[Analysis of mental health care utilization data in comparison with medical-specialist and general practitioner health care consumption data]. / Behoefte aan en consumptie van ggz-zorg vergeleken met somatische zorg in Nederland.
Tijdschr Psychiatr
; 63(1): 39-47, 2021.
Article
en Nl
| MEDLINE
| ID: mdl-33537973
BACKGROUND: Quantification of population-level socioeconomic-demographic factors impacting onset and course of health care consumption can help health care commissioning and public health planning.
AIM: To analyse associations between mental health care, medical-specialist care and general practitioner (GP) care with regional socioeconomic-demographic factors. Two cost parameters were examined: (i) absolute costs; and (ii) relative costs, defined as the proportion of PC3-level costs attributable to outliers (defined as costs above the 80th percentile - as a proxy for care intensity).
METHOD: Analysis of Vektis data over the period 2014-2017 in the age range of 18-65 years.
RESULTS: Mental health care cost variation was for 28% reducible to (younger) age, urbanicity, PC3-level ethnic density and PC3-level socioeconomic-demographic factors. Variation in medical-specialist care and GP care costs were reducible principally to (older) age. Costs attributable to outliers ranged from 34% for GP care to 55% for mental health care. Socioeconomic-demographic factors explained a substantial part of the variation in the PC3-level proportion of outlier costs for mental health care (31%), medical-specialist care (43%) and GP-care (33%).
CONCLUSION: Analysis of the degree and pattern of socioeconomic-demographic factors impacting mental health care can inform both public mental health planning and mental health care commissioning. Tijdschrift voor psychiatrie 63(2021)1, 39-47.
AIM: To analyse associations between mental health care, medical-specialist care and general practitioner (GP) care with regional socioeconomic-demographic factors. Two cost parameters were examined: (i) absolute costs; and (ii) relative costs, defined as the proportion of PC3-level costs attributable to outliers (defined as costs above the 80th percentile - as a proxy for care intensity).
METHOD: Analysis of Vektis data over the period 2014-2017 in the age range of 18-65 years.
RESULTS: Mental health care cost variation was for 28% reducible to (younger) age, urbanicity, PC3-level ethnic density and PC3-level socioeconomic-demographic factors. Variation in medical-specialist care and GP care costs were reducible principally to (older) age. Costs attributable to outliers ranged from 34% for GP care to 55% for mental health care. Socioeconomic-demographic factors explained a substantial part of the variation in the PC3-level proportion of outlier costs for mental health care (31%), medical-specialist care (43%) and GP-care (33%).
CONCLUSION: Analysis of the degree and pattern of socioeconomic-demographic factors impacting mental health care can inform both public mental health planning and mental health care commissioning. Tijdschrift voor psychiatrie 63(2021)1, 39-47.
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Psiquiatría
/
Costos de la Atención en Salud
/
Médicos Generales
/
Trastornos Mentales
/
Servicios de Salud Mental
Tipo de estudio:
Diagnostic_studies
Aspecto:
Implementation_research
Límite:
Adolescent
/
Adult
/
Aged
/
Female
/
Humans
/
Male
/
Middle aged
País/Región como asunto:
Europa
Idioma:
Nl
Revista:
Tijdschr Psychiatr
Año:
2021
Tipo del documento:
Article
Pais de publicación:
Países Bajos