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1.
Contemp Clin Trials ; 124: 107039, 2023 01.
Artigo em Inglês | MEDLINE | ID: mdl-36470556

RESUMO

BACKGROUND: Food insecurity is associated with worse glycemic management for individuals with type 2 diabetes mellitus (T2DM), but whether medically tailored meals (MTM), a food insecurity intervention, can improve glycemic management is unclear. OBJECTIVE: To describe the protocol for a trial assessing whether an MTM plus lifestyle intervention improves hemoglobin A1c (HbA1c) and participant-reported outcomes, relative to a food subsidy (money that can be spent on foods participants choose), for adults with both T2DM and food insecurity. METHODS: The Food as Medicine for Diabetes (FAME-D) randomized clinical trial (goal n = 200) is a pragmatic trial with an active comparator. Participants, who will have T2DM and report food insecurity, will be randomly assigned to a 6-month MTM plus telephone-delivered lifestyle change intervention, or a 6-month food subsidy ($40/month). The primary outcome is HbA1c at 6 months. Secondary outcomes include HbA1c at 12 months to assess whether the intervention effect (if any) is sustained, along with weight, food insecurity, diabetes distress, and health-related quality of life. Qualitative analyses of semi-structured interviews will help understand why, how, and under what circumstances the intervention achieved its observed results. CONCLUSION: Results from FAME-D will help inform clinical management of food insecurity when it co-occurs with T2DM. Further, results may be useful as healthcare payors are considering coverage for MTM interventions. CLINICALTRIALS: gov: NCT04828785.


Assuntos
Diabetes Mellitus Tipo 2 , Adulto , Humanos , Diabetes Mellitus Tipo 2/terapia , Insegurança Alimentar , Hemoglobinas Glicadas , Refeições , Qualidade de Vida , Ensaios Clínicos Controlados Aleatórios como Assunto , Ensaios Clínicos Pragmáticos como Assunto
2.
J Clin Nurs ; 32(1-2): 3-30, 2023 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-35403322

RESUMO

BACKGROUND: Healthcare organisations and teams perform improvement activities to facilitate high-quality healthcare. The use of an improvement coach who provides support and guidance to the healthcare team may facilitate improvement activities; however, no systematic review exists on the facilitators and barriers to implementing an improvement coach. AIMS: We conducted a qualitative evidence synthesis to examine the facilitators and barriers to the implementation of improvement coaching. METHODS: We searched MEDLINE® , Embase and CINAHL. The final search was in March 2021. The screening eligibility criteria included the following: interdisciplinary team receiving the coaching, improvement coaching, designs with a qualitative component and primary purpose of evaluating practice facilitation in OECD countries. An ecologically-informed consolidated framework for implementation research (CFIR) served as the framework for coding. Patterns of barriers and facilitators across domains were identified through matrix analysis. Risk of bias was assessed using Critical Appraisal Skills Program. PRISMA reporting guidelines served as a guide for reporting this review. RESULTS: Nineteen studies with a qualitative component met the inclusion criteria. Four themes of barriers and facilitators crossed multiple CFIR domains: adaptability (e.g. making adjustments to the project; process, or approach); knowledge and skills (e.g. understanding of content and process for the project); engagement (e.g. willingness to be involved in the process) and resources (e.g. assets required to complete the improvement process). CONCLUSION: Improvement coaching is a complex intervention that influences the context, healthcare team being coached and improvement activities. Improvement coaches should understand how to minimise barriers and promote facilitators that are unique to each improvement project across the domains. Limitations of the study are related to the nature of the intervention including potential publication bias given quality improvement focus; the variety of terms similar to improvement coaching or selection of framework.


