Efficiency and productivity gains of robotic surgery: The case of the English National Health Service.

This paper examines the effect of new medical technology (robotic surgery) on efficiency gains and productivity changes for surgical treatment in patients with prostate cancer from the perspective of a public health sector organization. In particular, we consider three interrelated surgical technologies within the English National Health System: robotic, laparoscopic and open radical prostatectomy. Robotic and laparoscopic techniques are minimally invasive procedures with similar clinical benefits. While the clinical benefits in adopting robotic surgery over laparoscopic intervention are unproven, it requires a high initial investment cost and carries high on-going maintenance costs. Using data from Hospital Episode Statistics for the period 2000-2018, we observe growing volumes of prostatectomies over time, mostly driven by an increase in robotic-assisted surgeries, and further analyze whether hospital providers that adopted a robot see improved measures of throughput. We then quantify changes in total factor and labor productivity arising from the use of this technology. We examine the impact of robotic adoption on efficiency gains employing a staggered difference-in-difference estimator and find evidence of a 50% reduction in length of stay (LoS), 49% decrease in post-LoS and 44% and 46% decrease in postoperative visits after 1 year and 2 years, respectively. Productivity analysis shows the growth in radical prostatectomy volume is sustained with a relatively stable number of urology surgeons. The robotic technique increases total production at the hospital level between 21% and 26%, coupled with a 29% improvement in labor productivity. These benefits lend some, but not overwhelming support for the large-scale hospital investments in such costly technology.

Patient outcomes, efficiency, and adverse events for elective hip and knee replacement in private and NHS hospitals: a population-based cohort study in England.

Background: Since the early 2000s, the National Health Service (NHS) in England has expanded provision of publicly funded care in private hospitals as a strategy to meet growing demand for elective care. This study aims to compare patient outcomes, efficiency and adverse events in private and NHS hospitals when providing elective hip and knee replacement. Methods: We conducted a population-based cohort study including patients ≥18 years, undergoing a publicly funded elective hip or knee replacement in private and NHS hospitals in England between January 1st 2016 and March 31st 2019. Comparative probability was estimated for three patient outcome measures (in-hospital mortality, emergency readmissions with 28 days, hospital transfers), two efficiency measures (pre-operative length of stay (LOS) >0 day and post-operative LOS >2 days), and four adverse events (hospital-associated infection, adverse drug reactions, pressure ulcers, venous thromboembolism). Probit regression was used to adjust for observable confounding followed by instrumental variable (IV) analyses to also account for unobserved confounding at the patient-level. Propensity score matching was then used as a robustness check. Findings: Our study sample included 169,232 patients in private hospitals, and 262,659 patients in NHS hospitals. Estimates from probit regression indicated that treatment in private hospital was associated with reduced probability of in-hospital mortality (-0.0009, 95% CI -0.0010, -0.0007), emergency readmissions (-0.0181, 95% CI -0.0191, -0.0172), hospital transfers (-0.0076, 95% CI -0.0084, -0.0068), prolonged post-operative LOS (-0.1174, 95% CI -0.1547, -0.0801), hospital-associated infection (-0.0115, 95% CI -0.0123, -0.0107), adverse drug reactions (-0.0051, 95% CI -0.0056, -0.0046), pressure ulcers (-0.0017, 95% CI -0.0019, -0.0014), and venous thromboembolism (-0.0027, 95% CI -0.0031, -0.0022). IV analyses produced no significant differences between private and NHS hospitals, except for lower probability in private hospitals of hospital-associated infection (-0.0057, 95% CI -0.0081, -0.0032), and greater probability in private hospitals of prolonged post-operative LOS (0.2653, 95% CI 0.1833, 0.3472). Propensity score matching produced similar results to probit regression. Interpretation: Our findings indicate there is potentially important unobservable confounding at the patient-level between private and NHS hospitals not adjusted for when using probit regression or propensity score matching. Funding: This research did not receive any dedicated funding.

