Improving productive efficiency in hospitals: findings from a review of the international evidence

A Scheduling Optimization Approach to Reduce Outpatient Waiting Times for Specialists

BACKGROUND/OBJECTIVES

Long waiting times for outpatient care remain a global challenge for public health systems. In Portugal, the National Health Service (NHS) ensures universal access to medical treatment, aiming to promote equity in healthcare. However, persistent delays in outpatient speciality appointments hinder this objective.

METHODS

This study proposes a prioritization-scheduling approach that integrates a mathematical model with a heuristic method to enhance accessibility in NHS hospitals. By optimizing the available capacity of hospitals within each geographic area, the model efficiently sequences patient appointments across different facilities, prioritizing those who have waited the longest. The approach was tested using simulated instances based on real NHS hospital data.

RESULTS

Results indicate that the model effectively integrates hospital resources within a region and efficiently allocates specialist appointments, significantly reducing waiting times.

CONCLUSIONS

This research introduces a promising strategy that, when incorporated into a decision support system, can serve as a valuable tool for healthcare management.

What is the relationship between hospital management practices and quality of care? A systematic review of the global evidence

There is a widely held view that good management improves organizational performance. However, hospitals are complex organizations, and the relationship between management practices and health service delivery is not straightforward. We conducted a global, systematic literature review of the quantitative evidence on the link between the adoption of management practices and quality of care in hospitals. We searched in PubMed, EMBASE, EconLit, Global Health, and Web of Science on 16 October 2024, without language or country restrictions. We included empirical studies from 1 January 2000 onwards, examining the quantitative association between hospital management practices and quality of care. Outcomes included structural quality (availability of resources such as drugs and equipment), clinical quality (adherence to guidelines), health outcomes, and patient satisfaction or experience with care. In every study, each tested association was categorized as significantly positive (at the 5% level), null, or significantly negative. The study was registered with PROSPERO (CRD42022301462). Of 11 731 articles, 25 studies met the inclusion criteria and had an acceptable risk of bias. Studies were equally distributed between high-income and low- and middle-income countries, with 22 cross-sectional and three intervention studies. Of 111 associations, 55 (49.5%) were significantly positive, one (1%) was significantly negative, and 55 (49.5%) were null. Among the associations tested, the majority were significantly positive for structural quality (79%), clinical quality (60%), and health outcomes (57%), while most associations between hospital management and patient satisfaction (80%) were null. The findings are mixed, with a similar proportion of positive and null associations between management practices and quality of care across studies. The evidence is limited by the risk of bias introduced by nonrandomized study designs. Evidence of positive associations in some settings warrants further investigation of the association through intervention studies or natural experiments. This could leverage methodological developments in quantitatively measuring management, highlighted by this review.

Contextually appropriate nurse staffing models: a realist review protocol

INTRODUCTION

Decisions about nurse staffing models are a concern for health systems globally due to workforce retention and well-being challenges. Nurse staffing models range from all Registered Nurse workforce to a mix of differentially educated nurses and aides (regulated and unregulated), such as Licensed Practical or Vocational Nurses and Health Care Aides. Systematic reviews have examined relationships between specific nurse staffing models and client, staff and health system outcomes (eg, mortality, adverse events, retention, healthcare costs), with inconclusive or contradictory results. No evidence has been synthesised and consolidated on how, why and under what contexts certain staffing models produce different outcomes. We aim to describe how we will (1) conduct a realist review to determine how nurse staffing models produce different client, staff and health system outcomes, in which contexts and through what mechanisms and (2) coproduce recommendations with decision-makers to guide future research and implementation of nurse staffing models.

METHODS AND ANALYSIS

Using an integrated knowledge translation approach with researchers and decision-makers as partners, we are conducting a three-phase realist review. In this protocol, we report on the final two phases of this realist review. We will use Citation tracking, tracing Lead authors, identifying Unpublished materials, Google Scholar searching, Theory tracking, ancestry searching for Early examples, and follow-up of Related projects (CLUSTER) searching, specifically designed for realist searches as the review progresses. We will search empirical evidence to test identified programme theories and engage stakeholders to contextualise findings, finalise programme theories document our search processes as per established realist review methods.

ETHICS AND DISSEMINATION

Ethical approval for this study was provided by the Health Research Ethics Board of the University of Alberta (Study ID Pro00100425). We will disseminate the findings through peer-reviewed publications, national and international conference presentations, regional briefing sessions, webinars and lay summary.

