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ANALYSIS OF THE EFFICIENCY OF HEALTH INSTITUTIONS WITH VZA AS A BENCHMARKING TOOL: EXAMPLE OF PUBLIC ORAL AND DENTAL HEALTH CENTERS

Yıl 2022, Cilt 5, Sayı 1, 56 - 72, 31.03.2022
https://doi.org/10.54993/syad.1063633

Öz

Timely and quality service delivery is important in health services. The complex nature of services, the purpose of providing timely and high quality services, is among the essential factors that make it difficult for corporate managers to control costs. For these reasons, managers of health institutions benefit from different methods for cost control. The study aims to determine the target resource numbers by measuring the efficiency levels of the public Oral and Dental Health Centers (ODHC) serving in the field of oral and dental health in Turkey. Thus, it aimed to contribute to the managers in terms of cost control. Data Envelopment Analysis (DEA) technique was used to determine the effectiveness of 132 ADSMs within the scope of the study. As a result of the research, it was determined that 34 ADSMs were effective and 98 ADSMs could not use their resources effectively. The average effectiveness of all ADSMs was 85.1%, and the average efficiency rate of ineffective ADSMs was 80%. In terms of efficiency, it is understood that health institutions are a structure where supply and demand support each other and progress in parallel. It will be the result of a health policy that will be put forward in ensuring that the possible demand rises (such as gaining routine health care needs and habits) and that the supply reaches a certain number of competencies.

