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Renuka Tipirneni - One of the best experts on this subject based on the ideXlab platform.
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Changes in Coverage, Access, and Health Following Implementation of Healthy Behavior Incentive Medicaid Expansions vs. Traditional Medicaid Expansions
Journal of General Internal Medicine, 2020Co-Authors: Daniel B. Nelson, Benjamin D. Sommers, Phillip M. Singer, Emily K. Arntson, Renuka TipirneniAbstract:Background Several states expanded Medicaid under the Affordable Care Act using Section 1115 waivers to implement Healthy Behavior incentive (HBI) programs, but the impact of this type of expansion relative to traditional expansion is not well understood. Objective To examine whether Medicaid expansion with Healthy Behavior incentive programs and traditional Medicaid expansion were associated with differential changes in coverage, access, and self-rated health outcomes among low-income adults. Design Difference-in-differences analysis of American Community Survey and Behavioral Risk Factor Surveillance System data from 2011 to 2017. Participants Low-income adults ages 19–64 in the Midwest Census region (American Community Survey, n = 665,653; Behavioral Risk Factor Surveillance System, n = 71,959). Interventions Exposure to either HBI waiver or traditional Medicaid expansion in the state of residence. Main Measures Coverage: Medicaid, private, or any health insurance coverage; access: routine checkup, personal doctor, delaying care due to cost; health: cancer screening, preventive care, Healthy Behaviors, self-reported health. Key Results Healthy Behavior incentive (HBI) and traditional expansion (TE) states experienced reductions in uninsurance (− 5.6 [− 7.5, − 3.7] and − 6.2 [− 8.1, − 4.4] percentage points, respectively) and gains in Medicaid (HBI, + 7.6 [2.4, 12.8]; TE, + 9.7 [5.9, 13.4] percentage points) relative to non-expansion states. Both expansion types were associated with increases in rates of having a personal doctor (HBI, + 3.8 [2.0, 5.6]; TE, + 5.9 [2.2, 9.6] percentage points) and mammography (HBI, + 5.6 [0.6, 10.6]; TE, + 7.3 [0.7, 13.9] percentage points). Meanwhile, checkups increased more in HBI than in TE states ( p
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changes in coverage access and health following implementation of Healthy Behavior incentive medicaid expansions vs traditional medicaid expansions
Journal of General Internal Medicine, 2020Co-Authors: Daniel B. Nelson, Benjamin D. Sommers, Phillip M. Singer, Emily K. Arntson, Renuka TipirneniAbstract:BACKGROUND Several states expanded Medicaid under the Affordable Care Act using Section 1115 waivers to implement Healthy Behavior incentive (HBI) programs, but the impact of this type of expansion relative to traditional expansion is not well understood. OBJECTIVE To examine whether Medicaid expansion with Healthy Behavior incentive programs and traditional Medicaid expansion were associated with differential changes in coverage, access, and self-rated health outcomes among low-income adults. DESIGN Difference-in-differences analysis of American Community Survey and Behavioral Risk Factor Surveillance System data from 2011 to 2017. PARTICIPANTS Low-income adults ages 19-64 in the Midwest Census region (American Community Survey, n = 665,653; Behavioral Risk Factor Surveillance System, n = 71,959). INTERVENTIONS Exposure to either HBI waiver or traditional Medicaid expansion in the state of residence. MAIN MEASURES Coverage: Medicaid, private, or any health insurance coverage; access: routine checkup, personal doctor, delaying care due to cost; health: cancer screening, preventive care, Healthy Behaviors, self-reported health. KEY RESULTS Healthy Behavior incentive (HBI) and traditional expansion (TE) states experienced reductions in uninsurance (- 5.6 [- 7.5, - 3.7] and - 6.2 [- 8.1, - 4.4] percentage points, respectively) and gains in Medicaid (HBI, + 7.6 [2.4, 12.8]; TE, + 9.7 [5.9, 13.4] percentage points) relative to non-expansion states. Both expansion types were associated with increases in rates of having a personal doctor (HBI, + 3.8 [2.0, 5.6]; TE, + 5.9 [2.2, 9.6] percentage points) and mammography (HBI, + 5.6 [0.6, 10.6]; TE, + 7.3 [0.7, 13.9] percentage points). Meanwhile, checkups increased more in HBI than in TE states (p < 0.01), but no other changes in health care services differed between expansion types. CONCLUSIONS Medicaid expansion was associated with improvements in coverage and access to care with few differences between expansion types.
