Hospital Cost Efficiency Research Articles

ANALISIS PERHITUNGAN UNIT COST PADA TINDAKAN TONSILEKTOMI DENGAN METODE ACTIVITY BASED COSTING (STUDI KASUS DI RUMAH SAKIT PKU MUHAMMADIYAH YOGYAKARTA)

Background: Private hospitals should strive to have the technical capability to manage and calculate costs based on the condition that both hospitals and facilities that can use the Indonesian Case Based Group (INA CBG) appropriately. RS PKU Muhammadiyah Yogyakarta as one of the private hospitals that participate and support the government's program of the Sistem Jaminan Sosial Nasional.Calculating the unit cost of a tonsillectomy was done as a study of the correspondence between the cost of services and a health claim
 Methods:The study was a descriptive qualitative case study design. Tonsillectomy unit cost calculation using activity based costing (ABC) with the goal difference obtained unit costs plus a margin to claim CBG INA in 2012.
 Result: Based on the calculation, the unit cost of services tonsillectomy with activity-based costing method is Rp. 2.265.732. ABC unit cost calculations result in a greater cost than the claims of INA CBG so get the difference in cost of Rp. 785.034.
 Conclusions: There is a negative difference between the calculation of service bi tonsillectomy ABC method with INA CBG claim. So that needs to be done by the hospital cost efficiency.

Hospital cost efficiency: an examination of US acute care inpatient hospitals.

The use of stochastic frontier models for inference on hospital efficiency is complicated by the inability to fully control for quality differences across hospitals. Additionally, the potential existence of cross-sectional dependence due to the presence of unobserved common factors leads to endogeneity problems that can bias both cost function and efficiency estimates. Using a panel consisting of 1518 hospitals for the years 1996-2013 (T=18), I adopt techniques for dealing with long, cross-sectionally dependent panel data in order to estimate cost parameters and hospital specific efficiency. In particular, I employ the estimation technique proposed by Bai (Econometrica 77(4):1229-1279, 2009), which assumes that the unobservable heterogenous effects have a factor structure. I find evidence of considerable scale economies and that hospital cost inefficiencies have been increasing during the period of 1996-2013, and that the growth in expenditures is, in part, driven by spending that increases patient satisfaction, but that does not significantly contribute to improved patient health outcomes.

Influence of Non-financial Factors on Cost-efficiency of a General Hospital in Slovenia

Introduction: Hospitals account for the largest share of health care expenditures, which are mainly financed by public funds. In healthcare, it is of paramount importance that the management focus not on reducing costs at the expense of patient health, but on improving the value and thus the healthcare outcomes. In addition to the economic factors used to determine a hospital's cost efficiency, non-economic or soft factors should be considered. The aim of this study was to elucidate the influence of non-financial factors on a hospital's cost-efficiency.
 Method: An online survey was conducted among the staff of a typical Slovenian general hospital (N = 150).
 Results: Self-assessment of cost-efficiency was influenced by communication in the hospital, satisfaction and cooperation within the multidisciplinary team, willingness of employees to innovate, cooperation with external providers and evaluation of the quality of healthcare. Communication with the patient had the greatest impact, followed by communication with external providers and communication with the management.
 Conclusion: In order to reduce costs while maintaining or even improving the healthcare outcomes, communication with patients is extremely important.

An observational study of health care provider collaboration networks and heterogenous hospital cost efficiency and quality outcomes.

Provider network structure has been linked to hospital cost, utilization, and to a lesser degree quality, outcomes; however, it remains unknown whether these relationships are heterogeneous across different acute care hospital characteristics and US states. The objective of this study is to evaluate whether there are heterogeneous relationships between hospital provider network structure and hospital outcomes (cost efficiency and quality); and to assess the sources of measured heterogeneous effects. We use recent causal random forest techniques to estimate (hospital specific) heterogeneous treatment effects between hospitals’ provider network structures and their performance (across cost efficiency and quality). Using Medicare cost report, hospital quality and provider patient sharing data, we study a population of 3061 acute care hospitals in 2016. Our results show that provider networks are significantly associated with costs efficiency (P < .001 for 7/8 network measures), patient rating of their care (P < .1 in 5/8 network measures), heart failure readmissions (P < .01 for 3/8 network measures), and mortality rates (P < .02 in 5/8 cases). We find that fragmented provider structures are associated with higher costs efficiency and patient satisfaction, but also with higher heart failure readmission and mortality rates. These effects are further found to vary systematically with hospital characteristics such as capacity, case mix, ownership, and teaching status. This study used an observational design. In summary, we find that hospital treatment responses to different network structures vary systematically with hospital characteristics..

