IDEAS home Printed from https://ideas.repec.org/a/eee/socmed/v255y2020ics0277953620302367.html
   My bibliography  Save this article

Diabetes management at community health centers: Examining associations with patient and regional characteristics, efficiency, and staffing patterns

Author

Listed:
  • Thorsen, Maggie
  • McGarvey, Ronald
  • Thorsen, Andreas

Abstract

A major source of primary health care for millions of Americans, community health centers (CHCs) act as a key point of access for diabetes care. The ability of a CHC to deliver high quality care, that supports patients’ management of their diabetes, may be impacted by the unique set of resources and constraints it faces, both in terms of characteristics of its patient population and aspects of operations. This study examines how patient and regional characteristics, staffing patterns, and efficiency were associated with diabetes management at CHCs (percentage of patients with uncontrolled diabetes, HbA1C > 9%). Data on a sample of 1229 CHCs came from multiple sources. CHC-level information was obtained from the Uniform Data System and regional-level information from the Behavioral Risk Factor Surveillance System and the US Census American Community Survey. A clustering methodology, latent class analysis, identified seven underlying staffing patterns at CHCs. Data envelopment analysis was performed to evaluate the efficiency of CHCs, relative to centers with similar staffing patterns. Finally, generalized linear models were used to examine the association between staffing patterns, efficiency, and patient and regional-level characteristics. Findings from this study have sociological, practical, and methodological implications. Findings highlight that the intersection of patient racial composition with regional racial composition is significant; diabetes control appears to be worse at CHCs serving racial minorities living in predominantly White areas. Findings suggest that CHCs that incorporate more behavioral health care into their staffing mix have lower rates of uncontrolled diabetes among their patients. Finally, greater efficiency in CHC operations is associated with better diabetes control among patients. By identifying sociodemographic and operational characteristics associated with better hemoglobin control among diabetes patients, the current study contributes to our understanding of both health care operations and health inequalities.

