Comment on “How does the Price Regulation Policy Impact on Patient–Nurse Ratios and the Length of Hospital Stays in Japanese Hospitals?”

• Published date: 01 July 2015
• Author: Toshiaki Iizuka
• DOI: http://doi.org/10.1111/aepr.12111
• Date: 01 July 2015

Comment on “How does the Price

Regulation Policy Impact on Patient–Nurse

Ratios and the Length of Hospital Stays in

Japanese Hospitals?”

Toshiaki IIZUKA†

University of Tokyo

JEL codes: I11, I18

It is well known that Japan has the longest average length of hospital stays (LHS) for

inpatient care among all countries of the Organisation for Economic Co-operation

Development (OECD). According to OECD Health Statistics, LHS in Japan was 24.8 in

2000, while the OECD average in the same year was only 8.3. Having noticed this long

LHS, since the late 1980s, the Japanese government has implemented a series of policies

that aim to lower the patient–nurse ratio (PNR) and shorten LHS. Noguchi (2015)

studies the impacts of these policy interventions on PNR and LHS. This is a timely study

as the government is now further introducing new policies that could drastically alter the

way that inpatient services are provided in Japan. In particular, the government intro-

duced a new 7:1 ward system in 2006, and as of 2013 more than 40% of general hospital

beds had adopted the new 7:1 payment. Given the rapid spread of this new payment, it is

important to examine whether the impact of the new payment differed from previous

interventions.

Although there is room for improvement, overall, I find Noguchi’s (2015) paper

interesting and stimulating. In particular, it nicely documents the long-term trend of the

key variables of the Japanese health-care system, such as LHS and PNR for inpatient care.

Moreover, as I discuss in detail below, Noguchi made a great attempt to identify the

causal impact of policy changes. I see this paper as being an important first step to fully

investigate the impact of the policy interventions that affect the production of inpatient

services.

Noguchi assembled a unique hospital-level dataset, combining two large data

obtained from the government. To identify the impact of policy changes, Noguchi

focused on the changes in inpatient payments implemented in 2000 and 2006. As

Noguchi noted, identifying the causal impact of a health policy is often difficult in

Japan because it is common that a health policy affects all hospitals and thus no clear

control group exists. In her econometric model, Noguchi attempted to overcome this

difficulty by combining the propensity score matching and the difference-in-difference

approaches. For example, for the 2006 policy changes, the government increased the

†Correspondence: Toshiaki Iizuka, Faculty of Economics, University of Tokyo, 7-3-1 Hongyo,

Bunkyo-ku, Tokyo 113-0033, Japan. Email: toshi.iizuka@gmail.com

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doi: 10.1111/aepr.12111 Asian Economic Policy Review (2015) 10, 326–327

© 2015 Japan Center for Economic Research326