Did the Acute Frailty Network improve outcomes for older people living with frailty? A staggered difference-in-difference panel event study.

OBJECTIVES: To evaluate whether the Acute Frailty Network (AFN) was more effective than usual practice in supporting older people living with frailty to return home from hospital sooner and healthier. DESIGN: Staggered difference-in-difference panel event study allowing for differential effects across intervention cohorts. SETTING: All English National Health Service (NHS) acute hospital sites. PARTICIPANTS: All 1 410 427 NHS patients aged 75+ with high frailty risk who had an emergency hospital admission to acute, general or geriatric medicine departments between 1 January 2012 and 31 March 2019. INTERVENTION: Membership of the AFN, a quality improvement collaborative designed to support acute hospitals in England deliver evidence-based care for older people with frailty. 66 hospital sites joined the AFN in six sequential cohorts, the first starting in January 2015, the sixth in May 2018. Usual care was delivered in the remaining 248 control sites. MAIN OUTCOME MEASURES: Length of hospital stay, in-hospital mortality, institutionalisation, hospital readmission. RESULTS: No significant effects of AFN membership were found for any of the four outcomes nor were there significant effects for any individual cohort. CONCLUSIONS: To realise its aims, the AFN might need to develop better resourced intervention and implementation strategies.

Living longer in declining health: Factors driving healthcare costs among older people.

BACKGROUND: Developed countries are facing challenges in caring for people who are living longer but with a greater morbidity burden. Such people are likely to be regular users of healthcare. OBJECTIVES: Our analytical aim is to identify factors that explain healthcare costs among: (1) people over 55 years old; (2) the top 5% and 1% high-cost users among this population; (3) those that transition into the top 5% and 1% from one year to the next; (4) those that appear in the top 5% and 1% over multiple years; and (5) those that remain in the top 5% and 1% over consecutive years. METHODS: The data covered 2011 to 2017 and comprised 1,485,170 observations for a random sample of 224,249 people aged over 55 years in the Catalan region of Spain. We analysed each person's annual healthcare costs across all public healthcare settings related to their age, gender, socio-economic status (SES), whether or not and when they died, and morbidity status, through Adjusted Morbidity Groups. RESULTS: After controlling for morbidity status, the oldest people did not have the highest costs and were less likely to be among the most costly patients. There was also only a modest impact on costs associated with SES and with dying. Healthcare costs were substantially higher for those with a neoplasm or four or more long term conditions (LTCs), costs rising with the complexity of their conditions. These morbidity indicators were also the most important factors associated with being and remaining in the top 5% or top 1% of costs. CONCLUSION: Our results suggest that age and proximity to death are poor predictors of higher costs. Rather, healthcare costs are explained mainly by morbidity status, particularly whether someone has neoplasms or multiple LTCs. Morbidity measures should be included in future studies of healthcare costs.

Divergent COVID-19 vaccine policies: Policy mapping of ten European countries.

BACKGROUND: The COVID-19 pandemic highlighted the fragmented nature of governmental policy decisions in Europe. However, the extent to which COVID-19 vaccination policies differed between European countries remains unclear. Here, we mapped the COVID-19 vaccination policies that were in effect in January 2022 as well as booster regulations in April 2022 in Austria, Denmark, England, France, Germany, Ireland, Italy, the Netherlands, Poland, and Spain. METHODS: National public health and health policy experts from these ten European nations developed and completed an electronic questionnaire. The questionnaire included a series of questions that addressed six critical components of vaccine implementation, including (1) authorization, (2) prioritization, (3) procurement and distribution, (4) data collection, (5) administration, and (6) mandate requirements. RESULTS: Our findings revealed significant variations in COVID-19 vaccination policies across Europe. We observed critical differences in COVID-19 vaccine formulations authorized for use, as well as the specific groups that were provided with priority access. We also identified discrepancies in how vaccination-related data were recorded in each country and what vaccination requirements were implemented. CONCLUSION: Each of the ten European nations surveyed in this study reported different COVID-19 vaccination policies. These differences complicated efforts to provide a coordinated pandemic response. These findings might alert policymakers in Europe of the need to coordinate their efforts to avoid fostering divergent and socially disruptive policies.

