriers to adhering were a lack of knowledge, the work environment and perceptions of patients' preferences. Repeated attention, cost-consciousness and an open culture facilitated the implementation. CONCLUSION: Although most nurses and physicians were aware of the recommendations, not all adhered to them. Increasing awareness is not enough for successful implementation. A tailored approach that removes the barriers is necessary, such as increasing knowledge about wounds and changing the work environment.

Evaluation of a remote monitoring app in head and neck cancer follow-up care.

BACKGROUND: A remote monitoring app was developed for head and neck cancer (HNC) follow-up during the SARS-CoV-2 pandemic. This mixed-methods study provides insight in the usability and patients' experiences with the app to develop recommendations for future use. METHODS: Patients were invited to participate if they were treated for HNC, used the app at least once and were in clinical follow-up. A subset was selected for semi-structured interviews through purposive sampling considering gender and age. This study was conducted between September 2021-May 2022 at a Dutch university medical center. RESULTS: 135 of the 216 invited patients completed the questionnaire, resulting in a total mHealth usability score of 4.72 (± 1.13) out of 7. Thirteen semi-structured interviews revealed 12 barriers and 11 facilitators. Most of them occurred at the level of the app itself. For example, patients received no feedback when all their answers were normal. The app made patients feel more responsible over their follow-up, but could not fulfill the need for personal contact with the attending physician. Patients felt that the app could replace some of the outpatient follow-up visits. CONCLUSIONS: Our app is user-friendly, makes patients feel more in control and remote monitoring can reduce the frequency of outpatient follow-up visits. The barriers that emerged must be resolved before the app can be used in regular HNC follow-up. Future studies should investigate the appropriate ratio of remote monitoring to outpatient follow-up visits and the cost-effectiveness of remote monitoring in oncology care on a larger scale.

[Trends in number of vitamin B12- and D-determinations in the Netherlands]. / Trends in vitamine B12- en D-bepalingen in Nederland.

OBJECTIVE: To gain insight into the volume of vitamin B12- and D-determinations over time. DESIGN: A retrospective cohort study. METHOD: Using declaration data of around 3.5 million insured Dutch citizens we examined the volume of vitamin B12- and D-testing between 2015-2019. Both trends in number and proportion of patients receiving a vitamin B12- and D determination were assessed. RESULTS: Between 2015-2019 the number of vitamin B12-determinations increased by 98,1% and the number of vitamin D-determinations by 112%. The proportion of patients receiving a determination increased from 4,8% to 8,4% for vitamin B12 and from 4,7% to 9,1% for vitamin D over the examined period. CONCLUSION: Both the number of and proportion of patients receiving a vitamin B12- and D-determinations increased over the examined time period. Our findings emphasize the need for proper patient and physician information regarding the indications which justify vitamin B12- or D testing, in order to reduce and prevent overtesting.

Exploring patients' perceptions of low-value care: An interview study.

OBJECTIVE: Clinicians consider patients' expectations and demands as a major driver of low-value care. However, little is known about the patients' perspective. We aimed to explore patients' perceptions of low-value care. METHODS: We performed semi-structured interviews with 24 patients from the Netherlands and explored their ideas of and experiences with low-value care, and their perception of its consequences and solutions. The interviews were analysed using inductive thematic analysis. RESULTS: Patients considered several types of care to be of low value, such as duplicate care, care that does not fit their preferences, inefficient care, and care that could have been prevented. The main causes of low-value care according to patients are poor clinician-patient communication and adhering to protocols instead of tailoring care to the individual patient. Consequences of low-value care were a burden for the patient, higher healthcare costs, and less room for high-value care. CONCLUSION: Patients' view of low-value care extends beyond care that is medically ineffective. Their experiences could help to identify opportunities to reduce the (perceived) use of low-value care. PRACTICE IMPLICATIONS: Future de-implementation studies could benefit from engaging patients. Dutch patients understand the importance of reducing low-value care and could be strong advocates for de-implementation programs.

Development of the SPREAD framework to support the scaling of de-implementation strategies: a mixed-methods study.

