Business model : reducing waiting time for patients through a self-check-in and a waiting time prediction tool for german medical practices
| Main Author: | |
|---|---|
| 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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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 |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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publishedVersion |
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http://hdl.handle.net/10400.14/39051 urn:tid:203038142 |
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eng |
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openAccess |
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application/pdf |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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