Factors associated with longer wait times, admission and reattendances in older patients attending emergency departments: an analysis of linked healthcare data.

BACKGROUND AND OBJECTIVE: Care for older patients in the ED is an increasingly important issue with the ageing society. To better assess the quality of care in this patient group, we assessed predictors for three outcomes related to ED care: being seen and discharged within 4 hours of ED arrival; being admitted from ED to hospital and reattending the ED within 30 days. We also used these outcomes to identify better-performing EDs. METHODS: The CUREd Research Database was used for a retrospective observational study of all 1 039 251 attendances by 368 754 patients aged 75+ years in 18 type 1 EDs in the Yorkshire and the Humber region of England between April 2012 and March 2017. We estimated multilevel logit models, accounting for patients' characteristics and contact with emergency services prior to ED arrival, time variables and the ED itself. RESULTS: Patients in the oldest category (95+ years vs 75-80 years) were more likely to have a long ED wait (OR=1.13 (95% CI=1.10 to 1.15)), hospital admission (OR=1.26 (95% CI=1.23 to 1.29)) and ED reattendance (OR=1.09 (95% CI=1.06 to 1.12)). Those who had previously attended (3+ vs 0 previous attendances) were more likely to have long wait (OR=1.07 (95% CI=1.06 to 1.08)), hospital admission (OR=1.10 (95% CI=1.09 to 1.12)) and ED attendance (OR=3.13 (95% CI=3.09 to 3.17)). Those who attended out of hours (vs not out of hours) were more likely to have a long ED wait (OR=1.33 (95% CI=1.32 to 1.34)), be admitted to hospital (OR=1.19 (95% CI=1.18 to 1.21)) and have ED reattendance (OR=1.07 (95% CI=1.05 to 1.08)). Those living in less deprived decile (vs most deprived decile) were less likely to have any of these three outcomes: OR=0.93 (95% CI=0.92 to 0.95), 0.92 (95% CI=0.90 to 0.94), 0.86 (95% CI=0.84 to 0.88). These characteristics were not strongly associated with long waits for those who arrived by ambulance. Emergency call handler designation was the strongest predictor of long ED waits and hospital admission: compared with those who did not arrive by ambulance; ORs for these outcomes were 1.18 (95% CI=1.16 to 1.20) and 1.85 (95% CI=1.81 to 1.89) for those designated less urgent; 1.37 (95% CI=1.33 to 1.40) and 2.13 (95% CI=2.07 to 2.18) for urgent attendees; 1.26 (95% CI=1.23 to 1.28) and 2.40 (95% CI=2.36 to 2.45) for emergency attendees; and 1.37 (95% CI=1.28 to 1.45) and 2.42 (95% CI=2.26 to 2.59) for those with life-threatening conditions. We identified two EDs whose patients were less likely to have a long ED, hospital admission or ED reattendance than other EDs in the region. CONCLUSIONS: Age, previous attendance and attending out of hours were all associated with an increased likelihood of exceeding 4 hours in the ED, hospital admission and reattendance among patients over 75 years. These differences were less pronounced among those arriving by ambulance. Emergency call handler designation could be used to identify those at the highest risk of long ED waits, hospital admission and ED reattendance.

Examining the effect of interventions in emergency care for older people using a system dynamics decision support tool.

