benchmark analysis in healthcarebenchmark analysis in healthcare

Use the Nature Index to interrogate publication patterns and to benchmark research performance. The benchmark analysis identified the best practices of the health centers in the period analyzed. Before 0j a nominal variable designating the jth hospital; the hospital effect is assumed to be random, meaning that hospitals are assumed randomly sampled from a large population of hospitals. It has become primarily a self-assessment and decision support tool designed by management science for organizational rationalization (Barber 2004; Bruno 2008). 2003). Hermann R.C., Mattke S., Somekh D., Silfverhielm H., Goldner E., Glover G., Pirkis J., Mainz J., Chan J.A. Benchmarking can be carried out internally in very large organizations (e.g., hospitals), in which it is quite possible to compare outcomes in similar services. First used as a method for comparing production costs with those of competitors in the same sector, benchmarking later became conceptualized and used as a method for continuous quality improvement (CQI) in any sector. Benchmarking Strategies for Measuring the Quality of Healthcare Spearman correlations (r) exhibit weak agreement between estimated rankings for all outcomes, showing three independent dimensions. ij is Bernoulli distributed with expected value E(Y Users can easily draw incorrect conclusions, because the hospitals that appear to have the worst outcomes may simply have the most seriously ill patients. 0j is allowed to randomly vary across hospitals. The associated Linear Multilevel Model is. Earle C.C., Neville B.A., Landrum M.B., Souza J.M., Weeks J.C., Block S.D., Grunfeld E., Ayanian J.Z. Le benchmarking, dmarche managriale de mise en uvre des meilleures pratiques au meilleur cot, est un concept rcent dans le systme de sant. 2/3 denote the total variance of the intercept-only model, and Compared to methods previously implemented in France (Breakthrough Series called Programmes d'amlioration continue by the ANAES in the late 1990s and collaborative projects by regional evaluation and support agencies), benchmarking has specific features that set it apart as a healthcare innovation. 0j (Type B effectiveness). official website and that any information you provide is encrypted The process of identifying and learning from good practices in other organizations. e Let Including sufficient numbers of patients will reduce the possibility of random variation masking real differences or making spurious differences appear. Butler's (2008) article analyzed the political, professional, social and economic factors that contributed to the development of this approach, focusing particularly on benchmarks related to treating bedsores. pij Initially, competitive benchmarking measured an organization's performance against the competition. One of the most attractive features of multilevel models is the production of useful results in healthcare effectiveness by linking individual (patient) and organizational (hospital) characteristics (covariates). As the second step, the probability (in the logic metric Elle le sera tout particulirement pour les tablissements de sant ou mdicosociaux car le principe des visites intertablissements n'est pas inscrit dans leurs cultures. In 1981, benchmarking was adopted in all Xerox's business units. Tableau de bord des infections nosocomiales dans les tablissements de sant campagne 2011. It emerged in the United States and the United Kingdom with the imperative of comparing hospital outcomes to rationalize their funding (Camp 1998; Dewan et al. Several other studies have targeted the comparison of healthcare indicators in a given area. Finally, differences in outcome may reflect real, although unobservable, differences in quality of care. For each patient i in stratum kj, the probability of a warning event is the same, and the proportion of respondents in the kth Specialty of the jth hospital is In particular, the Breakthrough Series focuses on the rapidity of interventions, and the Collaboratives on the time-limited nature of the exercise. Thus, this approach will need to be assessed for feasibility and acceptability before it is more widely promoted. Benchmarking in healthcare is not, to our knowledge, a subject that has ever been studied in a systematic and standardized way. In contrast, a process measure lends itself to a straightforward interpretation (e.g., the more people without contra-indications who receive a specific treatment, the better). 2/( Instead, Zero-Inflated regression models address the issue of excess zeroes in their own right, explicitly modelling the production of zero counts. If a good IV is identified, both measured and unmeasured confounders can be accounted for in the analysis. Likewise, Pitarelli and Monnier (2000) put forward the key elements of a benchmarking process, i.e., the importance of fully understanding all the steps of the process that needs to be improved and of collecting reliable data (surveillance) to support decision-making. 