Informed Health Care Decisions Research Articles

Evidence-Based Practice Quality Improvement Critical Appraisal Tool.

Optimal quality improvement in health care is based on research and other types of evidence. Critical appraisal of evidence is a fundamental component of evidence-based practice (EBP) and is also needed to evaluate the quality of quality improvement (QI) projects. Currently available EBP or QI critical appraisal tools can be challenging for students learning the critical appraisal process and for practicing clinicians who desire access to a standardized EBPQI approach to inform health care decision-making. The currently available tools are incomplete, too brief, or too complicated for ease of use in education and practice. This article introduces the first combined EBP and QI (EBPQI) critical appraisal tool, which is aligned with the new EBPQI mountain model. This newly developed appraisal tool may be used in appraising evidence for an EBPQI initiative and to appraise the quality of disseminated EBPQI.

Gastro-esophageal reflux disease among the urban population of Saudi Arabia

IntroductionGastro-esophageal Reflux Disease (GERD) is a significant global health issue affecting millions and placing a substantial burden on healthcare systems. This study investigates the prevalence and influencing factors of GERD among the urban population in Saudi Arabia, amidst rapid urbanization and lifestyle changes. The goal is to provide insights for targeted interventions and improved public health strategies. MethodologyA cross-sectional study was conducted using a comprehensive methodology. A validated, bilingual questionnaire was used to collect data on demographics, awareness, psychosocial aspects, symptoms, and medical history. The study included 493 participants, and data were collected through an online survey. Statistical analysis was performed using SPSS and Excel, maintaining a statistical power of 80 ​%. ResultsThe survey included 493 participants, revealing the following key findings: Gender distribution: 41.37 ​% male, 58.62 ​% female (p ​= ​0.053). Age categories: 18–25 (25.35 ​%), 26–40 (18.05 ​%), 41–55 (26.97 ​%), 56 and above (29.61 ​%) (p ​= ​0.055). Nationality: 51.92 ​% Saudi, 48.07 ​% non-Saudi (p ​= ​0.058). Other notable demographics: marital status, education levels, smoking habits, nutritional habits, BMI categories, and prevalence of bariatric surgery. GERD symptoms and psychological factors showed significant associations. Treatment preferences and lifestyle modifications varied widely. The data provide essential insights for tailored interventions and healthcare strategies. ConclusionThis study highlights the complex demographic patterns and lifestyle factors associated with GERD in Saudi Arabia's urban population. The findings emphasize the importance of tailored interventions and inform healthcare, research, and policy decisions for effective GERD management in urban settings.

Community health information needs assessment in the mid-south region of the United States indicates new roles for public libraries.

Libraries provide public access to information that may be used to inform healthcare decisions. Exploring the health information needs of library-users could improve community health outcomes, especially during times of crisis like the COVID-19 pandemic. The purpose of this study was to identify the health information needs of library-users to explore the potential role of libraries in advancing community health. A quantitative, descriptive, cross-sectional survey was employed. One hundred and fifty participants in the (Memphis) Tennessee metropolitan area, ranging from 18 to 84 years of age, completed the survey between September 2020 and April 2021. Most respondents reported seeking physical and mental health-related information from libraries. In addition, nearly half of respondents reported delaying medical care due to risk of exposure to COVID-19, cost or appointment issues. Study results indicated that there were urgent health information needs among library-users in this community, that COVID-19 further limited or delayed access to information, and that library-users accessed health information during library visits. Public libraries have the potential to serve as information hubs to improve community health outcomes. Additional research should be conducted to collect qualitative community health information needs and the ways in which public library systems can address them.

Systematic analysis of levels of evidence supporting Chinese clinical practice guidelines for gastrointestinal disease.

