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1.
Appl Clin Inform ; 11(1): 130-141, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-32074650

RESUMO

OBJECTIVE: To evaluate informatics-enabled quality improvement (QI) strategies for promoting time spent on face-to-face communication between ophthalmologists and patients. METHODS: This prospective study involved deploying QI strategies during implementation of an enterprise-wide vendor electronic health record (EHR) in an outpatient academic ophthalmology department. Strategies included developing single sign-on capabilities, activating mobile- and tablet-based applications, EHR personalization training, creating novel workflows for team-based orders, and promoting problem-based charting to reduce documentation burden. Timing data were collected during 648 outpatient encounters. Outcomes included total time spent by the attending ophthalmologist on the patient, time spent on documentation, time spent on examination, and time spent talking with the patient. Metrics related to documentation efficiency, use of personalization features, use of team-based orders, and note length were also measured from the EHR efficiency portal and compared with averages for ophthalmologists nationwide using the same EHR. RESULTS: Time spent on exclusive face-to-face communication with patients initially decreased with EHR implementation (2.9 to 2.3 minutes, p = 0.005) but returned to the paper baseline by 6 months (2.8 minutes, p = 0.99). Observed participants outperformed national averages of ophthalmologists using the same vendor system on documentation time per appointment, number of customized note templates, number of customized order lists, utilization of team-based orders, note length, and time spent after-hours on EHR use. CONCLUSION: Informatics-enabled QI interventions can promote patient-centeredness and face-to-face communication in high-volume outpatient ophthalmology encounters. By employing an array of interventions, time spent exclusively talking with the patient returned to levels equivalent to paper charts by 6 months after EHR implementation. This was achieved without requiring EHR redesign, use of scribes, or excessive after-hours work. Documentation efficiency can be achieved using interventions promoting personalization and team-based workflows. Given their efficacy in preserving face-to-face physician-patient interactions, these strategies may help alleviate risk of physician burnout.

2.
Ophthalmology ; 127(2): 151-158, 2020 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-31611015

RESUMO

PURPOSE: To determine recent incidence and visual outcomes for acute-onset endophthalmitis after cataract surgery performed in the United States. DESIGN: Retrospective cohort study. PARTICIPANTS: United States cataract surgery patients, 2013-2017 (5 401 686 patients). METHODS: Cases of acute-onset postoperative endophthalmitis occurring within 30 days after cataract surgery were identified using diagnosis codes in the American Academy of Ophthalmology IRIS (Intelligent Research in Sight) Registry database, drawn from electronic health records in ophthalmology practices across the nation. Annual and aggregate 5-year incidences were determined for all cataract surgeries and specifically for standalone procedures versus those combined with other ophthalmic surgeries. Patient characteristics were compared. Mean and median visual acuity was determined at 1 month preoperative as well as 1 week, 1 month, and 3 months postoperative among patients with and without endophthalmitis. MAIN OUTCOME MEASURES: Incidence of acute-onset postoperative endophthalmitis after cataract surgery. RESULTS: A total of 8 542 838 eyes underwent cataract surgery, 3629 of which developed acute-onset endophthalmitis (0.04%; 95% confidence interval, 0.04%-0.04%). Endophthalmitis incidence was highest among patients aged 0 to 17 years (0.37% over 5 years), followed by patients aged 18 to 44 years (0.18% over 5 years; P < 0.0001). Endophthalmitis occurred 4 times more often after combined cases (cataract with other ophthalmic procedures) than after standalone cataract surgeries (0.20% vs. 0.04% of cases), and occurred in 0.35% of patients receiving anterior vitrectomy. Mean 3-month postoperative visual acuity was 20/100 (median, 20/50) among endophthalmitis patients, versus a mean of approximately 20/40 (median, 20/30) among patients without endophthalmitis. However, 4% of endophthalmitis patients still achieved 20/20 or better visual acuity, and 44% achieved 20/40 or better visual acuity at 3 months. CONCLUSIONS: Acute-onset endophthalmitis occurred in 0.04% of 8 542 838 cataract surgeries performed in the United States between 2013 and 2017. Risk factors may include younger age, cataract surgery combined with other ophthalmic surgeries, and anterior vitrectomy. Visual acuity outcomes vary; however, patients can recover excellent vision after surgery. Big data from clinical registries like the IRIS Registry has great potential for evaluating rare conditions such as endophthalmitis, including developing benchmarks, longer-term time trend investigation, and comprehensive analysis of risk factors and prophylaxis.

