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1.
JAMA ; 2024 Sep 04.
Artigo em Inglês | MEDLINE | ID: mdl-39230911

RESUMO

This Viewpoint discusses the bias that exists in artificial intelligence (AI) algorithms used in health care despite recent federal rules to prohibit discriminatory outcomes from AI and recommends ways in which health care facilities, AI developers, and regulators could share responsibilities and actions to address bias.

3.
JAMA ; 332(10): 787-788, 2024 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-39133493

RESUMO

This Viewpoint highlights the potential for artificial intelligence (AI) health care tools to introduce unintended patient harm; calls for an efficient, rigorous approach to AI testing and certification that is the shared responsibility of developers and users; and makes recommendations to inform such an approach.


Assuntos
Inteligência Artificial , Certificação , Saúde Digital , Informática Médica , Humanos , Inteligência Artificial/legislação & jurisprudência , Inteligência Artificial/normas , Informática Médica/legislação & jurisprudência , Informática Médica/normas , Estados Unidos , Segurança do Paciente/normas , Saúde Digital/legislação & jurisprudência , Saúde Digital/normas
4.
J Am Med Inform Assoc ; 31(10): 2246-2254, 2024 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-39018492

RESUMO

OBJECTIVES: Physician burnout in the US has reached crisis levels, with one source identified as extensive after-hours documentation work in the electronic health record (EHR). Evidence has illustrated that physician preferences for after-hours work vary, such that after-hours work may not be universally burdensome. Our objectives were to analyze variation in preferences for after-hours documentation and assess if preferences mediate the relationship between after-hours documentation time and burnout. MATERIALS AND METHODS: We combined EHR active use data capturing physicians' hourly documentation work with survey data capturing documentation preferences and burnout. Our sample included 318 ambulatory physicians at MedStar Health. We conducted a mediation analysis to estimate if and how preferences mediated the relationship between after-hours documentation time and burnout. Our primary outcome was physician-reported burnout. We measured preferences for after-hours documentation work via a novel survey instrument (Burden Scenarios Assessment). We measured after-hours documentation time in the EHR as the total active time respondents spent documenting between 7 pm and 3 am. RESULTS: Physician preferences varied, with completing clinical documentation after clinic hours while at home the scenario rated most burdensome (52.8% of physicians), followed by dealing with prior authorization (49.5% of physicians). In mediation analyses, preferences partially mediated the relationship between after-hours documentation time and burnout. DISCUSSION: Physician preferences regarding EHR-based work play an important role in the relationship between after-hours documentation time and burnout. CONCLUSION: Studies of EHR work and burnout should incorporate preferences, and operational leaders should assess preferences to better target interventions aimed at EHR-based contributors to burnout.


Assuntos
Esgotamento Profissional , Documentação , Registros Eletrônicos de Saúde , Médicos , Humanos , Médicos/psicologia , Feminino , Masculino , Adulto , Fatores de Tempo , Pessoa de Meia-Idade , Plantão Médico , Atitude do Pessoal de Saúde , Inquéritos e Questionários , Assistência Ambulatorial
6.
JAMA Pediatr ; 178(7): 637-638, 2024 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-38739385

RESUMO

This Viewpoint provides recommendations and stakeholder actions to support safe and equitable use of artificial intelligence (AI) in pediatric clinical settings.


Assuntos
Inteligência Artificial , Pediatria , Humanos , Criança
7.
J Patient Saf ; 20(5): 345-351, 2024 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-38739020

RESUMO

OBJECTIVES: The purpose of this study is to understand how patient safety professionals from healthcare facilities and patient safety organizations develop patient safety interventions and the resources used to support intervention development. METHODS: Semistructured interviews were conducted with patient safety professionals at nine healthcare facilities and nine patient safety organizations. Interview data were qualitatively analyzed, and findings were organized by the following: patient safety solutions and interventions, use of external databases, and evaluation of patient safety solutions. RESULTS: Development of patient safety interventions across healthcare facilities and patient safety organizations was similar and included literature searches, internal brainstorming, and interviews. Nearly all patient safety professionals at healthcare facilities reported contacting colleagues at other healthcare facilities to learn about similar safety issues and potential interventions. Additionally, less than half of patient safety professionals at healthcare facilities and patient safety organizations interviewed report data to publicly available patient safety databases. Finally, most patient safety professionals at healthcare facilities and patient safety organizations stated that they evaluate the effectiveness of patient safety interventions; however, they mentioned methods that may be less rigorous including audits, self-reporting, and subjective judgment. CONCLUSIONS: Patient safety professionals often utilize similar methods and resources to develop and evaluate patient safety interventions; however, many of these efforts are not coordinated across healthcare organizations and could benefit from working collectively in a systematic fashion. Additionally, healthcare facilities and patient safety organizations face similar challenges and there are several opportunities for optimization on a national level that may improve patient safety.


