Preventive evidence into practice (PEP) study: implementation of guidelines to prevent primary vascular disease in general practice protocol for a cluster randomised controlled trial
- Mark F Harris1Email author,
- Jane Lloyd1,
- John Litt2,
- Mieke van Driel3,
- Danielle Mazza4,
- Grant Russell4,
- Jane Smith5,
- Chris Del Mar5,
- Elizabeth Denney-Wilson6,
- Sharon Parker1,
- Yordanka Krastev7,
- Upali W Jayasinghe1,
- Richard Taylor8,
- Nick Zwar8,
- Jinty Wilson9,
- Helen Bolger-Harris10 and
- Justine Waters11
© Harris et al.; licensee BioMed Central Ltd. 2013
Received: 23 November 2012
Accepted: 11 January 2013
Published: 18 January 2013
There are significant gaps in the implementation and uptake of evidence-based guideline recommendations for cardiovascular disease (CVD) and diabetes in Australian general practice. This study protocol describes the methodology for a cluster randomised trial to evaluate the effectiveness of a model that aims to improve the implementation of these guidelines in Australian general practice developed by a collaboration between researchers, non-government organisations, and the profession.
We hypothesise that the intervention will alter the behaviour of clinicians and patients resulting in improvements of recording of lifestyle and physiological risk factors (by 20%) and increased adherence to guideline recommendations for: the management of CVD and diabetes risk factors (by 20%); and lifestyle and physiological risk factors of patients at risk (by 5%). Thirty-two general practices will be randomised in a 1:1 allocation to receive either the intervention or continue with usual care, after stratification by state. The intervention will be delivered through: small group education; audit of patient records to determine preventive care; and practice facilitation visits adapted to the needs of the practices. Outcome data will be extracted from electronic medical records and patient questionnaires, and qualitative evaluation from provider and patient interviews.
We plan to disseminate study findings widely and directly inform implementation strategies by governments, professional bodies, and non-government organisations including the partner organisations.
KeywordsPrimary care Family medicine Guidelines Preventive care Cardiovascular disease
Cardiovascular disease (CVD) represents a substantial and increasing portion of healthcare expenditure and practitioner workload. It is estimated that 9 in 10 adult Australians have at least one risk factor for CVD. Behavioural risk factors include smoking, nutrition, alcohol, physical activity, and being overweight or obese. The physiological risk factors include high blood pressure and dyslipidaemia.
Primary care providers are well placed to help reduce the incidence of CVD. General practitioners provide clinical services to approximately 88% of Australians each year and are in an ideal position to screen for risk factors and provide brief interventions including advice about behavioural risk factors as well as medications. However, there are numerous barriers to implementation at the patient, practitioner, practice, and system levels[4–7].
The Australian Government Department of Health and Ageing, the National Health and Medical Research Council, the National Heart Foundation of Australia, The Royal Australian College of General Practitioners, The Cardiac Society of Australia and New Zealand and the National Vascular Disease Prevention Alliance have published guidelines that address the major behavioural and physiological risk factors for vascular disease. These guidelines synthesise the evidence for preventing CVD and provide clear messages for primary care providers on what targets to aim for and what strategies might be best employed at the patient provider interaction.
The guidelines have been widely disseminated and well received. However implementation requires more than dissemination, it requires a tailored approach to generate change in clinicians behaviour, and there exists evidence of gaps between the guideline recommendations and their implementation in Australian general practice[7, 11, 12]. Some of the reasons for the failure to implement prevention guidelines are related to the complexity of guideline recommendations and patient, practitioner, and practice barriers[7, 13], including lack of capacity to provide brief interventions or refer for more intensive education and support[14, 15]. Patients’ understanding of prevention is variable: they lack knowledge about what preventive care is what is relevant to them, and there is a tendency for patients with low health literacy and education attainment to be less likely to ask for, and therefore to receive, preventive care[16, 17]. The culture of individual practices, their openness to change, and the number and experience of providers, all influence the ability to implement preventive guideline recommendations.
