Thesis (MMed)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: BACKGROUND Post anesthesia discharge criteria scoring systems have been used successfully to aid discharge from the post anesthetic care unit (PACU) for over 40 years. They do not replace, but rather act in conjunction with good clinical judgment, and provide concise, standardized documentation of a patient’s readiness for discharge. 1,2,3,4,5 In order to improve patient safety, provide clear documentation and to aid future audit, a discharge criteria scoring system was developed for use in our PACU (Addendum A). It is a modification of the Aldrete Scoring System and the modified Post Anesthetic Discharge Scoring System (PADSS) proposed by Chung.1 There is a steadily increasing patient burden on the existing medical infrastructure in South Africa. Tygerberg Academic Hospital is no exception, and because of the high demand on our theatre services, optimal efficiency is essential. We speculated that our discharge criteria scoring system might increase the efficiency of our PACU when compared to the traditional time based system. The more healthy patients, undergoing minor procedures, could potentially spend less time in PACU, allowing the nurses to focus on problem cases. Increasing the speed of transit might also help prevent delays in theatre due to lack of bed space in PACU. Our primary endpoint was to compare the duration of time spent by patients in the PACU at Tygerberg Academic Hospital, from the moment they are admitted, to the time they are discharged to the ward, before and after the introduction of a discharge criteria scoring system. While planning the audit, one of the factors that staff identified as contributing to delayed discharge from PACU, was the time it took for the wards to collect their patients. A secondary objective, therefore, was to assess the amount of time that elapsed between calling the ward to collect the patient, and the patient leaving PACU. METHODS AND MATERIALS Prior to commencing the audit, approval was obtained from the Human Research Ethics Committee of the Faculty of Health Sciences of the University of Stellenbosch and Tygerberg Academic Hospital. The Audit, its purpose and possible benefits, was discussed with representatives of the nurses working in PACU, and written consent was obtained from those who would be involved in the data collection (Addendum B). Audit forms (Addendum C), collection boxes, and posters reminding staff to participate in the audit were prepared. Our first audit was performed over approximately a week in August 2012. During this period, the traditional time-based discharge system was still in operation. Data was captured from 327 patients. Audit forms were placed in a collection box, which was cleared daily by the primary investigator. The discharge criteria scoring system was introduced to the PACU staff in January 2013. The nurses were trained in its use, and a one month period was allowed for all involved to become accustomed to the new system. A second audit was performed in February 2013, again over a week, during which we gathered data from 313 patients. RESULTS The median value of the time spent by patients in the PACU decreased from 1 hour 25 minutes, to 1 hour 15 minutes, after introduction of the discharge criteria scoring system. This was statistically significant (p-value = 0.003). The median time between calling the ward to collect a patient, and the patient leaving recovery, was 15 minutes. CONCLUSION The main finding of the study was that the introduction of a discharge criteria scoring system decreased the median duration of time spent by patients in the post anesthetic care unit at Tygerberg Academic Hospital. / AFRIKAANSE OPSOMMING: AGTERGROND Puntestelsels as ontslag kriteria na narkose, word vir die afgelope 40 jaar suksesvol gebruik as maatstaf om pasiënte uit die herstelkamer te ontslaan. Hierdie kriteria vervang nie goeie kliniese oordeel nie, maar is ’n addisionele hulpmiddel om te bepaal of die pasiënt gereed is vir ontslag en om noukeurige, gestandardiseerde dokumentasie te verseker. 1,2,3,4,5 'n Nuwe puntestelsel vir ontslag is vir die herstelkamer van Tygerberg Akademiese Hospitaal ontwikkel om pasiëntesorg en dokumentasie te verbeter, asook om ouditering in die toekoms te vergemaklik (Addendum A). Hiervoor is die Aldrete Scoring System en die gemodifiseerde PADSS, voorgestel deur Chung, aangepas. 