Hospitals come under the focus of health planners and policy makers because they invariably consume large and increasing amounts of health care resources and performance is commonly believed to fall short of that possible. The common response by governments to this situation has been to implement hospital reforms. However, emerging evidence from impact evaluations of such reforms shows little clear evidence of performance enhancement. It is argued in this study that hospital reforms in most countries are implemented without enough understanding of current performance, or knowledge of hospital behaviour. Such information is necessary for effective design, implementation and evaluation of reforms. The aim of the study was to measure hospital performance and contribute to the understanding of its determinants. The role of internal organisation and management to hospital performance has been underplayed in most studies such that the workings of the hospital remain a "black box". The study sought to demonstrate that understanding hospital performance entails understanding not only the technical relationships of dimensions of hospital performance but also the institutional context, and behaviour of individuals or groups within it who ultimately shape hospital behaviour. A multiple case study approach was used to study six tertiary hospitals in Zimbabwe. Hospital performance was first assessed through analysis of utilisation statistics. This was followed by an assessment of two dimensions of hospital performance: costs and quality of inpatient services. Costs were measured using standard cost accounting methods at hospital, ward and patient level. At patient level, a combination of. prospective micro-costing and top-down costing methods was applied to cohorts of patients suffering from selected tracer diseases: 207 malaria and 158 pulmonary tuberculosis cases. The quality of hospital inpatient services was also measured at hospital and patient level using structural and process approaches. The relationship between cost and quality of services was then explored at patient level using tracer conditions. A triangulation of methods was then used to explore internal organisation and management: staff interviews, observations, attendance at hospital meetings and review of administrative records. Analysis of activity statistics showed that the six hospitals had different levels of activity although they had similar roles in the referral hierarchy. Distinctive unit cost patterns were observed across the hospitals. Unit cost variation across hospitals was generally similar at hospital, ward and patient level. The results from the analysis of activity statistics were predictive of hospital cost classifications. The quality of hospital services varied across hospitals from both structural and process perspectives. There was little convergence in results from hospital level structural quality assessment, and process quality assessment. Cost-quality relationships in inpatient care showed a distinct pattern across tracer diseases, which permitted classification of the six hospitals into three performance categories. These classifications were used to relate quantitative and qualitative results of the study. The institutional contexts within which public hospitals in Zimbabwe operate is explored and described. There are fundamental policy design weaknesses related to the way hospitals are financed, governed and managed, which affect hospital performance. Hospital staff appears apathetic about hospital performance because of lack of appropriate incentives. Several hospital internal factors were reported as impinging on hospital performance. These factors can broadly be summarised as lack of management capacity and skills, inappropriate internal organisational and management structures, and staff reward systems. The current incentive structure at individual and institution level does not engender performance improvement. Relative hospital performance did not vary systematically with different institutional characteristics. For instance, compliance or non-compliance with mandated organisation and management structures did not account for performance differences whilst weak associations were found between relative performance, and differences in management capacity and skills. The absence of direct relationships between institutional characteristics and relative performance was not unexpected given the exploratory nature of the study and the possible multiple interrelationships between these factors Nonetheless, the study systematically describes and exposes current weaknesses in the internal structure of public hospitals in Zimbabwe, and identifies those internal organisational and management features considered important to performance. The study concludes that there is considerable scope for improving hospital efficiency and quality of services (with available resources) by changing internal organisation and management of hospitals. Of particular importance is the need to change and align incentives (monetary and nonmonetary) at both individual and institution level in ways that promote performance improvement.

