Identifying technical inefficiencies and quality concerns in institutional pharmacies of private hospital groups using data envelopment analysis

[摘要] ENGLISH ABSTRACT: Private health care service providers continuously strive to find a balance in providing quality patient care while being cost-effective. This balance serves the interest of both the patient and the profit-driven organisations providing these services. Lower costs result in lower service fees, which is advantageous toorganisation market share and patient medical care costs.Institutional pharmaceutical services (i.e. those provided in a hospital) differ from other in-hospital medical specialities in that the hours of pharmacists and pharmacist's assistants are not billed to individual patients, but are rather absorbed in the operational cost of a hospital. Improving the performance of the institutional pharmacy can thus directly affect a hospital's bottom line.The problem is that identifying performance improvement initiatives are difficult, as the factors affecting performance are non-commensurate. Case studies from the literature show that the physical environment, process design, inventory management, scheduling, and human resources management and well-being affect pharmacy performance. These factors are however not easily comparable ormeasurable when analysing performance.Data Envelopment Analysis (DEA) is a frontier analysis technique used to measure the relative performance of Decision Making Units (DMUs) with commoninputs and outputs. The primal and dual (and thus slack values) of the DEA linear programming problems provide insight into inefficiencies of a DMU compared to the rest of the DMUs in the set.The aim of this study was to use DEA to identify technical inefficiencies and quality concerns in institutional pharmacies of private hospitals. This would enable pharmacy operational managers to identify underperforming pharmacies and tospecify and garner financial support for performance enhancing interventions.DEA was applied using data provided on the inputs and outputs of a private hospital group in South Africa. The measurable inputs used for the analysis included the employee hours per month, the percentage of aged stock, the number of call-outs for pharmacists per month and the number of reported incidents.Outputs included the number of prescriptions filled for in-hospital use, discharged patients and retail customers per month.Three DEA models, each with their primal and dual problems, were developed.Multiple models were developed to ensure that results were reasonable and consistent across the various models for verification and validation purposes. Two more models were developed to perform sensitivity analysis on model results.The DMU results were related back to the case studies from the literature by interpreting the results of three example DMUs in the set. This gave context to the results and illustrated how to identify possible actionable plans for improvement initiatives.As DEA only provides insight into how DMUs perform relative to each other, knowledge on how to improve the group of pharmacies continuously so as to remain competitive in a global context is also required. The literature on continuous improvement is presented, with case studies relating to the implementation of process improvement techniques and advanced pharmacy technologies. These studies are presented to be implemented in pharmacies already rated fully efficient through DEA, so as to continuously improve the standard for relative performance.

[发布机构] Stellenbosch University