Clinical validation of clinical decision support systems for medication review: A scoping review.

The aim of this scoping review is to summarize approaches and outcomes of clinical validation studies of clinical decision support systems (CDSSs) to support (part of) a medication review. A literature search was conducted in Embase and Medline. In total, 30 articles validating a CDSS were ultimately included. Most of the studies focused on detection of adverse drug events, potentially inappropriate medications and drug-related problems. We categorized the included articles in three groups: studies subjectively reviewing the clinical relevance of CDSS's output (21/30 studies) resulting in a positive predictive value (PPV) for clinical relevance of 4-80%; studies determining the relationship between alerts and actual events (10/30 studies) resulting in a PPV for actual events of 5-80%; and studies comparing output of CDSSs to chart/medication reviews in the whole study population (10/30 studies) resulting in a sensitivity of 28-85% and specificity of 42-75%. We found heterogeneity in the methods used and in the outcome measures. The validation studies did not report the use of a published CDSS validation strategy. To improve the effectiveness and uptake of CDSSs supporting a medication review, future research would benefit from a more systematic and comprehensive validation strategy.

Exploring supportive care and information needs through a proposed eHealth application among melanoma patients undergoing systemic therapy: a qualitative study.

BACKGROUND: During and after systemic therapy, patients with high risk and advanced melanoma experience challenges regarding cancer-related symptoms, treatment-related adverse events, and an impact of these symptoms on their physical and psychosocial well-being. Few studies have investigated the specific needs of these patients and the potential role of eHealth applications in meeting those needs. OBJECTIVE: To explore the supportive care and information needs of high risk and advanced melanoma patients, and how these needs can be supported by eHealth applications. METHODS: In this qualitative study, semi-structured interviews with high risk and advanced melanoma patients during or after systemic treatment were conducted to understand their needs and requirements as possible end-users of mobile eHealth applications. Interview transcripts were independently coded and thematically analyzed. RESULTS: Thirteen participants consented to be interviewed, aged 31 to 71 years. Nearly all patients (n = 12, 92%) experienced unmet information and supportive care needs during and after active treatment. Patients expected to value eHealth applications that facilitate information gathering, wellbeing interventions, and symptom management. The majority of patients (n = 10, 77%) anticipated various advantages from using an eHealth application, including increased autonomy, higher quality of life, and improved disease self-management. DISCUSSION: High risk and advanced melanoma patients have unmet supportive care and information needs during and after systemic treatment. The use of eHealth applications might be an effective way to meet these unmet needs. Patients anticipate a variety of advantages from using these applications, including deriving various benefits from the use of these applications, such as enhanced autonomy.

Potentially inappropriate medications and their effect on falls during hospital admission.

OBJECTIVE: to investigate the effect of potentially inappropriate medications (PIMs) on inpatient falls and to identify whether PIMs as defined by STOPPFall or the designated section K for falls of STOPP v2 have a stronger association with inpatient falls when compared to the general tool STOPP v2. METHODS: a retrospective observational matching study using an electronic health records dataset of patients (≥70 years) admitted to an academic hospital (2015-19), including free text to identify inpatient falls. PIMs were identified using the STOPP v2, section K of STOPP v2 and STOPPFall. We first matched admissions with PIMs to those without PIMs on confounding factors. We then applied multinomial logistic regression analysis and Cox proportional hazards analysis on the matched datasets to identify effects of PIMs on inpatient falls. RESULTS: the dataset included 16,678 hospital admissions, with a mean age of 77.2 years. Inpatient falls occurred during 446 (2.7%) admissions. Adjusted odds ratio (OR) (95% confidence interval (CI)) for the association between PIM exposure and falls were 7.9 (6.1-10.3) for STOPP section K, 2.2 (2.0-2.5) for STOPP and 1.4 (1.3-1.5) for STOPPFall. Adjusted hazard ratio (HR) (95% CI) for the effect on time to first fall were 2.8 (2.3-3.5) for STOPP section K, 1.5 (1.3-1.6) for STOPP and 1.3 (1.2-1.5) for STOPPFall. CONCLUSIONS: we identified an independent association of PIMs on inpatient falls for all applied (de)prescribing tools. The strongest effect was identified for STOPP section K, which is restricted to high-risk medication for falls. Our results suggest that decreasing PIM exposure during hospital stay might benefit fall prevention, but intervention studies are warranted.

