Background:Nigeria has a high population density but a weak health-care system. To improve the quality of care, 3 organizations carried out a quality improvement pilot intervention at the primary health-care level in selected rural areas.Objective:To assess the change in quality of care in primary health-care facilities in rural Nigeria following the provision of technical governance support and to document the successes and challenges encountered.Method:A total of 6 states were selected across the 6 geopolitical zones of the country. However, assessments were carried out in 40 facilities in only 5 states. Selection was based on location, coverage, and minimum services offered. The facilities were divided randomly into 2 groups. The treatment group received quality-of-care assessment, continuous feedback, and improvement support, whereas the control group received quality assessment and no other support. Data were collected using the SafeCare Healthcare Standards and managed on the SafeCare Data Management System—AfriDB. Eight core areas were assessed at baseline and end line, and compliance to quality health-care standards was compared.Result:Outcomes from 40 facilities were accepted and analyzed. Overall scores increased in the treatment facilities compared to the control facilities, with strong evidence of improvement (t = 5.28, P = .0004) and 11% average improvement, but no clear pattern of improvement emerged in the control group.Conclusion:The study demonstrated governance support and active community involvement offered potential for quality improvement in primary health-care facilities.

Background In 2015 the US President’s Emergency Plan for AIDS Relief (PEPFAR) initiated its Geographic Prioritization (GP) process whereby it prioritized high burden areas within countries, with the goal of more rapidly achieving the UNAIDS 90–90-90 targets. In Kenya, PEPFAR designated over 400 health facilities in Northeastern Kenya to be transitioned to government support (known as central support (CS)). Methods We conducted a mixed methods evaluation exploring the effect of GP on health systems, and HIV and non-HIV service delivery in CS facilities. Quantitative data from a facility survey and health service delivery data were gathered and combined with data from two rounds of interviews and focus group discussions (FGDs) conducted at national and sub-national level to document the design and implementation of GP. The survey included 230 health facilities across 10 counties, and 59 interviews and 22 FGDs were conducted with government officials, health facility providers, patients, and civil society. Results We found that PEPFAR moved quickly from announcing the GP to implementation. Despite extensive conversations between the US government and the Government of Kenya, there was little consultation with sub-national actors even though the country had recently undergone a major devolution process. Survey and qualitative data identified a number of effects from GP, including discontinuation of certain services, declines in quality and access to HIV care, loss of training and financial incentives for health workers, and disruption of laboratory testing. Despite these reports, service coverage had not been greatly affected; however, clinician strikes in the post-transition period were potential confounders. Conclusions This study found similar effects to earlier research on transition and provides additional insights about internal country transitions, particularly in decentralized contexts. Aside from a need for longer planning periods and better communication and coordination, we raise concerns about transitions driven by epidemiological criteria without adaptation to the local context and their implication for priority-setting and HIV investments at the local level.

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Introduction In 2015, the President’s Emergency Plan for AIDS Relief undertook policy shifts to increase efficiencies in its programming, including transitioning HIV/AIDS funding away from low burden areas. We examine the impact of these changes on HIV outreach in Kenya and Uganda. Methods Qualitative data collection was conducted as a part of a broader mixed-methods evaluation. Two rounds of facility-level case studies and national-level interviews were conducted in Kenya and Uganda, with health facility, sub-national and central Ministry of Health staff, HIV clients, and implementing partners. Results In both countries, the loss of outreach support affected community-based HIV/AIDS education, testing, peer support, and defaulter tracing. Discussion Loss of external support for outreach raises concerns for countries’ ability to reach the 90–90-90 UNAIDS target, as key linkages between vulnerable communities and health systems can be adversely affected. Conclusion Development partners should consider how to mitigate potential consequences of transition policies to prevent negative effects at the community level.

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We evaluated whether markers of economic empowerment are associated with a tolerant attitude toward spousal physical violence (SPV) among employed married women in Nigeria. Cross-sectional analyses of responses to the 2013 Nigeria Demographic Health Survey by a nationally representative sample of 3,999 women aged 15 to 49 years who reported being employed and married. Tolerance for SPV was defined as supporting statements with justifications for wife-beating. Logistic regression assessed the associations of reporting tolerance for SPV with educational attainment and interspousal equivalency in income, controlling for previous exposure to domestic abuse. The prevalence of tolerance for SPV among the sample was 37%. Women with tertiary education had lower odds of tolerance for SPV relative to their counterparts without formal education (adjusted odds ratio [aOR] = 0.22, 95% confidence interval [CI] = [0.12, 0.40], p < .0001). Compared with women with similar income levels as their partners, women who either earned more (aOR = 2.77, 95% CI = [1.36, 5.62], p = .005) or earned less income relative to their spouses (aOR = 1.93, 95% CI = [1.14, 3.26], p = .02) had higher odds of tolerance for SPV. Odds of tolerance for SPV were also higher among women reporting previous spousal abuse than among their counterparts without such a history (aOR = 1.55, 95% CI = [1.14, 2.12], p = .006). A history of nonspousal abuse was associated with lower odds of tolerance for SPV (aOR = 0.56, 95% CI = [0.37, 0.84], p = .005). Lower educational attainment and interspousal differences in income may contribute to tolerance of SPV. Efforts to increase economic empowerment should be combined with education to recognize cultural norms that foster SPV and build skills to exit violent relationships.

Quality measures pervade medicine. Thousands exist and are used to rate hospital quality, to evaluate physician performance, and to determine financial reimbursement, among other uses. 1 Quality measurement is therefore inextricably linked with clinical practice. Yet recently, half of primary care physicians perceived quality measures as negatively impacting the care they deliver. 2 Colloquially among physicians, one hears various explanations for this negative sentiment (e.g., "reporting burden," "measures don't apply to my panel," "measures don't reflect real quality," and so on). One sometimes hears that measures are not "evidence-based." If true, this would be a major obstacle to physician buy-in to quality measurement. The stronger the evidence base behind a measure, the stronger the ethical obligation for physicians to change practice patterns, motivate specific decisions or actions by their patients, and support quality improvement activities locally and nationally. 3 It therefore seems reasonable to ask: What is the evidence base behind quality measures? To help answer this question, we examined the strength of evidence behind quality measures used in Medicare's 2016 Shared Savings Program. These measures apply to over 430 accountable care organizations (ACOs) covering nearly 8 million Medicare beneficiaries. Medicare prefers quality measures endorsed by the National Quality Forum (NQF), which are considered "best in class." 4 When measure developers submit to NQF, they include evidence forms documenting evidence in support of the measure's use. We collected evidence forms for each of the 34 measures. Each form was reviewed independently (by EEA and ML), and the evidence grade(s) behind a measure were collected. We sought to categorize grades charitably, favoring the highest applicable grades. Areas of disagreement were resolved by consensus among all authors. Reviewers also collected the system or systems used to grade that evidence. NQF encourages, but does not require, use of a formal grading system, such as the United States