The Preventive Evidence into Practice (PEP) study is a partnership between New South Wales, Flinders, Monash, Bond, and Queensland Universities, the Royal Australian College of General Practitioners (RACGP), the National Heart Foundation of Australia (NHFA), and the BUPA Foundation. The PEP study is a national, cluster randomised control trial of an intervention designed to support general practices to implement the recommendations of evidence-based clinical management guidelines for the prevention of CVD in general practice among patients aged 40 to 69 years.
This study aims to evaluate the impact of the PEP intervention on: The behaviour of doctors and nurses in general practice in assessing and recording risk factors and providing interventions to address these; and patient behavioural and physiological risk factors.
We hypothesise that, for patients aged 40 to 69 years, the PEP intervention measured at the practice level over 12 months will improve: by 20% recording of behavioural and physiological risk factors; by 20% the adherence to the recommendations of guidelines for the management of these risk factors; and by 5% the lifestyle and physiological risk factors of patients with the risk factors.
The study is a cluster randomised controlled trial conducted in general practices in four states. This design was chosen because the primary intervention will be at the practice level and outcomes will be measured at the patient level.
Practices will be randomly assigned to intervention and late intervention (control) groups after stratification into blocks by state and practice size—i.e., the number of general practictioners (GPs) in a practice—using a computer-generated randomization list. Randomisation will be conducted centrally, after completion of the baseline general practice and practice nurse (PN) surveys, by one of the investigators, a statistician not involved in the data collection or intervention (UJ). Results of the randomisation will communicated to the project management committee prior to the commencement of the intervention.
The study is being conducted in general practices in four primary care organisations (Medicare Locals) in urban areas during 2012 and 2013.
The process for intervention development broadly followed the framework for design of complex interventions. In order to inform the development of the PEP intervention we initially conducted a review of the literature. This identified effective strategies for implementation of guidelines, including establishing small group education sessions with patients, clinician prompts and decision aids, audit and feedback, and external facilitation. Educational interventions that are interactive, provided feedback to participants, include an objective assessment of education needs and involve small groups are more likely to be effective[22, 23]. Small group interventions are most effective because they combine evidence-based material with peer influence. Audit and feedback can be effective in providing more preventive care. The variation of effect can be explained by the different ways in which audits are conducted and how feedback is provided. External facilitation has been shown to be effective in improving preventive care. Facilitation is usually included as part of a multifaceted intervention that includes auditing medical records.
We then conducted a mixed method study involving eight Sydney based general practices which included qualitative interviews with eight staff from two divisions of general practice, one allied health provider, eight GPs, four PNs, three practice managers and 24 patients. We also conducted a clinical audit of medical records in the eight practices for CVD preventive activities (for 2,409 patients aged 40 to 69 years). The findings from this, and the literature review, were discussed at a workshop involving the investigators and partners and external stakeholders including consumers, professional organisational representatives, and policy makers. The intervention was then piloted in three Sydney general practices and evaluated through audio recording of facilitation visits and interviews with practice staff before and after the intervention. The analysis resulted in changes to the audit feedback to practices, the program of practice visits, and the resources provided to practices. Following the pilot a facilitator manual was developed and discussed among the investigators prior to finalisation.
Description of intervention
The intervention is at the practice level. It will be carried out over a six-month period, and consists of a training workshop, three practice visits by a facilitator in each state based in the Medicare Local, and three follow-up phone calls. The facilitators will be trained together using the facilitator manual and case examples from the pilot study.
A clinical audit will be provided to the GPs and PNs at baseline and 12 months for patients aged 40 to 69 without heart or kidney disease, stroke, or diabetes. This will focus on body mass index (BMI) and waist circumference, BP, lipids, fasting glucose, and absolute cardiovascular risk. This will include analysis of both the recording of behavioural and physiological risk factors and the risk factors themselves. Comparative data are provided from other practices together with a commentary prepared by an investigator in each state asking questions and suggesting areas for improvement.