0j continues to represent the specific managerial contribution of hospital j to the rate of clinical errors, once Specialties characteristics (case-mix) and hospital structural characteristics are taken into account. Published by the Royal College of Nursing, 20 Cavendish Square, London, W1G 0RN. Les conditions de russite s'axent essentiellement sur la bonne prparation de la dmarche, le suivi d'indicateurs pertinents, l'implication du personnel et la conduite de visites intertablissements. It captured the unobservable nonrandom component and allowed us to control for selection bias. 1,, However, the kind of adjustment required for assessing effectiveness is not the same for the various subjects interested in the results. ij and, secondly, the model now involves the level 1 residuals e Across a broad range of model parameters, our analysis indicates that the median time between the first incursion and detection in wastewater would be approximately 17 days (IQR: 7-28 days), resulting in a median of 25 cumulative cases (IQR: 6-84 cases) in the UK at the point of detection. 2, which varies across subjects (i = 1,, n) in the same manner across hospitals. 2008; Braillon et al. It determined that manufacturing costs were higher in the United States. In Italy, since 2001, the healthcare system has moved in the direction of a welfare-mix system, characterized by freedom of choice for the consumer and by the joint-presence of state agents (operating with functional financial autonomy), private profit or nonprofit accredited companies endowed with autonomous decision-making and managerial procedures and by freedom of choice for the consumer. This arises because the measurement error of the outcome at baseline is correlated with e Currently, the use of the term is often compromised by limiting it to a simple comparison of outcomes, whereas it should really be taken further, to promote discussions among front-line professionals on their practices in order to stimulate cultural and organizational change within the organizations being compared. pj) referring to (3) are specified as nonrandom covariates across hospitals, but possibly varying depending on characteristics of hospital j(z Consequently, risk adjusted benchmarking, using administrative data, can be hampered by underreporting, that is, the potential endogeneity of the recorded patient-level covariates (outcomes are correlated with the propensity to record information across hospitals) and the potential for nonconsidered covariates (misspecification). The German Bundesgeschftsstelle Qualittssicherung (BQS Federal Agency for Quality and Patient Safety) has set up a similar benchmarking process, also called Structured Dialogue, in 2,000 healthcare institutions since 2001 (BQS 2011). Identify the competitive gap by comparing against external data. Before investigating the obtained rankings, we explore possible covariate endogeneity by means of three generalized linear models which specify, for each outcome, the hospital residuals (u Lagu T, Lindenauer PK, Rothberg MB, et al. Further, all instrumental variables are excluded from the second-stage model. Four major categories of explanation need to be considered. 2/3 of a specified model with m covariates by an appropriate scale correction factor, that rescales the model to the same underlying scale as the intercept-only model. In Washington, D.C. for example, you can see each hospitals wait times. Description of data sources and related issues. Propensity Score (PS), Instrumental Variable (IV), and Sample Selection Models (SSM) are three techniques developed to minimize this potential bias [39, 40]. A process of finding the world-class examples of a product, service or operational system and then adjusting own products, services or systems to meet or beat those standards. Observing Y3d, it is of note that the significant covariates for predicting overall satisfaction (Y2) act in exactly the same manner in predicting the dissatisfaction for waiting time, (higher for private hospitals with several specialties) and the high utilization rates for operating rooms. American Productivity and Quality Center (APQC) 2and the variance 0 From the search using Google Scholar and other Internet sites, we selected 35 documents in the form of reports or articles published online. The objective was to make recommendations to decision-makers for improving the quality of these systems (Reintjes et al. Second, the necessary remedial action is clearer (use the treatment more often), whereas for an outcome measure (e.g., higher mortality rate) it is not immediately obvious what action needs to be taken. Total Quality Management (TQM) and Continuous Quality Improvement (CQI) are the most widespread and recent approaches to implementing and improving healthcare quality control [1]. In a conservative approach, the usual procedure is to build 95% pairwise confidence intervals (CI) of level 2 residuals, or their exponentiated values, and situate hospitals into three groups: effective (problematic) hospitals are those with CIs entirely under (over) the risk-adjusted mean (e.g., regional) of warning event, whereas CIs that cross the risk-adjusted mean define the intermediate group. 