Heuristics for the sustainable harvest of wildlife in stochastic social-ecological systems.

Sustainable wildlife harvest is challenging due to the complexity of uncertain social-ecological systems, and diverse stakeholder perspectives of sustainability. In these systems, semi-complex stochastic simulation models can provide heuristics that bridge the gap between highly simplified theoretical models and highly context-specific case-studies. Such heuristics allow for more nuanced recommendations in low-knowledge contexts, and an improved understanding of model sensitivity and transferability to novel contexts. We develop semi-complex Management Strategy Evaluation (MSE) models capturing dynamics and variability in ecological processes, monitoring, decision-making, and harvest implementation, under a diverse range of contexts. Results reveal the fundamental challenges of achieving sustainability in wildlife harvest. Environmental contexts were important in determining optimal harvest parameters, but overall, evaluation contexts more strongly influenced perceived outcomes, optimal harvest parameters and optimal harvest strategies. Importantly, simple composite metrics popular in the theoretical literature (e.g. focusing on maximizing yield and population persistence only) often diverged from more holistic composite metrics that include a wider range of population and harvest objectives, and better reflect the trade-offs in real world applied contexts. While adaptive harvest strategies were most frequently preferred, particularly for more complex environmental contexts (e.g. high uncertainty or variability), our simulations map out cases where these heuristics may not hold. Despite not always being the optimal solution, overall adaptive harvest strategies resulted in the least value forgone, and are likely to give the best outcomes under future climatic variability and uncertainty. This demonstrates the potential value of heuristics for guiding applied management.

A SBM-DEA based performance evaluation and optimization for social organizations participating in community and home-based elderly care services.

The community and home-based elderly care service system has been proved an effective pattern to mitigate the elderly care dilemma under the background of accelerating aging in China. In particular, the participation of social organizations in community and home-based elderly care service has powerfully fueled the multi-supply of elderly care. As the industry of the elderly care service is in the ascendant, the management lags behind, resulting in the waste of significant social resources. Therefore, performance evaluation is proposed to resolve this problem. However, a systematic framework for evaluating performance of community and home-based elderly care service centers (CECSCs) is absent. To overcome this limitation, the SBM-DEA model is introduced in this paper to evaluate the performance of CECSCs. 186 social organizations in Nanjing were employed as an empirical study to develop the systematic framework for performance evaluation. Through holistic analysis of previous studies and interviews with experts, a systematic framework with 33 indicators of six dimensions (i.e., financial management, hardware facilities, team building, service management, service object and organization construction) was developed. Then, Sensitivity Analysis is used to screen the direction of performance optimization and specific suggestions were put forward for government, industrial associations and CECSCs to implement. The empirical study shows the proposed framework using SBM-DEA and sensitivity analysis is viable for conducting performance evaluation and improvement of CECSCs, which is conducive to the sustainable development of CECSCs.

A neurodynamic optimization approach to supervised feature selection via fractional programming.

Feature selection is an important issue in machine learning and data mining. Most existing feature selection methods are greedy in nature thus are prone to sub-optimality. Though some global feature selection methods based on unsupervised redundancy minimization can potentiate clustering performance improvements, their efficacy for classification may be limited. In this paper, a neurodynamics-based holistic feature selection approach is proposed via feature redundancy minimization and relevance maximization. An information-theoretic similarity coefficient matrix is defined based on multi-information and entropy to measure feature redundancy with respect to class labels. Supervised feature selection is formulated as a fractional programming problem based on the similarity coefficients. A neurodynamic approach based on two one-layer recurrent neural networks is developed for solving the formulated feature selection problem. Experimental results with eight benchmark datasets are discussed to demonstrate the global convergence of the neural networks and superiority of the proposed neurodynamic approach to several existing feature selection methods in terms of classification accuracy, precision, recall, and F-measure.

Informed Clustering of Donation Service Areas for Improved Benchmarking.

The donation community continuously strives to collaborate and share effective practices to further the mission of saving and healing lives. Donation service areas in which the Organ Procurement Organizations (OPOs) work are multifaceted in their demographics, inciting the Organ Procurement and Transplantation Network to consider a more holistic and objective measure of similarity rather than the size of population alone or locational proximity alone. This would allow OPOs, as a part of their quality improvement efforts, to learn from and mentor other organizations that are dealing with similar challenges. By incorporating multiple informative characteristics together, we can distinguish those likenesses only revealed by taking into account multiple factors simultaneously. We used statistical approaches that take many characteristics of interest describing a donation service area and purposely excluded performance measures that an OPO may be able to influence by their own practices. Unsupervised learning methods combined the original characteristics into a smaller number of new variables, eliminating correlation and overlap in information from the original characteristics, and clustered donation service areas based on the general characteristics and population of the area. This analysis is a first step in providing a different perspective for OPOs to learn from other organizations that may face similar challenges, as well as to share best practices and open new lines of communication.

