Pub Date : 2021-01-17eCollection Date: 2021-01-01DOI: 10.1080/20476965.2020.1857214
Paul R Harper, Joshua W Moore, Thomas E Woolley
We provide an open-source model to estimate the number of secondary Covid-19 infections caused by potentially infectious students returning from university to private homes with other occupants. Using a Monte-Carlo method and data derived from UK sources, we predict that an infectious student would, on average, infect 0.94 other household members. Or, as a rule of thumb, each infected student would generate (just less than) one secondary within-household infection. The total number of secondary cases for all returning students is dependent on the virus prevalence within each student population at the time of their departure from campus back home. Although the proposed estimation method is general and robust, the results are sensitive to the input data. We provide Matlab code and a helpful online app (http://bit.ly/Secondary_infections_app) that can be used to estimate numbers of secondary infections based on local parameter values. This can be used worldwide to support policy making.
{"title":"Covid-19 transmission modelling of students returning home from university.","authors":"Paul R Harper, Joshua W Moore, Thomas E Woolley","doi":"10.1080/20476965.2020.1857214","DOIUrl":"10.1080/20476965.2020.1857214","url":null,"abstract":"<p><p>We provide an open-source model to estimate the number of secondary Covid-19 infections caused by potentially infectious students returning from university to private homes with other occupants. Using a Monte-Carlo method and data derived from UK sources, we predict that an infectious student would, on average, infect 0.94 other household members. Or, as a rule of thumb, each infected student would generate (just less than) one secondary within-household infection. The total number of secondary cases for all returning students is dependent on the virus prevalence within each student population at the time of their departure from campus back home. Although the proposed estimation method is general and robust, the results are sensitive to the input data. We provide Matlab code and a helpful online app (http://bit.ly/Secondary_infections_app) that can be used to estimate numbers of secondary infections based on local parameter values. This can be used worldwide to support policy making.</p>","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"10 1","pages":"31-40"},"PeriodicalIF":1.8,"publicationDate":"2021-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7946042/pdf/THSS_10_1857214.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25526785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-15eCollection Date: 2022-01-01DOI: 10.1080/20476965.2020.1848356
Ramna Thakur, Shivendra Sangar
By using nationally representative consumption expenditure surveys (CES) conducted by the National Sample Survey Organisation (NSSO) in 1999-2000, 2004-05 and 2011-12, this paper has analysed the socioeconomic differentials in the burden of paying for healthcare in India. The study found that in all waves of data, the concentration of population reporting OOP health expenditure has shown a shift towards poor population, while the concentration of overshoot expenditure is still constant among the rich which is more pronounced in the rural areas of the country. Furthermore, Muslims and Sikhs among different religions, Scheduled Casts among social categories, self-employed and casual/agricultural labour among household types and rural areas among sectors are more likely to incur OOP health expenditure as compared to their counterparts. This study argues for the universal health insurance coverage to protect households from the significant burden of expenditure on critical healthcare.
{"title":"Socioeconomic differentials in the burden of paying for healthcare in India: a disaggregated analysis.","authors":"Ramna Thakur, Shivendra Sangar","doi":"10.1080/20476965.2020.1848356","DOIUrl":"https://doi.org/10.1080/20476965.2020.1848356","url":null,"abstract":"<p><p>By using nationally representative consumption expenditure surveys (CES) conducted by the National Sample Survey Organisation (NSSO) in 1999-2000, 2004-05 and 2011-12, this paper has analysed the socioeconomic differentials in the burden of paying for healthcare in India. The study found that in all waves of data, the concentration of population reporting OOP health expenditure has shown a shift towards poor population, while the concentration of overshoot expenditure is still constant among the rich which is more pronounced in the rural areas of the country. Furthermore, Muslims and Sikhs among different religions, Scheduled Casts among social categories, self-employed and casual/agricultural labour among household types and rural areas among sectors are more likely to incur OOP health expenditure as compared to their counterparts. This study argues for the universal health insurance coverage to protect households from the significant burden of expenditure on critical healthcare.</p>","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"11 1","pages":"48-58"},"PeriodicalIF":1.8,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/20476965.2020.1848356","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39756481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-15eCollection Date: 2022-01-01DOI: 10.1080/20476965.2020.1857663
Guillaume Lamé, Sonya Crowe, Matthew Barclay
Despite an increasing number of papers reporting applications of operational research (OR) to problems in healthcare, there remains little empirical evidence of OR improving healthcare delivery in practice. Without such evidence it is harder both to justify the usefulness of OR to a healthcare audience and to learn and continuously improve our approaches. To progress, we need to build the evidence-base on whether and how OR improves healthcare delivery through careful empirical evaluation. This position paper reviews evaluation standards in healthcare improvement research and dispels some common myths about evaluation. It highlights the current lack of robust evaluation of healthcare OR and makes the case for addressing this. It then proposes possible ways for building better empirical evaluations of OR interventions in healthcare.