Clinical practice guidelines (CPGs) inform healthcare decisions and improve patient care. However, an evaluation of guidelines on gastrointestinal diseases (GIDs) is lacking. This study aimed to systematically analyze the level of evidence (LOE) supporting Chinese CPGs for GIDs. CPGs for GIDs were identified by systematically searching major databases. Data on LOEs and classes of recommendations (CORs) were extracted. According to the Grades of Recommendation, Assessment, Development, and Evaluation system, LOEs were categorized as high, moderate, low, or very low, whereas CORs were classified as strong or weak. Statistical analyses were conducted to determine the distribution of LOEs and CORs across different subtopics and assess changes in evidence quality over time. Only 27.9% of these recommendations were supported by a high LOE, whereas approximately 70% were strong recommendations. There was a significant disparity among different subtopics in the proportion of strong recommendations supported by a high LOE. The number of guidelines has increased in the past 5 years, but there has been a concomitant decline in the proportion of recommendations supported by a high LOE. There is a general lack of high-quality evidence supporting Chinese CPGs for GIDs, and there are inconsistencies in strong recommendations that have not improved. This study identified areas requiring further research, emphasizing the need to bridge these gaps and promote the conduct of high-quality clinical trials. This study was supported by the National Key R&D Program of China (2022YFC2503604 and 2022YFC2503605) and Special Topics in Military Health Care (22BJZ25).

Trends and landscape of clinical outcome assessment use to support oncology product approvals.

e23186 Background: The regulatory landscape in oncology trials has evolved with growing emphasis on patient-focused drug development. Further to tumor and survival outcomes, measuring how patients feel and function via clinical outcome assessments (COAs) provides critical information on symptoms and treatment burden and may help to inform risk/benefit evaluation for new treatments. This study aimed to examine trends in the use of COAs to support efficacy or safety in oncology product labeling. Methods: Product labeling information was obtained from PROLABELS (Mapi Research Trust), a database containing COA-related data sourced from the efficacy or safety sections of FDA Product labels and EMA SmPC where at least one COA is mentioned. Oncology product labels were screened based on therapeutic indications and study information. The clinical study details published in the label/SPC between 1990 and 2022 were used for further analysis. Results: A total of 180 EMA and FDA approved drugs and devices for oncology indications where COAs were mentioned in the product label were identified. 288 studies with COAs supported these drug approvals. These studies were in 52 different indications, with most in multiple myeloma (31), followed by non-small-cell lung cancer (24), prostate cancer (22), and breast cancer (22). Of the COAs that were used, 47% were patient-reported outcomes, 18% were clinician-reported outcomes, 30% were composites, and 5% were unspecified. The number of studies conducted with COAs supporting a product label increased over time, with 3x more studies in the past 10 years (189 from 2013-2022) compared to the previous 10 years (60 from 2003-2012). For studies listing specific COA names, 63 unique COAs were used. Excluding response criteria assessments, the most common COAs were the EORTC-QLQ-C30 (57 studies), EORTC-QLQ-LC13 (18 studies), and EQ-5D-3L (17 studies). The two indications with the largest variety of COAs used were prostate cancer (10 unique COAs) and non-small-cell lung cancer (9 unique COAs). Conclusions: In line with regulators highlighting the utility of COAs in evaluating clinical benefit, results show an increase in studies using COAs to support efficacy and safety in oncology product approvals. With COAs providing critical information on symptoms, side effect impact, and quality of life, including this information on labels may help patients and providers make more informed healthcare decisions, and for market differentiation.

Effectiveness of Nirmatrelvir-Ritonavir for the Prevention of COVID-19-Related Hospitalization and Mortality: A Systematic Literature Review.

Nirmatrelvir/ritonavir (NMV/r) is an oral antiviral drug used to treat mild-to-moderate coronavirus disease 2019 (COVID-19) in patients aged 12 years or older at high risk of progression to severe disease (eg, hospitalization and death). Despite being the preferred option for outpatient treatment in the majority of countries worldwide, NMV/r is currently underutilized in real-world clinical practice. As numerous real-world studies have described patient outcomes following treatment with NMV/r, this systematic literature review provides a comprehensive summary of evidence on NMV/r effectiveness against hospitalization and mortality further organized by clinically meaningful categories, such as acute versus longer-term follow-up, age, underlying health conditions, and vaccination status, to help inform health care decision making. We searched Embase and PubMed (December 22, 2021-March 31, 2023) and congress abstracts (December 1, 2021-December 31, 2022) for reports describing NMV/r effectiveness. In total, 18 real-world studies met final selection criteria. The evidence showed that NMV/r significantly reduced postinfection risk of all-cause and COVID-19-related hospitalization and mortality in both acute (≤30 days) (21%-92%) and longer-term (>30 days) (1%-61%) follow-up. The reduction in postinfection risk was higher when treatment was received within 5 days of symptom onset. Real-world effectiveness of NMV/r treatment was observed regardless of age, underlying high-risk conditions, and vaccination status. The systematic literature review findings demonstrated the effectiveness of NMV/r against hospitalization and mortality during the Omicron period among individuals at high risk of progression to severe COVID-19 disease.

