Browsing by Subject "electronic health record"
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Item Open Access Health benefits and economic advantages associated with increased utilization of a smoking cessation program.(Journal of comparative effectiveness research, 2020-08-20) Datta, Santanu K; Dennis, Paul A; Davis, James MRationale, aim & objective: The goal of this study was to examine the health and economic impacts related to increased utilization of the Duke Smoking Cessation Program resulting from the addition of two relatively new referral methods - Best Practice Advisory and Population Outreach. Materials & methods: In a companion paper 'Comparison of Referral Methods into a Smoking Cessation Program', we report results from a retrospective, observational, comparative effectiveness study comparing the impact of three referral methods - Traditional Referral, Best Practice Advisory and Population Outreach on utilization of the Duke Smoking Cessation Program. In this paper we take the next step in this comparative assessment by developing a Markov model to estimate the improvement in health and economic outcomes when two referral methods - Best Practice Advisory and Population Outreach - are added to Traditional Referral. Data used in this analysis were collected from Duke Primary Care and Disadvantaged Care clinics over a 1-year period (1 October 2017-30 September 2018). Results: The addition of two new referral methods - Best Practice Advisory and Population Outreach - to Traditional Referral increased the utilization of the Duke Smoking Cessation Program in Primary Care clinics from 129 to 329 smokers and in Disadvantaged Care clinics from 206 to 401 smokers. The addition of these referral methods was estimated to result in 967 life-years gained, 408 discounted quality-adjusted life-years saved and total discounted lifetime direct healthcare cost savings of US$46,376,285. Conclusion: Health systems may achieve increased patient health and decreased healthcare costs by adding Best Practice Advisory and Population Outreach strategies to refer patients to smoking cessation services.Item Open Access Identifying Family and Unpaid Caregivers in Electronic Health Records: Descriptive Analysis.(JMIR formative research, 2022-07) Ma, Jessica E; Grubber, Janet; Coffman, Cynthia J; Wang, Virginia; Hastings, S Nicole; Allen, Kelli D; Shepherd-Banigan, Megan; Decosimo, Kasey; Dadolf, Joshua; Sullivan, Caitlin; Sperber, Nina R; Van Houtven, Courtney HBackground
Most efforts to identify caregivers for research use passive approaches such as self-nomination. We describe an approach in which electronic health records (EHRs) can help identify, recruit, and increase diverse representations of family and other unpaid caregivers.Objective
Few health systems have implemented systematic processes for identifying caregivers. This study aimed to develop and evaluate an EHR-driven process for identifying veterans likely to have unpaid caregivers in a caregiver survey study. We additionally examined whether there were EHR-derived veteran characteristics associated with veterans having unpaid caregivers.Methods
We selected EHR home- and community-based referrals suggestive of veterans' need for supportive care from friends or family. We identified veterans with these referrals across the 8 US Department of Veteran Affairs medical centers enrolled in our study. Phone calls to a subset of these veterans confirmed whether they had a caregiver, specifically an unpaid caregiver. We calculated the screening contact rate for unpaid caregivers of veterans using attempted phone screening and for those who completed phone screening. The veteran characteristics from the EHR were compared across referral and screening groups using descriptive statistics, and logistic regression was used to compare the likelihood of having an unpaid caregiver among veterans who completed phone screening.Results
During the study period, our EHR-driven process identified 12,212 veterans with home- and community-based referrals; 2134 (17.47%) veteran households were called for phone screening. Among the 2134 veterans called, 1367 (64.06%) answered the call, and 813 (38.1%) veterans had a caregiver based on self-report of the veteran, their caregiver, or another person in the household. The unpaid caregiver identification rate was 38.1% and 59.5% among those with an attempted phone screening and completed phone screening, respectively. Veterans had increased odds of having an unpaid caregiver if they were married (adjusted odds ratio [OR] 2.69, 95% CI 1.68-4.34), had respite care (adjusted OR 2.17, 95% CI 1.41-3.41), or had adult day health care (adjusted OR 3.69, 95% CI 1.60-10.00). Veterans with a dementia diagnosis (adjusted OR 1.37, 95% CI 1.00-1.89) or veteran-directed care referral (adjusted OR 1.95, 95% CI 0.97-4.20) were also suggestive of an association with having an unpaid caregiver.Conclusions