Benchmarking Data Sets from PubChem BioAssay Data: Current Scenario and Room for Improvement.

Developing realistic data sets for evaluating virtual screening methods is a task that has been tackled by the cheminformatics community for many years. Numerous artificially constructed data collections were developed, such as DUD, DUD-E, or DEKOIS. However, they all suffer from multiple drawbacks, one of which is the absence of experimental results confirming the impotence of presumably inactive molecules, leading to possible false negatives in the ligand sets. In light of this problem, the PubChem BioAssay database, an open-access repository providing the bioactivity information of compounds that were already tested on a biological target, is now a recommended source for data set construction. Nevertheless, there exist several issues with the use of such data that need to be properly addressed. In this article, an overview of benchmarking data collections built upon experimental PubChem BioAssay input is provided, along with a thorough discussion of noteworthy issues that one must consider during the design of new ligand sets from this database. The points raised in this review are expected to guide future developments in this regard, in hopes of offering better evaluation tools for novel in silico screening procedures.

Developing a template matching algorithm for benchmarking hospital performance in a diverse, integrated healthcare system.

Template matching is a proposed approach for hospital benchmarking, which measures performance based on matching a subset of comparable patient hospitalizations from each hospital. We assessed the ability to create the required matched samples and thus the feasibility of template matching to benchmark hospital performance in a diverse healthcare system.Nationwide Veterans Affairs (VA) hospitals, 2017.Observational cohort study.We used administrative and clinical data from 668,592 hospitalizations at 134 VA hospitals in 2017. A standardized template of 300 hospitalizations was selected, and then 300 hospitalizations were matched to the template from each hospital.There was substantial case-mix variation across VA hospitals, which persisted after excluding small hospitals, hospitals with primarily psychiatric admissions, and hospitalizations for rare diagnoses. Median age ranged from 57 to 75 years across hospitals; percent surgical admissions ranged from 0.0% to 21.0%; percent of admissions through the emergency department, 0.1% to 98.7%; and percent Hispanic patients, 0.2% to 93.3%. Characteristics for which there was substantial variation across hospitals could not be balanced with any matching algorithm tested. Although most other variables could be balanced, we were unable to identify a matching algorithm that balanced more than ∼20 variables simultaneously.We were unable to identify a template matching approach that could balance hospitals on all measured characteristics potentially important to benchmarking. Given the magnitude of case-mix variation across VA hospitals, a single template is likely not feasible for general hospital benchmarking.

Reliable identification of cardiac liability in drug discovery using automated patch clamp: Benchmarking best practices and calibration standards for improved proarrhythmic assessment.

INTRODUCTION: Screening compounds for activity on the hERG channel using patch clamp is a crucial part of safety testing. Automated patch clamp (APC) is becoming widely accepted as an alternative to manual patch clamp in order to increase throughput whilst maintaining data quality. In order to standardize APC experiments, we have investigated the effects on IC50 values under different conditions using several devices across multiple sites. METHODS: APC instruments SyncroPatch 384i, SyncroPatch 384PE and Patchliner, were used to record hERG expressed in HEK or CHO cells. Up to 27 CiPA compounds were used to investigate effects of voltage protocol, incubation time, labware and time between compound preparation and experiment on IC50 values. RESULTS: All IC50 values of 21 compounds recorded on the SyncroPatch 384PE correlated well with IC50 values from the literature (Kramer et al., 2013) regardless of voltage protocol or labware, when compounds were used immediately after preparation, but potency of astemizole decreased if prepared in Teflon or polypropylene (PP) compound plates 2-3 h prior to experiments. Slow acting compounds such as dofetilide, astemizole, and terfenadine required extended incubation times of at least 6 min to reach steady state and therefore, stable IC50 values. DISCUSSION: Assessing the influence of different experimental conditions on hERG assay reliability, we conclude that either the step-ramp protocol recommended by CiPA or a standard 2-s step-pulse protocol can be used to record hERG; a minimum incubation time of 5 min should be used and although glass, Teflon, PP or polystyrene (PS) compound plates can be used for experiments, caution should be taken if using Teflon, PS or PP vessels as some adsorption can occur if experiments are not performed immediately after preparation. Our recommendations are not limited to the APC devices described in this report, but could also be extended to other APC devices.

