Cost-effectiveness of thrombolytic therapy for acute myocardial infarction

Door to Needle Times Bulls' Eye or Just Bull? The Effect of Reducing Door to Needle Times on the Appropriate Administration of Thrombolysis: Implications and Recommendations

The provision of thrombolysis in a timely fashion is the mainstay of treatment for acute myocardial infarction. With the publication of the National Service Framework (NSF) for Coronary Heart Disease increasing efforts have been put into the reduction of the ‘pain to needle time’. Of the various parts of the patient journey the time delays in hospital are the easiest to resolve. Published research shows that the time taken for the patient to call for help is intractable at present. Therefore, the obvious target for the reduction in the overall time from pain to treatment is the in hospital portion of the delay (the door to needle time). There are several methods that have been recommended for the reduction of the door to needle time. However, the increasing focus on the door to needle time is leading health care providers away from other issues such as the safety and accuracy of assessment by a non-cardiologist. Furthermore, the standards for audit of the door to needle time have not been set by the NSF and this has led to the presentation of selected data and the avoidance of discussing issues of accuracy and appropriateness.

A review of health care models for coronary heart disease interventions

This article reviews models for the treatment of coronary heart disease (CHD). Whereas most of the models described were developed to assess the cost effectiveness of different treatment strategies, other models have also been used to extrapolate clinical trials, for capacity and resource planning, or to predict the future population with heart disease. In this paper we investigate the use of modelling techniques in relation to different types of health intervention, and we discuss the assumptions and limitations of these approaches. Many of the models reviewed in this paper use decision tree models for acute or short term interventions, and Markov or state transition models for chronic or long term interventions. Discrete event simulation has, however, been used for more complex whole system models, and for modelling resource-constrained interventions and operational planning. Nearly all of the studies in our review used cohort-based models rather than population based models, and therefore few models could estimate the likely total costs and benefits for a population group. Most studies used de novo purpose built models consisting of only a small number of health states. Models of the whole disease system were less common. The model descriptions were often incomplete. We recommend that the reporting of model structure, assumptions and input parameters is more explicit, to reduce the risk of biased reporting and ensure greater confidence in the model results.

Improving nurse-to-patient staffing ratios as a cost-effective safety intervention

BACKGROUND

Responding to research confirming the link between nurse staffing and patient outcomes, 14 states have introduced legislation to limit patient-to-nurse ratios. However, increased staffing places a considerable financial burden on hospitals.

OBJECTIVE

We sought to determine the cost-effectiveness of various nurse staffing ratios.

RESEARCH DESIGN

This was a cost-effectiveness analysis from the institutional perspective comparing patient-to-nurse ratios ranging from 8:1 to 4:1. Cost estimates were drawn from the medical literature and the Bureau of Labor Statistics. Patient mortality and length of stay data for different ratios were based on 2 large hospital level studies. Incremental cost-effectiveness was calculated for each ratio and sensitivity and Monte Carlo analyses performed.

SUBJECTS

The study included general medical and surgical patients.

MEASURES

: We sought to measure costs per life saved in 2003 US dollars. RESULTS OF BASE CASE ANALYSIS: Eight patients per nurse was the least expensive ratio but was associated with the highest patient mortality. Decreasing the number of patients per nurse improved mortality and increased costs, becoming progressively less cost-effective as the ratio declined from 8:1 to 4:1. Nonetheless, the incremental cost-effectiveness did not exceed US dollars 136,000 (95% CI US dollars 53,000-402,000) per life saved.

RESULTS OF SENSITIVITY ANALYSIS

The model was most sensitive to the effects of patient-to-nurse ratios on mortality. Lower ratios were most cost-effective when lower ratios shortened length of stay, and hourly wages were low. However, throughout the ranges of all these variables, the incremental cost-effectiveness of limiting the ratio to 4:1 never exceeded US dollars 449,000 per life saved.

CONCLUSIONS

As a patient safety intervention, patient-to-nurse ratios of 4:1 are reasonably cost-effective and in the range of other commonly accepted interventions.

Medical biotechnology in India

The potential of biotechnology has just began to emerge in the 20th century. After the full knowledge of human genomes is available, biotechnology is going to play a major role in shaping the concept of future drug discovery, drug delivery, diagnostic methodology, clinical trials, and to a great extent the major lifestyle of the human society. This article is a comprehensive review of the major impact of biotechnology in diagnostics, antibiotics, r-proteins, vaccines, and antibodies production. It also highlights the future aspects of gene therapy in the management of healthcare. A comprehensive list of biotech products in healthcare management has been given. Also, the growth of biotechnology throughout the world at large and in the Indian industries in particular has been highlighted. Constraints, concerns and difficulties in biotechnology in India have been addressed mainly related to human resources, training institutions in India, funding in biotechnology, patent-related issues and regulatory hurdles. Like in information technology, India has great potential in bioinformatics as well. Some of the recent information on bioinformatics centers in India has been summarized. Indian biotechnology industries have the potential to use the modern discoveries in life sciences to reach an enviable position in the world of biotechnology.

The limited incorporation of economic analyses in clinical practice guidelines

BACKGROUND

Because there is increasing concern that economic data are not used in the clinical guideline development process, our objective was to evaluate the extent to which economic analyses are incorporated in guideline development.

METHODS

We searched medline and HealthSTAR databases to identify English-language clinical practice guidelines (1996-1999) and economic analyses (1990-1998). Additional guidelines were obtained from The National Guidelines Clearinghouse Internet site available at http://www.guideline.gov. Eligible guidelines met the Institute of Medicine definition and addressed a topic included in an economic analysis. Eligible economic analyses assessed interventions addressed in a guideline and predated the guideline by 1 or more years. Economic analyses were defined as incorporated in guideline development if 1) the economic analysis or the results were mentioned in the text or 2) listed as a reference. The quality of economic analyses was assessed using a structured scoring system.

RESULTS

Using guidelines as the unit of analysis, 9 of 35 (26%) incorporated at least 1 economic analysis of above-average quality in the text and 11 of 35 (31%) incorporated at least 1 in the references. Using economic analyses as the unit of analysis, 63 economic analyses of above-average quality had opportunities for incorporation in 198 instances across the 35 guidelines. Economic analyses were incorporated in the text in 13 of 198 instances (7%) and in the references in 18 of 198 instances (9%).

CONCLUSIONS

Rigorous economic analyses may be infrequently incorporated in the development of clinical practice guidelines. A systematic approach to guideline development should be used to ensure the consideration of economic analyses so that recommendations from guidelines may impact both the quality of care and the efficient allocation of resources.