***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Abstract Objective : To evaluate the use of a computerised support system for decision making for implementing evidence based clinical guidelines for the management of asthma and angina in adults in primary care . Design : A before and after pragmatic cluster r and omised controlled trial utilising a two by two incomplete block design . Setting : 60 general practice s in north east Engl and . Participants : General practitioners and practice nurses in the study practice s and their patients aged 18 or over with angina or asthma . Main outcome measures : Adherence to the guidelines , based on review of case notes and patient reported generic and condition specific outcome measures . Results : The computerised decision support system had no significant effect on consultation rates , process of care measures ( including prescribing ) , or any patient reported outcomes for either condition . Levels of use of the software were low . Conclusions : No effect was found of computerised evidence based guidelines on the management of asthma or angina in adults in primary care . This was probably due to low levels of use of the software , despite the system being optimised as far as was technically possible . Even if the technical problems of producing a system that fully supports the management of chronic disease were solved , there remains the challenge of integrating the systems into clinical encounters where busy practitioners manage patients with complex , multiple conditions BACKGROUND Although computerized physician order entry reduces medication errors among in patients , little is known about the use of this system in primary care . METHODS We calculated the override rate among 3481 consecutive alerts generated at 5 adult primary care practice s that use a common computerized physician order entry system for prescription writing . For detailed review , we selected a r and om sample of 67 alerts in which physicians did not prescribe an alerted medication and 122 alerts that result ed in a written prescription . We identified factors associated with the physicians ' decisions to override a medication alert , and determined whether an adverse drug event ( ADE ) occurred . RESULTS Physicians overrode 91.2 % of drug allergy and 89.4 % of high-severity drug interaction alerts . In the multivariable analysis using the medical chart review sample ( n = 189 ) , physicians were less likely to prescribe an alerted medication if the prescriber was a house officer ( odds ratio [ OR ] , 0.26 ; 95 % confidence interval [ CI ] , 0.08 - 0.84 ) and if the patient had many drug allergies ( OR , 0.70 ; 95 % CI , 0.53 - 0.93 ) . They were more likely to override alerts for renewals compared with new prescriptions ( OR , 17.74 ; 95 % CI , 5.60 - 56.18 ) . We found no ADEs in cases where physicians observed the alert and 3 ADEs among patients with alert overrides , a nonsignificant difference ( P = .55 ) . Physician review ers judged that 36.5 % of the alerts were inappropriate . CONCLUSIONS Few physicians changed their prescription in response to a drug allergy or interaction alert , and there were few ADEs , suggesting that the threshold for alerting was set too low . Computerized physician order entry systems should suppress alerts for renewals of medication combinations that patients currently tolerate Background : Recent clinical trials indicate that treatment with lipid modifying therapy improves outcomes in patients with ischemic heart disease ( IHD ) and low levels of high density lipoprotein ( HDL ) cholesterol . The results of these trials , however , have not been widely implemented in clinical practice . Objectives : To develop and test an intervention design ed to increase the rate of prescription of lipid modifying therapy  and to determine the relative effectiveness of three different prompts ( progress notes , patient letters , or computer chart reminders ) . Methods : The study was conducted in 11 US Department of Veterans Affairs Medical Centers . The effect of the intervention on the proportion of eligible patients receiving lipid modifying therapy  was compared between five intervention sites and six matched control sites using a controlled before and after study design . Additionally , 92 providers within the intervention clinics were r and omized to receive one of the three prompts . Data were analyzed using logistic regression modeling which incorporated terms to account for the clustered nature of the data . Results : At the intervention sites the prescription rate increased from 8.3 % during the pre-intervention period to 39.1 % during the intervention ( OR = 6.5 , 95 % CI 5.2 to 8.2 , p<0.0001 ) but remained unchanged at the control sites . The interaction between group ( control v intervention ) and time period was highly significant ( p<0.0001 ) . The adjusted odds of receiving a prescription during the intervention period was 3.1 times higher at the intervention sites than at the control sites ( 95 % CI 2.1 to 4.7 ) . Overall , there was no significant difference in prescription rates among the three prompt groups . However , there was a significant interaction between prompt group and site , indicating that the efficacy of the prompts differed by site . Conclusion : An intervention for primary care providers consisting of an educational workshop , opinion leader influence , and prompts substantially increased the prescription rate of lipid modifying therapy OBJECTIVE The aim of this study was to evaluate the impact of an integrated patient-specific electronic clinical reminder system on diabetes and coronary artery disease ( CAD ) care and to assess physician attitudes toward this reminder system . DESIGN We enrolled 194 primary care physicians caring for 4549 patients with diabetes and 2199 patients with CAD at 20 ambulatory clinics . Clinics were r and omized so that physicians received either evidence -based electronic reminders within their patients ' electronic medical record or usual care . There were five reminders for diabetes care and four reminders for CAD care . MEASUREMENTS The primary outcome was receipt of recommended care for diabetes and CAD . We created a summary outcome to assess the odds of increased compliance with overall diabetes care ( based on five measures ) and overall CAD care ( based on four measures ) . We surveyed physicians to assess attitudes toward the reminder system . RESULTS Baseline adherence rates to all quality measures were low . While electronic reminders increased the odds of recommended diabetes care ( odds ratio [ OR ] 1.30 , 95 % confidence interval [ CI ] 1.01 - 1.67 ) and CAD ( OR 1.25 , 95 % CI 1.01 - 1.55 ) , the impact of individual reminders was variable . A total of three of nine reminders effectively increased rates of recommended care for diabetes or CAD . The majority of physicians ( 76 % ) thought that reminders improved quality of care . CONCLUSION An integrated electronic reminder system result ed in variable improvement in care for diabetes and CAD . These improvements were often limited and quality gaps persist BACKGROUND A cluster r and omized trial of tailored interventions to support the implementation of guidelines for  sore throat and urinary tract infection  found little or no change in the main outcomes , which were antibiotic prescriptions , use of laboratory tests and use of telephone consultations . There was great variation between the practice s in the change in these outcomes . OBJECTIVES Our aim was to evaluate how the interventions were received and to underst and why practice s did or did not change . METHODS The trial was conducted in general practice s in Norway . Data for this process evaluation were collected from the 120 practice s that completed the trial . Multiple methods were used : observations , semi-structured telephone interviews , a postal survey and data extracted from electronic medical records . We investigated factors that might explain a lack of change , including : agreement with the guidelines ; communication within each practice ; degree of participation in the project ; taking time to discuss the guidelines and their implementation ; use of the  components of the interventions ; and routines for telephone consultations .  Possible explanatory factors were explored in relation to variation in change and the overall extent of change in rates of use of antibiotics , laboratory tests and telephone consultations . RESULTS Sixty-three per cent of practice s agreed with the guidelines . Only 35 % reported having regular meetings , and 33 % discussed the project before its start , although 75 % reported agreement about participating within the practice . Only 33 % reported meeting to discuss the guidelines . Use of the components of the interventions ranged from 11 % for the increased fee for telephone consultations to 48 % for the computerized decision support . Forty-four per cent reported problems with telephone routines . No single factor explained the observed variation in the extent of change across practice s. CONCLUSIONS Inadequate time , re sources and support were the most salient factors that might explain a lack of change . Problems with internal communication and telephone routines were important contributing factors in many practice OBJECTIVE To assess the effects on health care re source utilization of a network of microcomputer workstations for writing all inpatient orders . DESIGN R and omized controlled clinical trial . SETTING Inpatient internal medicine service of an urban public hospital . SUBJECTS A total of 5219 internal medicine patients and the 68 teams of house officers , medical students , and faculty internists who cared for them . INTERVENTION Microcomputer workstations , linked to a comprehensive electronic medical record system , for writing all inpatient orders . MAIN OUTCOME MEASURES Total inpatient charges for each admission and charges for specific categories of orders . A time-motion study of selected interns assessed the ordering system 's time consumption . RESULTS Intervention teams generated charges that were $ 887 ( 12.7 % ) lower per admission than did control teams ( P = .02 ) . Significant reductions ( P < .05 ) were demonstrated separately for bed charges , diagnostic test charges , and drug charges . Reductions of similar proportion and statistical significance were found for hospital costs . The mean length of stay was 0.89 day shorter for intervention resident teams ( P = .11 ) . Interns in the intervention group spent an average of 33 minutes longer ( 5.5 minutes per patient ) during a 10-hour observation period writing orders than did interns in the control group ( P < .0001 ) . CONCLUSIONS A network of microcomputer workstations for writing all inpatient orders significantly lowered patient charges and hospital costs . This would amount to savings of more than $ 3 million in charges annually for this hospital 's medicine service and potentially tens of billions of dollars nationwide . However , the system required more physician time than did the paper charts . Research at other sites and system advances to reduce time requirements are warranted BACKGROUND Medication errors are frequently related to failure to appropriately select medications or adjust for laboratory parameters . Differences between guideline recommendations and actual frequency of therapeutic laboratory monitoring are substantial . This study evaluated interventions to improve laboratory monitoring at initiation of medication therapy . METHODS This cluster-r and omized trial compared 3 interventions to usual care for 10 medications in 15 primary care clinics in a health maintenance organization with an electronic medical record system . Eligible patients , identified from electronic data bases , had not received recommended laboratory monitoring within 5 days after new dispensing of a study medication . Interventions were an electronic medical record reminder to the prescribing health care professional , an automated voice message to the patient , and a pharmacy team outreach to the patient . Primary outcome was completion of all recommended baseline laboratory monitoring . RESULTS A total of 961 patients participated in the study . At 25 days , 95 ( 48.5 % ) of 196 patients in the electronic medical record reminder group , 177 ( 66.3 % ) of 267 in the automated voice message group , 214 ( 82.0 % ) of 261 in the pharmacy team outreach group , and 53 ( 22.4 % ) of 237 in the usual care group had completed all recommended baseline laboratory monitoring ( P<.001 ) . After adjustments , the hazard ratios for completing laboratory monitoring compared with usual care were 2.5 ( 95 % confidence interval , 1.8 - 3.5 ) for electronic medical record reminder , 4.1 ( 95 % confidence interval , 3.0 - 5.6 ) for automated voice message , and 6.7 ( 95 % confidence interval , 4.9 - 9.0 ) for pharmacy team outreach . CONCLUSIONS All 3 interventions were effective in increasing laboratory monitoring when initiating new medications in primary care . Further work is necessary to determine if these interventions improve patient outcomes Abstract Objective : To underst and the factors influencing the adoption of a  computerised clinical decision support system  for two chronic diseases in general practice . Design : Practice based , longitudinal , qualitative interview study . Setting : Five general practice s in north east Engl and . Participants : 13 respondents ( two practice managers , three nurses , and eight general practitioners ) gave a total of 19 semistructured interviews . 40 people in practice s included in the r and omised controlled trial ( 34 doctors , three nurses ) and interview study ( three doctors , one previously interviewed ) gave feedback . Results : Negative comments about the decision support system significantly outweighed the positive or neutral comments . Three main areas of concern among clinicians emerged : timing of the guideline trigger , ease of use of the system , and helpfulness of the content . Respondents did not feel that the system fitted well within the general practice context . Experience of “ on-dem and ” information sources , which were generally more positively viewed , informed the comments about the system . Some general practitioners suggested that nurses might find the guideline content more clinical ly useful and might be more prepared to use a computerised decision support system , but lack of feedback from nurses who had experienced the system limited the ability to assess this . Conclusions : Significant barriers exist to the use of complex clinical decision support systems for chronic disease by general practitioners . Key issues include the relevance and accuracy of messages and the flexibility to respond to other factors influencing decision making in primary care . What is already known on this topic R and omised controlled trials of complex computerised decision support systems have found low rates of use and no effects on process and outcomes of care What this study adds Clinicians found a  computerised decision support system for chronic disease in general practice to be difficult to use and 
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Further , systems that were endorsed by colleagues , minimized perceived threats to professional autonomy , and did not compromise doctor-patient interactions were accepted by users .