Assuntos
Entrevistas como Assunto , Liderança , Segurança do Paciente , Gestão da Segurança , Humanos , Gestão da Segurança/organização & administração
9.
J Imaging Inform Med ; 2024 Mar 19.
Artigo em Inglês | MEDLINE | ID: mdl-38504083

RESUMO

Radiologist interruptions, though often necessary, can be disruptive. Prior literature has shown interruptions to be frequent, occurring during cases, and predominantly through synchronous communication methods such as phone or in person causing significant disengagement from the study being read. Asynchronous communication methods are now more widely available in hospital systems such as ours. Considering the increasing use of asynchronous communication methods, we conducted an observational study to understand the evolving nature of radiology interruptions. We hypothesize that compared to interruptions occurring through synchronous methods, interruptions via asynchronous methods reduce the disruptive nature of interruptions by occurring between cases, being shorter, and less severe. During standard weekday hours, 30 radiologists (14 attendings, 12 residents, and 4 fellows) were directly observed for approximately 90-min sessions across three different reading rooms (body, neuroradiology, general). The frequency of interruptions was documented including characteristics such as timing, severity, method, and length. Two hundred twenty-five interruptions (43 Teams, 47 phone, 89 in-person, 46 other) occurred, averaging 2 min and 5 s with 5.2 interruptions per hour. Microsoft Teams interruptions averaged 1 min 12 s with only 60.5% during cases. In-person interruptions averaged 2 min 12 s with 82% during cases. Phone interruptions averaged 2 min and 48 s with 97.9% during cases. A substantial portion of reading room interruptions occur via predominantly asynchronous communication tools, a new development compared to prior literature. Interruptions via predominantly asynchronous communications tools are shorter and less likely to occur during cases. In our practice, we are developing tools and mechanisms to promote asynchronous communication to harness these benefits.

10.
JAMA Health Forum ; 5(2): e235514, 2024 Feb 02.
Artigo em Inglês | MEDLINE | ID: mdl-38393719

RESUMO

This Viewpoint offers 3 recommendations for health care organizations and other stakeholders to consider as part of the Health and Human Services' artificial intelligence safety program.


Assuntos
Inteligência Artificial , Segurança do Paciente , Humanos , Atenção à Saúde
11.
Artigo em Inglês | MEDLINE | ID: mdl-38131730

RESUMO

To understand whether patient safety and human factors are considered in healthcare technology procurement, we analyzed the case of infusion pumps as their use critically affects patient safety. We reviewed infusion pump procurements in the Spanish Public Sector Procurement Database. Sixty-three batches in 29 tenders for supplying 12.224 volumetric and syringe infusion pumps and consumables for an overall budget of EUR 30.4 M were identified and reviewed. Concepts related to "ease of use" were identified in the selection requirements of 35 (55.6%) batches, as part of the criteria for the selection of pumps in 23 (36.5%) batches, related to "intuitiveness" in the selection requirements of 35 (55.6%) batches, and in the criteria in 10 (15.9%) batches. No method to evaluate the ease of use, intuitiveness, or usability was mentioned. A review of the procurement teams responsible for the evaluation of the tenders showed no reported human factors or patient safety expertise. We conclude that infusion pump procurement considers usability as a relevant criterion for selection. However, no human factor experts nor specific methods for evaluation of the technology in this field are usually defined. Potential room for refining the selection of healthcare technology to improve patient safety is detected.


Assuntos
Bombas de Infusão , Segurança do Paciente , Humanos , Bases de Dados Factuais , Instalações de Saúde , Espanha
12.
Sci Rep ; 13(1): 18354, 2023 10 26.
Artigo em Inglês | MEDLINE | ID: mdl-37884577

RESUMO

Patient safety reporting systems give healthcare provider staff the ability to report medication related safety events and errors; however, many of these reports go unanalyzed and safety hazards go undetected. The objective of this study is to examine whether natural language processing can be used to better categorize medication related patient safety event reports. 3,861 medication related patient safety event reports that were previously annotated using a consolidated medication error taxonomy were used to develop three models using the following algorithms: (1) logistic regression, (2) elastic net, and (3) XGBoost. After development, models were tested, and model performance was analyzed. We found the XGBoost model performed best across all medication error categories. 'Wrong Drug', 'Wrong Dosage Form or Technique or Route', and 'Improper Dose/Dose Omission' categories performed best across the three models. In addition, we identified five words most closely associated with each medication error category and which medication error categories were most likely to co-occur. Machine learning techniques offer a semi-automated method for identifying specific medication error types from the free text of patient safety event reports. These algorithms have the potential to improve the categorization of medication related patient safety event reports which may lead to better identification of important medication safety patterns and trends.


