Racial and Ethnic Differences in the Use of Electronic Medical Record Messaging Among Patients With Breast Cancer: A Quality Improvement Study.

INTRODUCTION: Despite evidence that use of electronic medical record (EMR) messaging positively impacts patients with cancer, there is little research on utilization patterns. The objective of this study is to describe the use of EMR messaging among breast cancer patients so that future interventions may be developed and targeted appropriately. MATERIALS AND METHODS: Sociodemographic and MyChart usage data were collected. Study eligibility included patients who completed a visit at an academic breast center and sent at least one message to a provider during the study period (May 2021-May 2022). Chi-square and t-tests were used to describe differences between users and nonusers of EMR messaging. ANOVA and chi-square were used to describe differences between race/ethnicity. RESULTS: A total of 4069 patients with activated MyChart accounts were included in the analysis. About 3575 (87.9%) were messaging users and 494 (12.1%) were nonusers. The mean age of users was significantly lower compared to the nonusers (57.7 vs 61.2, P< .001). Compared to non-Hispanic White (NHW) individuals, non-Hispanic Black (NHB) (odds ratio [OR]: 0.38, CI [0.21, 0.37]) and Hispanic individuals (OR: 0.35, CI [0.22, 0.57]) were significantly less likely to use electronic messaging. There were statistically significant racial/ethnic differences in the types of messages sent among EMR users. CONCLUSION: Our study shows disparate EMR messaging utilization based on age, race, and primary language. As the availability of patient portals and electronic messaging increase, it is important to understand the barriers that patients face so that they can be addressed.

Relationship between food insecurity and housing instability on quality of care and quality of life in adults with diabetes.

OBJECTIVE: Examine the relationship between food and housing insecurities, quality of care and quality of life in adults with diabetes using a nationally representative data source. METHODS: Data from 39,604 adults with diabetes who indicated if they experienced food and/or housing insecurity in the Behavioral Risk Factor Surveillance System (2014, 2015, 2017) was analyzed. Outcomes included quality of care (HbA1c test, eye exam, diabetes education, foot check) and quality of life (general health status, poor physical and mental health days, poor overall health days). Logistic models were run for each quality of care measure and linear models were run for each quality of life measure adjusting for socio-demographics, insurance status, and comorbidity count. RESULTS: 35.6% of adults with diabetes reported housing insecurity, 31.8% reported food insecurity, and 23.4% reported both. After adjustment, food and housing insecurity was significantly associated with lower odds of having an eye exam (housing:0.73, 95%CI:0.63,0.85; food:0.78, 95%CI:0.67,0.92; both:0.69, 95%CI:0.59,0.82), worse general health status (housing:-0.06 95%CI:-0.11,-0.01; food:-0.16, 95%CI:-0.21,-0.10; both:-0.14, 95%CI:-0.20,-0.09), and an increased number of poor mental health days (housing:1.73, 95%CI:0.83,2.63; food:2.08, 95%CI:1.16,3.00; both:1.97, 95%CI:1.05,2.90). Food insecurity was also associated with lower odds of receiving diabetes education (0.86, 95%CI:0.74,0.99) and an increased number of poor physical health days (0.95, 95%CI:0.14,1.76). CONCLUSION: Changes to our healthcare delivery system are critical to improving standards of care and quality of life in all populations and may require a shift towards consideration of overlapping social risk factors rather than the siloed approach currently used.

The Utility of Monitoring Potassium in Transgender, Gender Diverse, and Nonbinary Individuals on Spironolactone.

Context: Current Endocrine Society guidelines recommend that transgender women taking spironolactone have their potassium levels checked every 3 months for the first year after initiating therapy and annually thereafter to monitor for hyperkalemia. Objective: The goal of this study was to assess the need for such frequent potassium monitoring and to investigate whether age plays a role in potassium abnormalities in transgender, gender diverse, and nonbinary (TGDNB) individuals taking spironolactone. Methods: Using EPIC-Clarity, a retrospective study of healthy, adult individuals with gender-identity disorder listed in their problem list and taking spironolactone was performed. We analyzed the incidence of hyperkalemia in this population. Data from June 2006 through November 2021 were obtained. Exclusion criteria included hypertension, renal failure, diabetes mellitus, heart failure, and medications that affect the renin-angiotensin-aldosterone system. Results: 318 healthy TGDNB individuals met our inclusion criteria. We identified 8/318 (2.5%) individuals with hyperkalemia on spironolactone. There was a significant difference in incidence of hyperkalemia events in those >45 years old and those ≤45 years old (8.9% vs 1.5%, P = .016). Conclusion: Our data suggest the incidence of hyperkalemia in our TGDNB population is low, particularly in those ≤45 years old; however, this risk increases with age. These findings suggest practice guidelines may need to be adjusted to minimize unnecessary testing in the population ≤45 years old who are not plagued by comorbidities that affect potassium handling.

