Following the Nepal earthquake in April 2015, UNFPA estimated that 1.4 million women of reproductive age were affected, with approximately 93,000 pregnant and 28,000 at risk of sexual violence. A set of priority reproductive health (RH) actions, the Minimum Initial Services Package (MISP), was initiated by government, international and local actors. The purpose of this study was to identify the facilitators and barriers affecting the implementation of priority RH services in two districts.In September 2015, a mixed methods study design was used in Kathmandu and Sindhupalchowk districts to assess the implementation of the priority RH services five months post-earthquake. Data collection activities included 32 focus group discussions with male and female participants aged 18–49; 26 key informant interviews with RH, gender-based violence (GBV), and human immunodeficiency virus (HIV) experts; and 17 health facility assessments.The implementation of priority RH services was achieved in both districts. In Kathmandu implementation of emergency RH services started within days of the earthquake. Facilitating factors for successful implementation included disaster preparedness; leadership and commitment among national, international, and district level actors; resource mobilization; strong national level coordination; existing reproductive and child health services and community outreach programs; and supply chain management. Barriers included inadequate MISP training for RH coordinators and managers; weak communication between national and district level stakeholders; inadequate staffing; under-resourced and fewer facilities in rural areas; limited attention given to local GBV and HIV organizations; low availability of clinical management of rape services; and low awareness of GBV services and benefits of timely care.Ensuring RH is included in emergency preparedness and immediate response efforts and is continued through the transition to comprehensive care is critical for national governments and humanitarian response agencies. The MISP for RH remains a critical component of response efforts, and the humanitarian community should consider these learnings in future emergency response. Reproductive health (RH) services in humanitarian emergencies remain a critical priority. As greater numbers of people become displaced and the contexts of their displacement becomes more diverse, ensuring access to the standard of care of priority RH services must be included in all types of emergency response efforts. Additionally, addressing comprehensive RH care when transitioning out of the emergency phase is vital. The priority RH services, known as Minimum Initial Services Package (MISP) for RH, were identified in 1996 and included in the Reproductive Health in Refugee Situations: An Inter-agency Field Manual (IAFM) in 1999 . The MISThrough the Inter-agency Working Group (IAWG) for Reproductive Health in Crisis, assessments of the degree to which the priority RH services have been implemented in an emergency response have been conducted in Indonesia 2005), Kenya (2008), Haiti (2010), and Jordan (2013) , 5. Incr, Kenya  in Nepal in two districts: Sindhupalchowk and Kathmandu. The objectives were to: 1) describe factors that facilitated implementation; 2) explain the barriers for implementing RH services; and 3) recommend solutions for improving RH response in Nepal. The study was conducted by a team from the IAWG on RH in Crises in September 2015, with results disseminated in reports to key stakeholders and available online –33.Mixed methods were employed including qualitative and quantitative designs to assess the implementation of priority RH services in two districts in Nepal. The study was conducted in Kathmandu and Sindhupalchowk from September 13–22, 2015. The districts were selected based on diversity of context , number of displaced persons, and number of people in need resulting from the earthquake . Data coFGD sites were selected by the study team based on proximity to a health facility, which was defined as near  and far (more than 1 h). Community health workers recruited FGD participants who were women and men aged 18 to 49, were living in the selected sites, were affected by the earthquake, and who spoke Nepali. The FGDs were conducted separately by gender and age (18–24 and 25–49) with up to eight participants per group.The discussion guides were adapted from the MISP assessment conducted in Jordan among Syrian refugees by IAWG members to fit the Nepali context, translated into Nepali and piloted in Kathmandu. Local Nepali researchers who had prior experience in qualitative research were hired and trained by the co-investigators to facilitate the focus groups. Facilitation and note taking were conducted in Nepali and then transcripts were translated and transcribed into English.KII participants were recruited by the lead RH agencies in the response, and the participants were selected based on their work in RH, GBV and HIV. From these agencies, participants were selected using purposive sampling with maximum variation to account for diverse perspectives. Coordinators, managers, directors, and focal points from government bodies, UN agencies, international, national, or local NGOs working in Kathmandu or Sindhupalchowk were selected to participate.The KIIs utilized three different semi-structured questionnaires  to gather information on knowledge about the MISP and the Additional Priorities, RH concerns and needs, MISP response, disaster risk reduction including preparedness, and facilitating factors and barriers to MISP implementation. The RH and GBV tools were pilot tested among current or former staff working in RH and GBV in Nepal; and the HIV tool was piloted with an HIV expert prior to data collection. All interviews were conducted by a study team member in English.Health facilities in the two districts were selected using the following criteria: served populations affected by the recent earthquakes, provided delivery and newborn services during the past six months, and accessible to the study team. An interview was conducted with the individual in-charge at each health facility. A semi-structured, quantitative questionnaire adapted from previous MISP assessments, was used to interview health providers and conduct direct observation of facilities. A study member conducted the interviews in English or with an interpreter in Nepali.Analysis was conducted by the study team member who oversaw or conducted data collection using a particular method within a specific district. Study team members residing in four locations selected the method for analysis in consideration of their experience, software or application availability, and whether it was deemed appropriate. For focus group discussions, English transcripts were coded and analyzed with themes defined a priori by the MISP components using NVivo 10. For KIIs, given the minimal qualitative data, interviews were coded in Microsoft Word with themes identified according to the components of the MISP. Quantitative data were entered the Census and Survey Processing System (CSPro) and analyzed using SPSS v.22 in alignment with the IAWG MISP online toolkit . HFA datValidity and credibility for the qualitative data were addressed by the research team’s oversight and involvement in the data collection process ensuring the data collected represented multiple perspectives of different stakeholders on the same topics and findings were triangulated using three methods: participants were asked to validate responses; debriefings were held daily to avoid personal bias; and an audit trail documented the process using transcripts and memos. In addition, preliminary findings were shared at a validation meeting with the RH Sub Cluster in Kathmandu at the end of data collection. Lastly, a white paper, summary report and participant report were shared with lead RH agencies following the full analysis and final drafts were shared online –33.The study received ethical approval from the Nepal Health Research Council (NHRC). Additional reviews were done by the Family Health Division (FHD)/Department of Health Services (DoHS) Nepal, and the Nepal RH Sub-cluster. Verbal and written consent were obtained from participants before each discussion. Confidentiality was maintained throughout the study process.Thirty-two FGDs were conducted across all sites, with 16 in each district. A total of 249 people participated with 127 women and 122 men. In Kathmandu, 54 participants were 18–24 years old, and 59 participants were 25–49 years old. In Sindhupalchowk, 69 participants were 18–24 years old, and 67 participants were 25–49 years old.A total of twenty-four KIIs were conducted in Kathmandu and Sindhupalchowk with informants representing the DoHS, UN agencies and, international and national organizations. Thirteen KIIs were conducted in Kathmandu including seven interviewees working on RH, five interviewees working on GBV, and one interviewee working on HIV. Further, 11 KIIs were conducted in Sindhupalchowk with four interviewees working on RH, five interviewees working on GBV, and two interviewees working on HIV.Assessments were conducted at seventeen facilities with eight in Kathmandu and nine in Sindhupalchowk. Facilities visited included public and private facilities, district level facilities, primary health care centers (PHCCs), and health posts. Participants included medical officers, nurses, and auxiliary nurse midwives (ANM) in charge of the health facility.The majority (10 out of 12) of lead RH agencies key informants were aware and had knowledge of the MISP objectives, but participants from non-lead agencies for RH were less knowledgeable about specific MISP objectives, or priority activities. Fewer than half (five out of 12) of the RH KIs in Kathmandu and Sindhupalchowk had been trained in the MISP despite trainings conducted prior to the earthquake in Kathmandu.Coordination was led by DoHS FHD and UNFPA, and implementation of the priority RH services began within days of the earthquake in Kathmandu. In Sindhupalchowk, coordination was first established in the health cluster and then in separate RH sub-cluster meetings approximately two months after the earthquake. However, RH related agendas were included and discussed in the health cluster meeting before the RH sub-cluster was established. In Kathmandu, RH KIs reported overall inclusion of key stakeholders, such as the DoHS, UN agencies, local and international NGOs and adolescents in RH sub-cluster coordination meetings. Overall, informants (83%) reported sufficient funding to meet RH emergency needs, including the availability of all RH kits (0–13). FGD participants in Kathmandu were involved in coordination efforts to distribute supplies and identify those in need. In Sindhupalchowk, Village Development Committees (VDC) were reported to be involved in distribution activities. The effectiveness of the coordination was rated ‘good’ or ‘excellent’ by most Kathmandu RH KIs and ‘good’ by all the RH KIs in Sindhupalchowk. Areas for improvement