Literature Collection

BACKGROUND: Specialist intervention in COPD is often reactive, resulting in inequalities in the provision of care. A proactive approach, in which individuals with modifiable disease are identified from primary care records, may help to tackle this inequality in access. AIM: To estimate the prevalence of "treatable traits" in COPD in a primary care research database and to assess health service usage. METHODS: We performed a secondary analysis of individuals with either 1) a primary care diagnosis of COPD or 2) obstructive spirometry and history of ever smoking in a large observational study recruiting individuals aged 40-69 years old in Leicestershire, UK. Spirometry, height, weight and smoking history were collected prospectively and linked to individuals' primary care records. "Treatable traits" were identified from primary care records (frequent exacerbations, current smoking, low body mass index, respiratory failure, severe breathlessness, potential suitability for lung volume reduction or psychological comorbidity). Differences in demographics and health usage between those with and without "treatable traits" were assessed. RESULTS: In total, of the 347 individuals with COPD, 186 had at least one "treatable trait". Compared to those without treatable traits, individuals with treatable traits were younger (61 vs 64 years, p<0.001), had more severe airflow obstruction (FEV(1) 86% vs 94% predicted, p=0.002), higher eosinophil count (0.32 vs 0.27 cells/μL, p=0.04) and were more socioeconomically deprived (UK Indices of Multiple Deprivation decile 4.3 vs 5.8, p<0.001). Individuals with treatable traits had a higher annual primary care health usage (47 vs 30 visits per year, p=0.001). Referrals rates to specialist respiratory services were low in both groups. CONCLUSION: Treatable traits are common in COPD and can be identified from routinely collected primary care data. Treatable traits are associated with younger age and greater deprivation. These individuals pose a significant burden to primary care yet are rarely referred to specialist respiratory services.

BACKGROUND: Adversity in childhood is increasing in the United Kingdom. Complex health and social problems affecting children cluster in families where adults also have high need, but services are rarely aligned to support the whole family. Household level segmentation can help identify households most needing integrated support. Thus, the aim was to develop a segmentation model to identify those households with children who have high levels of complex cross-sectoral needs, to use as a case-finding tool for health and social care services, and to describe characteristics of identified households, to inform service integration. METHOD: Working with stakeholders-in an English region of 2.7m population- we agreed a definition of families having complex needs which would benefit from service integration - including households with high intensity use, who had both physical and mental health problems amongst both adults and children and wider social risks. We then used individual and household linked data across multiple health and social care services to identify these households, providing an algorithm to be used in a case finding interface. Finally, to understand the needs of this segment, and to identify unmet need, to tailor support, we used descriptive statistics and Poisson regression to profile the segment and compare them with the rest of the population. RESULTS: Twenty one thousand and five hundreds twenty seven households (8% of the population of the region) were identified with complex needs, including 89,631 people (41,382 children), accounting for 34% of health and social care costs for families with children, £362 million in total, of which 42% was on children in care of local authorities. The households had contact with 3-4 different services, had high prevalence of mental health problems, most frequently co-morbid with respiratory problems, with high mental health emergency service use particularly amongst teenage girls many of whom had no prior elective treatment for conditions. CONCLUSION: Our model provides a potentially useful tool for identifying households that could benefit from better integration of services and targeted family support that can help break intergenerational transfer of adversity.

Background: Individuals with opioid use disorder (OUD) often have significant medical and behavioral health needs that are unaddressed. Opioid treatment programs (OTP) are uniquely positioned to provide integrated services for OUD, physical and mental health but are underutilized for this purpose. This study aims to describe the physical and mental healthcare needs of OTP clients in order to inform integrated care implementation in OTPs. Method: OTP clients (n = 1261) in an integrated care program in the Bronx borough of New York City were assessed for mental health symptoms (e.g., anxiety, depression), chronic disease indicators (e.g., blood pressure, cholesterol), and general functioning (e.g., capability of managing healthcare needs). Results: Symptoms of anxiety, post-traumatic stress, and depression were common. Self-reported health status and level of functioning were generally poor. Heavy smoking and obesity were the most frequent physical health risks. Other chronic disease indicators (e.g., blood pressure) showed 25-46% may be at risk. Sixty percent had multiple mental health risks and 85% had multiple physical health risks. Older clients had a higher rate of hypertension and diabetes risk than younger clients. Conclusions: Integrated care programs in OTPs must be prepared to address and coordinate care for chronic mental and physical health conditions in addition to OUD.