Trends In Emergency Admissions Research Articles

P302 Trends in hospital admissions in patients with ANCA-associated vasculitis before and during the COVID-19 pandemic

Abstract Background/Aims People with ANCA-associated vasculitis (AAV) have high rates of hospital admissions. They may have emergency admissions at the time of diagnosis, or day case admissions to receive immunosuppressive treatment. We describe the trends in emergency and day case admissions over the past 9 years, and the effect of the COVID-19 pandemic. Methods We extracted hospital episode statistics available publicly from NHS Digital for 2012/13 to 2019/20 and added provisional data from the National Congenital Anomaly and Rare Disease Registration Service for 2020/21 under their legal permissions (CAG 10-02(d)/2015) because the publicly available data had not yet been released. We extracted all emergency and day-case admission rates with ICD codes for each AAV subtype (M301, M313 and M317, in the primary position denoting main admission diagnosis). We used England population estimates from the Office for National Statistics as the denominator for rates. We calculated Poisson confidence intervals to quantify the difference in rates between 2019/20 and 2020/21 financial years. Results Rates of day case admissions per 1,000,000 for AAV increased from 49.1 (47.2 - 50.9) in 2012/13 to 63.3 (61.2 - 65.4) in 2019/20, then decreased by 26.4% to 48.6 (46.7 - 50.4) in 2020/21 (Table). The trends in emergency admissions were relatively unchanged between 2012/13 and 2019/20 (mean 6.7 per 1,000,000), and there was no significant decrease in emergency admissions during the COVID-19 pandemic. Conclusion Day case admission rates increased between 2012/13 and 2019/20 but decreased during the COVID-19 pandemic. Emergency admission rates for patients with AAV remained relatively unchanged, despite the context of the significant disruption and reconfiguration of healthcare services. Further work on patient-level data is needed to establish whether the day case reduction is due to fewer new patients or relapsing patients being diagnosed (and therefore fewer remission induction infusions) during this period or altered clinical practice leading to postponement of planned remission maintenance treatment that would have usually been given. Alternatively, this change may reflect a change in clinical practice to preferentially use oral rather than IV agents. All of this may have future consequences both for clinical practice and individual patient care and outcomes post-pandemic. Disclosure M. Odingo: None. M. Rutter: None. P. Lanyon: Grants/research support; Grants/research support; PCL has received funding for research from Vifor Pharma. M. Grainge: None. D. Groves: None. M. Bythell: None. J. Aston: None. S. Stevens: None. F. Pearce: Grants/research support; Grants/research support; FAP has received funding for research from Vifor Pharma.

Temporal trends in emergency admissions for diabetic ketoacidosis in people with diabetes in England before and during the COVID-19 pandemic: a population-based study

Diabetic ketoacidosis (DKA) has been reported to be increasing in frequency during the COVID-19 pandemic. We aimed to examine the rates of DKA hospital admissions and the patient demographics associated with DKA during the pandemic compared with in prepandemic years. Using a comprehensive, multiethnic, national dataset, the Secondary Uses Service repository, we extracted all emergency hospital admissions in England coded with DKA from March 1 to June 30, 2020 (first wave of the pandemic), July 1 to Oct 31, 2020 (post-first wave), and Nov 1, 2020, to Feb 28, 2021 (second wave), and compared these with DKA admissions in the equivalent periods in 2017-20. We also examined baseline characteristics, mortality, and trends in patients who were admitted with DKA. There were 8553 admissions coded with DKA during the first wave, 8729 during the post-first wave, and 10 235 during the second wave. Compared with preceding years, DKA admissions were 6% (95% CI 4-9; p<0·0001) higher in the first wave of the pandemic (from n=8048), 6% (3-8; p<0·0001) higher in the post-first wave (from n=8260), and 7% (4-9; p<0·0001) higher in the second wave (from n=9610). In the first wave, DKA admissions reduced by 19% (95% CI 16-21) in those with pre-existing type 1 diabetes (from n=4965 to n=4041), increased by 41% (35-47) in those with pre-existing type 2 diabetes (from n=2010 to n=2831), and increased by 57% (48-66) in those with newly diagnosed diabetes (from n=1072 to n=1681). Compared with prepandemic, type 2 diabetes DKA admissions were similarly common in older individuals and men but were higher in those of non-White ethnicities during the first wave. The increase in newly diagnosed DKA admissions occurred across all age groups and these were significantly increased in men and people of non-White ethnicities. In the post-first wave, DKA admissions did not return to the baseline level of previous years; DKA admissions were 14% (11-17) lower in patients with type 1 diabetes (from n=5208 prepandemic to n=4491), 30% (24-36) higher in patients with type 2 diabetes (from n=2011 to n=2613), and 56% (47-66) higher in patients with newly diagnosed diabetes (from n=1041 to n=1625). During the second wave, DKA admissions were 25% (22-27) lower in patients with type 1 diabetes (from n=5769 prepandemic to n=4337), 50% (44-56) higher in patients with type 2 diabetes (from n=2608 to n=3912), and 61% (52-70) higher in patients with newly diagnosed diabetes (from n=1234 to n=1986). Our results provide evidence for differences in the numbers and characteristics of people presenting with DKA during the COVID-19 pandemic compared with in the preceding 3 years. Greater awareness of risk factors for DKA in type 2 diabetes and vigilance for newly diagnosed diabetes presenting with DKA during the COVID-19 pandemic might help mitigate the increased impact of DKA. None.

