Translating Evidence into Practice: ACOs' Use of Care Plans for Patients with Complex Health Needs.

BACKGROUND: Care plans are an evidence-based strategy, encouraged by the Centers for Medicare and Medicaid Services, and are used to manage the care of patients with complex health needs that have been shown to lead to lower hospital costs and improved patient outcomes. Providers participating in payment reform, such as accountable care organizations, may be more likely to adopt care plans to manage complex patients. OBJECTIVE: To understand how Medicare accountable care organizations (ACOs) use care plans to manage patients with complex clinical needs. DESIGN: A qualitative study using semi-structured interviews with Medicare ACOs. PARTICIPANTS: Thirty-nine interviews were conducted across 18 Medicare ACOs with executive-level leaders and associated clinical and managerial staff. APPROACH: Development, structure, use, and management of care plans for complex patients at Medicare ACOs. KEY RESULTS: Most (11) of the interviewed ACOs reported using care plans to manage care of complex patients. All care plans include information about patient history, current medical needs, and future care plans. Beyond the core elements, care plans included elements based on the ACO's planned use and level of staff and patient engagement with care planning. Most care plans were developed and maintained by care management (not clinical) staff. CONCLUSIONS: ACOs are using care plans for patients with complex needs, but their use of care plans does not always meet the best practices. In many cases, ACO usage of care plans does not align with prescribed best practices: ACOs are adapting use of care plans to better fit the needs of patients and providers.

Role of Nurse Practitioners in Caring for Patients With Complex Health Needs.

OBJECTIVE: The objective of this study was to estimate trends in the percentage of Medicare beneficiaries cared for by nurse practitioners from 2012 to 2017, to characterize beneficiaries cared for by nurse practitioners in 2017, and to examine how the percentage of beneficiaries cared for by nurse practitioners varies by practice characteristics. DESIGN: An observational study of 2012-2017 Medicare fee-for-service beneficiaries' ambulatory visits. We computed the percentage of beneficiaries with 1 or more ambulatory visits from nurse practitioners and the percentage of beneficiaries receiving the plurality of their ambulatory visits from a nurse practitioner versus a physician (ie, predominant provider). We compared beneficiary demographics, clinical characteristics, and utilization by the predominant provider. We then characterized the predominant provider by practice characteristics. KEY RESULTS: In 2017, 28.9% of beneficiaries received any care from a nurse practitioner and 8.0% utilized nurse practitioners as their predominant provider-an increase from 4.4% in 2012. Among beneficiaries cared for by nurse practitioners in 2017, 25.9% had 3 or more chronic conditions compared with 20.8% of those cared for by physicians. Beneficiaries cared for in practices owned by health systems were more likely to have a nurse practitioner as their predominant provider compared with those attending practices that were independently owned (9.3% vs. 7.0%). CONCLUSIONS: Nurse practitioners are caring for Medicare beneficiaries with complex needs at rates that match or exceed their physician colleagues. The growing role of nurse practitioners, especially in health care systems, warrants attention as organizations embark on payment and delivery reform.

COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

BACKGROUND: Patients with cancer are purported to have poor COVID-19 outcomes. However, cancer is a heterogeneous group of diseases, encompassing a spectrum of tumour subtypes. The aim of this study was to investigate COVID-19 risk according to tumour subtype and patient demographics in patients with cancer in the UK. METHODS: We compared adult patients with cancer enrolled in the UK Coronavirus Cancer Monitoring Project (UKCCMP) cohort between March 18 and May 8, 2020, with a parallel non-COVID-19 UK cancer control population from the UK Office for National Statistics (2017 data). The primary outcome of the study was the effect of primary tumour subtype, age, and sex and on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence and the case-fatality rate during hospital admission. We analysed the effect of tumour subtype and patient demographics (age and sex) on prevalence and mortality from COVID-19 using univariable and multivariable models. FINDINGS: 319 (30·6%) of 1044 patients in the UKCCMP cohort died, 295 (92·5%) of whom had a cause of death recorded as due to COVID-19. The all-cause case-fatality rate in patients with cancer after SARS-CoV-2 infection was significantly associated with increasing age, rising from 0·10 in patients aged 40-49 years to 0·48 in those aged 80 years and older. Patients with haematological malignancies (leukaemia, lymphoma, and myeloma) had a more severe COVID-19 trajectory compared with patients with solid organ tumours (odds ratio [OR] 1·57, 95% CI 1·15-2·15; p<0·0043). Compared with the rest of the UKCCMP cohort, patients with leukaemia showed a significantly increased case-fatality rate (2·25, 1·13-4·57; p=0·023). After correction for age and sex, patients with haematological malignancies who had recent chemotherapy had an increased risk of death during COVID-19-associated hospital admission (OR 2·09, 95% CI 1·09-4·08; p=0·028). INTERPRETATION: Patients with cancer with different tumour types have differing susceptibility to SARS-CoV-2 infection and COVID-19 phenotypes. We generated individualised risk tables for patients with cancer, considering age, sex, and tumour subtype. Our results could be useful to assist physicians in informed risk-benefit discussions to explain COVID-19 risk and enable an evidenced-based approach to national social isolation policies. FUNDING: University of Birmingham and University of Oxford.

Integrated health and care systems in England: can they help prevent disease?

Objectives: Over the past 12 months, there has been increasing policy rhetoric regarding the role of the National Health Service (NHS) in preventing disease and improving population health. In particular, the NHS Long Term Plan sees integrated care systems (ICSs) and sustainability and transformation partnerships (STPs) as routes to improving disease prevention. Here, we place current NHS England integrated care plans in their historical context and review evidence on the relationship between integrated care and prevention. We ask how the NHS Long Term Plan may help prevent disease and explore the role of the 2019 ICS and STP plans in delivering this change. Methods: We reviewed the evidence underlying the relationship between integrated care and disease prevention, and analysed 2016 STP plans for content relating to disease prevention and population health. Results: The evidence of more integrated care leading to better disease prevention is weak. Although nearly all 2016 STP plans included a prevention or population health strategy, fewer than half specified how they will work with local government public health teams, and there was incomplete coverage across plans about how they would meet NHS England prevention priorities. Plans broadly focused on individual-level approaches to disease prevention, with few describing interventions addressing social determinants of health. Conclusions: For ICSs and STPs to meaningfully prevent disease and improve population health, they need to look beyond their 2016 plans and fill the gaps in the Long Term Plan on social determinants.

How Do Accountable Care Organizations Deliver Preventive Care Services? A Mixed-Methods Study.

BACKGROUND: The Affordable Care Act and the introduction of accountable care organizations (ACOs) have increased the incentives for patients and providers to engage in preventive care, for example, through quality metrics linked to disease prevention. However, little is known about how ACOs deliver preventive care services. OBJECTIVE: To understand how Medicare ACOs provide preventive care services to their attributed patients. DESIGN: Mixed-methods study using survey data reporting Medicare ACO capabilities in patient care management and interviews with high-performing ACOs. PARTICIPANTS: ACO executives completed survey data on 283 Medicare ACOs. These data were supplemented with 39 interviews conducted across 18 Medicare ACOs with executive-level leaders and associated clinical and managerial staff. MAIN MEASURES: Survey measures included ACO performance, organizational characteristics, collaboration experience, and capabilities in care management and quality improvement. Telephone interviews followed a semi-structured interview guide and explored the mechanisms used, and motivations of, ACOs to deliver preventive care services. KEY RESULTS: Medicare ACOs that reported being comprehensively engaged in the planning and management of patient care - including conducting reminders for preventive care services - had more beneficiaries and had a history of collaboration experience, but were not more likely to receive shared savings or achieve high-quality scores compared to other surveyed ACOs. Interviews revealed that offering annual wellness visits and having a system-wide approach to closing preventive care gaps are key mechanisms used by high-performing ACOs to address patients' preventive care needs. Few programs or initiatives were identified that specifically target clinically complex patients. Aside from meeting patient needs, motivations for ACOs included increasing patient attribution and meeting performance targets. CONCLUSIONS: ACOs are increasingly motivated to deliver preventive care services. Understanding the mechanisms and motivations used by high-performing ACOs may help both providers and payers to increase the use of preventive care.