Kaynakça

  • Ahmed, S., Hasan, M. Z., MacLennan, M., Dorin, F., Ahmed, M. W., Hasan, M. M., ... & Khan, J. A. (2019). Measuring the efficiency of health systems in Asia: a data envelopment analysis. BMJ open, 9(3), e022155.
  • Alizadeh, R., Beiragh, R. G., Soltanisehat, L., Soltanzadeh, E., & Lund, P. D. (2020). Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach. Energy Economics, 91, 104894.
  • Azreena, E., Juni, M. H., & Rosliza, A. M. (2018). A systematic review of hospital inputs and outputs in measuring technical efficiency using data envelopment analysis. International Journal of Public Health and Clinical Sciences, 5(1), 17-35.
  • Banker, R. D. , Charnes, A. , & Cooper, W. W. (1984). Some models for estimating tech- nical and scale inefficiencies in data envelopment analysis. Management Science, 30 (9), 1078–1092 .
  • Biçer, E. B., Arslan, Ö., & Biyan, M. (2019). Bulanık Mantık Yöntemiyle Maliyet Tespiti: Bir Üniversite Hastanesi Örneği. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 33(4), 1137-1152.
  • Braillon, A., Chaine, F. X., & Gignon, M. (2008, June). Healthcare quality is not so new: the benchmarking case. In Annales francaises d'anesthesie et de reanimation (Vol. 27, No. 6, pp. 467-469).
  • Charnes, A. , Cooper, W. W. , & Rhodes, E. (1978). Measuringtheefficiency ofdecision making units. European Journal of Operational Research, 2 (6), 429–4 4 4 .
  • Cinaroglu, S. (2020). Integrated k-means clustering with data envelopment analysis of public hospital efficiency. Health Care Management Science, 23(3), 325-338.
  • Emrouznejad, A. , & Yang, G. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978-2016. Socio-Economic Planning Sciences, 61 (1), 1–5 .
  • Erdem, B. (2006). İşletmelerde Yeni Bir Yönetim Yaklaşımı: Kıyaslama Benchmarking Yazınsal Bir İnceleme. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 9(15), 65-94.
  • Ersoy, K. , Kavuncubasi, S. , Ozcan, Y. A. , & Harris, J. M., II (1997). Technical efficiencies of Turkish hospitals: DEA approach. Journal of Medical Systems, 21 (2), 67–74 .
  • Ettorchi-Tardy, A., Levif, M., & Michel, P. (2009). Benchmarking: A Method for Continuous Quality Improvement in Health. Healthcare Policy, 101-119.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120 (3), 253–290 .
  • Gandhi, A. V., & Sharma, D. (2018). Technical efficiency of private sector hospitals in India using data envelopment analysis. Benchmarking: An International Journal.
  • Hollingsworth, B. , Dawson, P. , & Maniadakis, N. (1999). Efficiency measurement of health care: A review of non-parametric methods and applications. Health Care Management Science, 2 (3), 161–172 .
  • Ibrahim, M. D., & Daneshvar, S. (2018). Efficiency analysis of healthcare system in Lebanon using modified data envelopment analysis. Journal of healthcare engineering, 2018.
  • Irk, E. & Döven, M. S. (2018). Firmaların Uyguladıkları Rekabet Stratejileri ve Bu Karara Etki Eden Faktörler. İşletme Bilimi Dergisi, 6(1), 135-162.
  • Kim, C., & Kim, H. J. (2019). A study on healthcare supply chain management efficiency: Using bootstrap data envelopment analysis. Health care management science, 22(3), 534-548.
  • Kumar, S., & Chandra, C. (2001). Enhancing the Effectiveness of Benchmarking in Manufacturing Organizations. Industrial Management & Data Systems, 80-89.
  • Mariz, F. B., Almeida, M. R., & Aloise, D. (2018). A review of dynamic data envelopment analysis: State of the art and applications. International Transactions in Operational Research, 25(2), 469-505.
  • Omrani, H., Shafaat, K., & Emrouznejad, A. (2018). An integrated fuzzy clustering cooperative game data envelopment analysis model with application in hospital efficiency. Expert Systems with Applications, 114, 615-628.
  • Pantall, J. (2001). Benchmarking in Healthcare. NT Research Vol.6 No.2, 568-580.
  • Peykani, P., Mohammadi, E., Emrouznejad, A., Pishvaee, M. S., & Rostamy-Malkhalifeh, M. (2019). Fuzzy data envelopment analysis: an adjustable approach. Expert Systems with Applications, 136, 439-452.
  • Rezaee, M. J., Yousefi, S., & Hayati, J. (2018). A decision system using fuzzy cognitive map and multi-group data envelopment analysis to estimate hospitals’ outputs level. Neural Computing and Applications, 29(3), 761-777.
  • Şahin, B., & İlgün, G. (2019). Assessment of the impact of public hospital associations (PHAs) on the efficiency of hospitals under the ministry of health in Turkey with data envelopment analysis. Health care management science, 22(3), 437-446.
  • T.C. Sağlık Bakanlığı (2017) Kamu Hastaneleri İstatistik Raporu, Ağız ve Diş Sağlığı Hizmet Bilgileri. Erişim Adresi: https://khgmistatistikdb.saglik.gov.tr/Eklenti/21853/0/kamu-hastaneleri-istatistik-raporu--2017pdf.pdf, ss.1-249
  • Yang, W., Cai, L., Edalatpanah, S. A., & Smarandache, F. (2020). Triangular single valued neutrosophic data envelopment analysis: application to hospital performance measurement. Symmetry, 12(4), 588.
  • Zhang, T., Lu, W., & Tao, H. (2020). Efficiency of health resource utilisation in primary-level maternal and child health hospitals in Shanxi Province, China: a bootstrapping data envelopment analysis and truncated regression approach. BMC health services research, 20(1), 1-9.
  • Zhang, X., Tone, K., & Lu, Y. (2018). Impact of the local public hospital reform on the efficiency of medium‐sized hospitals in Japan: An improved slacks‐based measure data envelopment analysis approach. Health services research, 53(2), 896-918.

VERİ ZARFLAMA ANALİZİ YÖNTEMİ İLE SAĞLIK KURULUŞLARININ ETKİNLİĞİNİN ANALİZİ: KAMU AĞIZ VE DİŞ SAĞLIĞI MERKEZLERİ ÖRNEĞİ

Yıl 2022, Cilt 5, Sayı 1, 56 - 72, 31.03.2022
https://doi.org/10.54993/syad.1063633

