scholarly journals Factors associated with private health facilities reporting malaria in the National Health Management Information System in Zambia: a cross sectional study

2020 ◽  
Vol 37 ◽  
Author(s):  
Angela Gama ◽  
Ignatius Banda ◽  
Fred Kapaya ◽  
Mercy Mwanza Ingwe ◽  
Japhet Chiwaula ◽  
...  
Keyword(s):  
Information System ◽  
National Health ◽  
Management Information System ◽  
Health Management ◽  
Cross Sectional Study ◽  
Health Management Information System ◽  
Sectional Study ◽  
Management Information ◽  
Cross Sectional ◽  
Factors Associated

scholarly journals Status of Legislation and Factors affecting Disease Surveillance in Nigeria: A qualitative inquiry

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Olusesan A. Makinde ◽  
Clifford O. Odimegwu
Keyword(s):  
Infectious Disease ◽  
Information System ◽  
National Health ◽  
Management Information System ◽  
Disease Surveillance ◽  
Health Management ◽  
Health Management Information System ◽  
Management Information ◽  
Factors Affecting ◽  
Key Informants

ObjectiveAssess the legal framework establishing disease surveillance in Nigeria and identify major factors affecting the performance of the surveillance system.IntroductionThe outbreak of infectious diseases with a propensity to spread across international boundaries is on an upward rise. Such outbreaks can be devastating with significant associated morbidity and mortality. The recent Ebola Virus Disease outbreak in West Africa which spread to Nigeria is an example.(1) Nigeria like several other African countries implements the Integrated Disease Surveillance and Response (IDSR) system as its method for achieving the International Health Regulations (IHR). Yet, compliance to the IDSR is questioned. This study seeks to investigate the legal instruments in place and the factors affecting performance of the disease surveillance in the country.MethodsThe study reports the first objective of a larger study to investigate compliance to disease surveillance by private health providers.(2) An investigative search of the literature for legal instruments on disease surveillance in Nigeria was carried out. In addition, key informants were identified and interviewed at the national level and in selected states. The six states in the South-West were identified for an in-depth study. The IHR focal person and the National Health Management Information System officer were interviewed at the national level. The state epidemiologists and the state health management information system (HMIS) officers across the six states were interviewed. Each state has only one state epidemiologist and one HMIS officer as such it was a total sample. In all, 14 key informants were interviewed.ResultsSix legal instruments were identified as seen in table 1. The most recent comprehensive legal instrument on infectious disease control in Nigeria is a 2005 policy on IDSR. This is further supported by the National Health Act of 2014. However, the National Health Act is not detailed for infectious disease control. The substantive law which governs infectious diseases in Nigeria, the Quarantine Act was enacted almost a century ago during the colonial era in 1926. None of the states studied has an active law on infectious disease surveillance as noted by key informants. While all states refer to the IDSR policy, none has formally ratified the document. There are two independent overlapping data collection systems on infectious diseases: the IDSR and the National Health Management Information System (NHMIS). Data on malaria, HIV and tuberculosis are among data collected across the two systems. This was identified by key informants as a problem since the data collection forms differed across systems and almost always result in differing statistics. In addition, this duplication causes overburdening of frontline workers expected to fill the parallel data collection tools and results in inefficiency of the system. Funding of the surveillance system was identified to be inadequate with significant reliance on international partners.ConclusionsA review of the national law on disease surveillance to address emerging global health security challenges is necessary. State legislators need to enact or ratify national laws on infectious disease monitoring and control in their states. The duplication across the NHMIS and the IDSR surveillance system requires harmonization to improve efficiency. Government needs to invest more resources in disease surveillance.References. Makinde OA. As Ebola winds down, Lassa Fever reemerges yet again in West Africa. J Infect Dev Ctries [Internet]. 2016 Feb 28;10(02):199–200. Available from: http://www.jidc.org/index.php/journal/article/view/81482. Makinde OA, Odimegwu CO. Disease Surveillance by Private Health Providers in Nigeria: A Research Proposal. Online J Public Health Inform [Internet]. 2016 Mar 24;8(1). Available from: http://ojphi.org/ojs/index.php/ojphi/article/view/6554

scholarly journals Applying Nightingale charts to evaluate the heterogeneity of biomedical waste in a Hospital