The importance of clinical risk assessment in reducing the pathway of acute coronary syndrome

Introduction: Early diagnosis of acute coronary syndrome is emergency providers' task. In the last decade, vast amounts of clinical risk stratification scores were developed to decrease the hospital load of patients by selecting them properly. Objective: Together with the diagnostic and therapeutic challenges, decreasing treatment duration is essential for the improvement of acute coronary syndrome prognosis. Our aim was to assess the HEART score's time-and therapy -related effects on acute coronary syndrome detection as a decision support system. Method: We conducted a retrospective, quantitative study at a county state emergency department amongst patients with the myocardial infarction ICD codes. We assessed their admission time, the way they were delivered to the hos-pital, their presenting symptoms, vital parameters, chronic medical conditions, laboratory and imaging results and the time of their admission to the percutan intervention center. We calculated the HEART score retrospectively from the collected data. Results: Our sample size consisted of 360 people. Coronary artery disease (80%) and hypertension (73.3%) were the most common risk factors, while chest pain (80%) and shortness of breath (48.6%) were the most common com-plaints. Coronary artery disease, hypertension and diabetes are not related to percutan coronary intervention admis-sion times (p = 0.110; p = 0.173; p = 0.507). We found a correlation between the presence of chest pain and mortal-ity (p = 0.009). The calculated HEART score had a correlation with the fact of coronary intervention admission (p = 0.005). Conclusion: We conclude that the retrospectively calculated HEART score correlates with percutan coronary inter-vention admission. Choosing the proper risk stratification can increase the lifespan of the patients and hospital cost-efficiency.

Integrating hepatitis B care and treatment with existing HIV services is possible: cost of integrated HIV and hepatitis B treatment in a low-resource setting: a cross-sectional hospital-based cost-minimisation assessment

BackgroundHepatitis B and HIV care share health system challenges in the implementation of primary prevention, screening, early linkage to care, monitoring of therapeutic success and long-term medication adherence.SettingArua regional referral...

Investigation of patients\u2019 access to EHR data via smart apps in Chinese Hospitals

BackgroundGiven that China has encouraged EHR usage in hospitals for more than a decade, patients’ access to their own EHR data is still not as widely utilized as expected.MethodsWe cultivated a survey with four categories and field interviews of measures to identify whether hospitals have already released EHR data to patients, inpatients or outpatients, the top EHR release contents and the most popular release software.ResultsOf the 1344 responding hospitals from 30 provinces nationwide, 41.37% of hospitals have already released their EHR data to patients, of which 97.12% are through smart apps. More than 91% of hospitals use WeChat, and 32.37% of hospitals developed their own standalone apps or use vendors’ apps. A total of 54.63% were released to both outpatients and inpatients, and the top release contents were all objective. A rough estimation is made that releasing EHR data to patients via smart apps may save the hospital 15.9 million RMB per year and patients 9.4 million RMB altogether.ConclusionsEHR data release is believed to bring both patient and hospital cost savings and efficiency gains but is still considered spontaneous and requires legal support and government regulation.

Service mix, market competition, and cost efficiency: A longitudinal study of U.S. hospitals

AbstractWe examine the longitudinal impact of service mix on cost efficiency in U.S. acute care general hospitals. We propose two different dimensions of service mix, with the first dimension capturing internal emphasis on specific service lines (i.e., specialization) and the second dimension reflecting the deviation of a hospital from the average level of specialization for hospitals in the same service area (i.e., differentiation). We hypothesize that as the level of a hospital's specialization increases, hospital cost efficiency should improve at a decreasing rate. We also hypothesize that differentiation helps improve cost efficiency in competitive markets. Lastly, we examine whether acute care general hospitals can use service mix as an operational lever to improve cost efficiency when specialty hospitals are present in the same local markets. We find strong empirical support for the hypothesized relationships.

Hospital Competition in the National Health Service: Evidence from a Patient Choice Reform

We study the impact of exposing hospitals in a National Health Service (NHS) to non-price competition by exploiting a patient choice reform in Norway in 2001. The reform facilitates a difference-in-difference research design due to geographical variation in the scope for competition. Using rich administrative data covering the universe of NHS hospital admissions from 1998 to 2005, we find that hospitals in more competitive areas have a sharper reduction in AMI mortality, readmissions, and length of stay than hospitals in less competitive areas. These results indicate that competition improves patient health outcomes and hospital cost efficiency, even in the Norwegian NHS with large distances, low fixed treatment prices, and mainly public hospitals.

