Claudia Pavani and Guilherme Ary Plonski
Personalized medicine (PM) encompasses a set of procedures, technologies and medications; the term became more prominent from the 2000s onwards and stems from the mapping of the…
Abstract
Purpose
Personalized medicine (PM) encompasses a set of procedures, technologies and medications; the term became more prominent from the 2000s onwards and stems from the mapping of the human genome. The purposes of this study were to analyse the development stage of the process of technological innovation for PM and the obstacles that prevent PM from being adopted in the public health system in Brazil.
Design/methodology/approach
As a research method, this paper opts for a case study carried out at the Hospital das Clínicas, which belongs to São Paulo Medical School. In total, 22 in-depth interviews were carried out at the hospital to identify current practices in PM, future prospects and barriers imposed to the adoption of PM technologies in public health.
Findings
Personalized or precision medicine is already a reality for a small portion of the Brazilian population and is gradually gaining ground in public health care. One finding is that such changes are occurring in a disjointed manner in an incomplete and under development health innovation system. The analysis pointed out that the obstacles identified in Brazil are the same as those faced by high-income countries such as regulation, lack of clinical studies and need to adapt clinical studies to PM. They appear in all stages of the innovation cycle, from research to widespread use.
Research limitations/implications
The research method was a case study, so the findings cannot be extrapolated to other contexts. A limited number of professionals were interviewed, their opinions may not reflect those of their organizations.
Originality/value
There are several studies that discuss how health-care systems in high-income countries could incorporate these new technologies, but only a few focuses on low or middle-income countries such as Brazil.
Details
Keywords
Mahesh Babu Purushothaman, Jeff Seadon and Dave Moore
This study aims to highlight the system-wide potential relationships between forms of human bias, selected Lean tools and types of waste in a manufacturing process.
Abstract
Purpose
This study aims to highlight the system-wide potential relationships between forms of human bias, selected Lean tools and types of waste in a manufacturing process.
Design/methodology/approach
A longitudinal single-site ethnographic case study using digital processing to make a material receiving process Lean was adopted. An inherent knowledge process with internal stakeholders in a stimulated situation alongside process requirements was performed to achieve quality data collection. The results of the narrative analysis and process observation, combined with a literature review identified widely used Lean tools, wastes and biases that produced a model for the relationships.
Findings
The study established the relationships between bias, Lean tools and wastes which enabled 97.6% error reduction, improved on-time accounting and eliminated three working hours per day. These savings resulted in seven employees being redeployed to new areas with delivery time for products reduced by seven days.
Research limitations/implications
The single site case study with a supporting literature survey underpinning the model would benefit from testing the model in application to different industries and locations.
Practical implications
Application of the model can identify potential relationships between a group of human biases, 25 Lean tools and 10 types of wastes in Lean manufacturing processes that support decision makers and line managers in productivity improvement. The model can be used to identify potential relationships between forms of human biases, Lean tools and types of wastes in Lean manufacturing processes and take suitable remedial actions. The influence of biases and the model could be used as a basis to counter implementation barriers and reduce system-wide wastes.
Originality/value
To the best of the authors’ knowledge, this is the first study that connects the cognitive perspectives of Lean business processes with waste production and human biases. As part of the process, a relationship model is derived.