The business value of Information Technology (measuring the impact of IT investments on organizational productivity and efficiency) and quantifying Information technology’s tangible and intangible benefits havebeen significant areas of interest forresearchers and industry experts alike for more than threedecades. In healthcare, an information-rich industry that directly impacts peoples’ lives, investing in IT is still being challenged by questions of payoffs and returns; thus understanding how IT impacts quality outcomes and organizational financial performancein healthcare organizations is important in IT investment decisions. The goal of this research study is to critically examinethe business value of IT in healthcare. To this end, IT’s impact on hospital outcomes is assessed throughmeasures such as increasedpatient satisfaction, improved clinical outcomes (i.e. reduced numbers of adverse events incidents and rates of readmissions), and enhanced hospital financial condition. Additionally, the effect of readily available clinical and administrative data and well-aligned process redesign initiatives to enhance strategic decision making by leadership teams is considered. To address these issues, panel data on 17 performance indicators from 107 hospitals were collected to analyze the impact of IT investment on hospital financial performance and quality of outcomes. The study showsthat the relationship between IT investment and hospital performance measures is type dependent; community or small hospitals have different results from teaching hospitals,and IT investment has an impact on the financial condition of small hospitals only. Similarly, IT investments were shown to improve clinical outcomes in community hospitals but not in small or teaching hospitals. Finally, no direct relationship was found between IT investment and patient satisfaction in any type of hospital. The impact of IT investments is shown to be enhanced when combined with corresponding process-redesign initiatives; and making the right levels of investment in organizational corporate services such as administrative services, finance, human resources, and system support improved hospitals’ financial performance. Among the IT systems used in hospital organizationsare the decision support systems that enhance the decision-making capabilities of both clinicians and administrative leaders. The Hospital Analytics Dashboard is introduced as an example of the use of such systems to allow leaders to analyzehospital’s performance as it relates to the impact of IT on patient satisfaction, clinical outcomes, and financial conditions. This proof-of-concept decision support tool can be adapted to include other performance measures, and has been devised to help hospital leadership teams visualize and analyze the relationships among performance measurespresented in a static scorecard format.It provides benchmarking information from similar-sized hospitals and is accompanied by an interactive dashboard where historical performance information can be analyzed to predict future performance according to different inputs.

Strategic management and hospital performances in small and medium hospitals ---- From the viewpoint of Balanced Scorecard---- Abstract: ---------------------------------------------------------------------------------------------- The new era of National Health Insurance has impacted the management of the small and medium hospitals significantly. For the purpose of survival and maintaining good performance, the small and medium hospitals need to adopt a suitable strategic manage ment. The published literatures in the hospital performance are numerous but with more focus in the field of public and larger hospitals, very few of them discussed about the smaller hospitals. Previously ,the measurement of hospital performance has been mainly based on the financial guideline. In this work , we investigated the relationship between strategic management and hospital performance in the different scaled small and medium hospitals using the viewpoint of Balanced Scorecard(BSC). The purposes of this study are (1) to classify hospital strategies using the Miles & Snow¡¦s typology, (2) to investigate the effects of the hospital size on hospital strategies, and (3) to examine the relationships between these different strategies and hospital performance. This project was a cross-sectional and non-experimental study with a hospital as the unit of analysis. We used an eleven- items questionnaire (Conant, 1990) to classify hospitals into four different strategic types: prospector, defender, analyzer and reactor. (Miles & Snow,1978). We also used Kaplan & Norton¡¦s Balanced Scorecard to measure the hospital performance, which including 17- item questions for internal business process, innovation and learning, customer as well as financial perspectives. Four hundred and twenty three questionnaires were mailed to the hospital CEOs with 151 were returned, representing a response rate of 35.7%. Factor analysis, Chi-Square test, ANOVA and Scheffe¡¦s test were used for the statistical analysis. The distribution of bed size were 49.7% under 50-beds, 15.2% with 51-100 beds, 11.9% with 101-150 beds, 5.3% with 151-200 beds, 3.3% with 201-250 beds, as well as 14.6% with greater than 250 beds. The results showed that 37.7% of the hospitals were analyzer, followed by defender (26.5%), reactor (24.5%), and prospector (11.3%), respectively. From a factor analysis of 17 items related to the balanced scorecard, we obtained six measures of internal business perspective (£\=0.80), all six items had factor loading above 0.60 and eigenvalues above 1.0 derived from principal components analysis with varimax rotation. Innovation and learning perspective was measured by 5 measures (£\=0.76) with factor loading above 0.60 and eigenvalues greater than 1 . Customer perspective included 4 measures (£\=0.59) with factor loading above 0.50 and eigenvalues greater than 1. In addiction , we obtained two

