Role of community health worker in a mobile health program for early detection of oral cancer
Background: The global incidence of oral cancer occurs in low-resource settings. Community-based oral screening is a strategic step toward downstaging oral cancer by early diagnosis. The mobile health (mHealth) program is a technology-based platform, steered with the aim to assess the use of mHealth...
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Published in | Indian journal of cancer Vol. 56; no. 2; pp. 107 - 113 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
India
Wolters Kluwer India Pvt. Ltd
01.04.2019
Medknow Publications and Media Pvt. Ltd Medknow Publications & Media Pvt. Ltd |
Subjects | |
Online Access | Get full text |
ISSN | 0019-509X 1998-4774 |
DOI | 10.4103/ijc.IJC_232_18 |
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Abstract | Background: The global incidence of oral cancer occurs in low-resource settings. Community-based oral screening is a strategic step toward downstaging oral cancer by early diagnosis. The mobile health (mHealth) program is a technology-based platform, steered with the aim to assess the use of mHealth by community health workers (CHWs) in the identification of oral mucosal lesions.
MATERIALS AND METHODS: mHealth is a mobile phone-based oral cancer-screening program in a workplace setting. The participants were screened by two CHWs, followed by an assessment by an oral medicine specialist. A mobile phone-based questionnaire that included the risk assessment was distributed among participants. On specialist recommendation an oral surgeon performed biopsy on participants. The diagnosis by onsite specialist that was confirmed by histopathology was considered as gold standard. All individuals received the standard treatment protocol. A remote oral medicine specialist reviewed the uploaded data in Open Medical Record System. Sensitivity, specificity, positive and negative predictive values were calculated. Inter-rater agreement was analyzed with Cohen's kappa coefficient (κ) test, and the diagnostic ability of CHWs, onsite specialist, and remote specialist was illustrated using receiver operating characteristic curve.
RESULTS: CHWs identified oral lesions in 405 (11.8%) individuals; the onsite specialist identified oral lesions in 394 (11.4%) individuals; and the remote specialist diagnosed oral lesions in 444 (13%). The inter-rater agreement between the CHW and the onsite specialist showed almost perfect agreement with the κ score of 0.92, and a substantial agreement between CHW and remote specialist showed a score of 0.62. The sensitivity, specificity, positive and negative predictive values of CHWs in the identification of oral lesion were 84.7, 97.6, 84.8, and 97.7%, respectively.
CONCLUSION: The trained CHWs can aid in identifying oral potentially malignant disorders and they can be utilized in oral cancer-screening program mHealth effectively. |
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AbstractList | The global incidence of oral cancer occurs in low-resource settings. Community-based oral screening is a strategic step toward downstaging oral cancer by early diagnosis. The mobile health (mHealth) program is a technology-based platform, steered with the aim to assess the use of mHealth by community health workers (CHWs) in the identification of oral mucosal lesions.
mHealth is a mobile phone-based oral cancer-screening program in a workplace setting. The participants were screened by two CHWs, followed by an assessment by an oral medicine specialist. A mobile phone-based questionnaire that included the risk assessment was distributed among participants. On specialist recommendation an oral surgeon performed biopsy on participants. The diagnosis by onsite specialist that was confirmed by histopathology was considered as gold standard. All individuals received the standard treatment protocol. A remote oral medicine specialist reviewed the uploaded data in Open Medical Record System. Sensitivity, specificity, positive and negative predictive values were calculated. Inter-rater agreement was analyzed with Cohen's kappa coefficient (κ) test, and the diagnostic ability of CHWs, onsite specialist, and remote specialist was illustrated using receiver operating characteristic curve.
CHWs identified oral lesions in 405 (11.8%) individuals; the onsite specialist identified oral lesions in 394 (11.4%) individuals; and the remote specialist diagnosed oral lesions in 444 (13%). The inter-rater agreement between the CHW and the onsite specialist showed almost perfect agreement with the κ score of 0.92, and a substantial agreement between CHW and remote specialist showed a score of 0.62. The sensitivity, specificity, positive and negative predictive values of CHWs in the identification of oral lesion were 84.7, 97.6, 84.8, and 97.7%, respectively.