Differences in the relationship between social capital and hypertension in emerging vs. established economies in Sub-Saharan Africa.

BACKGROUND: The global burden of hypertension is growing, particularly in low- and middle-income countries. This study aimed to investigate differences in the relationship between social capital and hypertension between regions in Sub-Saharan Africa (West vs. South Africa) and within regions (rural vs. urban residence within each country). METHODS: Data for 9,800 adults were analyzed from the Study on Global Ageing and Adult Health (SAGE) 2007-2010 for Ghana (West African emerging economy) and South Africa (South African established economy). Outcomes were self-reported and measured hypertension. The primary independent variable was social capital, dichotomized into low vs. medium/high. Interaction terms were tested between social capital and rural/urban residence status for each outcome by country. Linear and logistic regression models were run separately for both countries and each outcome. RESULTS: Those with low social capital in the emerging economy of Ghana were more likely to have hypertension based on measurement (OR=1.35, 95% CI=1.18,1.55), but the relationship with self-reported hypertension lost significance after adjustment. There was no significant relationship in the relationship between social capital and hypertension in the established economy of South Africa after adjustment. No significant interactions existed by rural/urban residence status in either country. CONCLUSION: Low social capital was associated with worse hypertension outcomes, however, the relationship differed between South Africa and Ghana. Further investigation is needed to understand differences between and within countries to guide development of programs targeted at leveraging and promoting social capital as a positive component of overall health.

Short-term impact of COVID-19 on quality of life, perceived stress, and serious psychological distress in an adult population in the midwest United States.

PURPOSE: This study aimed to investigate changes over time in quality of life, perceived stress, and serious psychological distress for individuals diagnosed with COVID-19 in an urban academic health system. METHODS: Phone-based surveys were completed with adult patients tested for COVID-19 during emergency department visits, hospitalizations, or outpatient visits at the Froedtert and Medical College of Wisconsin Health Network. Data were then matched to medical record data. Unadjusted and adjusted mixed effects linear models using random intercept were run for each outcome (physical health-related quality of life, mental health-related quality of life, perceived stress, and serious psychological distress) with time (baseline vs 3-month follow-up) as the primary independent variable. Individuals were treated as a random effect, with all covariates (age, sex, race/ethnicity, payor, comorbidity count, hospitalization, and intensive care unit (ICU) stay) treated as fixed effects. RESULTS: 264 adults tested positive for COVID-19 and completed baseline and 3-month follow-up assessments. Of that number, 31.8% were hospitalized due to COVID-19, and 10.2% were admitted for any reason to the ICU. After adjustment, patients reported higher physical health-related quality of life at 3 months compared to baseline (0.63, 95% CI 0.15, 1.11) and decreased stress at 3 months compared to baseline (- 0.85, 95% CI - 1.33, - 0.37). There were no associations between survey time and mental health-related quality of life or serious psychological distress. CONCLUSIONS: Results suggest the influence of COVID-19 on physical health-related quality of life and stress may resolve over time, however, the influence of mental health on daily activities, work, and social activities may not.

Location Matters: Type of Hospital Unit Can Influence Medicine Patients' Satisfaction with Physician Communication.

Payors hold hospitals accountable for patient experience using the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. The objective was to determine if hospital unit (medicine versus nonmedicine [ie, cardiology, oncology, urology, physical medicine and rehabilitation, and surgery]) influences HCAHPS scores when care is given by the same providers on different units. This retrospective analysis of adult inpatient data (n = 845), included overall hospital satisfaction, staff communication, care and communication from physicians, and discharge communication. Average overall satisfaction was 8.9 out of 10 and length of stay was 4.6 days. Patients treated on nonmedicine units had higher overall satisfaction than those on medicine units (P = 0.02) and higher scores when asked how often doctors listened to the patient carefully (P = 0.002). The type of inpatient unit can influence overall satisfaction and satisfaction with physician communication. Differences in room environment, amenities, and staffing may explain why medicine patients were more satisfied on nonmedicine versus medicine units.

