There were no significant effects of organisational  interventions on lipid profile , HbA1c , medication adherence or recurrent cardiovascular events .
Pooled results indicated that educational interventions were not associated with clear differences in any of the review outcomes .
The estimated effects of organisational interventions were compatible with improvements and no differences in several modifiable risk factors .
BACKGROUND People with stroke or transient ischaemic attack ( TIA ) are at increased risk of future stroke and other cardiovascular events .
Evidence -based strategies for secondary stroke prevention have been established .
However , the implementation of prevention strategies could be improved .
OBJECTIVES To assess the effects of stroke service interventions for implementing secondary stroke prevention strategies on modifiable risk factor control , including patient adherence to prescribed medications , and the occurrence of secondary cardiovascular events .
A Multimethod Quality Improvement Intervention To Improve Preventive Cardiovascular Care
Context Interventions to promote guideline -recommended care have met with limited success . Quality improvement experts believe that multicomponent interventions are more effective than simpler strategies , but this belief rests on limited evidence . Contribution In this r and omized trial of 20 primary care practice s , intervention practice s received quarterly site visits and 2 network meetings about quality improvement in addition to copies of practice guidelines and quarterly performance reports . Intervention practice s had greater improvement in providing guideline -recommended care for cardiovascular disease prevention and treatment than practice s that received only the guidelines and performance reports . Caution s The study involved a small number of practice s. The Editors Widespread evidence reveals inadequate implementation of evidence -based clinical practice guidelines for prevention and management of cardiovascular disease and stroke in primary care setting s ( 1 - 3 ) . Primary prevention deficiencies exist in the screening and management of dyslipidemia ( 4 ) and hypertension ( 5 ) . Secondary prevention deficiencies include inadequate treatment of dyslipidemia in patients with coronary heart disease ( CHD ) ( 6 ) and inadequate use of antiplatelet therapy in patients with CHD or cerebrovascular disease ( 7 ) , inadequate use of -blockers after myocardial infa rct ion ( 8) , inadequate use of angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers in patients with heart failure ( 9 ) , and inadequate use of oral anticoagulant therapy in patients with atrial fibrillation ( 10 ) . Finally , patients with diabetes mellitus who are at high risk for cardiovascular disease as well as microvascular disease infrequently receive recommended screening and adequate treatment for elevated glycosylated hemoglobin levels , hypertension , and dyslipidemia ( 11 ) . Published systematic review s point to the importance of multifaceted interventions in increasing adherence to practice guidelines and improving disease control ( 12 , 13 ) . Little is known , however , about the relative effectiveness of different implementation strategies . More research is needed to develop and vali date effective , theoretically sound , and practical strategies for improving the provision of evidence -based medicine in primary care . Particularly important are studies that address multiple common , chronic conditions , which together reflect a large proportion of the work of primary care providers ( 14 ) . This study was design ed as a pragmatic clinical trial ( 15 ) , intended to assess whether a  multi method quality improvement intervention  was more effective than a less intensive intervention  for improving adherence to 21 quality indicators relevant to the primary and secondary prevention of cardiovascular disease and stroke . The multi method quality improvement intervention added practice site visits ( for academic detailing and quality improvement facilitation ) and network meetings ( for sharing best practice s ) to the approach of guideline dissemination and audit and feedback used in the less intensive intervention . The study was conducted in a practice -based research network ( PPRNet ) among users of a common electronic medical record ( Practice Partner Patient Records , Seattle , Washington ) , which historically provided audit and feedback to its practice members . Audit and feedback have already been shown to improve the practice of health care professionals , particularly in prescribing and test ordering ( 16 ) . Additional research is needed to assess the effect of audit and feedback in combination with other interventions . Methods Design The design was a cluster r and omized , controlled clinical trial , with the practice as the unit of r and omization . Twenty-three office-based primary care practice s in 15 states agreed to participate . The institutional review board at the Medical University of South Carolina approved the study . Study Indicators We derived the study indicators ( Table 1 ) from published sources ( 17 - 22 ) . Fourteen were process measures , which reflected whether recommended tests were done , appropriate diagnoses made , or appropriate medication prescribed . Seven were outcome measures , which reflected whether patients achieved recommended treatment goals . Some of the measures represented primary prevention , for example , screening for hypertension or dyslipidemia . Others represented secondary prevention , for example , reaching treatment goals for glycosylated hemoglobin levels , low-density lipoprotein ( LDL ) cholesterol levels , and blood pressure in patients with diabetes . An additional indicator , hormone replacement therapy for postmenopausal women , was included at the beginning of the study but was withdrawn in July 2002 when the results from the Women 's Health Initiative trial were published ( 23 ) . Table 1 . Study Indicators We determined practice performance for each study indicator at baseline and quarterly throughout the