Implementing new models of integrated mental health care: what impacts effective performance?

Introduction: In the Metro South geographical area in South East Queensland, the Logan Beaudesert Wellbeing Program was developed with the goal of implementing interdisciplinary approaches within a multidisciplinary team to increase wellbeing of people who experience mental illness alongside the overarching goal of building a healthier community. This study reports on the implementation process and highlights how existing structures within health systems impact how staff are able to engage with new models of care that aim to re-orient care. Theory / Methods: Data collection and analysis was guided by Normalisation Process Theory; a mid-range theory concerned with integration and embedding of practices in existing systems, which posits that to become normalised, new practices must ‘fit’ well within the existing patterns of the workforce, the organisation and the prevailing methods of delivering care. All staff employed to implement the model of care were invited to participate in a face-to-face semi-structured interview prior to and six months post implementation of the model of care. Interviews were digitally recorded and transcribed verbatim. Two researchers then thematically analysed the data using techniques of initial coding, categorisation and constant comparison until the most salient themes were identified and all data were taken into account. Results: Twenty-four staff participated in the initial interviews and twenty-one participated in the post-implementation interviews. Sixteen participants participated in both interviews. Staff were passionate and enthusiastic about the model of care and had high expectations of its capacity to facilitate quality health and wellbeing outcomes. As implementation progressed, there was an increasing pressure to perform and to meet pre-defined cost effectiveness measures. Existing structures impacted performance – especially resource, governance and leadership structures as well as historical and segregated ways of working. Discussion: Fuelled by enthusiasm from key decision makers and stakeholders, participants had huge expectations of the model of care; viewing it as a real option to improve mental health and wellbeing outcomes in the community. However, greater focus upon meeting key performance indicators such as hard hospital utilisation and cost-efficiency, which were not synonymous with person-centred care, compromised participants’ fidelity to the model, hence making consumers susceptible to being affected. In addition, because leadership and governance boundaries were unclear, unrest and confusion occurred. Conclusion: Although participants passionately endorsed the new model of care, pre-existing structures impacted the way that the program was implemented. Thus, when new teams are employed to deliver new models of care, they need to establish ways of working together, understand and negotiate their place within the health-culture landscape, and broker support from numerous stakeholder groups and individuals. Lessons Learned: When evidence-based and aspirational models of person-centred care are implemented, organising structures such as cost, time, resources, and established lines of governance and accountability are powerful forces that need to be factored into outcome measures. Limitations: Generalisability of the findings from this project is limited because of the nuances of the context in which the LBWP was implemented. Future Research: Future research regarding ways of adopting person-centred practice within existing teams and existing cultures is required.

Case mix–adjusted cost of colectomy at low-, middle-, and high-volume academic centers

Efforts to regionalize surgery based on thresholds in procedure volume may have consequences on the cost of health care delivery. This study aims to delineate the relationship between hospital volume, case mix, and variability in the cost of operative intervention using colectomy as the model. All patients undergoing colectomy (n=90,583) at 183 academic hospitals from 2009-2012 in The University HealthSystems Consortium Database were studied. Patient and procedure details were used to generate a case mix-adjusted predictive model of total direct costs. Observed to expected costs for each center were evaluated between centers based on overall procedure volume. Patient and procedure characteristics were significantly different between volume tertiles. Observed costs at high-volume centers were less than at middle- and low-volume centers. According to our predictive model, high-volume centers cared for a less expensive case mix than middle- and low-volume centers ($12,786 vs $13,236 and $14,497, P<.01). Our predictive model accounted for 44% of the variation in costs. Overall efficiency (standardized observed to expected costs) was greatest at high-volume centers compared to middle- and low-volume tertiles (z score -0.16 vs 0.02 and -0.07, P<.01). Hospital costs and cost efficiency after an elective colectomy varies significantly between centers and may be attributed partially to the patient differences at those centers. These data demonstrate that a significant proportion of the cost variation is due to a distinct case mix at low-volume centers, which may lead to perceived poor performance at these centers.

Efficiency and hospital effectiveness in improving Hospital Consumer Assessment of Healthcare Providers and Systems ratings.