BACKGROUND: Rising demand for Emergency and Urgent Care is a major international issue and outcomes for older people remain sub-optimal. Embarking upon large-scale service development is costly in terms of time, energy and resources with no guarantee of improved outcomes; computer simulation modelling offers an alternative, low risk and lower cost approach to explore possible interventions. METHOD: A system dynamics computer simulation model was developed as a decision support tool for service planners. The model represents patient flow through the emergency care process from the point of calling for help through ED attendance, possible admission, and discharge or death. The model was validated against five different evidence-based interventions (geriatric emergency medicine, front door frailty, hospital at home, proactive care and acute frailty units) on patient outcomes such as hospital-related mortality, readmission and length of stay. RESULTS: The model output estimations are consistent with empirical evidence. Each intervention has different levels of effect on patient outcomes. Most of the interventions show potential reductions in hospital admissions, readmissions and hospital-related deaths. CONCLUSIONS: System dynamics modelling can be used to support decisions on which emergency care interventions to implement to improve outcomes for older people.

Evaluation of the NHS England evidence-based interventions programme: a difference-in-difference analysis.

BACKGROUND: The NHS England evidence-based interventions programme (EBI), launched in April 2019, is a novel nationally led initiative to encourage disinvestment in low value care. METHOD: We sought to evaluate the effectiveness of this policy by using a difference-in-difference approach to compare changes in volume between January 2016 and February 2020 in a treatment group of low value procedures against a control group unaffected by the EBI programme during our period of analysis but subsequently identified as candidates for disinvestment. RESULTS: We found only small differences between the treatment and control group after implementation, with reductions in volumes in the treatment group 0.10% (95% CI 0.09% to 0.11%) smaller than in the control group (equivalent to 16 low value procedures per month). During the month of implementation, reductions in volumes in the treatment group were 0.05% (95% CI 0.03% to 0.06%) smaller than in the control group (equivalent to 7 low value procedures). Using triple difference estimators, we found that reductions in volumes were 0.35% (95% CI 0.26% to 0.44%) larger in NHS hospitals than independent sector providers (equivalent to 47 low value procedures per month). We found no significant differences between clinical commissioning groups that did or did not volunteer to be part of a demonstrator community to trial EBI guidance, but found reductions in volume were 0.06% (95% CI 0.04% to 0.08%) larger in clinical commissioning groups that posted a deficit in the financial year 2018/19 before implementation (equivalent to 4 low value procedures per month). CONCLUSIONS: Our analysis shows that the EBI programme did not accelerate disinvestment for procedures under its remit during our period of analysis. However, we find that financial and organisational factors may have had some influence on the degree of responsiveness to the EBI programme.

Assessing The Dangers Of A Hospital Stay For Patients With Developmental Disability In England, 2017-19.

People with developmental disability have higher health care needs and lower life expectancy compared with the general population. Poor quality of care resulting from interpersonal and systemic discrimination may further entrench existing inequalities. We examined the prevalence of five avoidable in-hospital patient safety incidents (adverse drug reactions, hospital-acquired infections, pressure ulcers, postoperative pulmonary embolism or deep vein thrombosis, and postoperative sepsis) for four developmental disability groups (people with intellectual disability, chromosomal abnormalities, pervasive developmental disorders, and congenital malformation syndrome) in the English National Health Service during the period April 2017-March 2019. We found that the likelihood of experiencing harm in disability groups was up to 2.7-fold higher than in patients without developmental disability. Patient safety incidents led to an excess length-of-stay in hospital of 3.6-15.4 days and an increased mortality risk of 1.4-15.0 percent. We show persisting quality differences in patients with developmental disability, requiring an explicit national policy focus on the needs of such patients to reduce inequalities, reach parity of care, and lower the burden on health system resources.

A comparison between the clinical frailty scale and the hospital frailty risk score to risk stratify older people with emergency care needs.

