Modeling the Effects of Formulary Exclusions: How Many Patients Could Be Affected by a Specific Exclusion?

Background: Medication formularies, initially designed to promote the use of cost-effective generic drugs, are now designed to maximize financial benefits for the pharmacy benefit management companies that negotiate purchase prices. In the second-largest pharmacy benefit management formulary that is publicly available, 55% of mandated substitutions are not for generic or biosimilar versions of the same active ingredient and/or formulation and may not be medically or financially beneficial to patients. Methods: We modeled the effect of excluding novel agents for atrial fibrillation/venous thromboembolism, migraine prevention, and psoriasis, which all would require substitution with a different active ingredient. Using population data, market share of the 2 largest US formularies, and 2021 prescription data, we calculated how many people could be affected by such exclusions. Using data from the published literature, we calculated how many of those individuals are likely to discontinue treatment and/or have adverse events due to a formulary exclusion. Results: The number of people likely to have adverse events due to the exclusion could be as high as 1 million for atrial fibrillation/venous thromboembolism, 900 000 for migraine prevention, and 500 000 for psoriasis. The numbers likely to discontinue treatment for their condition are as high as 924 000 for atrial fibrillation/venous thromboembolism, 646 000 for migraine, and 138 000 for psoriasis. Conclusion: Substitution with a nonequivalent treatment is common in formularies currently in use and is not without substantial consequences for hundreds of thousands of patients. Forced medication substitution results in costly increases in morbidity and mortality and should be part of the cost-benefit analysis of any formulary exclusion.

Testing non-wearable fall detection methods in the homes of older adults.

In this paper, we describe two longitudinal studies in which fall detection sensor technology was tested in the homes of older adults. The first study tested Doppler radar, a two-webcam system, and a depth camera system in ten apartments for two years. This continuous data collection allowed us to investigate the real-world setting of target users and compare the advantages and limitations of each sensor modality. Based on this study, the depth camera was chosen for a current ongoing study in which depth camera systems have been installed in 94 additional older adult apartments. We include a discussion of the different sensor systems, the pros and cons of each, and results of the fall detection and false alarms in the older adult homes.

Automated In-Home Fall Risk Assessment and Detection Sensor System for Elders.

PURPOSE OF THE STUDY: Falls are a major problem for the elderly people leading to injury, disability, and even death. An unobtrusive, in-home sensor system that continuously monitors older adults for fall risk and detects falls could revolutionize fall prevention and care. DESIGN AND METHODS: A fall risk and detection system was developed and installed in the apartments of 19 older adults at a senior living facility. The system includes pulse-Doppler radar, a Microsoft Kinect, and 2 web cameras. To collect data for comparison with sensor data and for algorithm development, stunt actors performed falls in participants' apartments each month for 2 years and participants completed fall risk assessments (FRAs) using clinically valid, standardized instruments. The FRAs were scored by clinicians and recorded by the sensing modalities. Participants' gait parameters were measured as they walked on a GAITRite mat. These data were used as ground truth, objective data to use in algorithm development and to compare with radar and Kinect generated variables. RESULTS: All FRAs are highly correlated (p < .01) with the Kinect gait velocity and Kinect stride length. Radar velocity is correlated (p < .05) to all the FRAs and highly correlated (p < .01) to most. Real-time alerts of actual falls are being sent to clinicians providing faster responses to urgent situations. IMPLICATIONS: The in-home FRA and detection system has the potential to help older adults remain independent, maintain functional ability, and live at home longer.

Fall detection in homes of older adults using the Microsoft Kinect.

A method for detecting falls in the homes of older adults using the Microsoft Kinect and a two-stage fall detection system is presented. The first stage of the detection system characterizes a person's vertical state in individual depth image frames, and then segments on ground events from the vertical state time series obtained by tracking the person over time. The second stage uses an ensemble of decision trees to compute a confidence that a fall preceded on a ground event. Evaluation was conducted in the actual homes of older adults, using a combined nine years of continuous data collected in 13 apartments. The dataset includes 454 falls, 445 falls performed by trained stunt actors and nine naturally occurring resident falls. The extensive data collection allows for characterization of system performance under real-world conditions to a degree that has not been shown in other studies. Cross validation results are included for standing, sitting, and lying down positions, near (within 4 m) versus far fall locations, and occluded versus not occluded fallers. The method is compared against five state-of-the-art fall detection algorithms and significantly better results are achieved.

Average in-home gait speed: investigation of a new metric for mobility and fall risk assessment of elders.

