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The growing utilization of massive open online courses (MOOCs) is opening opportunities for students worldwide, but the completion rate for MOOCs is low (Liyanagunawardena, Adams, & Williams, 2013). Partners In Health (PIH) implemented a "flipped" MOOC in Rwanda that incorporated in-class sessions to facilitate participant completion. In October 2013, PIH invited its employees, as well as those at the Ministry of Health, to participate in an online MOOC. Each site had at least one volunteer facilitator who accompanied participants throughout the course by providing course materials and facilitating the understanding of the online material during the weekly class sessions. Following the conclusion of the course, all participants were asked to complete an online survey. A total of 38 out of 62 registered participants completed the survey and of these 38 participants, 20 (52.6%) successfully finished the course. The number of in-person sessions attended was significantly associated with course completion (p < 0.05), and 85% who successfully completed the course attended at least three of seven sessions. Sixteen (80%) participants believed that the completion of this course would help them with career advancement. Half of the participants (19 of 38, 50%) were employed with a position related to research. Other job titles included the following: nurses (4 of 38, 10.5%), a pharmacist (1 of 38, 2.6%), a clinical psychologist (1 of 38, 2.6%), a dentist (1 of 38, 2.6%), and others (10 of 38, 26.3%). The job title was not significantly related to course completion. Our experience, with a completion rate of over 50%, yields several lessons for incorporating MOOCs into capacity-building programs to leverage the potential of online learning in resource-limited areas.

Abstract Background With increasing rates of chronic disease associated with lifestyle behavioural risk factors, there is urgent need for intervention strategies in primary health care. Currently there is a gap in the knowledge of factors that influence the delivery of preventive strategies by General Practitioners (GPs) around interventions for smoking, nutrition, alcohol consumption and physical activity (SNAP). This qualitative study explores the delivery of lifestyle behavioural risk factor screening and management by GPs within a 45–49 year old health check consultation. The aims of this research are to identify the influences affecting GPs' choosing to screen and choosing to manage SNAP lifestyle risk factors, as well as identify influences on screening and management when multiple SNAP factors exist. Methods A total of 29 audio-taped interviews were conducted with 15 GPs and one practice nurse over two stages. Transcripts from the interviews were thematically analysed, and a model of influencing factors on preventive care behaviour was developed using the Theory of Planned Behaviour as a structural framework. Results GPs felt that assessing smoking status was straightforward, however some found assessing alcohol intake only possible during a formal health check. Diet and physical activity were often inferred from appearance, only being assessed if the patient was overweight. The frequency and thoroughness of assessment were influenced by the GPs' personal interests and perceived congruence with their role, the level of risk to the patient, the capacity of the practice and availability of time. All GPs considered advising and educating patients part of their professional responsibility. However their attempts to motivate patients were influenced by perceptions of their own effectiveness, with smoking causing the most frustration. Active follow-up and referral of patients appeared to depend on the GPs' orientation to preventive care, the patient's motivation, and cost and accessibility of services to patients. Conclusion General practitioner attitudes, normative influences from both patients and the profession, and perceived external control factors (time, cost, availability and practice capacity) all influence management of behavioural risk factors. Provider education, community awareness raising, support and capacity building may improve the uptake of lifestyle modification interventions.

Abstract Background To study health-related quality of life (HRQOL) in a large sample of Australian chronically-ill patients and investigate the impact of characteristics of patients and their general practices on their HRQOL and to assess the construct validity of SF-12 in Australia. Methods Cross sectional study with 96 general practices and 7606 chronically-ill patients aged 18 years or more using standard SF-12 version 2. Factor analysis was used to confirm the hypothesized component structure of the SF-12 items. SF-12 physical component score (PCS-12) and mental component score (MCS-12) were derived using the standard US algorithm. Multilevel regression analysis (patients at level 1 and practices at level 2) was applied to relate PCS-12 and MCS-12 to patient and practice characteristics. Results There were significant associations between lower PCS-12 or MCS-12 score and poorer general health (10.8 (regression coefficient) lower for PCS-12 and 7.3 lower for MCS-12), low socio-economic status (5.1 lower PCS-12 and 2.9 lower MCS-12 for unemployed, 0.8 lower PCS-12 and 1.7 lower MCS-12 for non-owner-occupiers, 1.0 lower PCS-12 for less well-educated) and having two or more chronic conditions (up to 2.7 lower PCS-12 and up to 1.5 lower MCS-12 than those having a single disease). Younger age was associated with lower MCS-12 (2.2 and 6.0 lower than middle age and older age respectively) but higher PCS-12 (4.7 and 7.6 higher than middle age and older age respectively). Satisfaction with quality of care (regression coefficient = 1.2) and patients who were married or cohabiting (regression coefficient = 0.6) was positively associated with MCS-12. Patients born in non-English-speaking countries were more likely to have a lower MCS-12 (1.5 lower) than those born in Australia. Employment had a stronger association with the quality of life of males than that of females. Those attending smaller practices had lower PCS-12 (1.0 lower) and MCS-12 (0.6 lower) than those attending larger practices. At the patient level (level 1) 42% and 21% of the variance respectively for PCS-12 and MCS-12 were explained by the patients and practice characteristics. At the practice level (level 2), 73% and 49% of the variance respectively for PCS-12 and MCS-12 were explained by patients and practice characteristics. Conclusion The strong association between patient characteristics such as socio-economic status, age, and ethnicity and SF-12 physical and mental component summary scores underlines the importance of considering these factors in the management of chronically-ill patients in general practice. The SF-12 appears to be a valid measure for assessing HRQOL of Australian chronically-ill patients.