Potentially inappropriate prescribing in older hospitalized Dutch patients according to the STOPP/START criteria v2: a longitudinal study.

PURPOSE: To investigate prevalence, independent associations, and variation over time of potentially inappropriate prescriptions in a population of older hospitalized patients. METHODS: A longitudinal study using a large dataset of hospital admissions of older patients (≥ 70 years) based on an electronic health records cohort including data from 2015 to 2019. Potentially inappropriate medication (PIM) and potential prescribing omission (PPO) prevalence during hospital stay were identified based on the Dutch STOPP/START criteria v2. Univariate and multivariate logistic regression were used for analyzing associations and trends over time. RESULTS: The data included 16,687 admissions. Of all admissions, 56% had ≥ 1 PIM and 58% had ≥ 1 PPO. Gender, age, number of medications, number of diagnoses, Charlson score, and length of stay were independently associated with both PIMs and PPOs. Additionally, number of departments and number of prescribing specialties were independently associated with PIMs. Over the years, the PIM prevalence did not change (OR = 1.00, p = .95), whereas PPO prevalence increased (OR = 1.08, p < .001). However, when corrected for changes in patient characteristics such as number of diagnoses, the PIM (aOR = 0.91, p < .001) and PPO prevalence (aOR = 0.94, p < .001) decreased over the years. CONCLUSION: We found potentially inappropriate prescriptions in the majority of admissions of older patients. Prescribing relatively improved over time when considering complexity of the admissions. Nevertheless, the high prevalence shows a clear need to better address this issue in clinical practice. Studies seeking effective (re)prescribing interventions are warranted.

Anticipated Benefits and Concerns of Sharing Hospital Outpatient Visit Notes With Patients (Open Notes) in Dutch Hospitals: Mixed Methods Study.

BACKGROUND: The past few years have seen an increase in interest in sharing visit notes with patients. Sharing visit notes with patients is also known as "open notes." Shared notes are seen as beneficial for patient empowerment and communication, but concerns have also been raised about potential negative effects. Understanding barriers is essential to successful organizational change, but most published studies on the topic come from countries where shared notes are incentivized or legally required. OBJECTIVE: We aim to gather opinions about sharing outpatient clinic visit notes from patients and hospital physicians in the Netherlands, where there is currently no policy or incentive plan for shared visit notes. METHODS: This multimethodological study was conducted in an academic and a nonacademic hospital in the Netherlands. We conducted a survey of patients and doctors in March-April 2019. In addition to the survey, we conducted think-aloud interviews to gather more insight into the reasons behind participants' answers. We surveyed 350 physicians and 99 patients, and think-aloud interviews were conducted with an additional 13 physicians and 6 patients. RESULTS: Most patients (81/98, 77%) were interested in viewing their visit notes, whereas most physicians (262/345, 75.9%) were opposed to allowing patients to view their visit notes. Most patients (54/90, 60%) expected the notes to be written in layman's terms, but most physicians (193/321, 60.1%) did not want to change their writing style to make it more understandable for patients. Doctors raised concerns that reading the note would make patients feel confused and anxious, that the patient would not understand the note, and that shared notes would result in more documentation time or losing a way to communicate with colleagues. Interviews also revealed concerns about documenting sensitive topics such as suspected abuse and unlikely but worrisome differential diagnoses. Physicians also raised concerns that documenting worrisome thoughts elsewhere in the record would result in fragmentation of the patient record. Patients were uncertain if they would understand the notes (46/90, 51%) and, in interviews, raised questions about security and privacy. Physicians did anticipate some benefits, such as the patients remembering the visit better, shared decision-making, and keeping patients informed, but 24% (84/350) indicated that they saw no benefit. Patients anticipated that they would remember the visit better, feel more in control, and better understand their health. CONCLUSIONS: Dutch patients are interested in shared visit notes, but physicians have many concerns that should be addressed if shared notes are pursued. Physicians' concerns should be addressed before shared notes are implemented. In hospitals where shared notes are implemented, the effects should be monitored (objectively, if possible) to determine whether the concerns raised by our participants have actualized into problems and whether the anticipated benefits are being realized.