Preferences in trust regarding the provision of cancer information among adults.

BACKGROUND: Disparities associated with trust in health information exist warranting a need for research assessing this relationship among adults. Therefore, the aim of this study was to assess trust of cancer information among U.S. adults. METHODS: A weighted sample of 237,670,167 adults from the Health Information National Trends Survey (HINTS) from 2011-2014 was used for the analyses. Dependent variables were dichotomized answers to whether individuals trusted information from family/friends, the internet, or a doctor. Independent variables included age, sex, region, race/ethnicity, and cancer diagnosis to investigate associations between demographic factors and differences in trust. Logistic regression was run using R survey package. RESULTS: There were statistically significant differences in trust based on race/ethnicity, age, and cancer diagnosis. Minorities were less likely to trust information from a doctor, with Hispanics more likely to trust information from the internet (OR=1.8 (95% CI 1.36,2.43)), and Non-Hispanic Blacks trusting information from family and friends (OR=1.5 (95% CI 1.06, 2.13)). Adults ≥45 years of age were less likely to trust the doctor 'a lot' (45-64 years: OR=0.6 (95% CI 0.50, 0.83); 65+ years (OR=0.7 (95% CI 0.54, 0.92)), but more likely to not trust information from family and friends or the internet. Patients with cancer were more likely to trust information from a doctor 'a lot' (78%; p=0.01). DISCUSSION: Significant differences in preferences regarding trust in cancer information occurred based on sociodemographic characteristics. CONCLUSION: These finding suggest targeting specific population subgroups for information from sources they trust could be helpful in reducing disparities in trust.

Age and Gender Differences in Trends and Impact of Depression on Quality of Life in the United States, 2008 to 2016.

BACKGROUND: We aimed to examine age and gender differences in the relationship between depression and quality of life among United States adults. METHODS: Medical Expenditure Panel Survey data for 2008 to 2016 on 227,663 adults were analyzed. The dependent variable, quality of life, included physical component summary scores and mental component summary scores from the Short Form Health Survey. The key independent variable, depression, was measured using the two-item Patient Health Questionnaire. General linear regression models examined the relationship between quality of life and depression. Models were adjusted for individual and environmental characteristics, symptom status, functional and biological status, and health perceptions and were stratified by gender and age. RESULTS: In adjusted models, mental component summary scores were significantly lower among those with depression compared with those without depression (ß = -0.39; 95% confidence interval [CI], 0.38 to -1.16) and lower among women compared with men (ß = -0.10; 95% CI, 0.10 to -1.31). Models stratified by gender and age found women with depression ages 40 to 64 (ß = -0.07; 95% CI, 0.07 to -0.20) and 65 or older (ß = -0.08; 95% CI, 0.08 to -0.24) had significantly lower physical component summary scores compared with those without depression. Among men with depression, those ages 18 to 39 (ß = -0.03; 95% CI, 0.03 to -0.10) and 40 to 64 (ß = -0.09, 95% CI, 0.08 to -0.26) had lower physical component summary scores compared with those without depression. Women and men of all ages with depression had significantly lower mental component summary scores compared with those without depression. CONCLUSIONS: Public health interventions and clinical approaches to address depression in women and men should target functional status in men and perceptions of health in women.

Creating a culture of quality: our experience with providing feedback to frontline hospitalists.

