Communication About Health Information Technology Use Between Patients and Providers.

BACKGROUND: Although growing, the prevalence of the use of health information technology (HIT) by patients to communicate with their providers is not well understood on the population level, nor whether patients are communicating with their providers about their use of HIT. OBJECTIVE: To understand whether patients are communicating with their providers about HIT use and the patient characteristics associated with the communication. DESIGN: Cross-sectional, self-administered survey of a sample of patients across the state of Indiana. PARTICIPANTS: Nine hundred seventy adult participants from across Indiana, 54% female and 79.5% white. MAIN MEASURES: The survey included sections assessing health information-seeking behavior, use of health information technology, and discussions with doctors about the use of HIT. KEY RESULTS: The survey had a 12% response rate. Sixty-three percent of respondent reported going to the Internet as the first source when seeking health information, while only 19% of respondent reported their doctor was their first source. When communicating with doctors electronically, 31% reported using an electronic health record messaging system, 24% used email, and 18% used text messaging. Only 39% of respondents reported having had any conversation about HIT use with their providers. CONCLUSIONS: There remain many unmet opportunities for patients and providers to communicate about HIT use. More guidance for patients and care teams may both help facilitate these conversations and promote optimal use, such as recommendations to ask simple clarification questions and minimize inefficient, synchronous communication when unnecessary.

We were in the fight together: The expectations of bereaved caregivers of patients with acute myeloid leukemia from diagnosis to death.

PURPOSE: Patients with hematologic malignancies are more optimistic than their oncologists and their expectations may be a barrier to timely hospice care. Patient expectations toward the end of life (EOL), however, have not been characterized. In this study, we analyzed interviews of bereaved caregivers to understand the expectations of patients diagnosed with acute myeloid leukemia and the factors that influenced those expectations, from diagnosis until death. METHODS: Bereaved caregivers (n = 19) participated in an in-depth interview that included open-ended and semi-structured prompts, within 18 months following patient death. Interviews were analyzed using a modified grounded theory qualitative approach and constant comparative methods. RESULTS: We identified three themes relevant to expectations: Taking Stock, Being Stuck, and Disruption. Caregivers described clear and optimistic early expectations that AML is treatable. It was understood that treatment was required to survive. Later, when treatment options were limited, patients and caregivers became stuck in a belief that the patient could continue to live indefinitely on supportive care or at least until new more effective treatments were available. Caregivers often realized that the patient was at the end of life only when faced with a disruption, an event or conversation that changed their expectations for indefinite patient survival. CONCLUSIONS: Caregivers described continued expectations for patient survival until presented with irrefutable evidence to the contrary. The study suggests patients and caregivers may make better EOL care decisions if their early optimism is deliberately moderated by ongoing conversations with clinicians that highlight the sentinel events that signal treatment failure and explain how expectations and goals are changing from living a longer life to dying a more comfortable death.

Bereaved Informal Caregivers Rarely Recall a Relationship Between Transfusions and Hospice in Acute Myeloid Leukemia.

AIMS: The inability to prescribe blood transfusions is a potential barrier to timely hospice enrollment for patients with blood cancers. The benefits and harms of transfusions near the end of life (EOL), however, are poorly characterized and patients' preferences are unknown. We sought to characterize the recollections of bereaved caregivers about the relationships between transfusions and hospice enrollment decisions. METHODS: We recruited 18 bereaved caregivers of 15 decedents who died within 6-18 months of the interview. Interviews focused on caregivers' recollections of transfusion and hospice enrollment decisions. Transcripts were analyzed for themes. RESULTS: We identified 2 themes. First, caregivers described that transfusions were necessary and the decisions to receive transfusions or not were deferred to the clinicians. Second, only 1 caregiver recalled transfusions as relevant to hospice decisions. In that instance there was a delay. Caregivers identified difficulties recognizing death was imminent, hope for miracles, and the necessity of accepting life was ending as more relevant barriers. CONCLUSIONS: The results indicate clinicians' beliefs in transfusion at EOL may be a more relevant barrier to hospice enrollment than patients' preferences. Strategies to evaluate accurately and discuss the actual benefits and harms of transfusions at the EOL are necessary to advise patients and integrate their preferences into decisions.

Racial and Socioeconomic Disparities in Cancer-Related Knowledge, Beliefs, and Behaviors in Indiana.

BACKGROUND: This statewide survey examined differences in cancer-related knowledge, beliefs, and behaviors between racial and socioeconomic groups in select counties in Indiana. METHODS: A stratified random sample of 7,979 people aged 18-75 who lived in one of 34 Indiana counties with higher cancer mortality rates than the state average, and were seen at least once in the past year in a statewide health system were mailed surveys. RESULTS: Completed surveys were returned by 970 participants, yielding a 12% response rate. Black respondents were less likely to perceive they were at risk for cancer and less worried about getting cancer. Individuals most likely to perceive that they were unlikely to get cancer were more often black, with low incomes (less than $20,000) or high incomes ($50,000 or more), or less than a high school degree. Black women were greater than six times more likely to be adherent to cervical cancer screening. Higher income was associated with receiving a sigmoidoscopy in the last 5 years and a lung scan in the past year. Those with the highest incomes were more likely to engage in physical activity. Both income and education were inversely related to smoking. CONCLUSIONS: Socioeconomic and racial disparities were observed in health behaviors and receipt of cancer screening. Black individuals had less worry about cancer. IMPACT: Understanding populations for whom cancer disparities exist and geographic areas where the cancer burden is disproportionately high is essential to decision-making about research priorities and the use of public health resources.

Rural and Urban Differences in the Adoption of New Health Information and Medical Technologies.

BACKGROUND: This statewide survey sought to understand the adoption level of new health information and medical technologies, and whether these patterns differed between urban and rural populations. METHODS: A random sample of 7,979 people aged 18-75 years, stratified by rural status and race, who lived in 1 of 34 Indiana counties with high cancer mortality rates and were seen at least once in the past year in a statewide health system were surveyed. RESULTS: Completed surveys were returned by 970 participants. Rural patients were less likely than urban to use electronic health record messaging systems (28.3% vs 34.5%, P = .045) or any communication technology (43.0% vs 50.8%, P = .017). Rural patients were less likely to look for personal health information for someone else's medical record (11.0% vs 16.3%, P = .022), look-up test results (29.5% vs 38.3%, P = .005), or use any form of electronic medical record (EMR) access (57.5% vs 67.1%, P = .003). Rural differences in any use of communication technology or EMRs were no longer significant in adjusted models, while education and income were significantly associated. There was a trend in the higher use of low-dose computed tomography (CT) scan among rural patients (19.1% vs 14.4%, P = .057). No significant difference was present between rural and urban patients in the use of the human papilloma virus test (27.1% vs 26.6%, P = .880). CONCLUSIONS: Differences in health information technology use between rural and urban populations may be moderated by social determinants. Lower adoption of new health information technologies (HITs) than medical technologies among rural, compared to urban, individuals may be due to lower levels of evidence supporting HITs.