Predictive analytics for cardio-thoracic surgery duration as a stepstone towards data-driven capacity management

Effective capacity management of operation rooms is key to avoid surgery cancellations and prevent long waiting lists that negatively affect clinical and financial outcomes as well as patient and staff satisfaction. This requires optimal surgery scheduling, leveraging essential parameters like surgery duration, post-operative bed type and hospital length-of-stay. Common clinical practice is to use the surgeon's average procedure time of the last N patients as a planned surgery duration for the next patient. A discrepancy between the actual and planned surgery duration may lead to suboptimal surgery schedule. We used deidentified data from 2294 cardio-thoracic surgeries to first calculate the discrepancy of the current model and second to develop new predictive models based on linear regression, random forest, and extreme gradient boosting. The new ensamble models reduced the RMSE for elective and acute surgeries by 19% (0.99 vs 0.80, p = 0.002) and 52% (1.87 vs 0.89, p < 0.001), respectively. Also, the elective and acute surgeries "behind schedule" were reduced by 28% (60% vs. 32%, p < 0.001) and 9% (37% vs. 28%, p = 0.003), respectively. These improvements were fueled by the patient and surgery features added to the models. Surgery planners can benefit from these predictive models as a patient flow AI decision support tool to optimize OR utilization.

Solutions for improved hospital-wide patient flows - a qualitative interview study of leading healthcare providers

BACKGROUND

Hospital productivity is of great importance for patients and public health to achieve better availability and health outcomes. Previous research demonstrates that improvements can be reached by directing more attention to the flow of patients. There is a significant body of literature on how to improve patient flows, but these research projects rarely encompass complete hospitals. Therefore, through interviews with senior managers at the world's leading hospitals, this study aims to identify effective solutions to enable swift patient flows across hospitals and develop a framework to guide improvements in hospital-wide patient flows.

METHODS

This study drew on qualitative data from interviews with 33 senior managers at 18 of the world's 25 leading hospitals, spread across nine countries. The interviews were conducted between June 2021 and November 2021 and transcribed verbatim. A thematic analysis followed, based on inductive reasoning to identify meaningful subjects and themes.

RESULTS

We have identified 50 solutions to efficient hospital-wide patient flows. They describe the importance for hospitals to align the organization; build a coordination and transfer structure; ensure physical capacity capabilities; develop standards, checklists, and routines; invest in digital and analytical tools; improve the management of operations; optimize capacity utilization and occupancy rates; and seek external solutions and policy changes. This study also presents a patient flow improvement framework to be used by healthcare managers, commissioners, and decision-makers when designing strategies to improve the delivery of healthcare services to meet the needs of patients.

CONCLUSIONS

Hospitals must invest in new capabilities and technologies, implement new working methods, and build a patient flow-focused culture. It is also important to strategically look at the patient's whole trajectory of care as one unified flow that must be aligned and integrated between and across all actors, internally and externally. Hospitals need to both proactively and reactively optimize their capacity use around the patient flow to provide care for as many patients as possible and to spread the burden evenly across the organization.

Driving Efficiency Improvement (EI): Exploratory Analysis of a Centralised Model in New South Wales

Introduction

Public healthcare systems face rising demand coupled with reducing funding growth rates, necessitating ongoing approaches to efficiency improvement (EI). Centrally coordinated EI approaches l may support EI leaders, yet few such approaches exist internationally. This study provides evidence to inform system-wide EI by harnessing understanding of the perceptions, role demands and support requirements of key EI stakeholders in the centralised EI model implemented in New South Wales.

Methods

A purposive sample of key informants within NSW Health with responsibility for EI in their organisation were invited to participate. Semi-structured interviews were conducted, recorded and transcribed. A thematic analysis was undertaken using a theoretical deductive approach.

Results

Seventeen respondents participated who occupied EI leadership roles in metro (8) and rural (6) health services as well as non-clinical support (3) services. Four primary themes emerged on the perceptions and experiences of participants in 1. holding a unique skillset which enables them to undertake EI; 2. inheriting EI accountabilities as additional duties rather than holding dedicated EI roles; 3. the importance of senior support for EI success; and 4. feelings of isolation in undertaking EI. An additional underpinning theme that EI is not well conceptualized in public health systems also emerged, whereby EI planners felt that frontline staff generally do not consider efficiency as a component of their duties.