BACKGROUND: Older adults living with frailty who require treatment in hospitals are increasingly seen in the Emergency Departments (EDs). One quick and simple frailty assessment tool-the Clinical Frailty Scale (CFS)-has been embedded in many EDs in the United Kingdom (UK). However, it carries time/training and cost burden and has significant missing data. The Hospital Frailty Risk Score (HFRS) can be automated and has the potential to reduce costs and increase data availability, but has not been tested for predictive accuracy in the ED. The aim of this study is to assess the correlation between and the ability of the CFS at the ED and HFRS to predict hospital-related outcomes. METHODS: This is a retrospective cohort study using data from Leicester Royal Infirmary hospital during the period from 01/10/2017 to 30/09/2019. We included individuals aged + 75 years as the HFRS has been only validated for this population. We assessed the correlation between the CFS and HFRS using Pearson's correlation coefficient for the continuous scores and weighted kappa scores for the categorised scores. We developed logistic regression models (unadjusted and adjusted) to estimate Odds Ratios (ORs) and Confidence Intervals (CIs), so we can assess the ability of the CFS and HFRS to predict 30-day mortality, Length of Stay (LOS) > 10 days, and 30-day readmission. RESULTS: Twelve thousand two hundred thirty seven individuals met the inclusion criteria. The mean age was 84.6 years (SD 5.9) and 7,074 (57.8%) were females. Between the CFS and HFRS, the Pearson correlation coefficient was 0.36 and weighted kappa score was 0.15. When comparing the highest frailty categories to the lowest frailty category within each frailty score, the ORs for 30-day mortality, LOS > 10 days, and 30-day readmission using the CFS were 2.26, 1.36, and 1.64 and for the HFRS 2.16, 7.68, and 1.19. CONCLUSION: The CFS collected at the ED and the HFRS had low/slight agreement. Both frailty scores were shown to be predictors of adverse outcomes. More research is needed to assess the use of historic HFRS in the ED.

Emergency contracting and the delivery of elective care services across the English National Health Service and independent sector during COVID-19: a descriptive analysis.

BACKGROUND: Following a virtual standstill in the delivery of elective procedures in England, a national block contract between the NHS and the independent sector aimed to help restart surgical care. This study aims to describe subsequent changes in trends in elective care service delivery following implementation of the initial iteration of this contract. METHODS: Population-based retrospective cohort study, assessing the delivery of all publicly funded and privately funded elective care delivered in England between 1 April 2020 and 31 July 2020 compared with the same period in 2019. Discharge data from the Hospital Episode Statistics and private healthcare data from the Private Health Information Network was stratified by specialty, procedure, length of stay and patient complexity in terms of age and Charlson Comorbidity Index. RESULTS: COVID-19 significantly reduced publicly funded elective care activity, though changes were more pronounced in the independent sector (-65.1%) compared with the NHS (-52.7%), whereas reductions in privately funded elective care activity were similar in both independent sector hospitals (-74.2%) and NHS hospitals (-72.9%). Patient complexity increased in the independent sector compared with the previous year, with mixed findings in NHS hospitals. Most specialties, irrespective of sector or funding mechanisms, experienced a reduction in hospital admissions. However, some specialities, including medical oncology, clinical oncology, clinical haematology and cardiology, experienced an increase in publicly-funded elective care activity in the independent sector. CONCLUSION: Elective care delivered by the independent sector remained significantly below historic levels, although this overlooks significant variation between regions and specialities. There may be opportunities to learn from regions which achieved more significant increases in publicly funded elective care in independent sector providers as a strategy to address the growing backlog of elective care.

The association between frailty risk and COVID-19-associated all-mortality in hospitalised older people: a national cohort study.

INTRODUCTION: Frailty has emerged as an important construct to support clinical decision-making during the COVID-19 pandemic. However, doubts remain related to methodological limitations of published studies. METHODS: Retrospective cohort study of all people aged 75 + admitted to hospital in England between 1 March 2020 and 31 July 2021. COVID-19 and frailty risk were captured using International Classification of Disease-10 (ICD-10) diagnostic codes. We used the generalised gamma model to estimate accelerated failure time, reporting unadjusted and adjusted results. RESULTS: The cohort comprised 103,561 individuals, mean age 84.1, around half female, 82% were White British with a median of two comorbidities. Frailty risk was distributed approximately 20% low risk and 40% each at intermediate or high risk. In the unadjusted survival plots, 28-day mortality was almost 50% for those with an ICD-10 code of U071 (COVID-19 virus identified), and 25-35% for those with U072 (COVID-19 virus not identified). In the adjusted analysis, the accelerated failure time estimates for those with intermediate and high frailty risk were 0.63 (95% CI 0.58-0.68) and 0.67 (95% CI 0.62-0.72) fewer days alive respectively compared to those with low frailty risk with an ICD-10 diagnosis of U072 (reference category). CONCLUSION: In older people with confirmed COVID-19, both intermediate and high frailty risk were associated with reduced survival compared to those with low frailty risk.