OBJECTIVE: We aimed to increase the understanding of the scaling of de-implementation strategies by identifying the determinants of the process and developing a determinant framework. DESIGN AND METHODS: This study has a mixed-methods design. First, we performed an integrative review to build a literature-based framework describing the determinants of the scaling of healthcare innovations and interventions. PubMed and EMBASE were searched for relevant studies from 1995 to December 2020. We systematically extracted the determinants of the scaling of interventions and developed a literature-based framework. Subsequently, this framework was discussed in four focus groups with national and international de-implementation experts. The literature-based framework was complemented by the findings of the focus group meetings and adapted for the scaling of de-implementation strategies. RESULTS: The literature search resulted in 42 articles that discussed the determinants of the scaling of innovations and interventions. No articles described determinants specifically for de-implementation strategies. During the focus groups, all participants agreed on the relevance of the extracted determinants for the scaling of de-implementation strategies. The experts emphasised that while the determinants are relevant for various countries, the implications differ due to different contexts, cultures and histories. The analyses of the focus groups resulted in additional topics and determinants, namely, medical training, professional networks, interests of stakeholders, clinical guidelines and patients' perspectives. The results of the focus group meetings were combined with the literature framework, which together formed the supporting the scaling of de-implementation strategies (SPREAD) framework. The SPREAD framework includes determinants from four domains: (1) scaling plan, (2) external context, (3) de-implementation strategy and (4) adopters. CONCLUSIONS: The SPREAD framework describes the determinants of the scaling of de-implementation strategies. These determinants are potential targets for various parties to facilitate the scaling of de-implementation strategies. Future research should validate these determinants of the scaling of de-implementation strategies.

Quantifying the Electronic Health Record Burden in Head and Neck Cancer Care.

BACKGROUND: Although the main task of health care providers is to provide patient care, studies show that increasing amounts of time are spent on documentation. OBJECTIVE: To quantify the time and effort spent on the electronic health record (EHR) in head and neck cancer care. METHODS: Cross-sectional time-motion study. Primary outcomes were the percentages of time spent on the EHR and the three main tasks (chart review, input, placing orders), number of mouse events, and keystrokes per consultation. Secondary outcome measures were perceptions of health care providers regarding EHR documentation and satisfaction. RESULTS: In total, 44.0% of initial oncological consultation (IOC) duration and 30.7% of follow-up consultation (FUC) duration are spent on EHR tasks. During 80.0% of an IOC and 67.9% of a FUC, the patient and provider were actively communicating. Providers required 593 mouse events and 1,664 keystrokes per IOC and 140 mouse events and 597 keystrokes per FUC, indicating almost 13 mouse clicks and close to 40 keystrokes for every minute of consultation time. Less than a quarter of providers indicated that there is enough time for documentation. CONCLUSION: This study quantifies the widespread concern of high documentation burden for health care providers in oncology, which has been related to burnout and a decrease of patient-clinician interaction. Despite excessive time and effort spent on the EHR, health care providers still felt this was insufficient for proper documentation. However, the need for accurate and complete documentation is high, as reuse of information becomes increasingly important. The challenge is to decrease the documentation burden while increasing the quality of EHR data.

Identifying and prioritizing do-not-do recommendations in Dutch primary care.

BACKGROUND: Low-value care provides minimal or no benefit for the patient, wastes resources, and can cause harm. Explicit do-not-do recommendations in clinical guidelines are a first step in reducing low-value care. The aim of this study was to identify and prioritize do-not-do recommendations in general practice guidelines with priority for implementation. METHODS: We used a mixed method design in Dutch primary care. First, we identified do-not-do recommendations through a systematic assessment of 92 Dutch guidelines for general practitioners (GPs), resulting in 385 do-not-do recommendations. Second, we selected 146 recommendations addressing high prevalent conditions. Third, a random sample of 5000 Dutch GPs was invited for an online survey to prioritize recommendations based on the prevalence of the condition and low-value care practice, potential harm, and potential cost reduction on a scale from 1 to 5/6. Total scores could range from 4 to 22. Recommendations with a median score > 12 were included. In total, 440 GPs completed the survey. RESULTS: The selection process led to 30 prioritised recommendations. These covered drug treatments (n = 12), diagnostics (n = 10), referral to other healthcare professions (n = 5), and non-drug treatment (n = 3). CONCLUSION: Dutch clinical guidelines include many do-not-do recommendations that are perceived as highly relevant by the GPs. The list of 30 high-priority do-not-do recommendations can be used to raise awareness of low-value care among GPs. As the recommendations are supported with the latest evidence from international studies, primary healthcare professionals and policy makers worldwide can use the list for further validating the list in their local context and designing strategies to reduce low-value care.