BACKGROUND: One way to provide performance feedback to hospitalists is through the use of dashboards, which deliver data based on agreed-upon standards. Despite the growing trend on feedback performance on quality metrics, there remain limited data on the means, frequency and content of feedback that should be provided to frontline hospitalists. OBJECTIVE: The objective of our research is to report our experience with a comprehensive feedback system for frontline hospitalists, as well as report the change in our quality metrics after implementation. DESIGN, SETTING AND PARTICIPANTS: This quality improvement project was conducted at a tertiary academic medical centre among our hospitalist group consisting of 46 full-time faculty members. INTERVENTION OR EXPOSURE: A monthly performance feedback report was distributed to provide ongoing feedback to our hospitalist faculty, including an individual dashboard and a peer comparison report, complemented by coaching to incorporate process improvement tactics into providers' daily workflow. MAIN OUTCOMES AND MEASURES: The main outcome of our study is the change in quality metrics after implementation of the monthly performance feedback report RESULTS: The dashboard and rank order list were sent to all faculty members every month. An improvement was seen in the following quality metrics: length of stay index, 30-day readmission rate, catheter-associated urinary tract infections, central line-associated bloodstream infections, provider component of Healthcare Consumer Assessment of Healthcare Providers and Systems scores, attendance at care coordination rounds and percentage of discharge orders placed by 10:00. CONCLUSIONS: Implementation of a monthly performance feedback report for hospitalists, complemented by peer comparison and guidance on tactics to achieve these metrics, created a culture of quality and improvement in the quality of care delivered.

Differences in length of stay by teaching team status in an academic medical center in the Midwestern United States.

Background: Given the high cost of inpatient stays, hospital systems are investigating ways to decrease lengths of stay while ensuring high-quality care. The goal of this study was to determine if patients in teaching teams (hospitalist teams with residents and interns) had a higher length of stay after adjusting for relevant confounders compared to hospitalist-only teams (staffed only by attending physicians).Methods: Using a retrospective design, we investigated differences in length of stay for 17,577 inpatient encounters over a 2-year period. Length of stay was calculated based on the time between hospital admission and hospital discharge with no removal of outliers. Encounters were assigned to teams based on the discharge provider. Teams were grouped based on whether they were teaching teams or nonteaching teams. Since the length of stay was not normally distributed, it was modeled first using generalized linear models with gamma distribution and log link, and secondly by quantile regression. Models were adjusted for age, gender, race, medicine vs. non-medicine unit, MS-DRGs, and comorbidities.Results: Using gamma models to account for the skewed nature of the data, the length of stay for encounters assigned to teaching teams was 0.56 days longer (ß = 0.10 95% CI 0.06 0.14) than for nonteaching teams after adjustment. Using quantile regression, teaching teams had encounters on average 0.63 days longer (95% CI 0.44 0.81) than nonteaching teams at the 75th percentile and 1.19 days longer (95% CI 0.77 1.61) compared to nonteaching teams at the 90th percentile after adjustment.Conclusions: After adjusting for demographics and clinical factors, teaching teams on average had lengths of stay that were over half day longer than nonteaching teams. In addition, for the longest encounters, differences between teaching and nonteaching teams were over 1-day difference. Given these results, process improvement opportunities exist within teaching teams regarding length of stay, particularly for longer encounters.

Trends in Obesity and Medical Expenditure among Women with Diabetes, 2008-2016: Differences by Race/Ethnicity.

Objectives: Diabetes results in $327 billion in medical expenditures annually, while obesity, a risk factor for type 2 diabetes, leads to more than $147 billion in expenditure annually. The aims of this study were: 1) to evaluate racial/ethnic trends in obesity and medical expenditures; and 2) to assess incremental medical expenditures among a nationally representative sample of women with diabetes. Methods: Nine years of data (2008-2016) from the Medical Expenditure Panel Survey Full Year Consolidated File (unweighted = 11,755; weighted = 10,685,090) were used. The outcome variable was medical expenditure. The primary independent variable was race/ethnicity defined as non-Hispanic Black (NHB), Hispanic, or non-Hispanic White (NHW). Covariates included age, education, marital status, income, insurance, employment, region, comorbidity, and year. Cochran-Armitage tests determined statistical significance of trends in obesity and mean expenditure. Two-part modeling using Probit and gamma distribution was used to assess incremental medical expenditure. Data were clustered to 2008-2010, 2011-2013, 2014-2016. Results: Trends in medical expenditures differed significantly between NHB and NHW women between 2008-2016 (P<.001). Hispanic women paid $1,291 less compared with NHW women, after adjusting for relevant covariates. There were no significant differences in obesity trends from 2008-2016 between NHB (P=.989) or Hispanic women with diabetes (P=.938) compared with NHW women with diabetes. Conclusions: These findings suggest the need to further understand the factors associated with differences in trends for medical expenditures between NHB and NHW women with diabetes and incremental medical expenditures in Hispanic women with diabetes compared with NHW women with diabetes.