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Engagement with Health Risk Assessments and Commitment to Healthy Behaviors in Michigan’s Medicaid Expansion Program
Journal of General Internal Medicine, 2019Co-Authors: A. Taylor Kelley, Susan Dorr Goold, John Z. Ayanian, Minal R. Patel, Eunice Zhang, Erin Beathard, Tammy Chang, Erica Solway, Renuka TipirneniAbstract:Health risk assessments (HRAs) and Healthy Behavior incentives are increasingly used by state Medicaid programs to promote enrollees’ health. To evaluate enrollee experiences with HRAs and Healthy Behavior engagement in the Healthy Michigan Plan (HMP), a state Medicaid expansion program. Telephone survey conducted in Michigan January–October 2016. A random sample of HMP enrollees aged 19–64 with ≥ 12 months of enrollment, stratified by income and geographic region. Self-reported completion of an HRA, reasons for completing an HRA, commitment to a Healthy Behavior, and choice of Healthy Behavior. Among respondents (N = 4090), 49.3% (95% CI 47.3–51.2%) reported completing an HRA; among those with a primary care provider (PCP) (n = 3851), 85.2% (95% CI 83.5–86.7%) reported visiting their PCP during the last 12 months. Most enrollees having a recent PCP visit reported discussing Healthy Behaviors with them (91.1%, 95% CI 89.6–92.3%) and were more likely to have completed an HRA than enrollees without a recent PCP visit (52.7%, 95% CI 50.5–52.8% vs. 36.2%, 95% CI 31.7–41.1%; p
Teri Lindgren - One of the best experts on this subject based on the ideXlab platform.
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real time social support through a mobile virtual community to improve Healthy Behavior in overweight and sedentary adults a focus group analysis
Journal of Medical Internet Research, 2011Co-Authors: Yoshimi Fukuoka, Emiko Kamitani, Kemberlee Bonnet, Teri LindgrenAbstract:Background: The onset of type 2 diabetes mellitus can be prevented or delayed by lifestyle changes. Communication technologies such as a mobile phone can be used as a means of delivering these lifestyle changes. Objectives: The purposes of this analysis were to explore applicability of potential components of a mobile phone-based Healthy lifestyle program and to understand motivators and barriers to continued engagement in a mobile phone Healthy lifestyle program. Methods: We conducted 6 focus groups (4 female and 2 male groups) in May and June 2010 with 35 focus group participants. The qualitative data were analyzed by 3 researchers using a qualitative description method in an ATLAS.ti software program. Inclusion criteria for enrollment in a focus group were as follows: (1) being aged from 30 to 69 years, (2) speaking and reading English, (3) having a sedentary lifestyle at work or during leisure time (screened by the Brief Physical Activity Survey questionnaire), and (4) having a body mass index (BMI) >25 kg/m2 (Asian >23 kg/m2) based on self-reported weight and height or 5) having a self-reported prediabetic condition. Results: The mean age was 51 (SD 10.6) years; 54% (n = 19) were white; 71% (n = 25) used a mobile phone at least once a week during the last month prior to the study enrollment; and mean BMI was 32.5 (SD 6.5) kg/m2. In the qualitative analyses, the following 4 major themes and their subthemes emerged: (1) real-time social support (real-time peer support from participants who are similarly engaged in a diet or physical activity program, and professional support from health care providers or a researcher), (2) tailoring of mobile phone programs (3) self-monitoring and motivation, and (4) potential barriers and sustainability of the program (fear of failing, age and mobile technologies, and loss of interest over time). Conclusions: Participants from a wide range of age and racial groups expressed interest in a mobile phone-based lifestyle program. Such a program that incorporates the themes that we identified may be able to help motivate participants to increase their physical activity and to improve their diet. [J Med Internet Res 2011;13(3):e49]
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Real-time social support through a mobile virtual community to improve Healthy Behavior in overweight and sedentary adults: A focus group analysis
