AntecedentsEvolució del sistema sanitari a Catalunya. Ha comportat canvis en:- Aspectes jurídico-legals- Modernització tecnològica- Extensió de la Xarxa: construcció d'hospitals comarcals. Justificació de l'estudi La descripció i anàlisi de l'evolució de la casuística en els hospitals terciaris de la ciutat té interès fonamentalment en dues àrees: finançament i planejament. Objectius Descripció i valoració dels canvis de la casuística dels hospitals de la Vall d'Hebron entre l'any 1994 i l'any 1997. Material Bases de dades: any 1994 - 1997- Ciutat Sanitària de la Vall d'Hebron- XHUP Evolució de les línies de producte terciàries. Increment de la seva freqüència relativa. Els hospitals de la Vall d'Hebron mostren una lleugera reducció de l'1,5% del volum d'hospitalitzacions a l'any 97 respecte de l'any 94. En canvi al conjunt de la XHUP el volum d'hospitalitzacions ha augmentat al llarg del període. La Ciutat Sanitària de la Vall d'Hebron no ha presentat reducció de l'estada mitjana al llarg del període estudiat. El conjunt d'hospitals de la XHUP, en canvi, presenta una reducció del 14,8%. - Els hospitals de la Vall d'Hebron mostren l'any 97 una complexitat de la casuística superior respecte l'any 94. Aquest increment és superior al detectat al conjunt de centres de la XHUP (6,8% vs 6,25%).- Els hospitals de la Vall d'Hebron mostren una lleugera reducció de l'1,5% del volum d'hospitalitzacions l'any 97 respecte l'any 94. - En canvi al conjunt de la XHUP el volum d'hospitalitzacions ha augmentat al llarg del període i augmenta la seva complexitat.- La Ciutat Sanitària de la Vall d'Hebron no ha presentat reducció de l'estada mitjana al llarg del període estudiat. El conjunt d'hospitals de la XHUP, en canvi, presenta una reducció del 14,8%.ConclusionsMalgrat el lleuger augment de terciarització de la casuística de la Ciutat Sanitària, la major part de la seva activitat es composa de l'atenció a processos de complexitat homòloga a la que presenten els hospitals comarcals, destinats a cobrir les necessitats assistencials de la seva població adscrita, atès que aquestos han augmentat més la seva complexitat que els hospitals de la Vall d'Hebron. Per tant, el diferencial de complexitat no s'amplia. / AntecedentsEvolution of the health care system in Catalonia. It has involved changes in:- Legal aspects - Technological modernisation- Enlargement of the net: construction of comarcal hospitals (1). Justification of the study The description and analysis of the casuistics evolution in the city tertiary hospitals (top-level hospitals) has interest in two main areas: fionancing and planification. Objectives Description and evaluation of the changes in the casuistics of the Vall d'Hebron Hospitals between the year 1994 and the year 1997. Data Databases: year 1994 - 1997- Vall d'Hebron Sanitary Complex - XHUP (Xarxa Hospitalària d'Utilització Pública- Net of Hospitals of Public Use) Evolution of the tertiary product lines. Increase of the relative frequency. The Vall d'Hebron hospitals show a slight reduction of 1,5% in the hospitalisations' volume for the year 97 compared with that of the year 94. On the contrary, in the XHUP as a whole, the hospitalisations' volume has increased through the period. The Vall d'Hebron Sanitary Complex has not showed a decrease in the average stay for the studied period, whereas the XHUP hospitals showed as a whole a reduction of 14,8%. - The Vall d'Hebron hospitals show the year 97 a higher complexity of the casuistics compared with the year 94. This increase is higher than the one detected in the whole of the XHUP centres (6,8% vs 6,25%). - The Vall d'Hebron hospitals show a slight reduction of 1,5% in the hospitalizations volume the year 97 compared with the year 94. - On the contrary, in the whole XHUP the hospitalisations volume has increased through the period and has increased its complexity. - The Vall d'Hebron Sanitary Complex has not showed a reduction in the average stay in the studied period, whereas the XHUP hospitals as a whole show a reduction of 14,8%.ConclusionsDespite the slight increase of the casustics terciarization in the Vall d'Hebron Sanitary Complex, most of its activity is based on services to processes of similar complexity to those attended in comarcal hospitals (1). These hospitals, which are appointed to cover the assistential needs of their assigned population, have increased their complexity more than the Vall d'Hebron Hospitals. Therefore, the complexity differential is not expanded.

