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Feldacker C, Usiri J, Kiruthu-Kamamia C, Waehrer G, Weldemariam H, Huwa J, Hau J, Thawani A, Chapanda M, Tweya H. Crossing the digital divide: the workload of manual data entry and integration between mobile health applications and eHealth infrastructure. OXFORD OPEN DIGITAL HEALTH 2024; 2:ii9-ii17. [PMID: 40191682 PMCID: PMC11936321 DOI: 10.1093/oodh/oqae025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 04/06/2024] [Accepted: 05/23/2024] [Indexed: 04/09/2025]
Abstract
Many digital health interventions (DHIs), including mobile health (mHealth) apps, aim to improve both client outcomes and efficiency like electronic medical record systems (EMRS). Although interoperability is the gold standard, it is also complex and costly, requiring technical expertise, stakeholder permissions and sustained funding. Manual data linkage processes are commonly used to 'integrate' across systems and allow for assessment of DHI impact, a best practice, before further investment. For mHealth, the manual data linkage workload, including related monitoring and evaluation (M&E) activities, remains poorly understood. As a baseline study for an open-source app to mirror EMRS and reduce healthcare worker (HCW) workload while improving care in the Nurse-led Community-based Antiretroviral therapy Program (NCAP) in Lilongwe, Malawi, we conducted a time-motion study observing HCWs completing data management activities, including routine M&E and manual data linkage of individual-level app data to EMRS. Data management tasks should reduce or end with successful app implementation and EMRS integration. Data were analysed in Excel. We observed 69:53:00 of HCWs performing routine NCAP service delivery tasks: 39:52:00 (57%) was spent completing M&E data related tasks of which 15:57:00 (23%) was spent on manual data linkage workload, alone. Understanding the workload to ensure quality M&E data, including to complete manual data linkage of mHealth apps to EMRS, provides stakeholders with inputs to drive DHI innovations and integration decision making. Quantifying potential mHealth benefits on more efficient, high-quality M&E data may trigger new innovations to reduce workloads and strengthen evidence to spur continuous improvement.
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Affiliation(s)
- Caryl Feldacker
- Department of Global Health, University of Washington, 3980 15th Ave NE, Seattle, WA 98195, USA
- International Training and Education Center for Health, HMC#359932325 9th Avenue, Seattle, WA 98104-2499, USA
| | - Joel Usiri
- Department of Epidemiology, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA
| | - Christine Kiruthu-Kamamia
- International Training and Education Center for Health, HMC#359932325 9th Avenue, Seattle, WA 98104-2499, USA
- Lighthouse Trust, Kamuzu Central Hospital Area 33 Mzimba Street. P.O. Box 106, Lilongwe, Malawi
| | - Geetha Waehrer
- Pacific Institute for Research and Evaluation (PIRE), 4061 Powder Mill Rd # 350, Beltsville, MD, USA
| | - Hiwot Weldemariam
- Department of Epidemiology, University of Washington, 3980 15th Ave NE, Seattle, WA, 98195, USA
| | - Jacqueline Huwa
- Lighthouse Trust, Kamuzu Central Hospital Area 33 Mzimba Street. P.O. Box 106, Lilongwe, Malawi
| | - Jessie Hau
- Lighthouse Trust, Kamuzu Central Hospital Area 33 Mzimba Street. P.O. Box 106, Lilongwe, Malawi
| | - Agness Thawani
- Lighthouse Trust, Kamuzu Central Hospital Area 33 Mzimba Street. P.O. Box 106, Lilongwe, Malawi
| | - Mirriam Chapanda
- Lighthouse Trust, Kamuzu Central Hospital Area 33 Mzimba Street. P.O. Box 106, Lilongwe, Malawi
| | - Hannock Tweya
- Department of Global Health, University of Washington, 3980 15th Ave NE, Seattle, WA 98195, USA
- International Training and Education Center for Health, Capital City Lilongwe 3, Plot 13/14, 1st Floor ARWA House, Lilongwe, Malawi
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Rajagopal S, Balakrishnan V, Chiam YK. The direct effect of institutional factors on healthcare information systems (HIS) organisational interoperability in Malaysian public hospitals. Health Informatics J 2024; 30:14604582241294218. [PMID: 39431340 DOI: 10.1177/14604582241294218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2024]
Abstract
Background: Organisational interoperability (OIoP) of the Healthcare Information System (HIS) is crucial for the success of HIS, however little is known about the impact of institutional factors. Objective: This cross-sectional study aimed to investigate the direct effect of institutional factors on OIoP for HIS in public sector hospitals in Malaysia. Methods: A conceptual OIoP framework was developed using the Personal Health Systems Interoperability and Refined eHealth European Interoperability frameworks. A self-administered questionnaire survey was used to solicit data from 300 healthcare professionals. Data were assessed through an Exploratory Factor Analysis followed by a Confirmatory Factor Analysis. Results: Structured equation modelling revealed Security and Privacy Compliance, and Stakeholder Engagement and Awareness to significantly and positively affect OIoP (R2 = 0.380). Conclusion: Healthcare organisations should prioritise clear and effective policies and regulations and enough budget and resources for the suggested framework.
