How to identify when a performance indicator has run its course

The official published version can be found at the link below.Increasing numbers of countries are using indicators to evaluate the quality of clinical care, with some linking payment to achievement. For performance frameworks to remain effective the indicators need to be regularly reviewed. The frameworks cannot cover all clinical areas, and achievement on chosen indicators will eventually reach a ceiling beyond which further improvement is not feasible. However, there has been little work on how to select indictors for replacement. The Department of Health decided in 2008 that it would regularly replace indicators in the national primary care pay for performance scheme, the Quality and Outcomes Framework, making a rigorous approach to removal a priority. We draw on our previous work on pay for performance and our current work advising the National Institute for Health and Clinical Excellence (NICE) on the Quality and Outcomes Framework to suggest what should be considered when planning to remove indicators from a clinical performance framework

Analysing indicators of performance, satisfaction, or safety using empirical logit transformation

This is the final version of the article. Available from the publisher via the DOI in this record.Performance, satisfaction, and safety indicators are commonly measured on a percentage scale. Such indicators are often subject to ceiling or floor effects and performance may be inherently non-linear. For example, improving from 85% to 95% might be more difficult and need more effort than improving from 55% to 65%. As such, analysis of these indicators is not always straightforward and standard linear analysis could be problematic. We present the most common approach to dealing with this problem: a logit transformation of the score, following which standard linear analysis can be conducted on the transformed score. We also demonstrate how estimates can be back-transformed to percentages for easier communication of findings. In this paper, we discuss the benefits of this method, use algebra to describe the relevant steps in the transformation process, provide guidance on interpretation, and provide a tool for analysis.UK Medical Research Council Health eResearch Centre grant MR/K006665/1 supported the time and facilities of EK

Withdrawing performance indicators: retrospective analysis of general practice performance under UK Quality and Outcomes Framework.

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.OBJECTIVES: To investigate the effect of withdrawing incentives on recorded quality of care, in the context of the UK Quality and Outcomes Framework pay for performance scheme. DESIGN: Retrospective longitudinal study. SETTING: Data for 644 general practices, from 2004/05 to 2011/12, extracted from the Clinical Practice Research Datalink. PARTICIPANTS: All patients registered with any of the practices over the study period-13,772,992 in total. INTERVENTION: Removal of financial incentives for aspects of care for patients with asthma, coronary heart disease, diabetes, stroke, and psychosis. MAIN OUTCOME MEASURES: Performance on eight clinical quality indicators withdrawn from a national incentive scheme: influenza immunisation (asthma) and lithium treatment monitoring (psychosis), removed in April 2006; blood pressure monitoring (coronary heart disease, diabetes, stroke), cholesterol concentration monitoring (coronary heart disease, diabetes), and blood glucose monitoring (diabetes), removed in April 2011. Multilevel mixed effects multiple linear regression models were used to quantify the effect of incentive withdrawal. RESULTS: Mean levels of performance were generally stable after the removal of the incentives, in both the short and long term. For the two indicators removed in April 2006, levels in 2011/12 were very close to 2005/06 levels, although a small but statistically significant drop was estimated for influenza immunisation. For five of the six indicators withdrawn from April 2011, no significant effect on performance was seen following removal and differences between predicted and observed scores were small. Performance on related outcome indicators retained in the scheme (such as blood pressure control) was generally unaffected. CONCLUSIONS: Following the removal of incentives, levels of performance across a range of clinical activities generally remained stable. This indicates that health benefits from incentive schemes can potentially be increased by periodically replacing existing indicators with new indicators relating to alternative aspects of care. However, all aspects of care investigated remained indirectly or partly incentivised in other indicators, and further work is needed to assess the generalisability of the findings when incentives are fully withdrawn.National Institute for Health Research (NIHR

Effect of financial incentives on incentivised and non-incentivised clinical activities: longitudinal analysis of data from the UK Quality and Outcomes Framework

This is the final version. Available on open access from BMJ Publishing Group via the DOI in this recordData sharing: Technical appendix and statistical code available from the corresponding author ([email protected]). The dataset was derived from the General Practice Research Database and is not available from the authors, but it can be derived on application to GPRD.OBJECTIVE: To investigate whether the incentive scheme for UK general practitioners led them to neglect activities not included in the scheme. DESIGN: Longitudinal analysis of achievement rates for 42 activities (23 included in incentive scheme, 19 not included) selected from 428 identified indicators of quality of care. SETTING: 148 general practices in England (653 500 patients). MAIN OUTCOME MEASURES: Achievement rates projected from trends in the pre-incentive period (2000-1 to 2002-3) and actual rates in the first three years of the scheme (2004-5 to 2006-7). RESULTS: Achievement rates improved for most indicators in the pre-incentive period. There were significant increases in the rate of improvement in the first year of the incentive scheme (2004-5) for 22 of the 23 incentivised indicators. Achievement for these indicators reached a plateau after 2004-5, but quality of care in 2006-7 remained higher than that predicted by pre-incentive trends for 14 incentivised indicators. There was no overall effect on the rate of improvement for non-incentivised indicators in the first year of the scheme, but by 2006-7 achievement rates were significantly below those predicted by pre-incentive trends. CONCLUSIONS: There were substantial improvements in quality for all indicators between 2001 and 2007. Improvements associated with financial incentives seem to have been achieved at the expense of small detrimental effects on aspects of care that were not incentivised.There was no direct funding for this study, but the National Primary Care Research and Development Centre receives core funding from the UK Department of Health