included better communication between national and district levels regarding roles and responsibilities and more participation from district officers and representatives from HIV, GBV sectors as well as lesbian, gay, bisexual, transgender and intersex (LGBTI) communities, the private sector and local and international NGOs.All GBV KIs and the majority (10 out of 12) of RH KIs had heard of incidents of sexual violence in their districts. In Kathmandu, protection efforts varied by the level of health facility and hospital facilities had taken more steps to prevent GBV. Lighting provision in Kathmandu internally displaced person (IDP) camps was inadequate. In Sindhupalchowk, the temporary field hospital provided latrines that were sex-separated but made of tarpaulin during the first eight weeks. In Sindhupalchowk, only two of the eight health facilities visited had sex-separated latrines compared to five out of nine facilities visited in Kathmandu. All latrines were equipped with inside locks.Of 17 facilities visited in both locations, only two had private rooms for sexual violence survivors. FGD participants did not report safety concerns in accessing health facilities. The majority of RH KIs reported that clinical management of rape (CMoR) was at least partially available; however, the HFA found that only three out of nine facilities in Kathmandu could provide CMoR. In Sindhupalchowk, only half of facilities could provide partial CMoR with the gap most often seen in the availability of post-exposure prophylaxis for HIV. Reasons given for the unavailability of service provision included the need for training, additional supplies and equipment, or the lack of clients.“Women remain silent [so] that others would [not] know about it. Otherwise they will be blamed and disgraced, even if they are innocent.” Only one hospital in Kathmandu and the district hospital in Sindhupalchowk treated cases of sexual violence. Although there was a protocol for CMoR, and a referral pathway, there were no standard operating procedures available at health facilities for referral of survivors of sexual violence.Most RH and GBV KIs in both districts reported that although the GBV referral pathway included health, police, and legal actors, the quality of the referral system was a concern. Although there were information, education, and communication (IEC) campaigns to encourage reporting sexual violence, FGD participants were unaware of the referral pathway. Women in Sindhupalchowk said that they would report GBV cases to the police or women’s organizations. The great majority of FGD participants said sexual violence did not exist in their communities, although a few reported their communities had cases of intimate partner violence (IPV). Women living in Kathmandu’s displacement camps reported fear while collecting water or accessing the latrines, and in one FGD group conducted in Sindhupalchowk, women reported feelings of insecurity in their temporary shelters. However, FGD participants and health service providers all noted that reporting of GBV cases was low because of shame and stigma associated with sexual violence survivors. As one woman said in Sindhupalchowk, “If they get such disease, people are scared what society will say about them. Uneducated people hide the disease, but educated people treat it.” Nearly all RH and HIV KIs and FGD participants reported condoms were available for free, except for FGD participants in a Kathmandu displacement camp.RH and HIV KIs and HFA participants reported that safe blood transfusion was available in Kathmandu, but had not been available in Sindhupalchowk, since the temporary hospital ceased operation. Fifteen visited facilities had sufficient supplies for the implementation of standard precautions to be followed, and RH KIs reported at least partial availability of standard precautions with quality concerns in rural facilities. Only two hospitals, one in each district, provided post-occupational exposure treatment for staff. Knowledge on HIV and STI prevention and risk reduction varied among FGD participants. More awareness was found among 18–24-year-old age groups, and male participants in Kathmandu. The location of services was less known by participants, with many reporting that the stigma of persons living with HIV might prevent people from seeking treatment. As one man in Kathmandu reported, We have problems of the road. We have to carry the patient. Sometimes in a bed sheet, sometimes on our back. We have to carry till the road where the ambulance can come.” The majority of KIs (10 out of 12) mentioned ensuring the availability of SBAs and supplies for normal births as priority activities, and far fewer mentioned ensuring the availability of BEmOC and newborn care (5 out of 12) or CEmOC and newborn care (6 out of 12). Just three out of 12 KIs mentioned ensuring a 24-h, seven days per week referral system to support EmOC services, although one such system had been established for pregnancy complications. RH sub cluster members reported IEC radio and TV campaigns had been conducted to increase facility deliveries. In Sindhupalchowk, after the earthquake, the referral system included the temporary hospital for CEmOC. When it ceased to operate, referrals went to Dhulikhel Hospital in the neighboring district. Sindhupalchowk FGD participants reported bypassing nearby health posts or the district hospital when experiencing complications, and going directly to the neighboring district hospital or Kathmandu for quality care. On-going barriers to access delivery care in the facilities included the direct and indirect costs associated with reaching facilities, particularly in far-away districts. Noted by one Sindhupalchowk woman, “We go to the health post for small problems like stomach pain, but if any complication occurred we have to go to the district hospital and we cannot afford it.” In Sindhupalchowk, RH KIs reported that female community health volunteers (FCHVs) and health facilities distributed clean delivery kits (CDKs) to pregnant women. There was newborn care, although not always comprehensive, in both districts, with well-established comprehensive care in higher-level hospitals in Kathmandu. RH KIs in Sindhupalchowk reported barriers to implementing comprehensive newborn care included lack of or malfunctioning equipment.In Kathmandu, female participants had greater knowledge of danger signs during pregnancy compared to male participants. All participants knew where to go for maternal and child health (MCH) needs following the earthquake. FGD participants in Kathmandu preferred facility deliveries, whereas preferences varied in Sindhupalchowk and these findings aligned with interviews with facility staff. All facilities visited for the HFA were providing normal delivery services, and RH KIs reported basic emergency obstetric care (BEmOC) was available. CEmOC was available in Kathmandu but not reliably in Sindhupalchowk after the closing of the temporary hospital. Among the RH KIs, one-fourth had heard of incidents of maternal mortality, and one explained this was worse post-earthquake due to landslides, floods, and road and airport obstructions. Perceptions among FGD participants in Sindhupalchowk reflected the sense of risk due to road closures. One woman in Sindhupalchowk described, “KIs reported that during the immediate response, staff capacity assessments and trainings took place on RH Kits, CMoR, standard precautions, family planning, and quality assurance for maternal and newborn care. At the time of the assessment, RH KIs reported a continuing need for human resource assessments and training at the national and district levels. RH KIs reported that more birthing facilities were being identified, however with concerns that too many birthing facilities could limit provider’s practice of SBA. At the time of the assessment, nearly all visited health facilities reported a reliable supply chain. However, two-thirds of the facilities reported shortages immediately after the earthquake.Among FGD participants, groups reported awareness of short and long-term contraceptive methods, except for emergency contraception (EC), and knowledge of free services. A shortage of injectables and implants following the earthquake was filled by UNFPA, although the availability of EC continued to vary between and within districts. The HFA showed that all but two facilities (one in each district), provided syndromic treatment for STIs; however, nearly all facilities reported an insufficient supply of needed medicines for this care, significantly affecting quality. Most FGD participants had low knowledge of STIs or location of services. Most RH and HIV KIs reported that antiretroviral (ARV) therapy had continued, without delay, and referral systems were reportedly functioning. The HFA found that all visited facilities in Sindhupalchowk had a referral system for ARV therapy, including PMTCT. In Kathmandu, four facilities reported a referral system. Although all RH KIs reported that supplies for menstrual hygiene were at least partially available if not fully available through mobile services, availability varied between districts. In Kathmandu, only the two displacement camps visited reported having received menstrual hygiene supplies, compared to all FGDs except one in Sindhupalchowk. Participants asked for more guidance on disposal and for more supplies.There was little reporting of inclusion of LGBTI persons, adolescents, or persons with disabilities in programming. Only one facility in total was equipped with accessible toilets and wheelchair ramps.Although there was limited adolescent programming, a high interest among FGD participants was reported. RH KIs also cited adolescent corners in camps during the response. In Sindhupalchowk, adolescents could access SRH services without parental consent in 75% of visited facilities, and in Kathmandu, in a third of visited facilities.RH, GBV, and HIV KIs reported a number of RH-related emergency preparedness activities prior to the earthquake, including incorporation of MISP components in disaster preparedness and response plans; the pre-positioning of RH Kits; development of a logistics system; MISP trainings and emergency drills; facility assessments; emergency preparation by hospitals; establishment of a Code of Conduct (CoC) on sexual exploitation and abuse (SEA) prevention; inclusion of GBV in national disaster policy, with pre-positioning of post-rape kits and a GBV referral system; HIV prevention trainings; and a national-level pre-positioning of condoms and medicines. However, logistical challenges were reported by RH KIs during response efforts.These findings are further evidence of a global, positive trend in addressing the MISP for RH priorities from the onset of emergency response efforts, as also shown in recent MISP assessments conducted in Indonesia, Kenya, Haiti and Jordan , 5. ThesThe strength of the coordination of the priority RH services was likely due to the leadership commitment and existing emergency preparedness mechanisms that had been