The Impact of Structured and Standardized Documentation on Documentation Quality; a Multicenter, Retrospective Study.

The reuse of healthcare data for various purposes will become increasingly important in the future. To enable the reuse of clinical data, structured and standardized documentation is conditional. However, the primary purpose of clinical documentation is to support high-quality patient care. Therefore, this study investigated the effect of increased structured and standardized documentation on the quality of notes in the Electronic Health Record. A multicenter, retrospective design was used to assess the difference in note quality between 144 unstructured and 144 structured notes. Independent reviewers measured note quality by scoring the notes with the Qnote instrument. This instrument rates all note elements independently using and results in a grand mean score on a 0-100 scale. The mean quality score for unstructured notes was 64.35 (95% CI 61.30-67.35). Structured and standardized documentation improved the Qnote quality score to 77.2 (95% CI 74.18-80.21), a 12.8 point difference (p < 0.001). Furthermore, results showed that structured notes were significantly longer than unstructured notes. Nevertheless, structured notes were more clear and concise. Structured documentation led to a significant increase in note quality. Moreover, considering the benefits of structured data recording in terms of data reuse, implementing structured and standardized documentation into the EHR is recommended.

Low-value pharmaceutical care among Dutch GPs: a retrospective cohort study.

BACKGROUND: Low-value pharmaceutical care exists in general practice. However, the extent among Dutch GPs remains unknown. AIM: To assess the prevalence of low-value pharmaceutical care among Dutch GPs. DESIGN AND SETTING: Retrospective cohort study using data from patient records. METHOD: The prevalence of three types of pharmaceutical care prescribed by GPs between 2016 and 2019 were examined: topical antibiotics for conjunctivitis, benzodiazepines for non-specific lower back pain, and chronic acid-reducing medication (ARM) prescriptions. Multilevel logistic regression analysis was performed to assess prescribing variation and the influence of patient characteristics on receiving a low-value prescription. RESULTS: Large variation in prevalence as well as practice variation was observed among the types of low-value pharmaceutical GP care examined. Between 53% and 61% of patients received an inappropriate antibiotics prescription for conjunctivitis, around 3% of patients with lower back pain received an inappropriate benzodiazepine prescription, and 88% received an inappropriate chronic ARM prescription during the years examined. The odds of receiving an inappropriate antibiotic or benzodiazepine prescription increased with age (P<0.001), but decreased for chronic inappropriate ARM prescriptions (P<0.001). Sex affected only the odds of receiving a non-indicated chronic ARM, with males being at higher risk (P<0.001). The odds of receiving an inappropriate ARM increased with increasing neighbourhood socioeconomic status (P<0.05). Increasing practice size decreased the odds of inappropriate antibiotic and benzodiazepine prescriptions (P<0.001). CONCLUSION: The results show that the prevalence of low-value pharmaceutical GP care varies among these three clinical problems. Significant variation in inappropriate prescribing exists between different types of pharmaceutical care - and GP practices.

Key Factors that Promote Low-Value Care: Views of Experts From the United States, Canada, and the Netherlands.