{"title":"\"What's the evidence?\"-Towards more empirical evaluations of the impact of OR interventions in healthcare.","authors":"Guillaume Lamé, Sonya Crowe, Matthew Barclay","doi":"10.1080/20476965.2020.1857663","DOIUrl":"10.1080/20476965.2020.1857663","url":null,"abstract":"<p><p>Despite an increasing number of papers reporting applications of operational research (OR) to problems in healthcare, there remains little empirical evidence of OR improving healthcare delivery in practice. Without such evidence it is harder both to justify the usefulness of OR to a healthcare audience and to learn and continuously improve our approaches. To progress, we need to build the evidence-base on whether and how OR improves healthcare delivery through careful empirical evaluation. This position paper reviews evaluation standards in healthcare improvement research and dispels some common myths about evaluation. It highlights the current lack of robust evaluation of healthcare OR and makes the case for addressing this. It then proposes possible ways for building better empirical evaluations of OR interventions in healthcare.</p>","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"11 1","pages":"59-67"},"PeriodicalIF":1.2,"publicationDate":"2020-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8812794/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39756482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-28eCollection Date: 2022-01-01DOI: 10.1080/20476965.2020.1848355
Mohd Shoaib, Utkarsh Prabhakar, Sumit Mahlawat, Varun Ramamohan
We present a discrete-event simulation model of the kidney transplantation system in an Indian state, Rajasthan. Organs are generated across the state based on the organ donation rate among the general population, and are allocated to patients on the kidney transplantation waitlist. The organ allocation algorithm is developed using official guidelines published for kidney transplantation, and model parameters were estimated using publicly available data to the extent possible. Transplantation outcomes generated by the model include: (a) the probabilities of a patient receiving an organ within one to 5 years of registration and (b) the average number of deaths per year due to lack of donated organs. Simulation experiments involving observing the effect of increasing the organ arrival rate and establishing additional transplantation centres on transplantation outcomes are also conducted. We also demonstrate the use of such a model to optimally locate additional transplantation centres using simulation optimisation methods.
{"title":"A discrete-event simulation model of the kidney transplantation system in Rajasthan, India.","authors":"Mohd Shoaib, Utkarsh Prabhakar, Sumit Mahlawat, Varun Ramamohan","doi":"10.1080/20476965.2020.1848355","DOIUrl":"https://doi.org/10.1080/20476965.2020.1848355","url":null,"abstract":"<p><p>We present a discrete-event simulation model of the kidney transplantation system in an Indian state, Rajasthan. Organs are generated across the state based on the organ donation rate among the general population, and are allocated to patients on the kidney transplantation waitlist. The organ allocation algorithm is developed using official guidelines published for kidney transplantation, and model parameters were estimated using publicly available data to the extent possible. Transplantation outcomes generated by the model include: (a) the probabilities of a patient receiving an organ within one to 5 years of registration and (b) the average number of deaths per year due to lack of donated organs. Simulation experiments involving observing the effect of increasing the organ arrival rate and establishing additional transplantation centres on transplantation outcomes are also conducted. We also demonstrate the use of such a model to optimally locate additional transplantation centres using simulation optimisation methods.</p>","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"11 1","pages":"30-47"},"PeriodicalIF":1.8,"publicationDate":"2020-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/20476965.2020.1848355","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39756480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-26eCollection Date: 2022-01-01DOI: 10.1080/20476965.2020.1848357
Maartje Zonderland, Jos Bekkers, Jasper van Bommel, Maarten Ter Horst, Wouter van Leeuwen, Femke van den Wall Bake, Willem Wiegersma, Ad Bogers
The Thoraxcenter of Erasmus MC started an improvement project in 2015 in order to increase the number of open-heart surgeries by 150 for three consecutive years (450 in total, +46%), and to decrease the access time from 12-14 to 2-3 weeks by the end of 2016. This was required to attain economy of scale in a highly competitive market. In this paper we describe the first year of the project, focusing on its structure and interventions taken, resulting in 165 additional open-heart surgeries carried out in 2016 and a significantly shorter access time of 2-3 weeks.