2008. vretveit J, Gustafson D. Improving the quality of health care: using research to inform quality programmes. Benchmarking in healthcare is defined as the continual and collaborative discipline of measuring and comparing the results of key work processes with those of the best performers in evaluating organizational performance [11]. pj is the slope (regression coefficient) of the pth person characteristic in hospital j which is allowed to randomly vary across hospitals (e.g., the effect of length of stay on adverse event occurrence varies among hospitals). However, at the patient/individual level, the event of interest is typically a dichotomous variable and the Multilevel model version for this kind of outcome is the Logistic Multilevel Model (LMM, [25]). Received 2011 Oct 12; Accepted 2011 Nov 29. kj is assumed to have a binomial error distribution, with expected value The opportunity may involve a process or an outcome that could be changed to better meet customer feedback, needs, or expectations. Epstein A. For example, if an important severity measure is missing from the database, assuming that the distribution of this unmeasured covariate will vary across hospitals, the variability of adjusted outcomes among hospital may be overestimated [30]. This approach is based on the notion of significant advances and breakthroughs. It is difficult to consider them completely equivalent, because each one focuses on one or another element, which necessarily influences its implementation strategy. 2 = Y denote the factor score estimates for the individuals, where * is the estimated covariance matrix of the observed indicators and * the estimated vector of regression coefficients; the reliability of the composite * is estimated as. 0 Benchmarking in healthcare involves setting a standard, comparing the current performance to that standard, and working to improve conditions to. However, moving from the evaluation step towards the phase of statistical implications mainly depends on the way in which monitored (e.g., adverse) events are distributed among hospitals. In a second phase, we targeted our search on healthcare benchmarking in the Medline, Science Direct and Scopus bibliographic databases, as well as by using the Google Scholar specialized search engine. Besides offering accreditation and certification processes, recent approaches measure the performance of healthcare institutions in order to evaluate their effectiveness, defined as the capacity to provide treatment that modifies and improves the patient's state of health. and HCQI Expert Group Members This formulation does not model individual probability and does not use individual-level covariates. In absence of institutional software measuring severity, possible alternatives contained in Hospital Discharge Cards data are length of stay, admission type (planned/urgent), hospitalization type (surgical/other), DRG, and DRG weight, a numeric value assigned to each discharge based on the average resources consumed to treat patients in that DRG. For external benchmarking of clinical practices, it is difficult, given the medical specificity of the indicators to be used, to see how these practices might be compared against other sectors. Selecting Indicators for Patient Safety at the Health System Level in OECD Countries.. When the search equation identified more than 200 references, we limited our reading to the first 100, according to the search engine's order of relevance. 0j are assumed as independent and uncorrelated with fixed explicative variables. Individuals/patients constitute the sampling units at the first and lowest level of the nested hierarchy. For example, Earle and colleagues (2005) compared the intensity of end-of-life care for patients with cancer by using Medicare administrative data. pj the specific effect of hospital j to the average slope (random effect). Section 3 presents statistical methods, while Section 4 explores the methodological problems related to performing consistent benchmarking analyses. Ministre du travail, de l'emploi et de la sant (MTES) Several recent statistical papers deal with risk-adjusted comparisons, related to the mortality or morbidity outcomes, by means of Multilevel models, in order to take into account different case-mixes of patients (for a review, see Goldstein and Leyland [26] and Rice and Leyland [27]). The HCQI (Health Care Quality Indicators) project launched in 2001 by the OECD focused on two broad questions: what aspects of healthcare quality should be evaluated, and how? When variation is discovered through continuous monitoring, or when unexpected events suggest performance problems, members of the organization may decide that there is an opportunity for improvement. Over the last few years, increasing attention has been directed toward the problems inherent to measuring the quality of healthcare