1 Die bestaande mediese infrastruktuur in Suid-Afrika beleef tans ‘n geleidelike toename in die getal pasiënte. Tygerberg Akademiese Hospitaal is geen uitsondering nie en as gevolg van die hoë aanvraag na ons teaterdienste, is uiterste doeltreffendheid noodsaaklik. Ons vermoede was dat hierdie aangepaste puntestelsel doeltreffendheid in die herstelkamer sou verbeter in vergelyking met die meer tradisionele tyd-gebaseerde sisteem. Gesonde pasiënte wat kleiner prosedures ondergaan, sal waarskynlik na ’n korter periode ontslaan kan word wat die verpleegpersoneel in staat sal stel om meer aandag aan probleem gevalle te gee. Bespoediging van die pasiëntvloei behoort onnodige vertragings van teatergevalle weens 'n tekort aan beddens in die herstelkamer, te beperk. Die primêre doel van die studie was om te bepaal of die gebruik van die aangepaste puntestelsel as ontslag kriteria in Tygerberg Akademiese Hospitaal, die tydperk wat die pasiënt in die herstelkamer deurbring, verkort. Die herstelkamer verpleegsters het beweer dat die saal personeel ‘n lang tyd gevat het om hulle pasiente in herstelkamer te kom haal. Vervolgens is 'n sekondêre doelwit ingesluit om die tydperk te bepaal vandat die saalpersoneel in kennis gestel word, totdat die pasiënt die herstelkamer verlaat. METODE Goedkeuring is verkry van die Menslike Navorsing en Etiese Komitee van die Gesondheidswetenskap Fakulteit van die Universiteit van Stellenbosch en Tygerberg Akademiese Hospitaal voor die aanvang van die studie. Die studie, asook die doel en moontlike voordele daarvan is vooraf bepsreek met verteenwoordigers van die herstelkamer verpleegpersoneel en skriftelike toestemming is verkry van al die deelnemers wat betrokke sou wees by die data versameling (Addendum B). Oudit vorms (Addendum C), versamelhouers en inligtingsplakkate vir die betrokke personeel is voorberei. Die aanvanklike oudit is in Augustus 2012 oor 'n periode van ongeveer een week uitgevoer. Tydens hierdie oudit is die tradisionele tydgebaseerde sisteem gebruik. Inligting van 327 pasiёnte is versamel. Die oudit vorms is in die versamelbokse geplaas en is daagliks deur die primêre navorser verwyder. Die aangepaste puntestelsel as ontslag kriteria, is in Januarie 2013 in die herstelkamer geïmplementeer. Die verpleegpersoneel het opleiding ontvang waarna die aangepaste puntestelsel vir een maand gebruik is om te verseker dat die personeel vertroud is daarmee. In Februarie 2013, is ‘n tweede oudit oor ‘n tydperk van een week uitgevoer, waartydens inligting van 313 pasiёnte versamel is. RESULTATE Na die implementering van die aangepaste puntestelsel as ontslag kriteria, het die mediane tyd wat pasiënte in die herstelkamer deurbring afgeneem van 1 uur en 25 minute tot 1 uur en 15 minute. Hierdie afname is statities betekenisvol (p-waarde = 0.003) Die mediane tyd vandat die saal in kennis gestel is totdat die pasiënt die herstelkamer verlaat, was 15 minute. GEVOLGTREKKING Die hoof bevinding van die studie is dat die mediane tydperk wat die pasiënte in die herstelkamer deurbring verminder is deur die implementering van die aangepaste puntestelsel as ontslag kriteria in Tygerberg Akademiese Hospitaal.

Thesis (PhD)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: When estimating the covariance matrices of two or more populations, the covariance matrices are often assumed to be either equal or completely unrelated. The common principal components (CPC) model provides an alternative which is situated between these two extreme assumptions: The assumption is made that the population covariance matrices share the same set of eigenvectors, but have di erent sets of eigenvalues. An important question in the application of the CPC model is to determine whether it is appropriate for the data under consideration. Flury (1988) proposed two methods, based on likelihood estimation, to address this question. However, the assumption of multivariate normality is untenable for many real data sets, making the application of these parametric methods questionable. A number of non-parametric methods, based on bootstrap replications of eigenvectors, is proposed to select an appropriate common eigenvector model for two population covariance matrices. Using simulation experiments, it is shown that the proposed selection methods outperform the existing parametric selection methods. If appropriate, the CPC model can provide covariance matrix estimators that are less biased than when assuming equality of the covariance matrices, and of which the elements have smaller standard errors than the elements of the ordinary unbiased covariance matrix estimators. A regularised covariance matrix estimator under the CPC model is proposed, and Monte Carlo simulation results show that it provides more accurate estimates of the population covariance matrices than the competing covariance matrix estimators. Covariance matrix estimation forms an integral part of many multivariate statistical methods. Applications of the CPC model in discriminant analysis, biplots and regression analysis are investigated. It is shown that, in cases where the CPC model is appropriate, CPC discriminant analysis provides signi cantly smaller misclassi cation error rates than both ordinary quadratic