Measures of electronic health record use in outpatient settings across vendors.
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ABSTRACT:
SUBMITTER: Baxter SL
PROVIDER: S-EPMC8068413 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe Meaningful Use (MU) program has increased the national emphasis on electronic measurement of hospital quality.ObjectiveTo evaluate stroke MU and one VHA stroke electronic clinical quality measure (eCQM) in national VHA data and determine sources of error in using centralized electronic health record (EHR) data.DesignOur study is a retrospective cross-sectional study of stroke quality measure eCQMs vs. chart review in a national EHR. We developed local SQL algorithms to generate the eCQMs, then modified them to run on VHA Central Data Warehouse (CDW) data. eCQM results were generated from CDW data in 2130 ischemic stroke admissions in 11 VHA hospitals. Local and CDW results were compared to chart review.Main measuresWe calculated the raw proportion of matching cases, sensitivity/specificity, and positive/negative predictive values (PPV/NPV) for the numerators and denominators of each eCQM. To assess overall agreement for each eCQM, we calculated a weighted kappa and prevalence-adjusted bias-adjusted kappa statistic for a three-level outcome: ineligible, eligible-passed, or eligible-failed.Key resultsIn five eCQMs, the proportion of matched cases between CDW and chart ranged from 95.4 %-99.7 % (denominators) and 87.7 %-97.9 % (numerators). PPVs tended to be higher (range 96.8 %-100 % in CDW) with NPVs less stable and lower. Prevalence-adjusted bias-adjusted kappas for overall agreement ranged from 0.73-0.95. Common errors included difficulty in identifying: (1) mechanical VTE prophylaxis devices, (2) hospice and other specific discharge disposition, and (3) contraindications to receiving care processes.ConclusionsStroke MU indicators can be relatively accurately generated from existing EHR systems (nearly 90 % match to chart review), but accuracy decreases slightly in central compared to local data sources. To improve stroke MU measure accuracy, EHRs should include standardized data elements for devices, discharge disposition (including hospice and comfort care status), and recording contraindications.
| S-EPMC4803676 | biostudies-literature
Project description:To validate the use of electronic algorithms based on International Classification of Diseases (ICD)-10 codes to identify outpatient visits for urinary tract infections (UTI), one of the most common reasons for antibiotic prescriptions. ICD-10 symptom codes (e.g., dysuria) alone or in addition to UTI diagnosis codes plus prescription of a UTI-relevant antibiotic were used to identify outpatient UTI visits. Chart review (gold standard) was performed by two reviewers to confirm diagnosis of UTI. The positive predictive value (PPV) that the visit was for UTI (based on chart review) was calculated for three different ICD-10 code algorithms using (1) symptoms only, (2) diagnosis only, or (3) both. Of the 1087 visits analyzed, symptom codes only had the lowest PPV for UTI (PPV = 55.4%; 95%CI: 49.3-61.5%). Diagnosis codes alone resulted in a PPV of 85% (PPV = 84.9%; 95%CI: 81.1-88.2%). The highest PPV was obtained by using both symptom and diagnosis codes together to identify visits with UTI (PPV = 96.3%; 95%CI: 94.5-97.9%). ICD-10 diagnosis codes with or without symptom codes reliably identify UTI visits; symptom codes alone are not reliable. ICD-10 based algorithms are a valid method to study UTIs in primary care settings.
