Importance of Patient History in Artificial Intelligence-Assisted Medical Diagnosis: Comparison Study.

Background: Medical history contributes approximately 80% to a diagnosis, although physical examinations and laboratory investigations increase a physician's confidence in the medical diagnosis. The concept of artificial intelligence (AI) was first proposed more than 70 years ago. Recently, its role in various fields of medicine has grown remarkably. However, no studies have evaluated the importance of patient history in AI-assisted medical diagnosis. Objective: This study explored the contribution of patient history to AI-assisted medical diagnoses and assessed the accuracy of ChatGPT in reaching a clinical diagnosis based on the medical history provided. Methods: Using clinical vignettes of 30 cases identified in The BMJ, we evaluated the accuracy of diagnoses generated by ChatGPT. We compared the diagnoses made by ChatGPT based solely on medical history with the correct diagnoses. We also compared the diagnoses made by ChatGPT after incorporating additional physical examination findings and laboratory data alongside history with the correct diagnoses. Results: ChatGPT accurately diagnosed 76.6% (23/30) of the cases with only the medical history, consistent with previous research targeting physicians. We also found that this rate was 93.3% (28/30) when additional information was included. Conclusions: Although adding additional information improves diagnostic accuracy, patient history remains a significant factor in AI-assisted medical diagnosis. Thus, when using AI in medical diagnosis, it is crucial to include pertinent and correct patient histories for an accurate diagnosis. Our findings emphasize the continued significance of patient history in clinical diagnoses in this age and highlight the need for its integration into AI-assisted medical diagnosis systems.

The differential diagnosis of medical and psychogenic disease in primary care.

Diagnosis and management of psychogenic diseases such as conversion disorder, somatic symptom disorder (SSD), illness anxiety disorder, falsehood disorder, and psychotic disorder require an elaborate biopsychosocial approach and are often challenging. Herein, we propose the following points to differentiate medical diseases from these psychogenic diseases: correspondence between symptoms and objective findings or activities of daily living (ADL) impairment; placebo effect; clear provocative or palliative factors; progressive time course; paroxysmal or intermittent symptoms; unfamiliar but not strange expressions; symptoms worsen during sleep or rest.

Health Insurance Literacy Improvements Among Recently Diagnosed Adolescents and Young Adults With Cancer: Results From a Pilot Randomized Controlled Trial.

PURPOSE: Adolescents and young adults (AYAs; age 18-39 years) with cancer report needing support with health insurance. We conducted a pilot randomized controlled trial to assess the feasibility and acceptability of a virtual health insurance navigation intervention (HIAYA CHAT) to improve health insurance literacy (HIL), awareness of Affordable Care Act (ACA) protections, financial toxicity, and stress. MATERIALS AND METHODS: HIAYA CHAT is a four-session navigator delivered program; it includes psychoeducation on insurance, navigating one's plan, insurance-related laws, and managing costs. Participants were eligible if they could access an internet-capable device, were <1 year from diagnosis, and received treatment from University of Utah Healthcare or Intermountain Health systems. We assessed the feasibility, acceptability, and preliminary efficacy of HIAYA CHAT compared with usual navigation care, including HIL (nine items), insurance knowledge (13 items), ACA protections (eight items), COmprehensive Score for financial Toxicity (COST; 11 items), and Perceived Stress Scale (PSS; four items), using t tests and Cohen's d. RESULTS: From November 2020 to December 2021, N = 86 AYAs enrolled (44.6% participation) and 89.3% completed the 5-month follow-up survey; 68.6% were female, 72.1% were White, 23.3% were Hispanic, 65.1% were age 26-39 years, and 87.2% were privately insured. Of intervention participants (n = 45), 67.4% completed all four sessions; among an exit interview subset (n = 10), all endorsed the program (100%). At follow-up, compared with usual navigation care, intervention participants had greater improvements in HIL, insurance and ACA protections knowledge, and PSS; effect sizes ranged from moderate to large (0.42-0.77). COST did not differ. CONCLUSION: The results support the feasibility and acceptability of HIAYA CHAT with related improvements in HIL.

