Health Insurance Coverage as a Social Determinant of Osteoporosis Diagnosis in a Population-Based Cohort Study of Older American Adults

Patient-informed exploration of the aftermath of a diagnostic problem or mistake based on results of a national survey

Introduction

Despite the prevalence and devastating consequences of diagnostic breakdowns, there have been minimal efforts to systematically collect patient insight into diagnostic problems and mistakes. Collaborating with patient advocates to guide how patient-derived insights are interpreted and used is a critical, yet often overlooked, approach to identifying actionable solutions that speak to patients' priorities.

Objective

We collaborated with patient advocate co-authors to guide our understanding of findings from a mixed methods survey on diagnostic problems and mistakes, and report implications for patient engagement at three levels of action: (1) individual level before, during, after encounters (micro); (2) within health service delivery systems (meso); and (3) policy advocacy (macro).

Methods

Our research team applied narrative elicitation methods to conduct a novel survey about Americans' diagnostic experiences in a national, population-based survey. We shared early results with patient co-authors who highlighted the importance of further exploring how health systems and clinicians address the aftermath of diagnostic mishaps. Based on their input, we summarized the quantitative and qualitative survey results about the aftermath and worked with our patient co-authors to explore how findings might inform actionable next steps, including efforts to catalyze patient action, quality improvement efforts, and policy reform.

Results

Of the 3,684 survey respondents, about a third (33.0%, 1,216/3,684) of screened households reported diagnostic problems and mistakes in the past four years involving either themselves (18.9%, 697/3,684) or someone close to them (14.1%, 519/3,684). In the aftermath of a diagnostic mishap, over a third reported that someone in the healthcare setting where the mistake occurred acknowledged the mistake (35.9%, 432/1,204). In qualitative findings, reports that the health system "did nothing" surfacing as the most common response. Patient co-authors confirmed the results resonated with their experiences and emphasized the need for health systems to take accountability when a mishap occurs and to take follow-up actions to prevent future mishaps.

Discussion

Patients and care partners not only want and deserve acknowledgement of diagnostic problems or mistakes in their own care, they also want assurance that steps are being taken to prevent similar events from happening to others. Across micro-, meso-, and macro-levels of action, working with patients to understand and act on contributors to diagnostic breakdowns is aligned with high-reliability organizing principles.

Psychological Disorders Linked to Osteoporosis Diagnoses in a Population-Based Cohort Study of Middle and Older Age United States Adults

BACKGROUND AND OBJECTIVES

Although it is well established that psychological disorders and osteoporosis risk are linked, how the relationship manifests is not. This study examines depressive symptoms and a history of psychological problems as potential risk factors for osteoporosis diagnosis, adjudicating between 4 theoretical models rarely tested together. We analyze these models across multiple domains (i.e., demographic, socioeconomic, and health-related), while accounting for bone mineral density (BMD) scans, which have been shown to improve health equity across sex and racial/ethnic identities.

RESEARCH DESIGN AND METHODS

Data from the 2012-2016, nationally representative, population-based, cohort Health and Retirement Study (N = 18,224-18,359) were used to estimate 4 logistic regression models with the outcome of osteoporosis diagnosis. Approximately 50% of the sample identified as female and 50% as male, while about 81% identified as White/European American, 11% as Black/African American, and 8% as another race/ethnicity. The key independent variables were depressive symptoms-measured using two common scales-and a history of psychological problems.

RESULTS

A history of psychological problems and one depressive symptoms measure were associated with the odds of osteoporosis diagnosis in the presence of other known risk factors for osteoporosis.

DISCUSSION AND IMPLICATIONS

Support for the theoretical models was limited. Evidence suggests possible directionality; a history of psychological distress may be a risk factor for osteoporosis, though we cannot rule out the other direction. Public health professionals and healthcare providers should consider a history of psychological problems as a risk factor for osteoporosis when deciding whether to recommend a BMD scan.

3D Topographical Scanning for the Detection of Osteoporosis

Objectives

Osteoporosis is associated with greater risk of fracture, which can lead to increased morbidity and mortality. DEXA scans are often inaccessible for patients, leaving many cases of osteoporosis undetected. A portable 3D topographical scan offers an easily accessible and inexpensive potential adjunct screening tool. We hypothesized that 3D scanning of arm and calf circumference and volume would correlate with DEXA T-scores.

Methods

96 female patients were enrolled. Patients were consented and completed a topographical scan of bilateral arms and lower legs with a mobile 3D scanner for arm and calf circumference and volume in clinic. Patient charts were then retrospectively reviewed for DEXA T-scores.

Results

Forearm DEXA T-score was positively correlated with arm circumference (r = 0.49, p<0.01), arm volume (r=0.62, p<0.01), and calf volume (r=0.47, p<0.01). Femoral neck DEXA T-score was positively correlated with calf circumference (r=0.36, p<0.01) and calf volume (r=0.36, p<0.01).

Conclusions

Our results showed significant correlations between DEXA T-scores and topographical measurements from mobile device acquired 3D scans, although these were in the "moderate" range. Mobile device-based 3D scanning may hold promise as an adjunct screening tool for osteoporosis when DEXA scanning is not available or feasible for patients, although further studies are needed to elucidate the full potential of its clinical utility. At a minimum, identifying a patient as high risk may promote earlier diagnostic DEXA scanning.

