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Evaluation of resource allocation and supply–demand balance in clinical practice with high‐cost technologies
Author(s) -
Otsubo Tetsuya,
Imanaka Yuichi,
Lee Jason,
Hayashida Kenshi
Publication year - 2011
Publication title -
journal of evaluation in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 73
eISSN - 1365-2753
pISSN - 1356-1294
DOI - 10.1111/j.1365-2753.2010.01484.x
Subject(s) - balance (ability) , resource (disambiguation) , resource allocation , supply and demand , business , environmental economics , medicine , computer science , economics , microeconomics , management , physical therapy , computer network
Rationale, aims and objectives Japan has one of the highest numbers of high‐cost medical devices installed relative to its population. While evaluations of the distribution of these devices traditionally involve simple population‐based assessments, an indicator that includes the demand of these devices would more accurately reflect the situation. The purpose of this study was to develop an indicator of the supply–demand balance of such devices, using examples of magnetic resonance imaging scanners (MRI) and extracorporeal shockwave lithotripters (ESWL), and to investigate the relationship between this indicator, personnel distribution statuses and operating statuses at the prefectural level. Methods Using data from nation‐wide surveys and claims data from 16 hospitals, we developed an indicator based on the ratio of the supplied number of device units to the number of device units in demand for MRI and ESWL. The latter value was based on patient volume and utilization proportion. Correlation analyses were conducted between the supply–demand balances of these devices, personal distribution and operating statuses. Results Comparisons between our indicator and conventional population‐based indicators revealed that 15% and 30% of prefectures were at risk of underestimating the availability of MRI and ESWL, respectively. The numbers of specialist personnel/device units showed significant, negative correlations with our indicators in both devices. Conclusions Utilization‐based analyses of health care resource placement and utilization status provide a more accurate indication than simple population‐based assessments, and can assist decision makers in reviewing gaps between health policy and management. Such an indicator therefore has the potential to be a tool in helping to improve the efficiency of the allocation and placement of such devices.