Developing Medical Education Curriculum Reform Strategies to Address the Impact of Generative AI: Qualitative Study.

BACKGROUND: Generative artificial intelligence (GAI), represented by large language models, have the potential to transform health care and medical education. In particular, GAI's impact on higher education has the potential to change students' learning experience as well as faculty's teaching. However, concerns have been raised about ethical consideration and decreased reliability of the existing examinations. Furthermore, in medical education, curriculum reform is required to adapt to the revolutionary changes brought about by the integration of GAI into medical practice and research. OBJECTIVE: This study analyzes the impact of GAI on medical education curricula and explores strategies for adaptation. METHODS: The study was conducted in the context of faculty development at a medical school in Japan. A workshop involving faculty and students was organized, and participants were divided into groups to address two research questions: (1) How does GAI affect undergraduate medical education curricula? and (2) How should medical school curricula be reformed to address the impact of GAI? The strength, weakness, opportunity, and threat (SWOT) framework was used, and cross-SWOT matrix analysis was used to devise strategies. Further, 4 researchers conducted content analysis on the data generated during the workshop discussions. RESULTS: The data were collected from 8 groups comprising 55 participants. Further, 5 themes about the impact of GAI on medical education curricula emerged: improvement of teaching and learning, improved access to information, inhibition of existing learning processes, problems in GAI, and changes in physicians' professionality. Positive impacts included enhanced teaching and learning efficiency and improved access to information, whereas negative impacts included concerns about reduced independent thinking and the adaptability of existing assessment methods. Further, GAI was perceived to change the nature of physicians' expertise. Three themes emerged from the cross-SWOT analysis for curriculum reform: (1) learning about GAI, (2) learning with GAI, and (3) learning aside from GAI. Participants recommended incorporating GAI literacy, ethical considerations, and compliance into the curriculum. Learning with GAI involved improving learning efficiency, supporting information gathering and dissemination, and facilitating patient involvement. Learning aside from GAI emphasized maintaining GAI-free learning processes, fostering higher cognitive domains of learning, and introducing more communication exercises. CONCLUSIONS: This study highlights the profound impact of GAI on medical education curricula and provides insights into curriculum reform strategies. Participants recognized the need for GAI literacy, ethical education, and adaptive learning. Further, GAI was recognized as a tool that can enhance efficiency and involve patients in education. The study also suggests that medical education should focus on competencies that GAI hardly replaces, such as clinical experience and communication. Notably, involving both faculty and students in curriculum reform discussions fosters a sense of ownership and ensures broader perspectives are encompassed.

The influence of Gamification on medical students' diagnostic decision making and awareness of medical cost: a mixed-method study.

BACKGROUND: The gamification of learning increases student enjoyment, and motivation and engagement in learning tasks. This study investigated the effects of gamification using decision-making cards (DMCs) on diagnostic decision-making and cost using case scenarios. METHOD: Thirty medical students in clinical clerkship participated and were randomly assigned to 14 small groups of 2-3 medical students each. Decision-making was gamified using DMCs with a clinical information heading and medical cost on the front, and clinical information details on the back. First, each team was provided with brief clinical information on case scenarios. Subsequently, DMCs depending on the case were distributed to each team, and team members chose cards one at a time until they reached a diagnosis of the case. The total medical cost was then scored based on the number and contents of cards drawn. Four case scenarios were conducted. The quantitative outcomes including confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical costs were measured before and after our gamification by self-evaluation using a 7-point Likert scale. The qualitative component consisted of a content analysis on the benefits of learning clinical reasoning using DMCs. RESULT: Confidence in effective clinical decision-making, motivation to learn diagnostic decision-making, and awareness of medical cost were significantly higher after the gamification. Furthermore, comparing the clinical case scenario tackled last with the one tackled first, the average medical cost of all cards drawn by students decreased significantly from 11,921 to 8,895 Japanese yen. In the content analysis, seven advantage categories of DMCs corresponding to clinical reasoning components were extracted (information gathering, hypothesis generation, problem representation, differential diagnosis, leading or working diagnosis, diagnostic justification, and management and treatment). CONCLUSION: Teaching medical students clinical reasoning using DMCs can improve clinical decision-making confidence and learning motivation, and reduces medical cost in clinical case scenarios. In addition, it can help students to acquire practical knowledge, deepens their understanding of clinical reasoning, and identifies several important clinical reasoning skills including diagnostic decision-making and awareness of medical costs. Gamification using DMCs can be an effective teaching method for improving medical students' diagnostic decision-making and reducing costs.