4.
Am J Ophthalmol ; 2019 Dec 05.
Artigo em Inglês | MEDLINE | ID: mdl-31811860

RESUMO

PURPOSE: This study analyzed and quantified the sources of electronic health record (EHR) text documentation in ophthalmology progress notes. DESIGN: EHR documentation review and analysis. METHODS: Setting: a single academic ophthalmology department. STUDY POPULATION: a cohort study conducted between November 1, 2016, and December 31, 2018, using secondary EHR data and a follow-up manual review of a random samples. The cohort study included 123,274 progress notes documented by 42 attending providers. These notes were for patients with the 5 most common primary International Statistical Classification of Diseases and Related Health Problems, version 10, parent codes for each provider. For the manual review, 120 notes from 8 providers were randomly sampled. Main outcome measurements were characters or number of words in each note categorized by attribution source, author type, and time of creation. RESULTS: Imported text entries made up the majority of text in new and return patients, 2,978 characters (77%) and 3,612 characters (91%). Support staff members authored substantial portions of notes; 3,024 characters (68%) of new patient notes, 3,953 characters (83%) of return patient notes. Finally, providers completed large amounts of documentation after clinical visits: 135 words (35%) of new patient notes, 102 words (27%) of return patient notes. CONCLUSIONS: EHR documentation consists largely of imported text, is often authored by support staff, and is often written after the end of a visit. These findings raise questions about documentation accuracy and utility and may have implications for quality of care and patient-provider relationships.

5.
Artigo em Inglês | MEDLINE | ID: mdl-31750912

RESUMO

OBJECTIVE: To systematically review published literature and identify consistency and variation in the aims, measures, and methods of studies using electronic health record (EHR) audit logs to observe clinical activities. MATERIALS AND METHODS: In July 2019, we searched PubMed for articles using EHR audit logs to study clinical activities. We coded and clustered the aims, measures, and methods of each article into recurring categories. We likewise extracted and summarized the methods used to validate measures derived from audit logs and limitations discussed of using audit logs for research. RESULTS: Eighty-five articles met inclusion criteria. Study aims included examining EHR use, care team dynamics, and clinical workflows. Studies employed 6 key audit log measures: counts of actions captured by audit logs (eg, problem list viewed), counts of higher-level activities imputed by researchers (eg, chart review), activity durations, activity sequences, activity clusters, and EHR user networks. Methods used to preprocess audit logs varied, including how authors filtered extraneous actions, mapped actions to higher-level activities, and interpreted repeated actions or gaps in activity. Nineteen studies validated results (22%), but only 9 (11%) through direct observation, demonstrating varying levels of measure accuracy. DISCUSSION: While originally designed to aid access control, EHR audit logs have been used to observe diverse clinical activities. However, most studies lack sufficient discussion of measure definition, calculation, and validation to support replication, comparison, and cross-study synthesis. CONCLUSION: EHR audit logs have potential to scale observational research but the complexity of audit log measures necessitates greater methodological transparency and validated standards.