developed prior to the earthquake. Strong committed leadership is evidenced in immediate and ongoing coordination; concerted innovative efforts to address all of the MISP priority objectives and related priority activities; successful fundraising and procurement of supplies; ensuring a lead agency within the health cluster to support coordinated efforts to address the MISP -- all of which are established priority activities for the first objective of the MISP. The National Strategy for Disaster Risk Management, developed in 2008, made strides in preparation, planning, and policies that allowed for a stronger response to the earthquake than otherwise would have been possible . For RH,Despite dedicated leadership and pre-earthquake RH coordination mechanisms, there were significant barriers to more effective implementation of priority RH services. Although the need for the priority RH activities in emergencies was understood by stakeholders, concern of the prioritization of community needs – such as food and water – became a barrier to the provision of RH services. Inclusion of GBV and HIV actors, as well as intersectoral coordination with RH efforts, was reportedly weak, as was communication between district and national level authorities including the designation of roles and responsibilities between stakeholders. There was a lack of an opportunity to implement district contingency planning before the earthquake and a gap in understanding of the contents of RH kits to implement recommended RH services. International actors’ knowledge of existing national programs and of the human resources and capacity of local organizations was limited, leading to parallel activities by international agencies. Delays in establishing an RH sub-cluster in Sindhupalchowk after the earthquake led to delays in the MISP implementation. Funding was not always available during emergency response efforts despite overall reports of adequate funding. Insufficient human resources, including too few qualified staff to offer CMoR and HIV services, led to low capacity for adequate response and quality concerns in the referral pathway. Barriers to accessibility to all RH services included low awareness of services in some communities, direct and indirect financial costs accessing services, challenging road conditions, destruction of district hospital in Sindhupalchowk, and low reporting by community members because of their own survival priorities, as well as shame and stigma associated with GBV and HIV. Logistical challenges from the earthquake and subsequent monsoon, as well as hesitation from communities to engage in outside efforts to rebuild at the compromise of their own community’s rebuilding initiatives, were also reported as barriers.These findings contribute to the small body of peer-reviewed and grey literature exploring implementation of RH services in post-earthquake Nepal. Results vary across studies; a report by the Central Department of Population Studies found an overwhelming majority of respondents satisfied with health services, and 80% reported access to RH and women’s health information . SimilarMultiple efforts have taken place since the earthquake to continue strengthening RH services while transitioning out of emergency response to comprehensive RH services. This transition will continue to be aided by the policies, programs, and protocols established pre-earthquake. Attention to strengthening the implementation of these mechanisms and protocols will enable improved access to more long-term FP methods; stronger quality of and awareness and access to GBV, HIV, and STI services; reduce stigma of GBV and HIV; and improved access to culturally appropriate menstrual hygiene supplies. Notably, since the study, the National Family Planning Costed Implementation Plan (2015–2020) has been established to outline Nepal’s strategy of enabling provision of and access to quality family planning services, and central and district level MISP trainings were held with efforts to mainstream MISP into district disaster preparedness and response plans , 40. In Nepal’s geographical terrain and rural communities also demand on-going attention to increasing access for harder-to-reach communities and ensuring effective staffing, referral pathways, and supply chains to enable required services. Encouragingly, since the study, more than 300 health service providers have been trained on CMoR, and three new districts, including Sindhupalchowk, now have One Stop Crisis Management Centers (OSCMCs). Lastly, commitment to more inclusive programming is needed to accommodate the unique needs of key populations such as persons with disabilities, adolescents, and LGBTI individuals.The study took place approximately five months after the earthquake; therefore, some KIs involved in response had left Nepal, and the long recall period for participants might have made it difficult to accurately recall immediate, post-earthquake service availability. Additionally, FGD participants were selected based on their proximity to functioning birthing centers (not by their level of impact from the earthquake), which may have led to responses from those with greater access to services. In addition, we were unable to reach all operational health facilities in the districts due to time constraints and challenging road conditions. Lastly, this study took place in two districts and findings only reflect the RH response in these locations.Findings from Nepal contribute to a continuing global, positive trend in attention to RH priorities from the onset of an emergency. This attention was demonstrated by disaster preparedness by the government, commitment to RH before and immediately after the earthquake, a pre-existing health system and outreach program, and effectiveness of coordination particularly on a national level. The implementation of the MISP in post-earthquake Nepal provides valuable lessons for national governments and humanitarian practitioners on factors that facilitate and hinder effective implementation of critical RH services during an emergency. Considering these findings when preparing for, and responding to, crises will allow for stronger and more effective response efforts, and ultimately reducing women and girls’ excess morbidity and mortality.


Understanding links between behaviour change techniques (BCTs) and mechanisms of action (the processes through which they affect behaviour) helps inform the systematic development of behaviour change interventions.This research aims to develop and test a methodology for linking BCTs to their mechanisms of action.Study 1 (published explicit links): Hypothesised links between 93 BCTs  and mechanisms of action will be identified from published interventions and their frequency, explicitness and precision documented. Study 2 (expert-agreed explicit links): Behaviour change experts will identify links between 61 BCTs and 26 mechanisms of action in a formal consensus study. Study 3 (integrated matrix of explicit links): Agreement between studies 1 and 2 will be evaluated and a new group of experts will discuss discrepancies. An integrated matrix of BCT-mechanism of action links, annotated to indicate strength of evidence, will be generated. Study 4 (published implicit links): To determine whether groups of co-occurring BCTs can be linked to theories, we will identify groups of BCTs that are used together from the study 1 literature. A consensus exercise will be used to rate strength of links between groups of BCT and theories.A formal methodology for linking BCTs to their hypothesised mechanisms of action can contribute to the development and evaluation of behaviour change interventions. This research is a step towards developing a behaviour change ‘ontology’, specifying relations between BCTs, mechanisms of action, modes of delivery, populations, settings and types of behaviour. The development of a formal method to link behaviour change techniques with mechanisms of action to support investigators as they design and evaluate behavioural interventions. Human behaviour underlies many of the policy challenges of the twenty-first century: increasing health care needs, controlling epidemics and preventing pandemics, climate change, environmental degradation, poverty and inequality. In public health, behaviours  contribute to many of the world’s leading causes of mortality including cardiovascular disease, lung cancer, stroke and HIV , 2 and cBehavioural interventions have the potential to transform the health of populations, often at an extremely low cost , 8. A nuThe science of behaviour change has seen significant advances over the past few decades, including developing methods to standardise and improve the reporting of interventions and their underlying theory , 14–16. what is delivered), Michie and colleagues, in collaboration with a large international network, developed a formal means for characterising behaviour change interventions, the BCT Taxonomy v1 (BCTTv1). This is an extensive, integrated, hierarchical classification system for reliably specifying intervention components in terms of 93 BCTs, organised into 16 groupings . The resource will include the study outputs, worked examples of applying the matrices to complex intervention design and evaluation and research recommendations.We will increase awareness and understanding of the hypothesised BCT-mechanismof action and BCT-theory links through dissemination of the work and implementation of the findings. We will develop a guide to developing and evaluating theory-based interventions, providing wide access to the multidisciplinary research and user community [in similar fashion to those produced for the BCT Taxonomy project , 23, 24;https://www.gem-measures.org/Public/Home.aspx). We will hold national and international multidisciplinary workshops to introduce the developed matrices and provide supervised experience using the distance learning tutorial system, as developed for the BCT Taxonomy study. Overall, findings will be reported via national and international conferences, relevant high-quality peer-reviewed journal articles, presentations in association with MRC’s regional hubs of excellence and Population Health Sciences Research Network, and via the study website, which will also contain links to relevant sites.There will be a facility for commenting on our methodology and findings, for reporting experiences of applying the links and for sharing relevant research. We will link this with both the current project website and with the US National Institute of Health’s Grid-Enabled Measures (GEM) portal , and as part of our dissemination work.We will institute an automatic registration system to track usage of this database.The study will conform to relevant ethical and legal guidelines for participant consent, confidentiality and data storage. All data will be preserved and its availability for use by other research teams will be publicised via the website resource, on the Open Science Framework (see Supplementary MaterialsClick here for additional data file.


