Effect of Expansion of Abbreviations and Acronyms on Patient Comprehension of Their Health Records: A Randomized Clinical Trial.
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ABSTRACT:
SUBMITTER: Grossman Liu L
PROVIDER: S-EPMC9107024 | biostudies-literature | 2022 May
REPOSITORIES: biostudies-literature
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Effect of Expansion of Abbreviations and Acronyms on Patient Comprehension of Their Health Records: A Randomized Clinical Trial.
Grossman Liu Lisa L Russell David D Reading Turchioe Meghan M Myers Annie C AC Vawdrey David K DK Masterson Creber Ruth M RM
JAMA network open 20220502 5
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Project description:The term non-alcoholic fatty liver disease (NAFLD) has rapidly become the most common type of chronic liver disease. NAFLD points to excessive hepatic fat storage and no evidence of secondary hepatic fat accumulation in patients with "no or little alcohol consumption". Both the etiology and pathogenesis of NAFLD are largely unknown, and a definitive therapy is lacking. Since NAFLD is very often and closely associated with metabolic dysfunctions, a consensus process is ongoing to shift the acronym NAFLD to MAFLD, i.e., metabolic-associated fatty liver disease. The change in terminology is likely to improve the classification of affected individuals, the disease awareness, the comprehension of the terminology and pathophysiological aspects involved, and the choice of more personalized therapeutic approaches while avoiding the intrinsic stigmatization due to the term "non-alcoholic". Even more recently, other sub-classifications have been proposed to concentrate the heterogeneous causes of fatty liver disease under one umbrella. While awaiting additional validation studies in this field, we discuss the main reasons underlying this important shift of paradigm.
| S-EPMC10326150 | biostudies-literature
Project description:ObjectiveTo create a sense inventory of abbreviations and acronyms from clinical texts.MethodsThe most frequently occurring abbreviations and acronyms from 352,267 dictated clinical notes were used to create a clinical sense inventory. Senses of each abbreviation and acronym were manually annotated from 500 random instances and lexically matched with long forms within the Unified Medical Language System (UMLS V.2011AB), Another Database of Abbreviations in Medline (ADAM), and Stedman's Dictionary, Medical Abbreviations, Acronyms & Symbols, 4th edition (Stedman's). Redundant long forms were merged after they were lexically normalized using Lexical Variant Generation (LVG).ResultsThe clinical sense inventory was found to have skewed sense distributions, practice-specific senses, and incorrect uses. Of 440 abbreviations and acronyms analyzed in this study, 949 long forms were identified in clinical notes. This set was mapped to 17,359, 5233, and 4879 long forms in UMLS, ADAM, and Stedman's, respectively. After merging long forms, only 2.3% matched across all medical resources. The UMLS, ADAM, and Stedman's covered 5.7%, 8.4%, and 11% of the merged clinical long forms, respectively. The sense inventory of clinical abbreviations and acronyms and anonymized datasets generated from this study are available for public use at http://www.bmhi.umn.edu/ihi/research/nlpie/resources/index.htm ('Sense Inventories', website).ConclusionsClinical sense inventories of abbreviations and acronyms created using clinical notes and medical dictionary resources demonstrate challenges with term coverage and resource integration. Further work is needed to help with standardizing abbreviations and acronyms in clinical care and biomedicine to facilitate automated processes such as text-mining and information extraction.
| S-EPMC3932450 | biostudies-literature
Project description:Background and objectivesPatient navigators and enhanced personal health records improve the quality of health care delivered in other disease states. We aimed to develop a navigator program for patients with CKD and an electronic health record-based enhanced personal health record to disseminate CKD stage-specific goals of care and education. We also conducted a pragmatic randomized clinical trial to compare the effect of a navigator program for patients with CKD with enhanced personal health record and compare their combination compared with usual care among patients with CKD stage 3b/4.Design, setting, participants, & measurementsTwo hundred and nine patients from six outpatient clinics (in both primary care and nephrology settings) were randomized in a 2×2 factorial design into four-study groups: (1) enhanced personal health record only, (2) patient navigator only, (3) both, and (4) usual care (control) group. Primary outcome measure was the change in eGFR over a 2-year follow-up period. Secondary outcome measures included acquisition of appropriate CKD-related laboratory measures, specialty referrals, and hospitalization rates.ResultsMedian age of the study population was 68 years old, and 75% were white. At study entry, 54% of patients were followed by nephrologists, and 88% were on renin-angiotensin system blockers. After a 2-year follow-up, rate of decline in eGFR was similar across the four groups (P=0.19). Measurements of CKD-related laboratory parameters were not significantly different among the groups. Furthermore, referral for dialysis education and vascular access placement, emergency room visits, and hospitalization rates were not statistically significant different between the groups.ConclusionsWe successfully developed a patient navigator program and an enhanced personal health record for the CKD population. However, there were no differences in eGFR decline and other outcomes among the study groups. Larger and long-term studies along with cost-effectiveness analyses are needed to evaluate the role of patient navigators and patient education through an enhanced personal health record in those with CKD.
