Clinician Response to Patient Medication Prices Displayed in the Electronic Health Record.
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ABSTRACT:
SUBMITTER: Sinaiko AD
PROVIDER: S-EPMC10481319 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature
Publications
Clinician Response to Patient Medication Prices Displayed in the Electronic Health Record.
Sinaiko Anna D AD Sloan Caroline E CE Soto Mark J MJ Zhao Olivia O Lin Chen-Tan CT Goss Foster R FR
JAMA internal medicine 20231001 10
Similar Datasets
Project description:ObjectivesWe assessed how clinician satisfaction with a vendor electronic health record (EHR) changed over time in the 4 years following the transition from a homegrown EHR system to identify areas for improvement.MethodsWe conducted a multiyear survey of clinicians across a large health care system after transitioning to a vendor EHR. Eligible clinicians from the first institution to transition received a survey invitation by email in fall 2016 and then eligible clinicians systemwide received surveys in spring 2018 and spring 2019. The survey included items assessing ease/difficulty of completing tasks and items assessing perceptions of the EHR's value, usability, and impact. One item assessing overall satisfaction and one open-ended question were included. Frequencies and means were calculated, and comparison of means was performed between 2018 and 2019 on all clinicians. A multivariable generalized linear model was performed to predict the outcome of overall satisfaction.ResultsResponse rates for the surveys ranged from 14 to 19%. The mean response from 3 years of surveys for one institution, Brigham and Women's Hospital, increased for overall satisfaction between 2016 (2.85), 2018 (3.01), and 2019 (3.21, p < 0.001). We found no significant differences in mean response for overall satisfaction between all responders of the 2018 survey (3.14) and those of the 2019 survey (3.19). Systemwide, tasks rated the most difficult included "Monitoring patient medication adherence," "Identifying when a referral has not been completed," and "Making a list of patients based on clinical information (e.g., problem, medication)." Clinicians disagreed the most with "The EHR helps me focus on patient care rather than the computer" and "The EHR allows me to complete tasks efficiently."ConclusionSurvey results indicate room for improvement in clinician satisfaction with the EHR. Usability of EHRs should continue to be an area of focus to ease clinician burden and improve clinician experience.
| S-EPMC10431971 | biostudies-literature
Project description:In a general inpatient population, we predicted patient-specific medication orders based on structured information in the electronic health record (EHR). Data on over three million medication orders from an academic medical center were used to train two machine-learning models: A deep learning sequence model and a logistic regression model. Both were compared with a baseline that ranked the most frequently ordered medications based on a patient's discharge hospital service and amount of time since admission. Models were trained to predict from 990 possible medications at the time of order entry. Fifty-five percent of medications ordered by physicians were ranked in the sequence model's top-10 predictions (logistic model: 49%) and 75% ranked in the top-25 (logistic model: 69%). Ninety-three percent of the sequence model's top-10 prediction sets contained at least one medication that physicians ordered within the next day. These findings demonstrate that medication orders can be predicted from information present in the EHR.
| S-EPMC7325318 | biostudies-literature
Project description:Background and objectiveProviding patients access to their medical records offers many potential benefits including identification and correction of errors. The process by which patients ask for changes to be made to their records is called an 'amendment request'. Little is known about the nature of such amendment requests and whether they result in modifications to the chart.MethodsWe conducted a qualitative content analysis of all patient-initiated amendment requests that our institution received over a 7-year period. Recurring themes were identified along three analytic dimensions: (1) clinical/documentation area, (2) patient motivation for making the request, and (3) outcome of the request.ResultsThe dataset consisted of 818 distinct requests submitted by 181 patients. The majority of these requests (n=636, 77.8%) were made to rectify incorrect information and 49.7% of all requests were ultimately approved. In 6.6% of the requests, patients wanted valid information removed from their record, 27.8% of which were approved. Among all of the patients requesting a copy of their chart, only a very small percentage (approximately 0.2%) submitted an amendment request.ConclusionsThe low number of amendment requests may be due to inadequate awareness by patients about how to make changes to their records. To make this approach effective, it will be important to inform patients of their right to view and amend records and about the process for doing so. Increasing patient access to medical records could encourage patient participation in improving the accuracy of medical records; however, caution should be used.