Journal of Medical Internet Research, 2011Co-Authors: Yoshimi Fukuoka, Emiko Kamitani, Kemberlee Bonnet, Teri LindgrenAbstract:BACKGROUND: The onset of type 2 diabetes mellitus can be prevented or delayed by lifestyle changes. Communication technologies such as a mobile phone can be used as a means of delivering these lifestyle changes.\n\nOBJECTIVES: The purposes of this analysis were to explore applicability of potential components of a mobile phone-based Healthy lifestyle program and to understand motivators and barriers to continued engagement in a mobile phone Healthy lifestyle program.\n\nMETHODS: We conducted 6 focus groups (4 female and 2 male groups) in May and June 2010 with 35 focus group participants. The qualitative data were analyzed by 3 researchers using a qualitative description method in an ATLAS.ti software program. Inclusion criteria for enrollment in a focus group were as follows: (1) being aged from 30 to 69 years, (2) speaking and reading English, (3) having a sedentary lifestyle at work or during leisure time (screened by the Brief Physical Activity Survey questionnaire), and (4) having a body mass index (BMI) >25 kg/m(2) (Asian >23 kg/m(2)) based on self-reported weight and height or 5) having a self-reported prediabetic condition.\n\nRESULTS: The mean age was 51 (SD 10.6) years; 54% (n = 19) were white; 71% (n = 25) used a mobile phone at least once a week during the last month prior to the study enrollment; and mean BMI was 32.5 (SD 6.5) kg/m(2). In the qualitative analyses, the following 4 major themes and their subthemes emerged: (1) real-time social support (real-time peer support from participants who are similarly engaged in a diet or physical activity program, and professional support from health care providers or a researcher), (2) tailoring of mobile phone programs (3) self-monitoring and motivation, and (4) potential barriers and sustainability of the program (fear of failing, age and mobile technologies, and loss of interest over time).\n\nCONCLUSIONS: Participants from a wide range of age and racial groups expressed interest in a mobile phone-based lifestyle program. Such a program that incorporates the themes that we identified may be able to help motivate participants to increase their physical activity and to improve their diet.
Benjamin D. Sommers - One of the best experts on this subject based on the ideXlab platform.
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Changes in Coverage, Access, and Health Following Implementation of Healthy Behavior Incentive Medicaid Expansions vs. Traditional Medicaid Expansions
Journal of General Internal Medicine, 2020Co-Authors: Daniel B. Nelson, Benjamin D. Sommers, Phillip M. Singer, Emily K. Arntson, Renuka TipirneniAbstract:Background Several states expanded Medicaid under the Affordable Care Act using Section 1115 waivers to implement Healthy Behavior incentive (HBI) programs, but the impact of this type of expansion relative to traditional expansion is not well understood. Objective To examine whether Medicaid expansion with Healthy Behavior incentive programs and traditional Medicaid expansion were associated with differential changes in coverage, access, and self-rated health outcomes among low-income adults. Design Difference-in-differences analysis of American Community Survey and Behavioral Risk Factor Surveillance System data from 2011 to 2017. Participants Low-income adults ages 19–64 in the Midwest Census region (American Community Survey, n = 665,653; Behavioral Risk Factor Surveillance System, n = 71,959). Interventions Exposure to either HBI waiver or traditional Medicaid expansion in the state of residence. Main Measures Coverage: Medicaid, private, or any health insurance coverage; access: routine checkup, personal doctor, delaying care due to cost; health: cancer screening, preventive care, Healthy Behaviors, self-reported health. Key Results Healthy Behavior incentive (HBI) and traditional expansion (TE) states experienced reductions in uninsurance (− 5.6 [− 7.5, − 3.7] and − 6.2 [− 8.1, − 4.4] percentage points, respectively) and gains in Medicaid (HBI, + 7.6 [2.4, 12.8]; TE, + 9.7 [5.9, 13.4] percentage points) relative to non-expansion states. Both expansion types were associated with increases in rates of having a personal doctor (HBI, + 3.8 [2.0, 5.6]; TE, + 5.9 [2.2, 9.6] percentage points) and mammography (HBI, + 5.6 [0.6, 10.6]; TE, + 7.3 [0.7, 13.9] percentage points). Meanwhile, checkups increased more in HBI than in TE states ( p
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changes in coverage access and health following implementation of Healthy Behavior incentive medicaid expansions vs traditional medicaid expansions
