Vection in depth during treadmill walking

Vection has typically been induced in stationary observers (ie conditions providing visual-only information about self-motion). Two recent studies have examined vection during active treadmill walking--one reported that treadmill walking in the same direction as the visually simulated self-motion impaired vection (Onimaru et al, 2010 Journal of Vision 10(7):860), the other reported that it enhanced vection (Seno et al, 2011 Perception 40 747-750; Seno et al, 2011 Attention, Perception, & Psychophysics 73 1467-1476). Our study expands on these earlier investigations of vection during observer active movement. In experiment 1 we presented radially expanding optic flow and compared the vection produced in stationary observers with that produced during walking forward on a treadmill at a 'matched' speed. Experiment 2 compared the vection induced by forward treadmill walking while viewing expanding or contracting optic flow with that induced by viewing playbacks of these same displays while stationary. In both experiments subjects' tracked head movements were either incorporated into the self-motion displays (as simulated viewpoint jitter) or simply ignored. We found that treadmill walking always reduced vection (compared with stationary viewing conditions) and that simulated viewpoint jitter always increased vection (compared with constant velocity displays). These findings suggest that while consistent visual-vestibular information about self-acceleration increases vection, biomechanical self-motion information reduces this experience (irrespective of whether it is consistent or not with the visual input)

Medical, Social, and Other Determinants of Health Care Costs in MassHealth

As part of the mini-symposium entitled Innovations for Vulnerable Populations in Massachusetts, this presentation explores research into expanding the State’s existing risk models to include social determinants of health variables. Potential variables for inclusion in payment models (such as unstable housing, defined as having three or more addresses during a calendar year) have been identified. These models are being developed in support of alternative payment mechanisms for integrated delivery systems

Predicting Key Healthcare Outcomes

As part of the mini-symposium entitled Finding Signals Amidst the Noise, this presentation discusses how risk adjustment makes health care data more informative and enables useful comparisons

Great black-headed gulls Larus Ichythaetus and renecked Phalaropes Phalaropus Lobatus inland Ethiopia

Volume: 3

The Role of Expectation and Memory in the Hindsight Bias Effect: A Test of Cognitive Reconstruction Models

(First Paragraph) The Hindsight Bias Effect (HBE) describes the observation that once people are aware of an outcome to a situation, they have a tendency to falsely believe that they would have predicted the true outcome (see Guibault et al., 2004) Historically, the most popular explanations for this effect can be described as Cognitive Reconstruction Models of retrospective judgment formation (Hawkins & Hastie, 1990). These theories propose the hindsight bias occurs when people do not or cannot directly recall their initial judgment at the point of retrospection. Therefore, people attempt to reconstruct their original predictive judgment by re-judging the situation anew. All of these theories propose that the knowledge of the outcome somehow affects the information or cues used in this reconstruction process, thereby leading to retrospective judgments that are more in favor of the given outcome. However, these Cognitive Reconstruction theories all propose different mechanisms for reconstruction which lead to diverging predictions about what variables should moderate the HBE

Risk-Based Bonus Payments for the Patient-Centered Medical Home

Background The Patient-Centered Medical Home (PCMH) requires fundamental reform of health care financing. We propose a Risk-Based Comprehensive Payment system with risk-adjusted base and bonus payments. Bundled base payments cover the expected cost of primary care services but do not encourage quality. Bonus payments incentivize desired outcomes by rewarding better-than-expected performance in clinical quality, efficiency, and patient-centeredness. Base and bonus payments require credible risk adjustment to discourage practices from cherry-picking easy patients and dumping difficult ones. Methods We estimated models to predict thirteen cost and utilization measures in 17.4 million commercially insured people using diagnoses, age, and sex from Thomson-Reuters MarketScan® 2007 claims data. Using the same data, we imputed assignment of 456,781 people to 436 medium-sized primary care practitioner (PCP) panels (500 – 5000 patients). For each measure, a PCP’s performance is judged by summing the difference between observed (O) and expected (E) outcomes across panel members. For each outcome we calculated: mean; coefficient of variation, or CV = SD/mean; and both individual and grouped R2 as measures of predictive accuracy Results Using risk models to calculate expected outcomes explained 29-49% of the observed patient-level and 85-98% of practice-level variation in performance, with differential variability. Deviation from the mean in total health spending is more variable at the PCP level than other more targeted measures