Abstract Background Primary health care (PHC) clinicians have an important role to play in addressing lifestyle risk factors for chronic diseases. However they intervene only rarely, despite the opportunities that arise within their routine clinical practice. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about this for PHC clinicians working outside general practice. The aim of this study was to explore the beliefs and attitudes of PHC clinicians about incorporating lifestyle risk factor management into their routine care and to examine whether these varied according to their self reported level of risk factor management. Methods A cross sectional survey was undertaken with PHC clinicians (n = 59) in three community health teams. Clinicians' beliefs and attitudes were also explored through qualitative interviews with a purposeful sample of 22 clinicians from the teams. Mixed methods analysis was used to compare beliefs and attitudes for those with high and low levels of self reported risk factor management. Results Role congruence, perceived client acceptability, beliefs about capabilities, perceived effectiveness and clinicians' own lifestyle were key themes related to risk factor management practices. Those reporting high levels of risk factor screening and intervention had different beliefs and attitudes to those PHC clinicians who reported lower levels. Conclusion PHC clinicians' level of involvement in risk factor management reflects their beliefs and attitudes about it. This provides insights into ways of intervening to improve the integration of behavioural risk factor management into routine practice.

Abstract Background This article describes the development and psychometric evaluation of an interview instrument to assess provider-reported quality of general practice care for patients with diabetes, cardiovascular disease and asthma – the Australian General Practice Clinical Care Interview (GPCCI). Methods We administered the GPCCI to 28 general practitioners (family physicians) in 10 general practices. We conducted an item analysis and assessed the internal consistency of the instrument. We next assessed the quality of care recorded in the medical records of 462 of the general practitioners' patients with Type 2 diabetes, ischaemic heart disease/hypertension and/or moderate to severe asthma. This was then compared with results of the GPCCI for each general practice. Results Good internal consistency was found for the overall GPCCI (Cronbach's alpha = 0.75). As far as the separate sub-scales were concerned, diabetes had good internal consistency (0.76) but the internal consistency of the heart disease and asthma subscales was not strong (0.49 and 0.16 respectively). There was high inter-rater reliability of the adjusted scores of data extracted from patients' medical notes for each of the three conditions. Correlations of the overall GPCCI and patients' medical notes audit, combined across the three conditions and aggregated to practice level, showed that a strong relationship (r = 0.84, p = 0.003) existed between the two indices of clinical care. Conclusion This study suggests that the GPCCI has good internal consistency and concurrent validity with patients' medical records in Australian general practice and warrants further evaluation of its properties, validity and utility.

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Introduction: Although Rwanda’s health system underwent major reforms and improvements after the 1994 Genocide, the health system and population health in the southeast lagged behind other areas. In 2005, Partners In Health and the Rwandan Ministry of Health began a health system strengthening intervention in this region. We evaluate potential impacts of the intervention on maternal and child health indicators. Methods: Combining results from the 2005 and 2010 Demographic and Health Surveys with those from a supplemental 2010 survey, we compared changes in health system output indicators and population health outcomes between 2005 and 2010 as reported by women living in the intervention area with those reported by the pooled population of women from all other rural areas of the country, controlling for potential confounding by economic and demographic variables. Results: Overall health system coverage improved similarly in the comparison groups between 2005 and 2010, with an indicator of composite coverage of child health interventions increasing from 57.9% to 75.0% in the intervention area and from 58.7% to 73.8% in the other rural areas. Under-five mortality declined by an annual rate of 12.8% in the intervention area, from 229.8 to 83.2 deaths per 1000 live births, and by 8.9% in other rural areas, from 157.7 to 75.8 deaths per 1000 live births. Improvements were most marked among the poorest households. Conclusion: We observed dramatic improvements in population health outcomes including under-five mortality between 2005 and 2010 in rural Rwanda generally and in the intervention area specifically.

