Abstract

BackgroundRecent years have seen an influx of location-tracking, activity-monitoring sensors, and Web-cameras to remotely monitor the safety of older adults in their homes and to reduce reliance on in-person assistance. The state of research on these monitoring technologies leaves open crucial financial, social, and ethical cost-benefit questions, which have prevented widespread use. Medicaid is now the first large third-party payer in the United States to pay for these technologies, and their use is likely to increase as states transition to managed long-term services and supports (MLTSS).ObjectivesThis is the first study to examine how state Medicaid programs are treating passive remote monitoring technologies. This study identifies (1) which states allow location tracking, sensor systems, and cameras; (2) what policies are in place to track their use; (3) what implementation processes and program monitoring mechanisms are in place; and (4) what related insights Medicaid program stakeholders would like to learn from researchers.MethodsInterviews were conducted with 43 state, federal, and managed care organization (MCO) Medicaid program stakeholders about how these technologies are used in state waivers serving community-dwelling older adults in 15 states, and what policies are in place to regulate them. The interviews were analyzed by the research team using the framework analysis method for applied policy research.ResultsTwo-thirds of the states cover location tracking and activity-monitoring sensors and one-third cover cameras, but only 3 states have specific service categories that allow them to track when they are paying for any of these technologies, impeding regulation and understanding of their use at the state and federal level. Consideration of ethical and social risks is limited, and states struggle to understand which circumstances warrant use. They are further challenged by extreme resource restrictions and transitions to MLTSS by MCOs inexperienced in serving this growing “high-need, high-cost” population.ConclusionsDecisions about Medicaid reimbursement of technologies that have the potential to dramatically alter the way older adults receive supportive services are being made without research on their use, social and ethical implications, or outcomes. At a minimum, new service categories are needed to enable oversight. Participants prioritized 3 research aims to inform practice: (1) determine cost-effectiveness; (2) identify what type of information beneficiaries want to be generated and whom they want it to be shared with; and (3) understand how to support ethical decision making for beneficiaries with cognitive impairment. These findings provide direction for future research and reveal that greater interaction between policy makers and researchers in this field is needed.

Highlights

  • Families and living arrangements in the United States have changed over time, just as they have developed distinct regional trends because of factors such as local labor markets and migration patterns

  • The report highlights the complexity and variety of contemporary families and living arrangements and illustrates how they have changed over time

  • Over the last few decades the trend in the United States has been toward smaller households, 500 Miles as compared to the national average

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Summary

INTRODUCTION

Families and living arrangements in the United States have changed over time, just as they have developed distinct regional trends because of factors such as local labor markets and migration patterns. Asian and Hispanic one-parent family groups lived predominantly in the West, while Black one-parent groups lived predominantly in the South These patterns most likely reflect historical trends in residence and migration across the United States.[36] Table 6 shows differences between father-only and mother-only family groups. The most common family arrangement for the 74 million children in the United States in 2012 was living with two married parents (64 percent) (Table 10). 60 The years 2006, 2007, 2008, 2009, and 2010 were not statistically different from one another, nor were 2011 and 2012 different from one another

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Findings
SUMMARY

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