Overweight and obesity are America’s number one health concern. The prevalence of obesity in the United States is greater than 36%, a rate that has doubled since 1970. As the second most preventable cause of death, obesity is a risk factor for diabetes, cardiovascular disease, stroke, and cancer, all major causes of death. Primary care clinics may be an ideal setting for weight control interventions to help manage and prevent diabetes. For this reason, the Centers for Medicare and Medicaid Services (CMS) implemented a health care procedure coding system code for intensive behavioral therapy (IBT) for obesity within primary care in 2012 to facilitate payment for addressing obesity, which was followed by broader coverage by most insurers for IBT for adults in 2013. However, the impact of this coverage on patient-centered outcomes is largely unknown.The overarching goal of this study is to understand the comparative effectiveness of obesity counseling as covered by CMS and other insurers in improving weight loss for adults either with or at increased risk for type 2 diabetes.This study leverages the novel infrastructure of the Patient-Centered Outcomes Research Institute–funded PaTH Clinical Data Research Network. The PaTH network is comprised of Geisinger Health System, Johns Hopkins University, Johns Hopkins Health System, Lewis Katz School of Medicine at Temple University, Temple Health System, Penn State College of Medicine, Penn State Milton S Hershey Medical Center, University of Pittsburgh, UPMC and UPMC Health Plan, and the University of Utah. Electronic health record (EHR) data will originate from the 6 PaTH health systems. Specifically, we will (1) evaluate the impact of broader preventive service coverage for obesity screening and counseling on weight loss, diabetes incidence, and diabetes outcomes in patients with diabetes or at increased risk for diabetes (defined by body mass index [BMI] ≥25). We will determine how the annual probability of receiving obesity and/or nutritional counseling changed pre- and postpolicy across all insurers in a cohort of patients with diabetes and at high risk for diabetes. We will (2) compare patient weight loss and diabetes-related outcomes among those who receive obesity screening and counseling with those who do not, following implementation of preventive service coverage. We will examine postpolicy impact of obesity screening and counseling in a cohort of patients with diabetes and at increased risk for diabetes. Specific outcomes to be examined include weight loss, diabetes incidence, and diabetes outcomes. Exploratory outcomes will include patient-reported outcomes. Furthermore, we will determine patient characteristics, including demographics, and practice characteristics, including provider type.Our PCORI-funded study is underway. To date, we have obtained our second data extraction from the PaTH CDRN and are performing data editing and cleaning. Next steps include analysis of early policy change.Given patients who are overweight are at highest risk for diabetes, improved weight management services could prevent diabetes and its negative health outcomes. Comparing weight and diabetes outcomes in 3 states using EHRs and claims data before and after this policy was implemented using the PaTH Network will allow important insight into policy effectiveness.DERR1-10.2196/12054 Overweight and obesity are America’s number one health concern. The prevalence of obesity in the United States is greater than 36% , which iPrimary care clinics may be an ideal setting for weight control interventions. More than 80% of Americans see a primary care physician (PCP) regularly, and access to primary care is expected to increase with health care reform -11. The This study leverages the novel infrastructure of the Patient-Centered Outcomes Research Institute (PCORI)–funded PaTH Clinical Data Research Network (CDRN), a partnership of 4 mid-Atlantic academic health systems  that has established governance to operate as an integrated research network. In 2015, the University of Utah and Geisinger Health System also joined PaTH, creating an electronic health record (EHR)–based data infrastructure across 3 states .This study is significant for several reasons. First, diabetes is a leading public health concern and is associated with significant economic burden. Recent health policy changes  are expected to impact diabetes outcomes, and this study will capture differences in these outcomes through varied state implementation. Understanding effects on diabetes outcomes can inform future policies to improve overall diabetes care for patients. Second, this study focuses on the influence of policy-level factors for diabetes management. Poor outcomes are preventable but require complex medical and lifestyle management, including careful diet modification, medication use including oral pills and/or insulin injections, blood glucose self-monitoring, frequent medical visits and laboratory testing, cholesterol management, weight management, and physical activity. The ability of individuals with diabetes to effectively manage their diabetes is multifactorial, influenced by individual-, social-, and policy-level factors . FinallyThe overarching goal of this study was to understand the comparative effectiveness of obesity counseling as covered by CMS in improving weight loss for adults either with or at increased risk for type 2 diabetes. CMS and most insurers now include obesity screening and counseling benefits, with no cost sharing to patients . As patiAim 1: The study will evaluate the impact of broader preventive service coverage for obesity screening and counseling on weight loss, diabetes incidence, and diabetes outcomes in patients with diabetes or at increased risk for diabetes (defined by body mass index [BMI] ≥25). We will determine how the annual probability of receiving obesity counseling  changed pre- and postpolicy across all insurers in a cohort of patients with diabetes and at increased risk for diabetes. We hypothesize that individual patients are more likely to receive counseling following coverage implementation. Furthermore, we hypothesize that patients who receive a greater number of face-to-face visits will have greater weight loss compared with those who receive fewer visits. Exploratory outcomes will include patient-reported outcomes (PROs).1c [HbA1c], controlled blood pressure, and use of a statin medication). Exploratory outcomes will include PROs. Furthermore, we will determine patient characteristics, including demographics , and practice characteristics, including provider type, and their impact on receiving/providing obesity screening and counseling. Understanding patient and practice characteristics most likely to engage in obesity counseling can identify best practices and inform how to increase engagement by both patients and providers.Aim 2: The study will compare patient weight loss and diabetes-related outcomes among those who receive obesity screening and counseling with those who do not, following implementation of preventive service coverage. We will examine postpolicy impact of obesity screening and counseling in a cohort of patients with diabetes and at increased risk for diabetes. Specific outcomes to be examined include weight loss, diabetes incidence, and diabetes outcomes  or no insurance. The organizations are also diverse and are affiliated with community-based hospitals and outpatient practices in addition to their academic hospitals. Other facilities include rehabilitation hospitals, dialysis centers, fitness and wellness centers, psychiatric hospitals, ambulatory surgery centers, and home health care support.PaTH leverages health-related data from (1) EHRs, (2) PROs, (3) insurance claims data, and (4) biospecimen data. The PaTH data that will be used in the study will be limited to EHR data and claims data.The PaTH network has also established a centralized process for institutional review board (IRB) reviews. Creating separate IRB protocols with different formats and procedures to be reviewed by separate IRBs would be an inefficient and ineffective process. This problem has been recognized by the National Institutes of Health, which promotes use of a single IRB in multisite clinical research studies to reduce duplication of effort, speed-up the initiation of important research, and save time and resources . To thisEHR data will originate from the 6 PaTH health systems. These health systems have greater than 13 million patients with at least one encounter and 5 million active patients in their EHR systems see .PaTH has united previously disconnected health care systems with a common, scalable data architecture. Our health systems employ the 2 most commonly used EHR systems nationwide—Epic and Cerner. Penn State uses Cerner; University of Pittsburgh Medical Center (UPMC) uses Epic for its outpatient EHRs and Cerner for its inpatient EHRs; and Temple, Johns Hopkins, Geisinger, and the University of Utah use Epic. The health systems also incorporate data from ancillary Information Technology (IT) systems including Eclipsys, General Electric, AllScripts, and Phillips. Each EHR system has undergone extensive customization during their lifetimes, creating disparate systems with inherent interoperability gaps across all areas including diagnosis, lab results, and patient demographic data.All health systems are using, or will use, the following standards to achieve semantic interoperability for their EHRs and ancillary systems: LOINC for encoding laboratory tests; Systematized Nomenclature of Medicine (SNOMED) for medical terminologies; CPT and International Classification of Diseases (ICD)-9 and ICD-10 for encoding problems, diagnoses, and procedures; RxNORM for encoding medications; and DICOM for transmitting radiologic images. Given the heterogeneity of the EHRs, the PaTH network sought an existing solution that permits intersystem syntactic interoperability and leverages previous investments and expertise.Each health system’s efforts to utilize standard vocabularies and formats can significantly narrow the gap of interoperability, but the final bridge is the PCORnet-specified Common Data Model (CDM) . The PCOOnce the PaTH research team cooperatively identifies data elements appropriate for the prespecified research questions, extract, transform, load teams at each site extract these data elements from their EHRs or ancillary systems, deidentify the data, map these data to standard vocabularies as specified by the PCORnet CDM and any additional PaTH data element specifications, and load the data to Pittsburgh’s Comparative Effectiveness Research Core Data Center (CERC-DC), which provides secure data storage and high-throughput computing.The informatics design of PaTH has 2 main features: (1) the ability to support researchers to easily perform exploratory research queries  through the distributed data network and (2) the ability to support use of aggregated deidentified data that conform to our shared PaTH information model. Currently, the PaTH network uses the University of Pittsburgh CERC-DC to house these aggregated datasets. One important feature in this model is that it incorporates authorization and audit mechanisms to ensure that each site retains adequate control and logs of their data. The additional data integration with contextual data and the associated data flow for this study is described in A limitation of EHR data is the uncertainty of its completeness, that is, when a patient receives medical care outside of the health system or is hospitalized while away on vacation. However, claims data can capture clinical encounters that occur outside of our 6 health systems. Claims