Information Technology-Based Interventions to Improve Drug-Drug Interaction Outcomes: A Systematic Review on Features and Effects.

The purpose of this systematic review was to identify features and effects of information technology (IT)-based interventions on outcomes related to drug-drug interactions (DDI outcomes). A literature search was conducted in Medline, EMBASE, and the Cochrane Library for published English-language studies. Studies were included if a main outcome was related to DDIs, the intervention involved an IT-based system, and the study design was experimental or observational with controls. Study characteristics, including features and effects of IT-based interventions, were extracted. Nineteen studies comprising five randomized controlled trials (RCT), five non-randomized controlled trials (NRCT) and nine observational studies with controls (OWC) were included. Sixty-four percent of prescriber-directed interventions, and all non-prescriber interventions, were effective. Each of the following characteristics corresponded to groups of studies of which a majority were effective: automatic provision of recommendations within the providers' workflow, intervention at the time of decision-making, integration into other systems, and requiring the reason for not following the recommendations. Only two studies measured clinical outcomes: an RCT that showed no significant improvement and an OWC that showed improvement, but did not statistically assess the effect. Most studies that measured surrogate outcomes (e.g. potential DDIs) and other outcomes (e.g. adherence to alerts) showed improvements. IT-based interventions improve surrogate clinical outcomes and adherence to DDI alerts. However, there is lack of robust evidence about their effectiveness on clinical outcomes. It is recommended that researchers consider the identified features of effective interventions in the design of interventions and evaluate the effectiveness on DDI outcomes, particularly clinical outcomes.

Health information-seeking behavior of seniors who use the Internet: a survey.

BACKGROUND: The Internet is viewed as an important source for health information and a medium for patient empowerment. However, little is known about how seniors use the Internet in relation to other sources for health information. OBJECTIVE: The aim was to determine which information resources seniors who use the Internet use and trust for health information, which sources are preferred, and which sources are used by seniors for different information needs. METHODS: Questions from published surveys were selected based on their relevance to the study objectives. The Autonomy Preference Index was used to assess information needs and preferences for involvement in health decisions. Invitation to participate in this online survey was sent to the email list of a local senior organization (298 addresses) in the Netherlands. RESULTS: There were 118 respondents with a median age of 72 years (IQR 67-78 years). Health professionals, pharmacists, and the Internet were the most commonly used and trusted sources of health information. Leaflets, television, newspapers, and health magazines were also important sources. Respondents who reported higher use of the Internet also reported higher use of other sources (P<.001). Use of health professionals, pharmacists, leaflets, telephone, television, and radio were not significantly different; use of all other resources was significantly higher in frequent Internet users. When in need of health information, preferred sources were the Internet (46/105, 43.8%), other sources (eg, magazines 38/105, 36.2%), health professionals (18/105, 17.1%), and no information seeking (3/105, 2.8%). Of the 51/107 respondents who indicated that they had sought health information in the last 12 months, 43 sought it after an appointment, 23 were preparing for an appointment, and 20 were deciding if an appointment was needed. The source used varied by the type of information sought. The Internet was used most often for symptoms (27/42, 64%), prognosis (21/31, 68%), and treatment options (23/41, 62%), whereas health professionals were asked for additional information on medications (20/36, 56%), side effects (17/36, 47%), coping (17/31, 55%), practical care (12/14, 86%), and nutrition/exercise (18/30, 60%). CONCLUSIONS: For these seniors who use the Internet, the Internet was a preferred source of health information. Seniors who report higher use of the Internet also report higher use of other information resources and were also the primary consumers of paper-based resources. Respondents most frequently searched for health information after an appointment rather than to prepare for an appointment. Resources used varied by health topic. Future research should seek to confirm these findings in a general elderly population, investigate how seniors seek and understand information on the Internet, and investigate how to reach seniors who prefer not to use the Internet for health information.