Assuntos
Atenção à Saúde , Tutoria , Humanos , Equipe de Assistência ao Paciente , Pesquisa Qualitativa
3.
J Med Internet Res ; 24(8): e37100, 2022 08 26.
Artigo em Inglês | MEDLINE | ID: mdl-36018711

RESUMO

BACKGROUND: Extensive literature support telehealth as a supplement or adjunct to in-person care for the management of chronic conditions such as congestive heart failure (CHF) and type 2 diabetes mellitus (T2DM). Evidence is needed to support the use of telehealth as an equivalent and equitable replacement for in-person care and to assess potential adverse effects. OBJECTIVE: We conducted a systematic review to address the following question: among adults, what is the effect of synchronous telehealth (real-time response among individuals via phone or phone and video) compared with in-person care (or compared with phone, if synchronous video care) for chronic management of CHF, chronic obstructive pulmonary disease, and T2DM on key disease-specific clinical outcomes and health care use? METHODS: We followed systematic review methodologies and searched two databases (MEDLINE and Embase). We included randomized or quasi-experimental studies that evaluated the effect of synchronously delivered telehealth for relevant chronic conditions that occurred over ≥2 encounters and in which some or all in-person care was supplanted by care delivered via phone or video. We assessed the bias using the Cochrane Effective Practice and Organization of Care risk of bias (ROB) tool and the certainty of evidence using the Grading of Recommendations Assessment, Development, and Evaluation. We described the findings narratively and did not conduct meta-analysis owing to the small number of studies and the conceptual heterogeneity of the identified interventions. RESULTS: We identified 8662 studies, and 129 (1.49%) were reviewed at the full-text stage. In total, 3.9% (5/129) of the articles were retained for data extraction, all of which (5/5, 100%) were randomized controlled trials. The CHF study (1/5, 20%) was found to have high ROB and randomized patients (n=210) to receive quarterly automated asynchronous web-based review and follow-up of telemetry data versus synchronous personal follow-up (in-person vs phone-based) for 1 year. A 3-way comparison across study arms found no significant differences in clinical outcomes. Overall, 80% (4/5) of the studies (n=466) evaluated synchronous care for patients with T2DM (ROB was judged to be low for 2, 50% of studies and high for 2, 50% of studies). In total, 20% (1/5) of the studies were adequately powered to assess the difference in glycosylated hemoglobin level between groups; however, no significant difference was found. Intervention design varied greatly from remote monitoring of blood glucose combined with video versus in-person visits to an endocrinology clinic to a brief, 3-week remote intervention to stabilize uncontrolled diabetes. No articles were identified for chronic obstructive pulmonary disease. CONCLUSIONS: This review found few studies with a variety of designs and interventions that used telehealth as a replacement for in-person care. Future research should consider including observational studies and studies on additional highly prevalent chronic diseases.


Assuntos
Diabetes Mellitus Tipo 2 , Insuficiência Cardíaca , Doença Pulmonar Obstrutiva Crônica , Telemedicina , Envio de Mensagens de Texto , Adulto , Doença Crônica , Humanos
4.
J Gen Intern Med ; 37(4): 885-899, 2022 03.
Artigo em Inglês | MEDLINE | ID: mdl-34981354

RESUMO

BACKGROUND: A culture of improvement is an important feature of high-quality health care systems. However, health care teams often need support to translate quality improvement (QI) activities into practice. One method of support is consultation from a QI coach. The literature suggests that coaching interventions have a positive impact on clinical outcomes. However, the impact of coaching on specific process outcomes, like adoption of clinical care activities, is unknown. Identifying the process outcomes for which QI coaching is most effective could provide specific guidance on when to employ this strategy. METHODS: We searched multiple databases from inception through July 2021. Studies that addressed the effects of QI coaching on process of care outcomes were included. Two reviewers independently extracted study characteristics and assessed risk of bias. Certainty of evidence was assessed using GRADE. RESULTS: We identified 1983 articles, of which 23 cluster-randomized trials met eligibility criteria. All but two took place in a primary care setting. Overall, interventions typically targeted multiple simultaneous processes of care activities. We found that coaching probably has a beneficial effect on composite process of care outcomes (n = 9) and ordering of labs and vital signs (n = 6), and possibly has a beneficial effect on changes in organizational process of care (n = 5), appropriate documentation (n = 5), and delivery of appropriate counseling (n = 3). We did not perform meta-analyses because of conceptual heterogeneity around intervention design and outcomes; rather, we synthesized the data narratively. Due to imprecision, inconsistency, and high risk of bias of the included studies, we judged the certainty of these results as low or very low. CONCLUSION: QI coaching interventions may affect certain processes of care activities such as ordering of labs and vital signs. Future research that advances the identification of when QI coaching is most beneficial for health care teams seeking to implement improvement processes in pursuit of high-quality care will support efficient use of QI resources. PROTOCOL REGISTRATION: This study was registered and followed a published protocol (PROSPERO: CRD42020165069).


