Assessing Medicare Beneficiaries’ Strength‐of‐Preference Scores for Health Care Options: How Engaging Does the Elicitation Technique Need to Be?

The objective was to determine if participants’ strength‐of‐preference scores for elective health care interventions at the end‐of‐life (EOL) elicited using a non‐engaging technique are affected by their prior use of an engaging elicitation technique

Psychometric Results of a New Patient-Reported Outcome Measure for Uveal Melanoma Post-Brachytherapy Treatment: The PROM-UM

The objective of this study was to evaluate the psychometric properties of a new patient-reported outcome instrument intended for use with patients who have undergone brachytherapy for uveal melanoma (PROM-UM). Classical test theory and item response theory were used to evaluate the performance of individual items and domains. A convenience sample of 439 participants who had undergone brachytherapy for uveal melanoma from one of three North American ocular oncology treatment centers were included in this cross-sectional study. Exploratory factor analysis identified three domains which were labelled “Symptom Impairment”, “Worry”, and “Discomfort”. The acceptability of the instrument was supported by little missing data (range = 0.00–1.14%) and low maximum endorsement (range = 0.00–1.82%). Item-total (range = 0.68–0.85) and inter-item (range = 0.74–0.80) correlations indicated acceptable reliability. Discrimination and difficulty were assessed using item response theory. Items in all three domains indicated moderate to very high discrimination (range = 1.00–4.10). Two items in the Symptom Impairment domain were too difficult to measure. Response ranges in the other two domains demonstrated acceptable difficulty. These results from the study indicate that this new patient-reported outcome instrument can be used with patients treated with brachytherapy for uveal melanoma. Providers could use this instrument to help inform post-treatment management

Reinforcement learning based recommender systems: A survey

Recommender systems (RSs) have become an inseparable part of our everyday lives. They help us find our favorite items to purchase, our friends on social networks, and our favorite movies to watch. Traditionally, the recommendation problem was considered to be a classification or prediction problem, but it is now widely agreed that formulating it as a sequential decision problem can better reflect the user-system interaction. Therefore, it can be formulated as a Markov decision process (MDP) and be solved by reinforcement learning (RL) algorithms. Unlike traditional recommendation methods, including collaborative filtering and content-based filtering, RL is able to handle the sequential, dynamic user-system interaction and to take into account the long-term user engagement. Although the idea of using RL for recommendation is not new and has been around for about two decades, it was not very practical, mainly because of scalability problems of traditional RL algorithms. However, a new trend has emerged in the field since the introduction of deep reinforcement learning (DRL), which made it possible to apply RL to the recommendation problem with large state and action spaces. In this paper, a survey on reinforcement learning based recommender systems (RLRSs) is presented. Our aim is to present an outlook on the field and to provide the reader with a fairly complete knowledge of key concepts of the field. We first recognize and illustrate that RLRSs can be generally classified into RL- and DRL-based methods. Then, we propose an RLRS framework with four components, i.e., state representation, policy optimization, reward formulation, and environment building, and survey RLRS algorithms accordingly. We highlight emerging topics and depict important trends using various graphs and tables. Finally, we discuss important aspects and challenges that can be addressed in the future.Comment: To appear in ACM Computing Survey

Explainable Analytics to Predict the Quality of Life in Patients with Prostate Cancer from Longitudinal Data

Prostate cancer (PCa) is a complicated cancer with high level of unexplained variability that might affect the patient’s health-related quality of life (HRQoL). Using 2670 patients’ information with 433 measures per patient, our objective is to identify the minimal set of important variables which can predict 1-year follow-up HRQoL for PCa patients while adding interpretability to the proposed model. We address three problems of dimension reduction, prediction, and interpretability by first developing deep neural networks on top of a clustering algorithm to extract minimal set of important variables of baseline visit. Second, we build a model to predict a 1-year follow-up of HRQoL for PCa patients using the extracted important baseline variables. Third, we utilize Bayesian networks method to provide insights into the proposed model results to discover the relationship between patients’ baseline variables and their 1-year follow-up satisfaction. The results support the use of the proposed machine-learning technique as an essential tool in identifying potential baseline variables for predicting 1-year HRQoL. Furthermore, our approach to interpret the findings will help to establish guidelines for a better shared decision-making platform for PCa patients

