Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis.
<h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compou...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Luisa Rubiano [verfasserIn] Neal D E Alexander [verfasserIn] Ruth Mabel Castillo [verfasserIn] Álvaro José Martínez [verfasserIn] Jonny Alejandro García Luna [verfasserIn] Juan David Arango [verfasserIn] Leonardo Vargas [verfasserIn] Patricia Madriñán [verfasserIn] Lina-Rocío Hurtado [verfasserIn] Yenifer Orobio [verfasserIn] Carlos A Rojas [verfasserIn] Helena Del Corral [verfasserIn] Andrés Navarro [verfasserIn] Nancy Gore Saravia [verfasserIn] Eliah Aronoff-Spencer [verfasserIn] |
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| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Übergeordnetes Werk: |
In: PLoS Neglected Tropical Diseases - Public Library of Science (PLoS), 2008, 15(2021), 2, p e0008989 |
|---|---|
| Übergeordnetes Werk: |
volume:15 ; year:2021 ; number:2, p e0008989 |
| Links: |
Link aufrufen |
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| DOI / URN: |
10.1371/journal.pntd.0008989 |
|---|
| Katalog-ID: |
DOAJ006400531 |
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| 520 | |a <h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce.<h4<Methods</h4<We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician.<h4<Results</h4<The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was <95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel.<h4<Conclusions</h4<Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. | ||
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| 653 | 0 | |a Public aspects of medicine | |
| 700 | 0 | |a Neal D E Alexander |e verfasserin |4 aut | |
| 700 | 0 | |a Ruth Mabel Castillo |e verfasserin |4 aut | |
| 700 | 0 | |a Álvaro José Martínez |e verfasserin |4 aut | |
| 700 | 0 | |a Jonny Alejandro García Luna |e verfasserin |4 aut | |
| 700 | 0 | |a Juan David Arango |e verfasserin |4 aut | |
| 700 | 0 | |a Leonardo Vargas |e verfasserin |4 aut | |
| 700 | 0 | |a Patricia Madriñán |e verfasserin |4 aut | |
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| 700 | 0 | |a Yenifer Orobio |e verfasserin |4 aut | |
| 700 | 0 | |a Carlos A Rojas |e verfasserin |4 aut | |
| 700 | 0 | |a Helena Del Corral |e verfasserin |4 aut | |
| 700 | 0 | |a Andrés Navarro |e verfasserin |4 aut | |
| 700 | 0 | |a Nancy Gore Saravia |e verfasserin |4 aut | |
| 700 | 0 | |a Eliah Aronoff-Spencer |e verfasserin |4 aut | |
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10.1371/journal.pntd.0008989 doi (DE-627)DOAJ006400531 (DE-599)DOAJ021876eef7964e81b083402bf2e58405 DE-627 ger DE-627 rakwb eng RC955-962 RA1-1270 Luisa Rubiano verfasserin aut Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis. 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce.<h4<Methods</h4<We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician.<h4<Results</h4<The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was <95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel.<h4<Conclusions</h4<Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. Arctic medicine. Tropical medicine Public aspects of medicine Neal D E Alexander verfasserin aut Ruth Mabel Castillo verfasserin aut Álvaro José Martínez verfasserin aut Jonny Alejandro García Luna verfasserin aut Juan David Arango verfasserin aut Leonardo Vargas verfasserin aut Patricia Madriñán verfasserin aut Lina-Rocío Hurtado verfasserin aut Yenifer Orobio verfasserin aut Carlos A Rojas verfasserin aut Helena Del Corral verfasserin aut Andrés Navarro verfasserin aut Nancy Gore Saravia verfasserin aut Eliah Aronoff-Spencer verfasserin aut In PLoS Neglected Tropical Diseases Public Library of Science (PLoS), 2008 15(2021), 2, p e0008989 (DE-627)568915356 (DE-600)2429704-5 19352735 nnns volume:15 year:2021 number:2, p e0008989 https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/article/021876eef7964e81b083402bf2e58405 kostenfrei https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/toc/1935-2727 Journal toc kostenfrei https://doaj.org/toc/1935-2735 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 2, p e0008989 |
| spelling |