The diffusion of robotic surgery: Examining technology use in the English NHS.

This paper examines the adoption and diffusion of medical technology as associated with the dramatic recent increase in the surgical use of robots. We consider specifically the sequential adoption and diffusion patterns of three interrelated surgical technologies within a single healthcare system (the English NHS): robotic, laparoscopic and open radical prostatectomy. Robotic and laparoscopic techniques are minimally invasive procedures with similar patient benefits, but the newer robotic technique requires a high initial investment cost to purchase the robot and carries high maintenance costs over time. Using data from a large UK administrative database, Hospital Episodes Statistics, for the period 2000-2018, we analyse 173 hospitals performing radical prostatectomy, the most prevalent and earliest surgical area of adoption of robotic surgery. Our empirical analysis first identifies substitution effects, with robotic surgery replacing the incumbent technology, including the recently diffused laparoscopic technology. We then quantify the spillover of robotic surgery as it diffuses to other surgical specialties. Finally, we perform time-to-event analysis at the hospital level to quantitatively examine the adoption. Results show that a higher number of urologists and a wealthier referral area favor robot adoption.

Trends and characteristics of hospitalisations from the harmful use of opioids in England between 2008 and 2018: Population-based retrospective cohort study.

OBJECTIVE: To examine the trends and characteristics of opioid-related hospital admissions in England over 10 years, and its burden for the National Health Service and public finances. DESIGN: Patient-level data from the Hospital Episode Statistics database to examine all opioid-related hospitalisations from 2008 to 2018, stratified by type of opioid admission and patient demographics. SETTING: All National Health Service hospitals in England. PARTICIPANTS: Patients hospitalised from the harmful use of opioids. MAIN OUTCOME MEASURES: The number of opioid-related hospitalisations, length of stay, in-hospital mortality, 30-day readmission rate and treatment costs. RESULTS: Opioid-related hospitalisations increased by 48.9%, from 10,805 admissions in 2008 to 16,091 admissions in 2018, with total treatment costs of £137 million. The growth in opioid-related hospitalisations was 21% above the corresponding rate for all other emergency admissions in England. Relative changes showed that hospitalisations increased most for individuals older than 55 years (160%), those living in the most affluent areas of England (93.8%), and suffering from four co-morbidities (627.6%) or more. Hospitals reduced mean patient length of stay from 2.8 days to 1.1 days over 10 years. Mean in-hospital mortality was 0.4% and mean 30-day readmission risk was 16.6%. CONCLUSION: Opioid use is an increasing public health concern in England, though hospitalisation and mortality rates are less pronounced than in other countries. There are concerns about significant rises in hospitalisations from older, less deprived and sicker population groups. Our findings should prompt policymakers to go beyond monitoring mortality statistics when assessing the impacts of harmful use of opioids.

Opioid abuse and austerity: Evidence on health service use and mortality in England.