Journal of General Internal Medicine, 2020Co-Authors: Daniel B. Nelson, Benjamin D. Sommers, Phillip M. Singer, Emily K. Arntson, Renuka TipirneniAbstract:BACKGROUND Several states expanded Medicaid under the Affordable Care Act using Section 1115 waivers to implement Healthy Behavior incentive (HBI) programs, but the impact of this type of expansion relative to traditional expansion is not well understood. OBJECTIVE To examine whether Medicaid expansion with Healthy Behavior incentive programs and traditional Medicaid expansion were associated with differential changes in coverage, access, and self-rated health outcomes among low-income adults. DESIGN Difference-in-differences analysis of American Community Survey and Behavioral Risk Factor Surveillance System data from 2011 to 2017. PARTICIPANTS Low-income adults ages 19-64 in the Midwest Census region (American Community Survey, n = 665,653; Behavioral Risk Factor Surveillance System, n = 71,959). INTERVENTIONS Exposure to either HBI waiver or traditional Medicaid expansion in the state of residence. MAIN MEASURES Coverage: Medicaid, private, or any health insurance coverage; access: routine checkup, personal doctor, delaying care due to cost; health: cancer screening, preventive care, Healthy Behaviors, self-reported health. KEY RESULTS Healthy Behavior incentive (HBI) and traditional expansion (TE) states experienced reductions in uninsurance (- 5.6 [- 7.5, - 3.7] and - 6.2 [- 8.1, - 4.4] percentage points, respectively) and gains in Medicaid (HBI, + 7.6 [2.4, 12.8]; TE, + 9.7 [5.9, 13.4] percentage points) relative to non-expansion states. Both expansion types were associated with increases in rates of having a personal doctor (HBI, + 3.8 [2.0, 5.6]; TE, + 5.9 [2.2, 9.6] percentage points) and mammography (HBI, + 5.6 [0.6, 10.6]; TE, + 7.3 [0.7, 13.9] percentage points). Meanwhile, checkups increased more in HBI than in TE states (p < 0.01), but no other changes in health care services differed between expansion types. CONCLUSIONS Medicaid expansion was associated with improvements in coverage and access to care with few differences between expansion types.
Daniel B. Nelson - One of the best experts on this subject based on the ideXlab platform.
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Changes in Coverage, Access, and Health Following Implementation of Healthy Behavior Incentive Medicaid Expansions vs. Traditional Medicaid Expansions
Journal of General Internal Medicine, 2020Co-Authors: Daniel B. Nelson, Benjamin D. Sommers, Phillip M. Singer, Emily K. Arntson, Renuka TipirneniAbstract:Background Several states expanded Medicaid under the Affordable Care Act using Section 1115 waivers to implement Healthy Behavior incentive (HBI) programs, but the impact of this type of expansion relative to traditional expansion is not well understood. Objective To examine whether Medicaid expansion with Healthy Behavior incentive programs and traditional Medicaid expansion were associated with differential changes in coverage, access, and self-rated health outcomes among low-income adults. Design Difference-in-differences analysis of American Community Survey and Behavioral Risk Factor Surveillance System data from 2011 to 2017. Participants Low-income adults ages 19–64 in the Midwest Census region (American Community Survey, n = 665,653; Behavioral Risk Factor Surveillance System, n = 71,959). Interventions Exposure to either HBI waiver or traditional Medicaid expansion in the state of residence. Main Measures Coverage: Medicaid, private, or any health insurance coverage; access: routine checkup, personal doctor, delaying care due to cost; health: cancer screening, preventive care, Healthy Behaviors, self-reported health. Key Results Healthy Behavior incentive (HBI) and traditional expansion (TE) states experienced reductions in uninsurance (− 5.6 [− 7.5, − 3.7] and − 6.2 [− 8.1, − 4.4] percentage points, respectively) and gains in Medicaid (HBI, + 7.6 [2.4, 12.8]; TE, + 9.7 [5.9, 13.4] percentage points) relative to non-expansion states. Both expansion types were associated with increases in rates of having a personal doctor (HBI, + 3.8 [2.0, 5.6]; TE, + 5.9 [2.2, 9.6] percentage points) and mammography (HBI, + 5.6 [0.6, 10.6]; TE, + 7.3 [0.7, 13.9] percentage points). Meanwhile, checkups increased more in HBI than in TE states ( p
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changes in coverage access and health following implementation of Healthy Behavior incentive medicaid expansions vs traditional medicaid expansions