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Affiliation(s)
- Saravanan Rajagopal
- Department of Information Systems, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Vimala Balakrishnan
- Department of Information Systems, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Yin Kia Chiam
- Department of Software Engineering, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia
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Feldacker C, Usiri J, Kiruthu-Kamamia C, Waehrer G, Weldemariam H, Huwa J, Hau J, Thawani A, Chapanda M, Tweya H. Crossing the digital divide: The workload of manual data entry for integration between mobile health applications and eHealth infrastructure. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.23.24306024. [PMID: 38712169 PMCID: PMC11071550 DOI: 10.1101/2024.04.23.24306024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Background Many digital health interventions (DHIs), including mobile health (mHealth) apps, aim to improve both client outcomes and efficiency like electronic medical record systems (EMRS). Although interoperability is the gold standard, it is also complex and costly, requiring technical expertise, stakeholder permissions, and sustained funding. Manual data linkage processes are commonly used to "integrate" across systems and allow for assessment of DHI impact, a best practice, before further investment. For mHealth, the manual data linkage workload, including related monitoring and evaluation (M&E) activities, remains poorly understood. Methodology As a baseline study for an open-source app to mirror EMRS and reduce healthcare worker (HCW) workload while improving care in the Nurse-led Community-based Antiretroviral therapy Program (NCAP) in Lilongwe, Malawi, we conducted a time-motion study observing HCWs completing data management activities, including routine M&E and manual data linkage of individual-level app data to EMRS. Data management tasks should reduce or end with successful app implementation and EMRS integration. Data was analysed in Excel. Results We observed 69:53:00 of HCWs performing routine NCAP service delivery tasks: 39:52:00 (57%) was spent completing M&E data related tasks of which 15:57:00 (23%) was spent on manual data linkage workload, alone. Conclusion Understanding the workload to ensure quality M&E data, including to complete manual data linkage of mHealth apps to EMRS, provides stakeholders with inputs to drive DHI innovations and integration decision making. Quantifying potential mHealth benefits on more efficient, high-quality M&E data may trigger new innovations to reduce workloads and strengthen evidence to spur continuous improvement.
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Affiliation(s)
- Caryl Feldacker
- Department of Global Health, University of Washington, Seattle, WA USA
- International Training and Education Center for Health, Seattle, WA USA
| | - Joel Usiri
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Christine Kiruthu-Kamamia
- International Training and Education Center for Health, Seattle, WA USA
- Lighthouse Trust, Lilongwe, Malawi
| | - Geetha Waehrer
- Pacific Institute for Research and Evaluation (PIRE), Washington, DC USA
| | - Hiwot Weldemariam
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | | | | | | | | | - Hannock Tweya
- Department of Global Health, University of Washington, Seattle, WA USA
- International Training and Education Center for Health, Malawi
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Wang R, Zhang J, He S, Guo H, Li T, Zhong Q, Ma J, Xu J, He K. Design and application of a novel telemedicine system jointly driven by multinetwork integration and remote control: Practical experience from PLAGH, China. Healthc Technol Lett 2023; 10:113-121. [PMID: 38111799 PMCID: PMC10725722 DOI: 10.1049/htl2.12057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 11/15/2023] [Accepted: 11/22/2023] [Indexed: 12/20/2023] Open
Abstract
In China, several problems were common in the telemedicine systems, such as the poor network stability and difficult interconnection. A new telemedicine system jointly driven by multinetwork integration and remote control has been designed to address these problems. A multilink aggregation algorithm and an overlay network for telemedicine system (ONTMS) were developed to improve network stability, and a non-intervention remote control method was designed for Internet of Things (IoT) devices/systems. The authors monitored the network parameters, and distributed the questionnaire to participants, for evaluating the telemedicine system and services. Under a detection bandwidth of 8 Mbps, the aggregation parameters of Unicom 4G, Telecom 4G, and China Mobile 4G were optimal, with an uplink bandwidth, delay, and packet loss ratio (PLR) of 7.93 Mbps, 58.80 ms, and 0.06%, respectively. These parameters were significantly superior to those of China Mobile 4G, the best single network (p < 0.001). Through the ONTMS, the mean round-trip transporting delay from Beijing to Sanya was 76 ms, and the PLR was 0 at vast majority of time. A total of 1988 participants, including 1920 patients and 68 doctors, completed the questionnaires. More than 97% of participants felt that the audio and video transmission and remote control were fluent and convenient. 96% of patients rated the telemedicine services with scores of 4 or 5. This system has shown robust network property and excellent interaction ability, and satisfied the needs of patients and doctors.
