The impact of information technology resources on SMEs' innovation performance

This work aims to develop a research framework to examine the impact of information technology resources on the innovation performance of Saudi small-and-medium enterprises (SMEs). SMEs innovation capability influences growth and technological progress (Bruque & Moyano, 2007). However, many developing countries exhibit moderate or even low innovation performance. For instance, Saudi Arabia is ranked 54th by the Global Innovation Index (GII 2011). Innovation systems studies focus on the alignment between the interactions of innovation actors with their constantly changing environment toward better innovation performance (Etzkowitz & Leydesdorff, 2000). The dynamic capabilities of organisations have been highlighted as a crucial characteristic that helps to achieve a sustainable competitive advantage (Teece et al., 1997). The indirect impact IT resources on innovation performance represents an attractive research area (Benitez-Amado et al., 2010). Therefore, we argue that a closer look at Saudi SMEs information technology resources and their impact on the firm dynamic capabilities and innovation performance would make a significant contribution to existing knowledge. Areas such as the organisation strategies of developing countries, innovation management, dynamic capabilities, open innovation and strategic information systems are few examples of areas that might benefit from this work

Performance measurement systems and metrics: a framework for monitoring oil operations

Oil operations involve high levels of capital equipment and high capacity production processes for which performance measures can assist with monitoring production throughout the oil industry stages. The approach taken in this paper is to utilise the lifecycle approach of asset management as well as organisational resource factors in an integrative manner. This research will examine the use of performance measurement in both private and public oil companies with a focus on Developing Countries. National Oil companies are of national economic importance in Developing Countries. Thus purpose of this paper is to develop a conceptual framework for performance measures of current and future oil operations and the associated asset management for field operations. The approach taken is to recognise the national context and strategic drivers and then to examine within this context the three areas of: Asset Management; Oil Operations (including Technology and Development; Management approaches; Partnerships) and Performance Outcomes

Comparison of analyses of the QTLMAS XIII common dataset. II: QTL analysis

Background - Five participants of the QTL-MAS 2009 workshop applied QTL analyses to the workshop common data set which contained a time-related trait: cumulative yield. Underlying the trait were 18 QTLs for three parameters of a logistic growth curve that was used for simulating the trait. Methods - Different statistical models and methods were employed to detect QTLs and estimate position and effect sizes of QTLs. Here we compare the results with respect to the numbers of QTLs detected, estimated positions and percentage explained variance. Furthermore, limiting factors in the QTL detection are evaluated. Results - All QTLs for the asymptote and the scaling factor of the logistic curve were detected by at least one of the participants. Only one out of six of the QTLs for the inflection point was detected. None of the QTLs were detected by all participants. Dominant, epistatic and imprinted QTLs were reported while only additive QTLs were simulated. The power to map QTLs for the inflection point increased when more time points were added. Conclusions - For the detection of QTLs related to the asymptote and the scaling factor, there were no strong differences between the methods used here. Also, it did not matter much whether the time course data were analyzed per single time point or whether parameters of a growth curve were first estimated and then analyzed. In contrast, the power for detection of QTLs for the inflection point was very low and the frequency of time points appeared to be a limiting factor. This can be explained by a low accuracy in estimating the inflection point from a limited time range and a limited number of time points, and by the low correlation between the simulated values for this parameter and the phenotypic data available for the individual time point

Prioritising pre-hospital outcome measures with a multi-stakeholder group: a consensus methods study