Conclusion

EI leaders provide points of authority, experience and influence across organisations within public health systems. This study finds that EI planners possess a unique skillset, can feel isolated both within their health organisation and within the broader public health system and believe that EI is poorly conceptualized amongst health staff. Centralised support for EI stakeholders across a public health system can promote knowledge sharing and capability development. Addressing the role and support requirements of key EI stakeholders is essential.

Supporting efficiency improvement in public health systems: a rapid evidence synthesis

BACKGROUND

Public health systems internationally are under pressure to meet increasing demand for healthcare in the context of increasing financial resource constraint. There is therefore a need to maximise health outcomes achieved with public healthcare expenditure. This paper aims to establish and synthesize the contemporary evidence base for approaches taken at a system management level to improve efficiency.

METHODS

Rapid Evidence Assessment (REA) methodology was employed. A search strategy was developed and applied (PUBMED, MEDLINE) returning 5,377 unique titles. 172 full-text articles were screened to determine relevance with 82 publications included in the final review. Data regarding country, study design, key findings and approaches to efficiency improvement were extracted and a narrative synthesis produced. Publications covering health systems from developed countries were included.

RESULTS

Identified study designs included policy reviews, qualitative reviews, mixed methods reviews, systematic reviews, literature reviews, retrospective analyses, scoping reviews, narrative papers, regression analyses and opinion papers. While findings revealed no comprehensive frameworks for system-wide efficiency improvement, a range of specific centrally led improvement approaches were identified. Elements associated with success in current approaches included dedicated central functions to drive system-wide efficiency improvement, managing efficiency in tandem with quality and value, and inclusive stakeholder engagement.

CONCLUSIONS

The requirement for public health systems to improve efficiency is likely to continue to increase. Reactive cost-cutting measures and short-term initiatives aimed only at reducing expenditure are unlikely to deliver sustainable efficiency improvement. By providing dedicated central system-wide efficiency improvement support, public health system management entities can deliver improved financial, health service and stakeholder outcomes.

When patients get stuck: A systematic literature review on throughput barriers in hospital-wide patient processes

Hospital productivity is of great importance to policymakers, and previous research demonstrates that improved hospital productivity can be achieved by directing more focus towards patient throughput at healthcare organizations. There is also a growing body of literature on patient throughput barriers hampering the flow of patients. These projects rarely, however, encompass complete hospitals. Therefore, this paper provides a systematic literature review on hospital-wide patient process throughput barriers by consolidating the substantial body of studies from single settings into a hospital-wide perspective. Our review yielded a total of 2207 articles, of which 92 were finally selected for analysis. The results reveal long lead times, inefficient capacity coordination and inefficient patient process transfer as the main barriers at hospitals. These are caused by inadequate staffing, lack of standards and routines, insufficient operational planning and a lack in IT functions. As such, this review provides new perspectives on whether the root causes of inefficient hospital patient throughput are related to resource insufficiency or inefficient work methods. Finally, this study develops a new hospital-wide framework to be used by policymakers and healthcare managers when deciding what improvement strategies to follow to increase patient throughput at hospitals.

Is there scope for mixed markets in the provision of hospital care?

Market oriented reforms in hospital care have produced a variety of quasi markets that differ for the type of providers that are allowed to compete. Mixed markets, where public hospitals compete alongside private ones, are increasingly common, but the literature does not agree on their performances and their desirability. We review the contributions in this field by proposing a common framework which allows to account for the different approaches proposed to model public hospitals. In this paper we show under which conditions mixed markets perform better in terms of average quality, and we review the empirical literature to determine whether these conditions are met. In general, pure forms (private or public competition) are superior to mixed markets, unless patients interpret public hospitals as reference suppliers, and quality of care is important. The empirical evidence on these key questions shows that public hospitals behave differently from private organisations, but they are not necessarily less efficient. Research into patients choices seems to suggest that ownership is a value, but the empirical literature is still rather scant. From a policy point of view, our review suggests that there does not seem to be a clear answer to whether this market form should be used. Local conditions are going to play an important role.

Is capital investment in Australian hospitals effectively funding patient access to efficient public hospital care?