Reshaping Care for Older People: Trends in emergency admissions to hospital during a period of simultaneous interventions in Glasgow City, April 2011–March 2015

This study describes trends in emergency admissions (EAs) in Glasgow City during a period when interventions were designed and implemented, aimed at shifting the balance from institutional to community-based care. Standardised monthly rates of EAs between April 2011 and March 2015 were calculated, for residents of Glasgow City aged 65 years and over. Multilevel zero-inflated Negative Binomial models for EAs nested by datazone were created, adjusting for sex, 5-year age group, area-level deprivation (SIMD quintile), season, month and month squared. Models were also run for EAs by cause, for three causes: chronic obstructive pulmonary disease (COPD), falls and dementia. The rate of EAs first rose then fell during the study period. When modelled, RRs for month (RR for month 12 relative to month 1 and 95% CI=1.02 (0.99, 1.06)) and month squared (RR=0.999 (0.998, 0.999)) indicated a rise in admissions until February 2012, followed by a fall. Risk of admission was greater for males and increased with increasing age group. The risk of going into hospital for those from SIMD 5 (most affluent) was 0.58 (0.56, 0.59) relative to those from SIMD 1 (most deprived). Socioeconomic inequalities were particularly great for COPD-related admissions, where RR for SIMD 5 was 0.25 (0.23, 0.28) times that of SIMD 1. An interaction term between month and SIMD was not significant for any outcome. For dementia-related EAs there was a suggestion that inequalities may be reducing over time. EAs for those aged 65 years and more reduced during the Change Fund period, with similar relative reductions observed across all deprivation quintiles.

Emergency admissions across the transition from paediatric to adult care: cross-sectional analysis of English hospital data

BackgroundTransition from paediatric to adult health services is often sub-optimally achieved for children with long-term conditions. We investigated trends in emergency admissions across the transition from paediatric to adult care. MethodsUsing Hospital Episodes Statistics data, we analysed 1 186 392 emergency admissions between April 1, 2009, and March 31, 2012, in children and young people aged 10–24 years. We calculated emergency admission rates for this cohort before (10–15 years), during (16–18), and after transition (19–24) using mid-year population estimates as denominators. We stratified analyses by underlying long-term conditions, which we defined by validated International Classification of Diseases 10th revision codes. We excluded injury-related and maternity-related admissions. We used negative binomial regression to determine incidence rate ratios (IRRs). FindingsPrevalence rates for emergency admissions increased 64% for girls (29/1000 before transition to 48/1000 after transition) and 17% for boys (26/1000 to 31/1000). This increase overwhelmingly occurred during transition (16–18 years), when rates increased 4·0/1000 per year for girls and 2·3/1000 for boys. At the same time, average length of hospital stay increased from 2·1 to 2·9 days for girls, and 1·8 to 5·0 days for boys (increases of 38% and 186% for girls and boys, respectively). Disparities in admission rates increased during transition, with children and young people from the most deprived quintile more likely than those from the least deprived quintile to have an emergency admission (IRR 1·63, 95% CI 1·60–1·66), and more so than before transition (1·51, 1·45–1·56). The increase in admission rates was driven by underlying long-term conditions: overall, rates increased 14% (IRR 1·14, 95% CI 1·13–1·14), but for children and young people with long-term conditions rates increased 46% (1·46, 1·46–1·47). Rates increased most rapidly for mental health problems, metabolic and endocrine disorders, multiple long-term conditions (both sexes), and respiratory disorders (girls only). InterpretationOur results show that emergency admission rates, duration, and inequalities increase across transition, especially in children and young people with underlying long-term conditions. The extent to which this increase is due to transition within the health service, rather than other developments, requires further research. Our results are in keeping with the widely recognised difficulties that young people face when they transition to adult health services. FundingLPMMW and JW were supported by funding from the Department of Health Policy Research Programme through funding to the Policy Research Unit in the Health of Children, Young People and Families (grant reference 109/0001). RG is supported by awards establishing the Farr Institute of Health Informatics Research at University College London Partners from the Medical Research Council and a consortium of funders (MR/K006584/1).