Practice visit one will occur between one and four weeks post the training workshop. At this visit, the baseline audit results will be reviewed and two to three goals for improvement established. These goals might be to improve recording of certain risk factors, and intensify prescribing or advice given or referral to other services. Resources and local referral links will be provided and discussed at this initial visit as necessary.
Practice visit two will occur between three and four weeks after visit number one. The purpose of this visit will be to reflect on progress towards meeting the goals for improvement. Any barriers will be discussed and further resources and supports provided as needed. A particular focus in this visit will be on ensuring that preventive care is available for all patients including disadvantaged patients who may have low health literacy.
Practice visit three occurs between three and four weeks after visit number two. The purpose of this visit is to monitor improvements, workshop ways to overcome barriers and discuss how improvements might be maintained and incorporated as part of routine practice.
The Intervention Facilitator will conduct three follow-up and troubleshooting phone calls with the prevention coordinator. Each of the practice visits will be interspersed by a follow-up or trouble shooting phone call initiated by the intervention facilitator. Additional contact may be initiated by the prevention coordinator as required.
Participants and recruitment
Eight practices have been recruited by a primary care organisation (Medicare Local) in each of the four states (a total of 32 practices). Staff members from the Medicare Locals approached practices that met the eligibility criteria, such as having computerised medical records to enable an audit of medical records using the Pen Clinical Audit Tool (Pen CAT) and a PN. Of the 47 practices who expressed interest in the study and who were subsequently visited, 32 agreed to participate, a response rate of 68%. Figure2 shows the selection and randomisation process.
The patients of the practice will be involved in the study in two ways. Firstly the records of all patients aged between 40 to 69 years who are active patients of the GPs who agree to participate in the study, and without known cardiac disease, stroke, or diabetes will be extracted in a de-identified audit at baseline and 12 months. In order to be seen as an active patient for the purpose of this study, patients must have visited their GP within the practice at least once in the last 12 months. Secondly, a random sample of 160 patients from each practice who consent and meet the eligibility criteria will be invited to complete the patient survey. To be eligible to participate in the study patients must have sufficient English and cognitive ability to understand the patient information letter, consent form, and written questionnaire.
Data collection procedures
The practice manager or the principal GP from each practice will be asked to complete a Practice Assessment Survey that collects descriptive information about the practice, including the location of the practice, number, type, and roles of staff members and information systems used. This information will assist us in understanding how the practice operates and therefore in identifying opportunities to facilitate preventive care. During the analysis phase of the research, the collation of practice information will enable us to examine whether any patterns of preventive care improvements emerge according to practice location, size, and teamwork arrangements.
Information will then be collected from the practitioners at baseline and again at 12 months. The GPs and PNs are asked to complete a survey that asks about their demographic characteristics and years in practice, and also how preventive care assessment and management is provided including frequency of assessment and management of the behavioural and physiological risk factors. This survey is based on questions from the Preventive Medicine Attitudes and Activities Questionnaire (PMAAQ) used by us in previous research.
Recorded risk factors
Proportion of eligible patients with the following recorded
0 and 12 months
· In the previous 24 months:-
o Blood pressure (in patients without hypertension)
o Weight (with height for BMI)
o Waist circumference
o Fasting blood glucose
o Fasting Lipids
o Smoking status
o Alcohol intake
Proportion of eligible patients who were at risk who recalled being offered advice:
0 and 12 months
· Diet (fruit and vegetables, low saturated fat)
· Physical activity
· Weight control
Change in medications over previous 12 months
0 and 12 months
· lipid lowering,
0 and 12 months
· Physical activity score*
· Diet score**
· Smoking Status
· Alcohol intake (standard drinks per week)
· waist circumference
· blood pressure
· lipids (TC, LDL-C, HDL-C, TG).
