Efficiency of U.S. dialysis centers: an updated examination of facility characteristics that influence production of dialysis treatments

Efficiency and management factors: finding the balance in Thalassaemia care centres

BACKGROUND

Optimizing efficiency has become increasingly critical with the growing demand for finite healthcare resources driven by population growth and an ageing society. Hence, policymakers are urgently finding more efficient ways to deliver health services. Thalassemia is a complex inherited blood disorder with significant prevalence in Malaysia. The high number of patients put substantial strain on the healthcare system. This study aims to evaluate the technical efficiency of thalassaemia care centres throughout Malaysia and the determinants that affect the efficiency.

METHOD

Data from 30 public hospitals with thalassaemia care centres were collected. A double bootstrap data envelopment analysis (DEA) approach is used with the assumption of input-oriented and variable-to-scale DEA models to generate technical efficiency scores. Bootstrap truncated regression was later conducted to identify the factors affecting the efficiency scores.

RESULTS

The mean bias-corrected technical efficiency score has improved to 0.75 in 2017 from 0.71 in 2016. In both years, more than 50% of thalassaemia care centres showed good efficiency scores (0.8-1.0). Management factors that affect the efficiency scores include separation of patient management (β = 0.0653) and budget (β = 0.0843), where they are found to positively affect the efficiency scores. In contrast, having longer operating hours is found to inversely influence the performance levels (β = - 0.4023).

CONCLUSIONS

The study provides a pioneering framework to evaluate the technical efficiency of thalassaemia treatment centres in public healthcare settings and could provide a useful guide for policymaker and thalassaemia care centre managers to improve efficiency in service delivery to thalassaemia patients and their caregivers without compromising quality of care.

Performance of Accountable Care Organizations: Health Information Technology and Quality–Efficiency Trade-Offs

Under a traditional fee-for-service payment model, healthcare providers typically compromise the quality of care in order to reduce costs. Drawing on data from a national sample of accountable care organizations (ACOs), we study whether financial incentives offered under the Affordable Care Act led to fundamental changes in care delivery. Our research suggests that effective use of health information technology (IT) by ACO providers is critical in balancing competing goals of quality and efficiency. Unlike hospitals that did not participate in value-based care initiatives, ACOs were able to generate better quality outcomes while also improving overall efficiency. Furthermore, ACO providers that used health IT effectively demonstrated better patient health outcomes due to greater information integration with other providers. In other words, ACOs created value by not only reducing the cost of care but also improving patient outcomes simultaneously. Our research provides a roadmap for practitioners to succeed in a value-based healthcare environment and for policy makers to design better incentives to promote interorganizational information sharing across providers. Our findings suggest that healthcare policy needs to incorporate appropriate incentives to foster effective IT use for care coordination between healthcare providers.

Consolidation in dialysis Markets-Causes, consequences, and the role of policy

The dialysis industry is one of the most highly concentrated healthcare sectors in the United States. Despite decades of growth in the number of patients with end-stage renal disease and in the size of dialysis markets, two large dialysis organizations currently care for more than two-thirds of the dialysis population. Economies of scale, bargaining leverage with suppliers and private insurers, barriers to entry, and government regulations have contributed to highly concentrated dialysis markets by conferring advantages to larger organizations. Consolidated dialysis markets have coincided with both positive and negative trends in healthcare costs and outcomes. Costs per patient receiving dialysis have grown at a slower rate than per capita Medicare costs, while access to dialysis care remains available across a wide socioeconomic range. Mortality rates have declined despite a sicker dialysis patient population. Yet, concerns remain about the cost and quality of dialysis care. Evidence suggests that chain ownership, for profit status, and less market competition may negatively impact health outcomes. Future policies and innovations involving kidney health may temporarily disrupt consolidation. However, if the underlying mechanisms that contributed to past consolidation persist, dialysis markets may remain highly concentrated over the long term.

Efficiency Measurement in Health Facilities: A Systematic Review in Low- and Middle-Income Countries

BACKGROUND

Limited healthcare resources in low- and middle-income countries (LMICs) have led policy-makers to improve healthcare efficiency. Therefore, it is essential to understand how efficiency has been measured in the LMIC setting.

OBJECTIVE

This paper reviews methodologies used for efficiency studies in health facilities in LMICs.

METHODS

We searched MEDLINE, Embase, Global Health, EconLit and ProQuest Dissertations and Theses databases to Week 6 in 2018. We included all types of quantitative analysis studies relating to the measurement of the efficiency of services at health facilities in LMICs. We extracted data from eligible studies, and assessed the validity for each study. Because of the substantial heterogeneity of the studies, results were presented narratively.

RESULTS

A total of 137 papers were eligible for inclusion. These articles covered a wide range of health facility types, with more than half of the studies relating to hospitals. Our systematic review showed that there is an increasing trend in efficiency measurements in LMICs using various methods. Most studies employed data envelopment analysis as an efficiency measurement method. The studies typically included physical inputs and health services as outputs. Sixty-one percent of the studies analysed the contextual variables of the health facility efficiency.

CONCLUSION

This review highlights the potential for methodological improvement and policy impacts in efficiency measurements.

