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Feb 22, 2023 •193 likes •264 views

Enhancing Health Survey Data with Alternative Data Sources Session 2 Session 2: Enhancing Health Survey Data with Alternative Data Sources Who gets it right? Using survey and administrative data to evaluate characteristics associated with

Enhancing Health Survey Data with Alternative Data Sources Session 2
Session 2: Enhancing Health Survey Data with Alternative Data Sources • Who gets it right? Using survey and administrative data to evaluate characteristics associated with accurate reports of health insurance coverage – Kathleen Call, University of Minnesota • Using surveys to inform health policy: Appending premium information to surveys of healthcare coverage and access – Alisha Simon, Minnesota Dept. of Health • Comparing conceptual and machine-learning algorithms to categorize health insurance coverage – Joanne Pascale, Census Bureau • Incorporating sensor, app, and neurocognitive assessment data in a health study, lessons learned, impacts, and future implications for research – Steve Gomori, RTI • Disscusant – Ronald Iachan, ICF
Session 2: Enhancing Health Survey Data with Alternative Data Sources • Who gets it right? Using survey and administrative data to evaluate characteristics associated with accurate reports of health insurance coverage – Kathleen Call, University of Minnesota • Using surveys to inform health policy: Appending premium information to surveys of healthcare coverage and access – Alisha Simon, Minnesota Dept. of Health • Comparing conceptual and machine-learning algorithms to categorize health insurance coverage – Joanne Pascale, Census Bureau • Incorporating sensor, app, and neurocognitive assessment data in a health study, lessons learned, impacts, and future implications for research – Steve Gomori, RTI • Disscusant – Ronald Iachan, ICF
Session 2: Enhancing Health Survey Data with Alternative Data Sources • Who gets it right? Using survey and administrative data to evaluate characteristics associated with accurate reports of health insurance coverage – Kathleen Call, University of Minnesota • Using surveys to inform health policy: Appending premium information to surveys of healthcare coverage and access – Alisha Simon, Minnesota Dept. of Health • Comparing conceptual and machine-learning algorithms to categorize health insurance coverage – Joanne Pascale, Census Bureau • Incorporating sensor, app, and neurocognitive assessment data in a health study, lessons learned, impacts, and future implications for research – Steve Gomori, RTI • Disscusant – Ronald Iachan, ICF
Session 2: Enhancing Health Survey Data with Alternative Data Sources • Who gets it right? Using survey and administrative data to evaluate characteristics associated with accurate reports of health insurance coverage – Kathleen Call, University of Minnesota • Using surveys to inform health policy: Appending premium information to surveys of healthcare coverage and access – Alisha Simon, Minnesota Dept. of Health • Comparing conceptual and machine-learning algorithms to categorize health insurance coverage – Joanne Pascale, Census Bureau • Incorporating sensor, app, and neurocognitive assessment data in a health study, lessons learned, impacts, and future implications for research – Steve Gomori, RTI • Disscusant – Ronald Iachan, ICF
Session 2: Enhancing Health Survey Data with Alternative Data Sources • Who gets it right? Using survey and administrative data to evaluate characteristics associated with accurate reports of health insurance coverage – Kathleen Call, University of Minnesota • Using surveys to inform health policy: Appending premium information to surveys of healthcare coverage and access – Alisha Simon, Minnesota Dept. of Health • Comparing conceptual and machine-learning algorithms to categorize health insurance coverage – Joanne Pascale, Census Bureau • Incorporating sensor, app, and neurocognitive assessment data in a health study, lessons learned, impacts, and future implications for research – Steve Gomori, RTI • Disscusant – Ronald Iachan, ICF
Session 2: Enhancing Health Survey Data with Alternative Data Sources • Who gets it right? Using survey and administrative data to evaluate characteristics associated with accurate reports of health insurance coverage – Kathleen Call, University of Minnesota • Using surveys to inform health policy: Appending premium information to surveys of healthcare coverage and access – Alisha Simon, Minnesota Dept. of Health • Comparing conceptual and machine-learning algorithms to categorize health insurance coverage – Joanne Pascale, Census Bureau • Incorporating sensor, app, and neurocognitive assessment data in a health study, lessons learned, impacts, and future implications for research – Steve Gomori, RTI • Disscusant – Ronald Iachan, ICF

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