6.
J AAPOS ; 23(5): 264.e1-264.e4, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31521847

RESUMO

BACKGROUND: Aggressive posterior retinopathy of prematurity (APROP), which has a poor visual prognosis, is common in low- and middle-income countries (LMICs) as a result of suboptimal oxygen monitoring (primary prevention). The purpose of this study was to compare outcomes in APROP eyes treated with laser to eyes treated with antivascular endothelial growth factor (anti-VEGF) therapy. METHODS: The medical records of a cohort of APROP eyes treated with anti-VEGF (2010-2018) and another of eyes treated with laser photocoagulation (2002-2010) at the same institution in South India were reviewed retrospectively and compared. The main outcome was the proportion of eyes developing retinal detachment during resolution of acute ROP. RESULTS: A total of 398 eyes of 199 preterm babies with APROP were included: 168 eyes were treated with photocoagulation; 230, with anti-VEGF. From 2002 to 2010, compared to the more recent cohort, babies diagnosed with APROP tended to be heavier (P < 0.001), older (P < 0.001), and exposed to fewer days of oxygen (P = 0.02). In the laser-treated cohort, 17 of 168 eyes (10%) developed retinal detachment (7, stage 5; 12, stage 4), compared with 3 of 230 (1%) in the anti-VEGF cohort (all stage 4 [P = 0.002]). CONCLUSIONS: The incidence of retinal detachment was significantly lower in eyes treated with anti-VEGF compared with laser-.treated eyes In the absence of a randomized trial, these data suggest that anti-VEGF may lead to better anatomic outcomes, although questions remain concerning dosage, timing, and risks.

7.
J Pediatr Ophthalmol Strabismus ; 56(5): 282-287, 2019 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-31545861

RESUMO

PURPOSE: To characterize retinopathy of prematurity (ROP) training practices in international residency and fellowship programs. METHODS: A publicly available online-based platform (http://www.SurveyMonkey.com) was used to develop a 28-question multiple-choice survey that targeted ROP screening and treatment methods. The authors solicited training programs in the Philippines, Thailand, and Taiwan. RESULTS: Programs from three countries participated in the survey, and a total of 95 responses collected from residents, fellows, and attending ophthalmologists were analyzed. A descriptive analysis demonstrated that 45 participants (47%) reported 1% to 33% of ROP screenings were performed under direct supervision of attending ophthalmologists, and 35 (37%) reported the use of formal assessments. The majority of participants (Country A: 87%, Country B: 71%, and Country C: 75%) estimated 1% to 33% of their practice was spent screening for ROP. Notably, 44 participants (46%) reported performing zero laser photocoagulation treatments for ROP during training (Country A: 65%, Country B: 38%, and Country C: 38%). CONCLUSIONS: International ophthalmology trainees perform a limited number of ROP examinations and laser interventions. ROP screenings are often unsupervised and lead to no formal evaluation by an attending ophthalmologist. Limited ROP training among ophthalmologists may lead to misdiagnosis and ultimately mismanagement of a patient. Loss of vision and exposure to unwarranted treatments are among the implications of such errors. The findings highlight the need to improve ROP training in international ophthalmology residency and fellowship programs. [J Pediatr Ophthalmol Strabismus. 2019;56(5):282-287.].