Benchmarking biopharmaceutical process development and manufacturing cost contributions to R&D.

This study aims to benchmark and analyze the process development and manufacturing costs across the biopharmaceutical drug development cycle and their contribution to overall research and development (R&D) costs. This was achieved with a biopharmaceutical drug development lifecycle cost model that captured the costs, durations, risks and interdependencies of the clinical, process development and manufacturing activities. The budgets needed for process development and manufacturing at each phase of development to ensure a market success each year were estimated. The impact of different clinical success rate profiles on the process development and manufacturing costs at each stage was investigated, with a particular focus on monoclonal antibodies. To ensure a market success each year with an overall clinical success rate (Phase I to approval) of ~12%, the model predicted that a biopharmaceutical company needs to allocate process development and manufacturing budgets in the order of ~$60 M for pre-clinical to Phase II material preparation and ~$70 M for Phase III to regulatory review material preparation. For lower overall clinical success rates of ~4%, which are more indicative of diseases such as Alzheimer's, these values increase to ~$190 M for early-phase and ~$140 Mfor late-phase material preparation; hence, the costs increase 2.5 fold. The costs for process development and manufacturing per market success were predicted to represent 13-17% of the R&D budget from pre-clinical trials to approval. The results of this quantitative structured cost study can be used to aid decision-making during portfolio management and budget planning procedures in biopharmaceutical development.

Nutritional management of patients with oesophageal cancer throughout the treatment trajectory: benchmarking against best practice.

PURPOSE: Oesophageal cancer (OC) impacts nutritional status and outcomes. This study aims to benchmark the current nutrition management of patients with OC against best practice recommendations, identify critical points in the treatment trajectory where nutritional status is compromised, service gaps and opportunities for improvement. METHODS: A retrospective audit collected demographic, medical and nutritional data from medical records of patients who received curative treatment for OC at a tertiary referral hospital in Sydney, Australia. RESULTS: Thirty-seven patient records were audited over the time period. Twenty-nine patients underwent nutrition screening on admission to the service. Eighteen out of 25 patients receiving neoadjuvant radiation therapy, all patients during surgical admission, and only 19 patients at postsurgical discharge were seen by a dietitian. All patients received tube feeding post-operatively; however, initiation within 24 h only occurred for 14 patients. Weight significantly declined over the course of treatment (p < 0.001), whilst malnutrition during surgical admission (p = 0.004) and postsurgical discharge (p = 0.038) were both associated with significantly higher unplanned readmissions. CONCLUSIONS: Best practice recommendations were met for aspects of the immediate post-operative period; however, service gaps remain during pre-operative and post-discharge care. Findings from this study indicate that nutritional care is inconsistent across different treatment stages, and malnutrition impacts negatively on unplanned readmission. Research is needed to address evidence-practice gaps, assess appropriateness of recommendations and provide evidence for models of care during multimodality treatments and across different services.

Identifying and prioritising midwifery care process metrics and indicators: a Delphi survey and stakeholder consensus process.

BACKGROUND: Measuring care processes is an important component of any effort to improve care quality, however knowing the appropriate metrics to measure is a challenge both in Ireland and other countries. Quality of midwifery care depends on the expert knowledge of the midwife and her/his contribution to women and their babies' safety in the healthcare environment. Therefore midwives need to be able to clearly articulate and measure what it is that they do, the dimensions of their professional practice frequently referred to as midwifery care processes. The objective of this paper is to report on the development and prioritisation of a national suite of Quality Care Metrics (QCM), and their associated indicators, for midwifery care processes in Ireland. METHODS: The study involved four discrete, yet complimentary, phases; i) a systematic literature review to identify midwifery care process metrics and their associated measurement indicators; ii) a two-round, online Delphi survey of midwives to develop consensus on the set of midwifery care process metrics to be measured; iii) a two-round online Delphi survey of midwives to develop consensus on the indicators that will be used to measure prioritised metrics; and iv) a face-to-face consensus meeting with midwives to review the findings and achieve consensus on the final suite of metrics and indicators. RESULTS: Following the consensus meeting, 18 metrics and 93 indicators were prioritised for inclusion in the suite of QCM Midwifery Metrics. These metrics span the pregnancy, birth and postpartum periods. CONCLUSION: The development of this suite of process metrics and indicators for midwifery care provides an opportunity for measuring the safety and quality of midwifery care in Ireland and for adapting internationally. This initial work should be followed by a rigorous evaluation of the impact of the new suite of metrics on midwifery care processes.