| S-EPMC5586570 | biostudies-literature
Project description:BackgroundAlthough using the technologies for a variety of chronic health conditions such as personal health record (PHR) is reported to be acceptable and useful, there is a lack of evidence on the associations between the use of the technologies and the change of health outcome and patients' response to a digital health app.ObjectiveThis study aimed to examine the impact of the use of PHR and wearables on health outcome improvement and sustained use of the health app that can be associated with patient engagement.MethodsWe developed an Android-based mobile phone app and used a wristband-type activity tracker (Samsung Charm) to collect data on health-related daily activities from individual patients. Dietary record, daily step counts, sleep log, subjective stress amount, blood pressure, and weight values were recorded. We conducted a prospective randomized clinical trial across 4 weeks on those diagnosed with obstructive sleep apnea (OSA) who had visited the outpatient clinic of Seoul National University Bundang Hospital. The trial randomly assigned 60 patients to 3 subgroups including 2 intervention groups: (1) mobile app and wearable device users (n=20), (2) mobile app-only users (n=20), and (3) controls (n=20). The primary outcome measure was weight change. Body weights before and after the trial were recorded and analyzed during clinic visits. Changes in OSA-related respiratory parameters such as respiratory disturbance, apnea-hypopnea, and oxygenation desaturation indexes and snoring comprised the secondary outcome and were analyzed for each participant.ResultsWe collected the individual data for each group during the trial, specifically anthropometric measurement and laboratory test results for health outcomes, and the app usage logs for patient response were collected and analyzed. The body weight showed a significant reduction in the 2 intervention groups after intervention, and the mobile app-only group showed more weight loss compared with the controls (P=.01). There were no significant changes in sleep-related health outcomes. From a patient response point of view, the average daily step counts (8165 steps) from the app plus wearable group were significantly higher than those (6034 steps) from the app-only group because they collected step count data from different devices (P=.02). The average rate of data collection was not different in physical activity (P=.99), food intake (P=.98), sleep (P=.95), stress (P=.70), and weight (P=.90) in the app plus wearable and app-only groups, respectively.ConclusionsWe tried to integrate PHR data that allow clinicians and patients to share lifelog data with the clinical workflow to support lifestyle interventions. Our results suggest that a PHR-based intervention may be successful in losing body weight and improvement in lifestyle behavior.Trial registrationClinicalTrials.gov NCT03200223; https://clinicaltrials.gov/ct2/show/NCT03200223 (Archived by WebCite at http://www.webcitation.org/74baZmnCX).
| S-EPMC6682299 | biostudies-literature
Project description:A prior randomized controlled trial (RCT) showed no significant difference in wrong-patient errors between clinicians assigned to a restricted electronic health record (EHR) configuration (limiting to 1 record open at a time) versus an unrestricted EHR configuration (allowing up to 4 records open concurrently). However, it is unknown whether an unrestricted EHR configuration is more efficient. This substudy of the RCT compared clinician efficiency between EHR configurations using objective measures. All clinicians who logged onto the EHR during the substudy period were included. The primary outcome measure of efficiency was total active minutes per day. Counts were extracted from audit log data, and mixed-effects negative binomial regression was performed to determine differences between randomized groups. Incidence rate ratios (IRRs) were calculated with 95% confidence intervals (CIs). Among a total of 2556 clinicians, there was no significant difference between unrestricted and restricted groups in total active minutes per day (115.1 vs 113.3 min, respectively; IRR, 0.99; 95% CI, 0.93-1.06), overall or by clinician type and practice area.
