Should I and Can I?: a mixed methods study of clinician beliefs and attitudes in the management of lifestyle risk factors in primary health care

BackgroundPrimary 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.MethodsA cross sectional survey was undertaken with PHC clinicians (n = 59) in three community health teams. Clinicians\u27 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.ResultsRole congruence, perceived client acceptability, beliefs about capabilities, perceived effectiveness and clinicians\u27 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.ConclusionPHC clinicians\u27 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

Toward utilization of data for program management and evaluation: quality assessment of five years of health management information system data in Rwanda

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

Attitudes, norms and controls influencing lifestyle risk factor management in general practice

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

Comprehensive and integrated district health systems strengthening: the Rwanda Population Health Implementation and Training (PHIT) Partnership

Background: Nationally, health in Rwanda has been improving since 2000, with considerable improvement since 2005. Despite improvements, rural areas continue to lag behind urban sectors with regard to key health outcomes. Partners In Health (PIH) has been supporting the Rwanda Ministry of Health (MOH) in two rural districts in Rwanda since 2005. Since 2009, the MOH and PIH have spearheaded a health systems strengthening (HSS) intervention in these districts as part of the Rwanda Population Health Implementation and Training (PHIT) Partnership. The partnership is guided by the belief that HSS interventions should be comprehensive, integrated, responsive to local conditions, and address health care access, cost, and quality. The PHIT Partnership represents a collaboration between the MOH and PIH, with support from the National University of Rwanda School of Public Health, the National Institute of Statistics, Harvard Medical School, and Brigham and Women’s Hospital. Description of intervention The PHIT Partnership’s health systems support aligns with the World Health Organization’s six health systems building blocks. HSS activities focus across all levels of the health system — community, health center, hospital, and district leadership — to improve health care access, quality, delivery, and health outcomes. Interventions are concentrated on three main areas: targeted support for health facilities, quality improvement initiatives, and a strengthened network of community health workers. Evaluation design The impact of activities will be assessed using population-level outcomes data collected through oversampling of the demographic and health survey (DHS) in the intervention districts. The overall impact evaluation is complemented by an analysis of trends in facility health care utilization. A comprehensive costing project captures the total expenditures and financial inputs of the health care system to determine the cost of systems improvement. Targeted evaluations and operational research pieces focus on specific programmatic components, supported by partnership-supported work to build in-country research capacity. Discussion Building on early successes, the work of the Rwanda PHIT Partnership approach to HSS has already seen noticeable increases in facility capacity and quality of care. The rigorous planned evaluation of the Partnership’s HSS activities will contribute to global knowledge about intervention methodology, cost, and population health impact

Bubble CPAP to support preterm infants in rural Rwanda: a retrospective cohort study

Background: Complications from premature birth contribute to 35 % of neonatal deaths globally; therefore, efforts to improve clinical outcomes of preterm (PT) infants are imperative. Bubble continuous positive airway pressure (bCPAP) is a low-cost, effective way to improve the respiratory status of preterm and very low birth weight (VLBW) infants. However, bCPAP remains largely inaccessible in resource-limited settings, and information on the scale-up of this technology in rural health facilities is limited. This paper describes health providers’ adherence to bCPAP protocols for PT/VLBW infants and clinical outcomes in rural Rwanda. Methods: This retrospective chart review included all newborns admitted to neonatal units in three rural hospitals in Rwanda between February 1st and October 31st, 2013. Analysis was restricted to PT/VLBW infants. bCPAP eligibility, identification of bCPAP eligibility and complications were assessed. Final outcome was assessed overall and by bCPAP initiation status. Results: There were 136 PT/VLBW infants. For the 135 whose bCPAP eligibility could be determined, 83 (61.5 %) were bCPAP-eligible. Of bCPAP-eligible infants, 49 (59.0 %) were correctly identified by health providers and 43 (51.8 %) were correctly initiated on bCPAP. For the 52 infants who were not bCPAP-eligible, 45 (86.5 %) were correctly identified as not bCPAP-eligible, and 46 (88.5 %) did not receive bCPAP. Overall, 90 (66.2 %) infants survived to discharge, 35 (25.7 %) died, 3 (2.2 %) were referred for tertiary care and 8 (5.9 %) had unknown outcomes. Among the bCPAP eligible infants, the survival rates were 41.8 % (18 of 43) for those in whom the procedure was initiated and 56.5 % (13 of 23) for those in whom it was not initiated. No complications of bCPAP were reported. Conclusion: While the use of bCPAP in this rural setting appears feasible, correct identification of eligible newborns was a challenge. Mentorship and refresher trainings may improve guideline adherence, particularly given high rates of staff turnover. Future research should explore implementation challenges and assess the impact of bCPAP on long-term outcomes

Quality of chronic disease care in general practice: the development and validation of a provider interview tool

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

Quality of life of Australian chronically-ill adults: patient and practice characteristics matter

BackgroundTo 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.MethodsCross 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.ResultsThere 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.ConclusionThe 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.Upali W. Jayasinghe, Judith Proudfoot, Christopher A. Barton, Cheryl Amoroso, Chris Holton, Gawaine Powell Davies, Justin Beilby and Mark F. Harri