Objective This study asks ‘Is capital investment in Australian public hospitals effectively funding patient access to efficient hospital care?’ Methods The study drew information from semistructured interviews with senior health infrastructure officials, literature reviews and World Health Organization (WHO) reports. To identify which systems most effectively fund patient access to efficient hospitals, capital allocation systems for 17 Organisation for Economic Cooperation and Development (OECD) countries were assessed. Results Australian government objectives (equitable access to clinically appropriate, efficient, sustainable, innovative, patient-based) for acute health services are not directly addressed within Australian capital allocation systems for hospitals. Instead, Australia retains a prioritised hospital investment system for institutionally based asset replacement and capital planning, aligned with budgetary and political priorities. Australian systems of capital allocation for public hospitals were found not to match health system objectives for allocative, productive and dynamic efficiency. Australia scored below average in funding patient access to efficient hospitals. The OECD countries most effectively funding patient access to efficient hospital care have transitioned to diagnosis-related group (DRG) aligned capital funding. Measures of effective capital allocation for hospitals, patient access and efficiency found mixed government–private–public partnerships performed poorly with inferior access to capital than DRG-aligned systems, with the worst performing systems based on private finance. Conclusion Australian capital allocation systems for hospitals do not meet Australian government standards for the health system. Transition to a diagnosis-based system of capital allocation would align capital allocation with government standards and has been found to improve patient access to efficient hospital care. What is known about the topic? Very little is known about the effectiveness of Australian capital allocation for public hospitals. In Australia, capital is rarely discussed in the context of efficiency, although poor built capital and inappropriate technologies are acknowledged as limitations to improving efficiency. Capital allocated for public hospitals by state and territory is no longer reported by Australian Institute of Health and Welfare due to problems with data reliability. International comparative reviews of capital funding for hospitals have not included Australia. Most comparative efficiency reviews for health avoid considering capital allocation. The national review of hospitals found capital allocation information makes it difficult to determine ’if we have it right’ in terms of investment for health services. Problems with capital allocation systems for public hospitals have been identified within state-based reviews of health service delivery. The Productivity Commission was unable to identify the cost of capital used in treating patients in Australian public hospitals. Instead, building and equipment depreciation plus the user cost of capital (or the cost of using the money invested in the asset) are used to estimate the cost of capital required for patient care, despite concerns about accuracy and comparability. What does this paper add? This is the first study to review capital allocation systems for Australian public hospitals, to evaluate those systems against the contemporary objectives of the health systems and to assess whether prevailing Australian allocation systems deliver funds to facilitate patient access to efficient hospital care. This is the first study to evaluate Australian hospital capital allocation and efficiency. It compares the objectives of the Australian public hospitals system (for universal access to patient-centred, efficient and effective health care) against a range of capital funding mechanisms used in comparable health systems. It is also the first comparative review of international capital funding systems to include Australia. What are the implications for practitioners? Clinical quality and operational efficiency in hospitals require access for all patients to technologically appropriate hospitals. Funding for appropriate public hospital facilities, medical equipment and information and communications technology is not connected to activity-based funding in Australia. This study examines how capital can most effectively be allocated to provide patient access to efficient hospital care for Australian public hospitals. Capital investment for hospitals that is patient based, rather than institutionally focused, aligns with higher efficiency.

Hospital productivity bias when not adjusting for cost heterogeneity: The case of Spain

This research quantifies the bias caused in hospital productivity measurements when cost heterogeneity is not considered. A multi-output stochastic cost frontier under a normalised translog specification is used to approximate the structure of technology of a sample of public general hospitals in Spain during the period 2002–2009. To control for observable heterogeneity in costs, a set of variables related to hospital characteristics are included in the cost frontier specification (i.e., hospital complexity, degree of specialisation, availability of outpatient clinics, variety of high-technology equipment available, teaching activity and quality of care), whereas unobservable heterogeneity is accounted for by means of individual dummy variables. A measure of hospitals’ cost efficiency is first obtained, and the analysis is then completed by measuring and decomposing the total factor productivity index (TFP-I) change. Findings reveal that controlling for heterogeneity decreases total productivity from an annual average rate of 0.028% to 1.330%, mainly driven by the negative contribution of the cost efficiency change component. Hence, a bias of 1.303 percentage points in the overall TFP-I is found as consequence of not controlling for heterogeneity. In addition to this, if heterogeneity factors are not accounted for, the mean cost efficiency index during the period analysed is 0.730, figure that increases up to 0.974 if heterogeneity is considered. Hence, the omission of heterogeneity leads to a bias of 24.4 percentage points in the mean cost efficiency. Therefore, not adjusting for heterogeneity in costs gives rise to distorted measurements of hospital productivity, as well as distortions in the contribution of each of its components, which may lead to the adoption of inadequate policies and decisions on resource allocation.