discriminant analysis and linear discriminant analysis. A framework for the comparison of di erent types of biplots for data with distinct groups is developed, and CPC biplots constructed from common eigenvectors are compared to other types of principal component biplots using this framework. A subset of data from the Vermont Oxford Network (VON), of infants admitted to participating neonatal intensive care units in South Africa and Namibia during 2009, is analysed using the CPC model. It is shown that the proposed non-parametric methodology o ers an improvement over the known parametric methods in the analysis of this data set which originated from a non-normally distributed multivariate population. CPC regression is compared to principal component regression and partial least squares regression in the tting of models to predict neonatal mortality and length of stay for infants in the VON data set. The tted regression models, using readily available day-of-admission data, can be used by medical sta and hospital administrators to counsel parents and improve the allocation of medical care resources. Predicted values from these models can also be used in benchmarking exercises to assess the performance of neonatal intensive care units in the Southern African context, as part of larger quality improvement programmes. / AFRIKAANSE OPSOMMING: Wanneer die kovariansiematrikse van twee of meer populasies beraam word, word dikwels aanvaar dat die kovariansiematrikse of gelyk, of heeltemal onverwant is. Die gemeenskaplike hoofkomponente (GHK) model verskaf 'n alternatief wat tussen hierdie twee ekstreme aannames gele e is: Die aanname word gemaak dat die populasie kovariansiematrikse dieselfde versameling eievektore deel, maar verskillende versamelings eiewaardes het. 'n Belangrike vraag in die toepassing van die GHK model is om te bepaal of dit geskik is vir die data wat beskou word. Flury (1988) het twee metodes, gebaseer op aanneemlikheidsberaming, voorgestel om hierdie vraag aan te spreek. Die aanname van meerveranderlike normaliteit is egter ongeldig vir baie werklike datastelle, wat die toepassing van hierdie metodes bevraagteken. 'n Aantal nie-parametriese metodes, gebaseer op skoenlus-herhalings van eievektore, word voorgestel om 'n geskikte gemeenskaplike eievektor model te kies vir twee populasie kovariansiematrikse. Met die gebruik van simulasie eksperimente word aangetoon dat die voorgestelde seleksiemetodes beter vaar as die bestaande parametriese seleksiemetodes. Indien toepaslik, kan die GHK model kovariansiematriks beramers verskaf wat minder sydig is as wanneer aanvaar word dat die kovariansiematrikse gelyk is, en waarvan die elemente kleiner standaardfoute het as die elemente van die gewone onsydige kovariansiematriks beramers. 'n Geregulariseerde kovariansiematriks beramer onder die GHK model word voorgestel, en Monte Carlo simulasie resultate toon dat dit meer akkurate beramings van die populasie kovariansiematrikse verskaf as ander mededingende kovariansiematriks beramers. Kovariansiematriks beraming vorm 'n integrale deel van baie meerveranderlike statistiese metodes. Toepassings van die GHK model in diskriminantanalise, bi-stippings en regressie-analise word ondersoek. Daar word aangetoon dat, in gevalle waar die GHK model toepaslik is, GHK diskriminantanalise betekenisvol kleiner misklassi kasie foutkoerse lewer as beide gewone kwadratiese diskriminantanalise en line^ere diskriminantanalise. 'n Raamwerk vir die vergelyking van verskillende tipes bi-stippings vir data met verskeie groepe word ontwikkel, en word gebruik om GHK bi-stippings gekonstrueer vanaf gemeenskaplike eievektore met ander tipe hoofkomponent bi-stippings te vergelyk. 'n Deelversameling van data vanaf die Vermont Oxford Network (VON), van babas opgeneem in deelnemende neonatale intensiewe sorg eenhede in Suid-Afrika en Namibi e gedurende 2009, word met behulp van die GHK model ontleed. Daar word getoon dat die voorgestelde nie-parametriese metodiek 'n verbetering op die bekende parametriese metodes bied in die ontleding van hierdie datastel wat afkomstig is uit 'n nie-normaal verdeelde meerveranderlike populasie. GHK regressie word vergelyk met hoofkomponent regressie en parsi ele kleinste kwadrate regressie in die passing van modelle om neonatale mortaliteit en lengte van verblyf te voorspel vir babas in die VON datastel. Die gepasde regressiemodelle, wat maklik bekombare dag-van-toelating data gebruik, kan deur mediese personeel en hospitaaladministrateurs gebruik word om ouers te adviseer en die toewysing van mediese sorg hulpbronne te verbeter. Voorspelde waardes vanaf hierdie modelle kan ook gebruik word in normwaarde oefeninge om die prestasie van neonatale intensiewe sorg eenhede in die Suider-Afrikaanse konteks, as deel van groter gehalteverbeteringprogramme, te evalueer.