Context: A consensus event to discuss and prioritise ambulance service care outcome measures was held with 43 participants from a range of professional backgrounds including Commissioners; Policy makers; clinicians; managers; academics and patient and public representatives. Problem: Ambulance services in England manage 8 million emergency calls per years and treat 6.5 million people. Services are currently unable to ascertain whether the care they provide is safe, effective and of good quality as they receive no information about patients once they have been discharged from their care. The lack of robust patient focussed outcome measures for ambulance care means there is no opportunity for identifying and sharing good practice, identifying problems and measuring the impact of service developments and innovations. Assessment of problem and analysis of its causes: Historically ambulance service performance has been measured using response time as a proxy measure for quality. Although the limitations of this measure are recognised there is a lack of consensus on which outcome measures are important and little opportunity to measure alternatives due to poor information on what happens to patients after their ambulance service contact. The PhOEBE NIHR research programme aims to develop a linked ambulance service and secondary care dataset and to assess quality of care in this patient group using outcome measures identified from the literature and in consultation with different stakeholder groups. This means that for the first time the ambulance service will be able to assess the quality of care they provide to patients, rather than just how quickly the ambulance arrived. Intervention: Potential outcome measures identified from 2 systematic reviews were categorised into 1 of 3 headings (Service/operational, patient management and patient outcomes) and participants were pre-allocated to a discussion group. All discussion groups contained participants representing a range of stakeholder view points. Participants took part in small group themed discussions relating to a number of pre-specified outcome measures. They were also able to add to the list of measures. Directly following the discussion participants voted on the importance of the outcome measures in relation to ambulance service care quality. This was done using Turning Point software. Participants rated each outcome measure as either ‘Essential’, ‘Desirable’ or ‘Irrelevant’ using individual key pads. The voting was done independently and anonymously. Real time results were displayed following each vote. Study design: We used an interactive voting system coupled with a modified nominal group technique for the prioritisation of potential ambulance service outcome measures. Strategy for change: Following on from this study the top ranking outcome measures will be further refined as part of a Delphi study, before using the outcome measures to assess ambulance service quality of care in our linked data sample. The methods for linking the ambulance service data to other health care information and the identified outcome measures will enable all UK ambulance services to assess the quality of care they provide to patients and the impact of any service changes on care quality and patient outcomes. Measurement of improvement: The results from the outcome prioritisation voting exercise were ranked based on the highest proportion of ‘Essential’ rated measures. Where over 50% of participants rated a measure as ‘Essential’ these were taken forward and considered in further consensus studies. Effects of changes: From undertaking the consensus event we have prioritised potential ambulance service outcome measures. Lessons learnt: We have established that it is possible to incorporate voting technology into consensus methodologies and provide real time results to participants. Message for others: This research prioritised ambulance service outcome measures. Out of the 40 number of measures considered, the top 5 measures were Accuracy of dispatch decisions; Completeness and accuracy of patient records; Accuracy of call taker identification of different conditions; pain measurement and symptom relief and Patient experience

Developing new ways of measuring the impact of ambulance service care

Background Pre-hospital care in England is provided by ambulance services who deliver a diverse range of services to over 9 million patients a year but there is limited evidence about the effectiveness of this care. Historically ambulance performance has been measured by response times rather than clinical need or effectiveness. Progress on developing more appropriate performance measures is constrained by a lack of information about what happens to patients and their outcome after the pre-hospital component of care. If ambulance service information about patients could be linked to process and outcome data further along the care pathway then relevant measurement tools could be developed that allow a better assessment of the impact of pre-hospital care. The Pre-hospital Outcomes for Evidence Based Evaluation (PhOEBE) project is a 5 year programme of research funded by the UK National Institute of Health Research. Aims & objectives The aim of the programme is to develop new ways of measuring the impact of care provided by the ambulance service to support quality improvement through monitoring, audit and service evaluation. The objectives are to: 1) Review and synthesise the research literature on pre-hospital care outcome measures and identify measures relevant to the NHS and patients for further development; 2) Create a dataset linking routinely collected pre-hospital data, hospital data and mortality data to provide outcome information; 3) Develop new ways of measuring process and outcome indicators including building risk adjustment models that predict the outcomes using the linked data; 4) Explore the practical use of the linked dataset and the risk adjustment models to measure the effectiveness and quality of ambulance service care. Research plans The programme has 4 linked stages; 1. Synthesis of evidence on outcome measures and identification of measures for further development - review and assessment of the evidence base on outcome measurement for pre-hospital care and a consensus studies to identify measures relevant to patients and NHS staff. 2: Linking pre-hospital data with other patient data sources – creating a single dataset that links ambulance service electronic care records with routinely collected Hospital Episode Statistics (HES) and national mortality data. 3. Development of risk adjustment models for outcomes in patients attended by the ambulance service – using the linked data to develop risk adjustment tools that will allow patient differences to be taken into account and differences between expected and actual outcomes to be detected. Particular emphasis will be made to include the broad EMS population and not specific conditions as has been the case in the past. 4. Testing the risk adjustment models to assess if they can be used to measure effectiveness and quality – exploring the practical application of the measures by using them to assess if different ways of providing ambulance service care result in different consequences for patients. Outputs, outcomes and impact The programme will: • Provide a summary of relevant evidence on pre-hospital care outcome measurement • Develop a method for linking healthcare information into a format that can be used to support quality improvement, is acceptable to patients and complies with information legislation • Develop population based models for measuring the impact of pre-hospital care that can be used to monitor quality and safety, evaluate new service innovations and support quality improvement • Provide added value by using routine information and NHS infrastructure to operationalise the process and outcome models so that they will be of use across the NHS Progress to date The programme commenced in June 2011 and ends in May 2016. Two systematic reviews of measures used to measure the impact of ambulance service care (one policy literature and one research literature based) have been completed as has a qualitative study of recent service users to identify aspects of service they value. Potential measures identified by these studies were presented at a consensus conference and then further refined in a Delphi study to prioritise and identify measures for further development. Linked data is currently being created and the next stage will be the development of risk adjusted predictive models for the final identified measures