Improving decision accuracy using a clinical decision support system for medical students during history-taking: a randomized clinical trial.

BACKGROUND: A clinical diagnostic support system (CDSS) can support medical students and physicians in providing evidence-based care. In this study, we investigate diagnostic accuracy based on the history of present illness between groups of medical students using a CDSS, Google, and neither (control). Further, the degree of diagnostic accuracy of medical students using a CDSS is compared with that of residents using neither a CDSS nor Google. METHODS: This study is a randomized educational trial. The participants comprised 64 medical students and 13 residents who rotated in the Department of General Medicine at Chiba University Hospital from May to December 2020. The medical students were randomly divided into the CDSS group (n = 22), Google group (n = 22), and control group (n = 20). Participants were asked to provide the three most likely diagnoses for 20 cases, mainly a history of a present illness (10 common and 10 emergent diseases). Each correct diagnosis was awarded 1 point (maximum 20 points). The mean scores of the three medical student groups were compared using a one-way analysis of variance. Furthermore, the mean scores of the CDSS, Google, and residents' (without CDSS or Google) groups were compared. RESULTS: The mean scores of the CDSS (12.0 ± 1.3) and Google (11.9 ± 1.1) groups were significantly higher than those of the control group (9.5 ± 1.7; p = 0.02 and p = 0.03, respectively). The residents' group's mean score (14.7 ± 1.4) was higher than the mean scores of the CDSS and Google groups (p = 0.01). Regarding common disease cases, the mean scores were 7.4 ± 0.7, 7.1 ± 0.7, and 8.2 ± 0.7 for the CDSS, Google, and residents' groups, respectively. There were no significant differences in mean scores (p = 0.1). CONCLUSIONS: Medical students who used the CDSS and Google were able to list differential diagnoses more accurately than those using neither. Furthermore, they could make the same level of differential diagnoses as residents in the context of common diseases. TRIAL REGISTRATION: This study was retrospectively registered with the University Hospital Medical Information Network Clinical Trials Registry on 24/12/2020 (unique trial number: UMIN000042831).

Do clinical interview transcripts generated by speech recognition software improve clinical reasoning performance in mock patient encounters? A prospective observational study.

BACKGROUND: To investigate whether speech recognition software for generating interview transcripts can provide more specific and precise feedback for evaluating medical interviews. METHODS: The effects of the two feedback methods on student performance in medical interviews were compared using a prospective observational trial. Seventy-nine medical students in a clinical clerkship were assigned to receive either speech-recognition feedback (n = 39; SRS feedback group) or voice-recording feedback (n = 40; IC recorder feedback group). All students' medical interviewing skills during mock patient encounters were assessed twice, first using a mini-clinical evaluation exercise (mini-CEX) and then a checklist. Medical students then made the most appropriate diagnoses based on medical interviews. The diagnostic accuracy, mini-CEX, and checklist scores of the two groups were compared. RESULTS: According to the study results, the mean diagnostic accuracy rate (SRS feedback group:1st mock 51.3%, 2nd mock 89.7%; IC recorder feedback group, 57.5%-67.5%; F(1, 77) = 4.0; p = 0.049), mini-CEX scores for overall clinical competence (SRS feedback group: 1st mock 5.2 ± 1.1, 2nd mock 7.4 ± 0.9; IC recorder feedback group: 1st mock 5.6 ± 1.4, 2nd mock 6.1 ± 1.2; F(1, 77) = 35.7; p < 0.001), and checklist scores for clinical performance (SRS feedback group: 1st mock 12.2 ± 2.4, 2nd mock 16.1 ± 1.7; IC recorder feedback group: 1st mock 13.1 ± 2.5, 2nd mock 13.8 ± 2.6; F(1, 77) = 26.1; p < 0.001) were higher with speech recognition-based feedback. CONCLUSIONS: Speech-recognition-based feedback leads to higher diagnostic accuracy rates and higher mini-CEX and checklist scores. TRIAL REGISTRATION: This study was registered in the Japan Registry of Clinical Trials on June 14, 2022. Due to our misunderstanding of the trial registration requirements, we registered the trial retrospectively. This study was registered in the Japan Registry of Clinical Trials on 7/7/2022 (Clinical trial registration number: jRCT1030220188).