The EHR-driven process to identify veterans likely to have unpaid caregivers is systematic and resource intensive. Approximately 60% (813/1367) of veterans who were successfully screened had unpaid caregivers. In the absence of discrete fields in the EHR, our EHR-driven process can be used to identify unpaid caregivers; however, incorporating caregiver identification fields into the EHR would support a more efficient and systematic identification of caregivers.Trial registration
ClincalTrials.gov NCT03474380; https://clinicaltrials.gov/ct2/show/NCT03474380.Item Open Access Implementation of a Novel Tool to Collect Milk Feeding Data on Infants in Primary Care Clinics.(Clinical pediatrics, 2022-06-06) Maradiaga Panayotti, Gabriela M; Miner, Dean S; Hannon, Emily A; Kay, Melissa C; Shaikh, Sophie K; Jooste, Karen R; Erickson, Elizabeth; Kovarik, Teresa; Wood, Charles TWe aimed to capture milk feeding type in real time in a racially and socioeconomically diverse population. An electronic tool to assess milk feeding type at every medical visit for children aged 0 to 2 years was designed and incorporated into nursing workflows. The Milk Box tool was successfully added to the electronic clinical workspace of a large health system. There were eight clinics, with diverse characteristics, which incorporated the use of the Milk Box tool over 12 months. Time to 50% uptake of Milk Box varied from 3 to 5 months. Time to >80% uptake varied from 6 to 8 months. Our results show that Milk Box can be quickly incorporated into a clinical workflow when the team is given appropriate training and support. The tool also allows a primary care practice to study local breast milk consumption trends and to provide both individualized and system-level lactation support.Item Open Access Strategies for Referring Cancer Patients in a Smoking Cessation Program.(International journal of environmental research and public health, 2020-08-21) Davis, James M; Thomas, Leah C; Dirkes, Jillian EH; Swartzwelder, H ScottMost people who smoke and develop cancer are unable to quit smoking. To address this, many cancer centers have now opened smoking cessation programs specifically designed to help cancer patients to quit. An important question has now emerged-what is the most effective approach for engaging smokers within a cancer center in these smoking cessation programs? We report outcomes from a retrospective observational study comparing three referral methods-traditional referral, best practice advisory (BPA), and direct outreach-on utilization of the Duke Cancer Center Smoking Cessation Program. We found that program utilization rate was higher for direct outreach (5.4%) than traditional referral (0.8%), p < 0.001, and BPA (0.2%); p < 0.001. Program utilization was 6.4% for all methods combined. Inferring a causal relationship between referral method and program utilization was not possible because the study did not use a randomized design. Innovation is needed to generate higher utilization rates for cancer center smoking cessation programs.Item Open Access The Button Project: Using Chart Rounds for Teaching Clinical Ophthalmology with an Electronic Medical Record.(Advances in medical education and practice, 2019-01) Rosdahl, Jullia A; Zhang, Wenlan; Manjunath, VarshaObjective
Chart rounds have traditionally been used effectively for clinical teaching in ophthalmology. The introduction of the electronic health record has altered practice patterns and some evidence suggests interference with resident education. The purpose of this study was to investigate the use of chart rounds in our ophthalmology department and to see if a simple intervention, an "education button", could positively impact clinical teaching.Design
We used a cross-sectional survey, and pre- and post-intervention surveys to assess the utility of an intervention - an "education button".Setting
Department of Ophthalmology at Duke University, a tertiary care academic ophthalmology practice, in Durham, North Carolina.Participants
Ophthalmology trainees (37), including residents and clinical fellows, and clinical faculty (50) in the department were surveyed anonymously. The overall response rate for the cross-sectional survey was 83% (72/87). The overall response rate for the educational study was 53% for the first time-point and 59% for the second time-point.Results
For the cross-sectional survey, trainees found chart rounds to be useful and would like to increase their frequency. Most faculty reported doing them regularly, although not having enough time was the most common barrier (76% of the faculty). In the pre- and post-assessment of the "education button" (overall response rate 53%), the overall impression was positive with the button easy to use, but the implementation of the button did not appear to change the quality or frequency of chart rounds; nor did it appear to have an effect on covering learning objectives.Conclusion
While the "education button" could help with communication between the faculty and trainees during a busy clinic session to identify cases for discussion, it did not address the most common barrier identified by faculty members, that of not having enough time.