scholarly journals Researching, characterising, co-creating and testing innovations in Paper Health Information Systems (PHISICC) to support frontline health workers decision-making: protocol of a multi-country, transdisciplinary, mixed-methods research programme in three Sub-Saharan countries

2021 ◽  
Author(s):  
Xavier Bosch-Capblanch ◽  
David O'Donnell ◽  
L Kendall Krause ◽  
Christian Auer ◽  
Angela Oyo-Ita ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Information Systems ◽  
Health Information ◽  
Health Workers ◽  
Health Information Systems ◽  
Frontline Health Workers ◽  
Rural Settings ◽  
Wide Range ◽  
Sub Saharan

Abstract BackgroundHealth Information Systems (HIS) are crucial to provide data for decision-making and data demands are constantly growing. However, the link between data and decisions is not always rational nor linear and the management of data ends up overloading frontline health workers, who may have to compromise the health care. Despite limited evidence, there is an increasing push for HIS digitalisation, which faces enormous challenges, particularly in remote, rural settings in low- and middle-income countries. Paper-based tools will continue to be used and this warrants efforts to make them more responsive to local needs. Paper Health Information Systems (PHISICC) is a transdisciplinary, multi-country research initiative to create and test innovative paper-based HIS in three Sub-Saharan African countries.MethodsThe PHISICC initiative is taking place in remote, rural settings, in Côte d’Ivoire, Mozambique and Nigeria, through partnership with Ministries of Health and research institutions. We began with research syntheses to acquire the most up to date knowledge on HIS. These were coupled with field work in the three countries to understand the current design, patterns and contexts of use, and health care worker perspectives. Frontline health workers, with designers and researchers, used co-creation methods to produce the new PHISICC tools. This suite of tools is being tested in the three countries. Throughout the project we have engaged with a wide range of stakeholders and have kept the highest scientific standards to keep it relevant to health policy in each of the three countries.DiscussionWe have deployed a comprehensive research approach to ensure the robustness and future policy uptake of the finding. Beyond the resulting paper-based tool design innovations, our process itself was innovative. Rather than emphasizing the data management compliance aspects we focused instead on frontline health workers’ decision-making; by tackling the whole scope of health care areas in PHC rather than incremental improvement to existing tools, we developed an entirely new design approach and language for a suite of tools in Primary Health Care. The initiative is being tested in remote, rural areas where the most vulnerable live.

scholarly journals Researching, Co-creating and Testing Innovations in Paper Health Information Systems (PHISICC) to Support Health Workers Decision-making: Protocol of a Multi-country, Transdisciplinary, Mixed-methods Research Programme in Three Sub-saharan Countries

2021 ◽  
Author(s):  
Xavier Bosch-Capblanch ◽  
David O’Donnell ◽  
L Kendall Krause ◽  
Christian Auer ◽  
Angela Oyo-Ita ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Information Systems ◽  
Health Information ◽  
Health Workers ◽  
Health Information Systems ◽  
Primary Health ◽  
Frontline Health Workers ◽  
Rural Settings ◽  
Sub Saharan

Abstract BackgroundHealth Information Systems are crucial to provide data for decision-making and data demands are constantly growing. However, the link between data and decisions is not always rational nor linear and the management of data ends up overloading frontline health workers, who may have to compromise the health care. Despite limited evidence, there is an increasing push for the digitalisation of Health Information Systems, which faces enormous challenges, particularly in remote, rural settings in low- and middle-income countries. Paper-based tools will continue to be used and this warrants efforts to make them more responsive to local needs. Paper Health Information Systems (PHISICC) is a transdisciplinary, multi-country research initiative to create and test innovative paper-based Health Information Systems in three Sub-Saharan African countries.MethodsThe PHISICC initiative is taking place in remote, rural settings, in Côte d’Ivoire, Mozambique and Nigeria, through partnership with Ministries of Health and research institutions. We began with research syntheses to acquire the most up to date knowledge on Health Information Systems. These were coupled with field work in the three countries to understand the current design, patterns and contexts of use, and health care worker perspectives. Frontline health workers, with designers and researchers, used co-creation methods to produce the new PHISICC tools. This suite of tools is being tested in the three countries. Throughout the project, we have engaged with a wide range of stakeholders and have kept the highest scientific standards to keep it relevant to health policy in each of the three countries.DiscussionWe have deployed a comprehensive research approach to ensure the robustness and future policy uptake of the finding. Beyond the resulting paper-based tool design innovations, our process itself was innovative. Rather than emphasizing the data management compliance aspects we focused instead on frontline health workers’ decision-making; by tackling the whole scope of health care areas in Primary Health Care rather than incremental improvement to existing tools, we developed an entirely new design approach and language for a suite of tools in Primary Health Care. The initiative is being tested in remote, rural areas where the most vulnerable live.

