[Research Ranking of Spanish Public Universities (2019)].

Research Ranking of Spanish Public Universities (2019). BACKGROUND: The changes produced in the Spanish university system due to the Bologna process require periodically updated evaluation reports of research activity. The objective of this study is to update the last available ranking of Spanish public universities, based on data from 2013-2018. METHOD: The production and productivity of each university were assessed based on seven specific indicators and a global score: articles in journals indexed in the JCR (Journal Citation Reports), research periods, R+D projects, doctoral theses, FPU (training of university professors) grants, FPI (training of personal researchers) grants, and patents. RESULTS: Globally, the universities Complutense of Madrid, Barcelona, and Granada hold the first positions in terms of production, while the first positions in terms of productivity are held by the universities Pompeu Fabra, Autonomous of Madrid, and Autonomous of Barcelona. CONCLUSIONS: The universities that hold the top positions in this ranking remain relatively steady over time and are also the Spanish universities that stand out in international classifications.

Productivity in Pediatric Palliative Care: Measuring and Monitoring an Elusive Metric.

CONTEXT: Workforce productivity is poorly defined in health care. Particularly in the field of pediatric palliative care (PPC), the absence of consensus metrics impedes aggregation and analysis of data to track workforce efficiency and effectiveness. Lack of uniformly measured data also compromises the development of innovative strategies to improve productivity and hinders investigation of the link between productivity and quality of care, which are interrelated but not interchangeable. OBJECTIVES: To review the literature regarding the definition and measurement of productivity in PPC; to identify barriers to productivity within traditional PPC models; and to recommend novel metrics to study productivity as a component of quality care in PPC. METHODS: PubMed® and Cochrane Database of Systematic Reviews searches for scholarly literature were performed using key words (pediatric palliative care, palliative care, team, workforce, workflow, productivity, algorithm, quality care, quality improvement, quality metric, inpatient, hospital, consultation, model) for articles published between 2000 and 2016. Organizational searches of Center to Advance Palliative Care, National Hospice and Palliative Care Organization, National Association for Home Care & Hospice, American Academy of Hospice and Palliative Medicine, Hospice and Palliative Nurses Association, National Quality Forum, and National Consensus Project for Quality Palliative Care were also performed. Additional semistructured interviews were conducted with directors from seven prominent PPC programs across the U.S. to review standard operating procedures for PPC team workflow and productivity. RESULTS: Little consensus exists in the PPC field regarding optimal ways to define, measure, and analyze provider and program productivity. Barriers to accurate monitoring of productivity include difficulties with identification, measurement, and interpretation of metrics applicable to an interdisciplinary care paradigm. In the context of inefficiencies inherent to traditional consultation models, novel productivity metrics are proposed. CONCLUSIONS: Further research is needed to determine optimal metrics for monitoring productivity within PPC teams. Innovative approaches should be studied with the goal of improving efficiency of care without compromising value.

A New Approach of Measuring Hospital Performance for Low- and Middle-income Countries.

Efficiency of the hospitals affects the price of health services. Health care payments have equity implications. Evidence on hospital performance can support to design the policy; however, the recent literature on hospital efficiency produced conflicting results. Consequently, policy decisions are uncertain. Even the most of evidence were produced by using data from high income countries. Conflicting results were produced particularly due to differences in methods of measuring performance. Recently a management approach has been developed to measure the hospital performance. This approach to measure the hospital performance is very useful from policy perspective to improve health system from cost-effective way in low and middle income countries. Measuring hospital performance through management approach has some basic characteristics such as scoring management practices through double blind survey, measuring hospital outputs using various indicators, estimating the relationship between management practices and outputs of the hospitals. This approach has been successfully applied to developed countries; however, some revisions are required without violating the fundamental principle of this approach to replicate in low- and middle-income countries. The process has been clearly defined and applied to Nepal. As the results of this, the approach produced expected results. The paper contributes to improve the approach to measure hospital performance.

Classifying and comparing fundraising performance for nonprofit hospitals.

