Going into town or staying home: Rural patient experience and preference with home-based versus clinic-based telehealth.

INTRODUCTION: Telehealth is a model of care with potential to improve access, and in turn outcomes, for people living in rural areas. Since 2013, our endocrine clinic-based telehealth program has provided care at rural community hospitals in Nebraska and Iowa. At the start of the COVID-19 pandemic, when regulations around telehealth were adjusted, patients previously seen via clinic-based telehealth had the option to continue clinic-based visits or have a home-based telehealth visit. There is no literature comparing patient experiences between home-based and clinic-based telehealth. The purpose of this study was to understand rural patient preferences regarding endocrinology home-based versus clinic-based telehealth visits. METHODS: This was a survey study of adult, rural patients who experienced both a clinic-based and home-based telehealth visit with their established endocrinology provider. Respondents were asked about demographics, their reason for visit, preference for home versus clinic-based telehealth, and how they would have received care if telehealth were not an option. RESULTS: Forty-two patients (40.8%) responded to the survey, with 27 patients (64.3%) preferring home-based telehealth. There were no significant differences between the groups. However, 47.5% of patients would not have sought specialty care if telehealth were not an option. DISCUSSION: This survey of endocrine patients experienced in both clinic-based and home-based telehealth indicates that, while most respondents preferred home-based telehealth, there are distinct advantages to each model and patients appreciate having options. We believe it is important to maintain both lines of service to provide patient-centered care and improve access to specialty care.

In-Person and Telehealth Provider Access and Glycemic Control for People With Diabetes During the COVID-19 Pandemic.

BACKGROUND: Ambulatory care underwent rapid changes at the onset of the COVID-19 pandemic. Care for people with diabetes shifted from an almost exclusively in-person model to a hybrid model consisting of in-person visits, telehealth visits, phone calls, and asynchronous messaging. METHODS: We analyzed data for all patients with diabetes and established with a provider at a large academic medical center to identify in-person and telehealth ambulatory provider visits over two periods of time (a "pre-COVID" and "COVID" period). RESULTS: While the number of people with diabetes and any ambulatory provider visit decreased during the COVID period, telehealth saw massive growth. Per Hemoglobin A1c, glycemic control remained stable from the pre-COVID to COVID time periods. CONCLUSIONS: Findings support continued use of telehealth, and we anticipate hybrid models of care will be utilized for people with diabetes beyond the pandemic.

Telemedicine and health access inequalities during the COVID-19 pandemic.

Background: During the COVID-19 pandemic, health systems rapidly introduced in-home telehealth to maintain access to care. Evidence is evolving regarding telehealth's impact on health disparities. Our objective was to evaluate associations between socioeconomic factors and rurality with access to ambulatory care and telehealth use during the COVID-19 pandemic. Methods: We conducted a retrospective study at an academic medical centre in midwestern United States. We included established and new patients who received care during a one-year COVID-19 period vs pre-COVID-19 baseline cohorts. The primary outcome was the occurrence of in-person or telehealth visits during the pandemic. Multivariable analyses identified factors associated with having a health care provider visit during the COVID-19 vs pre-COVID-19 period, as well as having at least one telehealth visit during the COVID-19 period. Results: All patient visit types were lower during the COVID-19 vs the pre-COVID-19 period. During the COVID-19 period, 125 855 of 255 742 established patients and 53 973 new patients had at least one health care provider visit, with 41.1% of established and 23.5% of new patients having at least one telehealth visit. Controlling for demographic and clinical characteristics, established patients had 30% lower odds of having any health care provider visit during COVID-19 vs pre-COVID-19 (adjusted odds ratio (aOR) = 0.71, 95% confidence interval (CI) = 0.698-0.71) period. Factors associated with lower odds of having a telehealth visit during COVID-19 period for established patients included older age, self-pay or other insurance vs commercial insurance, Black or Asian vs White race and non-English preferred languages. Female patients, patients with Medicare or Medicaid coverage, and those living in lower income zip codes were more likely to have a telehealth visit. Living in a zip code with higher average internet access was associated with telehealth use but living in a rural zip code was not. Factors affecting telehealth visit during the COVID-19 period for new patients were similar, although new patients living in more rural areas had a higher odds of telehealth use. Conclusion: Healthcare inequities existed during the COVID-19 pandemic, despite the availability of in-home telehealth. Patient-level solutions targeted at improving digital literacy, interpretive services, as well as increasing access to stable high-speed internet are needed to promote equitable health care access.

Appropriate Use of Telehealth Visits in Endocrinology: Policy Perspective of the Endocrine Society.