Patient-Reported Outcome Measures in Neuromuscular Diseases: A Scoping Review.

Patient-reported outcome measures (PROMs) are valuable in comprehensively understanding patients' health experiences and informing healthcare decisions in research and clinical care without clinicians' input. Until now, no central resource containing information on all PROMS in neuromuscular diseases (NMD) is available, hindering the comparison and choice of PROMs used to monitor NMDs and appropriately reflect the patient's voice. This scoping review aimed to present a comprehensive assessment of the existing literature on using PROMs in children and adults with NMD. A scoping methodology was followed using Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines to assess the literature on PROMs in NMDs. Eligibility criteria encompassed articles describing psychometric development or evaluation of generic or disease-specific PROM-based instruments for adults and children with specific NMDs. The data charting process involved extracting measurement properties of included PROMs, comprising validity, reliability, responsiveness, and interpretability information. The review identified 190 PROMs evaluated across 247 studies in individuals with NMDs. The majority of PROMs were disease specific. The physical functioning domain was most assessed. Validity was the most frequently investigated measurement property, with a limited number of PROMs sufficiently evaluated for a range of psychometric characteristics. There is a strong need for further research on the responsiveness and interpretability of PROMs and the development of PROMs on social functioning in NMD.

Enhancing healthcare decision support through explainable AI models for risk prediction

Electronic health records (EHRs) are a valuable source of information that can aid in understanding a patient’s health condition and making informed healthcare decisions. However, modelling longitudinal EHRs with heterogeneous information is a challenging task. Although recurrent neural networks (RNNs) are frequently utilized in artificial intelligence (AI) models for capturing longitudinal data, their explanatory capabilities are limited. Predictive clustering stands as the most recent advancement within this domain, offering interpretable indications at the cluster level for predicting disease risk. Nonetheless, the challenge of determining the optimal number of clusters has put a brake on the widespread application of predictive clustering for disease risk prediction. In this paper, we introduce a novel non-parametric predictive clustering-based risk prediction model that integrates the Dirichlet Process Mixture Model (DPMM) with predictive clustering via neural networks. To enhance the model’s interpretability, we integrate attention mechanisms that enable the capture of local-level evidence in addition to the cluster-level evidence provided by predictive clustering. The outcome of this research is the development of a multi-level explainable artificial intelligence (AI) model. We evaluated the proposed model on two real-world datasets and demonstrated its effectiveness in capturing longitudinal EHR information for disease risk prediction. Moreover, the model successfully produced interpretable evidence to bolster its predictions.

The long-term cost-effectiveness of once-weekly semaglutide versus sitagliptin for the treatment of type 2 diabetes in China