Öz

Sağlık hizmetlerinde zamanında ve kaliteli hizmet sunumu önemlidir. Hizmetlerin karmaşık yapısı, zamanında ve kaliteli hizmet sunum amacı kurum yöneticilerin maliyet kontrolünü güçleştiren önemli faktörlerdendir. Bu sebeplerden dolayı sağlık kurumları yöneticileri maliyet kontrolü için farklı yöntemlerden faydalanmaktadırlar. Çalışma Türkiye’de ağız ve diş sağlığı alanında hizmet veren kamuya ait Ağız ve Diş Sağlığı Merkezlerinin (ADSM) etkinlik düzeylerini ölçerek hedef kaynak sayılarını belirlemeye yöneliktir. Böylece yöneticilere maliyet kontrolü açısından katkı sunmayı amaçlamıştır. Çalışma kapsamında 132 ADSM’nin etkinliğini belirlemek için Veri Zarflama Analizi (VZA) tekniğinden faydalanılmıştır. Araştırma sonucunda 34 ADSM’nin etkin olduğu, 98 ADSM’nin ise kaynaklarını etkin olarak kullanılamadığı tespit edilmiştir. Tüm ADSM’lerin etkinlik değeri ortalama %85,1, etkin olmayan ADSM’lerin etkinlik oranı ise ortalama %80 olarak bulunmuştur. Verimlilik açısından sağlık kurumları arz ile talebin bir birini desteklediği ve paralel ilerlediği bir yapı olduğu anlaşılmaktadır. Muhtemel talebin ortaya çıkmasını (rutin sağlık bakım ihtiyacı ve alışkanlığı kazandırmak gibi) ve arzın belirli bir yetkinlik sayısına ulaşmasını sağlamakta yine ortaya konulacak bir sağlık politikasının neticesi olacaktır.

Kaynakça

  • Ahmed, S., Hasan, M. Z., MacLennan, M., Dorin, F., Ahmed, M. W., Hasan, M. M., ... & Khan, J. A. (2019). Measuring the efficiency of health systems in Asia: a data envelopment analysis. BMJ open, 9(3), e022155.
  • Alizadeh, R., Beiragh, R. G., Soltanisehat, L., Soltanzadeh, E., & Lund, P. D. (2020). Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach. Energy Economics, 91, 104894.
  • Azreena, E., Juni, M. H., & Rosliza, A. M. (2018). A systematic review of hospital inputs and outputs in measuring technical efficiency using data envelopment analysis. International Journal of Public Health and Clinical Sciences, 5(1), 17-35.
  • Banker, R. D. , Charnes, A. , & Cooper, W. W. (1984). Some models for estimating tech- nical and scale inefficiencies in data envelopment analysis. Management Science, 30 (9), 1078–1092 .
  • Biçer, E. B., Arslan, Ö., & Biyan, M. (2019). Bulanık Mantık Yöntemiyle Maliyet Tespiti: Bir Üniversite Hastanesi Örneği. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 33(4), 1137-1152.
  • Braillon, A., Chaine, F. X., & Gignon, M. (2008, June). Healthcare quality is not so new: the benchmarking case. In Annales francaises d'anesthesie et de reanimation (Vol. 27, No. 6, pp. 467-469).
  • Charnes, A. , Cooper, W. W. , & Rhodes, E. (1978). Measuringtheefficiency ofdecision making units. European Journal of Operational Research, 2 (6), 429–4 4 4 .
  • Cinaroglu, S. (2020). Integrated k-means clustering with data envelopment analysis of public hospital efficiency. Health Care Management Science, 23(3), 325-338.
  • Emrouznejad, A. , & Yang, G. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978-2016. Socio-Economic Planning Sciences, 61 (1), 1–5 .
  • Erdem, B. (2006). İşletmelerde Yeni Bir Yönetim Yaklaşımı: Kıyaslama Benchmarking Yazınsal Bir İnceleme. Balıkesir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 9(15), 65-94.
  • Ersoy, K. , Kavuncubasi, S. , Ozcan, Y. A. , & Harris, J. M., II (1997). Technical efficiencies of Turkish hospitals: DEA approach. Journal of Medical Systems, 21 (2), 67–74 .
  • Ettorchi-Tardy, A., Levif, M., & Michel, P. (2009). Benchmarking: A Method for Continuous Quality Improvement in Health. Healthcare Policy, 101-119.
  • Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120 (3), 253–290 .
  • Gandhi, A. V., & Sharma, D. (2018). Technical efficiency of private sector hospitals in India using data envelopment analysis. Benchmarking: An International Journal.