PP15 Reshaping care for older people: trends in emergency admissions to hospital during a period of simultaneous interventions in glasgow city

Background Emergency admissions to hospital have been increasing for several decades in Glasgow, and across Scotland as a whole. The Reshaping Care for Older People Programme is a national programme aimed at enabling older people to stay independent and well at home without the need for care and support. The Change Fund was set up to stimulate a shift from institutional care to home and community based care via a programme of interventions across Scotland. This study aimed to describe the change in emergency admissions to hospital and inequalities in emergency admissions to hospital during the Change Fund period in Scotland. Methods Monthly crude and standardised rates of emergency admission between April 2011 and August 2014 were calculated, for residents of Glasgow City aged 65 years+, using annual population and corresponding monthly estimates. Multilevel Poisson models for emergency admissions nested by datazone were created, adjusting for sex, 5-year agegroup, area-level deprivation (SIMD quintile), season, month and month squared. Results Emergency admissions first rose then fell between Apr 2011 and Aug 2014. Similar trends were also observed in crude and standardised rates during this period. When modelled, both month (RR and 95% CI = 1.03 (1.02, 1.03)) and month squared (RR = 0.997 (0.997, 0.997)) were significant, indicating a rise in admissions followed by a fall. Males were more likely to be admitted to hospital than females, and risk increased with increasing agegroup. A seasonal effect was also measured with a greater risk of admission in winter (RR = 1.22 (1.19, 1.24)) when compared with spring, and a lower risk in summer (RR = 0.81 (0.79, 0.82)). SIMD1 (most deprived) residents accounted for 10 times as many emergency admissions as SIMD5 (most affluent). After adjustment for age and sex, risk of going into hospital for those from SIMD5 was 0.37 (0.35, 0.39) relative to those from SIMD1. An interaction term between month and SIMD quintile suggested significantly greater reductions in admissions among those living in SIMD1. When modelled separately, risk of admission increased over time for those living in SIMD5 (RR = 1.02 (1.01, 1.02 that of previous month)), while for those living in SIMD1 both month (RR = 1.08 (1.08, 1.09)), and month squared (RR = 0.997 (0.997, 0.997)) were significant, describing an increase, followed by a reduction from around July 2012 onwards. Conclusion Overall, emergency admissions have reduced during the Change Fund period. Additionally, socioeconomic inequalities in emergency admissions among those aged 65 years+ reduced over time.

Trends in emergency admissions per death

446 British Journal of Healthcare Management 2014 Vol 20 No 9 © 2 01 4 M A H ea lth ca re L td death may be a useful way of gauging the number of admissions per person over a lifetime, i.e. at any point in time emergency admissions are occurring at all points of the population’s life-cycle. In this respect, Figure 1 gives the monthly number of emergency admissions per death (both in and out of hospital) from February 2009 to February 2014. A seasonal profile is evident and this is shown in Figure 2. Deaths generally peak in January/ February; as do emergency admissions. However, deaths peak more strongly than emergency admissions and this leads to the summer peak in the ratio of emergency admissions per death. Since many emergency admissions are not directly linked to end of life, we can use this ratio as a rough snapshot of the average emergency admissions per person per lifetime. This assumption holds roughly true when births and deaths are matched. There were 1.43 births per death in England in 2013, so any ratio will be biased toward childhood emergency admissions. So how do we explain the very high figure of 11.5 (annual average) per death? First, we adjust for the current ratio of 1.43 births per death which brings the figure of 11.5 down to somewhere around 8 per death. Table 1 provides further useful insight. Admission to speciality accident and emergency (A&E) are mainly assessment unit admissions, and prior to 2002/03 was fairly constant at 2.2% of total emergency admissions. The A&E four-hour target changed all that, and by 2009/10, this had risen to 12.3% of emergency admissions. Rod Jones Trends in emergency admissions per death