Suggested Citation

  • Thorsen, Maggie & McGarvey, Ronald & Thorsen, Andreas, 2020. "Diabetes management at community health centers: Examining associations with patient and regional characteristics, efficiency, and staffing patterns," Social Science & Medicine, Elsevier, vol. 255(C).
    • Handle: RePEc:eee:socmed:v:255:y:2020:i:c:s0277953620302367
    DOI: 10.1016/j.socscimed.2020.113017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0277953620302367
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.socscimed.2020.113017?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ronald G. McGarvey & Andreas Thorsen & Maggie L. Thorsen & Rohith Madhi Reddy, 2019. "Measuring efficiency of community health centers: a multi-model approach considering quality of care and heterogeneous operating environments," Health Care Management Science, Springer, vol. 22(3), pages 489-511, September.
    2. Gaskin, D.J. & Thorpe, R.J., Jr. & McGinty, E.E. & Bower, K. & Rohde, C. & Young, J.H. & LaVeist, T.A. & Dubay, L., 2014. "Disparities in diabetes: The nexus of race, poverty, and place," American Journal of Public Health, American Public Health Association, vol. 104(11), pages 2147-2155.
    3. C A F Amado & R G Dyson, 2009. "Exploring the use of DEA for formative evaluation in primary diabetes care: An application to compare English practices," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(11), pages 1469-1482, November.
    4. Peter Wanke & Emel Aktas, 2018. "Efficiency of Diabetes Treatment," International Series in Operations Research & Management Science, in: Cengiz Kahraman & Y. Ilker Topcu (ed.), Operations Research Applications in Health Care Management, chapter 0, pages 351-377, Springer.
    5. Aleda Roth & Anita L. Tucker & Sriram Venkataraman & Jon Chilingerian, 2019. "Being on the Productivity Frontier: Identifying “Triple Aim Performance” Hospitals," Production and Operations Management, Production and Operations Management Society, vol. 28(9), pages 2165-2183, September.
    6. Jan Clement & Vivian Valdmanis & Gloria Bazzoli & Mei Zhao & Askar Chukmaitov, 2008. "Is more better? An analysis of hospital outcomes and efficiency with a DEA model of output congestion," Health Care Management Science, Springer, vol. 11(1), pages 67-77, March.
    7. H. David Sherman & Joe Zhu, 2006. "Service Productivity Management," Springer Books, Springer, number 978-0-387-33231-4, September.
    8. Laraia, Barbara A. & Karter, Andrew J. & Warton, E. Margaret & Schillinger, Dean & Moffet, Howard H. & Adler, Nancy, 2012. "Place matters: Neighborhood deprivation and cardiometabolic risk factors in the Diabetes Study of Northern California (DISTANCE)," Social Science & Medicine, Elsevier, vol. 74(7), pages 1082-1090.
    9. Larry J. Menor & Aleda V. Roth & Charlotte H. Mason, 2001. "Agility in Retail Banking: A Numerical Taxonomy of Strategic Service Groups," Manufacturing & Service Operations Management, INFORMS, vol. 3(4), pages 273-292, February.
    10. Thorsen, Maggie L. & Thorsen, Andreas & McGarvey, Ronald, 2019. "Operational efficiency, patient composition and regional context of U.S. health centers: Associations with access to early prenatal care and low birth weight," Social Science & Medicine, Elsevier, vol. 226(C), pages 143-152.
    11. Mary E. Deily & Niccie L. McKay, 2006. "Cost inefficiency and mortality rates in Florida hospitals," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 419-431, April.
    12. Vinikoor, Lisa C. & Kaufman, Jay S. & MacLehose, Richard F. & Laraia, Barbara A., 2008. "Effects of racial density and income incongruity on pregnancy outcomes in less segregated communities," Social Science & Medicine, Elsevier, vol. 66(2), pages 255-259, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. He Qiong & Li Qixiao & Chen Jindong, 2022. "Study on the improvement of medical service quality in Beijing’s Tianqiao Community Health Service Centre," Engineering Management in Production and Services, Sciendo, vol. 14(4), pages 61-76, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thorsen, Maggie L. & Thorsen, Andreas & McGarvey, Ronald, 2019. "Operational efficiency, patient composition and regional context of U.S. health centers: Associations with access to early prenatal care and low birth weight," Social Science & Medicine, Elsevier, vol. 226(C), pages 143-152.
    2. Nils Gutacker & Chris Bojke & Silvio Daidone & Nancy J. Devlin & David Parkin & Andrew Street, 2013. "Truly Inefficient Or Providing Better Quality Of Care? Analysing The Relationship Between Risk‐Adjusted Hospital Costs And Patients' Health Outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 22(8), pages 931-947, August.