Improving accessibility for outpatients in specialist clinics: reducing long waiting times and waiting lists with a simple analytic approach

Background

Lack of resources is often cited as a reason for long waiting times and queues in health services. However, recent research indicates these problems are related to factors such as uncoordinated variation of demand and capacity, planning horizons, and lower capacity than the potential of actual resources.

This study aimed to demonstrate that long waiting times and wait lists are not necessarily associated with increasing demand or changes in resources. We report how substantial reductions in waiting times/wait lists across a range of specialties was obtained by improvements of basic problems identified through value-stream mapping and unsophisticated analyses.

Methods

In-depth analyses of current operational processes by value-stream mapping were used to identify bottlenecks and sources of waste. Waiting parameters and measures of demand and resources were assessed monthly from 12 months before the intervention to 6 months after the intervention. The effect of the intervention on reducing waiting time and number of patients waiting were evaluated by a difference-in-differences analysis.

Results

Mean waiting time across all clinics was reduced from 162 + 69 days (range 74–312 days) at baseline to 52 + 10 days (range 41–74 days) 6 months after the intervention. The time needed to achieve a waiting time of 65 days varied from 4 to 21 months. The number of new patients waiting was reduced from 15,874 (range 369–2980) to 8922 (range 296–1650), and the number of delayed returning patients was reduced from 18,700 (310–3324) to 5993 (40–1337) (p < 0.01 for all). Improvement in waiting measures paralleled a significant increase in planning horizon.

Conclusions

Significant improvements in accessibility for patients waiting for service may be achieved by applying unsophisticated methods and analyses and without increasing resources. Engagement of clinical management and involvement of front line personnel are important factors for improvement.

Do hospitals respond to rivals' quality and efficiency? A spatial panel econometric analysis

We investigate whether hospitals in the English National Health Service change their quality or efficiency in response to changes in quality or efficiency of neighbouring hospitals. We first provide a theoretical model that predicts that a hospital will not respond to changes in the efficiency of its rivals but may change its quality or efficiency in response to changes in the quality of rivals, though the direction of the response is ambiguous. We use data on eight quality measures (including mortality, emergency readmissions, patient reported outcome, and patient satisfaction) and six efficiency measures (including bed occupancy, cancelled operations, and costs) for public hospitals between 2010/11 and 2013/14 to estimate both spatial cross-sectional and spatial fixed- and random-effects panel data models. We find that although quality and efficiency measures are unconditionally spatially correlated, the spatial regression models suggest that a hospital's quality or efficiency does not respond to its rivals' quality or efficiency, except for a hospital's overall mortality that is positively associated with that of its rivals. The results are robust to allowing for spatially correlated covariates and errors and to instrumenting rivals' quality and efficiency.

Hospital Trusts productivity in the English NHS: Uncovering possible drivers of productivity variations

BACKGROUND

Health care systems in OECD countries are increasingly facing economic challenges and funding pressures. These normally demand interventions (political, financial and organisational) aimed at improving the efficiency of the health system as a whole and its single components. In 2009, the English NHS Chief Executive, Sir David Nicholson, warned that a potential funding gap of £20 billion should be met by extensive efficiency savings by March 2015. Our study investigates possible drivers of differential Trust performance (productivity) for the financial years 2010/11-2012/13.

METHODS

Following accounting practice, we define Productivity as the ratio of Outputs over Inputs. We analyse variation in both Total Factor and Labour Productivity using ordinary least squares regressions. We explicitly included in our analysis factors of differential performance highlighted in the Nicholson challenge as the sources were the efficiency savings should come from. Explanatory variables include efficiency in resource use measures, Trust and patient characteristics, and quality of care.

RESULTS

We find that larger Trusts and Foundation Trusts are associated with lower productivity, as are those treating a greater proportion of both older and/or younger patients. Surprisingly treating more patients in their last year of life is associated with higher Labour Productivity.