COVID-19-Related Employment Disruptions and Increased Financial Burden Among Survivors of Adolescent and Young Adult Cancer.

Background: Financial burden is a major concern for survivors of adolescent and young adult (AYA) cancers. We identified if employment disruptions during the COVID-19 pandemic affected AYA survivors' financial burden. Methods: AYAs who were enrolled in a cancer patient navigation program were e-mailed a survey in fall 2020. Survey items included sociodemographics, employment disruption, and two measures of financial burden: COmprehensive Score for Financial Toxicity (COST) and material and behavioral financial hardship items (for any reason, COVID-19 induced, cancer induced). Financial burden outcomes were dichotomized at the median (COST = 21; financial hardship = 3). The association of employment disruptions and sociodemographics with financial burden was assessed using multivariable logistic regression models. Results: Reduced hours/job loss was reported by 24.0% of 341 participants. Survivors with a high school education or less (odds ratio [OR]: 2.70; 95% confidence interval [CI]: 1.21-6.03) or who had decreased hours or job loss (OR: 3.97; 95% CI: 2.01-7.84) had greater odds for high financial toxicity. Reduced hours/job loss was the only factor associated with high material and behavioral financial hardship for both any reason (OR: 2.75; 95% CI: 1.41-5.33) and owing to COVID-19 (OR: 4.98; 95% CI: 2.28-10.92). Cancer treatment since March 2020 was associated with cancer-induced high material and behavioral financial hardship (OR: 3.31; 95% CI: 1.96-5.58). Conclusion: Employment disruptions owing to the COVID-19 pandemic, lower education levels, and cancer treatment were associated with high financial burden among AYA cancer survivors. Our findings suggest the need for multilevel interventions to identify and address financial burden among vulnerable cancer survivors.

Sources of informal financial support among adolescent and young adult cancer survivors: a mixed methods analysis from the HIAYA CHAT study.

PURPOSE: The purpose of this exploratory sequential mixed methods study was to describe the sources of informal financial support used by adolescent and young adult (AYA) cancer survivors and how financial toxicity and demographic factors were associated with different types and magnitudes of informal financial support. METHODS: This analysis is part of a larger health insurance literacy study that included pre-trial interviews and a randomized controlled trial (RCT) for AYA cancer survivors. Eligible study participants were 18 years of age, diagnosed with cancer as an AYA (15-39 years), insured, and for the RCT sample less than 1 year from diagnosis. Interview audio was transcribed, quality checked, and thematically analyzed. RCT baseline and follow-up surveys captured informal financial support use. Chi-squared and Fisher's exact tests were used to assess differences in informal financial support type use and frequency by financial toxicity and AYA demographics. RESULTS: A total of N = 24 and N = 86 AYAs participated in pre-trial interviews and the RCT respectively. Interview participants reported a variety of informal financial support sources including savings, community, family/friends, and fundraisers. However, only half of participants reported their informal financial support to be sufficient. High financial toxicity was associated with the most types of informal financial support and a higher magnitude of use. The lowest income group accessed informal financial supports less frequently than higher income groups. CONCLUSION: Our study demonstrates that AYA survivors experiencing financial toxicity frequently turn to informal sources of financial support and the magnitude is associated with financial toxicity. However, low-income survivors, and other at-risk survivors, may not have access to informal sources of financial support potentially widening inequities.