Co-prescription of gastroprotective agents and their efficacy in elderly patients taking nonsteroidal anti-inflammatory drugs: a systematic review of observational studies.

BACKGROUND & AIMS: Guidelines recommend prescribing gastroprotective agents (proton pump inhibitors, misoprostol) to older patients (primarily ≥65 years old) taking nonsteroidal anti-inflammatory drugs (NSAIDs) to prevent gastrointestinal ulcers. Older individuals are underrepresented in clinical trials of these agents. We systematically reviewed evidence from observational studies on the use of gastroprotective agents in elderly patients and their ability to prevent NSAID-related ulcers in this population. METHODS: We performed a systematic search of Embase and MEDLINE and identified 23 observational studies that focused on elderly patients and reported data on co-prescription of gastroprotective agents and NSAIDs and/or the effectiveness of the agents in preventing gastrointestinal events in NSAID users. We collected data on rates of co-prescription and NSAID-related gastrointestinal events in patients with and without gastroprotection. RESULTS: A median of 24% (range, 10%-69%) of elderly patients taking NSAIDs received a co-prescription for gastroprotective agents; this percentage was only slightly higher in the oldest age groups. All studies of efficacy showed a positive effect of gastroprotection. However, the adjusted results were not suitable for synthesis, and the 5 studies reporting unadjusted results were too heterogeneous for meta-analysis (I(2) = 97%). The studies differed in outcomes, definitions of co-prescription, and differences in baseline risk factors between patients with and without gastroprotection. None of the studies assessed adverse effects of gastroprotective agents. The 2 cost-effectiveness studies reached opposing conclusions. CONCLUSIONS: In a systematic review, the observational evidence for the efficacy of gastroprotective agents in preventing NSAID-associated gastrointestinal events was in agreement with results of randomized controlled trials. However, because of heterogeneity of included studies, it is not clear what the effect would be if more patients were treated, or at what age gastroprotection should be recommended. We offer suggestions to facilitate comparison with other work and address the questions of risk and benefit in relation to age.

Attitudes and experience of Dutch general practitioners regarding computerized clinical decision support.

UNLABELLED: Dutch general practices have a high adoption rate for computerized patient records and clinical decision support. We sought to measure the attitudes and experience of Dutch general practitioners towards clinical decision support. METHODS: A preliminary survey was created based on questions from published surveys, modified with the results of interviews. The final web-based survey was administered to 43 general practitioners in a practice area where a decision support implementation is planned. RESULTS: Thirty general practitioners (70%) completed the survey. Most felt that decision support is a good idea (23/30), although fewer reported positive experience with decision support (10/30). Participants were supportive of rules and guidelines, but commonly had the sense that there were too many alerts. CONCLUSION: Dutch clinicians are positive about decision support, but future efforts should try to reduce the perception of overload, for example by ensuring that alerts are relevant and choosing less interruptive forms of notification for less severe alerts.

Use of an open-source electronic health record to establish a "virtual hospital": A tale of two curricula.