Re-thinking barriers to organizational change in public hospitals

Public hospitals are well known to be difficult to reform. This paper provides a comprehensive six-part analytic framework that can help policymakers and managers better shape their organizational and institutional behavior. The paper first describes three separate structural characteristics which, together, inhibit effective problem description and policy design for public hospitals. These three structural constraints are i) the dysfunctional characteristics found in most organizations, ii) the particular dysfunctions of professional health sector organizations, and iii) the additional dysfunctional dimensions of politically managed organizations. While the problems in each of these three dimensions of public hospital organization are well-known, and the first two dimensions clearly affect private as well as publicly run hospitals, insufficient attention has been paid to the combined impact of all three factors in making public hospitals particularly difficult to manage and steer. Further, these three structural dimensions interact in an institutional environment defined by three restrictive context limitations, again two of which also affect private hospitals but all three of which compound the management dilemmas in public hospitals. The first contextual limitation is the inherent complexity of delivering high quality, safe, and affordable modern inpatient care in a hospital setting. The second contextual limitation is a set of specific market failures in public hospitals, which limit the scope of the standard financial incentives and reform measures. The third and last contextual limitation is the unique problem of generalized and localized anxiety, which accompanies the delivery of medical services, and which suffuses decision-making on the part of patients, medical staff, hospital management, and political actors alike. This combination of six institutional characteristics - three structural dimensions and three contextual dimensions - can help explain why public hospitals are different in character from other parts of the public sector, and the scale of the challenge they present to political decision-makers.

Assessing physician productivity following Norwegian hospital reform: A panel and data envelopment analysis

BACKGROUND

Although health care reforms may improve efficiency at the macro level, less is known regarding their effects on the utilization of health care personnel. Following the 2002 Norwegian hospital reform, we studied the productivity of the physician workforce and the effect of personnel mix on this measure in all nineteen Norwegian hospitals from 2001 to 2013.

METHODS

We used panel analysis and non-parametric data envelopment analysis (DEA) to study physician productivity defined as patient treatments per full-time equivalent (FTE) physician. Resource variables were FTE and salary costs of physicians, nurses, secretaries, and other personnel. Patient metrics were number of patients treated by hospitalization, daycare, and outpatient treatments, as well as corresponding diagnosis-related group (DRG) scores accounting for differences in patient mix. Research publications and the fraction of residents/FTE physicians were used as proxies for research and physician training.

RESULTS

The number of patients treated increased by 47% and the DRG scores by 35%, but there were no significant increases in any of the activity measures per FTE physician. Total DRG per FTE physician declined by 6% (p < 0.05). In the panel analysis, more nurses and secretaries per FTE physician correlated positively with physician productivity, whereas physician salary was neutral. In 2013, there was a 12%-80% difference between the hospitals with the highest and lowest physician productivity in the differing treatment modalities. In the DEA, cost efficiency did not change in the study period, but allocative efficiency decreased significantly. Bootstrapped estimates indicated that the use of physicians was too high and the use of auxiliary nurses and secretaries was too low.

CONCLUSIONS

Our measures of physician productivity declined from 2001 to 2013. More support staff was a significant variable for predicting physician productivity. Personnel mix developments in the study period were unfavorable with respect to physician productivity.

Measuring Efficiency of Knowledge Production in Health Research Centers Using Data Envelopment Analysis (DEA): A Case Study in Iran

INTRODUCTION

Efficiency analysis is necessary in order to avoid waste of materials, energy, effort, money, and time during scientific research. Therefore, analyzing efficiency of knowledge production in health areas is necessary, especially for developing and in-transition countries. As the first step in this field, the aim of this study was the analysis of selected health research center efficiency using data envelopment analysis (DEA).

METHODS

This retrospective and applied study was conducted in 2015 using input and output data of 16 health research centers affiliated with a health sciences university in Iran during 2010-2014. The technical efficiency of health research centers was evaluated based on three basic data envelopment analysis (DEA) models: input-oriented, output-oriented, and hyperbolic-oriented. The input and output data of each health research center for years 2010-2014 were collected from the Iran Ministry of Health and Medical Education (MOHE) profile and analyzed by R software.

RESULTS

The mean efficiency score in input-oriented, output-oriented, and hyperbolic-oriented models was 0.781, 0.671, and 0.798, respectively. Based on results of the study, half of the health research centers are operating below full efficiency, and about one-third of them are operating under the average efficiency level. There is also a large gap between health research center efficiency relative to each other.

CONCLUSION

It is necessary for health research centers to improve their efficiency in knowledge production through better management of available resources. The higher level of efficiency in a significant number of health research centers is achievable through more efficient management of human resources and capital. Further research is needed to measure and follow the efficiency of knowledge production by health research centers around the world and over a period of time.