Adaptation and Development of a Health Insurance Education Program for Adolescent and Young Adult Cancer Patients.

Introduction: Adolescent and young adult (AYA) cancer patients report low health insurance literacy. We interviewed AYAs to gain their perspectives on the content and delivery of the Huntsman-Intermountain adolescent and young adult cancer health insurance (HIAYA CHAT) program. Methods: From October 2019 to March 2020, we interviewed N = 24 insured AYAs with cancer aged 18-39 years. Participants were recruited by study staff and social media. We elicited feedback on proposed HIAYA CHAT content including insurance terms/definitions, insurance coverage components, insurance legislation, cost management, and the suitability of the intervention delivery. Interviews were audio recorded, transcribed, and inductively analyzed using NVivo 12. We coded feedback into three categories of results: (1) delivery of HIAYA CHAT, (2) endorsements of proposed HIAYA CHAT content, and (3) recommendations to expand and improve HIAYA CHAT. Results: Participants were 58% female, 79% non-Hispanic white, and 79% receiving cancer treatment. First, AYAs felt that three to four different content areas, each 30 minutes or less, seemed feasible and that delivery should be through an online platform. Second, participants reflected on times during their treatment when having more insurance knowledge (e.g., appeals process) would have been useful, endorsing content about insurance policies, legal protections, and legislative impacts on health care costs. Third, AYAs recommended evaluating patients' health insurance literacy before starting HIAYA CHAT and wanted concrete learning tools (e.g., sample medical bills and budgeting). Conclusion: AYAs with cancer wanted health insurance education to include information about insurance policies and protections using tangible examples through an online delivery. Describing AYAs preferences for interventions may improve relevance and efficacy of the program. Clinical Trial Registration: ClinicalTrials.gov Identifier: NCT04448678.

Hybrid PBL and Pure PBL: Which one is more effective in developing clinical reasoning skills for general medicine clerkship?-A mixed-method study.

This study aims to compare the effectiveness of Hybrid and Pure problem-based learning (PBL) in teaching clinical reasoning skills to medical students. The study sample consisted of 99 medical students participating in a clerkship rotation at the Department of General Medicine, Chiba University Hospital. They were randomly assigned to Hybrid PBL (intervention group, n = 52) or Pure PBL group (control group, n = 47). The quantitative outcomes were measured with the students' perceived competence in PBL, satisfaction with sessions, and self-evaluation of competency in clinical reasoning. The qualitative component consisted of a content analysis on the benefits of learning clinical reasoning using Hybrid PBL. There was no significant difference between intervention and control groups in the five students' perceived competence and satisfaction with sessions. In two-way repeated measure analysis of variance, self-evaluation of competency in clinical reasoning was significantly improved in the intervention group in "recalling appropriate differential diagnosis from patient's chief complaint" (F(1,97) = 5.295, p = 0.024) and "practicing the appropriate clinical reasoning process" (F(1,97) = 4.016, p = 0.038). According to multiple comparisons, the scores of "recalling appropriate history, physical examination, and tests on clinical hypothesis generation" (F(1,97) = 6.796, p = 0.011), "verbalizing and reflecting appropriately on own mistakes," (F(1,97) = 4.352, p = 0.040) "selecting keywords from the whole aspect of the patient," (F(1,97) = 5.607, p = 0.020) and "examining the patient while visualizing his/her daily life" (F(1,97) = 7.120, p = 0.009) were significantly higher in the control group. In the content analysis, 13 advantage categories of Hybrid PBL were extracted. In the subcategories, "acquisition of knowledge" was the most frequent subcategory, followed by "leading the discussion," "smooth discussion," "getting feedback," "timely feedback," and "supporting the clinical reasoning process." Hybrid PBL can help acquire practical knowledge and deepen understanding of clinical reasoning, whereas Pure PBL can improve several important skills such as verbalizing and reflecting on one's own errors and selecting appropriate keywords from the whole aspect of the patient.

Financial burdens during the COVID-19 pandemic are related to disrupted healthcare utilization among survivors of adolescent and young adult cancers.