BACKGROUND: Around the world, policies and interventions are used to encourage clinicians to reduce low-value care. In order to facilitate this, we need a better understanding of the factors that lead to low-value care. We aimed to identify the key factors affecting low-value care on a national level. In addition, we highlight differences and similarities in three countries. METHODS: We performed 18 semi-structured interviews with experts on low-value care from three countries that are actively reducing low-value care: the United States, Canada, and the Netherlands. We interviewed 5 experts from Canada, 6 from the United States, and 7 from the Netherlands. Eight were organizational leaders or policy-makers, 6 as low-value care researchers or project leaders, and 4 were both. The transcribed interviews were analyzed using inductive thematic analysis. RESULTS: The key factors that promote low-value care are the payment system, the pharmaceutical and medical device industry, fear of malpractice litigation, biased evidence and knowledge, medical education, and a 'more is better' culture. These factors are seen as the most important in the United States, Canada and the Netherlands, although there are several differences between these countries in their payment structure, and industry and malpractice policy. CONCLUSION: Policy-makers and researchers that aim to reduce low-value care have experienced that clinicians face a mix of interdependent factors regarding the healthcare system and culture that lead them to provide low-value care. Better awareness and understanding of these factors can help policy-makers to facilitate clinicians and medical centers to deliver high-value care.

The Effect of Noninvasive Telemonitoring for Chronic Heart Failure on Health Care Utilization: Systematic Review.

BACKGROUND: Chronic heart failure accounts for approximately 1%-2% of health care expenditures in most developed countries. These costs are primarily driven by hospitalizations and comorbidities. Telemonitoring has been proposed to reduce the number of hospitalizations and decrease the cost of treatment for patients with heart failure. However, the effects of telemonitoring on health care utilization remain unclear. OBJECTIVE: This systematic review aims to study the effect of telemonitoring programs on health care utilization and costs in patients with chronic heart failure. We assess the effect of telemonitoring on hospitalizations, emergency department visits, length of stay, hospital days, nonemergency department visits, and health care costs. METHODS: We searched PubMed, Embase, and Web of Science for randomized controlled trials and nonrandomized studies on noninvasive telemonitoring and health care utilization. We included studies published between January 2010 and August 2020. For each study, we extracted the reported data on the effect of telemonitoring on health care utilization. We used P<.05 and CIs not including 1.00 to determine whether the effect was statistically significant. RESULTS: We included 16 randomized controlled trials and 13 nonrandomized studies. Inclusion criteria, population characteristics, and outcome measures differed among the included studies. Most studies showed no effect of telemonitoring on health care utilization. The number of hospitalizations was significantly reduced in 38% (9/24) of studies, whereas emergency department visits were reduced in 13% (1/8) of studies. An increase in nonemergency department visits (6/9, 67% of studies) was reported. Health care costs showed ambiguous results, with 3 studies reporting an increase in health care costs, 3 studies reporting a reduction, and 4 studies reporting no significant differences. Health care cost reductions were realized through a reduction in hospitalizations, whereas increases were caused by the high costs of the telemonitoring program or increased health care utilization. CONCLUSIONS: Most telemonitoring programs do not show clear effects on health care utilization measures, except for an increase in nonemergency outpatient department visits. This may be an unwarranted side effect rather than a prerequisite for effective telemonitoring. The consequences of telemonitoring on nonemergency outpatient visits should receive more attention from regulators, payers, and providers. This review further demonstrates the high clinical and methodological heterogeneity of telemonitoring programs. This should be taken into account in future meta-analyses aimed at identifying the effective components of telemonitoring programs.

Using Text Mining Techniques to Identify Health Care Providers With Patient Safety Problems: Exploratory Study.