The trained CHWs can aid in identifying oral potentially malignant disorders and they can be utilized in oral cancer-screening program mHealth effectively. Background: The global incidence of oral cancer occurs in low-resource settings. Community-based oral screening is a strategic step toward downstaging oral cancer by early diagnosis. The mobile health (mHealth) program is a technology-based platform, steered with the aim to assess the use of mHealth by community health workers (CHWs) in the identification of oral mucosal lesions. MATERIALS AND METHODS: mHealth is a mobile phone-based oral cancer-screening program in a workplace setting. The participants were screened by two CHWs, followed by an assessment by an oral medicine specialist. A mobile phone-based questionnaire that included the risk assessment was distributed among participants. On specialist recommendation an oral surgeon performed biopsy on participants. The diagnosis by onsite specialist that was confirmed by histopathology was considered as gold standard. All individuals received the standard treatment protocol. A remote oral medicine specialist reviewed the uploaded data in Open Medical Record System. Sensitivity, specificity, positive and negative predictive values were calculated. Inter-rater agreement was analyzed with Cohen's kappa coefficient (κ) test, and the diagnostic ability of CHWs, onsite specialist, and remote specialist was illustrated using receiver operating characteristic curve. RESULTS: CHWs identified oral lesions in 405 (11.8%) individuals; the onsite specialist identified oral lesions in 394 (11.4%) individuals; and the remote specialist diagnosed oral lesions in 444 (13%). The inter-rater agreement between the CHW and the onsite specialist showed almost perfect agreement with the κ score of 0.92, and a substantial agreement between CHW and remote specialist showed a score of 0.62. The sensitivity, specificity, positive and negative predictive values of CHWs in the identification of oral lesion were 84.7, 97.6, 84.8, and 97.7%, respectively. CONCLUSION: The trained CHWs can aid in identifying oral potentially malignant disorders and they can be utilized in oral cancer-screening program mHealth effectively. Background: The global incidence of oral cancer occurs in low-resource settings. Community-based oral screening is a strategic step toward downstaging oral cancer by early diagnosis. The mobile health (mHealth) program is a technology-based platform, steered with the aim to assess the use of mHealth by community health workers (CHWs) in the identification of oral mucosal lesions. MATERIALS AND METHODS: mHealth is a mobile phone-based oral cancer-screening program in a workplace setting. The participants were screened by two CHWs, followed by an assessment by an oral medicine specialist. A mobile phone-based questionnaire that included the risk assessment was distributed among participants. On specialist recommendation an oral surgeon performed biopsy on participants. The diagnosis by onsite specialist that was confirmed by histopathology was considered as gold standard. All individuals received the standard treatment protocol. A remote oral medicine specialist reviewed the uploaded data in Open Medical Record System. Sensitivity, specificity, positive and negative predictive values were calculated. Inter-rater agreement was analyzed with Cohen's kappa coefficient (κ) test, and the diagnostic ability of CHWs, onsite specialist, and remote specialist was illustrated using receiver operating characteristic curve. RESULTS: CHWs identified oral lesions in 405 (11.8%) individuals; the onsite specialist identified oral lesions in 394 (11.4%) individuals; and the remote specialist diagnosed oral lesions in 444 (13%). The inter-rater agreement between the CHW and the onsite specialist showed almost perfect agreement with the κ score of 0.92, and a substantial agreement between CHW and remote specialist showed a score of 0.62. The sensitivity, specificity, positive and negative predictive values of CHWs in the identification of oral lesion were 84.7, 97.6, 84.8, and 97.7%, respectively. CONCLUSION: The trained CHWs can aid in identifying oral potentially malignant disorders and they can be utilized in oral cancer-screening program mHealth effectively. |
Audience | Academic |
Author | Gurushanth, Keerthi Patrick, Sanjana Gurudath, Shubha Tiwari, Vidya Imran, Mohammed Sunny, Sumsum Rao, Pratima Raghavan, Shubhasini Hegde, Usha Birur, N Kuriakose, Moni Jain, Vipin |
Author_xml | – sequence: 1 givenname: N surname: Birur fullname: Birur, N organization: KLE Society's Institute of Dental Sciences; Oral Cancer Screening Program, Biocon Foundation, Bengaluru – sequence: 2 givenname: Keerthi surname: Gurushanth fullname: Gurushanth, Keerthi organization: KLE Society's Institute of Dental Sciences, Bengaluru – sequence: 3 givenname: Sanjana surname: Patrick fullname: Patrick, Sanjana organization: Oral Cancer Screening Program, Biocon Foundation, Bengaluru – sequence: 4 givenname: Sumsum surname: Sunny fullname: Sunny, Sumsum organization: Head and Neck Oncology, Mazumdar Shaw Cancer Center, Bengaluru – sequence: 5 givenname: Shubhasini surname: Raghavan fullname: Raghavan, Shubhasini organization: KLE Society's Institute of Dental Sciences, Bengaluru – sequence: 6 givenname: Shubha surname: Gurudath fullname: Gurudath, Shubha organization: KLE Society's Institute of Dental Sciences, Bengaluru – sequence: 7 givenname: Usha surname: Hegde fullname: Hegde, Usha organization: JSS Dental College, Mysore, Karnataka – sequence: 8 givenname: Vidya surname: Tiwari fullname: Tiwari, Vidya organization: Oral Medicine Specialist, KLE Society's Institute of Dental Sciences, Bengaluru – sequence: 9 givenname: Vipin surname: Jain fullname: Jain, Vipin organization: Department of Public Health Dentistry, KLE Society's Institute of Dental Sciences, Bengaluru – sequence: 10 givenname: Mohammed surname: Imran fullname: Imran, Mohammed organization: Oral Cancer Screening Program, Biocon Foundation, Bengaluru – sequence: 11 givenname: Pratima surname: Rao fullname: Rao, Pratima organization: Oral Cancer Screening Program, Biocon Foundation, Bengaluru – sequence: 12 givenname: Moni surname: Kuriakose fullname: Kuriakose, Moni organization: Cochin Cancer Research Center, Kerala |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31062727$$D View this record in MEDLINE/PubMed |
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Keywords | telemedicine oral potentially malignant disorders oral medicine specialist Early detection oral cancer screening |
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Snippet | Background: The global incidence of oral cancer occurs in low-resource settings. Community-based oral screening is a strategic step toward downstaging oral... The global incidence of oral cancer occurs in low-resource settings. Community-based oral screening is a strategic step toward downstaging oral cancer by early... |
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Title | Role of community health worker in a mobile health program for early detection of oral cancer |
URI | http://www.indianjcancer.com/article.asp?issn=0019-509X;year=2019;volume=56;issue=2;spage=107;epage=113;aulast=Birur;type=0 https://www.ncbi.nlm.nih.gov/pubmed/31062727 https://www.proquest.com/docview/2221135844 |
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