PURPOSE: We examined whether financial burdens occurring during the COVID-19 pandemic impacted healthcare utilization among survivors of adolescent and young adult cancers. METHODS: We surveyed survivors enrolled in a patient navigation program to obtain self-reports of delayed/skipped cancer care or other care, changes to medication obtainment, and changes to medication use since the COVID-19 pandemic began. Reported financial burdens were defined as financial toxicity in the past 4 weeks (COmprehensive Score for financial Toxicity [COST] ≤ median 21) and material hardships (range = 4-11) since March 2020. Adjusted logistic regression models calculated associations and effect modification by gender. RESULTS: Survivors (n = 341) were mostly female (61.3%) and non-Hispanic White (83.3%). Nearly 20% delayed/skipped cancer care, 35.2% delayed/skipped other care, 19.1% changed medication obtainment, and 12.6% changed medication use. Greater material hardships were associated with delayed/skipped cancer care (odds ratio (OR) = 3.13, 95% CI = 1.44-6.81) and other care (OR = 2.17, 95% CI = 1.18-3.98), and changed medication obtainment (OR = 2.72, 95% CI = 1.43-5.18) or use (OR = 4.49, 95% CI = 2.05-9.80). Financial toxicity was associated with delayed/skipped other care (OR = 2.53, 95% CI = 1.31-4.89) and changed medication obtainment (OR = 1.96, 95% CI = 1.01-3.83) and medication use (OR = 3.73, 95% CI = 1.59-8.73). The association of material hardships and any changes in healthcare utilization was greater among female compared to male survivors. CONCLUSION: Financial burdens experienced during the pandemic impeded survivors' ability to utilize necessary healthcare, with worse impacts among female survivors. IMPLICATIONS FOR CANCER SURVIVORS: Delayed or skipped healthcare may lead to an increased cancer mortality or severity of therapy-related conditions. Providing resources that enable survivors experiencing financial burdens to continue critical cancer and preventive care during the COVID-19 pandemic is a priority.

Association Between Physician Empathy and Difficult Patient Encounters: a Cross-Sectional Study.

BACKGROUND: Physicians frequently experience patients as difficult. Our study explores whether more empathetic physicians experience fewer patient encounters as difficult. OBJECTIVE: To investigate the association between physician empathy and difficult patient encounters (DPEs). DESIGN: Cross-sectional study. PARTICIPANTS: Participants were 18 generalist physicians with 3-8 years of experience. The investigation was conducted from August-September 2018 and April-May 2019 at six healthcare facilities. MAIN MEASURES: Based on the Jefferson Scale of Empathy (JSE) scores, we classified physicians into low and high empathy groups. The physicians completed the Difficult Doctor-Patient Relationship Questionnaire-10 (DDPRQ-10) after each patient visit. Scores ≥ 31 on the DDPRQ-10 indicated DPEs. We implemented multilevel mixed-effects logistic regression models to examine the association between physicians' empathy and DPE, adjusting for patient-level covariates (age, sex, history of mental disorders) and with physician-level clustering. KEY RESULTS: The median JSE score was 114 (range: 96-126), and physicians with JSE scores 96-113 and 114-126 were assigned to low and high empathy groups, respectively (n = 8 and 10 each); 240 and 344 patients were examined by physicians in the low and high empathy groups, respectively. Among low empathy physicians, 23% of encounters were considered difficulty, compared to 11% among high empathy groups (OR: 0.37; 95% CI = 0.19-0.72, p = 0.004). JSE scores and DDPRQ-10 scores were negatively correlated (r = -0.22, p < 0.01). CONCLUSION: Empathetic physicians were less likely to experience encounters as difficult. Empathy appears to be an important component of physician perception of encounter difficulty.

Validating the representation of distance between infarct diseases using word embedding.