data also provide other supplementary information—for example, the EHR only tells us a patient was prescribed a statin medication but not whether the patient picked it up from the pharmacy. The insurance data can verify whether a pharmacy claim for the medication was processed, indicating the patient received the medication.The PaTH network has established an operational data infrastructure with the necessary technical safeguards as agreed upon in the PaTH Data Use Agreement for sharing and analyzing data while addressing data confidentiality and security concerns. PaTH has deployed 2 mechanisms for storing, protecting, and sharing data (as described previously under PaTH governance and regulatory issues): (1) data with protected health information (PHI) are stored and protected behind each institution’s firewall in the distributed data network and (2) deidentified data are sent to the PaTH data center at the University of Pittsburgh (CERC-DC). Once data integration is accomplished at each site, sites will remove all PHI and send the deidentified version of the integrated data to the CERC-DC through PaTH’s virtual private network/secure file transfer protocol, which has been operational for data transmission since November 2014. Data analysis will then be performed via secure remote computing using standard statistical software packages .The PaTH CDRN data infrastructure is designed to support a broad range of research topics, with the ability to define specific patient cohorts when needed to support specific use case research questions. This study utilizes 2 patient cohorts: (1) diabetes cohort and (2) at increased risk for diabetes cohort. As demonstrated in . Using the PaTH Network infrastructure, we will examine the impact of the policies on a population of more than 328,000 patients with diabetes, as well as an additional 2,000,000 patients at increased risk for the development of diabetes.The overarching goal of this research was to understand the comparative effectiveness of obesity counseling as covered by CMS in improving weight loss for adults either with or at increased risk for type 2 diabetesEvaluate the impact of broader preventive service coverage for obesity screening and counseling on weight loss, diabetes incidence, and diabetes outcomes in patients with diabetes or at increased risk for diabetes (defined by BMI ≥25). We will determine how the annual probability of receiving obesity and/or nutritional counseling (as defined by CPT code) changed pre- and postpolicy across all insurers in a cohort of patients with diabetes and at increased risk for diabetes. We hypothesize that individual patients are more likely to receive counseling following coverage implementation. Furthermore, we hypothesize that patients who receive a greater number of face-to-face visits will have greater weight loss compared with those who receive fewer visits. Exploratory outcomes will include PROs, as outlined in Weight loss is an important patient-centered outcome, as nearly every patient with overweight/obesity desires weight loss and assistance from their physician but few currently receive it -21. Furt1c also remains an important patient-centered outcome, given it is well-established that improved glycemic control results in prevention of serious complications  and is appropriate for the timeframe of the study. In addition, we will examine blood pressure control, use of a statin medication, and appropriate diabetic screening, given the importance of these guideline-recommended measures in diabetes care. Exploratory outcomes will include PROs  listed in HbA1c results >7.0%, or 1 inpatient diagnosis code or 2 out-patient diagnosis codes for type 2 diabetes (ICD-9 codes 250.xx). This algorithm has been shown to have 98% sensitivity and 98% specificity for diabetes when compared with the gold standard of manual chart review by a trained research nurse ! Understanding more about diabetes and providing input to researchers about my personal experiences is mutually beneficial to the patient and the research.Patient coinvestigator1c. The distributions of outcome measures will be examined by using minima, maxima, ranges, medians, quartiles, means, and SDs for continuous variables and frequency and contingency tables for categorical variables.Descriptive statistics will be generated to describe the characteristics of different cohorts of interest. The diabetes-related outcomes will be summarized at the individual level on a yearly, quarterly, or monthly basis depending on the availability of the data within the data source. There will be binary outcomes (Yes/No) such as receiving obesity and/or nutritional counseling, controlled diabetes, controlled blood pressures, receiving annual eye exam, and count outcomes, such as numbers of clinic visits, emergency department visits, and hospitalization, and continuous outcomes, such as weight and HbATo evaluate the impact of policy changes on these outcomes (Aim 1), we will examine how these outcomes change over time, in response to the policy changes. As descriptive analyses, we will plot the mean trajectory of each outcome over time at the clinic level, health system level, and state level. Outcomes will be at least annually, but possibly monthly or quarterly, depending on variable availability from the data source. The statistical modeling of patterns of changes in individual-level outcomes will be carried out through multilevel mixed-effects models -28. The ijkt denote the binary response of receiving obesity and/or nutritional counseling at year t as broader coverage change in 2013 for the kth subject within the jth cluster of the ith state, t=–4, –3, ..., 0, 1, ..., 6, i=1, 2, 3; j=1, 2, ..., ci, and k=1, 2, ..., nij, where ci is the number of clusters within the ith state and nij is the sample size within the jth cluster of the ith state. An individual subject may not be in the system for all the time points of measurement, so t will have a smaller range of values for that individual subject. The probability of receiving obesity and/or nutritional counseling, μijkt = E(Yijkt)= Pr[Yijk = 1], can be described by equation b  are subject-specific regression parameters, with β0ijk being the log odds of receiving obesity and/or nutritional counseling at t=−4, and β1ijk and β2ijk being the slopes  for the pre- and postperiods, respectively.In the multilevel modeling, the first-level unit is the repeated measurement  for the individual subject (pre- and postpolicy); the second-level unit is the individual subject; the third-level unit is the health system, provider, or clinic within the health system (cluster); and the fourth-level unit is the state. For example, let Yuation b , a segmemijk is modeled by equation b , we define the expected value μijkt=E(Yijkt) and apply a Poisson regression model based on the natural log link function. The log expected number of clinical visits, log(μijkt) can be modeled with the aforementioned segmented mixed-effects model. The use of an offset term in the models yields the estimates of the rate of clinical visits rather than the mean number of visits. The fixed-effect parameters, β1 and β2, represent the effects of exposure variables on the annual changes in log of incidence rates for the pre- and postperiods, respectively. For a continuous outcome Yijkt, we will model the mean, μijkt=E(Yijkt), with the mixed-effects model, and the parameters β1 and β2 indicate the effects of exposure variables on the annual changes in the outcomes for the pre- and postperiods, respectively. Besides mixed-effects models, we will also consider marginal models based on generalized estimating equation approach. Although mixed-effects models in general yield subject-specific effects except for the continuous outcomes, marginal models yield population-level effects. All final statistical models will be assessed with regard to the goodness-of-fit and the appropriateness of model assumptions.Similarly, for a count outcome YFor Aim 2, we will compare patient weight loss and diabetes-related outcomes among those who receive obesity IBT to those who do not, following implementation of preventive service coverage. We will also investigate obesity counseling as a continuous variable to examine impact of intensity (defined as the number of sessions) on outcomes, including weight loss. The outcome data collected after the broader coverage change will be used for the analyses in Aim 2. To compare the trend of change in each outcome between 2 groups, we will use the mixed-effects models as described above. The indicator of receiving obesity IBT, time, and their interaction will be the primary variables of interest in the model. In addition, patient and practice characteristics will also be included as covariates to control for their effects on the outcomes. To incorporate different starting dates of IBT and multiple IBT over different years, we will use the time-varying indicator of receiving IBT in the models. For subjects who receive IBT, we will also examine how the intensity of IBT (number of visits) is associated with changes in the outcomes. The number of screening and counseling will be used as a predictor in the mixed-effects models. Patient and practice characteristics can be adjusted in the regression model to reduce the selection bias of receiving IBT. The propensity score matching method has also been widely used to balance the characteristics of those who receive IBT with those who do not. We will consider demographics, insurance coverage, access to IBT prescription, medical comorbidities, and information on use of health care services to calculate the propensity scores. In addition, we will consider health behaviors, which are available for analysis from some institutions, and include validated standardized questionnaires assessing nutritional intake , physical activity, and sleep. An initial step within this project is to inventory the availability of PROs across institutions, and therefore, limited details are available at this time. A subject with IBT will be matched with a subject without IBT based on age, gender, enrollment window, and propensity of receiving IBT. Then mixed-effects models can be used to compare the patterns of changes in the outcomes of interest between 2 groups. Statistical software SAS 9.4 and R environment will be used to implement the proposed analyses.Owing to the heterogeneity of the population and a dynamic cohort in our study, we will investigate subgroup analyses to assess how the policy impact varies across different subgroups. Following the general modeling approaches as described above, we will examine the benefits of policy changes for different subgroups including (1) patients with insurance throughout the study period, (2) patients who obtained insurance after the policy changes, (3) patients without insurance throughout the study period, (4) patients newly enrolled in the system after policy changes, and (5) other subgroups of interest according to gender, age , race-ethnicity, and rural status. Meta-analysis has been a powerful approach to combining the effects of interest across different studies, different populations, and different subgroups ,30. We wIn the modeling framework above, we adjust for subject-level and cluster-level differences by including the exposure variables at different levels as covariates in the models. We will also consider a secondary analysis with a propensity score–matching approach to adjust for these differences ,32. A wiThe primary analysis of our study focuses on the individual-level outcomes. The statistical models yield the estimate of average change at the individual level post policy implementation. Given the information