2014 ◽  
Vol 22 (6) ◽  
pp. 942-949 ◽  
Author(s):  
Janini Cristina Paiz ◽  
Marcio Bigolin ◽  
Vania Elisabete Schneider ◽  
Nilva Lúcia Rech Stedile
Keyword(s):  
Information System ◽  
Management Information System ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Management Information ◽  
Chemical Waste ◽  
Cross Sectional ◽  
Biomedical Waste ◽  
Waste Segregation ◽  
Chemical Wastes

OBJECTIVES: to evaluate the heterogeneity of biomedical waste (BW) using Nightingale charts.METHOD: cross-sectional study consisting of data collection on wastes (direct observation of receptacles, physical characterisation, and gravimetric composition), development of a Management Information System, and creation of statistical charts.RESULTS: the wastes with the greatest degree of heterogeneity are, in order, recyclable, infectious, and organic wastes; chemical waste had the most efficient segregation; Nightingale charts are useful for quick visualisation and systematisation of information on heterogeneity.CONCLUSION: the development of a management information system and the use of Nightingale charts allows for the identification and correction of errors in waste segregation, which increase health risks and contamination by infectious and chemical wastes and reduce the sale and profit from recyclables.

scholarly journals Data quality assessment and associated factors in the health management information system among health centers of Southern Ethiopia

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0255949
Author(s):  
Mastewal Solomon ◽  
Mesfin Addise ◽  
Berhan Tassew ◽  
Bahailu Balcha ◽  
Amene Abebe
Keyword(s):  
Information System ◽  
Data Quality ◽  
Management Information System ◽  
Health Professionals ◽  
Health Management ◽  
Health Centers ◽  
Southern Ethiopia ◽  
Health Management Information System ◽  
Management Information ◽  
Cross Sectional

Background A well designed Health management information system is necessary for improving health service effectiveness and efficiency. It also helps to produce quality information and conduct evidence based monitoring, adjusting policy implementation and resource use. However, evidences show that data quality is poor and is not utilized for program decisions in Ethiopia especially at lower levels of the health care and it remains as a major challenge. Method Facility based cross sectional study design was employed. A total of 18 health centers and 302 health professionals were selected by simple random sampling using lottery method from each selected health center. Data was collected by health professionals who were experienced and had training on HMIS tasks after the tools were pretested. Data quality was assessed using accuracy, completeness and timeliness dimensions. Seven indicators from national priority area were selected to assess data accuracy and monthly reports were used to assess completeness and timeliness. Statistical software SPSS version 20 for descriptive statistics and binary logistic regression was used for quantitative data analysis to identify candidate variable. Result A total of 291 respondents were participated in the study with response rate of 96%. Overall average data quality was 82.5%. Accuracy, completeness and timeliness dimensions were 76%, 83.3 and 88.4 respectively which was lower than the national target. About 52.2% respondents were trained on HMIS, 62.5% had supervisory visits as per standard and only 55.3% got written feedback. Only 11% of facilities assigned health information technicians. Level of confidence [AOR = 1.75, 95% CI (0.99, 3.11)], filling registration or tally completely [AOR = 3.4, 95% CI (1.3, 8.7)], data quality check, supervision AOR = 1.7 95% CI (0.92, 2.63) and training [AOR = 1.89 95% CI (1.03, 3.45)] were significantly associated with data quality. Conclusion This study found that the overall data quality was lower than the national target. Over reporting of all indicators were observed in all facilities. It needs major improvement on supervision quality, training status to increase confidence of individuals to do HMIS activities.

scholarly journals Gaps in the coverage of vitamin K1 prophylaxis among newborns in India: insights from secondary analysis of data from the Health Management Information System