study . To determine performance , participating practice s ran a computer program to extract patient activity during the previous quarter from their electronic medical record . To protect patient confidentiality , the extract program assigned a unique , anonymous numerical identifier to each patient . The extract program obtained demographic information , such as age , race , and sex ; diagnoses ; medications ; laboratory data ; and vital signs . Text of progress notes , consultation reports , and discharge summaries were not extracted . The data were copied to a diskette and mailed to PPRNet or sent electronically via a secure server . In the PPRNet offices , the data were bridged to st and ard data dictionaries and converted to SAS data sets ( SAS Institute , Inc. , Cary , North Carolina ) on st and ard microcomputers for analyses . Interventions The intervention began on 1 January 2001 and was completed on 1 January 2003 . During the first quarter of 2001 , the medical director of each practice was sent printed copies of each practice guideline referenced in the study . Beginning in the first quarter of 2001 , the medical director was sent quarterly performance reports documenting the practice 's adherence to each of the 21 study indicators . Each report contained the practice 's current performance , calculated as the percentage of eligible patients who had received the recommended service , the number of patients who were receiving the recommended medication , or the number of patients who had achieved the treatment goal . The report also presented data on the practice s ' previous performance since the beginning of the study and the performance target , calculated as the 90th percentile at baseline among all practice s. In practice s with more than 1 clinician , individual provider data were not given because the study emphasized improvement at the practice level . The medical director was encouraged to share the reports with others in the practice in order to stimulate motivation for improvement . The 90th percentile was selected as the performance target because it reflected a bold but achievable goal ( at least 2 practice s were at this level of performance at baseline ) . Practice s in the control group received no other interventions during the study . An example of 1 page of a practice report is available in the Appendix Figure . Appendix Figure . Sample practice report for blood pressure in coronary heart disease .  Practice s in the intervention group also participated in practice site visits and network meetings . Six or seven 1- or 2-day site visits were held at each practice approximately every 3 months during 2001 and 2002 . The practice site visit was led by 1 of the physician co authors , assisted during the first few visits in 2001 by a clinical pharmacist with expertise in academic detailing ( 24 ) , and at later visits by other co authors with expertise in quality improvement . Initial site visits focused on engaging clinicians and staff members in the project , through a formal presentation by the site visitors and group discussion with all members of the practice team , including providers , nurses , medical assistants , and reception and administrative personnel . Because of vacation or hospital coverage responsibilities , 1 or 2 providers were occasionally absent in the multiprovider practice s , and 1 practice involved only a few members of their staff . We placed detailed attention on the scientific justification for the chosen study indicators and on published frameworks for clinician behavior change ( 25 , 26 ) . Baseline practice performance on each study indicator was discussed , and previous evidence of the ability of PPRNet practice s to improve care was presented ( 27 ) . Practice s were encouraged to increase the use of quality improvement tools available in the electronic medical record , such as note templates with embedded practice guidelines , query functions , prompts , reminders , and messaging . At each visit , a participatory planning session was held in which practice members identified specific clinical indicators they wished to work on and improvement activities to conduct before the next site visit . Lessons from complexity theory were used in this exercisethe influence of each practice member on the system , the importance of replicating successful approaches and focusing on motivators for patients and staff , and the notion that simple changes are easiest to adopt and can have profound effects . In subsequent site visits , we focused on discussing the practice 's success in adopting its planned improvement activities , presenting up date d performance data , and planning additional practice -level interventions . The site visitors presented results from recently published studies relevant to the study indicators . Successful and unsuccessful approaches to improvement by other intervention sites were also presented . Two-day network meetings were held in Charleston , South Carolina , in May 2001 and May 2002 . The lead clinician from each intervention practice and the research team attended the first meeting . At this
There were no significant effects of organisational  interventions on lipid profile , HbA1c , medication adherence or recurrent cardiovascular events .
Pooled results indicated that educational interventions were not associated with clear differences in any of the review outcomes .
The estimated effects of organisational interventions were compatible with improvements and no differences in several modifiable risk factors .
BACKGROUND People with stroke or transient ischaemic attack ( TIA ) are at increased risk of future stroke and other cardiovascular events .
Evidence -based strategies for secondary stroke prevention have been established .
However , the implementation of prevention strategies could be improved .
OBJECTIVES To assess the effects of stroke service interventions for implementing secondary stroke prevention strategies on modifiable risk factor control , including patient adherence to prescribed medications , and the occurrence of secondary cardiovascular events .