Abstract
Background Prioritization is a critical factor in the healthcare sector, and it is critical that prioritization be based on relevant criteria which facilitate the comparison of different interventions and health measures. When deciding whether or not to implement new interventions, typically projections of increased costs are weighed against expected benefits of the interventions. This comparison allows the calculation of quality adjusted life year gains, also known as a QALY, as well as the comparison of the new intervention to existing measures or other new interventions, through the current cost per QALY, or through the incremental cost per QALY of additional intervention. Method This thesis is a case study of resource spending on patients recovering from stroke, using length of stay as a resource indicator and 30-day survival rate as health outcome. We compare all health enterprises and their differences in both length of stay and 30-day survival rate to determine whether there are any indications of correlation. We seek to answer the question of what the possible health effects would be of increasing length of stay by one day. To measure this, a simple equation was made to help measure the cost of an incremental QALY. Incremental cost per QALY = Incremental cost (Δc) = Cost of increasing one LOS Incremental benefit (Δb) Δp*Δy*Δq In this equation Δp is the increased probability in 30 day survival rate, Δy is the expected life years by surviving a stroke, Δq is the quality of life a stroke survivor has after the stroke. Results A linear regression model of a five year weighted average indicated a correlation of 0.18% increase in 30 day survival rate by increasing length of stay by one extra day for all Health Enterprises, resulting in a QALY of 372,802 NOK (the simulation yielded a 95% confidence interval of [232,208 - 656,220]). Other relevant linear regressions also yielded similar results with different significance. The results also indicated a negative correlation between increasing length of stay and 30 day readmittance rate. While more research would be needed to reach a definitive conclusion, as other factors not taken into account here could possibly affect length of stay or 30 day survival rate, this research indicates that increasing length of stay by a single day could yield a larger benefit than other measures which demand more resources as measured by incremental cost per QALY.