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

Uys, Nina (2015-12)

Thesis (MEng)--Stellenbosch University, 2015.

Thesis

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 to organisation 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 or measurable when analysing performance. Data Envelopment Analysis (DEA) is a frontier analysis technique used to measure the relative performance of Decision Making Units (DMUs) with common inputs 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 to specify 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.

AFRIKAANSE OPSOMMING: Private gesondheidsorg-dienste streef deurentyd na 'n balans tussen die verskaffing van gehalte-pasiëntesorg en hoe om koste-effektief te bly. So 'n balans bevoordeel die pasiënt se belange en dié van die winsgedrewe organisasies wat hierdie dienste lewer. Laer kostes lei tot laer diensfooie, wat voordelig is vir organisatoriese markaandeel asook pasiënte se gesondheidsorg-koste. Institusionele apteekdienste (d.i. dié wat in hospitale gelewer word) verskil van hospitale se ander mediese spesialisdienste deurdat 'n pasiënt nie vir aptekers en hul assistente se dienstye betaal nie maar dat die hospitaal se operasionele koste hierdie uitgawes absorbeer. Beter werkverrigting in die institusionele apteek raak dus die hospitaalbegroting direk. Die probleem is dat inisiatiewe vir beter werklewering moeilik uitkenbaar is want die faktore wat prestasie beïnvloed, is onvergelykbaar. Volgens gevallestudies uit die literatuur word apteekprestasie geraak deur die fisieke omgewing, prosesontwerp, voorradebestuur, skedulering, menslike hulpbronne en die algemene welstand van personeel. Vir prestasie-ontleding is dié faktore egter nie maklik vergelykbaar of meetbaar nie. Data Omvattings-Ontleding (DOO) [Data Envelopment Analysis, DEA] is 'n voorpunt-ontledingstegniek waarmee Besluitnemingseenhede (BNE's) [Decision Making Units: DMU's] wat gemeenskaplike in- en uitsette het, se relatiewe prestasie gemeet word. Die DOO liniêere program se vernaamste, tweeledige (en dus spelings-) waardes bied insig in die ondoeltreffendhede van 'n BNE teenoor die res van die BNE's in die stel voorbeelde. Dié studie se mikpunt was om DOO te gebruik om tegniese ondoeltreffendhede asook die gehalte waaroor daar kommer bestaan in private hospitale se institusionele apteke te meet. Dit kan apteke se operasionele bestuurders in staat stel om onderpresterende apteke uit te ken en om, vir ingryping ter wille van beter prestasie, finansiële steun te spesifiseer en te bewillig. DOO is toegepas deur die gebruik van data wat oor die in- en uitsette van 'n private hospitaalgroep in Suid-Afrika verskaf is. Die meetbare insette wat vir die ontleding gebruik is, het ingesluit die tyd wat die werknemers per maand gewerk het, die persentasie verouderde voorraad, hoeveel keer elke apteker elke maand uitgeroep is en hoeveel voorvalle aangemeld is. Uitsette het ingesluit die getal voorskrifte wat maandeliks vir hospitaalgebruik, ontslag-pasiënte en kleinhandel-kliënte ingevul is. Drie DOO-modelle is ontwikkel, elkeen met sy vernaamste én tweeledige probleme. Veelvuldige modelle is ontwikkel om te verseker dat resultate vir kontrole en bekragtiging dwarsoor die onderskeie modelle redelik en konsekwent was. Om sensitiwiteitsontledings op modelresultate uit te voer, is nog twee modelle ontwikkel. Die DOO-modelle is met die gevallestudies uit die literatuur in verband gebring deur die vertolking van die resultate van drie uit die stel DOO-voorbeelde. Dit het die resultate in konteks geplaas en geïllustreer hoe werkbare planne vir verbeterings-inisiatiewe geïdentifiseer kan word. Omdat DOO net insig bied in hoe BNE's in verhouding tot mekaar presteer, is kennis ook nodig oor hoe om die apteekgroep deurlopend te verbeter sodat dit globaal mededingend bly. Die literatuur oor deurlopende verbetering is dus aangebied, saam met gevallestudies wat verband hou met die inwerkingstelling van tegnieke vir prosesverbetering en vir gevorderde apteektegnologieë. Dié studies is aangebied sodat dit in werking gestel kan word in apteke wat reeds deur DOO as ten volle doeltreffend geëvalueer is, om die vlak van relatiewe prestasie voortdurend te verbeter.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/97913
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