PRIMEtime CE: a multistate life table model for estimating the cost-effectiveness of interventions affecting diet and physical activity.

BACKGROUND: Non-communicable diseases are the leading cause of death in England, and poor diet and physical inactivity are two of the principle behavioural risk factors. In the context of increasingly constrained financial resources, decision makers in England need to be able to compare the potential costs and health outcomes of different public health policies aimed at improving these risk factors in order to know where to invest so that they can maximise population health. This paper describes PRIMEtime CE, a multistate life table cost-effectiveness model that can directly compare interventions affecting multiple disease outcomes. METHODS: The multistate life table model, PRIMEtime Cost Effectiveness (PRIMEtime CE), is developed from the Preventable Risk Integrated ModEl (PRIME) and the PRIMEtime model. PRIMEtime CE uses routinely available data to estimate how changing diet and physical activity in England affects morbidity and mortality from heart disease, stroke, diabetes, liver disease, and cancers either directly or via raised blood pressure, cholesterol, and body weight. RESULTS: Model outcomes are change in quality adjusted life years, and change in English National Health Service and social care costs. CONCLUSION: This paper describes PRIMEtime CE and highlights its main strengths and limitations. The model can be used to compare any number of public policies affecting diet and physical activity, allowing decision makers to understand how they can maximise population health with limited financial resources.

Estimating the cost-effectiveness of salt reformulation and increasing access to leisure centres in England, with PRIMEtime CE model validation using the AdViSHE tool.

BACKGROUND: PRIMEtime CE is a multistate life table model that can directly compare the cost effectiveness of public health interventions affecting diet and physical activity levels, helping to inform decisions about how to spend finite resources. This paper estimates the costs and health outcomes in England of two scenarios: reformulating salt and expanding subsidised access to leisure centres. The results are used to help validate PRIMEtime CE, following the steps outlined in the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) tool. METHODS: The PRIMEtime CE model estimates the difference in quality adjusted life years (QALYs) and difference in NHS and social care costs of modelled interventions compared with doing nothing. The salt reformulation scenario models how salt consumption would change if food producers met the 2017 UK Food Standards Agency salt reformulation targets. The leisure centre scenario models change in physical activity levels if the Birmingham Be Active scheme (where swimming pools and gym access is free to residents during defined periods) was rolled out across England. The AdViSHE tool was developed by health economic modellers and divides model validation into five parts: validation of the conceptual model, input data validation, validation of computerised model, operational validation, and other validation techniques. PRIMEtime CE is discussed in relation to each part. RESULTS: Salt reformulation was dominant compared with doing nothing, and had a 10-year return on investment of £1.44 (£0.50 to £2.94) for every £1 spent. By contrast, over 10 years the Be Active expansion would cost £727,000 (£514,000 to £1,064,000) per QALY. PRIMEtime CE has good face validity of its conceptual model and has robust input data. Cross-validation produces mixed results and shows the impact of model scope, input parameters, and model structure on cost-per-QALY estimates. CONCLUSIONS: This paper illustrates how PRIMEtime CE can be used to compare the cost-effectiveness of two different public health measures affecting diet and physical activity levels. The AdViSHE tool helps to validate PRIMEtime CE, identifies some of the key drivers of model estimates, and highlights the challenges of externally validating public health economic models against independent data.

'Eyes In The Home': ACOs Use Home Visits To Improve Care Management, Identify Needs, And Reduce Hospital Use.