8.
Lancet ; 394(10208): 1551-1559, 2019 10 26.
Artigo em Inglês | MEDLINE | ID: mdl-31522845

RESUMO

BACKGROUND: Despite increasing worldwide use of anti-vascular endothelial growth factor agents for treatment of retinopathy of prematurity (ROP), there are few data on their ocular efficacy, the appropriate drug and dose, the need for retreatment, and the possibility of long-term systemic effects. We evaluated the efficacy and safety of intravitreal ranibizumab compared with laser therapy in treatment of ROP. METHODS: This randomised, open-label, superiority multicentre, three-arm, parallel group trial was done in 87 neonatal and ophthalmic centres in 26 countries. We screened infants with birthweight less than 1500 g who met criteria for treatment for retinopathy, and randomised patients equally (1:1:1) to receive a single bilateral intravitreal dose of ranibizumab 0·2 mg or ranibizumab 0·1 mg, or laser therapy. Individuals were stratified by disease zone and geographical region using computer interactive response technology. The primary outcome was survival with no active retinopathy, no unfavourable structural outcomes, or need for a different treatment modality at or before 24 weeks (two-sided α=0·05 for superiority of ranibizumab 0·2 mg against laser therapy). Analysis was by intention to treat. This trial is registered with ClinicalTrials.gov, NCT02375971. INTERPRETATION: Between Dec 31, 2015, and June 29, 2017, 225 participants (ranibizumab 0·2 mg n=74, ranibizumab 0·1 mg n=77, laser therapy n=74) were randomly assigned. Seven were withdrawn before treatment (n=1, n=1, n=5, respectively) and 17 did not complete follow-up to 24 weeks, including four deaths in each group. 214 infants were assessed for the primary outcome (n=70, n=76, n=68, respectively). Treatment success occurred in 56 (80%) of 70 infants receiving ranibizumab 0·2 mg compared with 57 (75%) of 76 infants receiving ranibizumab 0·1 mg and 45 (66%) of 68 infants after laser therapy. Using a hierarchical testing strategy, compared with laser therapy the odds ratio (OR) of treatment success following ranibizumab 0·2 mg was 2·19 (95% Cl 0·99-4·82, p=0·051), and following ranibizumab 0·1 mg was 1·57 (95% Cl 0·76-3·26); for ranibizumab 0·2 mg compared with 0·1 mg the OR was 1·35 (95% Cl 0·61-2·98). One infant had an unfavourable structural outcome following ranibizumab 0·2 mg, compared with five following ranibizumab 0·1 mg and seven after laser therapy. Death, serious and non-serious systemic adverse events, and ocular adverse events were evenly distributed between the three groups. FINDINGS: In the treatment of ROP, ranibizumab 0·2 mg might be superior to laser therapy, with fewer unfavourable ocular outcomes than laser therapy and with an acceptable 24-week safety profile. FUNDING: Novartis.


Assuntos
Inibidores da Angiogênese/administração & dosagem , Fotocoagulação a Laser , Ranibizumab/administração & dosagem , Retinopatia da Prematuridade/terapia , Inibidores da Angiogênese/efeitos adversos , Feminino , Idade Gestacional , Humanos , Recém-Nascido , Recém-Nascido de muito Baixo Peso , Injeções Intravítreas , Fotocoagulação a Laser/efeitos adversos , Masculino , Ranibizumab/efeitos adversos , Resultado do Tratamento , Fator A de Crescimento do Endotélio Vascular/antagonistas & inibidores
9.
JAMA Ophthalmol ; 2019 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-31268499

RESUMO

Importance: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide, but treatment failure and disease recurrence are important causes of adverse outcomes in patients with treatment-requiring ROP (TR-ROP). Objectives: To apply an automated ROP vascular severity score obtained using a deep learning algorithm and to assess its utility for objectively monitoring ROP regression after treatment. Design, Setting, and Participants: This retrospective cohort study used data from the Imaging and Informatics in ROP consortium, which comprises 9 tertiary referral centers in North America that screen high volumes of at-risk infants for ROP. Images of 5255 clinical eye examinations from 871 infants performed between July 2011 and December 2016 were assessed for eligibility in the present study. The disease course was assessed with time across the numerous examinations for patients with TR-ROP. Infants born prematurely meeting screening criteria for ROP who developed TR-ROP and who had images captured within 4 weeks before and after treatment as well as at the time of treatment were included. Main Outcomes and Measures: The primary outcome was mean (SD) ROP vascular severity score before, at time of, and after treatment. A deep learning classifier was used to assign a continuous ROP vascular severity score, which ranged from 1 (normal) to 9 (most severe), at each examination. A secondary outcome was the difference in ROP vascular severity score among eyes treated with laser or the vascular endothelial growth factor antagonist bevacizumab. Differences between groups for both outcomes were assessed using unpaired 2-tailed t tests with Bonferroni correction. Results: Of 5255 examined eyes, 91 developed TR-ROP, of which 46 eyes met the inclusion criteria based on the available images. The mean (SD) birth weight of those patients was 653 (185) g, with a mean (SD) gestational age of 24.9 (1.3) weeks. The mean (SD) ROP vascular severity scores significantly increased 2 weeks prior to treatment (4.19 [1.75]), peaked at treatment (7.43 [1.89]), and decreased for at least 2 weeks after treatment (4.00 [1.88]) (all P < .001). Eyes requiring retreatment with laser had higher ROP vascular severity scores at the time of initial treatment compared with eyes receiving a single treatment (P < .001). Conclusions and Relevance: This quantitative ROP vascular severity score appears to consistently reflect clinical disease progression and posttreatment regression in eyes with TR-ROP. These study results may have implications for the monitoring of patients with ROP for treatment failure and disease recurrence and for determining the appropriate level of disease severity for primary treatment in eyes with aggressive disease.