BACKGROUND: Regulatory bodies such as health care inspectorates can identify potential patient safety problems in health care providers by analyzing patient complaints. However, it is challenging to analyze the large number of complaints. Text mining techniques may help identify signals of problems with patient safety at health care providers. OBJECTIVE: The aim of this study was to explore whether employing text mining techniques on patient complaint databases can help identify potential problems with patient safety at health care providers and automatically predict the severity of patient complaints. METHODS: We performed an exploratory study on the complaints database of the Dutch Health and Youth Care Inspectorate with more than 22,000 written complaints. Severe complaints are defined as those cases where the inspectorate contact point experts deemed it worthy of a triage by the inspectorate, or complaints that led to direct action by the inspectorate. We investigated a range of supervised machine learning techniques to assign a severity label to complaints that can be used to prioritize which incoming complaints need the most attention. We studied several features based on the complaints' written content, including sentiment analysis, to decide which were helpful for severity prediction. Finally, we showcased how we could combine these severity predictions and automatic keyword analysis on the complaints database and listed health care providers and their organization-specific complaints to determine the average severity of complaints per organization. RESULTS: A straightforward text classification approach using a bag-of-words feature representation worked best for the severity prediction of complaints. We obtained an accuracy of 87%-93% (2658-2990 of 3319 complaints) on the held-out test set and an F1 score of 45%-51% on the severe complaints. The skewed class distribution led to only reasonable recall (47%-54%) and precision (44%-49%) scores. The use of sentiment analysis for severity prediction was not helpful. By combining the predicted severity outcomes with an automatic keyword analysis, we identified several health care providers that could have patient safety problems. CONCLUSIONS: Text mining techniques for analyzing complaints by civilians can support inspectorates. They can automatically predict the severity of the complaints, or they can be used for keyword analysis. This can help the inspectorate detect potential patient safety problems, or support prioritizing follow-up supervision activities by sorting complaints based on the severity per organization or per sector.

Identification of Factors Influencing the Adoption of Health Information Technology by Nurses Who Are Digitally Lagging: In-Depth Interview Study.

BACKGROUND: The introduction of health information technology (HIT) has drastically changed health care organizations and the way health care professionals work. Some health care professionals have trouble coping efficiently with the demands of HIT and the personal and professional changes it requires. Lagging in digital knowledge and skills hampers health care professionals from adhering to professional standards regarding the use of HIT and may cause professional performance problems, especially in the older professional population. It is important to gain more insight into the reasons and motivations behind the technology issues experienced by these professionals, as well as to explore what could be done to solve them. OBJECTIVE: Our primary research objective was to identify factors that influence the adoption of HIT in a sample of nurses who describe themselves as digitally lagging behind the majority of their colleagues in their workplaces. Furthermore, we aimed to formulate recommendations for practice and leadership on how to help and guide these nurses through ongoing digital transformations in their health care work settings. METHODS: In a Dutch university medical center, 10 face-to-face semi-structured interviews were performed with registered nurses (RN). Ammenwerth's FITT-framework (fit between the Individual, Task, and Technology) was used to guide the interview topic list and to formulate themes to explore. Thematic analysis was used to analyze the interview data. The FITT-framework was also used to further interpret and clarify the interview findings. RESULTS: Analyses of the interview data uncovered 5 main categories and 12 subthemes. The main categories were: (1) experience with digital working, (2) perception and meaning, (3) barriers, (4) facilitators, and (5) future perspectives. All participants used electronic devices and digital systems, including the electronic health record. The latter was experienced by some as user-unfriendly, time-consuming, and not supportive in daily professional practice. Most of the interviewees described digital working as "no fun at all," "working in a fake world," "stressful," and "annoying." There was a lack of general digital knowledge and little or no formal basic digital training or education. A negative attitude toward computer use and a lack of digital skills contributed to feelings of increased incompetency and postponement or avoidance of the use of HIT, both privately and professionally. Learning conditions of digital training and education did not meet personal learning needs and learning styles. A positive impact was seen in the work environment when colleagues and nurse managers were aware and sensitive to the difficulties participants experienced in developing digital skills, and when there was continuous training on the job and peer support from digitally savvy colleagues. The availability of a digital play environment combined with learning on the job and support of knowledgeable peers was experienced as helpful and motivating by participants. CONCLUSIONS: Nurses who are digitally lagging often have had insufficient and ineffective digital education. This leads to stress, frustration, feelings of incompetency, and postponement or avoidance of HIT use. A digital training approach tailored to the learning needs and styles of these nurses is needed, as well as an on-the-job training structure and adequate peer support. Hospital management and nurse leadership should be informed about the importance of the fit between technology, task, and the individual for adequate adoption of HIT.