Weighing Price and Performance for Decisions for Multisource Pharmaceutical Bidding in Public Hospitals in Thailand

Following a national law introduced in 2017 in Thailand, the selection of winning bidders for multisourced pharmaceuticals and medical supplies in public hospitals must reflect “price-performance” aligned with the principles of worthiness, transparency, efficiency, effectiveness and accountability. We describe how a practical tool using Multiple Criteria Decision Analysis (MCDA) for evidence-based decision making in hospital bidding (tender) was developed through a multi-stakeholder workshop format. The local leader of the initiative together with 2 international advisors guided the 37 workshop participants through five interactive steps for local adaptation of the previously developed and validated global MCDA-tool: (1) Criteria selection, (2) Scoring definition, (3) Weighting of price criterion, (4) Definition of cut-off point for price criterion, (5) Ranking and weighting of remaining criteria. All consensus judgments were imported to the decision tool which can later be used in the real-world situation in the hospitals to support the selection and document the underlying rationale. The final list of criteria differs from the previously suggested international template and now reflects the Thai decision priorities and current decision processes. In the book chapter, the resulting model will be presented and a pathway for implementation will be discussed

A cost Malmquist productivity index capturing group performance

This paper develops an index for comparing the productivity of groups of operating units in cost terms when input prices are available. In that sense it represents an extension of a similar index available in the literature for comparing groups of units in terms of technical productivity in the absence of input prices. The index is decomposed to reveal the origins of differences in performance of the groups of units both in terms of technical and cost productivity. The index and its decomposition are of value in contexts where the need arises to compare units which perform the same function but they can be grouped by virtue of the fact that they operate in different contexts as might for example arise in comparisons of water or gas transmission companies operating in different countries

Measuring intra-hospital clinic efficiency and productivity : an application to a Greek university general hospital

In this paper we use Data Envelopment Analysis and the Malmquist Productivity Index and its decompositions to assess the productive efficiency and productivity of the in-patient clinics of a large Greek University General Hospital. Clinics are represented by means of a simple model whereby they use inputs (labor and capital) to produce outputs (in-patient days and patient discharges). The efficiency model is input oriented and assumes constant returns to scale. Model validation analyses showed that this model appears to be externally valid. The framework proposed here is a simple and useful tool for informing intra-hospital management decisions.peer-reviewe

Health care services performance measurement : theory, methods and empirical evidence

Despite the growing international literature in the field of efficiency and productivity measurement there are very limited Greek applications partly due to inadequate and incomplete datasets. The aim of this article is to illustrate the main methodologies for health care services efficiency and productivity measurement, to present their strengths and weaknesses and to discuss the existing evidence from applications in other countries. Notwithstanding the fact that the related methodologies have been recently developed these methods may help practitioners and health care decisions makers in improving health care management in Greece.peer-reviewe

Measuring across hospital efficiency and productivity : the case of second regional health authority of Attica

The purpose of the study is to investigate technical efficiency and productivity change of a sample of Greek Hospitals over the period 1998 - 2005. Efficiency and productivity measurement became a crucial issue in Greece after the launching of health reforms in 2001, with the legislative Act No. 2889, aiming at cost containment and improvements in hospital efficiency. Applying the linear programming method of Data Envelopment Analysis we investigate how efficiently the hospital resources are used to obtain the maximum possible outcome, before and after the reforms. Hospital output is modelled in terms of interventions, laboratory examinations, outpatient and inpatient cases. Inputs considered include beds, doctors, nurses and rest personnel and operational expenses. The analysis indicates that the reforms have generated efficiency gains when only input and output quantities are considered. During the period 1998- 2002 an overall efficiency regress is observed followed by an upturn, after the launching of managerial reforms. However, when the running costs of the hospitals are considered, then the sample experiences significant regress, implying relatively higher production costs over time. We conclude that DEA is a useful technique to assess relative efficiency and optimum hospital performance across hospitals.peer-reviewe

Big data from electronic health records for early and late translational cardiovascular research: challenges and potential.

AIMS: Cohorts of millions of people's health records, whole genome sequencing, imaging, sensor, societal and publicly available data present a rapidly expanding digital trace of health. We aimed to critically review, for the first time, the challenges and potential of big data across early and late stages of translational cardiovascular disease research. METHODS AND RESULTS: We sought exemplars based on literature reviews and expertise across the BigData@Heart Consortium. We identified formidable challenges including: data quality, knowing what data exist, the legal and ethical framework for their use, data sharing, building and maintaining public trust, developing standards for defining disease, developing tools for scalable, replicable science and equipping the clinical and scientific work force with new inter-disciplinary skills. Opportunities claimed for big health record data include: richer profiles of health and disease from birth to death and from the molecular to the societal scale; accelerated understanding of disease causation and progression, discovery of new mechanisms and treatment-relevant disease sub-phenotypes, understanding health and diseases in whole populations and whole health systems and returning actionable feedback loops to improve (and potentially disrupt) existing models of research and care, with greater efficiency. In early translational research we identified exemplars including: discovery of fundamental biological processes e.g. linking exome sequences to lifelong electronic health records (EHR) (e.g. human knockout experiments); drug development: genomic approaches to drug target validation; precision medicine: e.g. DNA integrated into hospital EHR for pre-emptive pharmacogenomics. In late translational research we identified exemplars including: learning health systems with outcome trials integrated into clinical care; citizen driven health with 24/7 multi-parameter patient monitoring to improve outcomes and population-based linkages of multiple EHR sources for higher resolution clinical epidemiology and public health. CONCLUSION: High volumes of inherently diverse ('big') EHR data are beginning to disrupt the nature of cardiovascular research and care. Such big data have the potential to improve our understanding of disease causation and classification relevant for early translation and to contribute actionable analytics to improve health and healthcare