Evaluating efficiency of counties in providing diabetes preventive care using data envelopment analysis.

Data envelopment analysis Diabetes Efficiency Preventive care

Journal

Health services & outcomes research methodology
ISSN: 1387-3741
Titre abrégé: Health Serv Outcomes Res Methodol
Pays: Netherlands
ID NLM: 9815809

Informations de publication

Date de publication:
Sep 2021
Historique:
entrez: 26 11 2021
pubmed: 27 11 2021
medline: 27 11 2021
Statut: ppublish

Résumé

For patients with diabetes, annual preventive care is essential to reduce the risk of complications. Local healthcare resources affect the utilization of diabetes preventive care. Our objectives were to evaluate the relative efficiency of counties in providing diabetes preventive care and explore potential to improve efficiencies. The study setting is public and private healthcare providers in US counties with available data. County-level demographics were extracted from the Area Health Resources File using data from 2010 to 2013, and individual-level information of diabetes preventive service use was obtained from the 2010 Behavioral Risk Factor Surveillance System. 1112 US counties were analyzed. Cluster analysis was used to place counties into three similar groups in terms of economic wellbeing and population characteristics. Group 1 consisted of metropolitan counties with prosperous or comfortable economic levels. Group 2 mostly consisted of non-metropolitan areas between distress and mid-tier levels, while Group 3 were mostly prosperous or comfortable counties in metropolitan areas. We used data enveopement analysis to assess efficiencies within each group. The majority of counties had modest efficiency in providing diabetes preventive care; 36 counties (57.1%), 345 counties (61.1%), and 263 counties (54.3%) were inefficient (efficiency scores < 1) in Group 1, Group 2, and Group 3, respectively. For inefficient counties, foot and eye exams were often identified as sources of inefficiency. Available health professionals in some counties were not fully utilized to provide diabetes preventive care. Identifying benchmarking targets from counties with similar resources can help counties and policy makers develop actionable strategies to improve performance.

Identifiants

pubmed: 34824558
doi: 10.1007/s10742-020-00237-1
pmc: PMC8612454
mid: NIHMS1754076
doi:

Types de publication

Journal Article

Langues

eng

Pagination

324-338

Subventions

Organisme : NIDDK NIH HHS
ID : R01 DK113295
Pays : United States

Déclaration de conflit d'intérêts

Compliance with ethical standards Conflict of interest The authors declare that they have no conflicts of interest.

Références

Health Serv Res. 1983 Spring;18(1):49-74
pubmed: 6841113
Public Health. 2015 Jun;129(6):611-20
pubmed: 26025176
Qual Prim Care. 2013;21(6):345-57
pubmed: 24512833
Ann Intern Med. 2018 Dec 18;169(12):825-835
pubmed: 30458506
Patient Educ Couns. 2015 Feb;98(2):144-9
pubmed: 25468393
J Rural Health. 2010 Winter;26(1):3-11
pubmed: 20105262
Med Care Res Rev. 2011 Feb;68(1 Suppl):3S-19S
pubmed: 21075751
Health Serv Res. 2004 Jun;39(3):607-26
pubmed: 15149481
J Rural Health. 2006 Fall;22(4):351-8
pubmed: 17010033
Health Care Manag Sci. 2019 Sep;22(3):489-511
pubmed: 30145727
J Rehabil Res Dev. 2006 Sep-Oct;43(6):733-40
pubmed: 17310422
JAMA Ophthalmol. 2015 May;133(5):518-25
pubmed: 25741666
Health Care Manag (Frederick). 2014 Apr-Jun;33(2):117-27
pubmed: 24776830
Am J Public Health. 2016 Aug;106(8):1463-9
pubmed: 27310341
Am J Prev Med. 2011 Apr;40(4):434-9
pubmed: 21406277
J Rural Health. 2018 Feb;34 Suppl 1:s30-s38
pubmed: 28075508
Health Care Manag Sci. 2001 Jun;4(2):103-15
pubmed: 11393739
JAMA. 2006 Mar 1;295(9):1042-9
pubmed: 16507805
Diabetes Care. 2003 Jan;26 Suppl 1:S33-50
pubmed: 12502618
Diabetes Care. 2020 Jan;43(Suppl 1):S193-S202
pubmed: 31862758
Diabetes Spectr. 2018 Nov;31(4):310-319
pubmed: 30510385
Int J Nurs Stud. 2016 Jun;58:1-11
pubmed: 27087293
Radiol Manage. 1994 Fall;16(4):35-9
pubmed: 10139084
BMJ Open Diabetes Res Care. 2018 Sep 5;6(1):e000558
pubmed: 30233805
Am J Prev Med. 2015 Feb;48(2):229-233
pubmed: 25442228
Fam Community Health. 2006 Jul-Sep;29(3):186-94
pubmed: 16775468
Can Fam Physician. 2014 Apr;60(4):e230-6
pubmed: 24733343
Ann Fam Med. 2006 Jan-Feb;4(1):32-9
pubmed: 16449394
Health Serv Res. 2008 Oct;43(5 Pt 2):1781-6
pubmed: 18811736

Auteurs

Hyojung Kang (H)

Department of Kinesiology and Community Health, College of Applied Health Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA.

Soyoun Kim (S)

Department of Public Health Sciences, School of Medicine, University of Virginia, Hospital West, 3rd Floor, Room 3003, PO Box 800717, Charlottesville, VA 22908-0717, USA.

Kevin Malloy (K)

School of Data Science, University of Virginia, Charlottesville, VA, USA.

Timothy L McMurry (TL)

Department of Public Health Sciences, School of Medicine, University of Virginia, Hospital West, 3rd Floor, Room 3003, PO Box 800717, Charlottesville, VA 22908-0717, USA.

Rajesh Balkrishnan (R)

Department of Public Health Sciences, School of Medicine, University of Virginia, Hospital West, 3rd Floor, Room 3003, PO Box 800717, Charlottesville, VA 22908-0717, USA.

Roger Anderson (R)

Department of Public Health Sciences, School of Medicine, University of Virginia, Hospital West, 3rd Floor, Room 3003, PO Box 800717, Charlottesville, VA 22908-0717, USA.

Anthony McCall (A)

Division of Endocrinology and Metabolism, Department of Medicine, School of Medicine, University of Virginia, Charlottesville, VA, USA.

Min-Woong Sohn (MW)

Department of Health Management and Policy, College of Public Health, University of Kentucky, Lexington, KY, USA.

Jennifer Mason Lobo (JM)

Department of Public Health Sciences, School of Medicine, University of Virginia, Hospital West, 3rd Floor, Room 3003, PO Box 800717, Charlottesville, VA 22908-0717, USA.

Classifications MeSH