A study was conducted to assess how a new metric, average in-home gait speed (AIGS), measured using a low-cost, continuous, environmentally mounted monitoring system, compares to a set of traditional physical performance instruments used for mobility and fall risk assessment of elderly adults. Sixteen participants were recruited from a local independent living facility. In addition to having their gait monitored continuously in their home for an average of eleven months, the participants completed a monthly clinical assessment consisting of a set of traditional assessment instruments: Habitual Gait Speed, Timed-Up and Go, Short Physical Performance Battery, Berg Balance Scale--short form, and Multidirectional Reach Test. A methodology is developed to assess which of these instruments may work well with the largest subset of older adults, is best suited for detecting changes in an individual over time, and most reliably captures the true mobility level of an individual. Using the ability of an instrument to predict how an individual would score on all the instruments as a metric, AIGS performs best, having better predictive ability than the traditional instruments. AIGS also displays the best agreement between observed and smoothed values, indicating it has the lowest intra-individual test-retest variability of the instruments. AIGS, measured continuously, during normal everyday activity, represents a significant shift in assessment methodology compared to infrequently assessed, traditional physical performance instruments. Continuous, in-home data may provide a more accurate and precise picture of the physical function of older adults, leading to improved mobility and fall risk assessment.

Automated health alerts from Kinect-based in-home gait measurements.

A method for automatically generating alerts to clinicians in response to changes in in-home gait parameters is investigated. Kinect-based gait measurement systems were installed in apartments in a senior living facility. The systems continuously monitored the walking speed, stride time, and stride length of apartment residents. A framework for modeling uncertainty in the residents' gait parameter estimates, which is critical for robust change detection, is developed; along with an algorithm for detecting changes that may be clinically relevant. Three retrospective case studies, of individuals who had their gait monitored for periods ranging from 12 to 29 months, are presented to illustrate use of the alert method. Evidence suggests that clinicians could be alerted to health changes at an early stage, while they are still small and interventions may be most successful. Additional potential uses are also discussed.

Toward a passive low-cost in-home gait assessment system for older adults.

In this paper, we propose a webcam-based system for in-home gait assessment of older adults. A methodology has been developed to extract gait parameters including walking speed, step time, and step length from a 3-D voxel reconstruction, which is built from two calibrated webcam views. The gait parameters are validated with a GAITRite mat and a Vicon motion capture system in the laboratory with 13 participants and 44 tests, and again with GAITRite for 8 older adults in senior housing. Excellent agreement with intraclass correlation coefficients of 0.99 and repeatability coefficients between 0.7% and 6.6% was found for walking speed, step time, and step length given the limitation of frame rate and voxel resolution. The system was further tested with ten seniors in a scripted scenario representing everyday activities in an unstructured environment. The system results demonstrate the capability of being used as a daily gait assessment tool for fall risk assessment and other medical applications. Furthermore, we found that residents displayed different gait patterns during their clinical GAITRite tests compared to the realistic scenario, namely a mean increase of 21% in walking speed, a mean decrease of 12% in step time, and a mean increase of 6% in step length. These findings provide support for continuous gait assessment in the home for capturing habitual gait.

Evaluation of the Microsoft Kinect for screening ACL injury.

A study was conducted to evaluate the use of the skeletal model generated by the Microsoft Kinect SDK in capturing four biomechanical measures during the Drop Vertical Jump test. These measures, which include: knee valgus motion from initial contact to peak flexion, frontal plane knee angle at initial contact, frontal plane knee angle at peak flexion, and knee-to-ankle separation ratio at peak flexion, have proven to be useful in screening for future knee anterior cruciate ligament (ACL) injuries among female athletes. A marker-based Vicon motion capture system was used for ground truth. Results indicate that the Kinect skeletal model likely has acceptable accuracy for use as part of a screening tool to identify elevated risk for ACL injury.

Unobtrusive, continuous, in-home gait measurement using the Microsoft Kinect.

A system for capturing habitual, in-home gait measurements using an environmentally mounted depth camera, the Microsoft Kinect, is presented. Previous work evaluating the use of the Kinect sensor for in-home gait measurement in a lab setting has shown the potential of this approach. In this paper, a single Kinect sensor and computer were deployed in the apartments of older adults in an independent living facility for the purpose of continuous, in-home gait measurement. In addition, a monthly fall risk assessment protocol was conducted for each resident by a clinician, which included traditional tools such as the timed up a go and habitual gait speed tests. A probabilistic methodology for generating automated gait estimates over time for the residents of the apartments from the Kinect data is described, along with results from the apartments as compared to two of the traditionally measured fall risk assessment tools. Potential applications and future work are discussed.

In-home fall risk assessment and detection sensor system.