    3. Ortega-Díaz, M. Isabel & Martín, Juan Carlos, 2022. "How to detect hospitals where quality would not be jeopardized by health cost savings? A methodological approach using DEA with SBM analysis," Health Policy, Elsevier, vol. 126(10), pages 1069-1074.
    4. Marcos Pereira Estellita Lins & Sergio Orlando Antoun Netto & Maria Stella Castro Lobo, 2019. "Multimethodology applied to the evaluation of Healthcare in Brazilian municipalities," Health Care Management Science, Springer, vol. 22(2), pages 197-214, June.
    5. Christoph Pross & Christoph Strumann & Alexander Geissler & Helmut Herwartz & Nadja Klein, 2018. "Quality and resource efficiency in hospital service provision: A geoadditive stochastic frontier analysis of stroke quality of care in Germany," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-30, September.
    6. Matranga, Domenica & Sapienza, Francesca, 2015. "Congestion analysis to evaluate the efficiency and appropriateness of hospitals in Sicily," Health Policy, Elsevier, vol. 119(3), pages 324-332.
    7. Margit Sommersguter-Reichmann, 2022. "Health care quality in nonparametric efficiency studies: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(1), pages 67-131, March.
    8. Antony Andrews & Biresh K. Sahoo & Omphile Temoso & Sean Kimpton, 2023. "Quality‐efficiency trade‐off when the state is the sole provider of hospital services: Evidence from New Zealand," Australian Economic Papers, Wiley Blackwell, vol. 62(2), pages 335-348, June.
    9. Silvia Saravia-Matus & T. S. Amjath-Babu & Sreejith Aravindakshan & Stefan Sieber & Jimmy A. Saravia & Sergio Gomez y Paloma, 2021. "Can Enhancing Efficiency Promote the Economic Viability of Smallholder Farmers? A Case of Sierra Leone," Sustainability, MDPI, vol. 13(8), pages 1-17, April.
    10. Yanrong Qiu & Kaihuai Liao & Yanting Zou & Gengzhi Huang, 2022. "A Bibliometric Analysis on Research Regarding Residential Segregation and Health Based on CiteSpace," IJERPH, MDPI, vol. 19(16), pages 1-21, August.
    11. Khushalani, Jaya & Ozcan, Yasar A., 2017. "Are hospitals producing quality care efficiently? An analysis using Dynamic Network Data Envelopment Analysis (DEA)," Socio-Economic Planning Sciences, Elsevier, vol. 60(C), pages 15-23.
    12. Alessandra Cepparulo & Gilles Mourre, 2020. "How and How Much? The Growth-Friendliness of Public Spending through the Lens," European Economy - Discussion Papers 132, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    13. Ed Cook & Jason R. W. Merrick, 2023. "Technology Implementation at Capital One," Interfaces, INFORMS, vol. 53(3), pages 178-191, May.
    14. Alexandru FOTIA & Cezar TECLEAN, 2019. "The Innovation Efficiency In Central And Eastern Europe – An Input-Output Comparative Analysis Between Czech Republic, Hungary, Poland And Romania," EURINT, Centre for European Studies, Alexandru Ioan Cuza University, vol. 6, pages 269-287.
    15. Hisham Alidrisi, 2021. "The Development of an Efficiency-Based Global Green Manufacturing Innovation Index: An Input-Oriented DEA Approach," Sustainability, MDPI, vol. 13(22), pages 1-11, November.
    16. Yiming Zhuang & Meltem Denizel & Frank Montabon, 2023. "Examining Firms’ Sustainability Frontier: Efficiency in Reaching the Triple Bottom Line," Sustainability, MDPI, vol. 15(11), pages 1-22, May.
    17. Ferreira, D.C. & Marques, R.C., 2019. "Do quality and access to hospital services impact on their technical efficiency?," Omega, Elsevier, vol. 86(C), pages 218-236.
    18. Jan Clement & Vivian Valdmanis & Gloria Bazzoli & Mei Zhao & Askar Chukmaitov, 2008. "Is more better? An analysis of hospital outcomes and efficiency with a DEA model of output congestion," Health Care Management Science, Springer, vol. 11(1), pages 67-77, March.
    19. Sergio Orlando Antoun Netto & Marcos Pereira Estellita Lins, 2014. "Homogeneous Clustering of Brazilian Municipalities Based on Structuring Health Care through Concept Maps," Research in Applied Economics, Macrothink Institute, vol. 6(4), pages 40-52, December.
    20. Werner Maier & Christa Scheidt-Nave & Rolf Holle & Lars E Kroll & Thomas Lampert & Yong Du & Christin Heidemann & Andreas Mielck, 2014. "Area Level Deprivation Is an Independent Determinant of Prevalent Type 2 Diabetes and Obesity at the National Level in Germany. Results from the National Telephone Health Interview Surveys ‘German Hea," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-11, February.

    More about this item

    Keywords

    Diabetes; HbA1C; Community health centers; Staffing; Efficiency;
    All these keywords.

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:socmed:v:255:y:2020:i:c:s0277953620302367. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/315/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.