BACKGROUND: The electronic health record (EHR) is central to medical informatics. Its use is also recognized as an important skill for future clinicians. Typically, medical students' first exposure to an EHR is when they start their clinical internships, and medical informatics students may or may not get experience with an EHR before graduation. We describe the process of implementing an open-source EHR in two curricula: Medicine and Medical informatics. For medical students, the primary goals were to allow students to practice analyzing information from the EHR, creating therapeutic plans, and communicating with their colleagues via the EHR before they start their first clinical rotations. For medical informatics students, the primary goal was to give students hands-on experience with creating decision support in an EHR. APPROACH: We used the OpenMRS electronic health record with a custom decision support module based on Arden Syntax. Medical students needed a secure, stable environment to practice medical reasoning. Medical informatics students needed a more isolated system to experiment with the EHR's internal configuration. Both student groups needed synthetic patient cases that were realistic, but in different aspects. For medical students, it is essential that these cases are clinically consistent, and events unfold in a logical order. By contrast, synthetic data for medical informatics students should mimic the data quality problems found in real patient data. OUTCOMES: Medical informatics students show more mature reasoning about data quality issues and workflow integration than prior to using the EHR. Comments on both course evaluations have been positive, including comments on how working with a real-world EHR provides a realistic experience. CONCLUSION: The open-source EHR OpenMRS has proven to be a valuable addition to both the medicine and medical informatics curriculum. Both sets of students experience use of the EHR as giving them valuable, realistic learning experiences.

External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients.

PURPOSE: Fall prevention is a safety goal in many hospitals. The performance of the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) in older inpatients is largely unknown. We aimed to assess the JHFRAT performance in a large sample of Dutch older inpatients, including its trend over time. METHODS: We used an Electronic Health Records (EHR) dataset with hospitalized patients (≥ 70), admitted for ≥ 24 h between 2016 and 2021. Inpatient falls were extracted from structured and free-text data. We assessed the association between JHFRAT and falls using logistic regression. For test accuracy, we calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Discrimination was measured by the AUC. For calibration, we plotted the predicted fall probability with the actual probability of falls. For time-related effects, we calculated the AUC per 6 months (using data of patients admitted during the 6 months' time interval) and plotted these different AUC values over time. Furthermore, we compared the model (JHFRAT and falls) with and without adjusting for seasonal influenza, COVID-19, spring, summer, fall or winter periods. RESULTS: Data included 17,263 admissions with at least 1 JHFRAT measurement, a median age of 76 and a percentage female of 47%. The in-hospital fall prevalence was 2.5%. JHFRAT [OR = 1.11 (1.03-1.20)] and its subcategories were significantly associated with falls. For medium/high risk of falls (JHFRAT > 5), sensitivity was 73%, specificity 51%, PPV 4% and NPV 99%. The overall AUC was 0.67, varying over time between 0.62 and 0.71 (for 6 months' time intervals). Seasonal influenza did affect the association between JHFRAT and falls. COVID-19, spring, summer, fall or winter did not affect the association. CONCLUSIONS: Our results show an association between JHFRAT and falls, a low discrimination by JHFRAT for older inpatients and over-prediction in the calibration. Improvements in the fall-risk assessment are warranted to improve efficiency.

Development and Internal Validation of a Prediction Model for Falls Using Electronic Health Records in a Hospital Setting.

OBJECTIVE: Fall prevention is important in many hospitals. Current fall-risk-screening tools have limited predictive accuracy specifically for older inpatients. Their administration can be time-consuming. A reliable and easy-to-administer tool is desirable to identify older inpatients at higher fall risk. We aimed to develop and internally validate a prognostic prediction model for inpatient falls for older patients. DESIGN: Retrospective analysis of a large cohort drawn from hospital electronic health record data. SETTING AND PARTICIPANTS: Older patients (≥70 years) admitted to a university medical center (2016 until 2021). METHODS: The outcome was an inpatient fall (≥24 hours of admission). Two prediction models were developed using regularized logistic regression in 5 imputed data sets: one model without predictors indicating missing values (Model-without) and one model with these additional predictors indicating missing values (Model-with). We internally validated our whole model development strategy using 10-fold stratified cross-validation. The models were evaluated using discrimination (area under the receiver operating characteristic curve) and calibration (plot assessment). We determined whether the areas under the receiver operating characteristic curves (AUCs) of the models were significantly different using DeLong test. RESULTS: Our data set included 21,286 admissions. In total, 470 (2.2%) had a fall after 24 hours of admission. The Model-without had 12 predictors and Model-with 13, of which 4 were indicators of missing values. The AUCs of the Model-without and Model-with were 0.676 (95% CI 0.646-0.707) and 0.695 (95% CI 0.667-0.724). The AUCs between both models were significantly different (P = .013). Calibration was good for both models. CONCLUSIONS AND IMPLICATIONS: Both the Model-with and Model-without indicators of missing values showed good calibration and fair discrimination, where the Model-with performed better. Our models showed competitive performance to well-established fall-risk-screening tools, and they have the advantage of being based on routinely collected data. This may substantially reduce the burden on nurses, compared with nonautomatic fall-risk-screening tools.