Efficiency has emerged as a central goal to the operations of health care organizations. There are two competing perspectives on the relationship between efficiency and organizational performance. Some argue that organizational slack is a waste and that efficiency contributes to organizational performance, whereas others maintain that slack acts as a buffer, allowing organizations to adapt to environmental demands and contributing to organizational performance. As value-based purchasing becomes more prevalent, health care organizations are incented to become more efficient and, at the same time, improve their patients' experiences and outcomes. Unused slack resources might facilitate the timely implementation of these improvements. Building on previous research on organizational slack and inertia, we test whether efficiency and other organizational factors predict organizational effectiveness in improving Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) ratings. We rely on data from the American Hospital Association and HCAHPS. We estimate hospital cost-efficiency by Stochastic Frontier Analysis and use regression analysis to determine whether efficiency, competition, hospital size, and other organizational factors are significant predictors of hospital effectiveness. Our findings indicate that efficiency and hospital size have a significant negative association with organizational ability to improve HCAHPS ratings. Although achieving organizational efficiency is necessary for health care organizations, given the changes that are currently occurring in the U.S. health care system, it is important for health care managers to maintain a certain level of slack to respond to environmental demands and have the resources needed to improve their performance.

Measuring Patient Satisfaction's Relationship to Hospital Cost Efficiency: Can Administrators Make a Difference?

The aim of this study was to assess the ability and means by which hospital administrators can influence patient satisfaction and its impact on costs. Data are drawn from the American Hospital Association's Annual Survey of Hospitals, federally collected Hospital Cost Reports, and Medicare's Hospital Compare. Stochastic frontier analyses (SFA) are used to test the hypothesis that the patient satisfaction-hospital cost relationship is primarily a latent "management effect." The null hypothesis is that patient satisfaction measures are main effects under the control of care providers rather than administrators. Both SFA models were superior to the standard regression analysis when measuring patient satisfaction's relationship to hospitals' cost efficiency. The SFA model with patient satisfaction measures treated as main effects, rather than "latent, management effects," was significantly better comparing the log-likelihood statistics. Higher patient satisfaction scores on the environmental quality and provider communication dimensions were related to lower facility costs. Higher facility costs were positively associated with patients' overall impressions (willingness to recommend and overall satisfaction), assessments of medication and discharge instructions, and ratings of caregiver responsiveness (pain control and help when called). In the short term, managers have a limited ability to influence patient satisfaction scores, and it appears that working through frontline providers (doctors and nurses) is critical to success. In addition, results indicate that not all patient satisfaction gains are cost neutral and there may be added costs to some forms of quality. Therefore, quality is not costless as is often argued.

Cost inefficiency under financial strain: a stochastic frontier analysis of hospitals in Washington State through the Great Recession.

The importance of increasing cost efficiency for community hospitals in the United States has been underscored by the Great Recession and the ever-changing health care reimbursement environment. Previous studies have shown mixed evidence with regards to the relationship between linking hospitals' reimbursement to quality of care and cost efficiency. Moreover, current evidence suggests that not only inherently financially disadvantaged hospitals (e.g., safety-net providers), but also more financially stable providers, experienced declines to their financial viability throughout the recession. However, little is known about how hospital cost efficiency fared throughout the Great Recession. This study contributes to the literature by using stochastic frontier analysis to analyze cost inefficiency of Washington State hospitals between 2005 and 2012, with controls for patient burden of illness, hospital process of care quality, and hospital outcome quality. The quality measures included in this study function as central measures for the determination of recently implemented pay-for-performance programs. The average estimated level of hospital cost inefficiency before the Great Recession (10.4%) was lower than it was during the Great Recession (13.5%) and in its aftermath (14.1%). Further, the estimated coefficients for summary process of care quality indexes for three health conditions (acute myocardial infarction, pneumonia, and heart failure) suggest that higher quality scores are associated with increased cost inefficiency.

Complementary effect of patient volume and quality of care on hospital cost efficiency.

This study explores the direct effect of an increase in patient volume in a hospital and the complementary effect of quality of care on the cost efficiency of U.S. hospitals in terms of patient volume. The simultaneous equation model with three-stage least squares is used to measure the direct effect of patient volume and the complementary effect of quality of care and volume. Cost efficiency is measured with a data envelopment analysis method. Patient volume has a U-shaped relationship with hospital cost efficiency and an inverted U-shaped relationship with quality of care. Quality of care functions as a moderator for the relationship between patient volume and efficiency. This paper addresses the economically important question of the relationship of volume with quality of care and hospital cost efficiency. The three-stage least square simultaneous equation model captures the simultaneous effects of patient volume on hospital quality of care and cost efficiency.

A nursing care classification system for assessing workload and determining optimal nurse staffing in a teaching hospital in China: A pre-post intervention study.