{"title":"Increasing cardio-thoracic productivity at Erasmus MC.","authors":"Maartje Zonderland, Jos Bekkers, Jasper van Bommel, Maarten Ter Horst, Wouter van Leeuwen, Femke van den Wall Bake, Willem Wiegersma, Ad Bogers","doi":"10.1080/20476965.2020.1848357","DOIUrl":"https://doi.org/10.1080/20476965.2020.1848357","url":null,"abstract":"<p><p>The Thoraxcenter of Erasmus MC started an improvement project in 2015 in order to increase the number of open-heart surgeries by 150 for three consecutive years (450 in total, +46%), and to decrease the access time from 12-14 to 2-3 weeks by the end of 2016. This was required to attain economy of scale in a highly competitive market. In this paper we describe the first year of the project, focusing on its structure and interventions taken, resulting in 165 additional open-heart surgeries carried out in 2016 and a significantly shorter access time of 2-3 weeks.</p>","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"11 1","pages":"68-74"},"PeriodicalIF":1.8,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/20476965.2020.1848357","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39756483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-13DOI: 10.1101/2020.11.11.20229559
Paul Robert Harper, Joshua W. Moore, Thomas E. Woolley
We estimate the number of secondary Covid-19 infections caused by potentially infectious students returning from university to private homes with other occupants. Using a Monte-Carlo method and data derived from UK sources, we predict that an infectious student would, on average, infect 0.94 other household members. Or, as a rule of thumb, each infected student would generate (just less than) one secondary within-household infection. The total number of secondary cases for all returning students is dependent on the virus prevalence within the student population at the time of their departure from campus back home. Correspondingly, we provide results for prevalence ranging from 0.5% to 15%, which is based on observed minimum and maximum estimates from Cardiff University's asymptomatic testing service. Although the proposed estimation method is general and robust, the results are sensitive to the input data. We therefore provide Matlab code and a helpful online app (http://bit.ly/Secondary_infections_app) that can be used to estimate numbers of secondary infections based on local parameter values
{"title":"Secondary Household Covid-19 Transmission Modelling of Students Returning Home from University","authors":"Paul Robert Harper, Joshua W. Moore, Thomas E. Woolley","doi":"10.1101/2020.11.11.20229559","DOIUrl":"https://doi.org/10.1101/2020.11.11.20229559","url":null,"abstract":"We estimate the number of secondary Covid-19 infections caused by potentially infectious students returning from university to private homes with other occupants. Using a Monte-Carlo method and data derived from UK sources, we predict that an infectious student would, on average, infect 0.94 other household members. Or, as a rule of thumb, each infected student would generate (just less than) one secondary within-household infection. The total number of secondary cases for all returning students is dependent on the virus prevalence within the student population at the time of their departure from campus back home. Correspondingly, we provide results for prevalence ranging from 0.5% to 15%, which is based on observed minimum and maximum estimates from Cardiff University's asymptomatic testing service. Although the proposed estimation method is general and robust, the results are sensitive to the input data. We therefore provide Matlab code and a helpful online app (http://bit.ly/Secondary_infections_app) that can be used to estimate numbers of secondary infections based on local parameter values","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"1 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62316834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-06eCollection Date: 2022-01-01DOI: 10.1080/20476965.2020.1813056
Gustavo M Bacelar-Silva, James F Cox, Pedro Pereira Rodrigues
ABSTRACT Despite ever-increasing resources devoted to healthcare, lack of capacity and timeliness are still chronic problems worldwide. This systematic review aims to present an overview of the Theory of Constraints (TOC) implementations in healthcare services and their outcomes. We analysed 42 TOC implementations (15 full-text articles, 12 video proceedings, and 2 theses/disserations) from major scientific electronic databases and TOC International Certification Organization Conferences. All implementations reported positive outcomes, both tangible and intangible. The two main improvements reported by authors were in productivity (98%; n = 41) – more patients treated – and in the timeliness of care (83%; n = 35). Furthermore, the selected studies reported dramatic improvements: 50% mean reductions in patient waiting time; 38% reduction in patient length of stay; 43% mean increase in operating room productivity and 34% mean increase in throughput. TOC implementations attained positive results in all levels of the health and social care chain. Most TOC recommendations and changes showed almost immediate results and required little or no additional cost to implement. Evidence supports TOC as a promising solution for the chronic healthcare problem, improving quality and timeliness, both necessary conditions for providing effective healthcare.