The business value of Information Technology (measuring the impact of IT investments on organizational productivity and efficiency) and quantifying Information technology’s tangible and intangible benefits havebeen significant areas of interest forresearchers and industry experts alike for more than threedecades. In healthcare, an information-rich industry that directly impacts peoples’ lives, investing in IT is still being challenged by questions of payoffs and returns; thus understanding how IT impacts quality outcomes and organizational financial performancein healthcare organizations is important in IT investment decisions. The goal of this research study is to critically examinethe business value of IT in healthcare. To this end, IT’s impact on hospital outcomes is assessed throughmeasures such as increasedpatient satisfaction, improved clinical outcomes (i.e. reduced numbers of adverse events incidents and rates of readmissions), and enhanced hospital financial condition. Additionally, the effect of readily available clinical and administrative data and well-aligned process redesign initiatives to enhance strategic decision making by leadership teams is considered. To address these issues, panel data on 17 performance indicators from 107 hospitals were collected to analyze the impact of IT investment on hospital financial performance and quality of outcomes. The study showsthat the relationship between IT investment and hospital performance measures is type dependent; community or small hospitals have different results from teaching hospitals,and IT investment has an impact on the financial condition of small hospitals only. Similarly, IT investments were shown to improve clinical outcomes in community hospitals but not in small or teaching hospitals. Finally, no direct relationship was found between IT investment and patient satisfaction in any type of hospital. The impact of IT investments is shown to be enhanced when combined with corresponding process-redesign initiatives; and making the right levels of investment in organizational corporate services such as administrative services, finance, human resources, and system support improved hospitals’ financial performance. Among the IT systems used in hospital organizationsare the decision support systems that enhance the decision-making capabilities of both clinicians and administrative leaders. The Hospital Analytics Dashboard is introduced as an example of the use of such systems to allow leaders to analyzehospital’s performance as it relates to the impact of IT on patient satisfaction, clinical outcomes, and financial conditions. This proof-of-concept decision support tool can be adapted to include other performance measures, and has been devised to help hospital leadership teams visualize and analyze the relationships among performance measurespresented in a static scorecard format.It provides benchmarking information from similar-sized hospitals and is accompanied by an interactive dashboard where historical performance information can be analyzed to predict future performance according to different inputs.

Yes / The purpose of this paper is to study the effect of the implementation of Lean bundles on hospital performance in private hospitals in Jordan and evaluate how much the size of organization can affect the relationship between Lean bundles implementation and hospital performance. Design/methodology/approach The research is considered as quantitative method (descriptive and hypothesis testing). Three statistical techniques were adopted to analyse the data. Structural equation modeling techniques and multi-group analysis were used to examine the research’s hypothesis, and to perform the required statistical analysis of the data from the survey. Reliability analysis and confirmatory factor analysis were used to test the construct validity, reliability and measurement loadings that were performed. Findings Lean bundles have been identified as an effective approach that can dramatically improve the organizational performance of private hospitals in Jordan. Main Lean bundles – just in time, human resource management, and total quality management are applicable to large, small and medium hospitals without significant differences in advantages that depend on size. Originality/value According to the researchers’ best knowledge, this is the first research that studies the impact of Lean bundles implementation in healthcare sector in Jordan. This research also makes a significant contribution for decision makers in healthcare to increase their awareness of Lean bundles.

