Modelling the dynamics of a public health care system: evidence from time-series data

TY - JOUR

T1 - Modelling the dynamics of a public health care system

T2 - evidence from time-series data

AU - Iacone, Fabrizio

AU - Martin, Stephen

AU - Siciliani, Luigi

AU - Smith, Peter

PY - 2012/8

Y1 - 2012/8

N2 - The English National Health Service (NHS) was established in 1948, and has therefore yielded some long time series data on health system performance. Waiting time for inpatient care have been a persistent policy concern since the creation of the NHS. After developing a simple theoretical framework of the dynamic interaction between key indicators of health system performance, we investigate empirically the relationship between hospital activity, waiting time and population characteristics using aggregate time-series data for the NHS over the period 1952 to 2003. Structural Vector Autoregression (S-VAR) suggests that in the long run: higher activity is associated with lower waiting times (elasticity=-0.9); an increase in the elderly population is associated with higher waiting time (elasticity=1.3). In the short run, higher lagged waiting time leads to higher activity (elasticity=0.12). We also find that shocks in waiting times are countered by higher activity, so the effect is only temporary.

AB - The English National Health Service (NHS) was established in 1948, and has therefore yielded some long time series data on health system performance. Waiting time for inpatient care have been a persistent policy concern since the creation of the NHS. After developing a simple theoretical framework of the dynamic interaction between key indicators of health system performance, we investigate empirically the relationship between hospital activity, waiting time and population characteristics using aggregate time-series data for the NHS over the period 1952 to 2003. Structural Vector Autoregression (S-VAR) suggests that in the long run: higher activity is associated with lower waiting times (elasticity=-0.9); an increase in the elderly population is associated with higher waiting time (elasticity=1.3). In the short run, higher lagged waiting time leads to higher activity (elasticity=0.12). We also find that shocks in waiting times are countered by higher activity, so the effect is only temporary.

KW - waiting times

KW - dynamics

KW - vector auto-regression

UR - http://www.scopus.com/inward/record.url?scp=80051984134&partnerID=8YFLogxK

U2 - 10.1080/00036846.2011.568407

DO - 10.1080/00036846.2011.568407

M3 - Article

SN - 0003-6846

VL - 44

SP - 2955

EP - 2968

JO - Applied Economics

JF - Applied Economics

IS - 23

ER -