Efficiency and productivity measurement of rural township hospitals in China: a bootstrapping data envelopment analysis

Abstract

ObjectiveTownship hospitals (THs) are important components of the three-tier rural healthcare system of China. However, the efficiency and productivity of THs have been questioned since the healthcare reform was implemented in 2009. The objective of this study is to analyse the efficiency and productivity changes in THs before and after the reform process.Setting and participantsA total of 48 sample THs were selected from the Xiaogan Prefecture in Hubei Province from 2008 to 2014.Outcome measuresFirst, bootstrapping data envelopment analysis (DEA) was performed to estimate the technical efficiency (TE), pure technical efficiency (PTE) and scale efficiency (SE) of the sample THs during the period. Second, the bootstrapping Malmquist productivity index was used to calculate the productivity changes over time.ResultsThe average TE, PTE and SE of the sample THs over the 7-year period were 0.5147, 0.6373 and 0.7080, respectively. The average TE and PTE increased from 2008 to 2012 but declined considerably after 2012. In general, the sample THs experienced a negative shift in productivity from 2008 to 2014. The negative change was 2.14%, which was attributed to a 23.89% decrease in technological changes (TC). The sample THs experienced a positive productivity shift from 2008 to 2012 but experienced deterioration from 2012 to 2014.ConclusionsThere was considerable space for TE improvement in the sample THs since the average TE was relatively low. From 2008 to 2014, the sample THs experienced a decrease in productivity, and the adverse alteration in TC should be emphasised. In the context of healthcare reform, the factors that influence TE and productivity of THs are complex. Results suggest that numerous quantitative and qualitative studies are necessary to explore the reasons for the changes in TE and productivity.

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

“…Thus, the overall technical inefficiency of district-level MCHHs in Shanxi Province is serious but with huge potential for improvement. In other words, the resources invested to MCHHs at their current size are not fully utilised, and their output is insufficient [10,25]. Similarly, PTE was a widespread problem, that is, the capacity of management and technology in the district-level MCHHs was rather low.…”

“…Furthermore, the use of an output-orientated DEA, where DMUs are given a fixed quantity of resources (inputs) and asked to maximise output, is appropriate because the input of public hospitals is determined centrally by the Ministry of Health in China; hence, hospital managers have no control over the size of the hospitals they run [25]. The output-oriented DEA using a smooth bootstrapping procedure was adopted and operated on STATA 14.0.…”

Measuring Technical Efficiency of Hospitals Using Data Envelopment Analysis: A Review

“…A study conducted in China to measure technical efficiency for 127 public hospitals was employed CCR, CRS, input-orientation, and the total combination number of inputs and outputs was 6 . A study conducted in China to measure technical efficiency for 48 public hospitals was used CCR, CRS, output-oriented and the total combination number of inputs and outputs was 6 (Cheng et al, 2016). In Iran a study conducted to measure technical efficiency for 52 public and private hospitals was used BCC, VRS, input-oriented, and the total combination number of inputs and outputs was 8 (Kakeman, Forushani, & Dargahi, 2016).…”

“…In regard to return to scale, there were studies used VRS these studies were (Ali et al, 2017), (Kakeman et al, 2016), (Kalhor et al, 2016), (Mujasi et al, 2016), (H. Li & Dong, 2015), (Applanaidu et al, 2014), (J. P. Harrison & Meyer, 2014), (Jehu-Appiah et al, 2014), (Jat & Sebastian, 2013), (Yusefzadeh, Ghaderi, Bagherzade, & Barouni, 2013). For CRS model, the studies were shared in this model type were (N. Li, Wang, Ni, & Wang, 2017), , (Cheng et al, 2016). For both CRS and VRS, the studies were used this model were (Surat, Dalbir, & Kamlesh, 2017), (Mahate & Hamidi, 2016), (Kirigia & Asbu, 2013), (Cheng et al, 2015), (El-Seoud, 2013), (Kirigia & Asbu, 2013), (Kounetas & Papathanassopoulos, 2013), (Mitropoulos et al, 2013).…”

“…In term of model orientation, there were some studies applied out-oriented. These studies were (Ali et al, 2017), (Cheng et al, 2016), (Mahate & Hamidi, 2016), (Mujasi et al, 2016), (H. Li & Dong, 2015), (Jehu-Appiah et al, 2014), (Kirigia & Asbu, 2013).…”