Home visits are used for a variety of services and patient populations. We used national survey data from physician practices and accountable care organizations (ACOs), paired with qualitative interviews, to learn about home visiting programs. ACO practices were more likely to report using care transitions home visits than non-ACO practices were. Eighty percent of ACOs reported using home visits for some of their patients, with larger ACOs more commonly using home visits. Interviewed ACOs reported using home visits as part of care management and care transitions programs as well as to evaluate patients' home environments and identify needs. ACOs most often used nonphysician staff to conduct home visits. Home visit implementation for some types of patients can be challenging because of barriers related to reimbursement, staffing, and resources.

Estimating the potential impact of the UK government's sugar reduction programme on child and adult health: modelling study.

OBJECTIVE: To estimate the impact of the UK government's sugar reduction programme on child and adult obesity, adult disease burden, and healthcare costs. DESIGN: Modelling study. SETTING: Simulated scenario based on National Diet and Nutrition Survey waves 5 and 6, England. PARTICIPANTS: 1508 survey respondents were used to model weight change among the population of England aged 4-80 years. MAIN OUTCOME MEASURES: Calorie change, weight change, and body mass index change were estimated for children and adults. Impact on non-communicable disease incidence, quality adjusted life years, and healthcare costs were estimated for adults. Changes to disease burden were modelled with the PRIMEtime-CE Model, based on the 2014 population in England aged 18-80. RESULTS: If the sugar reduction programme was achieved in its entirety and resulted in the planned sugar reduction, then the calorie reduction was estimated to be 25 kcal/day (1 kcal=4.18 kJ=0.00418 MJ) for 4-10 year olds (95% confidence interval 23 to 26), 25 kcal/day (24 to 28) for 11-18 year olds, and 19 kcal/day (17 to 20) for adults. The reduction in obesity could represent 5.5% of the baseline obese population of 4-10 year olds, 2.2% of obese 11-18 year olds, and 5.5% of obese 19-80 year olds. A modelled 51 729 quality adjusted life years (95% uncertainty interval 45 768 to 57 242) were saved over 10 years, including 154 550 (132 623 to 174 604) cases of diabetes and relating to a net healthcare saving of £285.8m (€332.5m, $373.5m; £249.7m to £319.8m). CONCLUSIONS: The UK government's sugar reduction programme could reduce the burden of obesity and obesity related disease, provided that reductions in sugar levels and portion sizes do not prompt unanticipated changes in eating patterns or product formulation.

Estimating comparable English healthcare costs for multiple diseases and unrelated future costs for use in health and public health economic modelling.

OBJECTIVES: Healthcare interventions, and particularly those in public health may affect multiple diseases and significantly prolong life. No consensus currently exists for how to estimate comparable healthcare costs across multiple diseases for use in health and public health cost-effectiveness models. We aim to describe a method for estimating comparable disease specific English healthcare costs as well as future healthcare costs from diseases unrelated to those modelled. METHODS: We use routine national datasets including programme budgeting data and cost curves from NHS England to estimate annual per person costs for diseases included in the PRIMEtime model as well as age and sex specific costs due to unrelated diseases. RESULTS: The 2013/14 annual cost to NHS England per prevalent case varied between £3,074 for pancreatic cancer and £314 for liver disease. Costs due to unrelated diseases increase with age except for a secondary peak at 30-34 years for women reflecting maternity resource use. CONCLUSIONS: The methodology described allows health and public health economic modellers to estimate comparable English healthcare costs for multiple diseases. This facilitates the direct comparison of different health and public health interventions enabling better decision making.

Should we tax unhealthy food and drink?

The global burden of obesity leads to significant morbidity and has major economic implications. In April 2018, Britain will join a growing number of countries attempting to tackle this using fiscal measures when the UK Soft Drinks Industry Levy is introduced. We review recent evidence from natural experiments of the impact of health-related food and drink taxes on consumer behaviour, and discuss the possible consequences of these approaches on purchases and health. We highlight some of the potential indirect consequences and the importance of robust prospective evaluation.