| S-EPMC4215043 | biostudies-literature
Project description:BackgroundChallenges in the design of electronic health records (EHRs) include designing usable systems that must meet the complex, rapidly changing, and high-stakes information needs of clinicians. The ability to move and assemble elements together on the same page has significant human-computer interaction (HCI) and efficiency advantages, and can mitigate the problems of negotiating multiple fixed screens and the associated cognitive burdens.ObjectiveWe compare MedWISE-a novel EHR that supports user-composable displays-with a conventional EHR in terms of the number of repeat views of data elements for patient case appraisal.Design and methodsThe study used mixed-methods for examination of clinical data viewing in four patient cases. The study compared use of an experimental user-composable EHR with use of a conventional EHR, for case appraisal. Eleven clinicians used a user-composable EHR in a case appraisal task in the laboratory setting. This was compared with log file analysis of the same patient cases in the conventional EHR. We investigated the number of repeat views of the same clinical information during a session and across these two contexts, and compared them using Fisher's exact test.ResultsThere was a significant difference (p<.0001) in proportion of cases with repeat data element viewing between the user-composable EHR (14.6 percent) and conventional EHR (72.6 percent).Discussion and conclusionUsers of conventional EHRs repeatedly viewed the same information elements in the same session, as revealed by log files. Our findings are consistent with the hypothesis that conventional systems require that the user view many screens and remember information between screens, causing the user to forget information and to have to access the information a second time. Other mechanisms (such as reduction in navigation over a population of users due to interface sharing, and information selection) may also contribute to increased efficiency in the experimental system. Systems that allow a composable approach that enables the user to gather together on the same screen any desired information elements may confer cognitive support benefits that can increase productive use of systems by reducing fragmented information. By reducing cognitive overload, it can also enhance the user experience.
| S-EPMC4862763 | biostudies-literature
Project description:Conventional wisdom holds that older, busier clinicians who see complex patients are less likely to adopt and use novel electronic health record (EHR) functionality.To compare the characteristics of clinicians who did and did not use novel EHR functionality, we conducted a retrospective analysis of the intervention arm of a randomized trial of new EHR-based tobacco treatment functionality.The novel functionality was used by 103 of 207 (50%) clinicians. Staff physicians were more likely than trainees to use the functionality (64% vs 37%; p<0.001). Clinicians who graduated more than 10 years previously were more likely to use the functionality than those who graduated less than 10 years previously (64% vs 42%; p<0.01). Clinicians with higher patient volumes were more likely to use the functionality (lowest quartile of number of patient visits, 25%; 2nd quartile, 38%; 3rd quartile, 65%; highest quartile, 71%; p<0.001). Clinicians who saw patients with more documented problems were more likely to use the functionality (lowest tertile of documented patient problems, 38%; 2nd tertile, 58%; highest tertile, 54%; p=0.04). In multivariable modeling, independent predictors of use were the number of patient visits (OR 1.2 per 100 additional patients; 95% CI 1.1 to 1.4) and number of documented problems (OR 2.9 per average additional problem; 95% CI 1.4 to 6.1).Contrary to conventional wisdom, clinically busier physicians seeing patients with more documented problems were more likely to use novel EHR functionality.
| S-EPMC3241168 | biostudies-literature
Project description:ObjectiveClinicians spend significant time working in the electronic health record (EHR). The US is an outlier in EHR time, suggesting that EHR-related work may be driven in part by the legal environment and threat of malpractice. To assess this, we evaluate the association between state-level malpractice climate and clinician time spent in the EHR.Materials and methodsWe use EHR metadata from 351 ambulatory care health systems in the United States using Epic from January-August 2019 combined with state-level data on malpractice incidence and payouts. We used descriptive statistics to measure variation in clinician EHR time, including total EHR time, documentation time per day, and after-hours EHR time per day. Multi-variable regression evaluated the association between clinicians in high malpractice states and EHR use.ResultsWe found no association between location in a state in the top-quartile of malpractice payouts and time spent in the EHR per day, time spent in the EHR outside of scheduled hours, or time spent documenting per day, except for a subgroup of the clinicians in the highest malpractice specialties, where there was a small increase in EHR time per day (B = 6.08 min, P < 0.001) and time spent documenting notes (B = 2.77 min, P < 0.001).DiscussionState-level differences in malpractice incidence are unlikely to be a significant driver of EHR work for most clinicians.ConclusionPolicymakers seeking to address EHR documentation burden should examine burden driven by other socio-technical demands on clinician time, such as billing or quality measurement.