GP or nurse preventive care
· Self reported assessment
0 and 12 months
· Self reported advice
GP or nurse
· attitudes to preventive care in general practice
0 and 12 months
A purposive sample of eight intervention practices (two in each state that includes a cross section of various practice sizes) will be qualitatively studied. This study will determine what individual and organisational factors explain the success of the PEP intervention and explore the role of the intervention facilitator in supporting practices to make improvements. The qualitative study is broadly informed by a variety of theories and frameworks that help us to understand the organizational routines and patterns of work[37, 38], practice systems[39–41], and the way in which change is enacted and adapted in practices and a framework for organization of care activities (Chronic Care Model). The study will include qualitative interviews conducted by the field researchers with practice staff involved in the intervention early and late in the intervention process. Other qualitative data will be collected from the intervention facilitators, including a diary of meeting and contacts with the practice, their notes on the implementation of the intervention, and an interview towards the end of the intervention period. Analysis will be conducted with the aid of NVivo using an approach previously trialed by Cohen et al.. This will characterise narratives of the intervention at each study site looking for variation of key components, focus at each practice, and identifying factors which influence (or are perceived as influencing) the intervention.
The trial is being conducted in 32 practices. We estimate that the number of GPs and PNs recruited to the study will be 80.
We estimate that the records of at least 500 patients will be audited in each practice (i.e., 8,000 total). Assuming a design effect due to clustering of 1.8 based on previous studies, a sample of 188 patients in each group would have sufficient power (β = 0.8 and α = 0.05) to detect a 20% difference in the proportion of patients whose lifestyle and physiological risk factors are recorded. A sample size of 500 would have sufficient power to detect an effect size if 0.3 in recorded BMI (based on ICC = 0.047), LDL-Cholesterol (ICC 0.059), and systolic blood pressure after adjusting for clustering (ICC 0.062)[29, 46, 47].
It is estimated that at least 40 patients will be recruited to participate in the patient survey per practice or 640 patients in each arm of the trial. Allowing for 10% loss to follow up at 12 months, this will leave 36 patients per practice (576 in each group). Assuming a design effect due to clustering of two based on previous studies, a sample of 500 patients in each group would have sufficient power (β = 0.8 and α = 0.05) to detect a 15% difference in the proportion of patients offered education for diet or physical activity after adjusting for clustering (ICCs 0.051 and 0.035) and a 10% difference referral (ICCs 0.026 and 0.011). This sample size would have sufficient power to detect an effect size of 0.3 in serves of fruit and vegetables consumed (ICC 0.001) and physical activity scores (ICC 0.018).
We will examine the change of study variables within the intervention and control practices before and after interventions and compare the difference of outcomes between the two groups after adjusting for baseline differences. Primary analyses will be by intention to treat (patients and practices will be analysed as randomised, rather than by intervention actually received). We will analyse patient variables (risk behaviour, health service use, blood pressure, total cholesterol, HDL, LDL, General Practice Assessment Survey (GPAS) for within and between group differences using multilevel regression techniques adjusted for clustering of patients (level one) within practices (level two). The pre-randomisation value of each outcome will be used as lag covariates. Interactions as well as main effects will be tested. Secondary analysis will compare patients who were referred against those who were not, and defined as at risk. For cases lost to follow up at 12 months, we will conduct sensitivity analyses of the primary and secondary outcomes to determine the effect of their inclusion assuming no change in the outcome variables.
The study has been approved by the Royal Australian College of General Practitioners Human Research Ethics Committee and the Southern Adelaide Clinical Human Research Ethics Committee. This approval has been endorsed by the Human Research Ethics Committees at the University of New South Wales, Monash University, Bond and Queensland Universities. We obtained full informed written consent from participants.
The study is led by a project management committee that comprises the investigators and the project coordinator, which meets bimonthly. Intervention- and data collection subcommittees meet as required. There are Chief Investigators (CIs) from each of the four states participating in the study who implement the study in each state together with the Field Research Officers and the Intervention Facilitators. The Field Research Officers are responsible for the data collection. Their roles include conducting the clinical audit and administering surveys and interviewing practice staff and patients. The Field Research Officers are based at the local University and do not interact directly with the intervention facilitators. The Intervention Facilitators are responsible for working with practices to facilitate improvements in preventive activities. Their roles include working with practices to set appropriate targets and goals, provide resources to assist the practices in meeting their goals, monitoring improvements, and identifying how changes and improvements can be maintained. It is necessary that the data collection and the facilitation roles are carried out by different staff members so as not to contaminate the results. The Intervention Facilitators are based in the local Division of General Practice or Medicare Local.