OBJECTIVE: This work aims to guide clinicians practicing endocrinology in the use of telehealth (synchronous patient-clinician visits conducted over video or telephone) for outpatient care. PARTICIPANTS: The Endocrine Society convened a 9-member panel of US endocrinologists with expertise in telehealth clinical care, telehealth operations, patient-centered care, health care delivery research, and/or evidence-based medicine. EVIDENCE: The panel conducted a literature search to identify studies published since 2000 about telehealth in endocrinology. One member extracted a list of factors affecting the quality of endocrine care via telehealth from the extant literature. The panel grouped these factors into 5 domains: clinical, patient, patient-clinician relationship, clinician, and health care setting and technology. CONSENSUS PROCESS: For each domain, 2 or 3 members drew on existing literature and their expert opinions to draft a section examining the effect of the domain's component factors on the appropriateness of telehealth use within endocrine practice. Appropriateness was evaluated in the context of the 6 Institute of Medicine aims for health care quality: patient-centeredness, equity, safety, effectiveness, timeliness, and efficiency. The panel held monthly virtual meetings to discuss and revise each domain. Two members wrote the remaining sections and integrated them with the domains to create the full policy perspective, which was reviewed and revised by all members. CONCLUSIONS: Telehealth has become a common care modality within endocrinology. This policy perspective summarizes the factors determining telehealth appropriateness in various patient care scenarios. Strategies to increase the quality of telehealth care are offered. More research is needed to develop a robust evidence base for future guideline development.

Telehealth Fatigue: Is It Real? What Should Be Done?

This commentary article discusses the recent trends and changes in popularity of telehealth usage as well as the most recent efforts to redefine telehealth value and usability. Six strategies to improve the patient experience and increase telehealth acceptance by overcoming simultaneous barriers are presented, which include (1) creating a new healthcare paradigm using telehealth, (2) scheduling the telehealth visit, (3) preparing for the telehealth visit, (4) conducting the telehealth visit, (5) using data and biomarkers, and (6) providing digital equity. With the application of these strategies, we believe that the recent decline in the popularity of telehealth can be reversed.

Rural Telehealth Visits in the Management of Type 1 Diabetes.

INTRODUCTION: Despite advances in and increased adoption of technology, glycemic outcomes for individuals with type 1 diabetes (T1D) have not improved. Access to care is limited for many, in part due to a shortage of endocrinologists and their concentration in urban areas. Managing T1D via telehealth has potential to improve glycemic outcomes, as the barriers of travel-related time and cost are mitigated. METHODS: Our endocrine telehealth program started in 2013 and currently provides care to nine rural community hospitals in Nebraska and Iowa. A retrospective cohort study was performed to evaluate glycemic outcomes in people with T1D who received care at these telehealth clinics from 2013-2019. Data were collected on age, race, gender, prior diabetes provider, use of diabetes technology, and A1c values over time. RESULTS: One hundred thirty-nine individuals were followed for an average duration of 32 months (range 4-69 months). Sixty-six percent of people were previously under the care of an endocrinologist. The most common therapeutic action, in addition to insulin adjustment, was addition of a CGM (52%). Each year in telemedicine care was associated with a decline of 0.13% in A1c (95% CI: -0.20, -0.06). There was no association between A1c and age or gender. When stratifying by previous diabetes provider, all groups had a statistically significant decline in A1c, even those with a previous endocrine provider. There was no statistically significant decline in A1c based on addition of technology. CONCLUSION: We have shown that traditional telehealth visits are an effective way to provide care for people with T1D long-term and may provide distinct advantages to home telehealth visits.

The Association of Diabetes and Hyperglycemia on Inpatient Readmissions.

OBJECTIVE: To evaluate the association between inpatient glycemic control and readmission in individuals with diabetes and hyperglycemia (DM/HG). METHODS: Two data sets were analyzed from fiscal years 2011 to 2013: hospital data using the International Classification of Diseases, Ninth Revision (ICD-9) codes for DM/HG and point of care (POC) glucose monitoring. The variables analyzed included gender, age, mean, minimum and maximum glucose, along with 4 measures of glycemic variability (GV), standard deviation, coefficient of variation, mean amplitude of glucose excursions, and average daily risk range. RESULTS: Of 66 518 discharges in FY 2011-2013, 28.4% had DM/HG based on ICD-9 codes and 53% received POC monitoring. The overall readmission rate was 13.9%, although the rates for individuals with DM/HG were higher at 18.9% and 20.6% using ICD-9 codes and POC data, respectively. The readmitted group had higher mean glucose (169 ± 47 mg/dL vs 158 ± 46 mg/dL, P < .001). Individuals with severe hypoglycemia and hyperglycemia had the highest readmission rates. All 4 GV measures were consistent and higher in the readmitted group. CONCLUSION: Individuals with DM/HG have higher 30-day readmission rates than those without. Those readmitted had higher mean glucose, more extreme glucose values, and higher GV. To our knowledge, this is the first report of multiple metrics of inpatient glycemic control, including GV, and their associations with readmission.