2021 ◽  
pp. 1-24
Author(s):  
Kaustubh Bora
Keyword(s):  
Information System ◽  
Vitamin K ◽  
Management Information System ◽  
Tamil Nadu ◽  
Health Management ◽  
Secondary Analysis ◽  
Central Zone ◽  
Health Management Information System ◽  
Management Information ◽  
Cross Sectional

Abstract Objective: Despite operational guidelines, anecdotal evidence suggests that newborn vitamin K1 prophylaxis is not practiced routinely in India. This study determined the coverage of vitamin K1 prophylaxis among newborns in the country. Design: Nationwide cross-sectional data on live births and newborns receiving vitamin K1 during the 2019–20 reporting period were abstracted from the Health Management Information System (HMIS). The coverage estimates of newborn vitamin K1 prophylaxis were derived nationally and also for individual states and union territories (UTs). Additionally, coverage heterogeneities were investigated using classifiers, viz. geography, socio-demographic index (SDI), special developmental categories and institutional birth rate (IBR). Setting: India Participants: 20,208,804 newborns documented with HMIS. Results: Vitamin K1 was administered to overall 62.36% newborns (95% CI: 62.34 to 62.38%). The Central zone (49.0%), low SDI states (54.39%), Empowered Action Group states (53.32%), and states with low IBRs (44.69%) had the lowest coverage amongst their respective groupings. Across the individual states and UTs, the coverage ranged widely from 22.18% (in Tripura) to 99.38% (in Puducherry), exhibiting considerable variability (coefficient of variation: 33.74%) and inequality (Gini coefficient: 0.17). While the coverage in 8 states/UTs (i.e., Arunachal Pradesh, Manipur, Nagaland, Tripura, Uttar Pradesh, Uttarakhand, Telangana, and Andaman & Nicobar Islands) was below 50%; only five states/UTs (i.e., Chandigarh, Gujarat, Goa, Puducherry, and Tamil Nadu) achieved above 90% coverage. Conclusion: Vitamin K1 prophylaxis was not practiced in more than one-third newborns in India. It calls for identifying the barriers, addressing the gaps and implementing newborn vitamin K1 prophylaxis more effectively throughout the country.

scholarly journals Data Quality of the Routine Health Management Information System at the Primary Healthcare Facility and District Levels in Tanzania

2020 ◽  
Author(s):  
SUSAN F. RUMISHA ◽  
EMANUEL P. LYIMO ◽  
IRENE R. MREMI ◽  
PATRICK K. TUNGU ◽  
VICTOR S. MWINGIRA ◽  
...  
Keyword(s):  
Information System ◽  
Data Quality ◽  
Management Information System ◽  
Health Management ◽  
Health Centre ◽  
Healthcare Facility ◽  
Health Management Information System ◽  
Management Information ◽  
Service Areas

Abstract Background: Effective planning for disease prevention and control requiresaccurate, adequately-analysed, interpreted and communicated data. This study assessed the quality of routine Health Management Information System (HMIS) data at healthcare facility (HF) and district levels in Tanzania. Methods: HMIS tools used at primary health care facilities (dispensary, health centre, hospital) and district office were reviewed to assess their availability, completeness, and accuracy of collected data. The assessment involved seven health service areas namely, Outpatient department, Inpatient department, Antenatal care, Family Planning, Post-natal care, Labour and Delivery and Provider-initiated Testing and Counselling.Results: A total of 115 HFs in 11 districts were assessed. Registers (availability rate=91.1%; interquartile range (IQR):66.7%-100%) and reportforms (86.9%;IQR:62.2%-100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%;IQR:35.6%-100%). Tools availability at dispensary was 91.1%, health-centre 82.2% and hospital 77.8%, and was poor in urban districts. The availability rate atthe district level was 65% (IQR:48%-75%). Reports were highly over-represented in comparison to registers’ records, with large differences observed at HF phase of the data journey and more profound in hospitals.Tool availability and data quality varied by service-areas, indicators, facility level, and districts, however, with a remarkable improvement over the years.Conclusion: There are high variations and improvements in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the HFs. These results highlight the need to design tailored and inter-service strategies for improving data quality.

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