Patient and Healthcare System Delays in Tuberculosis Diagnosis and Tuberculosis Treatment

Patient and Healthcare System Delays in Tuberculosis Diagnosis and Tuberculosis Treatment

Registration ID: IJNRD_226702

Published ID: IJNRD2408258

DOI: Click Here to Get

Magoba Ronald Arnold , Dominic Mogere , Dennis Magu

Background: Long diagnosis delay contributes significantly to the failure to eradicate tuberculosis. The objective of this study was to evaluate the total, patient and system delays in diagnosis of pulmonary bacilliferous in the six tuberculosis Diagnostic and Treatment Centers at Kenyatta National Hospital-Nairobi County. Methods: A descriptive cross-sectional study was conducted among 384 microscopy-positive pulmonary tuberculosis patients in 2022 to address this objective. It concerned the socio-demographic, clinical, microbiological characteristics, and referral location/pathway characteristics of the patients. We then calculated the different delays. The “patient” (time from first symptoms to first consultation), “system” (time from first consultation to first diagnosis) and total (time from first symptoms to diagnosis) median diagnostic delay were estimated. Results: The response rate for quantitative data was 99.2% (n =127) from a sample size of 128 of the TB patients that presented to the hospital for diagnosis and treatment. For the focus group discussion, the investigator interviewed two (2) groups of seven (14) for both patients and health care workers at the TB clinic at KNH. Bivariate analyses showed significant associations on gender of the respondents that indicated that majority of the respondents were females 51.2% (n= 65) compared to the male counterpart with 48.8% (n = 62). This shows that women are more sensitive to their health issues compared with the male counterparts. This indicate that those with age (40 to 49) were majority 32.3% (n = 41) followed closely by age (30 to 39) 21.3% (n = 27). This is a middle age group thus indicating that they are high-risk group. If intervention is done, then they should be t2argeted to benefit. Conclusion: Well laid out TB management (diagnosis and treatment) at Kenyatta National Hospital is a leeway to efficient healthcare services delivery to the people. Kenyatta National hospital has various departments dealing with various ailments and complications. An effective TB diagnosis and treatment team is crucial in preparing for TB management at the facility. Due to the nature of the illness, TB patients and their households can face severe direct and indirect financial and economic costs. These pose barriers that can greatly affect their ability to access diagnosis and treatment, and to complete treatment successfully. Costs included in the TB-specific indicator include not only direct medical payments for diagnosis and treatment, but also direct nonmedical payments (e.g., transportation and lodging) and indirect costs (e.g., lost income). In contrast to SDG Indicator 3.8.2, the TB-specific indicator is restricted to a particular population: people diagnosed with TB who are users of health services that are part of NTP networks (Denholm JT .2021 et al.).

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"Patient and Healthcare System Delays in Tuberculosis Diagnosis and Tuberculosis Treatment", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 8, page no.c532-c539, August-2024, Available :https://ijnrd.org/papers/IJNRD2408258.pdf

Volume 9 Issue 8, August-2024

Pages : c532-c539

Paper Reg. ID: IJNRD_226702

Published Paper Id: IJNRD2408258

Downloads: 000121112

Research Area: Medical Science

Country: NAIROBI, NAIROBI, Kenya

Published Paper PDF: https://ijnrd.org/papers/IJNRD2408258.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2408258

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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