Federally regulated institutional review boards: The aspects of a "model" IRB---Is the current system in need of a tune up or complete overhaul?

Institutional Review Boards (IRBs) are the primary gatekeepers for the protection of ethical standards of federally regulated research on human subjects in this country. This paper focuses on what general, broad measures that may be instituted or enhanced to exemplify a "model IRB". This is done by examining the current regulatory standards of federally regulated IRBs, not private or commercial boards, and how many of those standards have been found either inadequate or not generally understood or followed. The analysis includes suggestions on how to bring about changes in order to make the IRB process more efficient, less subject to litigation, and create standardized educational protocols for members. The paper also considers how to include better oversight for multi-center research, increased centralization of IRBs, utilization of Data Safety Monitoring Boards when necessary, payment for research protocol review, voluntary accreditation, and the institution of evaluation/quality assurance programs. ^ This is a policy study utilizing secondary analysis of publicly available data. Therefore, the research for this paper focuses on scholarly medical/legal journals, web information from the Department of Health and Human Services, Federal Drug Administration, and the Office of the Inspector General, Accreditation Programs, law review articles, and current regulations applicable to the relevant portions of the paper. ^ Two issues are found to be consistently cited by the literature as major concerns. One is a need for basic, standardized educational requirements across all IRBs and its members, and secondly, much stricter and more informed management of continuing research. There is no federally regulated formal education system currently in place for IRB members, except for certain NIH-based trials. Also, IRBs are not keeping up with research once a study has begun, and although regulated to do so, it does not appear to be a great priority. This is the area most in danger of increased litigation. Other issues such as voluntary accreditation and outcomes evaluation are slowing gaining steam as the processes are becoming more available and more sought after, such as JCAHO accrediting of hospitals. ^ Adopting the principles discussed in this paper should promote better use of a local IRBs time, money, and expertise for protecting the vulnerable population in their care. Without further improvements to the system, there is concern that private and commercial IRBs will attempt to create a monopoly on much of the clinical research in the future as they are not as heavily regulated and can therefore offer companies quicker and more convenient reviews. IRBs need to consider the advantages of charging for their unique and important services as a cost of doing business. More importantly, there must be a minimum standard of education for all IRB members in the area of the ethical standards of human research and a greater emphasis placed on the follow-up of ongoing research as this is the most critical time for study participants and may soon lead to the largest area for litigation. Additionally, there should be a centralized IRB for multi-site trials or a study website with important information affecting the trial in real time. There needs to be development of standards and metrics to assess the performance of the IRBs for quality assurance and outcome evaluations. The boards should not be content to run the business of human subjects' research without determining how well that function is actually being carried out. It is important that federally regulated IRBs provide excellence in human research and promote those values most important to the public at large.^

A comparison of techniques for forecasting utilization of Veterans Affairs hospitals

This study demonstrated that accurate, short-term forecasts of Veterans Affairs (VA) hospital utilization can be made using the Patient Treatment File (PTF), the inpatient discharge database of the VA. Accurate, short-term forecasts of two years or less can reduce required inventory levels, improve allocation of resources, and are essential for better financial management. These are all necessary achievements in an era of cost-containment.^ Six years of non-psychiatric discharge records were extracted from the PTF and used to calculate four indicators of VA hospital utilization: average length of stay, discharge rate, multi-stay rate (a measure of readmissions) and days of care provided. National and regional levels of these indicators were described and compared for fiscal year 1984 (FY84) to FY89 inclusive.^ Using the observed levels of utilization for the 48 months between FY84 and FY87, five techniques were used to forecast monthly levels of utilization for FY88 and FY89. Forecasts were compared to the observed levels of utilization for these years. Monthly forecasts were also produced for FY90 and FY91.^ Forecasts for days of care provided were not produced. Current inpatients with very long lengths of stay contribute a substantial amount of this indicator and it cannot be accurately calculated.^ During the six year period between FY84 and FY89, average length of stay declined substantially, nationally and regionally. The discharge rate was relatively stable, while the multi-stay rate increased slightly during this period. FY90 and FY91 forecasts show a continued decline in the average length of stay, while the discharge rate is forecast to decline slightly and the multi-stay rate is forecast to increase very slightly.^ Over a 24 month ahead period, all three indicators were forecast within a 10 percent average monthly error. The 12-month ahead forecast errors were slightly lower. Average length of stay was less easily forecast, while the multi-stay rate was the easiest indicator to forecast.^ No single technique performed significantly better as determined by the Mean Absolute Percent Error, a standard measure of error. However, Autoregressive Integrated Moving Average (ARIMA) models performed well overall and are recommended for short-term forecasting of VA hospital utilization. ^