The trial is registered with the Australian Clinical Trials Registry ACTRN12612000578808.
The trial is underway with baseline data collection complete and the intervention commenced.
The PEP study aims to evaluate the effectiveness of an implementation strategy for cardiovascular preventive care guidelines in Australian general practice. This has the potential to address a significant evidence to practice gap. Although there is self-reported use of guidelines by most GPs, this does not mean that the guideline recommendations are routinely followed. There are significant barriers to be overcome, and considerable variation exists between practices and practitioners in their readiness to implement evidence based care. Effective practice interventions need to be tailored to the barriers and local context, be multifaceted, and involve the entire primary care team. Thus, the implementation strategy has been designed to take into the context of individual practices and their staff with a flexible approach based on small group education, medical record audit, and practice facilitation. This is a unique approach in the Australian context and one that is also being explored overseas.
The complexities of applied research have led us to shift our focus from examining what works in preventing CVD generally, to focus more specifically on how primary care practices can be best supported in different contexts. By working with practices across four states in Australia, we hope to identify important characteristics and processes that can help generate and sustain a collaborative approach to preventing CVD. A key function of this partnership project is to ensure that the findings emerging from the research are communicated to a range of government and non-government organisations. Space has been allocated into the timeframe to enable potential implementation strategies and operational changes to be considered as part of the project dissemination process.
National health and medical research council
Preventive evidence into practice (project)
- Pen CAT:
Pen clinical audit tool
Smoking nutrition, alcohol, physical activity and weight.
This study is funded by an Australian National Health and Medical Research Council (NHMRC) Partnership grant (ID 568978) together with the Australian National Heart Foundation, Royal Australian College of General Practitioners, and the BUPA Foundation. MH is supported by a NHMRC Senior Principle Research Fellowship. We gratefully acknowledge the involvement and support of the South West Sydney, Southern Adelaide, Metro North Brisbane and Inner East Melbourne Medicare Locals and their general practices involved in this study.
- Britt H, Miller GC, Charles J, Henderson J, Bayram C, Pan Y, Valenti L, Harrison C, O’Halloran J, Fahridin S: General practice series no 27. General practice activity in Australia 2009–10. 2010, Canberra: AIHWGoogle Scholar
- Australian Institute of Health and Welfare: Heart, stroke and vascular diseases, Australian facts. 2004, Canberra: Australian Institute of Health and WelfareGoogle Scholar
- Begg S, Vos T, Barker B, Stevenson C, Stanley L, Lopez AD: The burden of disease and injury in Australia. 2007, Canberra: Australian Institute of Health and WelfareGoogle Scholar
- Litt JC: Exploration of the delivery of prevention in the general practice setting. 2007, PhD. Adelaide: FlindersGoogle Scholar
- Young J, Ward J: Implementing guidelines of smoking cessation advice in Australian general practice: opinions, current practice, readiness to change and perceived barriers. Fam Pract. 2001, 18: 14-20. 10.1093/fampra/18.1.14.View ArticlePubMedGoogle Scholar