| S-EPMC7558992 | biostudies-literature
Project description:IntroductionAlthough infrequently recorded in electronic health records (EHRs), measures of SES are essential to describe health inequalities and account for confounding in epidemiologic research. Medical Assistance (i.e., Medicaid) is often used as a surrogate for SES, but correspondence between conventional SES and Medical Assistance has been insufficiently studied.MethodsGeisinger Clinic EHR data from 2001 to 2014 and a 2014 questionnaire were used to create six SES measures: EHR-derived Medical Assistance and proportion of time under observation on Medical Assistance; educational attainment, income, and marital status; and area-level poverty. Analyzed in 2016-2017, associations of SES measures with obesity, hypertension, type 2 diabetes, chronic rhinosinusitis, fatigue, and migraine headache were assessed using weighted age- and sex-adjusted logistic regression.ResultsAmong 5,550 participants (interquartile range, 39.6-57.5 years, 65.9% female), 83% never used Medical Assistance. All SES measures were correlated (Spearman's p≤0.4). Medical Assistance was significantly associated with all six health outcomes in adjusted models. For example, the OR for prevalent type 2 diabetes associated with Medical Assistance was 1.7 (95% CI=1.3, 2.2); the OR for high school versus college graduates was 1.7 (95% CI=1.2, 2.5). Medical Assistance was an imperfect proxy for SES: associations between conventional SES measures and health were attenuated <20% after adjustment for Medical Assistance.ConclusionsBecause systematically collected SES measures are rarely available in EHRs and are unlikely to appear soon, researchers can use EHR-based Medical Assistance to describe inequalities. As SES has many domains, researchers who use Medical Assistance to evaluate the association of SES with health should expect substantial unmeasured confounding.
| S-EPMC5818301 | biostudies-literature
Project description:The Accreditation Council for Graduate Medical Education expects resident duty hours to be monitored, yet no previous studies have examined the effect of after-hours electronic health record (EHR) use on resident hours or burnout.We assessed internal medicine residents' perceived and actual time spent on after-hours outpatient EHR use and calculated increased duty hours if after-hours EHR use were included; we also assessed its effect on resident burnout.We retrospectively aggregated time spent logged on to the outpatient EHR for residents in a general internal medicine clinic for 13 weeks in 2011. Residents completed a survey on EHR use, which was correlated with objectively recorded data on EHR usage. We compared actual and self-reported EHR time and identified violations that would be generated if these hours were included in reported duty hours. We also correlated resident after-hours EHR use with responses to an internally developed burnout survey.The 44 residents in this study overestimated time spent on the ambulatory EHR (they spent 3.03 hours/week on after-hours use compared with a recorded 1.20 hours/week). In total, 190 duty hour violations (mean duration of violation = 37 minutes) would have been generated if after-hours EHR usage were included in residents' reported duty hours.Resident estimates of EHR use by residents were not accurate; including after-hours EHR use would increase the number of reported duty hour violations. There was no association between after-hours EHR use and resident burnout.
| S-EPMC3963775 | biostudies-other
Project description:BACKGROUND:The transition to the electronic health record (EHR) has brought forth a rapid cultural shift in the world of medicine, presenting both new challenges as well as opportunities for improving health care. As clinicians work to adapt to the changes imposed by the EHR, identification of best practices around the clinically excellent use of the EHR is needed. OBJECTIVE:Using the domains of clinical excellence previously defined by the Johns Hopkins Miller Coulson Academy of Clinical Excellence, this review aims to identify best practices around the clinically excellent use of the EHR. METHODS:The authors searched the PubMed database, using keywords related to clinical excellence domains and the EHR, to capture the English-language, peer-reviewed literature published between January 1, 2000, and August 2, 2016. One author independently reviewed each article and extracted relevant data. RESULTS:The search identified 606 titles, with the majority (393/606, 64.9%) in the domain of communication and interpersonal skills. Twenty-eight of the 606 (4.6%) titles were excluded from full-text review, primarily due to lack of availability of the full-text article. The remaining 578 full-text articles reviewed were related to clinical excellence generally (3/578, 0.5%) or the specific domains of communication and interpersonal skills (380/578, 65.7%), diagnostic acumen (31/578, 5.4%), skillful negotiation of the health care system (4/578, 0.7%), scholarly approach to clinical practice (41/578, 7.1%), professionalism and humanism (2/578, 0.4%), knowledge (97/578, 16.8%), and passion for clinical medicine (20/578, 3.5%). CONCLUSIONS:Results suggest that as familiarity and expertise are developed, clinicians are leveraging the EHR to provide clinically excellent care. Best practices identified included deliberate physical configuration of the clinical space to involve sharing the screen with patients and limiting EHR use during difficult and emotional topics. Promising horizons for the EHR include the ability to augment participation in pragmatic trials, identify adverse drug effects, correlate genomic data to clinical outcomes, and follow data-driven guidelines. Clinician and patient satisfaction with the EHR has generally improved with time, and hopefully continued clinician, and patient input will lead to a system that satisfies all.
