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1.
J Gen Intern Med ; 29(8): 1105-12, 2014 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-24610308

RESUMO

BACKGROUND: To improve and learn from patient outcomes, particularly under new care models such as Accountable Care Organizations and Patient-Centered Medical Homes, requires establishing systems for follow-up and feedback. OBJECTIVE: To provide post-visit feedback to physicians on patient outcomes following acute care visits. DESIGN: A three-phase cross-sectional study [live follow-up call three weeks after acute care visits (baseline), one week post-visit live call, and one week post-visit interactive voice response system (IVRS) call] with three patient cohorts was conducted. A family medicine clinic and an HIV clinic participated in all three phases, and a cerebral palsy clinic participated in the first two phases. Patients answered questions about symptom improvement, medication problems, and interactions with the healthcare system. PATIENTS: A total of 616 patients were included: 142 from Phase 1, 352 from Phase 2 and 122 from Phase 3. MAIN MEASURES: Primary outcomes included: problem resolution, provider satisfaction with the system, and comparison of IVRS with live calls made by research staff. KEY RESULTS: During both live follow-up phases, at least 96% of patients who were reached completed the call compared to only 48% for the IVRS phase. At baseline, 98 of 113 (88%) patients reported improvement, as well as 167 of 196 (85%) in the live one-week follow-up. In the one-week IVRS phase, 25 of 39 (64%) reported improvement. In all phases, the majority of patients in both the improved and unimproved groups had not contacted their provider or another provider. While 63% of providers stated they wanted to receive patient feedback, they varied in the extent to which they used the feedback reports. CONCLUSIONS: Many patients who do not improve as expected do not take action to further address unresolved problems. Systematic follow-up/feedback mechanisms can potentially identify and connect such patients to needed care.


Assuntos
Assistência Ambulatorial/tendências , Continuidade da Assistência ao Paciente/tendências , Serviços Médicos de Emergência/tendências , Preferência do Paciente , Interface para o Reconhecimento da Fala , Telefone , Adulto , Idoso , Idoso de 80 Anos ou mais , Assistência Ambulatorial/métodos , Estudos de Coortes , Estudos Transversais , Serviços Médicos de Emergência/métodos , Retroalimentação Psicológica , Feminino , Seguimentos , Humanos , Masculino , Pessoa de Meia-Idade , Autorrelato/normas , Interface para o Reconhecimento da Fala/tendências , Telefone/tendências
2.
J Med Syst ; 37(2): 9905, 2013 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-23340825

RESUMO

In primary care settings, follow-up regarding the outcome of acute outpatient visits is largely absent. We sought to develop an automated interactive voice response system (IVRS) for patient follow-up with feedback to providers capable of interfacing with multiple pre-existing electronic medical records (EMRs). A system was designed to extract data from EMRs, integrate with the IVRS, call patients for follow-up, and provide a feedback report to providers. Challenges during the development process were analyzed and summarized. The components of the technological solution and details of its implementation are reported. Lessons learned include: (1) Modular utilization of system components is often needed to adapt to specific clinic workflow and patient population needs (2) Understanding the local telephony environment greatly impacts development and is critical to success, and (3) Ample time for development of the IVRS questionnaire (mapping all branching paths) and speech recognition tuning (sensitivity, use of barge-in tuning, use of "known voice") is needed. With proper attention to design and development, modular follow-up and feedback systems can be integrated into existing EMR systems providing the benefits of IVRS follow-up to patients and providers across diverse practice settings.


Assuntos
Retroalimentação , Atenção Primária à Saúde , Interface para o Reconhecimento da Fala , Interface Usuário-Computador , Registros Eletrônicos de Saúde , Humanos
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