scholarly journals Researching, co-creating and testing innovations in paper-based health information systems (PHISICC) to support health workers’ decision-making: protocol of a multi-country, transdisciplinary, mixed-methods research programme in three sub-Saharan countries

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Xavier Bosch-Capblanch ◽  
David O’Donnell ◽  
L. Kendall Krause ◽  
Christian Auer ◽  
Angela Oyo-Ita ◽  
...  
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Health Information ◽  
Health Workers ◽  
Health Information Systems ◽  
Research Approach ◽  
Frontline Health Workers ◽  
Rural Settings ◽  
Wide Range ◽  
Sub Saharan

Abstract Background Health information systems are crucial to provide data for decision-making and demand for data is constantly growing. However, the link between data and decisions is not always rational or linear and the management of data ends up overloading frontline health workers, which may compromise quality of healthcare delivery. Despite limited evidence, there is an increasing push for the digitalization of health information systems, which poses enormous challenges, particularly in remote, rural settings in low- and middle-income countries. Paper-based tools will continue to be used in combination with digital solutions and this calls for efforts to make them more responsive to local needs. Paper-based Health Information Systems in Comprehensive Care (PHISICC) is a transdisciplinary, multi-country research initiative to create and test innovative paper-based health information systems in three sub-Saharan African countries. Methods/Design The PHISICC initiative is being carried out in remote, rural settings in Côte d’Ivoire, Mozambique and Nigeria through partnership with ministries of health and research institutions. We began with research syntheses to acquire the most up-to-date knowledge on health information systems. These were coupled with fieldwork in the three countries to understand the current design, patterns and contexts of use, and healthcare worker perspectives. Frontline health workers, with designers and researchers, used co-creation methods to produce the new PHISICC tools. This suite of tools is being tested in the three countries in three cluster-randomized controlled trials. Throughout the project, we have engaged with a wide range of stakeholders and have maintained the highest scientific standards to ensure that results are relevant to the realities in the three countries. Discussion We have deployed a comprehensive research approach to ensure the robustness and future policy uptake of findings. Besides the innovative PHISICC paper-based tools, our process is in itself innovative. Rather than emphasizing the technical dimensions of data management, we focused instead on frontline health workers’ data use and decision-making. By tackling the whole scope of primary healthcare areas rather than a subset of them, we have developed an entirely new design and visual language for a suite of tools across healthcare areas. The initiative is being tested in remote, rural areas where the most vulnerable live.

scholarly journals Robotic Systems in Operating Theaters: New Forms of Team–Machine Interaction in Health Care

2019 ◽  
Vol 58 (S 01) ◽  
pp. e14-e25 ◽  
Author(s):  
Jochen Steil ◽  
Dominique Finas ◽  
Susanne Beck ◽  
Arne Manzeschke ◽  
Reinhold Haux
Keyword(s):  
Health Care ◽  
Information Systems ◽  
Health Information ◽  
Health Care Professionals ◽  
New Technologies ◽  
Health Information Systems ◽  
Robotic Systems ◽  
Intelligent Machines ◽  
Wide Range ◽  
Machine Interaction

Background Health information systems have developed rapidly and considerably during the last decades, taking advantage of many new technologies. Robots used in operating theaters represent an exceptional example of this trend. Yet, the more these systems are designed to act autonomously and intelligently, the more complex and ethical questions arise about serious implications of how future hybrid clinical team–machine interactions ought to be envisioned, in situations where actions and their decision-making are continuously shared between humans and machines. Objectives To discuss the many different viewpoints—from surgery, robotics, medical informatics, law, and ethics—that the challenges of novel team–machine interactions raise, together with potential consequences for health information systems, in particular on how to adequately consider what hybrid actions can be specified, and in which sense these do imply a sharing of autonomous decisions between (teams of) humans and machines, with robotic systems in operating theaters as an example. Results Team–machine interaction and hybrid action of humans and intelligent machines, as is now becoming feasible, will lead to fundamental changes in a wide range of applications, not only in the context of robotic systems in surgical operating theaters. Collaboration of surgical teams in operating theaters as well as the roles, competencies, and responsibilities of humans (health care professionals) and machines (robotic systems) need to be reconsidered. Hospital information systems will in future not only have humans as users, but also provide the ground for actions of intelligent machines. Conclusions The expected significant changes in the relationship of humans and machines can only be appropriately analyzed and considered by inter- and multidisciplinary collaboration. Fundamentally new approaches are needed to construct the reasonable concepts surrounding hybrid action that will take into account the ascription of responsibility to the radically different types of human versus nonhuman intelligent agents involved.