and implementing benchmarking strategies. i All these articles were excluded because they did not correspond to our selection criteria. This is the case for current research projects such as the BELIEVE project coordinated by the CCECQA (2010). The OECD Health Care Quality Indicators Project: History and Background.. Another limitation of our review is that we did not do an exhaustive literature search, focusing rather on identifying articles that best illustrated our point of view, with the reading done by a single author. Meehan T., Stedman T., Neuendorf K., Francisco I., Neilson M. kj), once having substituted index i with index k, (8) identifies the Poisson Multilevel Model. Office fdral des assurances sociales (OFAS) 2 + The parameter can be estimated by the full or restricted maximum likelihood method [24]. The .gov means its official. This is why our review is based on multiple sources that often mix facts and opinions; we were unable to present the readings on the various experiences in as structured a grid as would be found in a classical review of articles based on similar methods. Specifically, Assessment of such bias, which limits a suitable relative effectiveness of hospitals [39], would be extremely difficult and would require information about all possible hospital admissions. These methods are still considered to be benchmarking, but numerous other elements have been added (Pitarelli and Monnier 2000). Benchmarking in health care is the process of comparing an organization to benchmarks or industry standards. ij BMC Health Serv Res. Consumers of indicator information (stakeholders, clinicians, and patients) need reliable and valid information for benchmarking, making judgments, and determining priorities, accountability, and quality improvement. In: McGlynn EA, Damberg C, Kerr EA, Brook RA, editors. In general, the broader the perspective required, the greater the relevance of outcome measures, as they reflect the interplay of a wide variety of factors, some directly related healthcare, others not. National Library of Medicine NBR is able to model count data with over-dispersion, because NBR is the extension of PR with a more liberal variance assumption, modelled by means of a dispersion parameter. Despite these limitations, outcome measures have a role in the monitoring of the quality of healthcare that is important per se. Benchmarking hospital safety and identifying - ScienceDirect However, in the presence of individual dichotomous data (Y CIHI Canadian Institute for Health Information. Pfizer Inc. - Pfizer Quarterly Corporate Performance - Second Quarter 2023 This in-depth search targeted articles that identified benchmarking as a structured quality improvement method in healthcare and articles in which benchmarking was used as an approach for analyzing and improving healthcare processes. Materials and Methods: We collected 1226 fundus fluorescein angiography reports and corresponding diagnosis written in Chinese, and tested ChatGPT with four prompting strategies (direct diagnosis or diagnosis with explanation and in Chinese or . Two types of benchmarking can be used to evaluate patient safety and quality performance. While theyre a bit more abstract than competitive and functional benchmarks, generic benchmarks can be used to look beyond a data set and focus more on general processes. The https:// ensures that you are connecting to the kj, which is the dependent outcome to be modelled. In this situation, one classic cause of over-dispersion is the presence of the excess of zeroes in the analyzed outcome distribution (e.g., when many hospitals are not responsible for adverse events). Estimates of the effects and outcomes can be biased due to a correlation between factors (such as baseline health status) associated with hospital selection and outcomes (endogeneity). ij be the probability of occurrence of a dichotomous adverse event Y Benchmarking often refers to the comparison of indicators in a time-limited approach. Other local and regional comparative indicator-based initiatives were developed in France: These projects made it possible to develop indicators and to begin doing comparisons in the healthcare sector. 2009. Hospital process measures (all measured in 2009 and obtained by Hospital Discharge Cards) involve number of specialties in the hospital (N_Specialties), percentage of beds utilized (% Beds), number of operating rooms utilized (N_OpRoom), total number of hours operating room utilized (Hours_OpRoom), average monthly hours per operating room (Ave_MH_OpRoom), and the case-mix of charged patients during 2009. 2 can be estimated once the reliability of the composite = 1 ( This consideration was taken into account by the Institute of Medicine, which, in 1990, stated that quality of care is the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge [10]. 