The Linkage Between Hospitals and Nursing Homes: Alternative Approaches to Minimizing Transaction Costs

Finding more efficient ways to organize and deliver medical care is a major policy and management concern in the United States. High levels of expenditures for administrative and coordinating functions are attributed to the fact that health care systems are not seamless and that excessive transaction or friction costs are incurred in the exchanges between providers and purchasers and among providers. Renewed interest in vertical integration as a means to addressed these problems is being explored in the empirical literature, but rigorous theory-based investigations are rare. This study is a theory-based exploration of how hospitals address the make-or-buy decision of acquiring nursing home services for patients requiring post-acute stay placement. The purpose of the study is to investigate under what circumstances hospitals chose to undertake formal arrangements to acquire nursing home services for patients to be discharged, rather than simply arranging for each discharge in the spot market. In some instances this may be long-term contracting or leasing of beds, while in other instances it may mean the hospital acquires or develops its own skill nursing facility--a form of vertical integration. The study adopts Oliver Williamson\u27s transaction cost economics theory as the theoretical basis for the study. This framework argues that the most efficient mode of transacting is determined by analyzing three dimensions of the transaction: uncertainty, frequency, and asset specificity (supplier identity). At higher levels of each of these dimensions, organizations are more likely to observe that markets fail and that formal arrangements between buyers and sellers are preferable, with vertical integration representing the make versus buy option. The study uses data from the American Hospital Association Survey and other sources to identify if and how hospitals have made formal arrangements for nursing home services. It tests ten hypotheses derived from the theory that focus on the three dimensions of transactions and interactions among them. The methodology uses several analytical approaches to establish the validity of the measures of the dimensions, and then tests the hypotheses using multivariate logistic regression to contrast various modes of transaction. The importance of transaction uncertainty and specificity are strongly supported in the findings, while transaction frequency is weakly correlated to higher degrees of integration. The results are consistent with both the theoretical arguments advanced by transaction cost economics and with prior research, which is only available from non-health care applications. The study makes an important, and perhaps unique, contribution to empirically operationalizing and testing a transaction cost economics-based interpretation of the decision to vertically integrate in health care. It also provides useful insight into the need for vertical integration to be selectively adopted as it may not be the most efficient mode of organization in all make or buy decision opportunities

Disease Burden of Chronic Kidney Disease Due to Hypertension From 1990 to 2019: A Global Analysis

Background: Although it is widely known that hypertension is an important cause of chronic kidney disease (CKD), little detailed quantitative research exists on the burden of CKD due to hypertension.Objective: The objective of the study is to estimate the global disease burden of CKD due to hypertension and to evaluate the association between the socioeconomic factors and country-level disease burden of CKD due to hypertension.Methods: We extracted the disability-adjusted life-year (DALY) numbers, rates, and age-standardized rates of CKD due to hypertension from the Global Burden of Disease Study 2019 database to investigate the time trends of the burden of CKD due to hypertension from 1990 to 2019. Stepwise multiple linear regression analysis was performed to evaluate the correlations between the age-standardized DALY rate and socioeconomic factors and other related factors obtained from open databases.Results: Globally, from 1990 to 2019, DALY numbers caused by CKD due to hypertension increased by 125.2% [95% confidential interval (CI), 124.6 to 125.7%]. The DALY rate increased by 55.7% (55.3 to 56.0%) to 128.8 (110.9 to 149.2) per 100,000 population, while the age-standardized DALYs per 100,000 population increased by 10.9% (10.3 to 11.5%). In general, males and elderly people tended to have a higher disease burden. The distribution disparity in the burden of CKD due to hypertension varies greatly among countries. In the stepwise multiple linear regression model, inequality-adjusted human development index (IHDI) [β = −161.1 (95% CI −238.1 to −84.2), P < 0.001] and number of physicians per 10,000 people [β = −2.91 (95% CI −4.02 to −1.80), P < 0.001] were significantly negatively correlated with age-standardized DALY rate when adjusted for IHDI, health access and quality (HAQ), number of physicians per 10,000 people, and population with at least some secondary education.Conclusion: Improving the average achievements and equality of distribution in health, education, and income, as well as increasing the number of physicians per 10,000 people could help to reduce the burden of CKD due to hypertension. These findings may provide relevant information toward efforts to optimize health policies aimed at reducing the burden of CKD due to hypertension

Exploring human resource management in the top five global hospitals: a comparative study

BackgroundThe pivotal role of Human Resource Management (HRM) in hospital administration has been acknowledged in research, yet the examination of HRM practices in the world’s premier hospitals has been scant.ObjectiveThis study explored how the world’s leading hospitals attain operational efficiency by optimizing human resource allocation and melding development strategies into their HRM frameworks. A comparative analysis of the HRM frameworks in the top five global hospitals was undertaken to offer a reference model for other hospitals.MethodsThis research offers a comparative exploration of the HRM frameworks utilized by the top five hospitals globally, underscoring both shared and distinct elements. Using a multi-case study methodology, the research scrutinized each hospital’s HRM framework across six modules, drawing literature from publicly accessible sources, including websites, annual reports, and pertinent English-language scholarly literature from platforms such as Google Scholar, PubMed, Medline, and Web of Science.ResultsThe analyzed hospitals exhibited inconsistent HRM frameworks, yet all manifested potent organizational cultural attributes and maintained robust employee training and welfare policies. The design of the HR systems was strategically aligned with the hospitals’ objectives, and the study established that maintaining a sustainable talent system is pivotal to achieving hospital excellence.ConclusionThe HRM frameworks of the five analyzed hospitals align with their developmental strategies and exhibit unique organizational cultural attributes. All five hospitals heavily prioritize aligning employee development with overall hospital growth and place a spotlight on fostering a healthy working environment and nurturing employees’ sense of achievement. While compensation is a notable performance influencer, it is not rigorously tied to workload in these hospitals, with employees receiving mid-to-upper industry-range compensation. Performance assessment criteria focus on job quality and aligning employee actions with organizational values. Comprehensive welfare and protection are afforded to employees across all five hospitals