- Laws R, Kemp L, Harris M, Powell Davies G, Williams A, Eames-Brown R: An exploration of how clinician attitudes and beliefs influence the implementation of lifestyle risk factor management in primary healthcare: a grounded theory study. Implement Sci. 2009, 4: 66-10.1186/1748-5908-4-66.View ArticlePubMedPubMed CentralGoogle Scholar
- Harris MF, Fanaian M, Jayasinghe U, Passey MM, Lyle D, McKenzie S, Powell DG: What predicts patient reported GP management of SNAPW behaviours?. Australian J Prim Health. 2011, 18: 23-28.Google Scholar
- Whitlock E, Orleans T, Pender N, Allan J: Evaluating primary care behavioural counseling interventions: an evidence-based approach. Am J Prev Med. 2002, 22 (4): 267-284. 10.1016/S0749-3797(02)00415-4.View ArticlePubMedGoogle Scholar
- Oxman AD, Thomson MA, Davis DA: No magic bullets: a systematic review of 102 trials of interventions to help health care professionals deliver services more effectively or efficiently. J Canadian Med Assoc. 1995, 153: 1423-1431.Google Scholar
- Hulscher ME, Wensing M, van der Weijden T, Grol R: Interventions to implement prevention in primary care. Cochrane Database Syst Rev: Rev. 2005, 10.1002/14651858.CD000362.pub2.. Art. No.: CD000362., Issue 1Google Scholar
- Britt H, Miller GC, Charles J: General practice activity in Australia 1990–00 to 2008–09: 10 year data tables. 2009, Canberra: AIHWGoogle Scholar
- Amoroso C, Harris MF, Ampt M: Health check for 45–49 year old patients in general practice: feasibility and impact on practices and patient behaviour. Australian Family Physician. 2009, 38: 358-362.PubMedGoogle Scholar
- Mazza D, Harris MF: improving implementation of evidence-based prevention in primary care. Med Australia. 2010, 193 (2): 101-102.Google Scholar
- Harris MF, Hobbs C, Powell Davies G: Implementation of a SNAP intervention in two divisions of general practice: a feasibility study. Med J Australia. 2005, 183: s54-s58.PubMedGoogle Scholar
- Passey ME, Laws RA, Jayasinghe UW, Fanaian M, McKenzie S, Powell-Davies G, Lyle D, Harris MF: Predictors of primary care referrals to a vascular disease prevention lifestyle program among participants in a cluster randomised trial. BMC Health Serv Res. 2012, 12: 234-10.1186/1472-6963-12-234.View ArticlePubMedPubMed CentralGoogle Scholar
- Beach M, Roter D, Wang N, Duggan P, Cooper L: Are physicians’ attitudes of respect accurately perceived by patients and associated with more positive communication behaviours?. Patient Ed Counsell. 2006, 62: 347-354. 10.1016/j.pec.2006.06.004.View ArticleGoogle Scholar
- Mazza D, Harris MF: Improving implementation of evidence-based prevention in primary care. Med J Aust. 2010, 193 (2): 101-102.PubMedGoogle Scholar
- Hung DY, Rundall TG, Tallia AF, Cohen DJ, Halpin HA, Crabtree BF: Rethinking prevention in primary care: applying the chronic care model to address health risk behaviors. Milbank Quarter. 2007, 85 (1): 69-91.View ArticleGoogle Scholar
- Campbell M, Fitzpatrick R, Haines A, Kinmonth AL, Sandercock P, Spiegelhalter D, Tyrer P: Framework for design and evaluation of complex interventions to improve health. BMJ. 2000, 321 (7262): 694-696. 10.1136/bmj.321.7262.694.View ArticlePubMedPubMed CentralGoogle Scholar
- Christl B, Lloyd J, Krastev Y, Litt J, Harris M: Preventing vascular disease: effective strategies for implementing guidlines in general practice. Australian Family Physician. 2011, 40 (10): 825-828.PubMedGoogle Scholar
- Forsetlund L, Bjørndal A, Rashidian A, Jamtvedt G, O’Brien Mary A, Wolf F, Davis D, Odgaard-Jensen J, Oxman Andrew D: Cochrane database of systematic reviews. Continuing education meetings and workshops: effects on professional practice and health care outcomes. 2009, Chichester, UK: John Wiley & Sons, LtdGoogle Scholar