10.1371/journal.pntd.0008989 doi (DE-627)DOAJ006400531 (DE-599)DOAJ021876eef7964e81b083402bf2e58405 DE-627 ger DE-627 rakwb eng RC955-962 RA1-1270 Luisa Rubiano verfasserin aut Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis. 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce.<h4<Methods</h4<We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician.<h4<Results</h4<The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was <95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel.<h4<Conclusions</h4<Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. Arctic medicine. Tropical medicine Public aspects of medicine Neal D E Alexander verfasserin aut Ruth Mabel Castillo verfasserin aut Álvaro José Martínez verfasserin aut Jonny Alejandro García Luna verfasserin aut Juan David Arango verfasserin aut Leonardo Vargas verfasserin aut Patricia Madriñán verfasserin aut Lina-Rocío Hurtado verfasserin aut Yenifer Orobio verfasserin aut Carlos A Rojas verfasserin aut Helena Del Corral verfasserin aut Andrés Navarro verfasserin aut Nancy Gore Saravia verfasserin aut Eliah Aronoff-Spencer verfasserin aut In PLoS Neglected Tropical Diseases Public Library of Science (PLoS), 2008 15(2021), 2, p e0008989 (DE-627)568915356 (DE-600)2429704-5 19352735 nnns volume:15 year:2021 number:2, p e0008989 https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/article/021876eef7964e81b083402bf2e58405 kostenfrei https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/toc/1935-2727 Journal toc kostenfrei https://doaj.org/toc/1935-2735 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 2, p e0008989 |
| allfields_unstemmed |
10.1371/journal.pntd.0008989 doi (DE-627)DOAJ006400531 (DE-599)DOAJ021876eef7964e81b083402bf2e58405 DE-627 ger DE-627 rakwb eng RC955-962 RA1-1270 Luisa Rubiano verfasserin aut Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis. 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce.<h4<Methods</h4<We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician.<h4<Results</h4<The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was <95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel.<h4<Conclusions</h4<Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. Arctic medicine. Tropical medicine Public aspects of medicine Neal D E Alexander verfasserin aut Ruth Mabel Castillo verfasserin aut Álvaro José Martínez verfasserin aut Jonny Alejandro García Luna verfasserin aut Juan David Arango verfasserin aut Leonardo Vargas verfasserin aut Patricia Madriñán verfasserin aut Lina-Rocío Hurtado verfasserin aut Yenifer Orobio verfasserin aut Carlos A Rojas verfasserin aut Helena Del Corral verfasserin aut Andrés Navarro verfasserin aut Nancy Gore Saravia verfasserin aut Eliah Aronoff-Spencer verfasserin aut In PLoS Neglected Tropical Diseases Public Library of Science (PLoS), 2008 15(2021), 2, p e0008989 (DE-627)568915356 (DE-600)2429704-5 19352735 nnns volume:15 year:2021 number:2, p e0008989 https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/article/021876eef7964e81b083402bf2e58405 kostenfrei https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/toc/1935-2727 Journal toc kostenfrei https://doaj.org/toc/1935-2735 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 2, p e0008989 |
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10.1371/journal.pntd.0008989 doi (DE-627)DOAJ006400531 (DE-599)DOAJ021876eef7964e81b083402bf2e58405 DE-627 ger DE-627 rakwb eng RC955-962 RA1-1270 Luisa Rubiano verfasserin aut Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis. 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce.<h4<Methods</h4<We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician.<h4<Results</h4<The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was <95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel.<h4<Conclusions</h4<Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. Arctic medicine. Tropical medicine Public aspects of medicine Neal D E Alexander verfasserin aut Ruth Mabel Castillo verfasserin aut Álvaro José Martínez verfasserin aut Jonny Alejandro García Luna verfasserin aut Juan David Arango verfasserin aut Leonardo Vargas verfasserin aut Patricia Madriñán verfasserin aut Lina-Rocío Hurtado verfasserin aut Yenifer Orobio verfasserin aut Carlos A Rojas verfasserin aut Helena Del Corral verfasserin aut Andrés Navarro verfasserin aut Nancy Gore Saravia verfasserin aut Eliah Aronoff-Spencer verfasserin aut In PLoS Neglected Tropical Diseases Public Library of Science (PLoS), 2008 15(2021), 2, p e0008989 (DE-627)568915356 (DE-600)2429704-5 19352735 nnns volume:15 year:2021 number:2, p e0008989 https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/article/021876eef7964e81b083402bf2e58405 kostenfrei https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/toc/1935-2727 Journal toc kostenfrei https://doaj.org/toc/1935-2735 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 2, p e0008989 |
