RESUMO
BACKGROUND: Patients with chronic conditions routinely see multiple outpatient providers, who may or may not communicate with each other. Gaps in information across providers caring for the same patient can lead to harm for patients. However, the exact causes and consequences of healthcare fragmentation are not understood well enough to design interventions to address them. OBJECTIVE: We sought to elicit patients' and providers' views on the causes and consequences of healthcare fragmentation. DESIGN AND PARTICIPANTS: We conducted a qualitative study with focus groups of patients and, separately, of providers (attending physicians and nurse practitioners) at an academic hospital-based primary care practice in New York City in June-August 2017. Patient participants were English-speaking adults with ≥ 2 chronic conditions. APPROACH: Each focus group lasted 1 h and asked the same two questions: "Why do you think some patients receive care from many different providers and others do not?" and "What do you think happens as a result of patients receiving care from many different providers?" Data collection continued until a point of data saturation was reached. Thematic analysis was used to identify themes and subthemes. KEY RESULTS: We conducted 6 focus groups with a total of 46 participants (25 patients and 21 providers). Study participants identified 41 unique causes of fragmentation, which originate from 4 different levels of the healthcare system (patient, provider, healthcare organization, and healthcare environment); most causes were not related to medical need. Participants also identified 24 unique consequences of fragmentation, of which 3 were desirable and 21 were undesirable. CONCLUSIONS: The results of this study offer a granular roadmap for how to decrease healthcare fragmentation. The large number and severity of negative consequences (including medical errors, misdiagnosis, increased cost, and provider burnout) underscore the urgent need for interventions to address this problem directly.
Assuntos
Instituições de Assistência Ambulatorial/normas , Atitude do Pessoal de Saúde , Continuidade da Assistência ao Paciente/normas , Pessoal de Saúde/normas , Participação do Paciente , Pesquisa Qualitativa , Idoso , Feminino , Grupos Focais/normas , Pessoal de Saúde/psicologia , Humanos , Masculino , Pessoa de Meia-Idade , Participação do Paciente/psicologiaRESUMO
OBJECTIVES: To assess the utility of genomic testing in risk-stratifying Black patients with low and intermediate risk prostate cancer. METHODS: We retrospectively identified 63 Black men deemed eligible for active surveillance based on National Comprehensive Cancer Network (NCCN) guidelines, who underwent OncotypeDx Genomic Prostate Score testing between April 2016 and July 2020. Nonparametric statistical testing was used to compare relevant features between patients reclassified to a higher NCCN risk after genomic testing and those who were not reclassified. RESULTS: The median age was 66 years and median pre-biopsy PSA was 7.3. Initial risk classifications were: very low risk: 7 (11.1%), low risk: 24(38.1%), favorable intermediate risk: 31(49.2%), and unfavorable intermediate risk: 1 (1.6%). Overall, NCCN risk classifications after Genomic Prostate Score testing were significantly higher than initial classifications (P=.003, Wilcoxon signed-rank). Among patients with discordant risk designations, 28(28/40, 70%) were reclassified to a higher NCCN risk after genomic testing. A pre-biopsy prostate specific antigen of greater than 10 did not have significantly higher odds of HBR (OR:2.16 [95% CI: 0.64,7.59, P=.2). Of favorable intermediate risk patients, 20(64.5%) were reclassified to a higher NCCN risk. Ultimately, 18 patients underwent definitive treatment. CONCLUSIONS: Incorporation of genomic testing in risk stratifying Black men with low and intermediate-risk prostate cancer resulted in overall higher NCCN risk classifications. Our findings suggest a role for increased utilization of genomic testing in refining risk-stratification within this patient population. These tests may better inform treatment decisions on an individualized basis.