Primary care physician resource use changes associated with feedback reports.

OBJECTIVES: To measure changes in primary care physician (PCP) ordering rates for 4 global resource use measures before and after dissemination of physician feedback reports that provided peer-comparison resource use rates. We also explored whether physician practice characteristics (panel size, clinic size, and years of experience) were associated with resource use changes. STUDY DESIGN: Pre-post implementation study measuring physician resource use in an integrated healthcare system (2011-2014). METHODS: Kaiser Permanente Washington PCPs (N = 210) were provided annual feedback reports showing their personal ordering rates compared with those of their peers. Monthly physician ordering was measured from November 2011 to September 2014 (including prereport and postreport periods). We examined 4 physician ordering rates (specialty referrals, high-end imaging, laboratory tests, and 30-day prescriptions) per 1000 patients, adjusted for patient age, gender, and clinical complexity. RESULTS: After accounting for physician practice characteristics, monthly PCP ordering rates for high-end imaging significantly decreased by 0.8 images per 1000 patients (P <.01). In contrast, orders for laboratory tests and 30-day prescriptions significantly increased by 15.0 tests and 84.7 prescriptions per 1000 patients (both P <.01). We observed greater changes following feedback in physicians with fewer years of experience (≤10 years), who had 4.2 fewer specialty referrals (P = .01) and 101.3 more 30-day prescriptions (P <.01) compared with those with more experience (>20 years). CONCLUSIONS: Physician feedback reports may be associated with changes in physician resource use, and physicians with fewer years of experience may be more responsive to feedback reports. Better understanding of factors associated with changes in resource use is necessary for future targeted development of physician interventions.

Benchmarking Cancer Centers: From Care Pathways to Integrated Practice Units.

Background: Structuring cancer care into pathways can reduce variability in clinical practice and improve patient outcomes. International benchmarking can help centers with regard to development, implementation, and evaluation. A further step in the development of multidisciplinary care is to organize care in integrated practice units (IPUs), encompassing the whole pathway and relevant organizational aspects. However, research on this topic is limited. This article describes the development and results of a benchmark tool for cancer care pathways and explores IPU development in cancer centers. Methods: The benchmark tool was developed according to a 13-step benchmarking method and piloted in 7 European cancer centers. Centers provided data and site visits were performed to understand the context in which the cancer center operates and to clarify additional questions. Benchmark data were structured into pathway development and evaluation and assessed against key IPU features. Results: Benchmark results showed that most centers have formalized multidisciplinary pathways and that care teams differed in composition, and found almost 2-fold differences in mammography use efficiency. Suggestions for improvement included positioning pathways formally and structurally evaluating outcomes at a sufficiently high frequency. Based on the benchmark, 3 centers indicating that they had a breast cancer IPU were scored differently on implementation. Overall, we found that centers in Europe are in various stages of development of pathways and IPUs, ranging from an informal pathway structure to a full IPU-type of organization. Conclusions: A benchmark tool for care pathways was successfully developed and tested, and is available in an open format. Our tool allows for the assessment of pathway organization and can be used to assess the status of IPU development. Opportunities for improvement were identified regarding the organization of care pathways and the development toward IPUs. Three centers are in varying degrees of implementation and can be characterized as breast cancer IPUs. Organizing cancer care in an IPU could yield multiple performance improvements.

Implementation of the Western Australian Osteoporosis Model of Care: a fracture liaison service utilising emergency department information systems to identify patients with fragility fracture to improve current practice and reduce re-fracture rates: a 12-month analysis.