| S-EPMC6231887 | biostudies-other
Project description:ObjectiveThe study sought to characterize rates of problem list completeness and duplications in common chronic diseases and to identify any relationships that they may have with respect to disease type, demographics, and disease severity.Materials and methodsWe performed a retrospective analysis of electronic health record data from Partners HealthCare. We selected 8 common chronic diseases and identified patients with each of those diseases. We then analyzed each patient's problem list for completeness and duplications and also collected information regarding demographics and disease severity. Rates of completeness and duplications were calculated for each disease and compared according to disease type, demographics, and disease severity.ResultsA total of 327 695 unique patients and 383 404 problem list entries were identified. Problem list completeness varied from 72.9% in hypertension to 93.5% in asthma, whereas problem list duplications varied from 4.8% in hypertension to 28.2% in diabetes. There was a variable relationship between demographic factors and rates of completeness and duplication. Rates of completeness were positively correlated with disease severity for most diseases. Rates of duplication were consistently positively correlated with disease severity.ConclusionsIncompleteness and duplications are both important issues in problem lists. These issues vary widely across different diseases and can also be impacted by patient demographics and disease severity. Further studies are needed to investigate the effect of individual user behaviors and organizational policies on problem list utilization, which will aid the development of interventions that improve the utility of problem lists.
| S-EPMC7481031 | biostudies-literature
Project description:The use of electronic cigarettes (e-cigarettes) can affect patient health and clinical care. However, the current documentation of e-cigarette use in the electronic health records (EHR) is inconsistent. This report outlines how the ambulatory clinical practices of a large U.S. hospital system optimized its electronic health records (EHR) framework to better record e-cigarettes used by patients. The new EHR section for e-cigarette information was implemented for outpatient appointments. During a 30-week evaluation period post-implementation, 638,804 patients (12 yrs and older) completed ambulatory appointments within the health system; of these, the new section contained e-cigarette use information for 37,906 (6%) patients. Among these patients, 1005 (2.7%) were identified as current e-cigarette users (current every day or current some day e-cigarette use), 941 (2.5%) were reported as former e-cigarette users, and 35,960 (94%) had never used e-cigarettes. A separate EHR section to document e-cigarette use is feasible within existing clinical practice models. Utilization of the new section was modest in routine clinical practice, indicating the need for more intensive implementation strategies that emphasize the health effects of e-cigarette use, and how consistent ascertainment could improve clinical practice.
| S-EPMC7460036 | biostudies-literature
Project description:ObjectiveTo understand the use of electronic health record (EHR) functionalities by physicians practicing in an underserved setting.Data source/study settingA total of 333 Indian Health Service physicians (55 percent response rate) in August 2012.Study designCross-sectional.Data collectionThe survey assessed routine use of EHR functionalities, perceived usefulness, and barriers to adoption.Principal findingsPhysicians routinely used a median 7 of 10 EHR functionalities targeted by the Meaningful Use program, but only 5 percent used all 10. Most (63 percent) felt the EHR improved quality of care. Many (76 percent) reported increased documentation time and poorer quality patient-physician interactions (45 percent). Primary care specialty and time using the EHR were positively associated with use of EHR functionalities, while perceived productivity loss was negatively associated.ConclusionsSignificant opportunities exist to increase use of EHR functionalities and preserve physician-patient interactions and productivity in a resource-limited environment.
| S-EPMC5517683 | biostudies-literature
Project description:ObjectiveTo examine the impact of electronic health record (EHR) deployment on Surgical Care Improvement Project (SCIP) measures in a tertiary-care teaching hospital.Data sourcesSCIP Core Measure dataset from the CMS Hospital Inpatient Quality Reporting Program (March 2010 to February 2012).Study designOne-group pre- and post-EHR logistic regression and difference-in-differences analyses.Principal findingsStatistically significant short-term declines in scores were observed for the composite, postoperative removal of urinary catheter and post-cardiac surgery glucose control measures. A statistically insignificant improvement in scores for these measures was noted 3 months after EHR deployment.ConclusionThe transition to an EHR appears to be associated with a short-term decline in quality. Implementation strategies should be developed to preempt or minimize this initial decline.
| S-EPMC4319882 | 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