Underrecognition of sleep-disordered breathing and other common health conditions in the West Virginia Medicaid population: a driver of poor health outcomes

Factors impacting sleep center no-show rates after hospital discharge using geospatial coding in Appalachia

STUDY OBJECTIVES

Screening for early detection of sleep-disordered breathing in hospitalized patients has been shown to reduce readmission rates. However, postdischarge polysomnography for confirmation of diagnosis is required. We analyzed factors for "no-shows" using geospatial techniques.

METHODS

Data were obtained between September 2019 and September 2023. The outcome for the study was patients' no-show rate (nonadherent for polysomnography) after hospital discharge. Predictors included the patient's age, sex, body mass index, health literacy, Distressed Communities Index score, and distance to a sleep center for the patient's zip code of residence. Logistic regression was applied to estimate odds of patients' adherence at the patient level using a geospatial mapping technique. Geographically weighted logistic regression was applied to estimate the odds of a zip code's including adherent patients.

RESULTS

Of the 1,318 hospitalized patients established as high-risk for sleep-disordered breathing and referred for an overnight sleep study who were able to be geocoded, 228 were adherent and 1,130 were nonadherent. In nonspatial regression analyses, health literacy (adjusted odds ratio = 1.06; 95% confidence interval = 1.03, 1.09), age (adjusted odds ratio = 0.99; 95% confidence interval = 0.98, 0.99), and drive time (adjusted odds ratio = 0.95; 95% confidence interval = 0.92, 0.97) were identified as statistically significant predictors of patients' adherence. Spatial regression analyses identified areas that had high and low predictive probability of patients' adherence, as well as which community-level factors were co-occurring in those areas.

CONCLUSIONS

The findings suggest that both patient-level factors and the community where patients live may impact no-show rates. Health literacy was identified as a key modifiable predictor at the patient level. At the community level, we found that predicted probability of patient adherence varied throughout the state. Efforts should focus on enhancing patients' education at the individual level and understanding geographical factors to improve adherence.

CITATION

Sharma S, Stansbury R, Rojas E, et al. Factors impacting sleep center no-show rates after hospital discharge using geospatial coding in Appalachia. J Clin Sleep Med. 2025;21(4):667-674.

Prevalence and regional distribution of obstructive sleep apnea in Canada: Analysis from the Canadian Longitudinal Study on Aging

OBJECTIVES

Obstructive sleep apnea (OSA) is a common chronic condition that is often undiagnosed or diagnosed after many years of symptoms and has an impact on quality of life and several health factors. We estimated the Canadian national prevalence of OSA using a validated questionnaire and physical measurements in participants in the Canadian Longitudinal Study on Aging (CLSA).

METHODS

The method used individual risk estimation based upon the validated STOP-BANG scale developed for OSA. This stratified population sample spans Canada to provide regional estimates.

RESULTS

In this sample of adults aged 45 to 85 years old, the overall prevalence in 2015 of combined moderate and severe OSA in the 51,337 participants was 28.1% (95% confidence intervals, 27.8‒28.4). The regional prevalence varied statistically between Atlantic Canada and Western Canada (p < 0.001), although clinically the variations were limited. The provincial prevalence for moderate and severe OSA ranged from 27.5% (New Brunswick and British Columbia) to 29.1% (Manitoba). Body mass index (BMI) was the dominant determinant of the variance between provinces (β = 0.33, p < 0.001). Only 1.2% of participants had a clinical diagnosis of OSA.

CONCLUSION

The great majority (92.9%) of the participants at high risk of OSA were unrecognized and had no clinical diagnosis of OSA.

Early recognition and treatment of OSA in hospitalized patients and its impact on health care utilization in rural population: a real-world study

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is a highly prevalent, yet underdiagnosed, condition. Due to its adverse impact on risk for cardiopulmonary disorders, there is interest in proactive screening of OSA in hospitalized patients. We studied the long-term outcome of such screened patients who were initiated on positive airway pressure therapy.