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Affiliation(s)
- Ruiqing Wang
- Medical Big Data Research CenterChinese PLA General HospitalBeijingChina
| | - Jie Zhang
- Medical Engineering DepartmentChinese PLA General HospitalBeijingChina
| | - Shilin He
- Information DepartmentHainan Hospital of Chinese PLA General HospitalBeijingChina
| | - Huayuan Guo
- Medical Big Data Research CenterChinese PLA General HospitalBeijingChina
| | - Tao Li
- Medical Big Data Research CenterChinese PLA General HospitalBeijingChina
| | - Qin Zhong
- Medical Big Data Research CenterChinese PLA General HospitalBeijingChina
| | - Jun Ma
- Beijing HongYun RongTong Technology Co., LtdBeijingChina
| | - Jie Xu
- Beijing HongYun RongTong Technology Co., LtdBeijingChina
| | - Kunlun He
- Medical Big Data Research CenterChinese PLA General HospitalBeijingChina
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Broomhead SC, Mars M, Scott RE. A New eHealth Investment Appraisal Framework for Africa: Validation. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6426. [PMID: 37510658 PMCID: PMC10378755 DOI: 10.3390/ijerph20146426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 07/14/2023] [Accepted: 07/17/2023] [Indexed: 07/30/2023]
Abstract
(1) Background: Decisions to use eHealth are complex and involve addressing a large opportunity cost. Sound choices are essential. Weighing up investment options is challenging in resource-constrained settings where there are frequently insufficient economics data and expertise to conduct adequate appraisals. To address this, a new eHealth Investment Appraisal Framework (eHIAF) for Africa has been designed and developed. The aim of this paper was to validate the new framework to consider whether it is fit for purpose and to refine it as needed. (2) Methods: An online survey of purposively selected eHealth experts was used to conduct a desktop validation of the proposed eHIAF for Africa. The survey covered the framework development process, structure, content, completeness, and utility. Expert opinions were charted, and a reflective and iterative process used to assess the tool and extract recommendations for refinement. (3) Results: Eleven eHealth experts who completed the survey had experience in African countries and elsewhere. The majority agreed with the eHIAF for Africa development approach and output. They provided valuable suggestions for minor refinements and felt that with these amendments, the eHIAF for Africa would be 'fit for purpose'. (4) Conclusions: The eHIAF for Africa is considered appropriate for use by policy- and decision-makers working in resource-constrained settings who face the task of selecting optimal eHealth investments. It has the potential for applicability beyond Africa and the framework should now be tested in African countries.
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Affiliation(s)
- Sean C Broomhead
- Department of TeleHealth, School of Nursing & Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban 4041, South Africa
- Health Information Systems Program South Africa, Pretoria 0181, South Africa
- African Centre for eHealth Excellence, Cape Town 7130, South Africa
| | - Maurice Mars
- Department of TeleHealth, School of Nursing & Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban 4041, South Africa
| | - Richard E Scott
- Department of TeleHealth, School of Nursing & Public Health, College of Health Sciences, University of KwaZulu-Natal, Durban 4041, South Africa
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Alberta, AB T2N 1N4, Canada
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