We aimed to evaluate the effectiveness of a nursing care classification system for re-assessing nurse workload and determining staffing needs. Adequate bed-nurse ratios help manage hospital cost-efficiency, quality of care and patient safety. A prospective pre-post intervention study was conducted from January 2010 to December 2012 in 16 medical-surgical units of a tertiary teaching hospital. Nursing tasks were classified into four grades of care reflecting actual workload. Units were re-staffed accordingly and bed-nurse ratios compared with government-authorized bed-nurse ratios. Patient satisfaction, hospital stays and mortality were evaluated pre- and poststaffing changes. Average bed-nurse ratio (1:0.41) exceeded the national standard (1:0.40) in 16 units, but was inadequate in five units. Re-staffing increased average bed-nurse ratio from 1:0.41 to 1:0.48. Patients' satisfaction increased from 96.9% to 97.6%, and hospital stays decreased significantly. Nursing care classification effectively distributes nurse staffing to match patients' care levels, improving patient outcomes.

International hospital productivity comparison: Experiences from the Nordic countries

This article focuses on describing the methodological challenges intrinsic in international comparative studies of hospital productivity and how these challenges have been addressed within the context of hospital comparisons in the Nordic countries. The hospital sectors in the Nordic countries are suitable for international comparison as they exhibit similar structures in the organisation for hospital care, hold administrative data of good quality at the hospital level, apply a similar secondary patient classification system, and use similar definitions of operating costs. The results of a number of studies have suggested marked differences in hospital cost efficiency and hospital productivity across the Nordic countries and the Finnish hospitals have the highest estimates in all the analyses. Explanatory factors that were tested and seemed to be of limited importance included institutional, structural and technical. A factor that is yet to be included in the Nordic hospital productivity comparison is the quality of care. Patient-level data available from linkable national registers in each country enable the development of quality indicators and will be included in the forthcoming hospital productivity studies within the context of the EuroHOPE (European health care outcomes, performance and efficiency) project.

Making incentives work: Hospital organisation and performance

In 1997, financing of Norwegian hospitals was changed to a combination of block grants and activity-based reimbursements. Since then, many hospitals have also reorganised their internal structures, for instance by implementing activity-based budgets at the departmental level. The purpose of this study is to investigate the impact of departmental activity-based budgets on overall hospital productivity and unit costs. The analysis is based on register data on hospital admissions and hospital input factors, along with survey data on internal organisation of hospitals. Fixed-effects regression models are applied for the analysis. The main results indicate that hospitals with departmental activity-based budgets and department authority have higher productivity. The effect on unit costs is insignificant. The positive effect of the departmental activity-based budgets and departmental authority on productivity without increase in costs may indicate that providing incentives at lower hospital levels such as departments could be a useful tool for increasing overall hospital productivity and cost efficiency.

The impacts of hospital alliance membership, alliance size, and repealing certificate of need regulation, on the cost efficiency of non-profit hospitals

This paper investigates how alliance membership, size of the alliance, membership in multiple organizations, repealing certificate of need (CON) regulation for acute care facilities, and other factors, impacts hospital cost efficiency. Using a 1996–1999 panel of 144 urban US Midwestern hospitals, empirical results show that repealing state CON programs, signing more HMO and PPO contracts, and membership in only an alliance, helped to enhance cost efficiency. Membership in an additional organization (network, system) did not help enhance hospital cost efficiency. Membership in a larger size alliance (more hospitals in the alliance) contributed to an improvement in cost efficiency. Copyright © 2010 John Wiley & Sons, Ltd.

Cost efficiency of university hospitals in the Nordic countries: a cross-country analysis

This paper estimates cost efficiency scores using the bootstrap bias-corrected procedure, including variables for teaching and research, for the performance of university hospitals in the Nordic countries. Previous research has shown that hospital provision of research and education interferes with patient care routines and inflates the costs of health care services, turning university hospitals into outliers in comparative productivity and efficiency analyses. The organisation of patient care, medical education and clinical research as well as available data at the university hospital level are highly similar in the Nordic countries, creating a data set of comparable decision-making units suitable for a cross-country cost efficiency analysis. The results demonstrate significant differences in university hospital cost efficiency when variables for teaching and research are entered into the analysis, both between and within the Nordic countries. The results of a second-stage analysis show that the most important explanatory variables are geographical location of the hospital and the share of discharges with a high case weight. However, a substantial amount of the variation in cost efficiency at the university hospital level remains unexplained.