in the EHR data, we can also aggregate the diabetes outcomes at the community level and clinic level. For example, the proportion of patients with controlled diabetes can be obtained for each clinic and used as the outcome variable in the statistical modeling. The proposed mixed-effects modeling framework is still applicable in this case. The statistical analyses can be performed in a similar fashion to that for the individual-level outcomes.For example, our statistical analysis plan can be easily modified to compare the differences in weight loss and diabetes outcomes  between rural and urban areas. Although our main analysis is on individual-level outcomes, aggregated outcomes at the community or county level can also be extracted from the EHR data. For example, the proportions of patients with controlled diabetes in each county at each year can be obtained and used as the outcome variable after arcsine-square root transformation in the statistical modeling. We can evaluate the rural/urban effects on the pattern of changes in diabetes outcomes over years by including county-level characteristics such as rural versus urban in the mixed-effects models as fixed effects. The time origin in the analysis will be the beginning of the study period rather than the time when insurance policy changes occurred. The counties sharing similar characteristics  will be considered as a cluster, and the clustering effect will be accounted for in the mixed-effects model analysis by including cluster-level random effects. Instead of using segmented regression models to evaluate the trend in diabetes outcomes before and after the policy change, we will consider linear or nonlinear trends in the diabetes outcomes and allow rural and urban counties to have different patterns of changes in the models.Given that the study investigates a natural experiment, there is no primary data collection planned. However, there remains a risk of missing data. It is anticipated that the EHR will have incomplete data on outcomes of interest, which will be handled statistically as described below. Furthermore, the availability of claims data will assist in improving rates of missingness. Finally, we expect most missing data will be noninformative, that is, because of patients moving away from the health care institution. We will use validated statistical methods to handle missing data. These include the likelihood-based mixed-effects models to handle missing outcome data and multiple imputation method for missing covariates. The assumptions about missing data will be assessed based on the documented missing reasons and statistically as well. As participants are not recruited to this study, there will be no dropout to account for in the study design. However, given the prospective study design, there remains a risk for missing data. A consort-type diagram will be created to document each step to fully account for and justify patients who might be excluded. The missing data pattern will be summarized for primary outcomes. Baseline characteristics will be compared between those with missing outcome data and those without. A sensitivity analysis based on different assumptions of missing data mechanisms will be performed to evaluate the robustness of findings to the missing data.Owing to the very large sample sizes that are anticipated for the research studies , there is tremendous statistical power to detect very small effect sizes for individual-level exposure variables. Therefore, the clinical investigators on this project will need to examine each statistically significant result and determine whether it is also clinically significant. Furthermore, such large sample sizes ensure the robust estimation results from the proposed multilevel statistical modeling, which involves a large number of regression coefficient and covariance parameters. The major benefit of the large sample size for each research study is that it provides sufficient statistical power for investigating effects of interest within subgroups that might be constructed according to age, race-ethnicity, and cohort decompositions.Our PCORI-funded study is underway. To date, we have obtained our second data extraction from the PaTH CDRN and are performing data editing and cleaning. Next steps include analysis of early policy change .The overarching goal of this research is to understand the comparative effectiveness of obesity counseling as covered by CMS and other insurers in improving weight loss for adults either with or at increased risk of type 2 diabetes. As patients who are overweight are at highest risk for diabetes, improved weight management services could prevent diabetes and its negative health outcomes. Comparing weight and diabetes outcomes in 3 states using EHRs and claims data before and after this policy was implemented using the PaTH Network will allow important insight into policy effectiveness.Through the PaTH network, we have access to EHRs for patients who have been seen at Penn State Hershey Medical Center, University of Pittsburgh Medical Center, Johns Hopkins University, and Temple University Health System and, beginning in Fall 2015, the University of Utah and Geisinger Health System. Although this a uniquely large integrated research network, it only includes patients who seek care at one of these large health systems or affiliates and does not include those who preferentially seek care outside of large health systems or do not seek care at all. We address this limitation, in part, by supplementing our health record data with claims data where available. We will enrich the PaTH data with the UPMC Health Plan, Temple Health Plan, Johns Hopkins Health System, Geisinger Health Plan, and University of Utah Healthcare claims data to ensure capture of outcomes data that occur outside of the PaTH health systems.Our plans for data integration currently do not consider information extracted from images, videos, and free text, which can be important in some settings. However, our proposed design of the data infrastructure can be extended to incorporate such data in the future by leveraging state-of-the-art image analysis, video analysis, and natural language processing.The possibilities of residual confounding cannot be ruled out because of unmeasured or unavailable factors. For example, no detailed data on individual behavioral risk factors  are consistently available. Changes in individual behaviors will have large impacts on individual diabetes control. Similarly, data on built environment  are lacking. Finally, BMI and blood pressure are measured based on clinical practice not research protocol. They are subject to misclassification/measurement errors. Caution will, therefore, be exercised in interpreting our results.


Background: The sexual and reproductive health of African American women has been compromised due to multiple experiences of racism, including discriminatory healthcare practices from slavery through the post-Civil Rights era. However, studies rarely consider how the historical underpinnings of racism negatively influence the present-day health outcomes of African American women. Although some improvements to ensure equitable healthcare have been made, these historical influences provide an unexplored context for illuminating present-day epidemiology of sexual and reproductive health disparities among African American women.Methods: To account for the unique healthcare experiences influenced by racism, including healthcare provision, we searched online databases for peer-reviewed sources and books published in English only. We explored the link between historical and current experiences of racism and sexual and reproductive health outcomes.Results: The legacy of medical experimentation and inadequate healthcare coupled with social determinants has exacerbated African American women's complex relationship with healthcare systems. The social determinants of health associated with institutionalized and interpersonal racism, including poverty, unemployment, and residential segregation, may make African American women more vulnerable to disparate sexual and reproductive health outcomes.Conclusions: The development of innovative models and strategies to improve the health of African American women may be informed by an understanding of the historical and enduring legacy of racism in the United States. Addressing sexual and reproductive health through a historical lens and ensuring the implementation of culturally appropriate programs, research, and treatment efforts will likely move public health toward achieving health equity. Furthermore, it is necessary to develop interventions that address the intersection of the social determinants of health that contribute to sexual and reproductive health inequities. What happened on that auction block centuries ago is still unfinished business for African American women today.—Dr. Gail E. 1Wyatt2–6 According to the Centers for Disease Control and Prevention (CDC), African American women experience a high burden of maternal mortality, infant mortality, and sexually transmitted infections (STI), including HIV.4–9 Furthermore, racism is a fundamental determinant of health status because it contributes to social inequalities  that shape health behaviors, access to healthcare, and interactions with medical professionals.11Racism in the United States is pervasive and is a major contributor to sexual and reproductive health disparities of African American women. The historical narrative about racial inferiority has exacerbated discriminatory healthcare practices, in turn negatively affecting the quality and types of healthcare provided to African American women.13 For this reason, a historical analysis might shed light on how current sexual and reproductive health outcomes for African American women are shaped by racism and inform public health interventions to improve outcomes and promote health equity.Although legalized slavery, the most salient manifestation of race-based mistreatment for African Americans, ended in 1865, racism persists in institutions , and attitudes that marginalize African American women.First, we highlight a combination of significant historical events throughout four key eras that play a role in current health outcomes, including slavery, Black Codes/Jim Crow, Civil Rights, and post-Civil Rights (present day). The authors posit that a combination of these race-based events across eras impacts the current reproductive and sexual health status of African American women. We searched online databases  for peer-reviewed sources and books published in English only. To account for the unique healthcare experiences influenced by racism, including healthcare provision and research, our search was limited to the United States only. Second, we describe contemporary sexual and reproductive health outcomes. Third, we explore the link between these historical experiences and current sexual and reproductive health outcomes. Finally, we discuss the potential benefit for public health interventions that acknowledge the historical and current health status and healthcare experiences of African American women, and interventions that promote health equity.We argue that a careful examination of historical factors is essential to effectively address the current healthcare needs of African American women especially as they relate to chronic stress and impacts on health outcomes across a variety of conditions potentially rooted in racism, including STI  and pregnancy-related morbidity and mortality. If past influences that have potentially shaped current outcomes are not taken into consideration, then public health efforts may neglect the impact