This study explores behavioral health professionals’ perceptions of granular data. Semi-structured in-person interviews of 20 health professionals were conducted at two different sites. Qualitative and quantitative analysis was performed. While most health professionals agreed that patients should control who accesses their personal medical record (70%), there are certain types of health information that should never be restricted (65%). Emergent themes, including perceived reasons that patients might share or withhold certain types of health information (65%), care coordination (12%), patient comprehension (11%), stigma (5%), trust (3%), sociocultural understanding (3%), and dissatisfaction with consent processes (1%), are explored. The impact of care role (prescriber or non-prescriber) on data-sharing perception is explored as well. This study informs the discussion on developing technology that helps balance provider and patient data-sharing and access needs.
This pilot study compares medical record data sensitivity (e.g., depression is sensitive) and categorization perspective (e.g., depression categorized as mental health information) of patients with behavioral health conditions and healthcare providers using a mixed-methods approach employing patient’s own EHR. Perspectives of 25 English- and Spanish-speaking patients were compared with providers. Data categorization comparisons resulted in 66.3% agreements, 14.5% partial agreements, and 19.3% disagreements. Sensitivity comparisons obtained 54.5% agreement, 11.9% partial agreement, and 33.6% disagreements. Patients and providers disagreed in classification of genetic data, mental health, drug abuse, and physical health information. Factors influencing patients’ sensitivity determination were sensitive category comprehension, own experience, stigma towards category labels (e.g., drug abuse), and perception of information applicability (e.g., alcohol dependency). Knowledge of patients’ sensitivity perceptions and reconciliation with providers could expedite the development of granular and personalized consent technology.
The high variability found in SMBs and CTs highlights the need for real-time diabetes self-tracking mechanisms to better understand SMBs and CTs. Future work will use the developed app to collect SMBs and CTs and identify patient-specific diabetes adherence barriers that could be addressed with individualized education interventions.
Diabetes mellitus is a complex, chronic disease affecting 29.1 million (9.3%) US residents. 1 Chronic hyperglycemia can result in potentially devastating microvascular and macrovascular complications, leading to major morbidity, mortality, and economic consequences in this patient population. Evidence demonstrates that these complications can be prevented by maintaining glycemic control to near normal levels. Achieving and maintaining adequate glycemic control requires consistent medical care, and most importantly, ongoing patient self-management. 2 While evidence shows that alcohol and exercise affect the absorption of insulin and increase the risk of hypoglycemia, there is a lack of evidence-based decision tools to allow for translation of this information into practice. 3-6 Patients with type 1 diabetes (T1D) must manage their disease by injecting insulin deliverable through syringes, insulin pens, or insulin pumps. Premeal insulin dosage compliance and accuracy is a key factor in achieving target postprandial glucose levels. In 2013 insulin pumps were being used by over 350 000 people in the United States, 7 incorporate proprietary mathematical algorithms called bolus calculators or bolus wizards to determine individualized premeal dosing. 8-10 The benefits achieved through the use of insulin pumps and continuous 663746D STXXX10.
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