- Satterlee WG, Eggers RG, Grimes DA: Effective medical education: insights from the cochrane library. Obstet Gynecol Surv. 2008, 63 (5): 329-333. 10.1097/OGX.0b013e31816ff661.View ArticlePubMedGoogle Scholar
- Davis D, Davis N: Selecting educational interventions for knowledge translation. CMAJ. 2010, 182 (2): E89-E93.View ArticlePubMedPubMed CentralGoogle Scholar
- Bywood PT, Lunnay B, Roche AM: Strategies for facilitating change in alcohol and other drugs (AOD) professional practice: a systematic review of the effectiveness of reminders and feedback. Drug Alcohol Rev. 2008, 27 (5): 548-558. 10.1080/09595230802245535.View ArticlePubMedGoogle Scholar
- Hogg W, Lemelin J, Graham ID, Grimshaw J, Martin C, Moore L, Soto E, O’Rourke K: Improving prevention in primary care: evaluating the effectiveness of outreach facilitation. Fam Pract. 2008, 25 (1): 40-48.View ArticlePubMedGoogle Scholar
- PEN Clinical Audit Tool. Pen Computer Systems Pty Ltd and the The Royal Australian College of General Practitioners (RACGP) Melbourne Australia: http://www.clinicalaudit.com.au/ (accessed 17 Jan 2013)
- Yeazel M, Lindstrom Bremer K, Center B: A validated tool for gaining insight into clinicians’ preventive medicine behaviors and beliefs: The preventive medicine attitudes and activities questionnaire (PMAAQ). Prev Med. 2006, 43: 86-91. 10.1016/j.ypmed.2006.03.021.View ArticlePubMedGoogle Scholar
- Fanaian M, Laws RA, Passey M, McKenzie S, Wan Q, Powell Davies G, Lyle D, Harris MF: Health improvement and prevention study (HIPS) - evaluation of an intervention to prevent vascular disease in general practice. BMC Family Pracice. 2010, 11: 57-10.1186/1471-2296-11-57.View ArticleGoogle Scholar
- Irvine K, Baker DF, Eyeson-Annan M: Population health monitoring and surveillance: question development field testing - field test 3 report. 2004, Sydney: NSW: Department of HealthGoogle Scholar
- Amoroso C, Harris MF, Arno A, Laws RA, McKenzie S, Williams AM, Jayasinghe UW, Zwar NA, Davies GP: The 45 year old health check–feasibility and impact on practices and patient behaviour. Australian Family Physician. 2010, 38 (5): 358-Google Scholar
- Steptoe A, Perkins-Porras L, McKay C, Rink E, Hilton S, Cappuccio FP: Behavioural counselling to increase consumption of fruit & vegetables in low income adults. British M J. 2003, 326: 855-857. 10.1136/bmj.326.7394.855.View ArticleGoogle Scholar
- Smith B, Marshall A, Huang N: Screening for physical activity in family practice: evaluation of two brief assessment tools. Am J Prev Med. 2005, 29: 256-264. 10.1016/j.amepre.2005.07.005.View ArticlePubMedGoogle Scholar
- Bradley KA, Bush KR, Epler AJ, Dobie DJ, Davis TM, Sporleder JL, Maynard C, Burman ML, Kivlahan DR: Two brief alcohol-screening tests from the alcohol Use disorders identification test (AUDIT): validation in a female veterans affairs patient population. 2003, Chicago, IL, ETATS-UNIS: American Medical AssociationGoogle Scholar
- Zwar N, Richmond RL, Harris M: General practice patients: their readiness to quit smoking. Australian Family Physician. 2008, 37 (1–2): 81-83.PubMedGoogle Scholar
- Marshall AL, Smith BJ, Bauman AE, Kaur S, Bull F: Reliability and validity of a brief physical activity assessment for use by family doctors. British J Sports Med. 2005, 39 (5): 294-297. 10.1136/bjsm.2004.013771.View ArticleGoogle Scholar
- Becker MC, Lazaric N, Nelson RR, Winter SG: Applying organizational routines in understanding organizational change. Ind Corp Chang. 2005, 14 (5): 775-791. 10.1093/icc/dth071.View ArticleGoogle Scholar
