Service Selection using Predictive Models and Monte-Carlo Tree Search

This article proposes a method for automated service selection to improve treatment efficacy and reduce re-hospitalization costs. A predictive model is developed using the National Home and Hospice Care Survey (NHHCS) dataset to quantify the effect of care services on the risk of re-hospitalization. By taking the patient's characteristics and other selected services into account, the model is able to indicate the overall effectiveness of a combination of services for a specific NHHCS patient. The developed model is incorporated in Monte-Carlo Tree Search (MCTS) to determine optimal combinations of services that minimize the risk of emergency re-hospitalization. MCTS serves as a risk minimization algorithm in this case, using the predictive model for guidance during the search. Using this method on the NHHCS dataset, a significant reduction in risk of re-hospitalization is observed compared to the original selections made by clinicians. An 11.89 percentage points risk reduction is achieved on average. Higher reductions of roughly 40 percentage points on average are observed for NHHCS patients in the highest risk categories. These results seem to indicate that there is enormous potential for improving service selection in the near future

Exploring cancer survivor needs and preferences for communicating personalized cancer statistics from registry data: Qualitative multimethod study

Background: Disclosure of cancer statistics (eg, survival or incidence rates) based on a representative group of patients can help increase cancer survivors’ understanding of their own diagnostic and prognostic situation, and care planning. More recently, there has been an increasing interest in the use of cancer registry data for disclosing and communicating personalized cancer statistics (tailored toward personal and clinical characteristics) to cancer survivors and relatives. Objective: The aim of this study was to explore breast cancer (BCa) and prostate cancer (PCa) survivor needs and preferences for disclosing (what) and presenting (how) personalized statistics from a large Dutch population-based data set, the Netherlands Cancer Registry (NCR). Methods: To elicit survivor needs and preferences for communicating personalized NCR statistics, we created different (non)interactive tools visualizing hypothetical scenarios and adopted a qualitative multimethod study design. We first conducted 2 focus groups (study 1; n=13) for collecting group data on BCa and PCa survivor needs and preferences, using noninteractive sketches of what a tool for communicating personalized statistics might look like. Based on these insights, we designed a revised interactive tool, which was used to further explore the needs and preferences of another group of cancer survivors during individual think-aloud observations and semistructured interviews (study 2; n=11). All sessions were audio-recorded, transcribed verbatim, analyzed using thematic (focus groups) and content analysis (think-aloud observations), and reported in compliance with qualitative research reporting criteria. Results: In both studies, cancer survivors expressed the need to receive personalized statistics from a representative source, with especially a need for survival and conditional survival rates (ie, survival rate for those who have already survived for a certain period). Personalized statistics adjusted toward personal and clinical factors were deemed more relevant and useful to know than generic or average-based statistics. Participants also needed support for correctly interpreting the personalized statistics and putting them into perspective, for instance by adding contextual or comparative information. Furthermore, while thinking aloud, participants experienced a mix of positive (sense of hope) and negative emotions (feelings of distress) while viewing the personalized survival data. Overall, participants preferred simplicity and conciseness, and the ability to tailor the type of visualization and amount of (detailed) statistical information. Conclusions: The majority of our sample of cancer survivors wanted to receive personalized statistics from the NCR. Given the variation in patient needs and preferences for presenting personalized statistics, designers of similar information tools may consider potential tailoring strategies on multiple levels, as well as effective ways for providing supporting information to make sure that the personalized statistics are properly understood. This is encouraging for cancer registries to address this unmet need, but also for those who are developing or implementing personalized data-driven information tools for patients and relatives

Improving manual oxygen titration in preterm infants by training and guideline implementation

To study oxygen saturation (SpO2) targeting before and after training and guideline implementation of manual oxygen titration, two cohorts of preterm infants 21%. ABCs where oxygen therapy was given were identified and analyzed. After training and guideline implementation the %SpO2-wtr increased (median interquartile range (IQR)) 48.0 (19.6-63.9) % vs 61.9 (48.5-72.3) %; p 95% (44.0 (27.8-66.2) % vs 30.8 (22.6-44.5) %; p 95% did not decrease (73% vs 64%; ns) but lasted shorter (2 (0-7) vs 1 (1-3) minute; p < 0.004). CONCLUSION: Training and guideline implementation in manual oxygen titration improved SpO2 targeting in preterm infants with more time spent within the target range and less frequent hyperoxaemia. The durations of hypoxaemia and hyperoxaemia during ABCs were shorter. What is Known: • Oxygen saturation targeting in preterm infants can be challenging and the compliance is low when oxygen is titrated manually. • Hyperoxaemia often occurs after oxygen therapy for oxygen desaturation during apnoeas. What is New: • Training and implementing guidelines improved oxygen saturation targeting and reduced hyperoxaemia. • Training and implementing guidelines improved manual oxygen titration during ABC

Effects of song familiarity, singing training and recent song exposure on the singing of melodies

Findings of a singing experiment are presented in which trained and untrained singers sang melodies of familiar and less familiar Beatles songs from memory and after listening to the original song on CD. Results showed that adopting the correct pitch of a melody was done better by trained singers, and only after listening to the song. Contours of melodies were equally well reproduced by both trained and untrained singers. In contrast, the intervals of a melody were sung more accurately by trained singers than by untrained singers. These findings demonstrate the dominance of contour for remembering melodies and the poorer interval encoding of melodies or the lack of essential singing skills by untrained singers. When singing from memory, almost two-third of the singing came reasonably close to the actual tempo on the CD. This improved to more than 70% after listening to the song on CD. In general, the singing of less familiar melodies improved after song listening. Implications for ‘query by humming’ applications are discussed

Music and choice : adaptive systems and multimodal interaction

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