***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: BACKGROUND Although evidence suggests electronic health records ( EHRs ) can improve quality and efficiency , provider adoption rates in the US ambulatory setting are relatively low . Prior studies have identified factors correlated with EHR use , but less is known about characteristics of physicians on the verge of adoption . OBJECTIVE To compare characteristics of physicians who are imminent adopters of EHRs with EHR users and non-users . DESIGN AND PARTICIPANTS A survey was mailed ( June - November 2005 ) to a stratified r and om sample of all medical practice s in Massachusetts . One physician from each practice ( n=1884 ) was r and omly selected to participate . Overall , 1345 physicians ( 71.4 % ) responded to the survey , with 1082 eligible for analysis due to exclusion criteria . ' Imminent adopters ' were those planning to adopt EHRs within 12 months . MEASUREMENTS We assessed  physician and practice characteristics , availability of technology , barriers to adoption or expansion of health information technology ( HIT ) , computer proficiency , and financial considerations . RESULTS Compared to non-users , imminent adopters were younger , more experienced with technology , and more often in practice s engaged in quality improvement . More imminent adopters owned or partly owned their practice s ( 57.4 % ) than users ( 33.5 % ; p<0.001 ) , but fewer imminent adopters owned their practice s than non-users ( 65.7 % ; p<0.001 ) . Additionally , more imminent adopters ( 26.0 % ) reported personal financial incentives for HIT use than users ( 14.8 % ; p<0.001 ) and non-users ( 10.8 % ; p<0.001 ) . CONCLUSIONS Imminent adopters of EHRs differed from users and non-users . Financial considerations appear to play a major role in adoption decisions . Knowledge of these differences may assist policy-makers and healthcare leaders as they work to increase EHR adoption rates Design : Mailed survey to a stratified r and om sample of all medical practice s in Massachusetts in 2005 , with one physician per practice r and omly selected for survey . Measurements :  EHR adoption rates . Results : The response rate was 71 % ( 1345/1884 ) . Overall , while 45 % of physicians were using an EHR , EHRs were present in only 23 % of practice s. In multivariate analysis , practice size was strongly correlated with EHR adoption ; 52 % of practice s with 7 or more physicians had an EHR , as compared with 14 % of solo practice s ( adjusted odds ratio , 3.66 ; 95 % confidence interval , 2.28–5.87 ) . Hospital-based practice s ( adjusted odds ratio , 2.44 ; 95 % confidence interval , 1.53–3.91 ) and practice s that teach medical students or residents ( adjusted odds ratio , 2.30 ; 95 % confidence interval , 1.60–3.31 ) were more likely to have an EHR  . The most frequently cited barriers to adoption were start-up financial costs ( 84 % ) , ongoing financial costs ( 82 % ) , and loss of productivity ( 81 % ) . Conclusions : While almost half of physicians in Massachusetts are using an EHR , fewer than one in four practice s in Massachusetts have adopted EHRs .  Adoption rates are lower in smaller practice s , those not affiliated with hospitals , and those that do not teach medical students or residents . Interventions to exp and EHR use must address both financial and non-financial barriers , especially among smaller practice s. J Am Med Inform Assoc . 2007;14:110–117 . DOI 10.1197/jamia . M2187 . by gest on Sptem er 5 , 2016 Background Falls are the leading cause of injury-related deaths in the aging population .  Electronic medical record ( EMR ) systems can identify at-risk patients and enable interventions to decrease risk factors for falls . Objective The objectives of this study were to evaluate an EMR-based intervention to reduce overall medication use , psychoactive medication use , and occurrence of falls in an ambulatory elderly population at risk for falls . Design Prospect i ve , r and omized by clinic site . Patients / Participants Six-hundred twenty community-dwelling patients over 70 at risk for falls based on age and medication use . Interventions A st and ardized medication review was conducted and recommendations made to the primary physician via the EMR . Measurements and Main Results Patients were contacted to obtain self reports of falls at 3-month intervals over the 15-month period of study . Fall-related diagnoses and medication data were collected through the EMR . A combination of descriptive analyses and multivariate regression models were used to evaluate differences between the 2 groups , adjusting for baseline medication patterns and comorbidities . Although the intervention did not reduce the total number of medications , there was a significant negative relationship between the intervention and the total number of medications started during the intervention period ( p < .01 , regression estimate −0.199 ) and the total number of psychoactive medications ( p < .05 , regression estimate −0.204 . ) The impact on falls was mixed ; with the intervention group 0.38 times as likely to have had 1 or more fall-related diagnosis ( p < .01 ) ; when data on self-reported falls was included , a nonsignificant reduction in fall risk was seen . Conclusions The current study suggests that using an EMR to assess medication use in the elderly may reduce the use of psychoactive medications and falls in a community-dwelling elderly population BACKGROUND AND OBJECTIVES Physicians underdocument and undertreat obesity . Electronic medical records ( EMR ) reminders have improved other preventive services such as cancer screening and immunizations . We explored whether an EMR automatic calculation of body mass index ( BMI ) improved clinician documentation and treatment of overweight and obesity . METHODS We conducted a retrospective cross-sectional study of r and omly selected patient charts before and after the implementation of an EMR .  The primary outcome was documentation of overweight or obesity in the assessment /plan section or problem list section of the record . The secondary outcome was evidence in the medical record of treatment ( defined as nutrition or exercise counseling or referral to a nutritionist ) of overweight/obese patients . RESULTS Documentation of obesity ( BMI ? 