Effect of Behavioral Therapy With In-Clinic or Telephone Group Visits vs In-Clinic Individual Visits on Weight Loss Among Patients With Obesity in Rural Clinical Practice: A Randomized Clinical Trial.

Importance: Rural populations have a higher prevalence of obesity and poor access to weight loss programs. Effective models for treating obesity in rural clinical practice are needed. Objective: To compare the Medicare Intensive Behavioral Therapy for Obesity fee-for-service model with 2 alternatives: in-clinic group visits based on a patient-centered medical home model and telephone-based group visits based on a disease management model. Design, Setting, and Participants: Cluster randomized trial conducted in 36 primary care practices in the rural Midwestern US. Inclusion criteria included age 20 to 75 years and body mass index of 30 to 45. Participants were enrolled from February 2016 to October 2017. Final follow-up occurred in December 2019. Interventions: All participants received a lifestyle intervention focused on diet, physical activity, and behavior change strategies. In the fee-for-service intervention (n = 473), practice-employed clinicians provided 15-minute in-clinic individual visits at a frequency similar to that reimbursed by Medicare (weekly for 1 month, biweekly for 5 months, and monthly thereafter). In the in-clinic group intervention (n = 468), practice-employed clinicians delivered group visits that were weekly for 3 months, biweekly for 3 months, and monthly thereafter. In the telephone group intervention (n = 466), patients received the same intervention as the in-clinic group intervention, but sessions were delivered remotely via conference calls by centralized staff. Main Outcomes and Measures: The primary outcome was weight change at 24 months. A minimum clinically important difference was defined as 2.75 kg. Results: Among 1407 participants (mean age, 54.7 [SD, 11.8] years; baseline body mass index, 36.7 [SD, 4.0]; 1081 [77%] women), 1220 (87%) completed the trial. Mean weight loss at 24 months was -4.4 kg (95% CI, -5.5 to -3.4 kg) in the in-clinic group intervention, -3.9 kg (95% CI, -5.0 to -2.9 kg) in the telephone group intervention, and -2.6 kg (95% CI, -3.6 to -1.5 kg) in the in-clinic individual intervention. Compared with the in-clinic individual intervention, the mean difference in weight change was -1.9 kg (97.5% CI, -3.5 to -0.2 kg; P = .01) for the in-clinic group intervention and -1.4 kg (97.5% CI, -3.0 to 0.3 kg; P = .06) for the telephone group intervention. Conclusions and Relevance: Among patients with obesity in rural primary care clinics, in-clinic group visits but not telephone-based group visits, compared with in-clinic individual visits, resulted in statistically significantly greater weight loss at 24 months. However, the differences were small in magnitude and of uncertain clinical importance. Trial Registration: ClinicalTrials.gov Identifier: NCT02456636.

Has Technology Improved Diabetes Management in Relation to Age, Gender, and Ethnicity?

PURPOSE OF REVIEW: To review the current state of diabetes technology adoption and describe impact on outcomes in the context of age, gender, and ethnicity. We will discuss barriers and propose solutions that may help facilitate the adoption. RECENT FINDINGS: We are witnessing rapid evolution and increase in adoption of diabetes technology in all its forms, including insulin delivery and glucose monitoring devices, mobile medical applications, and telemedicine. This technology has a great potential to improve diabetes-related outcomes, including acute and chronic complications as well as quality of life for people living with diabetes. However, currently available outcome data are showing modest efficacy and evidence for disparities when it comes to age, gender, and ethnicity. Despite multiple barriers, the adoption of technology is steadily increasing. It is clear that disparities exist in terms of access to and use of technology, but they may be at least in part driven by unmet needs of end users and as such are not unsurmountable. While more research is needed to identify the specific causes for the disparities, future development of diabetes technology that is based on adaptation of behavioral theories has a potential to address the gaps. The disparities can be lessened by understanding the needs of end users and with improvement in personalization of technology, allowing the right device to be used by the right patient. Targeted interventions to increase awareness and education and help navigate the processes involved in currently available technology may help diminish the gaps in health equity.