scholarly journals Discussion of “Representation of People’s Decisions in Health Information Systems: A Complementary Approach for Understanding Health Care Systems and Population Health”

2017 ◽  
Vol 56 (S 01) ◽  
pp. e20-e29 ◽  
Author(s):  
Najeeb Al-Shorbaji ◽  
Elizabeth Borycki ◽  
Michio Kimura ◽  
Christoph Lehmann ◽  
Nancy Lorenzi ◽  
...  
Keyword(s):  
Health Care ◽  
Information Systems ◽  
Health Information ◽  
Population Health ◽  
Health Care Systems ◽  
Health Information Systems ◽  
Letters To The Editor ◽  
Discussion Section ◽  
Complementary Approach ◽  
Care Systems

SummaryThis article is part of a For-Discussion-Section of Methods of Information in Medicine about the paper “Representation of People’s Decisions in Health Information Systems: A Complementary Approach for Understanding Health Care Systems and Population Health” written by Fernan Gonzalez Bernaldo de Qui-ros, Adriana Ruth Dawidowski, and Silvana Figar. It is introduced by an editorial. This article contains the combined commentaries invited to independently comment on the paper of de Quiros, Dawidowski, and Figar. In subsequent issues the discussion can continue through letters to the editor.

scholarly journals Health Information Systems

2010 ◽  
Vol 19 (01) ◽  
pp. 30-33
Author(s):  
C. Bréant ◽  
Keyword(s):  
Health Care ◽  
Information Systems ◽  
Health Information ◽  
Health Information Systems ◽  
It Alignment

Summary Objectives: Summarize excellent current research in the field of Health Information Systems. Method: Synopsis of the articles selected for the IMIA Yearbook 2010. Results: Five papers from international peer reviewed journals have been selected for the section on health information systems. Conclusions: The elected articles illustrate how health care IT alignment, assessment and benchmarking have become a challenge and a key aspect to the strengthening of health information systems in order to maintain and expand the objectives and strategies of organizations.

scholarly journals Producing routine malaria data: an exploration of the micro-practices and processes shaping routine malaria data quality in frontline health facilities in Kenya

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
George Okello ◽  
Sassy Molyneux ◽  
Scholastica Zakayo ◽  
Rene Gerrets ◽  
Caroline Jones
Keyword(s):  
Information Systems ◽  
Data Collection ◽  
Health Information ◽  
Low Income ◽  
Health Workers ◽  
National Level ◽  
Health Information Systems ◽  
Health Facilities ◽  
Careful Examination ◽  
Data Generation

Abstract Background Routine health information systems can provide near real-time data for malaria programme management, monitoring and evaluation, and surveillance. There are widespread concerns about the quality of the malaria data generated through routine information systems in many low-income countries. However, there has been little careful examination of micro-level practices of data collection which are central to the production of routine malaria data. Methods Drawing on fieldwork conducted in two malaria endemic sub-counties in Kenya, this study examined the processes and practices that shape routine malaria data generation at frontline health facilities. The study employed ethnographic methods—including observations, records review, and interviews—over 18-months in four frontline health facilities and two sub-county health records offices. Data were analysed using a thematic analysis approach. Results Malaria data generation was influenced by a range of factors including human resource shortages, tool design, and stock-out of data collection tools. Most of the challenges encountered by health workers in routine malaria data generation had their roots in wider system issues and at the national level where the framing of indicators and development of data collection tools takes place. In response to these challenges, health workers adopted various coping mechanisms such as informal task shifting and use of improvised tools. While these initiatives sustained the data collection process, they also had considerable implications for the data recorded and led to discrepancies in data that were recorded in primary registers. These discrepancies were concealed in aggregated monthly reports that were subsequently entered into the District Health Information Software 2. Conclusion Challenges to routine malaria data generation at frontline health facilities are not malaria or health information systems specific; they reflect wider health system weaknesses. Any interventions seeking to improve routine malaria data generation must look beyond just malaria or health information system initiatives and include consideration of the broader contextual factors that shape malaria data generation.

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