Trends in emergency admission for fractured neck of femur

In order to monitor and improve the quality of health care and to protect patients, we need good reliable evidence of what is actually happening on the wards and elsewhere in practice. Policy needs to be based on actualities, as far as we can ascertain them. The more detailed the evidence we collect about the quality of health care, the better. This will allow for a much more informed and accurate information baseline on which to ground policies and practice and, ultimately, to protect patients. The QualityWatch Focus on hip fracture report (Smith et al, 2013) fits well into this profile. It is a valuable report examining trends in emergency admissions for fractured neck of femur from 2001 to 2011.

Trends in unscheduled care

British Journal of Healthcare ManagementVol. 19, No. 6 Money MattersTrends in unscheduled careRod JonesRod JonesSearch for more papers by this authorRod JonesPublished Online:27 Sep 2013https://doi.org/10.12968/bjhc.2013.19.6.301AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References Appleby J (2013) Are accident and emergency attendances increasing? Available at: www.kingsfund.org.uk/blog/2013/04/are-accident-and-emergency-attendances-increasing (accessed 29 May 2013) Google ScholarBughio F, Elliott D, Goodrum F (2013) An endothelial cell-specific requirement for the UL133-UL138 locus of human cytomegalovirus for efficient virus maturation. J Virology 87 (6): 3062–75 Crossref, Google ScholarGandhoke I, Hussain A, Pash S et al. (2012) Glycoprotein B genotyping in congenital/perinatal cytomegalovirus infection in symptomatic infants. Indian Pediatrics S097475591200352 (Epub ahead of print) Google ScholarGkrania-Klotsas E, Langenberg C, Sharp S, et al. (2012) Seropositivity and higher IgG antibody levels against Cytomegalovirus are associated with mortality in the population based EPIC-Norfolk cohort. Clinical Infectious Diseases 206 (12): 1897–1903 Google ScholarJones R (2009a) Trends in emergency admissions. BJHCM 15 (4): 188–96 Google ScholarJones R (2009b) Cycles in emergency admissions. BJHCM 15 (5): 239–46 Google ScholarJones R (2009c) Emergency admissions and hospital beds. BJHCM 15 (6): 289–96 Google ScholarJones R (2009d) Emergency admissions and financial risk. BJHCM 15 (7): 344–50 Google ScholarJones R (2011a) Hospital bed occupancy demystified and why hospitals of different size and complexity must operate at different average occupancy. BJHCM 17 (6): 242–8 Google ScholarJones R (2011b) A&E performance and inpatient bed occupancy. BJHCM 17 (6): 256–7 Google ScholarJones R (2011c) Bed occupancy – the impact on hospital planning. BJHCM 17 (7): 307–13 Google ScholarJones R (2012) Diagnoses, deaths and infectious outbreaks. BJHCM 18 (10): 539–48 Google ScholarJones R (2013a) An unexplained increase in deaths in England & Wales during 2012. BJHCM 19 (5): 248–53 Google ScholarJones R (2013b) Could cytomegalovirus be causing widespread outbreaks of chronic poor health. In: Shoja M, Agutter PS, Tubbs RS et al., eds. Hypotheses in Clinical Medicine: Nova Science Publishers. New York, NY: 37–79 Google ScholarKaffash J (2013) GPs not to blame for pressure on A&E, says NHS England adviser. www.pulsetoday.co.uk/commissioning/commissioning-topics/emergency-admissions/gps-not-to-blame-for-pressure-on-ae-says-nhs-england-adviser/20002989.article#.UZojIIY1P-8 (accessed 29 May 2013) Google ScholarKyoto V, Vuorinen T, Saukko P et al. (2005) Cytomegalovirus infection of the heart is common in patients with fatal myocarditis. Clin Infect Dis 40 (5): 683–8 Crossref, Google ScholarMcWhorter A, Smith L, Masters L et al. (2013) Natural killer cell dependent within-host competition arises during multiple MCMV infection: consequences for viral transmission and evolution. PLoS Pathog 9 (1): e1003111 Crossref, Google ScholarOliver D (2013) Closing acute hospital beds for older people—the way to save our services? Available at: http://britishgeriatricssociety.wordpress.com/2013/05/20/closing-acute-hospital-beds-for-older-people-the-way-to-save-our-services/ (accessed 29 May 2013) Google Scholar FiguresReferencesRelatedDetailsCited byImmunosenenescence: Role of cytomegalovirusExperimental Gerontology, Vol. 54What is happening in urgent care?5 March 2014 | Journal of Paramedic Practice, Vol. 6, No. 2 1 June 2013Volume 19Issue 6ISSN (print): 1358-0574ISSN (online): 1759-7382 Metrics History Published online 27 September 2013 Published in print 1 June 2013 Information© MA Healthcare LimitedPDF download