Journal of General Internal Medicine, 2020Co-Authors: Daniel B. Nelson, Benjamin D. Sommers, Phillip M. Singer, Emily K. Arntson, Renuka TipirneniAbstract:BACKGROUND Several states expanded Medicaid under the Affordable Care Act using Section 1115 waivers to implement Healthy Behavior incentive (HBI) programs, but the impact of this type of expansion relative to traditional expansion is not well understood. OBJECTIVE To examine whether Medicaid expansion with Healthy Behavior incentive programs and traditional Medicaid expansion were associated with differential changes in coverage, access, and self-rated health outcomes among low-income adults. DESIGN Difference-in-differences analysis of American Community Survey and Behavioral Risk Factor Surveillance System data from 2011 to 2017. PARTICIPANTS Low-income adults ages 19-64 in the Midwest Census region (American Community Survey, n = 665,653; Behavioral Risk Factor Surveillance System, n = 71,959). INTERVENTIONS Exposure to either HBI waiver or traditional Medicaid expansion in the state of residence. MAIN MEASURES Coverage: Medicaid, private, or any health insurance coverage; access: routine checkup, personal doctor, delaying care due to cost; health: cancer screening, preventive care, Healthy Behaviors, self-reported health. KEY RESULTS Healthy Behavior incentive (HBI) and traditional expansion (TE) states experienced reductions in uninsurance (- 5.6 [- 7.5, - 3.7] and - 6.2 [- 8.1, - 4.4] percentage points, respectively) and gains in Medicaid (HBI, + 7.6 [2.4, 12.8]; TE, + 9.7 [5.9, 13.4] percentage points) relative to non-expansion states. Both expansion types were associated with increases in rates of having a personal doctor (HBI, + 3.8 [2.0, 5.6]; TE, + 5.9 [2.2, 9.6] percentage points) and mammography (HBI, + 5.6 [0.6, 10.6]; TE, + 7.3 [0.7, 13.9] percentage points). Meanwhile, checkups increased more in HBI than in TE states (p < 0.01), but no other changes in health care services differed between expansion types. CONCLUSIONS Medicaid expansion was associated with improvements in coverage and access to care with few differences between expansion types.
Katie A. Siek - One of the best experts on this subject based on the ideXlab platform.
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CSCW - Snack Buddy: Supporting Healthy Snacking in Low Socioeconomic Status Families
Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing - CSCW '15, 2015Co-Authors: Christopher L. Schaefbauer, Danish U. Khan, Amy Le, Garrett Sczechowski, Katie A. SiekAbstract:We conducted a 12-week comparative field trial with 20 low socioeconomic status (SES) caregivers from 10 families to explore their use of a sociotechnical mobile application designed to promote Healthy snacking, Snack Buddy. Our analysis of the semi-structured interviews, pre/post-intervention instruments, and photo-elicitation interviews suggests that participants gained a greater awareness of their own snacking practices and those of their family members. Users were empowered to adjust their own practices and beliefs around Healthy eating because they were more aware of their family's snacking Behaviors. We describe the unique social dynamics of how families engaged with each other and the application, which includes positive social support for Healthy eating. By providing insights into family interactions and experiences with the application, we identify benefits, challenges, and strategies when designing family-level sociotechnical interventions for Healthy Behavior.
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snack buddy supporting Healthy snacking in low socioeconomic status families
Conference on Computer Supported Cooperative Work, 2015Co-Authors: Christopher L. Schaefbauer, Danish U. Khan, Amy Le, Garrett Sczechowski, Katie A. SiekAbstract:We conducted a 12-week comparative field trial with 20 low socioeconomic status (SES) caregivers from 10 families to explore their use of a sociotechnical mobile application designed to promote Healthy snacking, Snack Buddy. Our analysis of the semi-structured interviews, pre/post-intervention instruments, and photo-elicitation interviews suggests that participants gained a greater awareness of their own snacking practices and those of their family members. Users were empowered to adjust their own practices and beliefs around Healthy eating because they were more aware of their family's snacking Behaviors. We describe the unique social dynamics of how families engaged with each other and the application, which includes positive social support for Healthy eating. By providing insights into family interactions and experiences with the application, we identify benefits, challenges, and strategies when designing family-level sociotechnical interventions for Healthy Behavior.