{"title":"Outcomes of managing healthcare services using the Theory of Constraints: A systematic review.","authors":"Gustavo M Bacelar-Silva, James F Cox, Pedro Pereira Rodrigues","doi":"10.1080/20476965.2020.1813056","DOIUrl":"10.1080/20476965.2020.1813056","url":null,"abstract":"ABSTRACT Despite ever-increasing resources devoted to healthcare, lack of capacity and timeliness are still chronic problems worldwide. This systematic review aims to present an overview of the Theory of Constraints (TOC) implementations in healthcare services and their outcomes. We analysed 42 TOC implementations (15 full-text articles, 12 video proceedings, and 2 theses/disserations) from major scientific electronic databases and TOC International Certification Organization Conferences. All implementations reported positive outcomes, both tangible and intangible. The two main improvements reported by authors were in productivity (98%; n = 41) – more patients treated – and in the timeliness of care (83%; n = 35). Furthermore, the selected studies reported dramatic improvements: 50% mean reductions in patient waiting time; 38% reduction in patient length of stay; 43% mean increase in operating room productivity and 34% mean increase in throughput. TOC implementations attained positive results in all levels of the health and social care chain. Most TOC recommendations and changes showed almost immediate results and required little or no additional cost to implement. Evidence supports TOC as a promising solution for the chronic healthcare problem, improving quality and timeliness, both necessary conditions for providing effective healthcare.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"11 1","pages":"1-16"},"PeriodicalIF":1.8,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/20476965.2020.1813056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39756478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-29eCollection Date: 2022-01-01DOI: 10.1080/20476965.2020.1822146
Stephen McCarthy, Ciara Fitzgerald, Laura Sahm, Colin Bradley, Elaine K Walsh
Patient-held Health Information Technologies (HIT) can reduce medical error by improving communication between patients and the healthcare team. Despite the proposed benefits, the roll-out of patient-held HIT solutions remains nascent, leaving considerable gaps in our understanding of the adoption challenges inherent. This paper adopts Normalisation Process Theory to study the factors which support or impede the adoption and "normalisation" of patient-held HIT, particularly across the primary-secondary care interface. The authors conducted an in-depth case study of HIT adoption across four GP practices, and the wards of a 350 bed hospital. 35 semi-structured interviews were completed. Findings point towards both user-specific and network-specific factors as significant challenges to normalisation across primary-secondary care. This includes factors related to interactional workability, skill set workability, relational integration, and contextual integration. We also discuss challenges specific to patient-held HIT adoption e.g., understanding the patient/clinician experience, supporting informal clinician networks, and spanning across IT boundaries.
{"title":"Patient-held health IT adoption across the primary-secondary care interface: a Normalisation Process Theory perspective.","authors":"Stephen McCarthy, Ciara Fitzgerald, Laura Sahm, Colin Bradley, Elaine K Walsh","doi":"10.1080/20476965.2020.1822146","DOIUrl":"https://doi.org/10.1080/20476965.2020.1822146","url":null,"abstract":"<p><p>Patient-held Health Information Technologies (HIT) can reduce medical error by improving communication between patients and the healthcare team. Despite the proposed benefits, the roll-out of patient-held HIT solutions remains nascent, leaving considerable gaps in our understanding of the adoption challenges inherent. This paper adopts Normalisation Process Theory to study the factors which support or impede the adoption and \"normalisation\" of patient-held HIT, particularly across the primary-secondary care interface. The authors conducted an in-depth case study of HIT adoption across four GP practices, and the wards of a 350 bed hospital. 35 semi-structured interviews were completed. Findings point towards both user-specific and network-specific factors as significant challenges to normalisation across primary-secondary care. This includes factors related to interactional workability, skill set workability, relational integration, and contextual integration. We also discuss challenges specific to patient-held HIT adoption e.g., understanding the patient/clinician experience, supporting informal clinician networks, and spanning across IT boundaries.</p>","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"11 1","pages":"17-29"},"PeriodicalIF":1.8,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/20476965.2020.1822146","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39756479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-13eCollection Date: 2021-01-01DOI: 10.1080/20476965.2020.1817801
Usama Kadri
ABSTRACT Rapid testing of appropriate samples from patients suspected for a disease during an epidemic, such as the current Coronavirus outbreak, is of a great importance for disease management and control. We propose a method to enhance processing large amounts of collected samples. The method is based on mixing samples in testing tubes (pooling) in a specific configuration, as opposed to testing single samples in each tube, and recognise infected samples from variations of the total infection rates in each tube. To illustrate the efficiency of the suggested method, we carry out numerical tests for actual scenarios under various test conditions. Applying the proposed method allows testing many more patients using the same number of testing tubes, where all positives are identified with no false negatives, and no need for independent testing, and the effective testing time can be reduced drastically even when the uncertainty in the test is relatively high.