| S-EPMC10114017 | biostudies-literature
Project description:PurposeTo examine the impact of a personal health record (PHR) in patients with hypertension measured by changes in biological outcomes, patient empowerment, patient perception of quality of care, and use of medical services.MethodsA cluster-randomized effectiveness trial with PHR and no PHR groups was conducted in two ambulatory clinics. 453 of 1686 (26.4%) patients approached were included in the analyses. A PHR tethered to the patient's electronic medical record (EMR) was the primary intervention and included security measures, patient control of access, limited transmission of EMR data, blood pressure (BP) tracking, and appointment assistance. BP was the main outcome measure. Patient empowerment was assessed using the Patient Activation Measure and Patient Empowerment Scale. Quality of care was assessed using the Clinician and Group Assessment Score (CAHPS) and the Patient Assessment of Chronic Illness Care. Frequency of use of medical services was self-reported.ResultsNo impact of the PHR was observed on BP, patient activation, patient perceived quality, or medical utilization in the intention-to-treat analysis. Sub-analysis of intervention patients self-identified as active PHR users (25.7% of those with available information) showed a 5.25-point reduction in diastolic BP. Younger age, self-reported computer skills, and more positive provider communication ratings were associated with frequency of PHR use.ConclusionsFew patients provided with a PHR actually used the PHR with any frequency. Thus simply providing a PHR may have limited impact on patient BP, empowerment, satisfaction with care, or use of health services without additional education or clinical intervention designed to increase PHR use.Clinical trial registration numberhttp://ClinicalTrials.gov Identifier: NCT01317537.
| S-EPMC3384099 | biostudies-literature
Project description:ImportanceRecommendations in the United States suggest limiting the number of patient records displayed in an electronic health record (EHR) to 1 at a time, although little evidence supports this recommendation.ObjectiveTo assess the risk of wrong-patient orders in an EHR configuration limiting clinicians to 1 record vs allowing up to 4 records opened concurrently.Design, setting, and participantsThis randomized clinical trial included 3356 clinicians at a large health system in New York and was conducted from October 2015 to April 2017 in emergency department, inpatient, and outpatient settings.InterventionsClinicians were randomly assigned in a 1:1 ratio to an EHR configuration limiting to 1 patient record open at a time (restricted; n = 1669) or allowing up to 4 records open concurrently (unrestricted; n = 1687).Main outcomes and measuresThe unit of analysis was the order session, a series of orders placed by a clinician for a single patient. The primary outcome was order sessions that included 1 or more wrong-patient orders identified by the Wrong-Patient Retract-and-Reorder measure (an electronic query that identifies orders placed for a patient, retracted, and then reordered shortly thereafter by the same clinician for a different patient).ResultsAmong the 3356 clinicians who were randomized (mean [SD] age, 43.1 [12.5] years; mean [SD] experience at study site, 6.5 [6.0] years; 1894 females [56.4%]), all provided order data and were included in the analysis. The study included 12 140 298 orders, in 4 486 631 order sessions, placed for 543 490 patients. There was no significant difference in wrong-patient order sessions per 100 000 in the restricted vs unrestricted group, respectively, overall (90.7 vs 88.0; odds ratio [OR], 1.03 [95% CI, 0.90-1.20]; P = .60) or in any setting (ED: 157.8 vs 161.3, OR, 1.00 [95% CI, 0.83-1.20], P = .96; inpatient: 185.6 vs 185.1, OR, 0.99 [95% CI, 0.89-1.11]; P = .86; or outpatient: 7.9 vs 8.2, OR, 0.94 [95% CI, 0.70-1.28], P = .71). The effect did not differ among settings (P for interaction = .99). In the unrestricted group overall, 66.2% of the order sessions were completed with 1 record open, including 34.5% of ED, 53.7% of inpatient, and 83.4% of outpatient order sessions.Conclusions and relevanceA strategy that limited clinicians to 1 EHR patient record open compared with a strategy that allowed up to 4 records open concurrently did not reduce the proportion of wrong-patient order errors. However, clinicians in the unrestricted group placed most orders with a single record open, limiting the power of the study to determine whether reducing the number of records open when placing orders reduces the risk of wrong-patient order errors.Trial registrationclinicaltrials.gov Identifier: NCT02876588.