30 ) improved from 31 % to 71 % ( prevalence ratio [PR]=2.30 , 95 % confidence interval [CI]=1.44 - -3.68 ) of obese patients after the implementation of an EMR calculation of BMI . Documentation of treatment of obese patients also improved , from 35 % to 59 % , ( PR=1.84 , 95 % CI=1.19 - -2.86 ) , but documentation and treatment of overweight patients ( BMI > 25<30 ) did not significantly improve . CONCLUSIONS These findings support the effectiveness of an EMR automatic BMI calculation to improve documentation and treatment of obese patients but suggest that software modification and alternative strategies are needed to improve documentation and treatment for overweight patients OBJECTIVES Osteoporosis treatment rates after a fracture are low . This study evaluated methods to increase guideline -recommended osteoporosis care postfracture . DESIGN Participants were r and omly assigned to  usual care or one of two interventions . Analysis of primary outcomes used electronic data and linear regression . SETTING A Pacific Northwest nonprofit health maintenance organization . PARTICIPANTS Female patients aged 50 to 89 who suffered a fracture in 1999 and had not received bone mineral density ( BMD ) measurement or medication for osteoporosis ( n=311 ) and their primary care providers ( n=159 ) . INTERVENTION Patient-specific clinical guideline advice to the primary care provider delivered by electronic medical record ( EMR ) message or electronic reminder to the provider plus an educational letter mailed to the patient . MEASUREMENTS BMD measurement and osteoporosis medication . RESULTS At 6 months , provider reminder result ed in 51.5 % of patients receiving BMD measurement or osteoporosis medication , provider reminder plus patient education result ed in 43.1 % , and usual care result ed in 5.9 % ( P<.001 ) . The effect of provider advice combined with patient education was not significantly different from provider advice alone ( P=.88 ) . Patients aged 60 to 69 were 18 % ( 95 % confidence interval=3 - 34 ) more likely to receive BMD measurement or an osteoporosis medication than those aged 80 to 89 . CONCLUSION Patient-specific postfracture advice to the provider through an EMR message significantly increased BMD measurement and osteoporosis medication . As EMRs become more widespread , this intervention could improve osteoporosis management for many postfracture patients . Future research should identify barriers to and facilitators of care for older , high-risk patients BACKGROUND To improve the documentation and treatment of tobacco use in primary care , we developed and implemented a 3-part electronic health record enhancement : (1)smoking status icons , ( 2 ) tobacco treatment reminders , and ( 3 ) a Tobacco Smart Form that facilitated the ordering of medication and fax and e-mail counseling referrals . METHODS We performed a cluster-r and omized controlled trial of the enhancement in 26 primary care practice s between December 19 , 2006 , and September 30 , 2007 . The primary outcome was the proportion of documented smokers who made contact with a smoking cessation counselor .  Secondary outcomes included coded smoking status documentation and medication prescribing . RESULTS During the 9-month study period , 132 630 patients made 315 962 visits to study practice s.  Coded documentation of smoking status increased from 37 % of patients to 54 % ( + 17 % ) in intervention practice s and from 35 % of patients to 46 % ( + 11 % ) in control practice s ( P < .001 for the difference in differences ) . Among the 9589 patients who were documented smokers at the start of the study , more patients in the intervention practice s were recorded as nonsmokers by the end of the study ( 5.3 % vs 1.9 % in control practice s ; P < .001 ) . Among 12 207 documented smokers , more patients in the intervention practice s made contact with a cessation counselor ( 3.9 % vs 0.3 % in control practice s ; P < .001 ) . Smokers in the intervention practice s were no more likely to be prescribed smoking cessation medication ( 2 % vs 2 % in control practice s ; P = .40 ) . CONCLUSION This electronic health record-based intervention improved smoking status documentation and increased counseling assistance to smokers but not the prescription of cessation medication OBJECTIVE : The goal was to assess the impact of influenza vaccine clinical alerts on missed opportunities for vaccination and on overall influenza immunization rates for children and adolescents with asthma . METHODS : A prospect i ve , cluster-r and omized trial of 20 primary care sites was conducted between October 1 , 2006 , and March 31 , 2007 . At intervention sites , electronic health record-based clinical alerts for influenza vaccine appeared at all office visits for children between 5 and 19 years of age with asthma who were due for vaccine . The proportion of captured immunization opportunities at visits and overall rates of complete vaccination for patients at intervention and control sites were compared with those for the previous year , after st and ardization for relevant covariates . The study had > 80 % power to detect an 8 % difference in the change in rates between the study and baseline years at intervention versus control practice s. RESULTS : A total of 23 418 visits and 11 919 children were included in the study year and 21 422 visits and 10 667 children in the previous year . The majority of children were male , 5 to 9 years of age , and privately insured . With st and ardization for selected covariates , captured vaccination opportunities increased from 14.4 % to 18.6 % at intervention sites and from 12.7 % to 16.3 % at control sites , a 0.6 % greater improvement . St and ardized influenza vaccination rates improved 3.4 % more at intervention sites than at control sites . The 4 practice s with the greatest increases in rates ( ≥11 % ) were all in the intervention group . Vaccine receipt was more common among children who had been vaccinated previously , with increasing numbers of visits , with care early in the season , and at preventive versus acute care visits . CONCLUSIONS : Clinical alerts were associated with only modest improvements in influenza vaccination rates 
    Output:
    
HIT improves clinical outcomes , increases the use of vaccinations and improves medication adherence .
Furthermore , HIT adoption leads to cost savings for physician groups , improves staff productivity and enriches patient-provider interactions .
The largest barrier to HIT adoption in physician groups is the high initial and ongoing costs of electronic systems .
Lack of sufficient training , a disorganised or non-receptive practice culture and technological problems such as inadequate connectivity appear to impede effective HIT use .
HIT has the potential to positively impact on physician practice organisations , although significant and diverse barriers block adoption .