of larger, contextual factors that affect health and contribute to inequities. Given the nature of this article, our review was considered exempt by the institutional review board and not required.1415–19 Some sources estimate that 58% of all enslaved women aged 15–30 years were sexually assaulted by slave owners and other white men.20 Due to laws defining them as property, enslaved women had no legal protection from sexual assault by white men.19Race-based mistreatment that occurred during the 246-year enslavement (1619–1865) of Africans and their descendants involved many sexual and reproductive acts of violence against both enslaved African American women and their sexual partners. Enslaved women often experienced legalized sexual and reproductive exploitation.21 In addition to disrupting relationships between enslaved women and their male partners, such occurrences restricted their opportunities to reproduce with a partner of their choosing.Acts of sexual violence against African American men could also affect enslaved women. Because enslaved men were viewed as social threats, and had few criminal justice protections, mobs of white men publicly lynched and/or castrated them in efforts to assert their dominance over them.22 Because enslaved women and girls were denied reproductive rights to control their own sexuality, they were unable to determine with whom they engaged in sexual relationships.24 Women who were considered “strong” were sold as breeders and routinely sexually assaulted to birth more children into slavery.23 Some enslaved females attempted to avoid being sexually exploited for these purposes and aborted their pregnancies as an act of resistance.26Consequently, childbearing during slavery was often intrinsically related to an economic system that benefitted white slave owners more so than a matter of personal freedom.27 James Marion Sims, the “Father of Modern Gynecology” and former president of the American Medical Association, performed many reproductive experimental surgeries without anesthesia to treat various childbirth illnesses among enslaved African American women.28 Many physicians used enslaved women in other experimental reproductive surgeries, such as cesarean sections and ovariotomy, to perfect procedures that would later be used for all women.29Enslaved women had limited access to healthcare, and the available “care” often involved medical experimentation.31 Although the Emancipation Proclamation granted freedom to the enslaved, the Black Codes restricted African Americans' labor advancement and migration, and Jim Crow laws restricted their overall civil rights.33 In some states, laws regarding rape protected only white women although some sources contend that African American women were more often victimized by this crime.21 In the absence of laws to protect African American women, rape served to control them, which likely affected their self-esteem and self-worth.34 Lynching was also used to punish both women and men who sought racial equality through civil rights.36 Many African American women also endured public gang rape and genital mutilation before being lynched.37–40Adverse sexual and reproductive health and healthcare experiences continued for African American women throughout the Black Codes/Jim Crow era. .24,30,3141–43 These programs coerced African American women to undergo sterilizations without their full knowledge that these procedures were not reversible.44 Although the eugenic thesis was refuted by scientists, several state-supported eugenic sterilization programs remained active.46 Thirty states supported formal eugenic programs that enforced compulsory sterilization from the early 1900s to the 1970s.47Furthermore, eugenic programs emerged to control the size of the black population.48 Beginning in 1932, the U.S. Public Health Service recruited poor and uneducated African American men in Alabama to determine the effect of untreated syphilis. Although treatment became available, the men were misled, denied treatment, and not informed of the study findings until 1972.49 In addition to study subjects experiencing syphilis-related morbidity and mortality, some of their wives acquired syphilis, and some of their children suffered complications from congenital syphilis.50The longest running medical experiment in the United States was the “Tuskegee Syphilis Study of Untreated Syphilis in the Male Negro.”30 Both the Civil Rights and post-Civil Rights eras have been characterized by overt and subtle forms of racism in the U.S. healthcare system. Legal segregation in healthcare continued through the mid-1960s until Congress passed the Civil Rights Act of 1964.51 Shortly thereafter, the Medicaid program forced many hospitals to adhere to the Civil Rights Act and to hire doctors who would treat patients of all races, although unequally.51 Federal funding supported coerced sterilization, and some African American women were threatened with denial of medical care or termination of welfare benefits if they did not undergo sterilization.52 Moreover, in 1972, ∼20 women, mostly young, African American and poor, suffered unintentional abortions as a result of the super coil. The super coil was a device that caused uncontrollable bleeding and, in some cases, led to hysterectomies, abdominal pain, and anemia.53Inhumane healthcare provided during the Black Codes/Jim Crow era was replaced with limited, poor-quality, or no health services for many African Americans, particularly those living in poverty during the Civil Rights era.54 This exploitation of African American women became routine and perpetuated the eugenic movement during this time period.47 Although long-acting reversible contraceptives  are now recommended as the most effective contraception option for many women, including adolescents regardless of race/ethnicity, debates about reproductive justice and the use of these contraceptives among African American women persist.56 African American women also report experiences of racial discrimination when seeking family planning services, and are more likely than white women to be advised to restrict childbearing, which might engender feelings of mistrust.57–60 Likewise, black women of low socioeconomic status (SES) were more likely than white women of low SES to be recommended by their healthcare provider for intrauterine contraception.61In addition, many poor African American women underwent unnecessary hysterectomies as practice for medical students at select teaching hospitals.Taken together, these historical experiences of sexual violence, experimentation, and healthcare disenfranchisement support the intergenerational transmission of poor sexual and reproductive health outcomes among African American women in the United States.62 In 2012, compared with white women, African American women were more likely to be diagnosed with primary or secondary syphilis, gonorrhea, or chlamydia .62 African American women were also two to three times as likely as white women to have pelvic inflammatory disease.62 If left undiagnosed or untreated, these conditions can lead to pregnancy complications and infertility.62 In addition, CDC reported that African American women had an HIV incidence rate that was 20.1 times greater than that of white women in 2010.63 African American women are also more likely to have delayed HIV treatment compared with women of other races.64The CDC reports that African American women experience a high burden of STIs, including HIV.66 In 2013, CDC reported that the preterm rate for black infants was ∼60% higher than for white infants (17.1% and 10.8% respectively).67 In addition, the low birth weight rate for African Americans was 10.13% and 6.97% for whites.68 During 1998–2005, African American women had a three to four times higher risk of pregnancy-related death at every age interval compared with women of other races.69 African American women also have increased risk for pregnancy-related hypertension and chronic hypertension.70 Importantly, this increased risk of mortality suggests that African American women are less likely to receive quality prenatal care and other preventive services .71Pregnancy-related morbidity and mortality also disproportionately affect African American women.72–74 Kjerulff et al. also found that black women were more likely than other women to have longer hospital stays and three times the inhospital mortalities, as well as other complications .74African American women undergo more hysterectomies due to conditions  that are potentially treatable by less aggressive procedures than other women.75 First, racism is a social factor embedded within the historical legacy of the United States.76 The effects of racism and unconscious bias are difficult for African American women to avoid, because race and ultimately racism are based on physical characteristics . Whether racism is internalized, experienced within institutions , or through societal assumptions , it increases the risks of adverse sexual and reproductive health outcomes for this population.77 Second, there may be a reporting bias related to African Americans, because African Americans disproportionately access medical care in publicly funded clinics due to socioeconomic disparities. These clinics typically have more stringent reporting requirements.75 Finally, differences in sexual and reproductive health may be exaggerated as African Americans may be more likely to use service providers who use different patterns of testing and reporting.51Researchers are urged to examine any biases they may have about African American women before interpreting data about their sexual and reproductive health. Although focused on African American men, Leigh and Huff outline important considerations regarding reporting bias that are pertinent for African American women.51 In light of the nuances associated with the collection, analysis, interpretation, and reporting of health data for African American women, some researchers argue that there is an intersection between the health and healthcare experiences of African Americans and the social conditions  they live in, helping shape patterns of documented health inequities, including sexual and reproductive health inequities.78–81For example, healthcare systems that emphasize teaching and research related to patient care may have a higher proportion of African American patients, which can lead to the identification of health problems believed to be more common among African Americans .The historical context of racism continues to shape the sexual and reproductive health of African American women. 