10.
JAMA Ophthalmol ; 2019 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-31268518

RESUMO

Importance: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide, but clinical diagnosis is subjective and qualitative. Objective: To describe a quantitative ROP severity score derived using a deep learning algorithm designed to evaluate plus disease and to assess its utility for objectively monitoring ROP progression. Design, Setting, and Participants: This retrospective cohort study included images from 5255 clinical examinations of 871 premature infants who met the ROP screening criteria of the Imaging and Informatics in ROP (i-ROP) Consortium, which comprises 9 tertiary care centers in North America, from July 1, 2011, to December 31, 2016. Data analysis was performed from July 2017 to May 2018. Exposure: A deep learning algorithm was used to assign a continuous ROP vascular severity score from 1 (most normal) to 9 (most severe) at each examination based on a single posterior photograph compared with a reference standard diagnosis (RSD) simplified into 4 categories: no ROP, mild ROP, type 2 ROP or pre-plus disease, or type 1 ROP. Disease course was assessed longitudinally across multiple examinations for all patients. Main Outcomes and Measures: Mean ROP vascular severity score progression over time compared with the RSD. Results: A total of 5255 clinical examinations from 871 infants (mean [SD] gestational age, 27.0 [2.0] weeks; 493 [56.6%] male; mean [SD] birth weight, 949 [271] g) were analyzed. The median severity scores for each category were as follows: 1.1 (interquartile range [IQR], 1.0-1.5) (no ROP), 1.5 (IQR, 1.1-3.4) (mild ROP), 4.6 (IQR, 2.4-5.3) (type 2 and pre-plus), and 7.5 (IQR, 5.0-8.7) (treatment-requiring ROP) (P < .001). When the long-term differences in the median severity scores across time between the eyes progressing to treatment and those who did not eventually require treatment were compared, the median score was higher in the treatment group by 0.06 at 30 to 32 weeks, 0.75 at 32 to 34 weeks, 3.56 at 34 to 36 weeks, 3.71 at 36 to 38 weeks, and 3.24 at 38 to 40 weeks postmenstrual age (P < .001 for all comparisons). Conclusions and Relevance: The findings suggest that the proposed ROP vascular severity score is associated with category of disease at a given point in time and clinical progression of ROP in premature infants. Automated image analysis may be used to quantify clinical disease progression and identify infants at high risk for eventually developing treatment-requiring ROP. This finding has implications for quality and delivery of ROP care and for future approaches to disease classification.