METHODS

Hospitalized patients who screened positive for OSA and were confirmed with postdischarge polysomnography were dichotomized by positive airway pressure therapy adherence and followed for a period of 12 months to evaluate for the composite end point of hospital readmissions and emergency department visits for cardiopulmonary reasons. Cost analysis between the 2 groups was also conducted.

RESULTS

A total of 2,042 hospitalized patients were assessed for OSA as part of a hospital sleep medicine program from August 2019-June 2023. Of these, 293 patients were diagnosed with OSA and prescribed positive airway pressure therapy. Of these 293 patients, 108 were adherent to therapy and 185 were nonadherent. The overall characteristics of the groups included a mean (standard deviation) age of 58 years (12.82), mean body mass index (kg/m2) of 39.72 (10.71), 57% male sex, and apnea-hypopnea index of 25.49 (26). Of the patients, 78%, 41%, and 43% had hypertension, congestive heart failure, and diabetes mellitus, respectively. The composite end point of hospital readmissions and emergency department visits for cardiovascular and pulmonary reasons was significantly higher in the nonadherent group than in the adherent group (hazard ratio, 1.24; 95% confidence interval, 1-1.54) (P = .03). The cost of care for both hospital billing as well as professional billing was higher for the nonadherent group ($1,455.60 vs $1,723.50, P = .004 in hospital billing cost and $130.90 vs $144.70, P < .001 in professional billing). Length of stay was higher for nonadherent patients (2.7 ± 5.1 days vs 2.3 ± 5.9 days).

CONCLUSIONS

Hospitalized patients diagnosed with OSA and adherent to therapy have reduced readmissions and emergency department visits for cardiopulmonary reasons 12 months after discharge. Adherent patients have reduced cost of health care and length of stay during hospitalizations.

CITATION

Sharma S, Stansbury R, Srinivasan P, et al. Early recognition and treatment of OSA in hospitalized patients and its impact on health care utilization in rural population: a real-world study. J Clin Sleep Med. 2024;20(8):1313-1319.

Provider Perspectives on Sleep Apnea from Appalachia: A Mixed Methods Study

West Virginia (WV) has the highest rates of obesity and cardiopulmonary disease in the United States (U.S.). Recent work has identified a significant care gap in WV for obstructive sleep apnea (OSA). This OSA care gap likely has significant health implications for the region given the high rates of obesity and cardiopulmonary disease. The purpose of this mix methods study was to identify barriers that contribute to the rural OSA care disparity previously identified in WV. Methods: This study used mixed methods to evaluate the barriers and facilitators to management of OSA at Federally Qualified Health Centers serving communities in southern WV. Focus groups were conducted at federally qualified health centers with providers serving Appalachian communities. Participants also completed the validated Obstructive Sleep Apnea Knowledge and Attitudes (OSAKA) questionnaire to gain insight into provider knowledge and beliefs regarding OSA. EMR analysis using diagnostic codes was completed at the sites to assess OSA prevalence rates. The same individual served as the interviewer in all focus group sessions to minimize interviewer variability/bias. Our team checked to ensure that the professional transcriptions were correct and matched the audio via spot checks. Results: Themes identified from the focus groups fell into three broad categories: (1) barriers to OSA care delivery, (2) facilitators to OSA care delivery, and (3) community-based care needs to optimize management of OSA in the targeted rural areas. Questionnaire data demonstrated rural providers feel OSA is an important condition to identify but lack confidence to identify and treat OSA. Evaluation of the electronic medical record demonstrates an even larger OSA care gap in these rural communities than previously described. Conclusion: This study found a lack of provider confidence in the ability to diagnose and treat OSA effectively and identified specific themes that limit OSA care in the communities studied. Training directed toward the identified knowledge gaps and on new technologies would likely give rural primary care providers the confidence to take a more active role in OSA diagnosis and management. An integrated model of care that incorporates primary care providers, specialists and effective use of modern technologies will be essential to address the identified OSA care disparities in rural WV and similar communities across the U.S. Community engaged research such as the current study will be essential to the creation of feasible, practical, relevant and culturally competent care pathways for providers serving rural communities with OSA and other respiratory disease to achieve health equity.