The need to strengthen the evaluation of the impact of Artificial Intelligence-based decision support systems on healthcare provision.

Despite the renewed interest in Artificial Intelligence-based clinical decision support systems (AI-CDS), there is still a lack of empirical evidence supporting their effectiveness. This underscores the need for rigorous and continuous evaluation and monitoring of processes and outcomes associated with the introduction of health information technology. We illustrate how the emergence of AI-CDS has helped to bring to the fore the critical importance of evaluation principles and action regarding all health information technology applications, as these hitherto have received limited attention. Key aspects include assessment of design, implementation and adoption contexts; ensuring systems support and optimise human performance (which in turn requires understanding clinical and system logics); and ensuring that design of systems prioritises ethics, equity, effectiveness, and outcomes. Going forward, information technology strategy, implementation and assessment need to actively incorporate these dimensions. International policy makers, regulators and strategic decision makers in implementing organisations therefore need to be cognisant of these aspects and incorporate them in decision-making and in prioritising investment. In particular, the emphasis needs to be on stronger and more evidence-based evaluation surrounding system limitations and risks as well as optimisation of outcomes, whilst ensuring learning and contextual review. Otherwise, there is a risk that applications will be sub-optimally embodied in health systems with unintended consequences and without yielding intended benefits.

Validation of the ADFICE_IT Models for Predicting Falls and Recurrent Falls in Geriatric Outpatients.

OBJECTIVES: Before being used in clinical practice, a prediction model should be tested in patients whose data were not used in model development. Previously, we developed the ADFICE_IT models for predicting any fall and recurrent falls, referred as Any_fall and Recur_fall. In this study, we externally validated the models and compared their clinical value to a practical screening strategy where patients are screened for falls history alone. DESIGN: Retrospective, combined analysis of 2 prospective cohorts. SETTING AND PARTICIPANTS: Data were included of 1125 patients (aged ≥65 years) who visited the geriatrics department or the emergency department. METHODS: We evaluated the models' discrimination using the C-statistic. Models were updated using logistic regression if calibration intercept or slope values deviated significantly from their ideal values. Decision curve analysis was applied to compare the models' clinical value (ie, net benefit) against that of falls history for different decision thresholds. RESULTS: During the 1-year follow-up, 428 participants (42.7%) endured 1 or more falls, and 224 participants (23.1%) endured a recurrent fall (≥2 falls). C-statistic values were 0.66 (95% CI 0.63-0.69) and 0.69 (95% CI 0.65-0.72) for the Any_fall and Recur_fall models, respectively. Any_fall overestimated the fall risk and we therefore updated only its intercept whereas Recur_fall showed good calibration and required no update. Compared with falls history, Any_fall and Recur_fall showed greater net benefit for decision thresholds of 35% to 60% and 15% to 45%, respectively. CONCLUSIONS AND IMPLICATIONS: The models performed similarly in this data set of geriatric outpatients as in the development sample. This suggests that fall-risk assessment tools that were developed in community-dwelling older adults may perform well in geriatric outpatients. We found that in geriatric outpatients the models have greater clinical value across a wide range of decision thresholds compared with screening for falls history alone.

Effects of a clinical decision support system and patient portal for preventing medication-related falls in older fallers: Protocol of a cluster randomized controlled trial with embedded process and economic evaluations (ADFICE_IT).