Submitted by Maicon Juliano Schmidt (maicons) on 2015-08-13T19:37:53Z No. of bitstreams: 1 Marcus Reusch.pdf: 2604830 bytes, checksum: a7d8af2b022aae968a9783f70ec12fb3 (MD5) / Made available in DSpace on 2015-08-13T19:37:53Z (GMT). No. of bitstreams: 1 Marcus Reusch.pdf: 2604830 bytes, checksum: a7d8af2b022aae968a9783f70ec12fb3 (MD5) Previous issue date: 2015-04-30 / Nenhuma / A dificuldade e os métodos para avaliar o desempenho das organizações de saúde representam um enorme desafio para os gestores hospitalares. O Diagnosis Related Groups (DRG) constitui-se em um completo sistema de classificação, que visa instrumentalizar a gestão hospitalar possibilitando a mensuração e avaliação de desempenho das instituições hospitalares. Foi proposta a utilização da metodologia DRG para avaliar o desempenho da casuística cirúrgica de uma unidade hospitalar. A fundamentação teórica enfatizou três temas: Histórico e evolução da classificação DRG, a classificação AP-DRG e a avaliação do desempenho e gestão hospitalar por DRG. O método utilizado consistiu em uma pesquisa tipo estudo de caso único com abordagem exploratória e descritiva de dados, de natureza quali-quantitativa. O campo do estudo foi um Hospital Geral de Grande Porte (HGGP). Os dados foram coletados a partir das informações contidas nos documentos de alta hospitalar de cada paciente submetido a procedimento cirúrgico, no período de um ano (Agosto de 2013 a Julho de 2014), foram após processados no Software Grouper, instrumento inicial da análise, dando origem a 213 DRGs cirúrgicos distintos. Foi desenvolvido o processo de implantação da metodologia DRG, identificados impactos na gestão dos serviços hospitalares com o uso do DRG, comparado o desempenho da casuística cirúrgica do HGGP com outras instituições hospitalares utilizando o DRG e foram identificadas oportunidades de melhoria em processos da assistência hospitalar no HGGP. Constatou-se que 16 DRGs corresponderam a 50% de toda casuística cirúrgica, e 44 DRGs (20% dos 213 DRGs cirúrgicos da amostra) representaram 80% de toda casuística cirúrgica da instituição. Para comparação de desempenho, foram utilizados dados publicados anualmente do Sistema de Saúde de Portugal. Dos 20 DRGs mais frequentes do HGGP, três apresentaram um desempenho inferior ao do grupo de Portugal. Nos outros 17 DRGs da amostra estudada, o desempenho foi superior, aferido em termos de tempo de permanência hospitalar. O objetivo geral proposto para o trabalho, da utilização do DRG para avaliar o desempenho da casuística cirúrgica da instituição foi alcançado. / The difficulty and the methods to evaluate the performance of health organizations represent a huge challenge for hospital managers. The Diagnosis Related Groups (DRG) is a complete classification system, which aims to equip the hospital management enabling the measurement and evaluation of hospitals performance. We propose the use of DRG methodology to evaluate the performance of the surgical cases within a hospital unit. The theoretical foundation emphasized three themes: History and evolution of the DRG classification, the AP-DRG classification and performance evaluation and hospital management by DRG. The method used consisted of case study research with qualitative and quantitative exploratory and descriptive approach of data. The field of study was a General Hospital with 386 beds. The data were collected from the information contained in the hospital discharge document of each patient that underwent surgery in the period of one year (August 2013 to July 2014), and processed in the Grouper Software, initial instrument of the analysis, originating 213 different surgical DRGs. It was found that 16 DRGs accounted for 50% of all surgical cases, and 44 DRGs (20% of 213 sample surgical DRGs) accounted for 80% of all surgical cases of the institution. For comparison, we used data published annually by the Health Care System of Portugal. Of the 20 most frequent DRGs of the General Hospital, three presented a performance lower than the group of Portugal. However the performance of the other 17 DRGs of the sample was higher considering the hospital length of stay. The general objective proposed for the study, using the DRG to evaluate the performance of the surgical cases of the institution was achieved, as well as the objectives of developing the process of implementation of the DRG methodology, identification of impacts in the management of hospital services with the use of DRG, the comparison of the surgical series of the General Hospital performance with other hospitals using DRG and identification of improvement opportunities in processes of hospital care.

The prolonged wars in Iraq and Afghanistan have taken a toll on the United States as a whole and the United States military in particular. The primary aim of this research is to determine what impact the wars in Iraq and Afghanistan have had on the performance of military hospitals over the fiscal years 2001-2006. Specifically, what direct effect has the war in Iraq and Afghanistan had on the productivity and quality of military hospitals, and, do productivity and quality trends differ based on hospital characteristics? Since observations over multiple time periods are nested within hospitals, multilevel mixed effects regression and Poisson regression models are used to evaluate changes in productivity and quality while accounting for differences within hospitals. Using a contingency theory framework, this study fills the gap in looking at the impact of war on permanent military hospitals’ productivity and quality using nationally developed and implemented quality indicators (Agency for Healthcare Quality and Research Inpatient Quality Indicators and Patient Safety Indicators). Structural characteristics of the hospital, teaching status and branch of Armed Service influenced productivity and certain quality indicators. The structural components were not able to reliably predict differences in productivity and all quality indicators, but overseas hospitals and non-teaching hospitals were most likely to differ from major teaching hospitals. The wars in Iraq and Afghanistan, denoted by the variables for wounded discharges and deployed staff, were only partially related to the productivity of military hospitals. Only an increase in the percentage of wounded discharges was related to productivity of military hospitals, and none were related to the quality indicators. In essence, the war affected the workload and productivity of military hospitals, but it did not affect the quality provided in the hospitals, as measured by AHRQ inpatient and patient safety quality indicators. Structural characteristics account for more of the variation in quality among military hospitals than the impact of war within the timeframe studied.