{"title":"Variation of quantified infection rates of mixed samples to enhance rapid testing during an epidemic.","authors":"Usama Kadri","doi":"10.1080/20476965.2020.1817801","DOIUrl":"https://doi.org/10.1080/20476965.2020.1817801","url":null,"abstract":"ABSTRACT Rapid testing of appropriate samples from patients suspected for a disease during an epidemic, such as the current Coronavirus outbreak, is of a great importance for disease management and control. We propose a method to enhance processing large amounts of collected samples. The method is based on mixing samples in testing tubes (pooling) in a specific configuration, as opposed to testing single samples in each tube, and recognise infected samples from variations of the total infection rates in each tube. To illustrate the efficiency of the suggested method, we carry out numerical tests for actual scenarios under various test conditions. Applying the proposed method allows testing many more patients using the same number of testing tubes, where all positives are identified with no false negatives, and no need for independent testing, and the effective testing time can be reduced drastically even when the uncertainty in the test is relatively high.","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"10 1","pages":"24-30"},"PeriodicalIF":1.8,"publicationDate":"2020-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/20476965.2020.1817801","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25526784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-30eCollection Date: 2021-01-01DOI: 10.1080/20476965.2020.1803148
Ralf Müller-Polyzou, Melanie Reuter-Oppermann, Anke Engbert, Raphael Schmidt
Increasing efficiency and reducing risk in radiotherapy cancer treatment is of high importance. User assistance systems within a digitally connected radiotherapy environment can support all involved professionals to perform their individual tasks faster and better. This paper presents a qualitative analysis of radiotherapy workflows and a corresponding process modelling in order to identify hypothetical user assistance systems for specific process activities. In addition, the results of an empirical study on the identified systems are presented together with derived requirements and design principles for these systems. A structured online survey with 50 medical physicists in Germany has been conducted. Among others the acceptance, the increase of perceived efficiency and the risk reduction while using the assistance systems are analysed and discussed. The results support the creation of value adding user assistance systems for radiotherapy that improve efficiency, reduce treatment risks and reach high user acceptance levels.
{"title":"Identifying user assistance systems for radiotherapy to increase efficiency and help saving lives.","authors":"Ralf Müller-Polyzou, Melanie Reuter-Oppermann, Anke Engbert, Raphael Schmidt","doi":"10.1080/20476965.2020.1803148","DOIUrl":"10.1080/20476965.2020.1803148","url":null,"abstract":"<p><p>Increasing efficiency and reducing risk in radiotherapy cancer treatment is of high importance. User assistance systems within a digitally connected radiotherapy environment can support all involved professionals to perform their individual tasks faster and better. This paper presents a qualitative analysis of radiotherapy workflows and a corresponding process modelling in order to identify hypothetical user assistance systems for specific process activities. In addition, the results of an empirical study on the identified systems are presented together with derived requirements and design principles for these systems. A structured online survey with 50 medical physicists in Germany has been conducted. Among others the acceptance, the increase of perceived efficiency and the risk reduction while using the assistance systems are analysed and discussed. The results support the creation of value adding user assistance systems for radiotherapy that improve efficiency, reduce treatment risks and reach high user acceptance levels.</p>","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"10 4","pages":"318-336"},"PeriodicalIF":1.2,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8567950/pdf/THSS_10_1803148.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39597978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}