BackgroundTo estimate the long-term cost-effectiveness of once-weekly semaglutide versus sitagliptin as an add-on therapy for type 2 diabetes patients inadequately controlled on metformin in China, to better inform healthcare decision making.MethodsThe Cardiff diabetes model which is a Monte Carlo micro-simulation model was used to project short-term effects of once-weekly semaglutide versus sitagliptin into long-term outcomes. Short-term data of patient profiles and treatment effects were derived from the 30-week SUSTAIN China trial, in which 868 type 2 diabetes patients with a mean age of 53.1 years inadequately controlled on metformin were randomized to receive once-weekly semaglutide 0.5 mg, once-weekly semaglutide 1 mg, or sitagliptin 100 mg. Costs and quality-adjusted life years (QALYs) were estimated from a healthcare system perspective at a discount rate of 5%. Univariate sensitivity analysis, scenario analysis, and probabilistic sensitivity analysis were conducted to test the uncertainty.ResultsOver patients’ lifetime projections, patients in both once-weekly semaglutide 0.5 mg and 1 mg arms predicted less incidences of most vascular complications, mortality, and hypoglycemia, and lower total costs compared with those in sitagliptin arm. For an individual patient, compared with sitagliptin, once-weekly semaglutide 0.5 mg conferred a small QALY improvement of 0.08 and a lower cost of $5173, while once-weekly semaglutide 1 mg generated an incremental QALY benefit of 0.12 and a lower cost of $7142, as an add-on to metformin. Therefore, both doses of once-weekly semaglutide were considered dominant versus sitagliptin with more QALY benefits at lower costs.ConclusionOnce-weekly semaglutide may represent a cost-effective add-on therapy alternative to sitagliptin for type 2 diabetes patients inadequately controlled on metformin in China.

Preanalytical Errors in Clinical Laboratory Testing at a Glance: Source and Control Measures.

The accuracy of diagnostic results in clinical laboratory testing is paramount for informed healthcare decisions and effective patient care. While the focus has traditionally been on the analytical phase, attention has shifted towards optimizing the preanalytical phase due to its significant contribution to total laboratory errors. This review highlights preanalytical errors, their sources, and control measures to improve the quality of laboratory testing. Blood sample quality is a critical concern, with factors such as hemolysis, lipemia, and icterus leading to erroneous results. Sources of preanalytical errors encompass inappropriate test requests, patient preparation lapses, and errors during sample collection, handling, and transportation. Mitigating these errors includes harmonization efforts, education and training programs, automated methods for sample quality assessment, and quality monitoring. Collaboration between laboratory personnel and healthcare professionals is crucial for implementing and sustaining these measures to enhance the accuracy and reliability of diagnostic results, ultimately improving patient care.

Cumulative Blast Impulse Is Predictive for Changes in Chronic Neurobehavioral Symptoms Following Low Level Blast Exposure during Military Training.

Cumulative low-level blast exposure during military training may be a significant occupational hazard, increasing the risk of poor long-term outcomes in brain function. US Public Law 116-92 section717 mandates that US Department of Defense agencies document the blast exposure of each Service member to help inform later disability and health care decisions. However, which empirical measures of training blast exposure, such as the number of incidents, peak overpressure, or impulse, best inform changes in the neurobehavioral symptoms reflecting brain health have not been established. This study was approved by the US Army Special Operations Command, the University of North Carolina at Chapel Hill, and the VA Puget Sound Health Care System. Using methods easily deployable across different organizational structures, this study sought to identify and measure candidate risk factors related to career occupational blast exposure predictive of changes in neurobehavioral symptom burden. Blast dosimetry-symptom relationships were first evaluated in mice and then tested in a military training environment. In mice, the righting time neurobehavioral response was measured after exposure to a repetitive low-level blast paradigm modeled after Special Operations training. In the military training environment, 23 trainees enrolled in a 6-week explosive breaching training course, 13 instructors, and 10 Service member controls without blast exposure participated in the study (46 total). All participants provided weekly Neurobehavioral Symptom Inventory (NSI) surveys. Peak blast overpressure, impulse, total number of blasts, Time in Low-Level Blast Occupation, and Time in Service were analyzed by Bayesian analysis of regression modeling to determine their probability of influence on the post-training symptoms reported by participants. We tested the hypothesis that cumulative measures of low-level blast exposure were predictive of changes in neurobehavioral symptoms. In mice, repetitive blast resulted in reduced righting times correlated with cumulative blast impulse. In Service members, peak blast overpressure, impulse, total number of blasts, Time in Low-Level Blast Occupation, and Time in Service all showed strong evidence of influence on NSI scores after blast exposure. However, only models including baseline NSI scores and cumulative blast impulse provided significant predictive value following validation. These results indicate that measures of cumulative blast impulse may have utility in predicting changes in NSI scores. Such paired dosimetry-symptom measures are expected to be an important tool in safely guiding Service members' occupational exposure and optimizing force readiness and lethality.