The recent reports by Institute of Medicine, `To Err is Human' and `Crossing Quality Chasm', revealed a large prevalence of medical errors and substandard care in US hospitals. Since then there has been a substantial increase in the efforts to measure and improve quality of care. The objective of this study was to compare the quality of care across hospitals using available performance indicators and examine the association between organizational factors and hospital performance. The main focus of this study was on important structural attributes of hospitals, namely - teaching status, location and market competition. The Nationwide Inpatient Sample for years 2003 and 2005, and the State Inpatient Database for years 2004 to 2006 were used for analyses. Two types of hospital performance indicators were examined to compare quality of care - Patient safety indicators developed by Agency for Healthcare Research and Quality, and process of care indicators developed by Centers for Medicare and Medicaid services. Multivariable regression analyses were performed using generalized estimating equations and random effects regression models. Several organizational factors as well as patient characteristics were included in the multivariable models as control variables. Overall, the results from this study showed an inconsistent relationship between teaching status, location of hospitals or market competition and quality of care in hospitals. In addition, the results demonstrated that isolating potential effects of hospital structure on outcomes requires controlling for the variation in patient characteristics, such as age and comorbidities, which increase patients' risk for incurring patient safety events. The findings from this study provide useful insight into the areas where the patient safety and quality initiatives should be focused. Moreover, the results identified the organizational factors that are relevant to certain types of hospitals and which should be considered before evaluating quality of care and enacting any policies about publicly reporting of performance or payment initiatives that are relevant to these hospitals.

The entrance space of a hospital has formed an effective period of hospital life since it has reflected the scope and the image of the entire facility. Therefore it has directly influenced by the new formation of healthcare facilities on preserving and growing role of the community health instead of threatening the illnesses. Since entrance space is apart from the other spaces in the facility that has shaped by the restrictive nature of the medical technology, the space most efficiently implement these new objectives more than any space of the entire facility. However, entrance spaces of hospitals in Turkey are still bothered with many insufficiencies and displayed a problematic panorama. Therefore, this thesis has obtained the problems of main entrance space, and has analyzed it with a consistent form of criteria to gather new solution proposals. In order to serve for this purpose, the present Turkish health care environment has explored and entrance space has been analyzed around new emerging concepts that reflect the changing ideals of the community. To present the problems and solution proposals about this specific place sufficiently, they are also evaluated through design and performance criteria. The essence of coping with the stress created by the environment with healing potential is emphasized. As a result, this thesis is expected to influence further researches, new hospital main entrance space designs as well as the renovation of older ones.

Risk-adjustment schemes are used to monitor hospital performance, on the assumption that excess mortality not explained by case mix is largely attributable to suboptimal care. We have developed a model to estimate the proportion of the variation in standardised mortality ratios (SMRs) that can be accounted for by variation in preventable mortality. The model was populated with values from the literature to estimate a predictive value of the SMR in this context-specifically the proportion of those hospitals with SMRs among the highest 2.5% that fall among the worst 2.5% for preventable mortality. The extent to which SMRs reflect preventable mortality rates is highly sensitive to the proportion of deaths that are preventable. If 6% of hospital deaths are preventable (as suggested by the literature), the predictive value of the SMR can be no greater than 9%. This value could rise to 30%, if 15% of deaths are preventable. The model offers a 'reality check' for case mix adjustment schemes designed to isolate the preventable component of any outcome rate.