BACKGROUND: Falls are the leading cause of injury-related mortality and hospitalization among adults aged ≥ 65 years. An important modifiable fall-risk factor is use of fall-risk increasing drugs (FRIDs). However, deprescribing is not always attempted or performed successfully. The ADFICE_IT trial evaluates the combined use of a clinical decision support system (CDSS) and a patient portal for optimizing the deprescribing of FRIDs in older fallers. The intervention aims to optimize and enhance shared decision making (SDM) and consequently prevent injurious falls and reduce healthcare-related costs. METHODS: A multicenter, cluster-randomized controlled trial with process evaluation will be conducted among hospitals in the Netherlands. We aim to include 856 individuals aged ≥ 65 years that visit the falls clinic due to a fall. The intervention comprises the combined use of a CDSS and a patient portal. The CDSS provides guideline-based advice with regard to deprescribing and an individual fall-risk estimation, as calculated by an embedded prediction model. The patient portal provides educational information and a summary of the patient's consultation. Hospitals in the control arm will provide care-as-usual. Fall-calendars will be used for measuring the time to first injurious fall (primary outcome) and secondary fall outcomes during one year. Other measurements will be conducted at baseline, 3, 6, and 12 months and include quality of life, cost-effectiveness, feasibility, and shared decision-making measures. Data will be analyzed according to the intention-to-treat principle. Difference in time to injurious fall between the intervention and control group will be analyzed using multilevel Cox regression. DISCUSSION: The findings of this study will add valuable insights about how digital health informatics tools that target physicians and older adults can optimize deprescribing and support SDM. We expect the CDSS and patient portal to aid in deprescribing of FRIDs, resulting in a reduction in falls and related injuries. TRIAL REGISTRATION: ClinicalTrials.gov NCT05449470 (7-7-2022).

An eHealth App (CAPABLE) Providing Symptom Monitoring, Well-Being Interventions, and Educational Material for Patients With Melanoma Treated With Immune Checkpoint Inhibitors: Protocol for an Exploratory Intervention Trial.

BACKGROUND: Since treatment with immune checkpoint inhibitors (ICIs) is becoming standard therapy for patients with high-risk and advanced melanoma, an increasing number of patients experience treatment-related adverse events such as fatigue. Until now, studies have demonstrated the benefits of using eHealth tools to provide either symptom monitoring or interventions to reduce treatment-related symptoms such as fatigue. However, an eHealth tool that facilitates the combination of both symptom monitoring and symptom management in patients with melanoma treated with ICIs is still needed. OBJECTIVE: In this pilot study, we will explore the use of the CAPABLE (Cancer Patients Better Life Experience) app in providing symptom monitoring, education, and well-being interventions on health-related quality of life (HRQoL) outcomes such as fatigue and physical functioning, as well as patients' acceptance and usability of using CAPABLE. METHODS: This prospective, exploratory pilot study will examine changes in fatigue over time in 36 patients with stage III or IV melanoma during treatment with ICI using CAPABLE (a smartphone app and multisensory smartwatch). This cohort will be compared to a prospectively collected cohort of patients with melanoma treated with standard ICI therapy. CAPABLE will be used for a minimum of 3 and a maximum of 6 months. The primary endpoint in this study is the change in fatigue between baseline and 3 and 6 months after the start of treatment. Secondary end points include HRQoL outcomes, usability, and feasibility parameters. RESULTS: Study inclusion started in April 2023 and is currently ongoing. CONCLUSIONS: This pilot study will explore the effect, usability, and feasibility of CAPABLE in patients with melanoma during treatment with ICI. Adding the CAPABLE system to active treatment is hypothesized to decrease fatigue in patients with high-risk and advanced melanoma during treatment with ICIs compared to a control group receiving standard care. The Medical Ethics Committee NedMec (Amsterdam, The Netherlands) granted ethical approval for this study (reference number 22-981/NL81970.000.22). TRIAL REGISTRATION: ClinicalTrials.gov NCT05827289; https://clinicaltrials.gov/study/NCT05827289. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49252.