Examining racial and ethnic trends and differences in annual healthcare expenditures among a nationally representative sample of adults with arthritis from 2008 to 2016.

BACKGROUND: Disparities in health care utilization and outcomes for racial and ethnic minorities with arthritis are well-established. However, there is a paucity of research on racial and ethnic differences in healthcare expenditures and if this relationship has changed over time. Our objectives were to: 1) examine trends in annual healthcare expenditures for adults with arthritis by race and ethnicity, and 2) determine if racial and ethnic differences in annual healthcare expenditures were independent of other factors such as healthcare access and functional disability. METHODS: We used the Medical Expenditures Panel Survey (2008-2016) to examine trends in annual healthcare expenditures within and between racial and ethnic groups with arthritis (n = 227,663). A two-part model was used to estimate the marginal differences in expenditures by race and ethnicity after adjusting for relevant covariates, including the impact of healthcare access. RESULTS: Between 2008 and 2016, there were no significant changes in unadjusted healthcare expenditures within any of the racial and ethnic groups, but the trend among non-Hispanic whites did differ significantly from Hispanics and Other. In fully adjusted analysis, mean annual expenditures for non-Hispanic whites was $946, $939, and $1178 more than non-Hispanic blacks, Hispanics, and Other, respectively (p < .001). Healthcare access also independently explained expenditure differences in this population with adults who delayed care spending significantly more ($2629) versus those who went without care spending significantly less (-$1591). CONCLUSIONS: Race and ethnicity are independent drivers of healthcare expenditures among adults with arthritis independent of healthcare access and functional disability. This underscores the need for ongoing research on the factors that influence persistent racial and ethnic differences in this population.

Redesigning primary care in an academic medical center: lessons, challenges, and opportunities.

PURPOSE: To evaluate patient access, provider productivity, and patient satisfaction during a 24-month redesign process of an academic medical center, which requires balance between clinical and educational missions. METHODS: A series of activities were conducted to optimize primary care across 17 attending physicians, 6 Advanced Practice Providers (APPs), and 39 residents. Patient access was defined as the next available appointment for either existing/established patients or new patients. Productivity was measured using panel sizes for each provider. Patient satisfaction was based on the Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CGCAHPS). RESULTS: Despite decreasing clinical effort to allow faculty and APPs to participate in education and research, there was an overall increase in access for both new and established patients, and an increase the percent of each providers' panel that was full from 78.89% in 2017 to 115.29% in 2019. When comparing panel sizes for the 11 faculty present before and after strategic changes, we found significant increase in both overall panel size, and actual to expected ratios between 2017 and 2019. In addition, throughout the time period, patient satisfaction remained high with no significant changes. CONCLUSIONS: While this project was limited to one site, the inclusion of a set of well-planned metrics, and tracking of processes over time can provide insight for ongoing primary care redesign efforts at similar sites seeking to balance the academic mission with clinical productivity and high patient satisfaction.

The Relationship between Dialysis Metrics and Patient-Reported Cognition, Fatigue, and Physical Function.

INTRODUCTION: The impact of achieving hemodialysis laboratory and hemodynamic quality metrics on patient-reported outcomes (PROs) is unknown. OBJECTIVE: To determine if meeting dialysis laboratory quality of care measures is associated with improved PROs. METHODS: In this cross-sectional study, we measured the relationship between dialysis patients' Patient Reported Outcome Measurement Information System (PROMIS) scores and commonly used dialysis quality of care measures. RESULTS: PROMIS surveys were administered to 92 dialysis patients. The mean ± SD scores demonstrated higher fatigue (55.0 ± 9.8) and lower physical function (37.9 ± 7.9) but similar cognition (50.3 ± 10.9) compared to general population normative scores of 50 ± 10. Dialysis patients meeting Kt/V goals had no better scores than those who did not. Meeting the hemoglobin (Hgb) value of ≥10 g/dL was associated with a lower fatigue score, but no difference in cognitive or physical function scores. Meeting the serum albumin goal of ≥4.0 mg/dL was associated with a higher physical function score but made no difference for cognitive function or fatigue score. As a continuous variable, a higher Hgb was associated with lower reported fatigue (HR -1.74 95%, CI [-3.09, -0.39]), but no other measures were associated with PRO scores when adjusted for demographics and comorbidities. CONCLUSIONS: We found little association between measures currently used to assess the quality of dialysis care and PROs. Encouraging improved utilization of PROs and incorporating PROs into quality measurements might give a more robust assessment of quality of care. Future studies should assess the benefits of this approach.