I detta arbete studeras värdeskapande inom vårdsektorn. Syftet är att undersöka hur värdeskapande mäts inom vården genom att kvantitativt jämföra värdeskapandet mellan två vårdenheter på Karolinska Universitetssjukhuset. Värdeskapande utgår i detta arbete från det koncept, Värdebaserad Vård (VBV), som utvecklats av ekonomerna Michael Porter och Elizabeth Teisberg. Resultatet från den kvantitativa studien visar att de två studerade vårdenheterna skiljer sig något åt gällande värdeskapande men att dessa skillnader blir väldigt små då hänsyn tas till de behandlade patientpopulationernas egenskaper. Slutsatserna från studien visar att de främsta svårigheterna för en undersökning av detta slag är relaterade till de praktiska metodvalen som behöver göras under undersökningen. För att lyckas med en implementering utav VBV-konceptet behövs ett gediget arbete för att utforma ramverk och procedurer för att mäta och jämföra värdeskapandet.

Background: Immunological and virological responses to ART are important outcome indicators that are mostly used to evaluate the success of an ART program. A comparative performance between ART providers based on the two outcomes can be useful in optimising resources to underperforming providers and advising quality improvement plans. Aim: To compare immunological and virological responses of ART for adult HIV positive patients between providers in Tshwane District, Gauteng Province, South Africa. Methodology: This study was an analytical observational study that retrospectively compared patient treatment outcomes on immunological and virological responses between 16 Antiretroviral Therapy (ART) providers. The analysis compared baseline patients’ status on these two outcomes with their statuses after 6 and12 months on ART. Ordinary logistic regression was used to calculate Standardised Incidence Ratios (SIR), while multilevel model analysis was used to calculate specific provider random effects of poor immunological and virological responses. Results: After 6 months of treatment, the SIR of poor immunological outcome for all clinics under study, as predicted by the unadjusted logistic regression models was 0.29 (95% CI: 0.27-0.31), but varied from a low of 0.14 (95% CI: 0.00-0.40) to a high of 0.66 (95% CI: 0.13-1.20) between the clinics. Two clinics had a Standardised Incidence Ratio (SIR) of poor immunological response that was significantly below 1 (poor immunological rate below average), while three clinics had an SIR above 1 (poor immunological rate above average) under the unadjusted logistic models. After adjusting for the effects of gender, age, drug combination, religion and present virological status, no clinic had a SIR that was significantly below 1, but two clinics had a SIR that was significantly above 1. xi Under the logistic multilevel (MLLR) analysis, the unadjusted model flagged two clinics whose clinic specific effects were below zero (lower rate of poor immunological outcome below that of the total sample) and one clinic whose clinic specific effect was above zero (higher rate of poor immunological outcome below the total sample rate). The adjusted model showed that no clinic had residual effects that were significantly below or above zero. The confidence intervals for MLLR model were found not to be wider than those of the logistic regression (LR) models particularly for clinics with small sample sizes. A number of clinics changed the relative order of their SIR/random effects after case-mix adjustments under both the LR and MLLR modelling. For poor virological response, both the LRD and MLLR models indicated no clinic specific effects. The predicted poor virological response rate by the case-mix unadjusted LR model was 0.12 (95% CI 0.11 - 0.13). All clinics except one had SIRs that were not significantly different from 1. After adjusting for CD4 count and age, no clinic had an SIR that was significantly different from 1. Conclusions: Case-mix or patients baseline characteristics explained much of the variation in the Standardised Incidence Ratios (SIR) of poor immunological outcome after 6 months of patient treatment, while provider (clinic) specific effects explained much of the variation after 12 months of treatment. After 6 months of treatment, the results also showed that there were significant differences in the SIR between the clinics before case-mix adjustments, but the differences disappeared after case-mix adjustments. This shows that comparison of treatment outcomes between providers (clinics) can be misleading if no proper adjustment are made for confounding factors. Differences in the SIRs for poor virological outcome, after 6 months of patient treatment were no longer significant between clinics after taking account of CD4 count and age. / Dissertation (MSc)--University of Pretoria, 2014. / gm2014 / School of Health Systems and Public Health / unrestricted

Competition among hospitals and managed care have forced hospital industry to be more efficient. With higher degrees of hospital competition and managed care penetration, hospitals have argued that the rate of increase in hospital cost is greater than the rate of increase in hospital revenue. By developing a payer-specific case mix index (CMI) for third-party patients, this paper examined the effect of hospital case mix on hospital cost and revenue for third-party patients in California using the hospital financial and utilization data covering 1986-1998. This study found that the coefficients for CMIs in the third-party hospital revenue model were greater than those in the hospital cost model until 1995. Since 1995, however, the coefficients for CMIs in the third-party hospital revenue model have been less than those in hospital cost models. Over time, the differences in coefficients for CMIs in hospital revenue and cost models for third-party patients have become smaller and smaller although those differences are statistically insignificant.

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