Is secondary preventive care improving? Observational study of 10-year trends in emergency admissions for conditions amenable to ambulatory care

ObjectiveTo identify trends in emergency admissions for patients with clinical conditions classed as ‘ambulatory care sensitive’ (ACS) and assess if reductions might be due to improvements in preventive care.DesignObservational study...

Is the increase in emergency short‐stay admissions sustainable? Trends across Melbourne, 2000 to 2009

To describe the trends in emergency admissions over 10 years in terms of volume, age-specific rates, hospital length of stay (LOS) and clinical reasons. A retrospective analysis of population-based linked Department of Health ED and hospital admission data for metropolitan Melbourne 1999/2000 to 2008/2009 was conducted. Outcome measures included: hospital admission numbers (total, single day/overnight, ≥2 days LOS); admission rates per 1000 person-years (total, single day/overnight, ≥2 days LOS); hospital LOS. The volume of patients admitted to hospital through EDs rose by 56% over the 10 years to June 2009. The number of same day/overnight admissions rose by 60%, equating to a 6.1% average annual increase beyond that accounted for by demographic change (95% CI 5.7-6.5%). The volume of patients admitted for ≥2 days also increased; however, the admission rate per 1000 persons for these longer-stay patients declined over the decade by 9% (95% CI 5-12%). The most frequent discharge diagnoses were injury or poisoning, and disorders of the circulatory, respiratory or digestive systems. The numbers and mortality rate for ED admissions declined over the decade. Emergency hospital admissions have risen over the last decade even after adjustment for population changes. There was a disproportionate rise in same day/overnight admissions, with overrepresentation of the elderly. This is possibly related to changes in ED models of care, including introduction of short-stay units, improved diagnostic and therapeutic capability, and risk-averse management to optimise safe discharge, within the context of time-based performance targets.