  • Hollingsworth, B. , Dawson, P. , & Maniadakis, N. (1999). Efficiency measurement of health care: A review of non-parametric methods and applications. Health Care Management Science, 2 (3), 161–172 .
  • Ibrahim, M. D., & Daneshvar, S. (2018). Efficiency analysis of healthcare system in Lebanon using modified data envelopment analysis. Journal of healthcare engineering, 2018.
  • Irk, E. & Döven, M. S. (2018). Firmaların Uyguladıkları Rekabet Stratejileri ve Bu Karara Etki Eden Faktörler. İşletme Bilimi Dergisi, 6(1), 135-162.
  • Kim, C., & Kim, H. J. (2019). A study on healthcare supply chain management efficiency: Using bootstrap data envelopment analysis. Health care management science, 22(3), 534-548.
  • Kumar, S., & Chandra, C. (2001). Enhancing the Effectiveness of Benchmarking in Manufacturing Organizations. Industrial Management & Data Systems, 80-89.
  • Mariz, F. B., Almeida, M. R., & Aloise, D. (2018). A review of dynamic data envelopment analysis: State of the art and applications. International Transactions in Operational Research, 25(2), 469-505.
  • Omrani, H., Shafaat, K., & Emrouznejad, A. (2018). An integrated fuzzy clustering cooperative game data envelopment analysis model with application in hospital efficiency. Expert Systems with Applications, 114, 615-628.
  • Pantall, J. (2001). Benchmarking in Healthcare. NT Research Vol.6 No.2, 568-580.
  • Peykani, P., Mohammadi, E., Emrouznejad, A., Pishvaee, M. S., & Rostamy-Malkhalifeh, M. (2019). Fuzzy data envelopment analysis: an adjustable approach. Expert Systems with Applications, 136, 439-452.
  • Rezaee, M. J., Yousefi, S., & Hayati, J. (2018). A decision system using fuzzy cognitive map and multi-group data envelopment analysis to estimate hospitals’ outputs level. Neural Computing and Applications, 29(3), 761-777.
  • Şahin, B., & İlgün, G. (2019). Assessment of the impact of public hospital associations (PHAs) on the efficiency of hospitals under the ministry of health in Turkey with data envelopment analysis. Health care management science, 22(3), 437-446.
  • T.C. Sağlık Bakanlığı (2017) Kamu Hastaneleri İstatistik Raporu, Ağız ve Diş Sağlığı Hizmet Bilgileri. Erişim Adresi: https://khgmistatistikdb.saglik.gov.tr/Eklenti/21853/0/kamu-hastaneleri-istatistik-raporu--2017pdf.pdf, ss.1-249
  • Yang, W., Cai, L., Edalatpanah, S. A., & Smarandache, F. (2020). Triangular single valued neutrosophic data envelopment analysis: application to hospital performance measurement. Symmetry, 12(4), 588.
  • Zhang, T., Lu, W., & Tao, H. (2020). Efficiency of health resource utilisation in primary-level maternal and child health hospitals in Shanxi Province, China: a bootstrapping data envelopment analysis and truncated regression approach. BMC health services research, 20(1), 1-9.
  • Zhang, X., Tone, K., & Lu, Y. (2018). Impact of the local public hospital reform on the efficiency of medium‐sized hospitals in Japan: An improved slacks‐based measure data envelopment analysis approach. Health services research, 53(2), 896-918.

Ayrıntılar

Birincil Dil Türkçe
Konular İşletme
Bölüm Araştırma Makaleleri
Yazarlar

Altuğ ÇAĞATAY> (Sorumlu Yazar)
TOKAT GAZİOSMANPAŞA ÜNİVERSİTESİ
0000-0001-7067-5570
Türkiye


Abdurrahman İSKENDER>
SİVAS CUMHURİYET ÜNİVERSİTESİ
0000-0001-8055-7869
Türkiye

Erken Görünüm Tarihi 31 Mart 2022
Yayımlanma Tarihi 31 Mart 2022
Kabul Tarihi 23 Mart 2022
Yayınlandığı Sayı Yıl 2022, Cilt 5, Sayı 1

Kaynak Göster

APA Çağatay, A. & İskender, A. (2022). VERİ ZARFLAMA ANALİZİ YÖNTEMİ İLE SAĞLIK KURULUŞLARININ ETKİNLİĞİNİN ANALİZİ: KAMU AĞIZ VE DİŞ SAĞLIĞI MERKEZLERİ ÖRNEĞİ . Stratejik Yönetim Araştırmaları Dergisi , 5 (1) , 56-72 . DOI: 10.54993/syad.1063633