BACKGROUND: The pivot and cluster strategy (PCS) is a diagnostic reasoning strategy that automatically elicits disease clusters similar to a differential diagnosis in a batch. Although physicians know empirically which disease clusters are similar, there has been no quantitative evaluation. This study aimed to determine whether inter-disease distances between word embedding vectors using the PCS are a valid quantitative representation of similar disease groups in a limited domain. METHODS: Abstracts were extracted from the Ichushi Web database and subjected to morphological analysis and training using Word2Vec, FastText, and GloVe. Consequently, word embedding vectors were obtained. For words including "infarction," we calculated the cophenetic correlation coefficient (CCC) as an internal validity measure and the adjusted rand index (ARI), normalized mutual information (NMI), and adjusted mutual information (AMI) with ICD-10 codes as the external validity measures. This was performed for each combination of metric and hierarchical clustering method. RESULTS: Seventy-one words included "infarction," of which 38 diseases matched the ICD-10 standard with the appearance of 21 unique ICD-10 codes. When using Word2Vec, the CCC was most significant at 0.8690 (metric and method: euclidean and centroid), whereas the AMI was maximal at 0.4109 (metric and method: cosine and correlation, and average and weighted). The NMI and ARI were maximal at 0.8463 and 0.3593, respectively (metric and method: cosine and complete). FastText and GloVe generally resulted in the same trend as Word2Vec, and the metric and method that maximized CCC differed from the ones that maximized the external validity measures. CONCLUSIONS: The metric and method that maximized the internal validity measure differed from those that maximized the external validity measures; both produced different results. The cosine distance should be used when considering ICD-10, and the Euclidean distance when considering the frequency of word occurrence. The distributed representation, when trained by Word2Vec on the "infarction" domain from a Japanese academic corpus, provides an objective inter-disease distance used in PCS.

The relationship between CPAP and health literacy: A prospective observational study.

Background: We aimed to assess differences in health literacy between those who improved CPAP non-adherent and those who remained non-adherent. Methods: We included patients newly diagnosed with sleep apnea syndrome who had started CPAP therapy between February 2019 and October 2020 with ≥6 follow-up months or who self-interrupted CPAP therapy <6 months. We recorded the CPAP wearing time after 3 and 6 months. Patients were divided into the CPAP adherent (using CPAP for ≥4 h per night) and non-adherent (self-interrupted CPAP therapy/using CPAP for <4 h per night) groups. We compared the European Health Literacy Survey Questionnaire 47 (HLS-EU-Q47) score between those who were CPAP non-adherent after 3 months and become CPAP adherent after 6 months, and those who remained non-adherent after 6 months. Results: At 3 months, 34 patients were CPAP non-adherent. After 6 months, there were 7 and 27 patients in the CPAP adherent and non-adherent groups, respectively. There was a significant difference in the HLS-EU-Q47 score between the patients who became adherent to CPAP and who remained non-adherent after 6 months. Conclusion: Previously non-adherent patients who subsequently became adherent tended to have higher health literacy.

HIAYA CHAT study protocol: a randomized controlled trial of a health insurance education intervention for newly diagnosed adolescent and young adult cancer patients.

BACKGROUND: For adolescent and young adult (AYA) cancer patients aged 18 to 39 years, health insurance literacy is crucial for an effective use of the health care system. AYAs often face high out-of-pocket costs or have unmet health care needs due to costs. Improving health insurance literacy could help AYAs obtain appropriate and affordable health care. This protocol illustrates a randomized controlled trial testing a virtual health insurance education intervention among AYA patients. METHODS: This is a two-arm multisite randomized controlled trial. A total of 80 AYAs diagnosed with cancer in the Mountain West region will be allocated to either usual navigation care or tailored health insurance education intervention with a patient navigator that includes usual care. All participants will complete a baseline and follow-up survey 5 months apart. The primary outcomes are feasibility (number enrolled and number of sessions completed) and acceptability (5-point scale on survey measuring satisfaction of the intervention). The secondary outcomes are preliminary efficacy measured by the Health Insurance Literacy Measure and the COmprehensive Score for financial Toxicity. DISCUSSION: This trial makes a timely contribution to test the feasibility and acceptability of a virtual AYA-centered health insurance education program. TRIAL REGISTRATION: ClinicalTrials.gov NCT04448678. Registered on June 26, 2020.