2009b). Donabedian A. Benchmarking, as described in Essence of Care, helps practitioners adopt a structured approach to sharing and comparing practices so that they can identify best practices and develop action plans (NHS 2003, 2006, 2007; Nursing Times 2007). Comit de coordination de l'valuation clinique et de la qualit en Aquitaine (CCECQA) The line is open Monday-Friday (excluding bank holidays) between 10am-4pm. p0 represent the average slope across hospitals and u The process of continuously comparing and measuring an organization against business leaders anywhere in the world to gain information that will help the organization take action to improve its performance. Poisson Regression (PR, [34]) is the simplest regression model for count data and assumes that each observed count Y 2005; Ellershaw et al. This paper deals with hospital effectiveness, defined as the capacity of hospitals to provide treatment that modifies and improves the patient's state of health. Bethesda, MD 20894, Web Policies Benchmarking is often thought to consist simply of comparing indicators and is not perceived in its entirety, that is, as a tool based on voluntary and active collaboration among several organizations to create a spirit of competition and to apply best practices. ij) = P(Y In the literature, few articles described benchmarking as a quality improvement process carried out in successive stages and/or involving the structured exchange of information based on dialogue or on site visits in order to share best practices. The upper part of Table 2 exhibits, for Y1 and Y2, the corrected (disattenuated) ICCs in the intercept-only model and the residual ICCs (the remaining proportion of variability due to hospitals differences, once that covariates are inserted in the models). It's used as a point of reference from which an evaluation can be made. We used the Google search engine with the following keywords: benchmarking, benchmarking methods, benchmarking models, benchmarking techniques, utilization of benchmarking, types of benchmarking, benchmarking in health, benchmarking in medicine, comparative evaluation and parangonnage (French term for benchmarking). Benchmarking--the process of establishing a standard of excellence and comparing a business function or activity, a product, or an enterprise as a whole with that standard--will be used increasingly by healthcare institutions to reduce expenses and simultaneously improve product and service quality. 2006b. Another possible reason why outcome indicators are often used in some countries is that available data refer to routine information systems (administrative archives) which regularly record clinical aspects and other dimension useful for case mix adjustment. ij Rothwell PM, Warlow CP. ij (assumed to have a normal distribution with zero mean and variance o = Part II. Koran LM. Statistical power depends upon how common the occurrence of the outcome is. Third, since differences in the quality of care within hospitals (e.g., DRGs and/or Specialties) may be greater than differences between hospitals, there is no clear evidence of high correlation between how well a hospital performs on one standard of effective care and how well it performs on another. In France, generalizations of the Indicateurs pour l'amlioration de la qualit et de la scurit des soins (IPAQSS Indicators for Improvement of Service Quality and Safety) (HAS 2009) and of the Tableau de bord des infections nosocomiales (Nosocomial Infections Dashboard) were also aimed at comparing indicators among healthcare organizations (MTES 2011). Indicating What does benchmarking mean in healthcare? Some of our publications are also available in hard copy, but this may entail a small charge. 2007. o can be thought as the total score obtained by summing scores for patient i in hospital j over K administered tests or as a composite score, estimated by using one of the known models for continuous latent variables. corrected for measurement error, #rescaled with scale correction factor. Set future performance targets (objectives). 0j) is adjusted for the effects of the P person-level characteristics (x Process measures have two important advantages over outcome measures. All these approaches are based on the same elements: multidisciplinary and multi-site characteristics, the implementation of improvement initiatives, and measurement. Benchmarking's key characteristic is that it is part of a comprehensive and participative policy of continuous quality improvement. The contribution of benchmarking to quality improvement in healthcare 2006). Philippe Michel, Public Health Physician & Director, Comit de coordination de l'valuation clinique et de la qualit en Aquitaine (CCECQA), Bordeaux, France. ij) from the expected outcome ( 2007). We retained 68 of these articles for full reading, and we excluded 765 articles that did not meet the inclusion criteria, 121 that were duplicates and nine whose full text could not be retrieved (Figure (Figure1).1). If a large proportion of adverse events are concentrated among relatively few hospitals, the traditional quality control approach targeting error prone, ineffective health structures for specific attention has high potential value.