The impact of the housing status on clinical outcomes and health care utilization among individuals living with HIV

ABSTRACT

The lack of stable housing can impair access and continuity of care for patients living with human immunodeficiency virus (HIV). This study investigated the relationship between housing status assessed at multiple time points and several core HIV-related outcomes within the same group of HIV patients experiencing homelessness. Patients with consistently stable housing (CSH) during the year were compared to patients who lacked CSH (non-CSH group). The study outcomes included HIV viral load (VL), CD4 counts, and health care utilization. Multivariable and propensity weighted analyses were used to assess outcomes adjusting for potential group differences. Of 208 patients, 88 (42%) had CSH and 120 (58%) were non-CSH. Patients with CSH had significantly higher proportion of VL suppression and higher mean CD4 counts. The frequency of nurse visits in the CSH group was less than a half of that in the non-CSH group. Patients with CSH were less likely to be admitted to the medical respite facility, and if admitted, their length of stay was about a half of that for the non-CSH group. Our study findings show that patients with CSH had significantly better HIV virologic control and immune status as well as improved health care utilization.     

Correction: Thrombotic and bleeding events,mortality, and anticoagulant use among 546,656 hospitalized patients with COVID‑19 in the United States: a retrospective cohort study

Journal of Thrombosis and Thrombolysis -     

The success of Australia’s ‘No Jab,No Pay’ policy at a local level; retrospective clinical audit of a single medical practice assessing incidence of catch-up vaccinations

Vaccination is a vital health care initiative to prevent individual and population infection. To increase vaccination rates the federal government implemented the ‘No Jab, No Pay’ policy, where eligibility for several government benefits required children to be fully vaccinated by removing ‘conscientious objections’ and expanding the age range of children whose families receive benefits. This study assesses the impact of this policy at a local area within a single medical practice community in NSW, Australia. A retrospective clinical audit was performed between 2012 and 2017 on a single general practice's vaccination records for children ≤19 years. Catch-up vaccinations were assessed based on age at vaccination. Incidence of catch-up vaccinations was assessed for each of four years before and two years after the implementation of the ‘No Jab, No Pay’ policy in January 2016, along with the age of children and vaccination(s) given. Catch-up vaccinations were assessed temporally either side of implementation of ‘No Jab, No Pay’. Comparing the average annual vaccination catch-up incidence rate of 6.2% pre-implementation (2012–2015), there was an increase to 9.2% in 2016 (p < .001) and 7.8% in 2017 (p = .027). Secondary outcome measurement of catch-up vaccination incidence rates before (2012–2015) and after (2016–2017) ‘No Jab, No Pay’ implementation showed statistically significant increases for children aged 8–11 years (3.2%–5.6%, p = .038), 12–15 years (7.5%–14.7%, p < .001) and 16–19 years (3.3%–10.2%, p < .001) along with a statistically significant reduction in children aged 1–3 years (11.4%–6.2%, p = .015). Also, catch-up rates for DTPa significantly increased after program implementation. This study demonstrates that the Australian federal government vaccination policy ‘No Jab, No Pay’ was coincident with an increase in catch-up vaccinations within a rural NSW community served by one medical practice, especially for older children.     

Comparing the rates of low-value back images ordered by physicians and nurse practitioners for Medicare beneficiaries in primary care

BackgroundLittle is known about the extent of ordering low-value services by.PurposeTo compare the rates of low-value back images ordered by primary care physicians (PCMDs) and primary care nurse practitioners (PCNPs).MethodWe used 2012 and 2013 Medicare Part B claims for all beneficiaries in 18 hospital referral ?regions (HRRs) and a measure of low-value back imaging from Choosing Wisely. Models included random clinician effect and fixed effects for beneficiary age, disability, Elixhauser comorbidities, clinician sex, the emergency department setting, back pain visit volume, organization, and region (HRR).FindingsPCNPs (N = 231) and PCMDs (N = 4,779) order low-value back images at similar rates (NP: all images: 26.5%; MRI/CT: 8.4%; MD: all images: 24.5%; MRI/CT: 7.7%), with no detectable significant difference when controlling for covariates.DiscussionPCNPs and PCMDs order low-value back images at an effectively similar rate.