Studies pertaining to the ACOVE quality criteria: a systematic review.

PURPOSE: To identify and uniformly describe studies employing the Assessing Care Of Vulnerable Elders (ACOVE) quality indicators within a comprehensive thematic model that reflects how the indicators were used. DATA SOURCES: A systematic search of MEDLINE, EMBASE and CINAHL was conducted. STUDY SELECTION: English-language studies meeting our criteria published prior to January 2010. Data extraction Included studies were analyzed and described by two independent researchers. RESULTS OF DATA SYNTHESIS: A total of 41 articles met our selection criteria. Studies were classified into the themes 'Application of indicators' (32 studies) and ' ANALYSIS: and development of indicators' (13 studies). 'Application' studies included assessing quality of care, influencing behavior of health professionals and examining the association of quality of care with other factors. 'Analysis and development' included studies developing new indicator sets, and those adapting and validating the original quality indicators to new settings. CONCLUSIONS: The indicators were used in a wide range of applications with two main foci: the assessment of quality of care for elderly patients, and investigating the feasibility of similar indicators and their adaptation to new settings. Very few of the studies published to date have addressed the goal of care improvement. We foresee an important role for application of indicators that proactively help health-care professionals to deliver the right care at the right time, for example by resorting to decision support systems.

Application of the logical elements rule method for formalization of clinical rules: case study of ACOVE-NLI.

The Logical Elements Rule Method (LERM) is a step-wise method for formalizing if-then clinical rules. We applied LERM to a set of 40 clinical rules used in pharmacological quality assessment initiatives to assess (1) the amenability of the rules to formalization for decision support application (2) comparing adherence to rules that can and cannot be formalized, and (3) the usefulness of LERM as a tool for this task. Five rules could not be formalized, all due to unclear decision criteria. The adherence to ambiguous, non-formalizable rules was significantly lower than for formalizable ones (<0.001). We modified LERM with three additions for this task: (a) adding the sub-step of restating the rules in a consistent natural-language grammar before decomposing them into normal form, (b) creating rules to use in lieu of a controlled vocabulary, and (c) adding the requirement that a time frame must be defined for all medications (before hospitalization, current medication, new medication, or discharge medication). Although the clinical rules in this sample are all stated as semi-structured if-then recommendations and are used in quality assessment initiatives, many ambiguities and inconsistencies in the clinical rules were identified by using LERM.

General Practitioners' needs and wishes for clinical decision support Systems: A focus group study.

BACKGROUND: Shared decision making (SDM) can be beneficial for patients, healthcare professionals, but is often not applied in practice. A clinical decision support system (CDSS) can facilitate SDM. However, CDSS acceptance rates are rather low. One context in which SDM between a general practitioner (GP) and patient regarding medication can be of great value is older patients' medication-related fall risk. Applying user-centered design to optimally tailor the CDSS to the needs and wishes of GPs can help overcome the low CDSS-acceptance rates. The current study aims to learn GPs' needs and wishes for a CDSS focused on diminishing medication-related fall risk. MATERIALS AND METHODS: Participants were recruited through the Amsterdam Academic Network of General Practice and were sent a web-lecture as preparation. Three online focus groups with a total of 13 GPs were performed and were led by two moderators. The focus groups were recorded and transcribed verbatim. Transcripts were analyzed using Atlas.ti. RESULTS: GPs' views on the workflow, risk presentation and advice of the system were elicited. The fit with the GPs' workflow was elaborately discussed, for instance how the CDSS could support the selection of patients at risk. GPs articulated a strong preference for a visual risk presentation, in the form of a gradient scale ranging from bright green to dark red. Furthermore, they preferred receiving both medication-related and non-medication-related advice, which should be presented on request. DISCUSSION: The findings provide a valuable insight into GPs' needs and wishes for a CDSS focused on medication-related fall prevention. This will inform the design of a first prototype of the CDSS which will be subjected to usability tests. The findings of this study can also be used to support the development of medication-related CDSSs in a broader context.