11.
Neural Netw ; 118: 65-80, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31254769

RESUMO

We consider learning from comparison labels generated as follows: given two samples in a dataset, a labeler produces a label indicating their relative order. Such comparison labels scale quadratically with the dataset size; most importantly, in practice, they often exhibit lower variance compared to class labels. We propose a new neural network architecture based on siamese networks to incorporate both class and comparison labels in the same training pipeline, using Bradley-Terry and Thurstone loss functions. Our architecture leads to a significant improvement in predicting both class and comparison labels, increasing classification AUC by as much as 35% and comparison AUC by as much as 6% on several real-life datasets. We further show that, by incorporating comparisons, training from few samples becomes possible: a deep neural network of 5.9 million parameters trained on 80 images attains a 0.92 AUC when incorporating comparisons.


Assuntos
Bases de Dados Factuais/classificação
13.
Prog Retin Eye Res ; 72: 100759, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31048019

RESUMO

The advent of computer graphic processing units, improvement in mathematical models and availability of big data has allowed artificial intelligence (AI) using machine learning (ML) and deep learning (DL) techniques to achieve robust performance for broad applications in social-media, the internet of things, the automotive industry and healthcare. DL systems in particular provide improved capability in image, speech and motion recognition as well as in natural language processing. In medicine, significant progress of AI and DL systems has been demonstrated in image-centric specialties such as radiology, dermatology, pathology and ophthalmology. New studies, including pre-registered prospective clinical trials, have shown DL systems are accurate and effective in detecting diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD), retinopathy of prematurity, refractive error and in identifying cardiovascular risk factors and diseases, from digital fundus photographs. There is also increasing attention on the use of AI and DL systems in identifying disease features, progression and treatment response for retinal diseases such as neovascular AMD and diabetic macular edema using optical coherence tomography (OCT). Additionally, the application of ML to visual fields may be useful in detecting glaucoma progression. There are limited studies that incorporate clinical data including electronic health records, in AL and DL algorithms, and no prospective studies to demonstrate that AI and DL algorithms can predict the development of clinical eye disease. This article describes global eye disease burden, unmet needs and common conditions of public health importance for which AI and DL systems may be applicable. Technical and clinical aspects to build a DL system to address those needs, and the potential challenges for clinical adoption are discussed. AI, ML and DL will likely play a crucial role in clinical ophthalmology practice, with implications for screening, diagnosis and follow up of the major causes of vision impairment in the setting of ageing populations globally.

14.
Ophthalmol Retina ; 3(5): 444-450, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-31044738

RESUMO

PURPOSE: Accurate image-based ophthalmic diagnosis relies on fundus image clarity. This has important implications for the quality of ophthalmic diagnoses and for emerging methods such as telemedicine and computer-based image analysis. The purpose of this study was to implement a deep convolutional neural network (CNN) for automated assessment of fundus image quality in retinopathy of prematurity (ROP). DESIGN: Experimental study. PARTICIPANTS: Retinal fundus images were collected from preterm infants during routine ROP screenings. METHODS: Six thousand one hundred thirty-nine retinal fundus images were collected from 9 academic institutions. Each image was graded for quality (acceptable quality [AQ], possibly acceptable quality [PAQ], or not acceptable quality [NAQ]) by 3 independent experts. Quality was defined as the ability to assess an image confidently for the presence of ROP. Of the 6139 images, NAQ, PAQ, and AQ images represented 5.6%, 43.6%, and 50.8% of the image set, respectively. Because of low representation of NAQ images in the data set, images labeled NAQ were grouped into the PAQ category, and a binary CNN classifier was trained using 5-fold cross-validation on 4000 images. A test set of 2109 images was held out for final model evaluation. Additionally, 30 images were ranked from worst to best quality by 6 experts via pairwise comparisons, and the CNN's ability to rank quality, regardless of quality classification, was assessed. MAIN OUTCOME MEASURES: The CNN performance was evaluated using area under the receiver operating characteristic curve (AUC). A Spearman's rank correlation was calculated to evaluate the overall ability of the CNN to rank images from worst to best quality as compared with experts. RESULTS: The mean AUC for 5-fold cross-validation was 0.958 (standard deviation, 0.005) for the diagnosis of AQ versus PAQ images. The AUC was 0.965 for the test set. The Spearman's rank correlation coefficient on the set of 30 images was 0.90 as compared with the overall expert consensus ranking. CONCLUSIONS: This model accurately assessed retinal fundus image quality in a comparable manner with that of experts. This fully automated model has potential for application in clinical settings, telemedicine, and computer-based image analysis in ROP and for generalizability to other ophthalmic diseases.