The Hidden Toll of Psychological Distress in Australian Adults and Its Impact on Health-Related Quality of Life Measured as Health State Utilities.

Psychological distress (PD) is a major health problem that affects all aspects of health-related quality of life including physical, mental and social health, leading to a substantial human and economic burden. Studies have revealed a concerning rise in the prevalence of PD and various mental health conditions among Australians, particularly in female individuals. There is a scarcity of studies that estimate health state utilities (HSUs), which reflect the overall health-related quality of life in individuals with PD. No such studies have been conducted in Australia thus far. We aimed to evaluate the age-specific, sex-specific and PD category-specific HSUs (disutilities) in Australian adults with PD to inform healthcare decision making in the management of PD. Data on age, sex, SF-36/SF6D responses, Kessler psychological distress (K10) scale scores and other characteristics of N = 15,139 participants (n = 8149 female individuals) aged >15 years were derived from the latest wave (21) of the nationally representative Household, Income and Labor Dynamics in Australia survey. Participants were grouped into the severity categories of no (K10 score: 10-19), mild (K10: 20-24), moderate (K10: 25-29) and severe PD (K10: 30-50). Both crude and adjusted HSUs were calculated from participants' SF-36 profiles, considering potential confounders such as smoking, marital status, remoteness, education and income levels. The calculations were based on the SF-6D algorithm and aligned with Australian population norms. Additionally, the HSUs were stratified by age, sex and PD categories. Disutilities of PD, representing the mean difference between HSUs of people with PD and those without, were also calculated for each group. The average age of individuals was 46.130 years (46% male), and 31% experienced PD in the last 4 weeks. Overall, individuals with PD had significantly lower mean HSUs than those likely to be no PD, 0.637 (95% confidence interval [CI] 0.636, 0.640) vs 0.776 (95% CI 0.775, 0.777) i.e. disutility: -0.139 [95% CI -0.139, -0.138]). Mean disutilities of -0.108 (95% CI -0.110, -0.104), -0.140 (95% CI -0.142, -0.138), and -0.188 (95% CI -0.190, -0.187) were observed for mild PD, moderate PD and severe PD, respectively. Disutilities of PD also differed by age and sex groups. For instance, female individuals had up to 0.049 points lower mean HSUs than male individuals across the three classifications of PD. There was a clear decline in health-related quality of life with increasing age, demonstrated by lower mean HSUs in older population age groups, that ranged from 0.818 (95% CI 0.817, 0.818) for the 15-24 years age group with no PD to 0.496 (95% CI 0.491, 0.500) for the 65+ years age group with severe PD). Across all ages and genders, respondents were more likely to report issues in certain dimensions, notably vitality, and these responses did not uniformly align with ageing. The burden of PD in Australia is substantial, with a significant impact on female individuals and older individuals. Implementing age-specific and sex-specific healthcare interventions to address PD among Australian adults may greatly alleviate this burden. The PD state-specific HSUs calculated in our study can serve as valuable inputs for future health economic evaluations of PD in Australia and similar populations.

Machine learning-based analysis of adverse events in mesh implant surgery reports

AbstractMesh implant surgery, commonly used for various medical conditions, has been linked to a range of negative effects, significantly impacting patient experiences and outcomes. Additionally, the growing volume of medical data, especially text-based reports, presents challenges in deriving meaningful insights for informed healthcare decisions. To address these challenges, our study extensively analyzed the Manufacturer and User Facility Device Experience (MAUDE) dataset from 2000 to 2021. We have meticulously identified a range of adverse events associated with mesh implant surgeries, including Dyspareunia, Urinary problems, Chronic Inflammation, Prolapse Recurrence, Mesh Erosion, Urinary Tract Infections, discomfort, and sleep disturbances. Using topic modeling, we explored patient experiences and the interrelationships among these adverse events. This approach uncovered key topics linked to mesh surgery, such as Stress Urinary Incontinence, Incisional Hernia, Inguinal Hernia, and Umbilical Hernia, along with their side effects. While the analysis focused on common symptoms such as pain, infection, and bleeding, it also brought to light specific symptoms like sleeping issues, mental stress, and discomfort. We also examined the interconnectedness of these adverse events with identified topics and their temporal trends, revealing shifts in patient experiences over time. Notably, there was an increase in reports of Stress Urinary Incontinence around 2011–2012 and a surge in Inguinal Hernia concerns in 2017–2018. This study provides a comprehensive understanding of adverse events and associated topics in mesh implant surgeries, contributing valuable insights into patient experiences and aiding in informed healthcare decision-making.