Impact of Medicare Advantage penetration and hospital competition on technical efficiency of nursing care in US intensive care units

This study aimed to evaluate technical efficiency of US intensive care units and determine the effects of environmental factors on technical efficiency in providing quality of nursing care. Data were obtained from the 2014 National Database of Nursing Quality Indicators and the Centers for Medicare and Medicaid Services. Data envelopment analysis was used to estimate technical efficiency for each intensive care unit. Multilevel modeling was used to determine the effects of environmental factors on technical efficiency. Overall, Medicare Advantage penetration and hospital competition in a market did not create pressure for intensive care units to become more efficient by reducing their inputs. However, these 2 environmental factors showed positive influences on technical efficiency in intensive care units with certain levels of technical efficiency. The implications of the study results for management strategies and health policy may vary according to the levels of technical efficiency in intensive care units. Further studies are needed to examine why and how intensive care units with particular levels of technical efficiency are differently affected by certain environmental factors.

Evaluating Technical Efficiency of Nursing Care Using Data Envelopment Analysis and Multilevel Modeling

Data envelopment analysis (DEA) is an advantageous non-parametric technique for evaluating relative efficiency of performance. This article describes use of DEA to estimate technical efficiency of nursing care and demonstrates the benefits of using multilevel modeling to identify characteristics of efficient facilities in the second stage of analysis. Data were drawn from LTCFocUS.org , a secondary database including nursing home data from the Online Survey Certification and Reporting System and Minimum Data Set. In this example, 2,267 non-hospital-based nursing homes were evaluated. Use of DEA with nurse staffing levels as inputs and quality of care as outputs allowed estimation of the relative technical efficiency of nursing care in these facilities. In the second stage, multilevel modeling was applied to identify organizational factors contributing to technical efficiency. Use of multilevel modeling avoided biased estimation of findings for nested data and provided comprehensive information on differences in technical efficiency among counties and states.

Efficiency of the implementation of cardiovascular risk management in primary care practices: an observational study

Background

This study aimed to document the variation in technical efficiency of primary care (PC) practices in delivering evidence-based cardiovascular risk management (CVRM) and to identify associated factors.

Methods

This observational study was based on the follow-up measurements in a cluster randomized trial. Patients were recruited from 41 general practices in the Netherlands, involving 106 GPs and 1671 patients. Data on clinical performance were collected from patient records. The analysis focused on PC practices and used a two-stage data envelopment analysis (DEA) approach. Bias-corrected DEA technical efficiency scores for each PC practice were generated, followed by regression analysis with practice efficiency as outcomes and organizational features of general practice as predictors.

Results

Not all PC practices delivered recommended CVRM with the same technical efficiency; a significant difference from the efficient frontier was found (p < .000; 95 % CI 1.018–1.041). The variation in technical efficiency between PC practices was associated with training practice status (p = .026). Whether CVRM clinical tasks were performed by a practice nurse or a GP did not influence technical efficiency in a statistical significant way neither did practice size.

Conclusions

Technical efficiency in delivering evidence-based CVRM increased with having a training practice status. Nurse involvement and practice size showed no statistical impact.

Improving the effectiveness of service delivery in the public healthcare sector: the case of ophthalmology services in Malaysia

Background

Rising demand of ophthalmology care is increasingly straining Malaysia’s public healthcare sector due to its limited human and financial resources. Improving the effectiveness of ophthalmology service delivery can promote national policy goals of population health improvement and system sustainability. This study examined the performance variation of public ophthalmology service in Malaysia, estimated the potential output gain and investigated several factors that might explain the differential performance.

Methods

Data for 2011 and 2012 on 36 ophthalmology centres operating in the Ministry of Health hospitals were used in this analysis. We first consulted a panel of ophthalmology service managers to understand the production of ophthalmology services and to verify the production model. We then assessed the relative performance of these centres using Data Envelopment Analysis (DEA). Efficiency scores (ES) were decomposed into technical, scale, and congestion component. Potential increase in service output was estimated. Sensitivity analysis of model changes was performed and stability of the result was assessed using bootstrap approach. Second stage Tobit regression was conducted to determine if hospital type, availability of day services and population characteristics were related to the DEA scores.

Results

In 2011, 33 % of the ophthalmology centres were found to have ES > 1 (mean ES = 1.10). Potential output gains were 10 % (SE ± 2.92), 7.4 % (SE ± 2.06), 6.9 % (SE ± 1.97) if the centres could overcome their technical, scale and congestion inefficiencies. More centres moved to the performance frontier in 2012 (mean ES = 1.07), with lower potential output gain. The model used has good stability. Robustness checks show that the DEA correctly identified low performing centres. Being in state hospital was significantly associated with better performance.

Conclusions

Using DEA to benchmarking service performance of ophthalmology care could provide insights for policy makers and service managers to intuitively visualise the overall performance of resource use in an otherwise difficult to assess scenario. The considerable potential output gain estimated indicates that effort should be invested to understand what drove the performance variation and optimise them. Similar performance assessment should be undertaken for other healthcare services in the country in order to work towards a sustainable health system.

Electronic supplementary material

The online version of this article (doi:10.1186/s12913-015-1011-0) contains supplementary material, which is available to authorized users.