AIMC Topic: Medicare

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Patient Coded Severity and Payment Penalties Under the Hospital Readmissions Reduction Program: A Machine Learning Approach.

Medical care Nov 1, 2020
OBJECTIVE: The objective of this study was to examine variation in hospital responses to the Centers for Medicare and Medicaid's expansion of allowable secondary diagnoses in January 2011 and its association with financial penalties under the Hospita...
Humans Machine Learning Policy Clinical Coding Diagnosis-Related Groups Centers for Medicare and Medicaid Services, U.S. Insurance Claim Review Hospital Bed Capacity Severity of Illness Index United States Medicare Patient Readmission
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Machine intelligence for early targeted precision management and response to outbreaks of respiratory infections.

The American journal of managed care Oct 1, 2020
OBJECTIVES: To evaluate the utility of machine learning (ML) for the management of Medicare beneficiaries at risk of severe respiratory infections in community and postacute settings by (1) identifying individuals in a community setting at risk of in...
Skilled Nursing Facilities Humans United States Artificial Intelligence Patient Discharge Hospitalization Precision Medicine Medicare Aged Retrospective Studies Respiratory Tract Infections Disease Outbreaks
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Using Machine Learning to Predict Primary Care and Advance Workforce Research.

Annals of family medicine Jul 1, 2020
PURPOSE: To develop and test a machine-learning-based model to predict primary care and other specialties using Medicare claims data.
Humans Machine Learning Physicians, Primary Care Insurance Claim Review United States Algorithms Area Under Curve Cross-Sectional Studies Medicare ROC Curve Workforce Primary Health Care
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Computer vision's potential to improve health care.

Lancet (London, England) May 16, 2020
Computers Delivery of Health Care Intensive Care Units Electronic Health Records Humans Artificial Intelligence Algorithms Video Recording Vision, Ocular Patient Harm Clinical Decision-Making Surgeons United States Medicare
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Does machine learning improve prediction of VA primary care reliance?

The American journal of managed care Jan 1, 2020
OBJECTIVES: The Veterans Affairs (VA) Health Care System is among the largest integrated health systems in the United States. Many VA enrollees are dual users of Medicare, and little research has examined methods to most accurately predict which vete...
Medicare United States Department of Veterans Affairs Patient Acceptance of Health Care Veterans Health Services Middle Aged Humans Primary Health Care Machine Learning Logistic Models Forecasting United States Female Aged Aged, 80 and over Male
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Robotics Against the Evidence.

JAMA surgery Jan 1, 2020
Colectomy United States Robotics Medicare Humans Aged
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Novel Machine Learning Approach to Identify Preoperative Risk Factors Associated With Super-Utilization of Medicare Expenditure Following Surgery.

JAMA surgery Nov 1, 2019
IMPORTANCE: Typically defined as the top 5% of health care users, super-utilizers are responsible for an estimated 40% to 55% of all health care costs. Little is known about which factors may be associated with increased risk of long-term postoperati...
Postoperative Care Elective Surgical Procedures Aged Medicare Humans Machine Learning Health Expenditures Preoperative Care Male Retrospective Studies Patient Acceptance of Health Care Risk Assessment Female Risk Factors United States
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Bundled Care for Hip Fractures: A Machine-Learning Approach to an Untenable Patient-Specific Payment Model.

Journal of orthopaedic trauma Jul 1, 2019
OBJECTIVES: With the transition to a value-based model of care delivery, bundled payment models have been implemented with demonstrated success in elective lower extremity joint arthroplasty. Yet, hip fracture outcomes are dependent on patient-level ...
United States Bayes Theorem Aged Medicare Humans Patient Care Bundles Arthroplasty, Replacement, Hip Health Expenditures Male Machine Learning Health Care Costs Middle Aged Hip Fractures Female Length of Stay
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Measuring Exposure to Incarceration Using the Electronic Health Record.

Medical care Jun 1, 2019
BACKGROUND: Electronic health records (EHRs) are a rich source of health information; however social determinants of health, including incarceration, and how they impact health and health care disparities can be hard to extract.
Prisoners Sensitivity and Specificity Male Middle Aged Humans United States United States Department of Veterans Affairs Cohort Studies Electronic Health Records Ethnicity Veterans Natural Language Processing Female Medicare Information Storage and Retrieval Administrative Claims, Healthcare Adult Self Report
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Identifying Specific Combinations of Multimorbidity that Contribute to Health Care Resource Utilization: An Analytic Approach.

Medical care Mar 1, 2017
BACKGROUND: Multimorbidity affects the majority of elderly adults and is associated with higher health costs and utilization, but how specific patterns of morbidity influence resource use is less understood.
United States Aged Humans Health Expenditures Medicare Machine Learning Socioeconomic Factors Activities of Daily Living Self Report Aged, 80 and over Retrospective Studies Female Male Comorbidity Health Behavior Health Status Age Factors
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