Evaluating the implementation of EMR systems from the perspective of health professionals

In health informatics, the updated DeLone and McLean IS success model is reviewed as a mature model in measuring health information system (HIS) success. This research provided an evaluation model to estimate the implementation of electronic medical records (EMR) systems from a health professional perspective by combined the updated DeLone and McLean IS success model, data quality management model, and EMR systems safety attributes. Based on evidence-based management (EBM), this research could be regarded as an empirical example for further EMR systems research since it not only provided a model to measure the Taiwanese EMR systems in two hospitals by implementing a structure instrument and structure equation modeling (SEM) of quantitative methods, but also introduced how to identify the possible effects in such evaluation research

Mortality Predicted Accuracy for Hepatocellular Carcinoma Patients with Hepatic Resection Using Artificial Neural Network

The aim of this present study is firstly to compare significant predictors of mortality for hepatocellular carcinoma (HCC) patients undergoing resection between artificial neural network (ANN) and logistic regression (LR) models and secondly to evaluate the predictive accuracy of ANN and LR in different survival year estimation models. We constructed a prognostic model for 434 patients with 21 potential input variables by Cox regression model. Model performance was measured by numbers of significant predictors and predictive accuracy. The results indicated that ANN had double to triple numbers of significant predictors at 1-, 3-, and 5-year survival models as compared with LR models. Scores of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) of 1-, 3-, and 5-year survival estimation models using ANN were superior to those of LR in all the training sets and most of the validation sets. The study demonstrated that ANN not only had a great number of predictors of mortality variables but also provided accurate prediction, as compared with conventional methods. It is suggested that physicians consider using data mining methods as supplemental tools for clinical decision-making and prognostic evaluation

Disease-Free Survival after Hepatic Resection in Hepatocellular Carcinoma Patients: A Prediction Approach Using Artificial Neural Network

Background: A database for hepatocellular carcinoma (HCC) patients who had received hepatic resection was used to develop prediction models for 1-, 3- and 5-year disease-free survival based on a set of clinical parameters for this patient group. Methods: The three prediction models included an artificial neural network (ANN) model, a logistic regression (LR) model, and a decision tree (DT) model. Data for 427, 354 and 297 HCC patients with histories of 1-, 3- and 5-year disease-free survival after hepatic resection, respectively, were extracted from the HCC patient database. From each of the three groups, 80 % of the cases (342, 283 and 238 cases of 1-, 3- and 5-year disease-free survival, respectively) were selected to provide training data for the prediction models. The remaining 20 % of cases in each group (85, 71 and 59 cases in the three respective groups) were assigned to validation groups for performance comparisons of the three models. Area under receiver operating characteristics curve (AUROC) was used as the performance index for evaluating the three models. Conclusions: The ANN model outperformed the LR and DT models in terms of prediction accuracy. This study demonstrated the feasibility of using ANNs in medical decision support systems for predicting disease-free survival based on clinical databases in HCC patients who have received hepatic resection

Socio-demographic and health-related factors associated with cognitive impairment in the elderly in Taiwan

<p>Abstract</p> <p>Background</p> <p>Cognitive impairment is an age-related condition as the rate of cognitive decline rapidly increases with aging. It is especially important to better understand factors involving in cognitive decline for the countries where the older population is growing rapidly. The aim of this study was to examine the association between socio-demographic and health-related factors and cognitive impairment in the elderly in Taiwan.</p> <p>Methods</p> <p>We analysed data from 2119 persons aged 65 years and over who participated in the 2005 National Health Interview Survey. Cognitive impairment was defined as having the score of the Mini Mental State Examination lower than 24. The χ²test and multiple logistic regression models were used to evaluate the association between cognitive impairment and variables of socio-demography, chronic diseases, geriatric conditions, lifestyle, and dietary factors.</p> <p>Results</p> <p>The prevalence of cognitive impairment was 22.2%. Results of multivariate analysis indicated that low education, being single, low social support, lower lipid level, history of stroke, physical inactivity, non-coffee drinking and poor physical function were associated with a higher risk of cognitive impairment.</p> <p>Conclusion</p> <p>Most of the characteristics in relation to cognitive impairment identified in our analysis are potentially modifiable. These results suggest that improving lifestyle behaviours such as regular exercise and increased social participation could help prevent or decrease the risk of cognitive impairment. Further investigations using longitudinal data are needed to clarify our findings.</p

The development of Taiwanese electronic medical record systems evaluation instrument

This study used Item Analysis, Exploratory Factor Analysis (EFA) and Reliability Analysis (Cronbach’s α value) to exam the Questions which selected by the Delphi method based on the issue of “Socio-technical system (STS)” and user-centered perspective. A structure questionnaire with seventy-four questions which could be categorized into nine dimensions (healthcare environment, organization behaviour, system quality, medical data quality, service quality, safety quality, user usage, user satisfaction, and organization net benefits) was provided to evaluate EMR of the Taiwanese healthcare environment