Fracture liaison service linked to an emergency department database effectively identifies patients with OP, improves best practice care, reduces recurrent fractures, and improves quality of life (QoL). The next step is to establish cost-effectiveness. This should be seen as the standard model of care. INTRODUCTION: The Western Australian Osteoporosis Model of Care recommends implementation of a fracture liaison service (FLS) to manage patients with minimal trauma fractures (MTFs). This study evaluates the efficacy of a FLS linked to a tertiary hospital emergency department information system (EDIS) in reducing recurrent fractures. METHODS: Patients aged ≥ 50 years with MTF identified from EDIS were invited to the FLS. Patient outcomes were compared to routine care (retrospective group-same hospital, and prospective group-other hospital) at 3- and 12-month follow-up. RESULTS: Two hundred forty-one of 376 (64.1%) eligible patients participated in the FLS with 12 months of follow-up. Absolute risk of recurrent MTF at 12 months was reduced by 9.2 and 10.2% compared with the prospective and retrospective controls, respectively. After age/sex adjustment, FLS participants had less MTF at 12 months vs. the retrospective controls, OR 0.38 (95%CI 0.18-0.79), but not the prospective controls, OR 0.40 (95%CI 0.16-1.01). FLS patients were more likely to receive the 'best practice' care, i.e. awareness of osteoporosis, investigations, and treatment (all p < 0.05). 'Fallers' (OR 0.48 (95%CI 0.24, 0.96)) and fall rates were lower in the FLS (p = 0.001) compared to the prospective control. FLS experienced the largest improvement in QoL from 3 to 12 months as measured by the EuroQoL 5-domain (EQ-5D) UK weighted score (+ 15 vs. - 11 vs. - 16%, p < 0.001) and EQ-5D Health State visual analogue scale (+ 29 vs. - 2 vs. + 1%, p < 0.001). CONCLUSION: Patients managed in a linked EDIS-FLS were more likely to receive the 'best practice' care and had lower recurrent MTF and improved QoL.

Incorporating Longitudinal Comorbidity and Acute Physiology Data in Template Matching for Assessing Hospital Quality: An Exploratory Study in an Integrated Health Care Delivery System.

OBJECTIVE: We sought to build on the template-matching methodology by incorporating longitudinal comorbidities and acute physiology to audit hospital quality. STUDY SETTING: Patients admitted for sepsis and pneumonia, congestive heart failure, hip fracture, and cancer between January 2010 and November 2011 at 18 Kaiser Permanente Northern California hospitals. STUDY DESIGN: We generated a representative template of 250 patients in 4 diagnosis groups. We then matched between 1 and 5 patients at each hospital to this template using varying levels of patient information. DATA COLLECTION: Data were collected retrospectively from inpatient and outpatient electronic records. PRINCIPAL FINDINGS: Matching on both present-on-admission comorbidity history and physiological data significantly reduced the variation across hospitals in patient severity of illness levels compared with matching on administrative data only. After adjustment for longitudinal comorbidity and acute physiology, hospital rankings on 30-day mortality and estimates of length of stay were statistically different from rankings based on administrative data. CONCLUSIONS: Template matching-based approaches to hospital quality assessment can be enhanced using more granular electronic medical record data.

[Results of stroke care in Hungary in the frame of international comparison]. / A stroke-ellátás hazai eredményei a nemzetközi adatok tükrében.

INTRODUCTION: The EuroHOPE FP7 project analysed the effectiveness and efficiency of stroke care between 2010 and 2014. AIM: The study introduces Hungarian data in comparison with international results and explores the causes of differences. METHOD: The analysis was performed on data available from regular data collection in Finland, The Netherlands, Hungary, Italy, Scotland, and Sweden, with standardized indicators. Hungarian data was analysed between 2005 and 2009, and the international benchmarking in 2008, with multivariate logistic regression analysis for risk adjustment. RESULTS: Stroke incidence in Hungary was the double of the Italian or Finnish results (43.3/10,000 inhabitants), while comorbidities did not differ among countries. In Hungary, 19.9% of patients purchased anti-coagulants, one-third of the rate in Finland. One-year mortality in Hungary was 30%, the worst among the countries. Possible causes are inadequate prevention, more severe status of patients, and deficiencies of hospital care and rehabilitation. CONCLUSION: Causal analysis of these results and corrective measurements are recommended. Orv. Hetil., 2016, 157(41), 1635-1641.

Single Particle and PET-based Platform for Identifying Optimal Plasmonic Nano-Heaters for Photothermal Cancer Therapy.

