Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices

Bibliographic Details
Main Author: Vecchio, Alexander Schulz Del
Publication Date: 2022
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.14/39051
Summary: The aim of this thesis is to develop an initial business model and validate the business idea of the start-up, named DOC+. The solution offers the most time efficient way to plan and execute a physician visit for practices and patients though self-check-in and though waiting time predictions. First, the business idea is described, followed by an analytical and structured approach to create the business model. It is validated through the analysis of an online survey for patients and semi-structured interviews with physicians. The quantitative data is statistically analyzed with regression analyses and the qualitative data according to Mayring's coding scheme. Ash Maurya's Lean Canvas, a one-page business model, serves as the basis for the thesis. It is designed to serve as a foundation for DOC+ and for the evaluation of strategic plans and projects, which will be refined in future iteration steps. To fill in the key frames of the canvas, different frameworks are used. Key findings are that physicians have a demand to address root causes that trigger waiting times. This points at the excessive burden of administrative tasks and the need for relief. This also represents the greatest value creation for the paying customer, the physician: Reduction of workload for staff and their use of time for essential tasks. It is also identified that it is more advantageous for DOC+ to collaborate than to compete. The biggest advantage for collaboration with a competitor is the reduction of market entry barriers and having access to their resources.
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spelling Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practicesBusiness modelMachine learningSelf-check-inWaiting time predictionsLean CanvasValue proposition CanvasEntrepreneurial strategy compassPatientPhysicianMedical practicePractice softwareStart-upGermanyModelo de negóciosCheck-in automáticoPrevisão de tempo de esperaProposta de valor CanvasOrientação de estratégia de negócioPacienteMédicoPrática médicaSoftware de práticaAlemanhaThe aim of this thesis is to develop an initial business model and validate the business idea of the start-up, named DOC+. The solution offers the most time efficient way to plan and execute a physician visit for practices and patients though self-check-in and though waiting time predictions. First, the business idea is described, followed by an analytical and structured approach to create the business model. It is validated through the analysis of an online survey for patients and semi-structured interviews with physicians. The quantitative data is statistically analyzed with regression analyses and the qualitative data according to Mayring's coding scheme. Ash Maurya's Lean Canvas, a one-page business model, serves as the basis for the thesis. It is designed to serve as a foundation for DOC+ and for the evaluation of strategic plans and projects, which will be refined in future iteration steps. To fill in the key frames of the canvas, different frameworks are used. Key findings are that physicians have a demand to address root causes that trigger waiting times. This points at the excessive burden of administrative tasks and the need for relief. This also represents the greatest value creation for the paying customer, the physician: Reduction of workload for staff and their use of time for essential tasks. It is also identified that it is more advantageous for DOC+ to collaborate than to compete. The biggest advantage for collaboration with a competitor is the reduction of market entry barriers and having access to their resources.Xavier, RuteVeritatiVecchio, Alexander Schulz Del2023-03-29T00:30:47Z2022-04-272022-032022-04-27T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.14/39051urn:tid:203038142enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-13T10:46:22Zoai:repositorio.ucp.pt:10400.14/39051Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T01:37:35.105820Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices
title Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices
spellingShingle Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices
Vecchio, Alexander Schulz Del
Business model
Machine learning
Self-check-in
Waiting time predictions
Lean Canvas
Value proposition Canvas
Entrepreneurial strategy compass
Patient
Physician
Medical practice
Practice software
Start-up
Germany
Modelo de negócios
Check-in automático
Previsão de tempo de espera
Proposta de valor Canvas
Orientação de estratégia de negócio
Paciente
Médico
Prática médica
Software de prática
Alemanha
title_short Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices
title_full Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices
title_fullStr Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices
title_full_unstemmed Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices
title_sort Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices
author Vecchio, Alexander Schulz Del
author_facet Vecchio, Alexander Schulz Del
author_role author
dc.contributor.none.fl_str_mv Xavier, Rute
Veritati
dc.contributor.author.fl_str_mv Vecchio, Alexander Schulz Del
dc.subject.por.fl_str_mv Business model
Machine learning
Self-check-in
Waiting time predictions
Lean Canvas
Value proposition Canvas
Entrepreneurial strategy compass
Patient
Physician
Medical practice
Practice software
Start-up
Germany
Modelo de negócios
Check-in automático
Previsão de tempo de espera
Proposta de valor Canvas
Orientação de estratégia de negócio
Paciente
Médico
Prática médica
Software de prática
Alemanha
topic Business model
Machine learning
Self-check-in
Waiting time predictions
Lean Canvas
Value proposition Canvas
Entrepreneurial strategy compass
Patient
Physician
Medical practice
Practice software
Start-up
Germany
Modelo de negócios
Check-in automático
Previsão de tempo de espera
Proposta de valor Canvas
Orientação de estratégia de negócio
Paciente
Médico
Prática médica
Software de prática
Alemanha
description The aim of this thesis is to develop an initial business model and validate the business idea of the start-up, named DOC+. The solution offers the most time efficient way to plan and execute a physician visit for practices and patients though self-check-in and though waiting time predictions. First, the business idea is described, followed by an analytical and structured approach to create the business model. It is validated through the analysis of an online survey for patients and semi-structured interviews with physicians. The quantitative data is statistically analyzed with regression analyses and the qualitative data according to Mayring's coding scheme. Ash Maurya's Lean Canvas, a one-page business model, serves as the basis for the thesis. It is designed to serve as a foundation for DOC+ and for the evaluation of strategic plans and projects, which will be refined in future iteration steps. To fill in the key frames of the canvas, different frameworks are used. Key findings are that physicians have a demand to address root causes that trigger waiting times. This points at the excessive burden of administrative tasks and the need for relief. This also represents the greatest value creation for the paying customer, the physician: Reduction of workload for staff and their use of time for essential tasks. It is also identified that it is more advantageous for DOC+ to collaborate than to compete. The biggest advantage for collaboration with a competitor is the reduction of market entry barriers and having access to their resources.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-27
2022-03
2022-04-27T00:00:00Z
2023-03-29T00:30:47Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.14/39051
urn:tid:203038142
url http://hdl.handle.net/10400.14/39051
identifier_str_mv urn:tid:203038142
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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