- Becker MC: Organizational routines: a review of the literature. Ind Corp Chang. 2004, 13 (4): 643-678. 10.1093/icc/dth026.View ArticleGoogle Scholar
- Miller WL, Crabtree BF, Nutting PA, Stange KC, Jaen CR: Primary care practice development: a relationship-centered approach. Annals Family Med. 2010, 8 (Suppl 1): S68-S79.View ArticleGoogle Scholar
- Stroebel CK, McDaniel RR, Crabtree BF, Miller WL, Nutting PA, Stange KC: How complexity science Can inform a reflective process for improvement in primary care practices. Jt Com J Qual Patient Saf. 2005, 31 (8): 438-446.Google Scholar
- Plsek PE, Greenhalgh T: Complexity science: the challenge of complexity in health care. BMJ. 2001, 323 (7313): 625-628. 10.1136/bmj.323.7313.625.View ArticlePubMedPubMed CentralGoogle Scholar
- Gunn JM, Palmer VJ, Dowrick CF, Herrman HE, Griffiths FE, Kokanovic R, Blashki GA, Hegarty KL, Johnson CL, Potiriadis M: Embedding effective depression care: using theory for primary care organisational and systems change. Implement Sci. 2010, 5: 62-10.1186/1748-5908-5-62.View ArticlePubMedPubMed CentralGoogle Scholar
- Bodenheimer T, Wagner EH, Grumbach K: Improving primary care for patients with chronic illness. JAMA. 2002, 288 (14): 1775-1779. 10.1001/jama.288.14.1775.View ArticlePubMedGoogle Scholar
- Cohen DJ, Crabtree BF, Etz RS, Balasubramanian BA, Donahue KE, Leviton LC, Clark EC, Isaacson NF, Stange KC, Green LW: Fidelity versus flexibility: translating evidence-based research into practice. Am J Prev Med. 2008, 35 (5 Suppl): S381-S389.View ArticlePubMedGoogle Scholar
- Georgiou A, Burns J, McKenzie S, Penn D, Flack J, Harris M: Monitoring change in diabetes care using diabetes registers: experience from divisions of general practice. Australian Family Physician. 2006, 35 (1–2): 77-80.PubMedGoogle Scholar
- The Counterweight Project Team: Evaluation of the counterweight programme for obesity management in primary care: a starting point for continuous improvement. Br J Gen Pract. 2008, 58: 548-554. 10.3399/bjgp08X319710.View ArticleGoogle Scholar
- Counterweight Project Team and Trueman P: Long-term cost-effectiveness of weight management in primary care. Int J Clin Pract. 2010, 64: 775-783.View ArticleGoogle Scholar
- Harris MF, Lloyd J, Krastev Y, Fanaian M, Davies GP, Zwar N, Liaw S-T: Routine use of clinical management guidelines in Australian general practice. Australian J Prim Health. 2012,http://dx.doi.org/10.1071/PY12078,Google Scholar
- Christl B, Harris M, Jayasinghe U, Proudfoot J, Taggart J, Tan J: Readiness for organisational change among general practice staff. Quality Safety Health Care. 2010, 19 (5): 1-4. 10.1136/qshc.2007.026229.Google Scholar
- Harrison MB, Legare F, Graham ID, Fervers B: Adapting clinical practice guidelines to local context and assessing barriers to their use. Cmaj. 2010, 182 (2): E78-E84.View ArticlePubMedPubMed CentralGoogle Scholar
- Medves J, Godfrey C, Turner C, Paterson M, Harrison M, MacKenzie L, Durando P: Systematic review of practice guideline dissemination and implementation strategies for healthcare teams and team-based practice. Int J Evid Based Healthc. 2010, 8 (2): 79-89.PubMedGoogle Scholar
- Hogg W, Lemelin J, Moroz I, Soto E, Russell G: Improving prevention in primary care: evaluating the sustainability of outreach facilitation. Canadian Family Physician. 2008, 54: 712-720.PubMedPubMed CentralGoogle Scholar
- Knox L, Taylor EF, Geonnotti K, Machta R, Kim J, Nysenbaum J, Parchman M: Developing and running a primary care practice facilitation program: a How-to guide: december 2011. 2011, Rockville, MD: US Agency for Healthcare Research and QualityGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.