Prehospital outcomes for ambulance service care: systematic review

Background: Ambulance service performance measurement has previously focused on response times and survival. We conducted a systematic review of the international literature on quality measures and outcomes relating to pre-hospital ambulance service care, aiming to identify a broad range of outcome measures to provide a more meaningful assessment of ambulance service care. Methods: We searched a number of electronic databases including CINAHL, the Cochrane Library, EMBASE, Medline, and Web of Science. For inclusion, studies had to report either research or evaluation conducted in a pre-hospital setting, published in the English language from 1982 to 2011, and reporting either outcome measures or specific outcome instruments. Results: Overall, 181 full-text articles were included: 83 (46%) studies from North America, 50 (28%) from Europe and 21 (12%) from the UK. A total of 176 articles were obtained after examining 257 full-text articles in detail from 5,088 abstracts screened. A further five papers were subsequently identified from references of the articles examined and studies known to the authors. There were 140 articles (77%) which contained at least one survival-related measure, 47 (34%) which included information about length of stay and 87 (48%) which identified at least one place of discharge as an outcome. Limitations: We encountered the problem of incomplete information, for instance studies not specifying which pain scales when these had been used or using survival without a specific time period. Conclusion and recommendations: In addition to measures relating to survival, length of stay and place of discharge, we identified 247 additional outcome measures. Few studies included patient reported or cost outcomes. By identifying a wide range of outcome measures this review will inform further research looking at the feasibility of using a wider range of outcome measures and developing new outcome measures in prehospital research and quality improvement

Households’ Water-Use Demand and Willingness to Pay for Improved Water Services in Ijebu Ode Local Government Area, Ogun State, Nigeria

This study examined the households’ water choice decision and willingness to pay for improvement in water services. Data were collected from 216 randomly selected households from the ten sub-zones of Ijebu- Ode local government area, Ogun State. The data were analysed using descriptive statistics, generalized linear demand and logit regression models. Results show that majority of households’ water supply was from private piped/borehole (64.8%) followed by public piped (18.5%), and well (16.7 %,). Also, majority (58.3%) of the households are dissatisfied with the current water supply situation and the households preferred water choices are public piped (64.4%), private piped/borehole (30.1%) and well water (5.6%).. These preferences of household’s water choices were determined by quality, convenience, availability and cost with 35.6%, 33.3%, 18.5% and 12.5% respectively. It was revealed further that household per capita expenditure on water is N60 (US$0.38) per day an equivalent of N1,800 (US$11.5) per month which are significantly higher than current connection charge for public piped per month. The result of generalized linear demand model shows that connection charges, household size, distance to water source, availability and quality of water source, unit price paid per liter,  and marital status were determinants of households’ water choices. Logit regression analysis result shows that marital status, education, connection charges, household size and income are the correlates of willingness to pay for improved water services in the study area. It was recommended that the government and other donor agencies should facilitate the improvements of public water utilities in this area by increasing the number of public piped to cover all the sub- zones of Ijebu Ode and its environs. Keywords: Households,  water-use, Willingness to-pay, Generalized linear demand

How should we measure ambulance service quality and performance?

The problem Ambulance services in England treat 6.5 million people per year but get no information about what happens to patients after discharge. This has led to a reliance on measuring response times rather than outcomes to assess how well services perform, and little opportunity for identifying problems and good practice or evaluating service developments. Research aim There is a lack of consensus on which outcome measures are important for pre-hospital care so we set out to address this within the Prehospital Outcomes for Evidence Based Evaluation (PhOEBE) research programme. Methods We conducted a two round Delphi study to prioritise outcome measures identified from a systematic review and a multi-stakeholder consensus event. 20 participants scored 57 measures over two rounds. Participants included policy makers and commissioners, clinical ambulance service and ambulance service operational groups. Outcomes were scored in three categories: patient outcomes; whole service measures and clinical management. Results Highly ranked patient outcome measures related to pain, survival, recontacts and patient experience. High ranking outcomes in the Clinical Management group related to compliance with protocols and guidelines and appropriateness and accuracy of triage. In the Whole Service measures group highly ranked measures related to completeness of clinical records, staff training and time to definitive care. Conclusions The next steps are to identify which measures are suitable for measuring with routine data; use a linked dataset to build predictive models and determine what aspects of care can predict good or poor outcomes (mortality and non-mortality); measure the effectiveness and quality of ambulance service care, and; assess the practical use of the measures and the linked data as a way to support quality improvement in the NHS