Falls are a major problem in older adults. A continuous, unobtrusive, environmentally mounted (i.e., embedded into the environment and not worn by the individual), in-home monitoring system that automatically detects when falls have occurred or when the risk of falling is increasing could alert health care providers and family members to intervene to improve physical function or manage illnesses that may precipitate falls. Researchers at the University of Missouri Center for Eldercare and Rehabilitation Technology are testing such sensor systems for fall risk assessment (FRA) and detection in older adults' apartments in a senior living community. Initial results comparing ground truth (validated measures) of FRA data and GAITRite System parameters with data captured from Microsoft(®) Kinect and pulse-Doppler radar are reported.

Capturing habitual, in-home gait parameter trends using an inexpensive depth camera.

Results are presented for measuring the gait parameters of walking speed, stride time, and stride length of five older adults continuously, in their homes, over a four month period. The gait parameters were measured passively, using an inexpensive, environmentally mounted depth camera, the Microsoft Kinect. Research has indicated the importance of measuring a person's gait for a variety of purposes from fall risk assessment to early detection of health problems such as cognitive impairment. However, such assessments are often done infrequently and most current technologies are not suitable for continuous, long term use. For this work, a single Microsoft Kinect sensor was deployed in four apartments, containing a total of five residents. A methodology for generating trends in walking speed, stride time, and stride length based on data from identified walking sequences in the home is presented, along with trend estimates for the five participants who were monitored for this work.

Passive in-home measurement of stride-to-stride gait variability comparing vision and Kinect sensing.

We present an analysis of measuring stride-to-stride gait variability passively, in a home setting using two vision based monitoring techniques: anonymized video data from a system of two web-cameras, and depth imagery from a single Microsoft Kinect. Millions of older adults fall every year. The ability to assess the fall risk of elderly individuals is essential to allowing them to continue living safely in independent settings as they age. Studies have shown that measures of stride-to-stride gait variability are predictive of falls in older adults. For this analysis, a set of participants were asked to perform a number of short walks while being monitored by the two vision based systems, along with a marker based Vicon motion capture system for ground truth. Measures of stride-to-stride gait variability were computed using each of the systems and compared against those obtained from the Vicon.

Nighttime in-home action monitoring for eldercare.

In this work, we develop a system to automatically monitoring actions of elderly people at home for safety enhancement and health monitoring. We use an Infrared camera embedded in a living environment to capture images. We study the characteristics of different clothing in Infrared images and develop an efficient silhouette extraction method for Infrared (IR) images using spatio-temporal filtering. We recognize human action using supervised learning methods. Our experimental results demonstrate that our proposed method is efficient.

Extracting footfalls from voxel data.

In this paper, we present a method for extracting footfall locations from three dimensional voxel data created from a pair of silhouettes. With the growth of the elderly population, there is a need for passive monitoring of physical activity to allow older adults to continue living in independent settings. Prior research using anonymized video data has shown good results in passively acquiring information useful for assessing physical function; and, additionally, research has shown that video data anonymized through the use of silhouettes alleviates privacy concerns of older adults towards the technology. Previous work in acquiring gait information from voxel data has not included a technique for identifying individual footfall locations, from which additional information useful for assessing asymmetric gait patterns and other physical parameters may be obtained. Furthermore, visualization of the footfall locations during a walking sequence may provide additional insight to care providers for assessing physical function. To evaluate our approach, participants were asked to walk across a GAITRite electronic mat, used to validate our results, while also being monitored by our camera system. Results show good agreement between the footfalls extracted by our system and those from the GAITRite.

Testing an in-home gait assessment tool for older adults.

In this paper, we present results of an automatic vision-based gait assessment tool, using two cameras. Elderly residents from TigerPlace, a retirement community, were recruited to participate in the validation and test of the system in scripted scenarios representing everyday activities. The residents were first tested on a GAITRite mat, an electronic walkway that captures footfalls, and with inexpensive web cameras recording images. The extracted gait parameters from the camera system were compared with the GAITRite; excellent agreement was achieved. The residents then participated in the scenarios, with only the cameras recording. We found that the residents displayed different gait patterns during the realistic scenarios compared to the GAITRite runs. This finding provides support of the importance and advantage of continuous gait assessment in a daily living environment. Results on 4 elderly participants are included in the paper.

Gait analysis and validation using voxel data.

In this paper, we present a method for extracting gait parameters including walking speed, step time and step length from a three-dimensional voxel reconstruction, which is built from two calibrated camera views. These parameters are validated with a GAITRite Electronic mat and a Vicon motion capture system. Experiments were conducted in which subjects walked across the GAITRite mat at various speeds while the Vicon cameras recorded the motion of reflective markers attached to subjects' shoes, and our two calibrated cameras captured the images. Excellent agreements were found for walking speed. Step time and step length were also found to have good agreement given the limitation of frame rate and voxel resolution.