| S-EPMC6518341 | biostudies-literature
Project description:BackgroundPersonal health records (PHRs) or patient portals have been on the healthcare policy agenda for many countries as a promising mechanism to support patient-centred healthcare by making medical records accessible to patients and those assisting patients in health self-management. Studies on clinical outcome have been inconsistent. To help us to understand why, we propose to look at measures that precede clinical outcome, specifically patient engagement and activation. Patient activation describes the knowledge, skills and confidence a person has in managing their own health and healthcare.ObjectiveTo systematically review the current evidence on the impact of PHRs on patient activation.MethodsA literature search was conducted for randomised controlled trials and quasi-experimental studies published up to January 2024 across EMBASE, PsycINFO, CINAHL and PubMed. Publications were included in the study if they examined any association between PHR use and activation.ResultsThe search initially produced 3062 papers for review, of which 88 full-text articles were screened for eligibility. Two reviewers assessed 22 of these articles, and 8 papers were identified as meeting the selection criteria. Among these, seven studies found no statistically significant differences in activation. However, one study reported a significantly greater effect than the others. Data from seven randomised controlled trials and quasi-experimental studies examining the effects of PHRs on patient activation and similar measures were extracted for meta-analysis. Overall, the use of PHRs was associated with a 0.41 standardised mean difference increase in activation (95% confidence interval 0.31-0.51). There was a high degree of heterogeneity (I² = 98%), with one study showing a much larger effect size compared to the rest.ConclusionMost studies showed little impact on activation, but one study found a large effect. This study notably offered PHRs combined with health coaching and training in the use of the system to their intervention group, which may indicate an important requirement for how to get the best out of a PHR system.
| S-EPMC11752559 | biostudies-literature
Project description:ObjectiveThe authors sought to determine whether providing summaries of patients' social media and other digital data to patients and their clinicians improves patients' health-related quality of life (HRQoL) measured by the RAND 36-Item Short Form Health Survey (SF-36).MethodsThe authors randomly assigned 115 adults receiving outpatient mental health therapy to usual care or to periodic sharing of summaries of their digital data with their clinician providing psychosocial therapy. The study was conducted October 2020-December 2021.ResultsPatients' mean±SD age was 31.3±10.5 years, and 82% were women. At 60 days after enrollment, no statistically significant change was detected in SF-36 scores for patients randomly allocated to the intervention (mean difference=-0.39, 95% CI=-4.17, 3.39) or to usual care (mean difference=-1.98, 95% CI=-5.74, 1.77), and no significant between-arm difference was observed (between-arm difference=1.60, 95% CI=-3.67, 6.86).ConclusionsCollecting and summarizing digital data for use in mental health treatment was feasible for patients but did not significantly improve their HRQoL or other measures of mental health.
| S-EPMC10949211 | biostudies-literature
Project description:PurposeTo examine the impact of a personal health record (PHR) on medication-use safety among older adults.BackgroundOnline PHRs have potential as tools to manage health information. We know little about how to make PHRs accessible for older adults and what effects this will have.MethodsA PHR was designed and pretested with older adults and tested in a 6-month randomized controlled trial. After completing mailed baseline questionnaires, eligible computer users aged 65 and over were randomized 3:1 to be given access to a PHR (n=802) or serve as a standard care control group (n=273). Follow-up questionnaires measured change from baseline medication use, medication reconciliation behaviors, and medication management problems.ResultsOlder adults were interested in keeping track of their health and medication information. A majority (55.2%) logged into the PHR and used it, but only 16.1% used it frequently. At follow-up, those randomized to the PHR group were significantly less likely to use multiple non-steroidal anti-inflammatory drugs-the most common warning generated by the system (viewed by 23% of participants). Compared with low/non-users, high users reported significantly more changes in medication use and improved medication reconciliation behaviors, and recognized significantly more side effects, but there was no difference in use of inappropriate medications or adherence measures.ConclusionsPHRs can engage older adults for better medication self-management; however, features that motivate continued use will be needed. Longer-term studies of continued users will be required to evaluate the impact of these changes in behavior on patient health outcomes.
| S-EPMC4078278 | biostudies-literature