Differences in Preferences for Drug Therapy Between Patients with Metastatic Versus Early-Stage Breast Cancer: A Systematic Literature Review.

Compared with early stages (eBC) metastatic BC (mBC) is incurable. In mBC, aggressive treatment may increase the duration of survival but may also cause severe treatment side effects. A better understanding how patients with BC value different aspects of drug therapy might improve treatment effectiveness, satisfaction and adherence. This systematic review aims to identify and summarise studies evaluating patient preferences for drug therapy of BC and to compare preferences of patients with eBC and mBC. The systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The electronic databases PubMed and Web of Science were searched on 22 June 2023. All studies published to this point were considered. Original studies reporting patient preferences on BC drug therapy determined by any type of choice experiment were eligible. A narrative synthesis of the effect measures presented as relative importance ratings, trade-offs (required benefit to make a therapy worthwhile) or monetary values of the treatment attributes was reported for each study. Risk of bias assessment for individual studies was performed using the checklist for observational studies from the STROBE Statement and the checklist from 'Conducting Discrete Choice Experiments to Inform Healthcare Decision Making: A User's Guide'. The study protocol was registered at the PROSPERO database (CRD42022377031). A total of 34 studies met the inclusion criteria were included in the analysis evaluating the preferences of patients with eBC (n = 18), mBC (n = 10) or any stage BC (n = 6) on, for example, chemotherapy, endocrine therapy, hormonal therapy or CKD4/6-inhibitors using different types of choice experiments. Regardless of the stage, most patients valued treatment effectiveness in terms of survival gains higher than potential adverse drug reactions (ADRs). Treatment cost, mode of administration, treatment regimen and monitoring aspects were considered as least important treatment attributes. In addition, preferences concerning 16 different types of ADRs were described, showing high heterogeneity within BC stages. Yet, comparable results across BC stages were observed. Regardless of the stage, patients with BC consistently valued survival gains as the most important attribute and were willing to accept the risk of potential ADRs. Incorporating patient preferences in shared decision making may improve the effectiveness of interventions by enhancing adherence to drug therapy in patients suffering from BC.

Validation of a Model Estimating the Budget Impact of Video Capsule Endoscopy for Surveillance of Crohn’s Disease in an Italian Center

Background: Crohn’s disease is a chronic ailment affecting the gastrointestinal tract. Mucosal healing, a marker of reduced disease activity, is currently assessed in the colonic sections using ileocolonoscopy and magnetic resonance enteroscopy. Video capsule endoscopy (VCE) offers visualization of the entire GI mucosae. Objective: To validate a Crohn’s disease model estimating the budget impact of VCE compared with the standard of care (SOC) in Italy. Methods: A patient-level, discrete-event simulation was developed to estimate the budget impact of VCE compared with SOC for Crohn’s disease surveillance over 5 years in the Italian setting. Input data were sourced from a physician-initiated study from Sant’Orsola-Malpighi Hospital in Bologna, Italy, and the literature. The care pathway followed hospital clinical practice. Comparators were the current SOC (ileocolonoscopy, with or without magnetic resonance enteroscopy) and VCE. Sensitivity analysis was performed using 500-patient bootstraps. A comparative analysis regarding clinical outcomes (biologics use, surgical interventions, symptom remission) was performed to explore the validity of the model compared with real-world data. Cumulative event incidences were compared annually and semi-annually. Bayesian statistical analysis further validated the model. Results: Implementing VCE yielded an estimated €67 savings per patient per year, with savings in over 55% of patients, compared with SOC. While annual costs are higher up to the second year, VCE becomes cost saving from the third year onward. The real-world validation analysis proved a good agreement between the model and real-world patient records. The highest agreement was found for biologics, where Bayesian analysis estimated an 80.4% probability (95% CI: 72.2%-87.5%) that a decision maker would accept the result as an actual reflection of real-world data. Even where trend data diverged (eg, for surgery [43.1% likelihood of acceptance, 95% CI: 33.7%-52.8%]), the cumulative surgery count over 5 years was within the margin of error of the real-world data. Conclusions: Implementing VCE in the surveillance of patients with Crohn’s disease and small bowel involvement may be cost saving in Italy. The congruence between model predictions and real-world patient records supports using this discrete-event simulation to inform healthcare decisions.