Assuntos
Oftalmoscopia/métodos , Retinopatia da Prematuridade/diagnóstico por imagem , Algoritmos , Feminino , Humanos , Processamento de Imagem Assistida por Computador/métodos , Recém-Nascido , Masculino , Curva ROC
17.
Am J Ophthalmol ; 206: 161-167, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-30910517

RESUMO

PURPOSE: To assess time requirements for patient encounters and estimate after-hours demands of paper-based clinical workflows in ophthalmology. DESIGN: Time-and-motion study with a structured survey. METHODS: This study was conducted in a single academic ophthalmology department. A convenience sample consisted of 7 attending ophthalmologists from 6 subspecialties observed during 414 patient encounters for the time-motion analysis and 12 attending ophthalmologists for the survey. Outcome measurements consisted of total time spent by attending ophthalmologists per patient and time spent on documentation, examination, and talking with patients. The survey assessed time requirements of documentation-related activities performed outside of scheduled clinic hours. RESULTS: Among the 7 attending ophthalmologists observed (6 men and 1 woman), mean ± SD age 43.9 ± 7.1 years, during encounters with 414 patients (57.8 ± 24.6 years of age), total time spent per patient was 8.1 ± 4.8 minutes, with 2.8 ± 1.4 minutes (38%) for documentation, 1.2 ± 0.9 minutes (17%) for examination, and 3.3 ± 3.1 minutes (37%) for talking with patients. New patient evaluations required significantly more time than routine follow-up visits and postoperative visits. Higher clinical volumes were associated with less time per patient. Survey results indicated that paper-based documentation was associated with minimal after-hours work on weeknights and weekends. CONCLUSIONS: Paper-based documentation takes up a substantial portion of the total time spent for patient care in outpatient ophthalmology clinics but is associated with minimal after-hours work. Understanding paper-based clinical workflows may help inform targeted strategies for improving electronic health record use in ophthalmology.

19.
Ophthalmology ; 126(6): 783-791, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-30664893

RESUMO

PURPOSE: With the current wide adoption of electronic health records (EHRs) by ophthalmologists, there are widespread concerns about the amount of time spent using the EHR. The goal of this study was to examine how the amount of time spent using EHRs as well as related documentation behaviors changed 1 decade after EHR adoption. DESIGN: Single-center cohort study. PARTICIPANTS: Six hundred eighty-five thousand three hundred sixty-one office visits with 70 ophthalmology providers. METHODS: We calculated time spent using the EHR associated with each individual office visit using EHR audit logs and determined chart closure times and progress note length from secondary EHR data. We tracked and modeled how these metrics changed from 2006 to 2016 with linear mixed models. MAIN OUTCOME MEASURES: Minutes spent using the EHR associated with an office visit, chart closure time in hours from the office visit check-in time, and progress note length in characters. RESULTS: Median EHR time per office visit in 2006 was 4.2 minutes (interquartile range [IQR], 3.5 minutes), and increased to 6.4 minutes (IQR, 4.5 minutes) in 2016. Median chart closure time was 2.8 hours (IQR, 21.3 hours) in 2006 and decreased to 2.3 hours (IQR, 18.5 hours) in 2016. In 2006, median note length was 1530 characters (IQR, 1435 characters) and increased to 3838 characters (IQR, 2668.3 characters) in 2016. Linear mixed models found EHR time per office visit was 31.9±0.2% (P < 0.001) greater from 2014 through 2016 than from 2006 through 2010, chart closure time was 6.7±0.3 hours (P < 0.001) shorter from 2014 through 2016 versus 2006 through 2010, and note length was 1807.4±6.5 characters (P < 0.001) longer from 2014 through 2016 versus 2006 through 2010. CONCLUSIONS: After 1 decade of use, providers spend more time using the EHR for an office visit, generate longer notes, and close the chart faster. These changes are likely to represent increased time and documentation pressure for providers. Electronic health record redesign and new documentation regulations may help to address these issues.