Who breaches the four-hour emergency department wait time target? A retrospective analysis of 374,000 emergency department attendances between 2008 and 2013 at a type 1 emergency department in England.

BACKGROUND: The four-hour target is a key hospital emergency department performance indicator in England and one that drives the physical and organisational design of the ED. Some studies have identified time of presentation as a key factor affecting waiting times. Few studies have investigated other determinants of breaching the four-hour target. Therefore, our objective was to describe patterns of emergency department breaches of the four-hour wait time target and identify patients at highest risk of breaching. METHODS: This was a retrospective cohort study of a large type 1 Emergency department at an NHS teaching hospital in Oxford, England. We analysed anonymised individual level patient data for 378,873 emergency department attendances, representing all attendances between April 2008 and April 2013. We examined patient characteristics and emergency department presentation circumstances associated with the highest likelihood of breaching the four-hour wait time target. RESULTS: We used 374,459 complete cases for analysis. In total, 8.3% of all patients breached the four-hour wait time target. The main determinants of patients breaching the four-hour wait time target were hour of arrival to the ED, day of the week, patient age, ED referral source, and the types of investigations patients receive (p < 0.01 for all associations). Patients most likely to breach the four-hour target were older, presented at night, presented on Monday, received multiple types of investigation in the emergency department, and were not self-referred (p < 0.01 for all associations). Patients attending from October to February had a higher odds of breaching compared to those attending from March to September (OR 1.63, 95% CI 1.59 to 1.66). CONCLUSIONS: There are a number of independent patient and circumstantial factors associated with the probability of breaching the four-hour ED wait time target including patient age, ED referral source, the types of investigations patients receive, as well as the hour, day, and month of arrival to the ED. Efforts to reduce the number of breaches could explore late-evening/overnight staffing, access to diagnostic tests, rapid discharge facilities, and early assessment and input on diagnostic and management strategies from a senior practitioner.

Health impact assessment of the UK soft drinks industry levy: a comparative risk assessment modelling study.

BACKGROUND: In March, 2016, the UK Government proposed a tiered levy on sugar-sweetened beverages (SSBs; high tax for drinks with >8 g of sugar per 100 mL, moderate tax for 5-8 g, and no tax for <5 g). We estimate the effect of possible industry responses to the levy on obesity, diabetes, and dental caries. METHODS: We modelled three possible industry responses: reformulation to reduce sugar concentration, an increase of product price, and a change of the market share of high-sugar, mid-sugar, and low-sugar drinks. For each response, we defined a better-case and worse-case health scenario. We developed a comparative risk assessment model to estimate the UK health impact of each scenario on prevalence of obesity and incidence of dental caries and type 2 diabetes. The model combined data for sales and consumption of SSBs, disease incidence and prevalence, price elasticity estimates, and estimates of the association between SSB consumption and disease outcomes. We drew the disease association parameters from a meta-analysis of experimental studies (SSBs and weight change), a meta-analysis of prospective cohort studies (type 2 diabetes), and a prospective cohort study (dental caries). FINDINGS: The best modelled scenario for health is SSB reformulation, resulting in a reduction of 144 383 (95% uncertainty interval 5102-306 743; 0·9%) of 15 470 813 adults and children with obesity in the UK, 19 094 (6920-32 678; incidence reduction of 31·1 per 100 000 person-years) fewer incident cases of type 2 diabetes per year, and 269 375 (82 211-470 928; incidence reduction of 4·4 per 1000 person-years) fewer decayed, missing, or filled teeth annually. An increase in the price of SSBs in the better-case scenario would result in 81 594 (3588-182 669; 0·5%) fewer adults and children with obesity, 10 861 (3899-18 964; 17·7) fewer incident cases of diabetes per year, and 149 378 (45 231-262 013; 2·4) fewer decayed, missing, or filled teeth annually. Changes to market share to increase the proportion of low-sugar drinks sold in the better-case scenario would result in 91 042 (4289-204 903; 0·6%) fewer adults and children with diabetes, 1528 (4414-21 785; 19·7) fewer incident cases of diabetes per year, and 172 718 (47 919-294 499; 2·8) fewer decayed, missing, or filled teeth annually. The greatest benefit for obesity and oral health would be among individuals aged younger than 18 years, with people aged older than 65 years having the largest absolute decreases in diabetes incidence. INTERPRETATION: The health impact of the soft drinks levy is dependent on its implementation by industry. Uncertainty exists as to how industry will react and about estimation of health outcomes. Health gains could be maximised by substantial product reformulation, with additional benefits possible if the levy is passed on to purchasers through raising of the price of high-sugar and mid-sugar drinks and activities to increase the market share of low-sugar products. FUNDING: None.