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10.1371/journal.pntd.0008989 doi (DE-627)DOAJ006400531 (DE-599)DOAJ021876eef7964e81b083402bf2e58405 DE-627 ger DE-627 rakwb eng RC955-962 RA1-1270 Luisa Rubiano verfasserin aut Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis. 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier <h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce.<h4<Methods</h4<We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician.<h4<Results</h4<The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was <95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel.<h4<Conclusions</h4<Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. Arctic medicine. Tropical medicine Public aspects of medicine Neal D E Alexander verfasserin aut Ruth Mabel Castillo verfasserin aut Álvaro José Martínez verfasserin aut Jonny Alejandro García Luna verfasserin aut Juan David Arango verfasserin aut Leonardo Vargas verfasserin aut Patricia Madriñán verfasserin aut Lina-Rocío Hurtado verfasserin aut Yenifer Orobio verfasserin aut Carlos A Rojas verfasserin aut Helena Del Corral verfasserin aut Andrés Navarro verfasserin aut Nancy Gore Saravia verfasserin aut Eliah Aronoff-Spencer verfasserin aut In PLoS Neglected Tropical Diseases Public Library of Science (PLoS), 2008 15(2021), 2, p e0008989 (DE-627)568915356 (DE-600)2429704-5 19352735 nnns volume:15 year:2021 number:2, p e0008989 https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/article/021876eef7964e81b083402bf2e58405 kostenfrei https://doi.org/10.1371/journal.pntd.0008989 kostenfrei https://doaj.org/toc/1935-2727 Journal toc kostenfrei https://doaj.org/toc/1935-2735 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 15 2021 2, p e0008989 |
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adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis |
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Adaptation and performance of a mobile application for early detection of cutaneous leishmaniasis. |
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<h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce.<h4<Methods</h4<We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician.<h4<Results</h4<The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was <95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel.<h4<Conclusions</h4<Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. |
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<h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce.<h4<Methods</h4<We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician.<h4<Results</h4<The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was <95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel.<h4<Conclusions</h4<Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. |
| abstract_unstemmed |
<h4<Background</h4<Detection and management of neglected tropical diseases such as cutaneous leishmaniasis present unmet challenges stemming from their prevalence in remote, rural, resource constrained areas having limited access to health services. These challenges are frequently compounded by armed conflict or illicit extractive industries. The use of mobile health technologies has shown promise in such settings, yet data on outcomes in the field remain scarce.<h4<Methods</h4<We adapted a validated prediction rule for the presumptive diagnosis of CL to create a mobile application for use by community health volunteers. We used human-centered design practices and agile development for app iteration. We tested the application in three rural areas where cutaneous leishmaniasis is endemic and an urban setting where patients seek medical attention in the municipality of Tumaco, Colombia. The application was assessed for usability, sensitivity and inter-rater reliability (kappa) when used by community health volunteers (CHV), health workers and a general practitioner, study physician.<h4<Results</h4<The application was readily used and understood. Among 122 screened cases with cutaneous ulcers, sensitivity to detect parasitologically proven CL was <95%. The proportion of participants with parasitologically confirmed CL was high (88%), precluding evaluation of specificity, and driving a high level of crude agreement between the app and parasitological diagnosis. The chance-adjusted agreement (kappa) varied across the components of the risk score. Time to diagnosis was reduced significantly, from 8 to 4 weeks on average when CHV conducted active case detection using the application, compared to passive case detection by health facility-based personnel.<h4<Conclusions</h4<Translating a validated prediction rule to a mHealth technology has shown the potential to improve the capacity of community health workers and healthcare personnel to provide opportune care, and access to health services for underserved populations. These findings support the use of mHealth tools for NTD research and healthcare. |
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