Development of a diverse osteoporosis screening tool for older US adults from the health and retirement study

Existing osteoporosis screening tools have limitations, including using race as a predictor, and development on homogeneous samples. This biases risk assessment of osteoporosis in diverse populations and increases health inequities. We develop a tool that relies on variables easily learned during point-of-care, known by individuals, and with negligible racial bias. Data from the 2012-2016 waves of the population-based cohort Health and Retirement Study (HRS) were used to build a predictive model of osteoporosis diagnosis on a 75 % training sample of adults ages 50-90. The model was validated on a 25 % holdout sample and a cross-sectional sample of American individuals ages 50-80 from the National Health and Nutrition Examination Survey (NHANES). Sensitivity and specificity were compared across sex and race/ethnicity. The model has high sensitivity in the HRS holdout sample (89.9 %), which holds for those identifying as female and across racial/ethnic groups. Specificity is 57.9 %, and area under the curve (AUC) is approximately 0.81. Validation in the NHANES sample using empirically measured osteoporosis produced relatively good values of sensitivity, specificity, and consistency across groups. The model was used to create a publicly-available, open-source tool called the Osteoporosis Health Equality (& Equity) Evaluation (OsteoHEE). The model provided high sensitivity for osteoporosis diagnosis, with consistently high results for those identifying as female, and across racial/ethnic groups. Use of this tool is expected to improve equity in screening and increase access to bone density scans for those at risk of osteoporosis. Validation on alternative samples is encouraged.

Adapting forensic case reporting to account for marginalization and vulnerability

Scholarship of forensic sciences has shown politicalization of human remains and potential biases in criminal investigations. Specifically, concerns have been raised regarding how forensic anthropology analysis and documentation may hinder identification processes or obfuscate other data. As part of this scholarship, some have suggested that forensic anthropologists expand their reporting to include broader public health and safety information as well as reconsider who should be included in reports of anthropological findings. In response to these burgeoning discussions, this piece provides examples of ways anthropologists may formulate reports that capture evidence of marginalization or structural vulnerability. Documentation of findings can occur in myriad formats, including, but not limited to, individual case reports, reports on population analyses from cases, collaborative end-of-year reporting conducted with other medicolegal professionals, and collaborative databasing. This piece provides various templates and suggestions for reporting this kind of data while encouraging further discussion on related merits and concerns.

Childhood Family Environment and Osteoporosis in a Population-Based Cohort Study of Middle-to Older-Age Americans

Demographic and early-life socioeconomic and parental investment factors may influence later-life health and development of chronic and progressive diseases, including osteoporosis, a costly condition common among women. The "long arm of childhood" literature links negative early-life exposures to lower socioeconomic attainment and worse adult health. We build on a small literature linking childhood socioeconomic status (SES) and bone health, providing evidence of whether associations exist between lower childhood SES and maternal investment and higher risk of osteoporosis diagnosis. We further examine whether persons identifying with non-White racial/ethnic groups experience underdiagnosis. Data from the nationally representative, population-based cohort Health and Retirement Study (N = 5,490-11,819) were analyzed for participants ages 50-90 to assess these relationships. Using a machine learning algorithm, we estimated seven survey-weighted logit models. Greater maternal investment was linked to lower odds of osteoporosis diagnosis (odds ratio [OR] = 0.80, 95% confidence interval [CI] = 0.69, 0.92), but childhood SES was not (OR = 1.03, 95% CI = 0.94, 1.13). Identifying as Black/African American (OR = 0.56, 95% CI = 0.40, 0.80) was associated with lower odds, and identifying as female (OR = 7.22, 95% CI = 5.54, 9.40) produced higher odds of diagnosis. There were differences in diagnosis across intersectional racial/ethnic and sex identities, after accounting for having a bone density scan, and a model predicting bone density scan receipt demonstrated unequal screening across groups. Greater maternal investment was linked to lower odds of osteoporosis diagnosis, likely reflecting links to life-course accumulation of human capital and childhood nutrition. There is some evidence of underdiagnosis related to bone density scan access. Yet results demonstrated a limited role for the long arm of childhood in later-life osteoporosis diagnosis. Findings suggest that (1) clinicians should consider life-course context when assessing osteoporosis risk and (2) diversity, equity, and inclusivity training for clinicians could improve health equity. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Structural Inequity and Socioeconomic Status Link to Osteoporosis Diagnosis in a Population-Based Cohort of Middle-Older-Age Americans

Socioeconomic status (SES) is an important social determinant of health inequities that has been linked to chronic conditions, including osteoporosis, but research tends to focus on socioeconomic disadvantage rather than how socioeconomic advantage may facilitate these inequities. This study accounts for structural inequities and assesses the relationship between early-life and later-life SES, and risk of osteoporosis diagnosis. Data come from the nationally representative, population-based cohort Health and Retirement Study and include individuals ages 50 to 90. The outcome variable is osteoporosis diagnosis. Logistic regression models of the relationship between SES and osteoporosis diagnosis are estimated, accounting for demographic, health, and childhood variables. Higher levels of childhood and adult SES link to lower odds of osteoporosis diagnosis. Structural inequities in income and underdiagnosis of osteoporosis among persons identifying as Black/African American were detected. Accounting for bone density scan access, inequities in osteoporosis diagnosis appear to stem from barriers to accessing health care due to financial constraints. The important role of SES and evidence of structural inequities leading to underdiagnosis suggest the critical importance of clinicians receiving Diversity, Equity, and Inclusion training to reduce health inequities.