Research Article
Leveraging Pareto Analysis of Outpatient Morbidity for Strategic Drug Procurement and Health Promotion in Resource-Constrained Setting in Ghana
Richmond Bediako Nsiah*,
James Ankamah,
Theresah Krah,
Akua Kumi Yeboah,
Dominic Nyarko,
Jonathan Mawutor Gmanyami,
Florence Owusuaa Peprah,
Frank Prempeh,
Charlotte Yeboah Domfeh,
Isaac Ayirebi,
Mark Bonnir,
Isaac Morrison,
Margaret Morrison,
Patrick Larbi-Debrah,
Geoffrey Akungoe Ayambire,
Priscilla Sarkodie,
Kenneth Baga Sabogu,
Obed Atsu-Ofori,
Kwame Kusi Agyemang,
Daniel Ike Adinkrah
Issue:
Volume 12, Issue 6, December 2024
Pages:
154-164
Received:
21 September 2024
Accepted:
11 October 2024
Published:
13 November 2024
DOI:
10.11648/j.ajhr.20241206.11
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Abstract: Background: Effective health management in resource-limited settings requires strategic resource allocation and intervention planning. Pareto analysis, based on the 80/20 rule, aids in identifying key health conditions impacting outpatient morbidity, guiding intervention prioritization and resource optimization. This study applied Pareto analysis on outpatient morbidity data from Goaso Government Hospital, Ghana, to identify common health conditions and improve drug procurement and health promotion strategies. The methodology also serves as a guide for applying Pareto chart analysis to enhance decision-making in healthcare delivery. Methods: A cross-sectional study was conducted analyzing outpatient department (OPD) data from January to December 2023. Data were extracted from the Ghana Health Service Monthly Outpatient Morbidity Reports via the District Health Information Management System 2 (DHIMS 2). Data analysis was conducted using SPSS version 20 to estimate the mean and standard deviation. Microsoft Excel 2016 was employed for Pareto analysis and the creation of column charts. Results: The analysis revealed that female patients had a higher average number of outpatient cases (M = 259, SD = 430.7) compared to male patients (M = 156, SD = 282.5). Key conditions contributing to 80% of the cases included Upper Respiratory Tract Infections (URTIs), Pneumonia, Malaria, Acute Urinary Tract Infections (UTIs), Diarrhoeal diseases, Typhoid Fever, Anaemia, Rheumatism/Arthritis, Skin Diseases, and Septicaemia. Notably, young adults (ages 20-34) and children (ages 1-4) were most affected. Conclusions: A strategic approach to drug procurement is essential due to high disease prevalence. Key actions include maintaining a three-month supply of ACTs for malaria, stocking essential antibiotics, and ensuring a two-month supply of ORS. Utilizing data-driven forecasting and establishing strong supplier partnerships are crucial for optimizing drug availability. Simultaneously, targeted health promotion efforts should focus on respiratory health, malaria prevention, UTIs, WASH practices, anaemia, rheumatism, and skin diseases through public education. Additionally, qualitative research, such as patient interviews and provider surveys, is recommended to understand high morbidity rates and evaluate existing interventions.
Abstract: Background: Effective health management in resource-limited settings requires strategic resource allocation and intervention planning. Pareto analysis, based on the 80/20 rule, aids in identifying key health conditions impacting outpatient morbidity, guiding intervention prioritization and resource optimization. This study applied Pareto analysis o...
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Research Article
Yearly Assessment of Weather and Air Quality Impact on Respiratory Disease Hospitalizations: Faial Island (Azores) Study
Issue:
Volume 12, Issue 6, December 2024
Pages:
165-178
Received:
28 September 2024
Accepted:
17 October 2024
Published:
18 November 2024
DOI:
10.11648/j.ajhr.20241206.12
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Abstract: Building upon our previous research conducted at weekly and monthly intervals, this study investigates the yearly dynamics of weather conditions and air quality on respiratory diseases, specifically tailored to Faial Island in the Azores. Expanding our analysis to a yearly basis allows for a more comprehensive understanding of long-term trends and seasonal variations in hospital admissions. Drawing upon extensive daily data spanning from 2008 to 2019, sourced from the Statistics Service of Hospital da Horta, the Meteorological Observatory Príncipe Alberto de Mónaco, and the Air Quality Monitoring Network of the Azores, we examined the differentiated relationships between yearly meteorological variables, such as temperature, dew point, and wind direction, and respiratory health outcomes. Additionally, we explored the persistent influence of air quality indicators, including suspended particulate matter with an aerodynamic diameter of 10 micrometers (µm) or less (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3), across different seasons and years. By incorporating yearly data into our analysis, this study aims to provide a comprehensive and nuanced understanding of the interplay between environmental factors and respiratory disease hospitalizations, thereby informing targeted interventions and public health strategies in insular regions. The principal component analysis (PCA) applied to the yearly data reveals interesting correlation patterns between meteorological variables and hospitalizations for respiratory diseases such as asthma, pneumonia, and rhinitis. Hospital admissions were found to increase during periods of lower temperatures and smaller temperature amplitudes, suggesting that prolonged cold conditions may exacerbate symptoms of these diseases. Additionally, atmospheric pollutant concentrations, such as suspended particles PM10, SO2, NO2, and O3, significantly varied across seasons, with a notable influence on the exacerbation of respiratory diseases. In insular regions like the Azores, these findings highlight the importance of targeted public health strategies to mitigate the impact of environmental factors on respiratory health.
Abstract: Building upon our previous research conducted at weekly and monthly intervals, this study investigates the yearly dynamics of weather conditions and air quality on respiratory diseases, specifically tailored to Faial Island in the Azores. Expanding our analysis to a yearly basis allows for a more comprehensive understanding of long-term trends and ...
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