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1.
Health Serv Res ; 56(5): 755-765, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-34498259

RESUMO

OBJECTIVE: To assess the prevalence of patient administrative tasks and whether they are associated with delayed and/or foregone care. DATA SOURCE: March 2019 Health Reform Monitoring Survey. STUDY DESIGN: We assess the prevalence of five common patient administrative tasks-scheduling, obtaining information, prior authorizations, resolving billing issues, and resolving premium problems-and associated administrative burden, defined as delayed and/or foregone care. Using multivariate logistic models, we examined the association of demographic characteristics with odds of doing tasks and experiencing burdens. Our outcome variables were five common types of administrative tasks as well as composite measures of any task, any delayed care, any foregone care, and any burden (combined delayed/foregone), respectively. DATA COLLECTION: We developed and administered survey questions to a nationally representative sample of insured, nonelderly adults (n = 4155). PRINCIPAL FINDINGS: The survey completion rate was 62%. Seventy-three percent of respondents reported performing at least one administrative task in the past year. About one in three task-doers, or 24.4% of respondents overall, reported delayed or foregone care due to an administrative task: Adjusted for demographics, disability status had the strongest association with administrative tasks (adjusted odds ratio [OR] 2.91, p < 0.001) and burden (adjusted OR 1.66, p < 0.001). Being a woman was associated with doing administrative tasks (adjusted OR 2.19, p < 0.001). Being a college graduate was associated with performing an administrative task (adjusted OR 2.79, p < 0.001), while higher income was associated with fewer subsequent burdens (adjusted OR 0.55, p < 0.01). CONCLUSIONS: Patients frequently do administrative tasks that can create burdens resulting in delayed/foregone care. The prevalence of delayed/foregone care due to administrative tasks is comparable to similar estimates of cost-related barriers to care. Demographic disparities in burden warrant further attention. Enhancing measurement of patient administrative work and associated burdens may identify opportunities for assessing quality, value, and patient experience.


Assuntos
Administração de Serviços de Saúde , Pacientes/psicologia , Pacientes/estatística & dados numéricos , Adolescente , Adulto , Agendamento de Consultas , Informática Aplicada à Saúde dos Consumidores/economia , Informática Aplicada à Saúde dos Consumidores/estatística & dados numéricos , Custo Compartilhado de Seguro/economia , Custo Compartilhado de Seguro/estatística & dados numéricos , Feminino , Acessibilidade aos Serviços de Saúde , Nível de Saúde , Humanos , Comportamento de Busca de Informação , Masculino , Pessoa de Meia-Idade , Autorização Prévia/economia , Autorização Prévia/estatística & dados numéricos , Fatores Sociodemográficos , Fatores de Tempo , Tempo para o Tratamento , Adulto Jovem
2.
Yearb Med Inform ; 28(1): 158-164, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31419828

RESUMO

OBJECTIVES: To present the breadth and depth of Consumer Health Informatics (CHI) initiatives and in particular, identify areas to further enhance such solutions with the incorporation of advances in artificial intelligence (AI). METHODS: A literature review was conducted. Inclusion criteria focused on barriers and facilitators as well as key milestones for CHI over the last 10 years. In addition, significant international initiatives in regions and /or countries and opportunities to incorporate the advances of AI also made up the inclusion criteria. Exclusion criteria included factors that made reach/range of solutions to individuals or groups of individuals less than 50 people. Journals in Medline were accessed as well as the grey literature. RESULTS: 200 papers were identified but this was narrowed to 25 due to repetitions and similarities of the types of solutions presented. From this, it was possible to identify key barriers and facilitators including: socio-political factors, financial factors, infrastructure, as well as levels of health literacy. CONCLUSIONS: The relatively nascent domain of CHI has developed and is growing. Full benefits will only be realized when more precision solutions that incorporate AI advances will be designed. The example of RxPredict is provided as a case vignette to illustrate.


Assuntos
Informática Aplicada à Saúde dos Consumidores , Telemedicina , Inteligência Artificial , Informática Aplicada à Saúde dos Consumidores/economia , Informática Aplicada à Saúde dos Consumidores/tendências , Registros Eletrônicos de Saúde , Portais do Paciente
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