Observational studyBMC health services research2018
Supply factors as determinants of treatment costs: clinicians' assessments of a given set of referrals to community mental health centers in Norway.
Observational study in BMC health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- National hospital costing systems matter for universal healthcare: the India PM-JAY experience.BMJ global health · 2023Article
- Referral assessment and patient waiting time decisions in specialized mental healthcare: an exploratory study of early routine collection of PROM (LOVePROM).BMC health services research · 2022Article
- Cost of hospital services in India: a multi-site study to inform provider payment rates and Health Technology Assessment.BMC health services research · 2022Article
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Authors and funding
2 authors.
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Abstract
backgroundPrevious works that uses patterns of prior spending to predict future mental health care expenses (utilization models) are mainly concerned with demand (need) variables. In this paper, we introduce supply variables, both individual rater variables and center variables. The aim is to assess these variables' explanatory power, and to investigate whether not accounting for such variables could create biased estimates for the effects of need variables.
methodsWe employed an observational study design where the same set of referrals was assessed by a sample of clinicians, thus creating data with a panel structure being particularly relevant for analyzing supply factors. The referrals were obtained from Norwegian Community Mental Health Centers (outpatient services), and the clinicians assessed the referrals with respect to recommended treatment costs and health status.
resultsSupply variables accounted for more than 10% of the total variation and about one third of the explained variation. Two groups of supply variables, individual rater variables and center variables (institutions) were equally important.
conclusionsOur results confirm that supply factors are important but ignoring such variables, when analyzing demand variables, do not generally seem to produce biased (confounded) coefficients.
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