Surgical assessment: measuring unobserved health

Background: The federal and provincial governments in Canada have invested an enormous amount of resources to measure, report and reduce surgical wait times. Yet these measures under-report the wait period that patients’ actually experience, because they do not capture the length of time a patient spends waiting to see the surgeon for a surgical assessment. This unmeasured time is referred to as the “wait one” (W1). Little is known about W1 and the effects that this has on patients’ health. Similarly, it is not understood whether patients waiting for surgical assessment actually want or need surgery. Existing administrative and clinical dataset do not capture information on health and decision-making while the patient is waiting for care form a specialist. The objective of this proposed study is to understand the impact that W1 for elective surgeries has on the health of patients and to determine whether this time can be reduced. Methods/Design A prospective survey design will be used to measure the health of patients waiting for surgical assessment. Working with the support of the surgical specialities in Vancouver Coastal Health, we will survey patients immediately after being referred for surgical assessment, and every four months thereafter, until they are seen by the surgeon. Validated survey instruments will be used, including: generic and condition-specific health status questionnaires, pain and depression assessments. Other factors that will be measured include: patients’ knowledge about their condition, and their desired autonomy in the decision making process. We have piloted data collection in one surgical specialty in order to demonstrate feasibility. Discussion The results from this study will be used to quantify changes in patients’ health while they wait for surgical assessment. Based on this, policy- and decision-makers could design care interventions during W1, aimed at mitigating any negative health consequences associated with waiting. The results from this study will also be used to better understand whether there are factors that predict patients’ desire to proceed to surgery. These could be used to guide future research into experimenting with interventions to minimize inappropriate referrals and where they are best targeted.Orthopaedics, Department ofNon UBCMedicine, Faculty ofPopulation and Public Health (SPPH), School ofReviewedFacult

Testing the feasibility of eliciting preferences for health states from adolescents using direct methods

Abstract Background Measuring adolescents’ preferences for health states can play an important role in evaluating the delivery of pediatric healthcare. However, formal evaluation of the common direct preference elicitation methods for health states has not been done with adolescents. Therefore, the purpose of this study is to test how these methods perform in terms of their feasibility, reliability, and validity for measuring health state preferences in adolescents. Methods This study used a web-based survey of adolescents, 18 years of age or younger, living in the United States. The survey included four health states, each comprised of six attributes. Preferences for these health states were elicited using the visual analogue scale, time trade-off, and standard gamble. The feasibility, test-retest reliability, and construct validity of each of these preference elicitation methods were tested and compared. Results A total of 144 participants were included in this study. Using a web-based survey format to elicit preferences for health states from adolescents was feasible. A majority of participants completed all three elicitation methods, ranked those methods as being easy, with very few requiring assistance from someone else. However, all three elicitation methods demonstrated weak test-retest reliability, with Kendall’s tau-a values ranging from 0.204 to 0.402. Similarly, all three methods demonstrated poor construct validity, with 9–50% of all rankings aligning with our expectations. There were no significant differences across age groups. Conclusions Using a web-based survey format to elicit preferences for health states from adolescents is feasible. However, the reliability and construct validity of the methods used to elicit these preferences when using this survey format are poor. Further research into the effects of a web-based survey approach to eliciting preferences for health states from adolescents is needed before health services researchers or pediatric clinicians widely employ these methods

The impact of chronic airway disease on symptom severity and global suffering in Canadian rhinosinusitis patients