82 Given the well-established link between racism, poverty, and health, the socioeconomic conditions associated with institutionalized and interpersonal racism make African American women more vulnerable to sexual and reproductive health problems.81 For example, African American women are more likely than other women to live in neighborhoods in which the HIV prevalence is relatively high,83 increasing the likelihood that they will encounter HIV-infected partners.84Transgenerational poverty originated in slavery and continues to disproportionately affect African Americans.14 In later periods, most African American women had few opportunities for formal education, and black schools were given lower quality educational materials than schools educating white students. Low educational attainment may be associated with multiple sexual and reproductive health issues.85–88 Studies show that limited education is associated with an increased likelihood of poor HIV treatment adherence, preterm births and infant mortality, and undergoing hysterectomy.89–91 Furthermore, the frequency of hysterectomies among African American women with poor education has amplified concerns about the frequency with which this procedure is used.92Limited education may contribute to health issues experienced by African American women. During slavery, laws prohibited enslaved women from receiving a formal education.94 Ultimately, residential segregation by race provides a foundation to maintain other forms of institutional and societal segregation.80 Importantly, it plays a central role in reproductive and sexual health by limiting access to quality health services.96 For example, African Americans living in predominantly black communities are considerably less likely to receive early HIV testing and treatment than whites.97 In addition, residential segregation is linked with adverse reproductive health outcomes, which are rooted in social inequalities.98Race-based residential segregation continues to differentially structure access to quality educational opportunities in many predominantly African American neighborhoods.99 Low-paying jobs with few opportunities for advancement have been found to influence decision-making around sexual behavior. Poverty is associated with sexual risk decisions in efforts to acquire basic needs, such as food and shelter.100–103Some researchers have discussed structural inequalities in employment opportunities in relation to sexual and reproductive health outcomes. Historically , African American women were not compensated for the work they performed. As slavery came to an end, they were not provided access to resources or immediate employment opportunities to sustain themselves and their families.105 Repeated assaults have been linked to trauma, which can increase the likelihood that women will experience sexual health problems .106–108 African American women living in poverty have an increased likelihood of enduring childhood sexual abuse.109 Furthermore, reproductive coercion diminishes self-esteem, resulting in feelings of inferiority, high levels of stress, and vulnerability to sexual risk behaviors.110A personal history of sexual violence may also influence the overall health of African American women.111–113 Negative sexual stereotypes of African American women began as a means to justify their enslavement and subsequent sexual violence, including rape and sexual assault.114 Negative sexual imagery of African American women continued throughout the four time periods.115–117 Peterson et al. recently found that African American women who reported viewing more sexual stereotypes in rap videos engaged in more sexual risk behaviors than females who did not. Some data suggest that these negative stereotypes help to further racist sentiments because they can be internalized by African Americans.118 Men of color who perpetuate these images either intentionally or unintentionally have themselves been victims of persistent negative imagery throughout history that often translates into internalized racism.119Present-day stereotypes of African American women as “hypersexual,” “aggressive,” and “angry” were born of representations that emerged in the past.120 Many African American women lack access to preventive reproductive screenings, including mammograms and Pap smears.121 Some data suggest that factors contributing to disparities in preterm birth risk or infant mortality include differences in prenatal care, nutrition, and SES as well as experiences of racism-related stress.121–125Because many African American women lack access to quality healthcare, they have an increased likelihood of late-stage diagnoses of HIV and other medical conditions that increase the risk for early mortality.126–129 Low birth weight among contemporary African Americans has been proposed to be a result of differences in current exposures to social and environmental factors that affect fetal development and from conditions experienced during slavery. Enslaved women endured poor health across their life span due to insufficient diet, extreme physical work, and disease.131 Jasienska highlights the concept of “fetal programming,” the idea that the physiological development of the fetus can be affected by environmental events, which may endure into adulthood, thereby affecting future generations. Although slavery was abolished in the United States in 1865, Jasienska argues that there has not been enough time to eliminate the physical effects of slavery, which contributes to the disproportionately high levels of low birth weight in African American infants born in the 21st century.130 Although there are multiple risk factors for preterm birth and low birth weight, long-term, multigenerational exposure to inadequate nutrition as evidenced during slavery should be considered when addressing low birth rate.130Some suggest the origins of adult health begin with intrauterine and early postnatal experiences or as a result of “weathering,” through which repeated experiences with discrimination result in physical health deterioration in early adulthood.133 Some researchers argue that the study of African Americans is incomplete if cultural mistrust is not taken into consideration.134 Research suggests that African Americans are reluctant to engage in clinical trials and may refuse treatment as a result of their own race-related experiences.135–137 The lingering effects of the “Tuskegee Study of Untreated Syphilis” on African American women support the need for present-day medical schools to adopt culturally and linguistically appropriate curricula that consider how this study continues to impact the reproductive health and related behaviors of African American women.50Additionally, the legacy of medical experimentation and inadequate healthcare has exacerbated African American women's complex relationship with healthcare systems, past and present, and laid a foundation of mistrust of the medical establishment.138 For example, programs designed to address individual-level , interpersonal-level , community-level , and importantly system-level factors  might facilitate long-term, sustainable improvements in health for the larger population of African American women.139The historical and contemporary racism-related health and healthcare experiences of African American women to date highlight the need to develop new models for health promotion. Socioecological models are useful for understanding the context of both race-specific and gender-specific issues relative to sexual and reproductive healthcare experiences.Consistent with strategies outlined in the Department of Health and Human Services Action Plan to Reduce Racial and Ethnic Health Disparities and Healthy People 2020, we highlight the following strategies as first steps in reversing historical patterns of poor sexual and reproductive health outcomes among African American women: (1) ensure strategies focus on culturally and contextually appropriate research and prevention, (2) ensure equal access to effective sexual health information and quality healthcare services, (3) support quality education and training for public health professionals, and (4) support policies that promote sexual and reproductive health equity.140 Similarly, it is important to closely examine macrolevel factors that impact health outcomes, such as the socioeconomic, cultural, and dimensions of the community/environmental context. This approach further illuminates the impact of social determinants of health on African American women and expands opportunities and strategies for primary prevention.To ensure strategies incorporate culturally and contextually appropriate research and prevention, an understanding of cultural theories and perspectives is central to prevention efforts. This approach enables the development of programmatic systems and policy actions that are relevant and appropriate for the intended audience. African American women must be involved in the design, implementation, and evaluation of all aspects of the research and implementation of agreed-upon programs. Such an approach is modeled by community-based participatory research.121 The ACA was designed to expand access for preventive screening services for women, increases maternity coverage, and increases funding to community health centers, which are generally located in disenfranchised communities serving large numbers of African Americans. Moreover, to effectively and efficiently address those underlying causes of adverse sexual and reproductive health outcomes for African American women, public health agencies are encouraged to broaden their partnerships to include nontraditional partners  who might have more direct influence over some of the social determinants affecting the health status of African American women.Addressing equal access to effective sexual and reproductive health information and quality healthcare services that stem from institutional racism and discrimination entails reducing barriers to access to quality care, increasing access to health insurance, and ensuring the provision of culturally appropriate and specialized care. The Affordable Care Act (ACA) could improve African American women's access to quality, affordable health coverage and help reduce inequities.142 Patient/provider relationships are also a factor in achieving patient satisfaction and medication adherence.144 Effective patient/provider communication is paramount to delivering high-quality health services, and patients are more apt to share information helpful to their provider when they feel valued.145Addressing the shortage of African American public health professionals and supporting quality education and training are significant in improving the provision of high-quality healthcare. Their representation in the workforce has both educational service and relationship benefits for patients and providers. In addition, ensuring their presence within the healthcare profession serves as an opportunity to address the discriminatory practices that may have prevented their entry into healthcare professions.145In addition, public health researchers should be familiar with the histories and lived experience of their African American patients to appropriately design collaborative prevention efforts that ameliorate racism and its health-related impacts among African American women. Learning to be culturally competent and sensitive is essential for providers and public health practitioners providing services to populations that have traditionally been marginalized and medically underserved.147Moreover, policies that promote health equity can be powerful tools for social change. Enforcing policies that promote racial and gender equality, quality education for all students, equal access to job training and employment opportunities, and equal access to quality health care for all could enhance population health.The field of public health will be more successful addressing the root causes of health inequities when strategies are informed by rigorous social and epidemiological research. Properly framed and executed, such research can support the development of approaches that take into account the unique experiences of African American women. This overview of historical health-related experiences of African American women is a first step in describing how the historical impact of racism links past events to present sexual and reproductive health outcomes. Addressing sexual and reproductive health through a historical lens and ensuring the implementation of culturally appropriate programs, research, and treatment efforts will likely move public health toward achieving health equity, which will benefit the health of African American women.The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.