Economic Burden of Osteoporosis-Related Fractures in the US Medicare Population.

BACKGROUND: Osteoporosis-related fractures are an important public health burden. OBJECTIVE: To examine health care costs in Medicare patients with an osteoporosis-related fracture. METHODS: Medicare fee-for-service members with an osteoporosis-related fracture between January 1, 2010, to September 30, 2014 were included. A nonfracture comparator group was selected by propensity score matching. Generalized linear models using a gamma distribution were used to compare costs between fracture and nonfracture cohorts. RESULTS: A total of 885 676 Medicare beneficiaries had fracture(s) and met inclusion criteria. Average age was 80.5 (±8.4) years; 91% were White, and 94% female. Mean all-cause costs were greater in the fracture vs nonfracture cohort ($47 163.25 vs $16 034.61) overall and for men ($52 273.79 vs $17 352.68). The highest mean costs were for skilled nursing facility ($29 216), inpatient costs ($24 190.19), and hospice care ($20 996.83). The highest incremental costs versus the nonfracture cohort were for hip ($71 057.83 vs $16 807.74), spine ($37 543.87 vs $16 860.49), and radius/ulna ($24 505.27 vs $14 673.86). Total medical and pharmacy costs for patients who experienced a second fracture were higher compared with those who did not ($78 137.59 vs $44 467.47). Proportionally more patients in the fracture versus nonfracture cohort died (18% vs 9.3%), with higher death rates among men (20% vs 11%). CONCLUSION AND RELEVANCE: The current findings suggest a significant economic burden associated with fractures. Early identification and treatment of patients at high risk for fractures is of paramount importance for secondary prevention and reduced mortality.

The Design and Validation of a New Algorithm to Identify Incident Fractures in Administrative Claims Data.

Our study validated a claims-based algorithm for the identification of incident and recurrent fractures in administrative data. We used Centers for Medicare and Medicaid (CMS) claims from 2005 to 2014 linked to the Reasons for Geographic and Racial Differences in Stroke (REGARDS) database. Case qualifying (CQ) fractures were identified among participants with ≥12 months of fee-for-service coverage before first fracture claim and ≥6 months after. Recurrent fractures were defined as the first CQ fracture that occurred following a clean period of at least 90 days from the last claim associated with the preceding incident fracture. We used medical records (discharge summary, imaging, and surgical report) to adjudicate fractures. We calculated positive predictive values (PPVs) for incident and recurrent fractures. Our study was not designed to assess the algorithm sensitivity or negative predictive value. We identified 2049 potential incident fractures from claims among 1650 participants. Record retrieval was attempted for 728 (35.5%) suspected incident fractures (prioritizing more recent CQ fractures associated with osteoporosis, but without explicitly requiring any osteoporosis ICD-9 diagnosis code). Our final sample included 520 claims-identified fractures with medical records, of which 502 (96.5%) were confirmed. The PPVs (95% CI) of the hip, wrist, humerus, and clinical vertebra-all exceeded 95%. We identified 117 beneficiaries with 292 ≥2 CQ fracture episodes at the same site, and attempted retrieval on 105 (36.0%) episodes. Our analytic sample included 72 (68.5%) CQ episodes from 33 participants. The PPVs for identifying recurrent clinical vertebral, hip/femur, and nonvertebral fractures with a 90-day clean period exceeded 95%. Although we could not ascertain sensitivity, our updated fracture identification algorithms had high PPV for the identification of incident and recurrent fractures of the same site. Although medical record review and clinical adjudication remain a gold standard, our claims-based algorithm provides an alternative approach to fracture ascertainment when high PPV is desired. © 2019 American Society for Bone and Mineral Research.

Experience of primary care among homeless individuals with mental health conditions.

The delivery of primary care to homeless individuals with mental health conditions presents unique challenges. To inform healthcare improvement, we studied predictors of favorable primary care experience among homeless persons with mental health conditions treated at sites that varied in degree of homeless-specific service tailoring. This was a multi-site, survey-based comparison of primary care experiences at three mainstream primary care clinics of the Veterans Administration (VA), one homeless-tailored VA clinic, and one tailored non-VA healthcare program. Persons who accessed primary care service two or more times from July 2008 through June 2010 (N = 366) were randomly sampled. Predictor variables included patient and organization characteristics suggested by the patient perception model developed by Sofaer and Firminger (2005), with an emphasis on mental health. The primary care experience was assessed with the Primary Care Quality-Homeless (PCQ-H) questionnaire, a validated survey instrument. Multiple regression identified predictors of positive experiences (i.e. higher PCQ-H total score). Significant predictors of a positive experience included a site offering tailored service design, perceived choice among providers, and currently domiciled status. There was an interaction effect between site and severe psychiatric symptoms. For persons with severe psychiatric symptoms, a homeless-tailored service design was significantly associated with a more favorable primary care experience. For persons without severe psychiatric symptoms, this difference was not significant. This study supports the importance of tailored healthcare delivery designed for homeless persons' needs, with such services potentially holding special relevance for persons with mental health conditions. To improve patient experience among the homeless, organizations may want to deliver services that are tailored to homelessness and offer a choice of providers.

Development of the Primary Care Quality-Homeless (PCQ-H) instrument: a practical survey of homeless patients' experiences in primary care.

BACKGROUND: Homeless patients face unique challenges in obtaining primary care responsive to their needs and context. Patient experience questionnaires could permit assessment of patient-centered medical homes for this population, but standard instruments may not reflect homeless patients' priorities and concerns. OBJECTIVES: This report describes (a) the content and psychometric properties of a new primary care questionnaire for homeless patients; and (b) the methods utilized in its development. METHODS: Starting with quality-related constructs from the Institute of Medicine, we identified relevant themes by interviewing homeless patients and experts in their care. A multidisciplinary team drafted a preliminary set of 78 items. This was administered to homeless-experienced clients (n=563) across 3 VA facilities and 1 non-VA Health Care for the Homeless Program. Using Item Response Theory, we examined Test Information Function (TIF) curves to eliminate less informative items and devise plausibly distinct subscales. RESULTS: The resulting 33-item instrument (Primary Care Quality-Homeless) has 4 subscales: Patient-Clinician Relationship (15 items), Cooperation among Clinicians (3 items), Access/Coordination (11 items), and Homeless-specific Needs (4 items). Evidence for divergent and convergent validity is provided. TIF graphs showed adequate informational value to permit inferences about groups for 3 subscales (Relationship, Cooperation, and Access/Coordination). The 3-item Cooperation subscale had lower informational value (TIF<5) but had good internal consistency (α=0.75) and patients frequently reported problems in this aspect of care. CONCLUSIONS: Systematic application of qualitative and quantitative methods supported the development of a brief patient-reported questionnaire focused on the primary care of homeless patients and offers guidance for future population-specific instrument development.