The use of a bayesian hierarchy to develop and validate a co-morbidity score to predict mortality for linked primary and secondary care data from the NHS in England

Background: We have assessed whether the linkage between routine primary and secondary care records provided an opportunity to develop an improved population based co-morbidity score with the combined information on co-morbidities from both health care settings. Methods: We extracted all people older than 20 years at the start of 2005 within the linkage between the Hospital Episodes Statistics, Clinical Practice Research Datalink, and Office for National Statistics death register in England. A random 50% sample was used to identify relevant diagnostic codes using a Bayesian hierarchy to share information between similar Read and ICD 10 code groupings. Internal validation of the score was performed in the remaining 50% and discrimination was assessed using Harrell’s C statistic. Comparisons were made over time, age, and consultation rate with the Charlson and Elixhauser indexes. Results: 657,264 people were followed up from the 1st January 2005. 98 groupings of codes were derived from the Bayesian hierarchy, and 37 had an adjusted weighting of greater than zero in the Cox proportional hazards model. 11 of these groupings had a different weighting dependent on whether they were coded from hospital or primary care. The C statistic reduced from 0.88 (95% confidence interval 0.88–0.88) in the first year of follow up, to 0.85 (0.85–0.85) including all 5 years. When we stratified the linked score by consultation rate the association with mortality remained consistent, but there was a significant interaction with age, with improved discrimination and fit in those under 50 years old (C=0.85, 0.83–0.87) compared to the Charlson (C=0.79, 0.77–0.82) or Elixhauser index (C=0.81, 0.79–0.83). Conclusions: The use of linked population based primary and secondary care data developed a co-morbidity score that had improved discrimination, particularly in younger age groups, and had a greater effect when adjusting for co-morbidity than existing scores

Scenario analysis for strategy design: A case study of the Colombian electricity industry

The technology transformation of the power industry is crucial for electricity companies, which need to be prepared for the transition of their traditional business. Using scenario-planning exercises, combined with SWOT and PESTEL analysis, as well as a systems thinking approach, this paper explores potential strategies for electricity companies to grasp the opportunities and offset threats, by focusing on the formulation process for a broad, innovative strategy for the transition in the power business. The paper concludes that the transformation of the Colombian energy industry poses serious challenges to electricity companies when policy and regulation promote the adoption of non-conventional energy sources, at a time when the cost of renewables keep declining; however, with a robust adaptive strategy, companies could better face the transition from current business to new alternatives. Keywords: Scenario planning, Technological transformation in energy, Power industry, Electricity compan