Football-induced fatigue in hypoxia impairs repeated sprint ability and perceptual-cognitive skills

The present study investigated the effects of football-induced fatigue during hypoxia on RS and perceptual-cognitive skills. Ten male semi-professional football players underwent four sessions; a control session (0-m) to quantify RS in a non-fatigued state; and three further sessions at hypoxia (0-m;1500-m;3000-m) examining RS and perceptual-cognitive skill responses for a given physical workload. Anticipation and decision-making accuracy were obtained at the 30-min mark of each half. The mean number of trials (%) in which the player made the correct response was used for analysis. HR, TC, RPE and % saturation of O2 were measured during the warm-up, football-induced fatigue and RS test. It was found that HR, RPE and % saturation of O2 were different between conditions (P<0.05; ES=0.44-6.13). Further, RS were affected by football-induced fatigue for DC (4.8%; P=0.019; ES=0.68) and AV (5.5%; P=0.006; ES=0.79). In hypoxia, it was observed that football-induced fatigue decreased by 6.5% in DC, 6.3% in AV and 3.1% in PV at 1500-m compared to 0-m (P<0.05). Further significant changes were found at 3000-m compared to 0-m decreasing 12.8% in DC, 12.8% in AV and 6.2% in PV (P<0.0005). More pronounced declines in perceptual-cognitive skills were found as altitude increased (5.0-12.5 %; P<0.05; ES=1.17-2.41) and between both halves (5.3-6.7 %; P<0.05). The data demonstrates that the RS test was highly sensitive to fatigue and hypoxia for a given physical load. Simulated matches in hypoxia revealed larger decreases, when compared to normoxia in RS and perceptual-cognitive skills, highlighting the need for optimal acclimatisation strategies, including physical and technical preparation, prior to playing a

N-player quantum games in an EPR setting

The $N$-player quantum game is analyzed in the context of an Einstein-Podolsky-Rosen (EPR) experiment. In this setting, a player's strategies are not unitary transformations as in alternate quantum game-theoretic frameworks, but a classical choice between two directions along which spin or polarization measurements are made. The players' strategies thus remain identical to their strategies in the mixed-strategy version of the classical game. In the EPR setting the quantum game reduces itself to the corresponding classical game when the shared quantum state reaches zero entanglement. We find the relations for the probability distribution for $N$-qubit GHZ and W-type states, subject to general measurement directions, from which the expressions for the mixed Nash equilibrium and the payoffs are determined. Players' payoffs are then defined with linear functions so that common two-player games can be easily extended to the $N$-player case and permit analytic expressions for the Nash equilibrium. As a specific example, we solve the Prisoners' Dilemma game for general $N \ge 2$. We find a new property for the game that for an even number of players the payoffs at the Nash equilibrium are equal, whereas for an odd number of players the cooperating players receive higher payoffs.Comment: 26 pages, 2 figure

Presymptomatic risk assessment for chronic non-communicable diseases

The prevalence of common chronic non-communicable diseases (CNCDs) far overshadows the prevalence of both monogenic and infectious diseases combined. All CNCDs, also called complex genetic diseases, have a heritable genetic component that can be used for pre-symptomatic risk assessment. Common single nucleotide polymorphisms (SNPs) that tag risk haplotypes across the genome currently account for a non-trivial portion of the germ-line genetic risk and we will likely continue to identify the remaining missing heritability in the form of rare variants, copy number variants and epigenetic modifications. Here, we describe a novel measure for calculating the lifetime risk of a disease, called the genetic composite index (GCI), and demonstrate its predictive value as a clinical classifier. The GCI only considers summary statistics of the effects of genetic variation and hence does not require the results of large-scale studies simultaneously assessing multiple risk factors. Combining GCI scores with environmental risk information provides an additional tool for clinical decision-making. The GCI can be populated with heritable risk information of any type, and thus represents a framework for CNCD pre-symptomatic risk assessment that can be populated as additional risk information is identified through next-generation technologies.Comment: Plos ONE paper. Previous version was withdrawn to be updated by the journal's pdf versio

rEHR: An R package for manipulating and analysing Electronic Health Record data

Research with structured Electronic Health Records (EHRs) is expanding as data becomes more accessible; analytic methods advance; and the scientific validity of such studies is increasingly accepted. However, data science methodology to enable the rapid searching/extraction, cleaning and analysis of these large, often complex, datasets is less well developed. In addition, commonly used software is inadequate, resulting in bottlenecks in research workflows and in obstacles to increased transparency and reproducibility of the research. Preparing a research-ready dataset from EHRs is a complex and time consuming task requiring substantial data science skills, even for simple designs. In addition, certain aspects of the workflow are computationally intensive, for example extraction of longitudinal data and matching controls to a large cohort, which may take days or even weeks to run using standard software. The rEHR package simplifies and accelerates the process of extracting ready-for-analysis datasets from EHR databases. It has a simple import function to a database backend that greatly accelerates data access times. A set of generic query functions allow users to extract data efficiently without needing detailed knowledge of SQL queries. Longitudinal data extractions can also be made in a single command, making use of parallel processing. The package also contains functions for cutting data by time-varying covariates, matching controls to cases, unit conversion and construction of clinical code lists. There are also functions to synthesise dummy EHR. The package has been tested with one for the largest primary care EHRs, the Clinical Practice Research Datalink (CPRD), but allows for a common interface to other EHRs. This simplified and accelerated work flow for EHR data extraction results in simpler, cleaner scripts that are more easily debugged, shared and reproduced