| S-EPMC9093025 | biostudies-literature
Project description: Not available
| S-EPMC8271359 | biostudies-literature
Project description:ObjectiveWe validated an algorithm designed to identify new or prevalent users of antidepressant medications via population-based drug prescription records.Patients and methodsWe obtained population-based drug prescription records for the entire Olmsted County, Minnesota, population from 2011 to 2012 (N=149,629) using the existing electronic medical records linkage infrastructure of the Rochester Epidemiology Project (REP). We selected electronically a random sample of 200 new antidepressant users stratified by age and sex. The algorithm required the exclusion of antidepressant use in the 6 months preceding the date of the first qualifying antidepressant prescription (index date). Medical records were manually reviewed and adjudicated to calculate the positive predictive value (PPV). We also manually reviewed the records of a random sample of 200 antihistamine users who did not meet the case definition of new antidepressant user to estimate the negative predictive value (NPV).Results161 of the 198 subjects electronically identified as new antidepressant users were confirmed by manual record review (PPV 81.3%). Restricting the definition of new users to subjects who were prescribed typical starting doses of each agent for treating major depression in non-geriatric adults resulted in an increase in the PPV (90.9%). Extending the time windows with no antidepressant use preceding the index date resulted in only modest increases in PPV. The manual abstraction of medical records of 200 antihistamine users yielded an NPV of 98.5%.ConclusionsOur study confirms that REP prescription records can be used to identify prevalent and incident users of antidepressants in the Olmsted County, Minnesota, population.
| S-EPMC4147111 | biostudies-literature
Project description:Background and study aims
The Federal Ministry of Education and Research (BMBF) has funded the development of a patient controlled “Personal Electronic Health Record” (PEPA) as part of their current INFOPAT project. PEPA allows for the exchange of medical data between all interested groups, including the patients thenselves. A PEPA contains medical reports and findings including, for example, x-rays, CT scans and MRIs. The patients can safeguard their information and access all content. The aim of this study is to test the PEPA-prototype for cancer patients being treated at the National Center for Tumor Diseases (NCT) in Heidelberg.
Who can participate?
Adult colorectal cancer patients being treated at the National Center for Tumor Diseases (NCT) in Heidelberg.
What does the study involve?
There are two part to this study. The first part involves focus groups, in which a group of people are asked their opinion and attitudes towards, for example, an idea, product or service. Here, focus groups are set up that involve the patients, doctors and other health professionals to discuss current problems with the coordination of care offered to cancer patients, as well as discuss what people want to get from using PEPA (i.e. user requirements). The PEPA-prototype is then developed taking into account the conclusions from the focus groups. In the second part of the study, patients are encouraged to use the PEPA-prototype to prepare and follow up meetings with their physicians.
| 2424890 | ecrin-mdr-crc
Project description:ProblemBecause many medical students do not have access to electronic health records (EHRs) in the clinical environment, simulated EHR training is necessary. Explicitly training medical students to use EHRs appropriately during patient encounters equips them to engage patients while also attending to the accuracy of the record and contributing to a culture of information safety.ApproachFaculty developed and successfully implemented an EHR objective structured clinical examination (EHR-OSCE) for clerkship students at two institutions. The EHR-OSCE objectives include assessing EHR-related communication and data management skills.OutcomesThe authors collected performance data for students (n = 71) at the first institution during academic years 2011-2013 and for students (n = 211) at the second institution during academic year 2013-2014. EHR-OSCE assessment checklist scores showed that students performed well in EHR-related communication tasks, such as maintaining eye contact and stopping all computer work when the patient expresses worry. Findings indicated student EHR skill deficiencies in the areas of EHR data management including medical history review, medication reconciliation, and allergy reconciliation. Most students' EHR skills failed to improve as the year progressed, suggesting that they did not gain the EHR training and experience they need in clinics and hospitals.Next stepsCross-institutional data comparisons will help determine whether differences in curricula affect students' EHR skills. National and institutional policies and faculty development are needed to ensure that students receive adequate EHR education, including hands-on experience in the clinic as well as simulated EHR practice.
| S-EPMC5177541 | biostudies-literature