Charitable contributions are becoming increasingly important to nonprofit hospitals, yet fundraising can sometimes be one of the more troublesome aspects of management for nonprofit organizations. This study utilizes an organizational effectiveness and performance framework to identify groups of nonprofit organizations as a method of classifying organizations for performance evaluation and benchmarking that may be more informative than commonly used characteristics such as organizational age and size. Cluster analysis, ANOVA and chi-square analysis are used to study 401 organizations, which includes hospital foundations as well as nonprofit hospitals directly engaged in fundraising. Three distinct clusters of organizations are identified based on performance measures of productivity, efficiency, and complexity. A general profile is developed for each cluster based upon the cluster analysis variables and subsequent analysis of variance on measures of structure, maturity, and legitimacy as well as selected institutional characteristics. This is one of only a few studies to examine fundraising performance in hospitals and hospital foundations, and is the first to utilize data from an industry survey conducted by the leading general professional association for healthcare philanthropy. It has methodological implications for the study of fundraising as well as practical implications for the strategic management of fundraising for nonprofit hospital and hospital foundations.

Comprehensive review of the limitations of relative value unit measurements of productivity in academic departments.

Measuring radiologist, especially sonologist, productivity has never been of greater interest than now, as radiology has moved from its historical status as a cost center to the largest revenue generator in most institutions. With more local institutional and federal oversight and regulation into the reimbursement and valuation of imaging procedures, including emphasis on outsourcing, overvalued procedures, and bundling, the ability to measure productivity and to draw meaningful conclusions from the data becomes increasingly imperative if we as radiologists and sonologists expect to contribute meaningfully to the process. This article presents a history of the "relative value unit" and discusses the valuation of radiologist/sonologist productivity in this era of ubiquitous high-technology implementation.

Rating healthy organizational performance.

Across the spectrum of philanthropy, donors are asking what evidence exists that an organization is actually creating positive, meaningful and sustainable change. Just as patient outcomes were adopted to demonstrate the efficacy of treatment, so too should organizational outcomes be adopted by health care facilities and the development organizations that support them to demonstrate the tangible and lasting benefits to the communities they serve.

Stochastic frontier analysis of hospital inefficiency: a review of empirical issues and an assessment of robustness.

Twenty stochastic frontier analysis (SFA) studies of hospital inefficiency in the United States were analyzed. Results from best-practice methods were compared against previously used methods in hospital studies to ascertain the robustness of SFA in estimating cost inefficiency. To compare past studies and analyze new data, SFA methods were varied by (a) the assumptions of the structure of costs and distribution of the error term, (b) inclusion of quality and product descriptor measures, and (c) use of simultaneous and two-stage estimation techniques. SFA results were relatively insensitive to several model variations.

Worker productivity outcome measures in arthritis.

Arthritis is a leading cause of work disability and makes up a significant amount of the socioeconomic cost and health burden to the working age population. We discuss the measurement of worker productivity: that is, absenteeism and presenteeism. Absenteeism refers to the time missed from work due to health reasons and presenteeism refers to the time of impaired performance while at work due to health reasons resulting in productivity loss. While the term absenteeism is commonly used and has several definitions by itself, the current arthritis literature lacks the use of presenteeism as a work outcome measure in describing health states of the workers and for economic costing. Due to advanced medical management and job accommodations that allow workers to stay at work, absenteeism alone may not be enough to give us a complete picture of worker productivity. From our review, we found that the conceptualization and measurement of absenteeism and presenteeism differ. Our research agenda was to carry forward a work outcome measurement that can be used for cost calculation and that can determine levels or states of productivity loss so we can accurately measure the influence of arthritis and advance arthritis care. We recognize the need to perform psychometric testing of work outcome measures and to improve our ability to identify transitions (i.e., move in and out of a productivity state over time) made by workers with arthritis.

A review of methods to measure health-related productivity loss.

BACKGROUND: Annual US health-related productivity losses are estimated to reach some $260 billion, attributable not only to absenteeism but also to presenteeism (being present at work but working at a reduced capacity). The search for remedies has been hampered by the lack of accurate estimates of the loss of productivity and its true costs. To date, little effort has been made to assess the availability of measurement instruments or the validity and reliability of those that exist. OBJECTIVES: To systematically review the instruments used to measure productivity loss and its costs and to assess limitations in current research. DESIGN: A systematic search was conducted of the published and gray-market research literature from 1995 through 2005 on methods for estimating productivity loss and monetizing that loss. RESULTS: Twenty survey instruments were identified that assess the effect of health problems on absenteeism or presenteeism by attempting to quantify self-perceived or comparative impairment or by measuring unproductive work time. Some of the methods have been validated. The challenges of measuring presenteeism far exceed those of measuring absenteeism primarily because many jobs do not have easily measurable output. Methods to estimate the cost of lost productivity were also identified; however, none have been validated, to our knowledge. CONCLUSIONS: The greatest impediment to estimating the cost of productivity lost to illness is the lack of established and validated methods for monetization. The issues raised in this review are intended to stimulate future research to validate and improve such methods.