Assuntos
Erros de Medicação , Segurança do Paciente , Humanos , Modelos Logísticos , Mineração de Dados , Relatório de Pesquisa
13.
J Gen Intern Med ; 38(Suppl 4): 946-948, 2023 10.
Artigo em Inglês | MEDLINE | ID: mdl-37798586
15.
JAMIA Open ; 6(3): ooad066, 2023 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-37575956

RESUMO

Text messages used by healthcare organizations to communicate with patients have known limitations for certain populations, especially older adults. This study analyzed text message interactions with over 17 000 patients aged 65 and older during the initial phase of the COVID-19 vaccination campaign. We coded the responses of 4247 patients who responded to this outreach to understand issues they experienced with the text message system. Our analysis highlighted areas for technology improvement and the need for more robust strategies to effectively reach older populations.

16.
J Am Med Inform Assoc ; 30(10): 1717-1719, 2023 09 25.
Artigo em Inglês | MEDLINE | ID: mdl-37468440

RESUMO

OBJECTIVE: To determine whether the Office of the National Coordinator's policy change restricting the use of "gag clauses" in contracts between electronic health record (EHR) vendors and healthcare facilities increased the prevalence of screenshots in peer-reviewed literature. MATERIALS AND METHODS: We reviewed EHR usability and safety-related peer-reviewed journal articles from 2015 to 2023 and quantified the number of articles containing screenshots. For those that did not contain screenshots, we identified whether they would have benefited from screenshots. RESULTS: When gag clauses were permitted 6 of 79 (7.6%) of articles contained screenshots and 8 (10.1%) would have benefited from screenshots. When gag clauses were restricted 3 of 40 (7.5%) contained screenshots and 8 (20%) would have benefited from screenshots. DISCUSSION: The policy change does not appear to have an impact on the prevalence of screenshots in peer-reviewed literature. CONCLUSIONS: Additional steps are necessary to promote the use of screenshots in peer-reviewed literature.


Assuntos
Comércio , Registros Eletrônicos de Saúde , Prevalência , Instalações de Saúde
17.
JAMA Netw Open ; 6(7): e2321955, 2023 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-37410468

RESUMO

This cross-sectional study assesses variation in the provision of telemedicine services among primary care physicians and quantifies the extent to which this variation may be explained by the individual physician vs temporal, patient, or visit factors.


Assuntos
Médicos , Telemedicina , Humanos
18.
Health Policy Technol ; 12(3): 100772, 2023 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-37389330

RESUMO

Objectives: The objective of this study is to quantify how long patients took to complete their rescheduled primary care appointment pre-pandemic (2019) and during an initial pandemic period (2020). In doing so, the study evaluates telehealth's role in helping primary care patients - particularly in patients with chronic conditions - withstand COVID's significant disruption in care. Methods: Cancelled and completed primary care appointments for adult patients were extracted from the beginning of the pandemic (March 1 to July 31, 2020) and a similar period pre-pandemic (March 1 to July 31, 2019). Days to the subsequent completed visit after cancellation (through June 30, 2021) and appointment modality (in-person, phone, video) were examined. Statistical testing was done to determine statistical significance, and a linear regression was run to control for effects of other study variables. Results: Pre-pandemic patients with chronic conditions needed 52.3 days on average to reschedule their cancelled in-person appointment. During the early pandemic period, chronic condition patients who saw their provider in-person took on average 78.8 days. During the same pre-pandemic period, patients with chronic conditions had their average wait time decrease to 51.5 days when rescheduling via telehealth. These differences were similar for patients without chronic conditions. Conclusions: This analysis shows that telehealth created return to care timelines comparable to the pre-pandemic period which is especially important for patients with chronic conditions. Public interest summary: Telehealth visits (i.e., talking with a physician via phone or video call) help patients continue to receive the medical care they need - especially during disruptive periods such as the COVID pandemic. Access to telehealth is the strongest predictor in determining how soon a patient will complete their reschedule primary care appointment. Because telehealth is so important, health care providers and systems need to continue to offer patients the ability to talk with their physician via phone or video call.

20.
JAMA Netw Open ; 6(4): e238399, 2023 04 03.
Artigo em Inglês | MEDLINE | ID: mdl-37058308

RESUMO

This qualitative study analyzes closed legal claims data to determine whether problems with electronic health records are associated with diagnostic errors, in which part of the diagnostic process errors occur, and the specific types of errors that occur.


Assuntos
Registros Eletrônicos de Saúde , Revisão da Utilização de Seguros , Humanos , Erros de Diagnóstico/prevenção & controle , Assistência Ambulatorial
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