Analysis of Compliance with Universal Precautions among Staff and Student Nurses in Olabisi Onabanjo University Teaching Hospital

The study assessed compliance with universal precautions among staff and student nurses in a teaching hospital in Ogun state south west Nigeria. One hundred staff and student nurses were selected, using the convenient sampling procedure, to participate in the study. Required information was collected from the respondents via structured questionnaire. Data gathered included demographic variables, items on hand washing, method of waste disposal, and exposure to body fluid and injury. Data were analyzed using descriptive statistics. The result showed that most of the respondents were female (85%), Christians (88%) with more than 10 years working experience (55%). Further result showed that respondents have good compliance to precautions relating to handling or care of patients and hand washing. Most of the respondents claimed they use universal compliance whether the patients are confirmed to be non-infectious (60%), where potential for exposure to infections are not anticipated (69%) or where the patient been treated is a known person or a colleague at work (86%). However, 64 percent of the respondents had experienced glove failure, 52 percent have had needle-stick injury, and 72 percent had been a victim of accidental unprotected contact with patient’s body fluid. Furthermore, many of the respondents did not take adequate precautions in relation to use of masks, gloves, goggles and protective gowns. Major factors limiting the compliance of the respondents with universal precautions include high job demands (52%), unavailable equipments (58%) and cost of equipments or materials (69%). As a provision to enhancing compliance with universal precaution among nurses the health facility (hospital), assisted by government should make provision for availability and affordability of protective materials. Emphasis on periodic and continuous training of health workers on the use of precaution should be highlighted in institutional policy. Keywords: Compliance, Universal Precautions, nurses, Nigeria

Improving Maternal Care through a State-Wide Health Insurance Program: A Cost and Cost-Effectiveness Study in Rural Nigeria.

While the Nigerian government has made progress towards the Millennium Development Goals, further investments are needed to achieve the targets of post-2015 Sustainable Development Goals, including Universal Health Coverage. Economic evaluations of innovative interventions can help inform investment decisions in resource-constrained settings. We aim to assess the cost and cost-effectiveness of maternal care provided within the new Kwara State Health Insurance program (KSHI) in rural Nigeria.We used a decision analytic model to simulate a cohort of pregnant women. The primary outcome is the incremental cost effectiveness ratio (ICER) of the KSHI scenario compared to the current standard of care. Intervention cost from a healthcare provider perspective included service delivery costs and above-service level costs; these were evaluated in a participating hospital and using financial records from the managing organisations, respectively. Standard of care costs from a provider perspective were derived from the literature using an ingredient approach. We generated 95% credibility intervals around the primary outcome through probabilistic sensitivity analysis (PSA) based on a Monte Carlo simulation. We conducted one-way sensitivity analyses across key model parameters and assessed the sensitivity of our results to the performance of the base case separately through a scenario analysis. Finally, we assessed the sustainability and feasibility of this program's scale up within the State's healthcare financing structure through a budget impact analysis. The KSHI scenario results in a health benefit to patients at a higher cost compared to the base case. The mean ICER (US$46.4/disability-adjusted life year averted) is considered very cost-effective compared to a willingness-to-pay threshold of one gross domestic product per capita (Nigeria, US$ 2012, 2,730). Our conclusion was robust to uncertainty in parameters estimates (PSA: median US$49.1, 95% credible interval 21.9-152.3), during one-way sensitivity analyses, and when cost, quality, cost and utilization parameters of the base case scenario were changed. The sustainability of this program's scale up by the State is dependent on further investments in healthcare.This study provides evidence that the investment made by the KSHI program in rural Nigeria is likely to have been cost-effective; however, further healthcare investments are needed for this program to be successfully expanded within Kwara State. Policy makers should consider supporting financial initiatives to reduce maternal mortality tackling both supply and demand issues in the access to care

Unit costs by cost category for low and high utilisation profiles.

<p>ANC, antenatal care.</p

Cost-effectiveness of KSHI program (US$ 2012).

<p>SoC, standard of care; KSHI, Kwara state health insurance; DALY, disability-adjusted life year; ICER, incremental cost-effectiveness ratio; HIF, health insurance fund; CS, cost saving. Scenario 1 of the standard of care (SoC1) refers to an increased utilization of the standard of care clinics; scenario 2 of the standard of care (SoC2) refers to an increased cost and quality of care improvement in the standard of care clinics (ie access to EOC if delivery in a health facility and access to preventive treatment of hypertensive disorder complications if access to ANC); and scenario 3 of the standard of care (SoC3) refers to increased utilization, cost and quality of care improvement in the standard of care clinics.</p><p>Cost-effectiveness of KSHI program (US$ 2012).</p

Projected incremental and relative annual cost of maternal care in Kwara state, Nigeria.

<p>Scale up scenarios refer to scenarios where the access to the insurance program is scaled up to 60, 80 or 100% of the population in need.</p

One-way sensitivity analysis comparing KSHI care vs standard of care.

<p>P, probability; y, year; mo, month; US$, US dollar. Blue bars represent the change in ICER when a parameter is varied to a lower value than the base case estimate. Red bars represent the change in ICER when a parameter is varied to a higher value than the base case estimate. All values for the parameters tested in this sensitivity analysis and the resulting ICERs are given in additional results (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139048#pone.0139048.s001" target="_blank">S1 File</a>).</p

Cohort distribution and outcomes.

<p>SoC, standard of care; KSHI, Kwara state health insurance; ANC, antenatal care; EOC, essential obstetric care; PPH, post-partum heamorrhage; HTD, hypertensive disorders; OL, obstructed labour; n, number.</p><p>*death among complicated deliveries only.</p><p>Cohort distribution and outcomes.</p

Input parameters for cost-effectiveness analyses.

<p>ANC, antenatal care; EOC, essential obstetric care; distr: probability distribution specified for each parameter in the Monte Carlo simulations; ref, reference; rr, relative risk; OL, obstructed labour; HTD, hypertensive disorder. Beta distributions are specified by mean (standard deviation); uniform distributions by minimum and maximum values; triangular distributions by average (minimum and maximum).</p><p>*Own calculation (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139048#pone.0139048.s001" target="_blank">S1 File</a>).</p><p>Input parameters for cost-effectiveness analyses.</p