Managed care and the scale efficiency of US hospitals.

Managed care penetration has been partly responsible for slowing down increases in health care costs in recent years. This study uses a 1992-1996 Health Care Utilization Project sample of hospitals to analyze the relationship between managed care penetration in local insurance markets and hospital scale efficiency. After controlling for hospital and market area variables, we find that managed care insurance, particularly the preferred provider type, is associated with increases in hospital scale efficiency in tertiary cases. The results presented here are consistent with the view that managed care can lead to reductions in health cost inflation by controlling the diffusion of technology via improvements in the scale efficiency of hospitals.

Economic profiling of primary care physicians: consistency among risk-adjusted measures.

OBJECTIVE: To investigate whether different risk-adjustment methodologies and economic profiling or "practice efficiency" metrics produce differences in practice efficiency rankings for a set of primary care physicians (PCPs). DATA SOURCE: Twelve months of claims records (inpatient, outpatient, professional, and pharmacy) for an independent practice association HMO. STUDY DESIGN: Patient risk scores obtained with six profiling risk-adjustment methodologies were used in conjunction with claims cost tabulations to measure practice efficiency of all primary care physicians who managed 25 or more members of an HMO. DATA COLLECTION: For each of the risk-adjustment methodologies, two measures of "efficiency" were constructed: the standardized cost difference between total observed (standardized actual) and total expected costs for patients managed by each PCP, and the ratio of the PCP's total observed to total expected costs (O/E ratio). Primary care physicians were ranked from most to least efficient according to each risk-adjusted measure, and level of agreement among measures was tested using weighted kappa. Separate rankings were constructed for pediatricians and for other primary care physicians. FINDINGS: Moderate to high levels of agreement were observed among the six risk-adjusted measures of practice efficiency. Agreement was greater among pediatrician rankings than among adult primary care physician rankings, and, with the standardized difference measure, greater for identifying the least efficient than the most efficient physicians. The O/E ratio was shown to be a biased measure of physician practice efficiency, disproportionately targeting smaller sized panels as outliers. CONCLUSIONS: Although we observed moderate consistency among different risk-adjusted PCP rankings, consistency of measures does not prove that practice efficiency rankings are valid, and health plans should be careful in how they use practice efficiency information. Indicators of practice efficiency should be based on the standardized cost difference, which controls for number of patients in a panel, instead of O/E ratio, which does not.

A review of health-related workplace productivity loss instruments.

The objective of this review was to identify health-related workplace productivity loss survey instruments, with particular emphasis on those that capture a metric suitable for direct translation into a monetary figure. A literature search using Medline, HealthSTAR, PsycINFO and Econlit databases between 1966 and 2002, and a telephone-administered survey of business leaders and researchers, were conducted to identify health-related workplace productivity measurement survey instruments. This review was conducted from the societal perspective. Each identified instrument was reviewed for the following: (i). reliability; (ii). content validity; (iii). construct validity; (iv). criterion validity; (v). productivity metric(s); (vi). instrument scoring technique; (vii). suitability for direct translation into a monetary figure; (viii). number of items; (ix). mode(s) of administration; and (x). disease state(s) in which it had been tested. Reliability and validity testing have been performed for 8 of the 11 identified surveys. Of the 11 instruments identified, six captured metrics that are suitable for direct translation into a monetary figure. Of those six, one instrument measured absenteeism, while the other five measured both absenteeism and presenteeism. All of the identified instruments except for one were available as paper, self-administered questionnaires and many were available in languages other than English. This review provides a comprehensive overview of the published, peer-reviewed survey instruments available to measure health-related workplace productivity loss. As the field of productivity measurement matures, tools may be developed that will allow researchers to accurately calculate lost productivity costs when performing cost-effectiveness and cost-benefit analyses. Using data captured by these instruments, society and healthcare decision makers will be able to make better informed decisions concerning the value of the medications, disease management and health promotion programmes that individuals receive.

