Objective: To examine the efficiency of the Hong Kong hospitalisation system based on hospitalisation days. Design: Retrospective study. Setting: Hospitalisation data (2000-2010) for all government-funded hospitals in Hong Kong. Population: Hospitalisation data for the entire Hong Kong population (7.0 million in 2011). Methods: A decomposition method was used to determine the effects on total hospitalisation days during the period 2000-2010 of the following three factors: (i) hospitalisation rate per person; (ii) the number of visits per patient; and (iii) the mean duration of stay per visit. Main outcome measures: The decomposition method provides empirical measures of how the three factors contributed to the change in total hospitalisation days during the period 2000-2010 and identifies the most effective way to contain increases in hospitalisation days. Results: The results of decomposition analysis show that the decrease in mean duration of stay per visit (reducing from 6.83 to 4.58 days) is the most important factor in the reduction in the total number of hospitalisation days, despite increases in total population size (from 6.7 to 7.0 million), the number of individual hospital admissions (from 583 000 to 664 000) and the number of episodes (from 1.2 to 1.4 million) from 2000 to 2010. Hospitalisation days per person decreased from 1.18 in 2000 to 0.93 in 2010. The decline in the mean duration of stay per visit contributed 200.6% to this reduction but was offset by -51.1% due to a slight growth in the number of visits per patient and by -49.4% as a result of changed hospitalisation rates per person. Conclusions: Better management of the duration of stay of per visit without compromising patient satisfaction levels or the quality of service is the most important factor for controlling increases in health expenditure in Hong Kong.
CITATION STYLE
Yip, P. S. F., Lee, C. K. M., Chow, C. B., & Lo, W. T. L. (2014). What makes the hospitalisation system more efficient? An application of the decomposition method to Hong Kong morbidity data. BMJ Open, 4(3). https://doi.org/10.1136/bmjopen-2013-003903
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