Plasmonic nanoparticle-based photothermal cancer therapy is a promising new tool to inflict localized and irreversible damage to tumor tissue by hyperthermia, without harming surrounding healthy tissue. We developed a single particle and positron emission tomography (PET)-based platform to quantitatively correlate the heat generation of plasmonic nanoparticles with their potential as cancer killing agents. In vitro, the heat generation and absorption cross-section of single irradiated nanoparticles were quantified using a temperature sensitive lipid-based assay and compared to their theoretically predicted photo-absorption. In vivo, the heat generation of irradiated nanoparticles was evaluated in human tumor xenografts in mice using 2-deoxy-2-[F-18]fluoro-D-glucose ((18)F-FDG) PET imaging. To validate the use of this platform, we quantified the photothermal efficiency of near infrared resonant silica-gold nanoshells (AuNSs) and benchmarked this against the heating of colloidal spherical, solid gold nanoparticles (AuNPs). As expected, both in vitro and in vivo the heat generation of the resonant AuNSs performed superior compared to the non-resonant AuNPs. Furthermore, the results showed that PET imaging could be reliably used to monitor early treatment response of photothermal treatment. This multidisciplinary approach provides a much needed platform to benchmark the emerging plethora of novel plasmonic nanoparticles for their potential for photothermal cancer therapy.

Benchmarking road safety of U.S. states: a DEA-based Malmquist productivity index approach.

In this study, a DEA based Malmquist index model was developed to assess the relative efficiency and productivity of U.S. states in decreasing the number of road fatalities. Even though the national trend in fatal crashes has reached to the lowest level since 1949 (Traffic Safety Annual Assessment Highlights, 2010), a state-by-state analysis and comparison has not been studied considering other characteristics of the holistic national road safety assessment problem in any work in the literature or organizational reports. In this study, a DEA based Malmquist index model was developed to assess the relative efficiency and productivity of 50 U.S. states in reducing the number of fatal crashes. The single output, fatal crashes, and five inputs were aggregated into single road safety score and utilized in the DEA-based Malmquist index mathematical model. The period of 2002-2008 was considered due to data availability for the inputs and the output considered. According to the results, there is a slight negative productivity (an average of -0.2 percent productivity) observed in the U.S. on minimizing the number of fatal crashes along with an average of 2.1 percent efficiency decline and 1.8 percent technological improvement. The productivity in reducing the fatal crashes can only be attributed to the technological growth since there is a negative efficiency growth is occurred. It can be concluded that even though there is a declining trend observed in the fatality rates, the efficiency of states in utilizing societal and economical resources towards the goal of zero fatality is not still efficient. More effective policy making towards increasing safety belt usage and better utilization of safety expenditures to improve road condition are derived as the key areas to focus on for state highway safety agencies from the scope of current research.

Improving the reliability of physician "report cards".

BACKGROUND: Performance measures are widely used to profile primary care physicians (PCPs) but their reliability is often limited by small sample sizes. We evaluated the reliability of individual PCP profiles and whether they can be improved by combining measures into composites or by profiling practice groups. METHODS: We performed a cross-sectional analysis of electronic health record data for patients with diabetes (DM), congestive heart failure (CHF), ischemic vascular disease (IVD), or eligible for preventive care services seen by a PCP within a large, integrated health care system between April 2009 and May 2010. We evaluated performance on 14 measures of DM care, 9 of CHF, 7 of IVD, and 4 of preventive care. RESULTS: There were 51,771 patients observed by 163 physicians in 17 clinics. Few PCPs (0%-60%) could be profiled with 80% reliability using single process or intermediate-outcome measures. Combining measures into single-disease composites improved reliability for DM and preventive care with 74.5% and 76.7% of PCPs having sufficient panel sizes, but composites remained unreliable for CHF and IVD. A total of 85.3% of PCPs could be reliably profiled using a single overall composite. Aggregating PCPs into practice groups (3 to 21 PCPs per group) did not improve reliability in most cases because of little between-group practice variation. CONCLUSIONS: Single measures rarely differentiate between individual PCPs or groups of PCPs reliably. Combining measures into single-disease or multidisease composites can improve reliability for some common conditions, but not all. Assessing PCP practice groups within a single health care system, rather than individual PCPs, did not substantially improve reliability.

Analysis of metrics for the usability evaluation of EHR management systems.

Electronic health records are replacing conventional paper-based health records. For a doctor it is a working instrument, which can significantly reduce the time spent on paper work. Patients can benefit from accessing the electronic health records even though they usually do not have a medical background. Therefore, when specifying a graphical user interface (GUI) it is necessary to take into account the requirements of the different users: e.g. the functionality for the doctors and the presentation of data in an understandable manner for the patients. The study aims to review and analyze metrics used to evaluate the usability of user interfaces in health information systems. The scope of the search included the analysis of existing usability evaluating metrics that are applied both in healthcare and other domains, where the standard of storage and presentation of information are applied. We identified a set of metrics and evaluation methods that provide holistic evaluation facilities for graphical user interfaces.