Assuntos
Documentação/tendências , Registros Eletrônicos de Saúde/tendências , Oftalmologia/tendências , Optometria/tendências , Centros Médicos Acadêmicos , Estudos de Coortes , Documentação/estatística & dados numéricos , Registros Eletrônicos de Saúde/estatística & dados numéricos , Feminino , Pessoal de Saúde , Humanos , Masculino , Visita a Consultório Médico/estatística & dados numéricos , Oftalmologistas , Oftalmologia/estatística & dados numéricos , Optometristas , Optometria/estatística & dados numéricos , Fatores de Tempo
20.
Ophthalmology ; 126(3): 347-354, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30312629

RESUMO

PURPOSE: To improve clinic efficiency through development of an ophthalmology scheduling template developed using simulation models and electronic health record (EHR) data. DESIGN: We created a computer simulation model of 1 pediatric ophthalmologist's clinic using EHR timestamp data, which was used to develop a scheduling template based on appointment length (short, medium, or long). We assessed its impact on clinic efficiency after implementation in the practices of 5 different pediatric ophthalmologists. PARTICIPANTS: We observed and timed patient appointments in person (n = 120) and collected EHR timestamps for 2 years of appointments (n = 650). We calculated efficiency measures for 172 clinic sessions before implementation vs. 119 clinic sessions after implementation. METHODS: We validated clinic workflow timings calculated from EHR timestamps and the simulation models based on them with observed timings. From simulation tests, we developed a new scheduling template and evaluated it with efficiency metrics before vs. after implementation. MAIN OUTCOME MEASURES: Measurements of clinical efficiency (mean clinic volume, patient wait time, examination time, and clinic length). RESULTS: Mean physician examination time calculated from EHR timestamps was 13.8±8.2 minutes and was not statistically different from mean physician examination time from in-person observation (13.3±7.3 minutes; P = 0.7), suggesting that EHR timestamps are accurate. Mean patient wait time for the simulation model (31.2±10.9 minutes) was not statistically different from the observed mean patient wait times (32.6±25.3 minutes; P = 0.9), suggesting that simulation models are accurate. After implementation of the new scheduling template, all 5 pediatric ophthalmologists showed statistically significant improvements in clinic volume (mean increase of 1-3 patients/session; P ≤ 0.05 for 2 providers; P ≤ 0.008 for 3 providers), whereas 4 of 5 had improvements in mean patient wait time (average improvements of 3-4 minutes/patient; statistically significant for 2 providers, P ≤ 0.008). All of the ophthalmologists' examination times remained the same before and after implementation. CONCLUSIONS: Simulation models based on big data from EHRs can test clinic changes before real-life implementation. A scheduling template using predicted appointment length improves clinic efficiency and may generalize to other clinics. Electronic health records have potential to become tools for supporting clinic operations improvement.


Assuntos
Centros Médicos Acadêmicos/estatística & dados numéricos , Agendamento de Consultas , Eficiência Organizacional/estatística & dados numéricos , Registros Eletrônicos de Saúde/estatística & dados numéricos , Visita a Consultório Médico/estatística & dados numéricos , Oftalmologia/estatística & dados numéricos , Centros Médicos Acadêmicos/organização & administração , Adolescente , Criança , Pré-Escolar , Simulação por Computador , Humanos , Lactente , Recém-Nascido , Oftalmologia/organização & administração , Fatores de Tempo , Fluxo de Trabalho
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