Opioid abuse has become a public health concern among many developed countries, with policymakers searching for strategies to mitigate adverse effects on population health and the wider economy. The United Kingdom has seen dramatic increases in opioid-related mortality following the financial crises in 2008. We examine the impact of spending cuts resulting from government prescribed austerity measures on opioid-related hospitalisations and mortality, thereby expanding on existing evidence suggesting a countercyclical relationship with macroeconomic performance. We take advantage of the variation in spending cuts passed down from central government to local authorities since 2010, with reductions in budgets of up to fifty percent in some areas resulting in the rescaling of vital public services. Longitudinal panel data methods are used to analyse a comprehensive, linked dataset that combines information from spending records, official death registry data and large administrative health care data for 152 local authorities (i.e., unitary authorities and county councils) in England between April 2010 and March 2017. A total of 280,827 people experienced a hospital admission in the English National Health Service because of an opioid overdose and 14,700 people died from opioids across the study period. Local authorities that experienced largest spending cuts also saw largest increases in opioid abuse. Interactions between changes in unemployment and spending items for welfare programmes show evidence about the importance for governments to protect populations from social-risk effects at times of deteriorating macroeconomic performance. Our study carries important lessons for countries aiming to address high rates of opioid abuse, including the United States, Canada and Sweden.

Comparing the dangers of a stay in English and German hospitals for high-need patients.

OBJECTIVE: To estimate the risk of an avoidable adverse event for high-need patients in England and Germany and the causal impact that has on outcomes. DATA SOURCES: We use administrative, secondary data for all hospital inpatients in 2018. Patient records for the English National Health Service are provided by the Hospital Episode Statistics database and for the German health care system accessed through the Research Data Center of the Federal Statistical Office. STUDY DESIGN: We calculated rates of three hospital-acquired adverse events and their causal impact on mortality and length of stay through propensity score matching and estimation of average treatment effects. DATA COLLECTION/EXTRACTION METHODS: Patients were identified based on diagnoses codes and translated Patient Safety Indicators developed by the Agency for Healthcare Research and Quality. PRINCIPAL FINDINGS: For the average hospital stay, the risk of an adverse event was 5.37% in the English National Health Service and 3.26% in the German health care system. High-need patients are more likely to experience an adverse event, driven by hospital-acquired infections (2.06%-4.45%), adverse drug reactions (2.37%-2.49%), and pressure ulcers (2.25%-0.45%). Adverse event risk is particularly high for patients with advancing illnesses (10.50%-27.11%) and the frail elderly (17.75%-28.19%). Compared to the counterfactual, high-need patients with an adverse event are more likely to die during their hospital stay and experience a longer length of stay. CONCLUSIONS: High-need patients are particularly vulnerable with an adverse event risking further deterioration of health status and adding resource use. Our results indicate the need to assess the costs and benefits of a hospital stay, particularly when care could be provided in settings considered less hazardous.

Patterns of adoption of robotic radical prostatectomy in the United States and England.

OBJECTIVES: To compare patterns of technological adoption of minimally invasive surgery for radical prostatectomy across the United States and England. DATA SOURCES: We examine radical prostatectomy in the United States and England between 2005 and 2017, using de-identified administrative claims data from the OptumLabs Data Warehouse in the United States and the Hospital Episodes Statistics in England. STUDY DESIGN: We conducted a longitudinal analysis of robotic, laparoscopic, and open surgery for radical prostatectomy. We compared the trends of adoption over time within and across countries. Next, we explored whether differential adoption patterns in the two health systems are associated with differences in volumes and patient characteristics. Finally, we explored the relationship between these adoption patterns and length of stay, 30-day readmission, and urology follow-up visits. DATA COLLECTION: Open, laparoscopic, and robotic radical prostatectomies are identified using Office of Population Censuses and Surveys Classification of Interventions and Procedures (OPCS) codes in England and International Classification of Diseases ninth revision (ICD9), ICD10, and Current Procedural Terminology (CPT) codes in the United States. PRINCIPAL FINDINGS: We identified 66,879 radical prostatectomies in England and 79,358 in the United States during 2005-2017. In both countries, open surgery dominates until 2009, where it is overtaken by minimally invasive surgery. The adoption of robotic surgery is faster in the United States. The adoption rates and, as a result, the observed centralization of volume, have been different across countries. In both countries, patients undergoing radical prostatectomies are older and have more comorbidities. Minimally invasive techniques show decreased length of stay and 30-day readmissions compared to open surgery. In the United States, robotic approaches were associated with lower length of stay and readmissions when compared to laparoscopic. CONCLUSIONS: Robotic surgery has become the standard approach for radical proctectomy in the United States and England, showing decreased length of stay and in 30-day readmissions compared to open surgery. Adoption rates and specialization differ across countries, likely a product of differences in cost-containment efforts.

