Literature DB >> 28395014

Low-Value Medical Services in the Safety-Net Population.

Michael L Barnett1, Jeffrey A Linder2, Cheryl R Clark2, Benjamin D Sommers1.   

Abstract

Importance: National patterns of low-value and high-value care delivered to patients without insurance or with Medicaid could inform public policy but have not been previously examined. Objective: To measure rates of low-value care and high-value care received by patients without insurance or with Medicaid, compared with privately insured patients, and provided by safety-net physicians vs non-safety-net physicians. Design, Setting, and Participants: This multiyear cross-sectional observational study included all patients ages 18 to 64 years from the National Ambulatory Medical Care Survey (2005-2013) and the National Hospital Ambulatory Medical Care Survey (2005-2011) eligible for any of the 21 previously defined low-value or high-value care measures. All measures were analyzed with multivariable logistic regression and adjusted for patient and physician characteristics. Exposures: Comparison of patients by insurance status (uninsured/Medicaid vs privately insured) and safety-net physicians (seeing >25% uninsured/Medicaid patients) vs non-safety-net physicians (seeing 1%-10%). Main Outcomes and Measures: Delivery of 9 low-value or 12 high-value care measures, based on previous research definitions, and composite measures for any high-value or low-value care delivery during an office visit.
Results: Overall, 193 062 office visits were eligible for at least 1 measure. Mean (95% CI) age for privately insured patients (n = 94 707) was 44.7 (44.5-44.9) years; patients on Medicaid (n = 45 123), 39.8 (39.3-40.3) years; and uninsured patients (n = 19 530), 41.9 (41.5-42.4) years. Overall, low-value and high-value care was delivered in 19.4% (95% CI, 18.5%-20.2%) and 33.4% (95% CI, 32.4%-34.3%) of eligible encounters, respectively. Rates of low-value and high-value care delivery were similar across insurance types for the majority of services examined. Among Medicaid patients, adjusted rates of use were no different for 6 of 9 low-value and 9 of 12 high-value services compared with privately insured beneficiaries, whereas among the uninsured, rates were no different for 7 of 9 low-value and 9 of 12 high-value services. Safety-net physicians provided similar care compared with non-safety-net physicians, with no difference for 8 out of 9 low-value and for all 12 high-value services. Conclusions and Relevance: Overuse of low-value care is common among patients without insurance or with Medicaid. Rates of low-value and high-value care were similar among physicians serving vulnerable patients and other physicians. Overuse of low-value care is a potentially important focus for state Medicaid programs and safety-net institutions to pursue cost savings and improved quality of health care delivery.

Entities:  

Mesh:

Year:  2017        PMID: 28395014      PMCID: PMC5540058          DOI: 10.1001/jamainternmed.2017.0401

Source DB:  PubMed          Journal:  JAMA Intern Med        ISSN: 2168-6106            Impact factor:   21.873


  25 in total

1.  Changes in Self-reported Insurance Coverage, Access to Care, and Health Under the Affordable Care Act.

Authors:  Benjamin D Sommers; Munira Z Gunja; Kenneth Finegold; Thomas Musco
Journal:  JAMA       Date:  2015-07-28       Impact factor: 56.272

2.  Electronic health record use and the quality of ambulatory care in the United States.

Authors:  Jeffrey A Linder; Jun Ma; David W Bates; Blackford Middleton; Randall S Stafford
Journal:  Arch Intern Med       Date:  2007-07-09

3.  Trends and quality of care in outpatient visits to generalist and specialist physicians delivering primary care in the United States, 1997-2010.

Authors:  Samuel T Edwards; John N Mafi; Bruce E Landon
Journal:  J Gen Intern Med       Date:  2014-02-25       Impact factor: 5.128

4.  Comparison of Low-Value Care in Medicaid vs Commercially Insured Populations.

Authors:  Christina J Charlesworth; Thomas H A Meath; Aaron L Schwartz; K John McConnell
Journal:  JAMA Intern Med       Date:  2016-07-01       Impact factor: 21.873

5.  Antibiotic prescribing for adults with acute bronchitis in the United States, 1996-2010.

Authors:  Michael L Barnett; Jeffrey A Linder
Journal:  JAMA       Date:  2014-05-21       Impact factor: 56.272