Profiling resource use: do different outcomes affect assessments of provider efficiency?

OBJECTIVES: To examine whether 2 outcome measures result in different assessments of efficiency across 22 service networks within the Department of Veterans Affairs (VA). STUDY DESIGN: A retrospective analysis using VA inpatient and outpatient administrative databases. METHODS: A 60% random sample of veterans who used healthcare services during fiscal year 1997 was split into a 40% sample (n = 1,046,803) for development and a 20% sample (n = 524,461) for validation. Weighted concurrent case-mix models using adjusted clinical groups were developed to explain variation in 2 outcomes: "days of care"--the sum of a patient's inpatient and outpatient annual visit days, and "average accounting costs"--the sum of the average service costs multiplied by the units of service for each patient. Two profiling indicators were calculated for each outcome: an unadjusted efficiency index and an adjusted efficiency index. These indices were compared to examine network efficiency. RESULTS: Although about half the networks were identified as "efficient" before and after case-mix adjustment, assessments of individual network efficiency were affected by the adjustment. The 2 outcomes differed on which networks were efficient. For example, 4 networks that appeared as efficient based on days of care appeared as inefficient based on average costs. CONCLUSIONS: Assessments of provider efficiency across the 22 networks depended on the outcome measure used. Knowledge about the extent to which assessments of provider efficiency depend on the outcome measure used is an important step toward improved and more equitable comparisons across providers.

Strategies for more efficient performance through hospital merger.

This article compares the operating performance of merged and non-merged local hospitals during the late 1980s and early 1990s, a period not unlike that being experienced in hospitals today. A matched case-control design is employed to create "synthetically" merged hospitals--to represent them as if they had effected a merger--and compares their performance to a group of similar hospitals that did merge.

The efficiency of the delivery of neonatal care in the UK.

BACKGROUND: A recent paper in Journal of Public Health Medicine (O'Neill et al., 2000; 22(1): 108-115) used regression modelling to determine the average costs of neonatal care services for a sample of 49 units in the United Kingdom in 1990-1991, and concluded that economies of scale were present in the sample as a whole. Although this form of modelling is useful, analysis of the efficiency of production for individual units is also important. METHODS: Data envelopment analysis (DEA) was used to analyse the data set published by O'Neil et al., to determine technical efficiency of neonatal units, measuring efficiency compared with a benchmark efficient frontier, and estimating economies of scale for each unit. Potential cost savings if units were to operate efficiently are estimated. RESULTS: There is evidence of substantial levels of technical inefficiency. Economies of scale varied between units, with increasing returns in the 36 inefficient units, and mainly constant returns in the 13 efficient units. This suggests that the presence of technical inefficiency was as important as scale inefficiencies. Total cost savings, if all units were operating efficiently, are estimated at l10.4 million, equivalent to 10 extra units producing 57,000 additional days of care. CONCLUSIONS: DEA is a technique of great potential value in analysing the efficiency of health care production. As well as inefficiencies in the production of neonatal care in the United Kingdom due to differences in the scale of production, there appears to have been considerable technical inefficiency, which was not due to differences in case mix. The potential cost savings from efficiency gains are large.

Staff nurse views of their productivity and nonproductivity.

Could better collaboration and cooperation to improve productivity occur between administrators and nurses if we understood nurse views of their productivity? Interviews of 30 staff nurses revealed that these nurses evaluated their productivity by the quantity and quality of their work. Working hard, finishing everything, and providing excellent care made them feel productive, while anything that interfered with this was a source of feeling nonproductive.

Impact of HMO penetration and other environmental factors on hospital X-inefficiency.

This study examined the impact of health maintenance organization (HMO) market penetration and other internal and external environmental factors on hospital X-inefficiency in a national sample (N = 1,966) of urban U.S. hospitals in 1997. Stochastic frontier analysis, a frontier regression technique, was used to measure X-inefficiency and estimate parameters of the correlates of X-inefficiency. Log-likelihood restriction tests were used to test a variety of assumptions about the empirical model that guided its selection. Average estimated X-inefficiency in study hospitals was 12.96 percent. Increases in managed care penetration, dependence on Medicare and Medicaid, membership in a multihospital system, and location in areas where competitive pressures and the pool of uncompensated care are greater were associated with less X-inefficiency. Not-for-profit ownership was associated with increased X-inefficiency.