Patient Centered Communication and E-Health Information Exchange Patterns: Findings From a National Cross-Sectional Survey.

This paper aimed to determine whether there was a connection between patient's perception of communication with their doctors in the visit and their use of online health information exchange using a nationally representative survey. We used the data from the Health Information National Trends survey pooled HINTS4 Cycle 4 data and assessed outcomes using logistic regression modeling composite communication scores as a continuous variable. We weighted participants to create population-level estimates. We adjusted for age, gender, race, and census region. The 3677 patients were included in the analysis who had an outpatient visit within the previous 12 months. In unadjusted analysis and analysis adjusted for demographic factors, patients who experienced higher communication scores were more likely to use online health information exchange with their providers. In unadjusted analysis, patients had 0.04 higher odds of interest in receiving appointment reminders from health care providers electronically (OR = 1.04 and [Formula: see text]) and 0.03 higher odds of interest in receiving general health tips (OR = 1.03 and [Formula: see text]) for every score increase in the communication summary score. In adjusted model, for each score increment in the communication score, patients were 7% more inclined to receive appointment reminders ([Formula: see text]), 4% more inclined to receive general health tips ([Formula: see text]), and 4% more likely to exchange information about lifestyle behaviors ([Formula: see text]). Findings suggest that the quality of the communication in the visit might increase use of informatics tool to exchange health information.

Preferences for Health Information Technologies Among US Adults: Analysis of the Health Information National Trends Survey.

BACKGROUND: Emerging health technologies are increasingly being used in health care for communication, data collection, patient monitoring, education, and facilitating adherence to chronic disease management. However, there is a lack of studies on differences in the preference for using information exchange technologies between patients with chronic and nonchronic diseases and factors affecting these differences. OBJECTIVE: The purpose of this paper is to understand the preferences and use of information technology for information exchange among a nationally representative sample of adults with and without 3 chronic disease conditions (ie, cardiovascular disease [CVD], diabetes, and hypertension) and to assess whether these preferences differ according to varying demographic variables. METHODS: We utilized data from the 2012 and 2014 iteration of the Health Information National Trends Survey (N=7307). We used multiple logistic regressions, adjusting for relevant demographic covariates, to identify the independent factors associated with lower odds of using health information technology (HIT), thus, identifying targets for awareness. Analyses were weighted for the US population and adjusted for the sociodemographic variables of age, gender, race, and US census region. RESULTS: Of 7307 participants, 3529 reported CVD, diabetes, or hypertension. In the unadjusted models, individuals with diabetes, CVD, or hypertension were more likely to report using email to exchange medical information with their provider and less likely to not use any of the technology in health information exchange, as well as more likely to say it was not important for them to access personal medical information electronically. In the unadjusted model, additional significant odds ratio (OR) values were observed. However, after adjustment, most relationships regarding the use and interest in exchanging information with the provider were no longer significant. In the adjusted model, individuals with CVD, diabetes, or hypertension were more likely to access Web-based personal health information through a website or app. Furthermore, we assessed adjusted ORs for demographic variables. Those aged >65 years and Hispanic people were more likely to report no use of email to exchange medical information with their provider. Minorities (Hispanic, non-Hispanic black, and Asian people) were less likely to indicate they had no interest in exchanging general health tips with a provider electronically. CONCLUSIONS: The analysis did not show any significant association among those with comorbidities and their proclivity toward health information, possibly implying that HIT-related interventions, particularly design of information technologies, should focus more on demographic factors, including race, age, and region, than on comorbidities or chronic disease status to increase the likelihood of use. Future research is needed to understand and explore more patient-friendly use and design of information technologies, which can be utilized by diverse age, race, and education or health literacy groups efficiently to further bridge the patient-provider communication gap.