Partners In Health (PIH) implemented an electronic medical record (EMR) system in Rwanda in 2005 to support and improve HIV and TB patient care. The system holds detailed patient records, accessible to clinicians through printed reports or directly via a computer in the consultation rooms. Ongoing assessment of data quality and clinical data use has led multiple interventions to be put in place. One such evaluation cycle led to the implementation of a system which identified 15 previously undiagnosed pediatric patients with HIV. Another cycle led to an EMR intervention which helped to decrease the proportion of completed critical CD4 lab results that did not reach clinicians by 34.2% (p=.002). Additionally an automated data quality improvement system reduced known errors by 92% by providing local data officers a tool and training to allow them to easily access and correct data errors. Electronic systems can be used to support care in rural resource-poor settings, and frequent assessment of data quality and clinical use of data can be used to support that goal. [ABSTRACT FROM AUTHOR]

Objective and Background: We investigated the quality of primary care asthma management in a sample of Australian general practices. Methods: 247 general practitioners (GPs) from 97 practices completed a structured interview about management of asthma, diabetes and hypertension/heart disease. A further structured interview with the senior practice principal and practice manager was used to collect information about practice capacity for chronic disease management. Results: Just under half of GPs (47%) had access to an asthma register and the majority (76%) had access to spirometry in their practice. In terms of routine management of asthma, 12% of GPs reported using spirometry routinely, 13% routinely reviewed written asthma action plans, 27% routinely provided education about trigger factors, 30% routinely reviewed inhaler technique, 24% routinely assessed asthma severity, and 29% routinely assessed physical activity. Practice characteristics such as practice size (p=1.0) and locality (rural/metropolitan) (p=0.7) did not predict quality of asthma management nor did indicators of practice capacity including Business maturity, IT/IM maturity, Multidisciplinary teamwork, and Clinical linkages. Conclusion: Gaps remain in the provision of evidence-based care for patients with asthma in general practice. Markers of practice capacity measured here were not associated with guideline-based respiratory care within practices. [ABSTRACT FROM AUTHOR]

Few studies have explored how lifestyle counselling can be integrated into routine practice for primary health care (PHC) clinicians working outside general practice. This paper describes the feasibility of models of lifestyle counselling developed for PHC clinicians working in community health services and the congruence with routine practice. Action research methods were used to develop and implement models of lifestyle counselling in three community health teams.Following a six-month implementation period, semi-structured interviews were conducted with a purposeful sample of participants (n=30) to explore the appropriateness of implementing risk factor management models in practice. Models were considered appropriate if they fitted the clinician's philosophy of practice, were relevant to existing work tasks, could easily be integrated into workflow and were perceived as being acceptable to the client. The approach to service delivery and team priorities were also important in influencing which models suited particular teams. Models of lifestyle counselling for PHC clinicians outside general practice should be tailored to the clinicians' and teams' way of working and thus may need to be discipline-specific. Engaging PHC clinicians and teams is important in developing models that are acceptable and feasible in everyday practice. [ABSTRACT FROM AUTHOR]

Background: Health data can be useful for effective service delivery, decision making, and evaluating existing programs in order to maintain high quality of healthcare. Studies have shown variability in data quality from national health management information systems (HMISs) in sub-Saharan Africa which threatens utility of these data as a tool to improve health systems. The purpose of this study is to assess the quality of Rwanda's HMIS data over a 5-year period. Methods: The World Health Organization (WHO) data quality report card framework was used to assess the quality of HMIS data captured from 2008 to 2012 and is a census of all 495 publicly funded health facilities in Rwanda. Factors assessed included completeness and internal consistency of 10 indicators selected based on WHO recommendations and priority areas for the Rwanda national health sector. Completeness was measured as percentage of non-missing reports. Consistency was measured as the absence of extreme outliers, internal consistency between related indicators, and consistency of indicators over time. These assessments were done at the district and national level. Results: Nationally, the average monthly district reporting completeness rate was 98% across 10 key indicators from 2008 to 2012. Completeness of indicator data increased over time: 2008, 88%; 2009, 91%; 2010, 89%; 2011, 90%; and 2012, 95% (p<0.0001). Comparing 2011 and 2012 health events to the mean of the three preceding years, service output increased from 3% (2011) to 9% (2012). Eighty-three percent of districts reported ratios between related indicators (ANC/DTP1, DTP1/DTP3) consistent with HMIS national ratios. Conclusion and policy implications Our findings suggest that HMIS data quality in Rwanda has been improving over time. We recommend maintaining these assessments to identify remaining gaps in data quality and that results are shared publicly to support increased use of HMIS data.