Diabetes Management Through Remote Patient Monitoring: The Importance of Patient Activation and Engagement with the Technology.

Background: The documented efficacy and promise of telemedicine in diabetes management does not necessarily mean that it can be easily translated into clinical practice. An important barrier concerns patient activation and engagement with telemedicine technology. Objective: To assess the importance of patient activation and engagement with remote patient monitoring technology in diabetes management among patients with type 2 diabetes. Methods: Ordinary least squares and logistic regression analyses were used to examine how patient activation and engagement with remote patient monitoring technology were related to changes in hemoglobin A1c (HbA1c) for 1,354 patients with type 2 diabetes monitored remotely for 3 months between 2015 and 2017. Results: Patients with more frequent and regular participation in remote monitoring had lower HbA1c levels at the end of the program. Compared to patients who uploaded their biometric data every 2 days or less frequently, patients who maintained an average frequency of one upload per day were less likely to have a postmonitoring HbA1c > 9% after adjusting for selected covariates on baseline demographics and health conditions. Conclusions: Higher levels of patient activation and engagement with remote patient monitoring technology were associated with better glycemic control outcomes. Developing targeted interventions for different groups of patients to promote their activation and engagement levels would be important to improve the effectiveness of remote patient monitoring in diabetes management.

App-Based Insulin Calculators: Current and Future State.

PURPOSE OF REVIEW: To perform a comprehensive literature review and critical assessment of peer-reviewed manuscripts addressing the efficacy, safety, or usability of insulin calculator apps. RECENT FINDINGS: Managing diabetes with insulin can be complex, and literacy and numeracy skills pose barriers to manual insulin dose calculations. App-based insulin calculators are promising tools to help people with diabetes administer insulin safely and have potential to improve glycemic control. While a large number of apps which assist with insulin dosing are available, there is limited data evaluating their efficacy, safety, and usability. Recently, a need for regulatory oversight has been recognized, but few apps meet federal standards. Thus, choosing an appropriate app is challenging for both patients and providers. An electronic literature review was performed to identify insulin calculator apps with either evidence for efficacy, safety or usability published in peer-reviewed literature or with FDA/CE approval. Twenty apps were identified intended for use by patients with diabetes on insulin. Of these, nine included insulin calculators. Summaries of each app, including pros and cons, are provided. Insulin-calculator apps have the potential to improve self-management of diabetes. While current literature demonstrates improvements in quality of life and glycemic control after use of these programs, larger trials are needed to collect outcome and safety data. Also, further human factor analysis is needed to assure these apps will be adopted appropriately by people with diabetes. App features including efficacy and safety data need to be easily available for consumer review and decision making. Higher standards need to be set for app developers to ensure safety and efficacy.

Remote Patient Monitoring and Clinical Outcomes for Postdischarge Patients with Type 2 Diabetes.

The objective of this study was to evaluate changes in clinical outcomes for patients with type 2 diabetes (T2D) after a 3-month remote patient monitoring (RPM) program, and examine the relationship between hemoglobin A1c (HbA1c) outcomes and participant characteristics. The study sample included 955 patients with T2D who were admitted to an urban Midwestern medical center for any reason from 2014 to 2017, and used RPM for 3 months after discharge. Clinical outcomes included HbA1c, weight, body mass index (BMI), and patient activation scores. Logistic regression was used to estimate the likelihood of having a postintervention HbA1c <9% by patient characteristics, among those who had baseline HbA1c >9%. Most patients experienced decreases in HbA1c (67%) and BMI (58%), and increases in patient activation scores (67%) (P < 0.001 in all 3 cases) at the end of RPM. Logistic regression analyses revealed that among patients who had HbA1c >9% at baseline, men (odds ratio [OR] = 3.72; 95% confidence interval [CI], 1.43-9.64), those who had increased patient activation scores after intervention (OR = 1.05; 95% CI, 1.01-1.09), those who had higher baseline patient activation scores, and those who had a greater number of biometric data uploads during the intervention (OR = 1.02; 95% CI, 1.00-1.04) were more likely to have reduced their HbA1c to <9% at the end of RPM. RPM for postdischarge patients with T2D might be a promising approach for HbA1c control with increased patient engagement. Future studies with study designs that include a control group should provide more robust evidence.

Protocol for the Rural Engagement in Primary Care for Optimizing Weight Reduction (RE-POWER) Trial: Comparing three obesity treatment models in rural primary care.

