Can Bayesian methods make data and analyses more relevant to decision makers? A perspective from Medicare.

Decision making in health care has become increasingly reliant on information technology, evidence-based processes, and performance measurement. It is therefore a time at which it is of critical importance to make data and analyses more relevant to decision makers. Those who support Bayesian approaches contend that their analyses provide more relevant information for decision making than do classical or "frequentist" methods, and that a paradigm shift to the former is long overdue. While formal Bayesian analyses may eventually play an important role in decision making, there are several obstacles to overcome if these methods are to gain acceptance in an environment dominated by frequentist approaches. Supporters of Bayesian statistics must find more accommodating approaches to making their case, especially in finding ways to make these methods more transparent and accessible. Moreover, they must better understand the decision-making environment they hope to influence. This paper discusses these issues and provides some suggestions for overcoming some of these barriers to greater acceptance.

Technology assessment, coverage decisions, and conflict: the role of guidelines.

As pressure grows for health plans to be accountable for increasing quality of care within a cost-control environment, coverage of new technologies becomes a particularly challenging issue. For a number of reasons, health plans have adopted evidence-based methods for guiding technology decisions. The implementation of these methods has not been free of controversy, and conflicts have arisen between plans and proponents of technologies who often use the political and legal arena in an attempt to secure coverage. Unless these conflicts are resolved, the healthcare system may have difficulty meeting cost and quality objectives. Technology assessment and coverage process guidelines and flexible coverage approaches may be possible ways of resolving these conflicts.

Prevention of hepatitis B virus transmission by immunization. An economic analysis of current recommendations.

OBJECTIVE: To evaluate the outcome of immunization strategies to prevent hepatitis B virus (HBV) transmission. DESIGN AND SETTING: A decision model was used to determine the incremental effects of the following hepatitis B immunization strategies in a birth cohort receiving immunization services in the public sector: (1) prevention of perinatal HBV infection, (2) routine infant vaccination, or (3) routine adolescent vaccination. MAIN OUTCOME MEASURES: Over the lifetime of the cohort, the reduction in infections and medical and work-loss costs of HBV-related liver disease were determined for each strategy and compared with the outcome without immunization. RESULTS: Prevention of perinatal infection and routine infant vaccination would lower the 4.8% lifetime risk of HBV infection by at least 68%, compared with a 45% reduction for adolescent vaccination. From a societal perspective, each strategy was found to be cost saving, but was not cost saving with respect to direct medical costs. The estimated cost per year of life saved was $164 to prevent perinatal HBV infection, $1522 for infant vaccination, and $3730 for adolescent vaccination. CONCLUSIONS: Routine vaccination of infants in successive birth cohorts to prevent HBV transmission is cost-effective over a wide range of assumptions. While economically less attractive than infant vaccination, adolescent vaccination could serve to protect those children who were not vaccinated as infants.

Recombinant human granulocyte-macrophage colony-stimulating factor after autologous bone marrow transplantation for lymphoid cancer: an economic analysis of a randomised, double-blind, placebo-controlled trial.

In a blinded retrospective economic evaluation of a double-blind, randomised, placebo-controlled clinical trial, total utilisation and charges for lymphoid cancer patients who received recombinant human granulocyte-macrophage colony-stimulating factor (rhGM-CSF) or placebo were compared following autologous bone marrow transplantation. The 40 patients enrolled (22 rhGM-CSF, 18 placebo) could have acute lymphoblastic leukaemia, non-Hodgkins lymphoma or Hodgkin's disease, be of any age, and were undergoing autologous bone marrow transplantation in a metropolitan cancer research centre. Main outcome measures consisted of initial hospital lengths of stay (LOS), total and department charges, rehospitalisation rates and charges, and outpatient charges, all inclusive of the first 100 days following bone marrow infusion. The perspective of the study is that of the third party payer. Initial hospitalisation charges were $US54 100 for patients who received rhGM-CSF and $US68 600 for patients who received placebo (p = 0.05). The difference of $US14 500 was 21% less in patients who received rhGM-CSF, mainly due to lower average LOS with rhGM-CSF (24.2 days) compared with placebo (30.8 days). Outpatient charges were $US9500 (rhGM-CSF) and $US6800 (placebo) {p = 0.18}. Total charges, including readmission (10 per group) were $US12 200 lower in the rhGM-CSF group ($US70 300 vs $US82 500, p = 0.19). The use of rhGM-CSF after autologous bone marrow transplantation was shown to result in substantial cost savings during the initial hospitalisation. When comparing total inpatient and outpatient medical charges within the first 100 days following bone marrow infusion, we found no evidence that these savings were negated.

Are PPS payments adequate? Issues for updating and assessing rates.

Declining operating margins under Medicare's prospective payment system (PPS) have focused attention on the adequacy of payment rates. The question of whether annual updates to the rates have been too low or cost increases too high has become important. In this article we discuss issues relevant to updating PPS rates and judging their adequacy. We describe a modification to the current framework for recommending annual update factors. This framework is then used to retrospectively assess PPS payment and cost growth since 1985. The preliminary results suggest that current rates are more than adequate to support the cost of efficient care. Also discussed are why using financial margins to evaluate rates is problematic and alternative methods that might be employed.

Alternatives for using multivariate regression to adjust prospective payment rates.

Multivariate regression analysis has been used in structuring three of the adjustments to Medicare's prospective payment rates. Because the indirect-teaching adjustment, the disproportionate-share adjustment, and the adjustment for large cities are responsible for distributing approximately $3 billion in payments each year, the specification of regression models for these adjustments is of critical importance. In this article, the application of regression for adjusting Medicare's prospective rates is discussed, and the implications that differing specifications could have for these adjustments are demonstrated.