Choosing an epidemiological model structure for the economic evaluation of non-communicable disease public health interventions.

Non-communicable diseases are the leading global causes of mortality and morbidity. Growing pressures on health services and on social care have led to increasing calls for a greater emphasis to be placed on prevention. In order for decisionmakers to make informed judgements about how to best spend finite public health resources, they must be able to quantify the anticipated costs, benefits, and opportunity costs of each prevention option available. This review presents a taxonomy of epidemiological model structures and applies it to the economic evaluation of public health interventions for non-communicable diseases. Through a novel discussion of the pros and cons of model structures and examples of their application to public health interventions, it suggests that individual-level models may be better than population-level models for estimating the effects of population heterogeneity. Furthermore, model structures allowing for interactions between populations, their environment, and time are often better suited to complex multifaceted interventions. Other influences on the choice of model structure include time and available resources, and the availability and relevance of previously developed models. This review will help guide modelers in the emerging field of public health economic modeling of non-communicable diseases.

Simulating the impact on health of internalising the cost of carbon in food prices combined with a tax on sugar-sweetened beverages.

BACKGROUND: Rising greenhouse gas emissions (GHGEs) have implications for health and up to 30 % of emissions globally are thought to arise from agriculture. Synergies exist between diets low in GHGEs and health however some foods have the opposite relationship, such as sugar production being a relatively low source of GHGEs. In order to address this and to further characterise a healthy sustainable diet, we model the effect on UK non-communicable disease mortality and GHGEs of internalising the social cost of carbon into the price of food alongside a 20 % tax on sugar sweetened beverages (SSBs). METHODS: Developing previously published work, we simulate four tax scenarios: (A) a GHGEs tax of £2.86/tonne of CO2 equivalents (tCO2e)/100 g product on all products with emissions greater than the mean across all food groups (0.36 kgCO2e/100 g); (B) scenario A but with subsidies on foods with emissions lower than 0.36 kgCO2e/100 g such that the effect is revenue neutral; (C) scenario A but with a 20 % sales tax on SSBs; (D) scenario B but with a 20 % sales tax on SSBs. An almost ideal demand system is used to estimate price elasticities and a comparative risk assessment model is used to estimate changes to non-communicable disease mortality. RESULTS: We estimate that scenario A would lead to 300 deaths delayed or averted, 18,900 ktCO2e fewer GHGEs, and £3.0 billion tax revenue; scenario B, 90 deaths delayed or averted and 17,100 ktCO2e fewer GHGEs; scenario C, 1,200 deaths delayed or averted, 18,500 ktCO2e fewer GHGEs, and £3.4 billion revenue; and scenario D, 2,000 deaths delayed or averted and 16,500 ktCO2e fewer GHGEs. Deaths averted are mainly due to increased fibre and reduced fat consumption; a SSB tax reduces SSB and sugar consumption. CONCLUSIONS: Incorporating the social cost of carbon into the price of food has the potential to improve health, reduce GHGEs, and raise revenue. The simple addition of a tax on SSBs can mitigate negative health consequences arising from sugar being low in GHGEs. Further conflicts remain, including increased consumption of unhealthy foods such as cakes and nutrients such as salt.