Validation of a Model Estimating the Budget Impact of Video Capsule Endoscopy for Surveillance of Crohn's Disease in an Italian Center.

Background: Crohn's disease is a chronic ailment affecting the gastrointestinal tract. Mucosal healing, a marker of reduced disease activity, is currently assessed in the colonic sections using ileocolonoscopy and magnetic resonance enteroscopy. Video capsule endoscopy (VCE) offers visualization of the entire GI mucosae. Objective: To validate a Crohn's disease model estimating the budget impact of VCE compared with the standard of care (SOC) in Italy. Methods: A patient-level, discrete-event simulation was developed to estimate the budget impact of VCE compared with SOC for Crohn's disease surveillance over 5 years in the Italian setting. Input data were sourced from a physician-initiated study from Sant'Orsola-Malpighi Hospital in Bologna, Italy, and the literature. The care pathway followed hospital clinical practice. Comparators were the current SOC (ileocolonoscopy, with or without magnetic resonance enteroscopy) and VCE. Sensitivity analysis was performed using 500-patient bootstraps. A comparative analysis regarding clinical outcomes (biologics use, surgical interventions, symptom remission) was performed to explore the validity of the model compared with real-world data. Cumulative event incidences were compared annually and semi-annually. Bayesian statistical analysis further validated the model. Results: Implementing VCE yielded an estimated €67 savings per patient per year, with savings in over 55% of patients, compared with SOC. While annual costs are higher up to the second year, VCE becomes cost saving from the third year onward. The real-world validation analysis proved a good agreement between the model and real-world patient records. The highest agreement was found for biologics, where Bayesian analysis estimated an 80.4% probability (95% CI: 72.2%-87.5%) that a decision maker would accept the result as an actual reflection of real-world data. Even where trend data diverged (eg, for surgery [43.1% likelihood of acceptance, 95% CI: 33.7%-52.8%]), the cumulative surgery count over 5 years was within the margin of error of the real-world data. Conclusions: Implementing VCE in the surveillance of patients with Crohn's disease and small bowel involvement may be cost saving in Italy. The congruence between model predictions and real-world patient records supports using this discrete-event simulation to inform healthcare decisions.

A Social Media Quality Review of Popular Sinusitis Videos on TikTok.

Social media may inform health care decisions among younger patient populations. TikTok is a social media platform that allows users to post short-form videos. This study aimed to assess the quality of sinusitis-related videos on TikTok. We searched TikTok on January 29, 2023, for sinusitis-related hashtags: #sinusitis, #sinus, #sinusinfection. Internet. The number of views/shares per day, uploader type (nonmedical influencer, lay individual, and medical professional) content categories (medical advice, marketing, comedy, and lifestyle/acceptability), and content type (educational vsfactual) were collected. The Patient Education Materials Assessment Tool for Audiovisual Material and Journal of the American Medical Association criteria score was used to measure understandability, actionability, and reliability. The Global Quality Scale (GQS) was used to evaluate the quality of videos; the harm/benefit score was used to evaluate causative effects. Analyses were performed using analysis of variance (α = .05). There were 221 videos identified, which garnered over 300 million views and 1 million shares. Almost half of the videos were published by nonmedical influencers. When controlling for covariates, nonmedical influencers and lay uploaders were more likely to have harmful harm/benefit scores, less understandable videos, and lower GQS scores compared to medical professionals. Less than half of videos posted by nonmedical influencers categorized as educational were factual (46.7%); lay individuals and medical professionals had higher rates of factual educational content (79.9% and 83.7%, respectively). Most nonmedical influencer-posted TikTok videos about sinusitis are inaccurate, despite being portrayed as medical advice/educational. Rhinologists must find modern ways to disseminate true disease-related content via social media to combat medical misinformation.