Assuntos
Tutoria , Melhoria de Qualidade , Atenção à Saúde , Serviços de Saúde , Humanos , Qualidade da Assistência à Saúde
5.
Sci Diabetes Self Manag Care ; 47(2): 153-163, 2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-34078177

RESUMO

PURPOSE: The purpose of the study was to explore patient perspectives on socioeconomic barriers related to diabetes self-management and interventions to address these barriers. METHODS: Focus groups (n = 8) were conducted with a diverse sample of adults with type 2 diabetes (T2D; n = 53). Researchers used a semistructured moderator guide; focus groups were audio recorded and transcribed verbatim. Researchers employed the constant comparison method for qualitative content analysis and utilized Atlas.ti (Version 8.1.1) to digitalize the analytic process. RESULTS: Findings revealed 3 primary themes: (1) Existing food and nutrition resources are insufficient to support healthy eating for diabetes; (2) healthy eating is critical for diabetes management, but socioeconomic circumstances make doing so challenging; and (3) participants supported several broad categories of preferred intervention strategies. First, they endorsed lifestyle intervention informed by socioeconomic status (SES; eg, focusing on food resource management, sensitive health coaching and nutritional counseling). Next, they expressed enthusiasm for group-based learning opportunities, such as cooking classes and support groups with similar SES peers. Finally, they suggested healthy food access resources. CONCLUSIONS: Participant suggestions should be incorporated into intervention development. Ultimately, these interventional strategies should be tested and refined to help improve health for individuals with type 2 diabetes.


Assuntos
Diabetes Mellitus Tipo 2 , Adulto , Diabetes Mellitus Tipo 2/terapia , Grupos Focais , Comportamentos Relacionados com a Saúde , Humanos , Estilo de Vida , Classe Social
6.
Eval Program Plann ; 39: 51-6, 2013 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-23669647

RESUMO

OBJECTIVES: Determine the cost of implementing a call center-based cancer screening navigator program. METHODS: Social service call centers in Houston and Weslaco, TX, assessed cancer risks and implemented cancer screening promotion and navigation. Micro costing was used to estimate the program costs. Staff logs and call records tracked personnel time and material costs, including a standard 30% overhead rate. Sensitivity analysis examined the effect of varying uncertain cost parameters. Scale effects were simulated for larger population coverage. RESULTS: The total cost to recruit and navigate 732 persons, out of 2933 individuals who called the center was $215,847. The participant time cost was $19,503, and the personnel cost was $116,523. The cost per navigated participant was $295 (95% CI, $290.56-$298.07). The average cost per participant for recruitment and referral only, was $36 (95% CI, $34.9-$36.9). Average cost declines to $34 for recruitment and referral, and to $225 for recruitment, referral, and navigation when the number of participants increases to 15,000 individuals. CONCLUSIONS: Expanding 2-1-1 referral services with opportunistic cancer screening promotion takes advantage of existing infrastructure but requires substantial additional staff time, participant time, and budget. Cost estimation is the first step in a full economic evaluation and informs program planners and decision-makers on the resource and budgetary requirements of this innovative strategy for increasing cancer screening in low income communities.


Assuntos
Custos de Cuidados de Saúde , Linhas Diretas/economia , Programas de Rastreamento/economia , Neoplasias/prevenção & controle , Navegação de Pacientes/economia , Adolescente , Adulto , Idoso , Estudos de Casos e Controles , Feminino , Implementação de Plano de Saúde/economia , Linhas Diretas/organização & administração , Humanos , Masculino , Programas de Rastreamento/organização & administração , Pessoa de Meia-Idade , Modelos Econométricos , Navegação de Pacientes/organização & administração , Avaliação de Programas e Projetos de Saúde/economia , Encaminhamento e Consulta/economia , Encaminhamento e Consulta/organização & administração , Medição de Risco , Texas
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