The Association of Physical (in)Activity with Mental Health. Differences between Elder and Younger Populations: A Systematic Literature Review.

BACKGROUND: Physical activity is associated with mental health benefits. This systematic literature review summarises extant evidence regarding this association, and explores differences observed between populations over sixty-five years and those younger than sixty-five. METHODS: We reviewed articles and grey literature reporting at least one measure of physical activity and at least one mental disorder, in people of all ages. RESULTS: From the 2263 abstracts screened, we extracted twenty-seven articles and synthesized the evidence regarding the association between physical (in)activity and one or more mental health outcome measures. We confirmed that physical activity is beneficial for mental health. However, the evidence was mostly based on self-reported physical activity and mental health measures. Only one study compared younger and elder populations, finding that increasing the level of physical activity improved mental health for middle aged and elder women (no association was observed for younger women). Studies including only the elderly found a restricted mental health improvement due to physical activity. CONCLUSIONS: We found inverse associations between levels of physical activity and mental health problems. However, more evidence regarding the effect of ageing when measuring associations between physical activity and mental health is needed. By doing so, prescription of physical activity could be more accurately targeted.

The use of linked routine data to optimise calculation of the Hospital Frailty Risk Score on the basis of previous hospital admissions: a retrospective observational cohort study.

BACKGROUND: The Hospital Frailty Risk Score (HFRS) has been widely but inconsistently applied in published studies, particularly in how diagnostic information recorded in previous hospital admissions is used in its construction. We aimed to assess how many previous admissions should be considered when constructing the HFRS and the influence of frailty risk on long length of stay, in-hospital mortality, and 30-day readmission. METHODS: This is a retrospective observational cohort study of patients aged 75 years or older who had at least one emergency admission to any of 49 hospital sites in the Yorkshire and Humber region of England, UK. We constructed multiple versions of the HFRS for each patient, each form incorporating diagnostic data from progressively more previous admissions in its construction within a 1-year or 2-year window. We assessed the ability of each form of the HFRS to predict long length of stay (>10 days), in-hospital death, and 30-day readmission. FINDINGS: Between April 1, 2013, and March 31, 2017, 282 091 patients had 675 155 hospital admissions. Regression analyses assessing the different constructions of HFRS showed that the form constructed with diagnostic information recorded in the current and previous two admissions within the preceding 2 years performed best for predicting all three outcomes. Under this construction, 263 432 (39·0%) of 674 615 patient admissions were classified as having low frailty risk, for whom 33 333 (12·7%) had a long length of stay, 10 145 (3·9%) died in hospital, and 45 226 (17·2%) were readmitted within 30 days. By contrast with those patients with low frailty risk, for those with intermediate frailty risk, the probability was 2·5-times higher (95% CI 2·4 to 2·6) for long length of stay, 2·17-times higher (2·1 to 2·2) for in-hospital death, and 0·7% higher (0·5 to 1) for readmission. For patients with high frailty risk, the probability was 4·3-times higher (4·2 to 4·5) for long length of stay, 2·48-times higher (2·4 to 2·6) for in-hospital death, and -1% (-1·2 to -0·5) lower for readmission than those with low frailty risk. The intermediate and high frailty risk categories were more important predictors of long length of stay than any of the other rich set of control variables included in our analysis. These categories also proved to be important predictors of in-hospital mortality, with only the Charlson Comorbidity Index offering greater predictive power. INTERPRETATION: We recommend constructing the HFRS with diagnostic information from the current admission and from the previous two admissions in the preceding 2 years. This HFRS form was a powerful predictor of long length of stay and in-hospital mortality, but less so of emergency readmissions. FUNDING: National Institute of Health Research.