Background: Patients with Chronic Rhinosinusitis (CRS) can suffer from a significant decline in their quality of life. CRS patients have a high prevalence of comorbid conditions and it is important to understand the impact of these conditions on their CRS-related quality of life. This study measures the impacts of chronic pulmonary comorbidities on quality of life, pain, and depression scores among patients with CRS awaiting Endoscopic Sinus Surgery (ESS). Methods: This study is based on cross-sectional analysis of prospectively collected patient-reported outcome data collected pre-operatively from patients waiting for ESS. Surveys were administered to patients to assess sino-nasal morbidity (SNOT-22), depression and pain. The impact of pulmonary comorbidity on SNOT-22 scores, pain and depression was measured. Results: Two hundred fifthy-three patients were included in the study, 91 with chronic pulmonary comorbidity. The mean SNOT-22 scores were significantly higher among patients with chronic pulmonary comorbidities than among patients without (37 and 48, respectively). This difference is large enough to be clinically significant. Patients with chronic pulmonary comorbidities reported slightly higher depression scores than those without. Conclusions: This study found that among CRS patients waiting for ESS, chronic pulmonary comorbidities are strongly associated with significantly higher symptom burden.Medicine, Faculty ofOther UBCNon UBCSurgery, Department ofReviewedFacult

The impact of comorbid depression in chronic rhinosinusitis on post-operative sino-nasal quality of life and pain following endoscopic sinus surgery

Background: Depression and chronic pain are debilitating disorders that co-exist with many chronic diseases. Chronic rhinosinusitis (CRS) is no exception. Nonetheless, little is known about the association between these co-related conditions and the treatment of CRS. The objective of this study is to measure outcomes following endoscopic sinus surgery (ESS) in CRS patients reporting significant pre-operative depression and pain. Methods: This is a prospective longitudinal cohort study examining patients with CRS who had failed maximal medical therapy and subsequently underwent ESS. Participants completed a several patient-reported outcome (PRO) instruments pre-operatively and 6 months post-operatively. The PROs included the Sinonasal Outcome Test-22 (SNOT-22), the Patient Health Questionnaire (PHQ-9) measuring symptoms of depression and an assessment of chronic pain using the pain intensity (P), interference with enjoyment of life (E) and general (G) activity instrument, the PEG instrument. Results: The study had 142 participants complete their pre-operative and post-operative surveys. The participation rate was 40.1% among eligible patients. The prevalence of at least moderate depression was 22 patients (15.5%) among participants. Compared with non-depressed participants, the pre-operative sino-nasal disease burden and pain scores were higher among depressed participants (p <  0.001) and the gain in health following surgery was smaller (p <  0.001). Conclusions: Pre-operative disease burden is higher among depressed patients. Post-operative gains in sino-nasal quality of life attributable to endoscopic sinus surgery were significantly smaller among depressed participants. Pre-operative screening for depression could identify opportunities for medical intervention and improve outcomes among CRS patients.Medicine, Faculty ofOther UBCPopulation and Public Health (SPPH), School ofSurgery, Department ofReviewedFacult

Wait lists and adult general surgery: is there a socioeconomic dimension in Canada?

Background: Little is known about whether patients’ socioeconomic status influences their access to elective general surgery in Canada. The purpose of this study was to assess the association between socioeconomic status and wait times for elective general surgery. Methods: Analysis of prospectively recruited participants’ data. The setting was six hospitals in the Vancouver Coastal Health Authority, a geographically defined region that includes Vancouver, British Columbia, Canada. Participants had elective general surgery between October 2013 and April 2017, community dwelling, aged 19 years or older and could complete survey forms. The outcome measure was wait time, defined as the number of weeks between being registered for elective general surgery and surgery date. Results: One thousand three hundred twenty elective general surgery participants were included in the study. The response rate among eligible patients was 53%. Regression analyses found no statistically significant association between patients’ wait time with SES, adjusting for health status, cancer status, surgical priority level, comorbidity burden and demographic characteristics. Participants with proven or suspected cancer status had shorter waits relative to participants waiting for surgery for benign conditions. Participants with at least one comorbidity tended to experience shorter waits of approximately 5 weeks (p < 0.01). Pre-operative pain or depression/anxiety were not associated with shorter wait times. Conclusions: Although this study found no relationship between SES and surgical wait time for elective general surgeries in the study hospitals, patients in lower SES categories reported worse health when assigned to the surgical queue.Medicine, Faculty ofOther UBCNon UBCPopulation and Public Health (SPPH), School ofSurgery, Department ofReviewedFacult