6.  Low-Value Health Care Services in a Commercially Insured Population.

Authors:  Rachel O Reid; Brendan Rabideau; Neeraj Sood
Journal:  JAMA Intern Med       Date:  2016-10-01       Impact factor: 21.873

7.  In 2011 nearly one-third of physicians said they would not accept new Medicaid patients, but rising fees may help.

Authors:  Sandra L Decker
Journal:  Health Aff (Millwood)       Date:  2012-08       Impact factor: 6.301

8.  Trends in the overuse of ambulatory health care services in the United States.

Authors:  Minal S Kale; Tara F Bishop; Alex D Federman; Salomeh Keyhani
Journal:  JAMA Intern Med       Date:  2013-01-28       Impact factor: 21.873

9.  MEDICARE PAYMENTS AND SYSTEM-LEVEL HEALTH-CARE USE: The Spillover Effects of Medicare Managed Care.

Authors:  Katherine Baicker; Jacob A Robbins
Journal:  Am J Health Econ       Date:  2015-10-16

10.  The Quality of Outpatient Care Delivered to Adults in the United States, 2002 to 2013.

Authors:  David M Levine; Jeffrey A Linder; Bruce E Landon
Journal:  JAMA Intern Med       Date:  2016-12-01       Impact factor: 21.873

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  22 in total

1.  Analysis of Physician Variation in Provision of Low-Value Services.

Authors:  Aaron L Schwartz; Anupam B Jena; Alan M Zaslavsky; J Michael McWilliams
Journal:  JAMA Intern Med       Date:  2019-01-01       Impact factor: 21.873

2.  Development and validation of a 5-year mortality prediction model using regularized regression and Medicare data.

Authors:  Jennifer L Lund; Tzy-Mey Kuo; M Alan Brookhart; Anne-Marie Meyer; Alexandra F Dalton; Christine E Kistler; Stephanie B Wheeler; Carmen L Lewis
Journal:  Pharmacoepidemiol Drug Saf       Date:  2019-03-19       Impact factor: 2.890

3.  ACOs with risk-bearing experience are likely taking steps to reduce low-value medical services.

Authors:  Margje H Haverkamp; David Peiris; Alexander J Mainor; Gert P Westert; Meredith B Rosenthal; Thomas D Sequist; Carrie H Colla
Journal:  Am J Manag Care       Date:  2018-07-01       Impact factor: 2.229

Review 4.  Identifying drivers of health care value: a scoping review of the literature.

Authors:  Susan N Landon; Jane Padikkala; Leora I Horwitz
Journal:  BMC Health Serv Res       Date:  2022-06-30       Impact factor: 2.908

5.  Differences in Rates of High-Value and Low-Value Care Between Community Health Centers and Private Practices.

Authors:  Carlos Irwin A Oronce; Robert J Fortuna
Journal:  J Gen Intern Med       Date:  2019-11-19       Impact factor: 5.128

6.  Access to US primary care physicians for new patients concerned about smoking or weight.

Authors:  Sarah E Tinkler; Rajiv L Sharma; Raven R H Susu-Mago; Sudeshna Pal; Miron Stano
Journal:  Prev Med       Date:  2018-04-30       Impact factor: 4.018

7.  Impact of hospital safety-net status on failure to rescue after major cardiac surgery.

Authors:  Yas Sanaiha; Sarah Rudasill; Sohail Sareh; Alexandra Mardock; Habib Khoury; Boback Ziaeian; Richard Shemin; Peyman Benharash
Journal:  Surgery       Date:  2019-07-12       Impact factor: 3.982

8.  Validation of the "Wisconsin Criteria" for Obtaining Dedicated Facial Imaging and Its Financial Impact at a Level 1 Trauma Center.

Authors:  Christopher N Stewart; Lily Wood; Ruth Jo Barta
Journal:  Craniomaxillofac Trauma Reconstr       Date:  2020-03-15

9.  Association of Primary Care Physician Compensation Incentives and Quality of Care in the United States, 2012-2016.

Authors:  David S Burstein; David T Liss; Jeffrey A Linder
Journal:  J Gen Intern Med       Date:  2021-04-14       Impact factor: 5.128

10.  Effects of employer-offered high-deductible plans on low-value spending in the privately insured population.

Authors:  Brendan Rabideau; Matthew D Eisenberg; Rachel Reid; Neeraj Sood
Journal:  J Health Econ       Date:  2021-01-09       Impact factor: 3.883

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