Obesity disproportionately affects rural residents in the United States, and primary care has the potential to fill a major gap in the provision of weight management services for rural communities. The objective of this cluster-randomized pragmatic trial is to evaluate the comparative effectiveness of three obesity treatment models in rural primary care: the Intensive Behavior Therapy fee-for-service (FFS) model reimbursed by Medicare, a team-based model that recognizes the patient-centered medical home (PCMH) as a preferred delivery approach, and the centralized disease management (DM) model, in which phone-based counseling is provided outside of the primary care practice. We hypothesize that the PCMH and DM treatments will be more effective than FFS in reducing weight at 24 months. Thirty-six practices from the rural Midwestern U.S. are randomized to deliver one of the three interventions to 40 patients (N=1440) age 20 to 75 with a BMI 30-45 kg/m(2). In the FFS arm, primary care providers and their personnel counsel patients to follow evidence-based weight loss guidelines using the Medicare-designated treatment schedule. In the PCMH arm, patients receive a comprehensive weight management intervention delivered locally by practice personnel using a combination of in-person and phone-based group sessions. In the DM arm, the same intervention is delivered remotely by obesity treatment specialists via group conference calls. The primary outcome is weight loss at 24 months. Additional measures include fasting glucose, lipids, quality of life indicators, and implementation process measures. Findings will illuminate effective obesity treatment intervention(s) in rural primary care.

Inpatient hypoglycemia: a challenge that must be addressed.

Hypoglycemia in the inpatient setting is a common occurrence with potentially harmful outcomes. Large trials in both the inpatient and outpatient settings have found a correlation between hypoglycemia and morbidity and mortality. The incidence of hypoglycemia is difficult to assess, due to a lack of standardized definitions and different methods of data collection between hospital systems. Risk factors that predispose to hypoglycemia involve the changing clinical statuses of patients, nutrition issues, and hospital processes. Mechanisms contributing to morbidity due to hypoglycemia may include an increase in sympathoadrenal responses, as well as indirect changes affecting cytokine production, coagulation, fibrinolysis, and endothelial function. Prevention of hypoglycemia requires implementation of several strategies that include patient safety, quality control, multidisciplinary communication, and transitions of care. In this article, we discuss all of these issues and provide suggestions to help predict and prevent hypoglycemic episodes during an inpatient stay. We address the issues that occur upon admission, during the hospital stay, and around the time of discharge. We believe that decreasing the incidence of inpatient hypoglycemia will both decrease costs and improve patient outcomes.

Silent corticotroph adenomas: Emory University cohort and comparison with ACTH-negative nonfunctioning pituitary adenomas.

BACKGROUND: Silent corticotroph adenomas (SCAs) are clinically nonfunctioning pituitary adenomas (NFPAs) with positive staining for corticotropin (ACTH) by immunohistochemistry. Whether SCAs behave more aggressively than NFPAs without ACTH immunoreactivity (ACTH negative) remains controversial. OBJECTIVE: To compare characteristics and outcomes of SCAs with ACTH-negative NFPAs and to identify predictors of aggressive outcome. Primary composite endpoint included the first of any of the following events: progression, recurrence, or death. METHODS: We reviewed all cases of SCAs and all ACTH-negative macroadenomas operated on between April 1995 and December 2007 by 1 neurosurgeon. RESULTS: Our retrospective cohorts included 33 SCAs followed for 42.5 months (median) (range, 6.7-179.0 months) and 126 ACTH-negative patients followed for 42 months (range, 6-142 months). SCA were younger (mean ± SD; 49.6 ± 14.1) than ACTH-negative patients (55.6 ± 12.8, P = .02). Tumor diameter was similar (2.8 ± 1.0 cm); cavernous sinus invasion was present in 45.5% of SCAs and 30.2% of ACTH-negative NFPAs (P = .09). Postoperative tumor residual was detected in 53.1% of SCAs and 49.6% of ACTH-negative patients. Radiation was administered in 40.6% of SCAs at 16 months (range, 3-149 months) and 33.3% of ACTH-negative patients at 13 months (range, 3-94) postoperatively. Progression of residual tumor occurred in 24.2% of SCAs and 11.1% of ACTH-negative patients (P = .08); recurrence was similar (6.0% SCAs vs 5.5% ACTH-negative patients). Cumulative event-free survival rates were not significantly different between the 2 groups (P = .3). Age, sex, tumor size, cavernous sinus invasion, or SCA subtypes were not associated with outcome. CONCLUSION: SCA patients were younger, but exhibited similar postoperative tumor regrowth rates as ACTH-negative macroadenomas while using a similar adjuvant radiation protocol. Long-term follow-up is warranted because predictors of regrowth are currently lacking.