Protocol for the development of a tool (INSPECT-SR) to identify problematic randomised controlled trials in systematic reviews of health interventions

IntroductionRandomised controlled trials (RCTs) inform healthcare decisions. It is now apparent that some published RCTs contain false data and some appear to have been entirely fabricated. Systematic reviews are performed...

Use of Healthcare Claims Data to Generate Real-World Evidence on Patients With Drug-Resistant Epilepsy: Practical Considerations for Research.

Objectives: Regulatory bodies, health technology assessment agencies, payers, physicians, and other decision-makers increasingly recognize the importance of real-world evidence (RWE) to provide important and relevant insights on treatment patterns, burden/cost of illness, product safety, and long-term and comparative effectiveness. However, RWE generation requires a careful approach to ensure rigorous analysis and interpretation. There are limited examples of comprehensive methodology for the generation of RWE on patients who have undergone neuromodulation for drug-resistant epilepsy (DRE). This is likely due, at least in part, to the many challenges inherent in using real-world data to define DRE, neuromodulation (including type implanted), and related outcomes of interest. We sought to provide recommendations to enable generation of robust RWE that can increase knowledge of "real-world" patients with DRE and help inform the difficult decisions regarding treatment choices and reimbursement for this particularly vulnerable population. Methods: We drew upon our collective decades of experience in RWE generation and relevant disciplines (epidemiology, health economics, and biostatistics) to describe challenges inherent to this therapeutic area and to provide potential solutions thereto within healthcare claims databases. Several examples were provided from our experiences in DRE to further illustrate our recommendations for generation of robust RWE in this therapeutic area. Results: Our recommendations focus on considerations for the selection of an appropriate data source, development of a study timeline, exposure allotment (specifically, neuromodulation implantation for patients with DRE), and ascertainment of relevant outcomes. Conclusions: The need for RWE to inform healthcare decisions has never been greater and continues to grow in importance to regulators, payers, physicians, and other key stakeholders. However, as real-world data sources used to generate RWE are typically generated for reasons other than research, rigorous methodology is required to minimize bias and fully unlock their value.

Use of Healthcare Claims Data to Generate Real-World Evidence on Patients With Drug-Resistant Epilepsy: Practical Considerations for Research

Objectives: Regulatory bodies, health technology assessment agencies, payers, physicians, and other decision-makers increasingly recognize the importance of real-world evidence (RWE) to provide important and relevant insights on treatment patterns, burden/cost of illness, product safety, and long-term and comparative effectiveness. However, RWE generation requires a careful approach to ensure rigorous analysis and interpretation. There are limited examples of comprehensive methodology for the generation of RWE on patients who have undergone neuromodulation for drug-resistant epilepsy (DRE). This is likely due, at least in part, to the many challenges inherent in using real-world data to define DRE, neuromodulation (including type implanted), and related outcomes of interest. We sought to provide recommendations to enable generation of robust RWE that can increase knowledge of “real-world” patients with DRE and help inform the difficult decisions regarding treatment choices and reimbursement for this particularly vulnerable population. Methods: We drew upon our collective decades of experience in RWE generation and relevant disciplines (epidemiology, health economics, and biostatistics) to describe challenges inherent to this therapeutic area and to provide potential solutions thereto within healthcare claims databases. Several examples were provided from our experiences in DRE to further illustrate our recommendations for generation of robust RWE in this therapeutic area. Results: Our recommendations focus on considerations for the selection of an appropriate data source, development of a study timeline, exposure allotment (specifically, neuromodulation implantation for patients with DRE), and ascertainment of relevant outcomes. Conclusions: The need for RWE to inform healthcare decisions has never been greater and continues to grow in importance to regulators, payers, physicians, and other key stakeholders. However, as real-world data sources used to generate RWE are typically generated for reasons other than research, rigorous methodology is required to minimize bias and fully unlock their value.