Principles of safe and timely hospital discharge

British Journal of Hospital MedicineVol. 72, No. Sup8 Clinical PracticePrinciples of safe and timely hospital dischargeRobin H Johns, Ananna Rahman, Sarah Sharp, Carol Back, Ahmed Ishaque, Huw S JenkinsRobin H JohnsSearch for more papers by this author, Ananna RahmanSearch for more papers by this author, Sarah SharpSearch for more papers by this author, Carol BackSearch for more papers by this author, Ahmed IshaqueSearch for more papers by this author, Huw S JenkinsSearch for more papers by this authorRobin H Johns; Ananna Rahman; Sarah Sharp; Carol Back; Ahmed Ishaque; Huw S JenkinsPublished Online:16 Aug 2013https://doi.org/10.12968/hmed.2011.72.Sup8.M120AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References Agterof MJ, Schutgens RE, Snijder RJ et al. (2010) Out of hospital treatment of acute pulmonary embolism in patients with a low NT-proBNP level. J Thromb Haemost 8(6): 1235–41 Crossref, Medline, Google ScholarBlunt I, Bardsley M, Dixon J (2010) Trends in Emergency Admissions in England 2004-2009. The Nuffield Trust, London Google ScholarCare Quality Commission (2010) The state of healthcare and adult social care in England. Key themes and quality of services in 2009. Her Majesty's Stationery Office, London Google ScholarCotton MM, Bucknall CE, Dagg KD, Johnson MK, MacGregor G, Stewart C, Stevenson RD (2000) Early discharge for patients with exacerbations of chronic obstructive pulmonary disease: a randomized controlled trial. Thorax 55(11): 902–6 Crossref, Medline, Google ScholarDarzi A (2007) A Framework For Action. Healthcare for London, London Google ScholarDepartment of Health (2003) Discharge from hospital: pathway, process and practice. Department of Health, London Google ScholarDepartment of Health (2009a) Decision Support Tool for NHS Continuing Healthcare. Department of Health, London Google ScholarDepartment of Health (2009b) Fast Track Pathway Tool for NHS Continuing Healthcare. Department of Health, London Google ScholarDepartment of Health (2009c) NHS Continuing Care Checklist. Department of Health, London Google ScholarDepartment of Health (2009d) The National Framework for NHS Continuing Healthcare and NHS-funded Nursing Care. Department of Health, London Google ScholarDepartment of Health (2010a) Care Services Efficiency Delivery Homecare Re-ablement Toolkit. Intermediate Care and Homecare Re-ablement: What's in a Name? Department of Health, London Google ScholarDepartment of Health (2010b) Equity and excellence: Liberating the NHS. Department of Health, London Google ScholarDepartment of Health (2010c) Prioritising need in the context of Putting People First: A whole system approach to eligibility for social care. Guidance on Eligibility Criteria for Adult Social Care, England 2010. Department of Health, London Google ScholarHarker R (2009) NHS bed availability in England, House of Commons Library, London Google ScholarLeff B, Burton L, Mader S et al. (2006) Satisfaction with hospital at home care. J Am Geriatr Soc 54(9): 1355–63 Crossref, Medline, Google ScholarLim WS, Baudouin SV, George RC et al. (2009) BTS guidelines for the management of community acquired pneumonia in adults: update 2009. Thorax 64(Suppl 3): iii1–55 Crossref, Medline, Google ScholarRoyal College of Nursing (2004) Needs Assessment and Older People. A Royal College of Nursing Toolkit. Royal College of Nursing, London Google Scholar FiguresReferencesRelatedDetailsCited ByInterventions to improve the continuity of medication management upon discharge of patients from hospital to residential aged care facilities16 April 2019 | Journal of Pharmacy Practice and Research, Vol. 49, No. 2 1 August 2011Volume 72Issue Sup8ISSN (print): 1750-8460ISSN (online): 1759-7390 Metrics History Published online 16 August 2013 Published in print 1 August 2011 Information© MA Healthcare LimitedPDF download

Cycles in inpatient waiting time

British Journal of Healthcare ManagementVol. 17, No. 2 Money MattersCycles in inpatient waiting timeRod JonesRod JonesSearch for more papers by this authorRod JonesPublished Online:16 Aug 2013https://doi.org/10.12968/bjhc.2011.17.2.80AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References Jones R (1996) How many patients next year? Healthcare Analysis & Forecasting, Camberley, UK Google ScholarJones R (2009a) Trends in emergency admissions. Br J Healthcare Manag 15(4): 188-96 Link, Google ScholarJones R (2009b) Cycles in emergency admissions. Br J Healthcare Manag 15(5): 239-46 Link, Google ScholarJones R (2009c) Emergency admissions and hospital beds. Br J Healthcare Manag 15(6): 289-96 Link, Google ScholarJones R (2009d) Emergency admissions and financial risk. Br J Healthcare Manag 15(7): 344-50 Link, Google ScholarJones R (2009e) Crafting efficient bed pools. Br J Healthcare Manag 15(12): 614-6 Link, Google ScholarJones R (2010a) Cyclic factors behind NHS deficits and surpluses. Br J Healthcare Manag 16(1): 48-50 Link, Google ScholarJones R (2010b) Emergency preparedness. Br J Healthcare Manag 16 (2): 94-95 Link, Google ScholarJones R (2010c) Do NHS cost pressures follow long-term patterns? Br J Healthcare Manag 16(4): 192-4 Link, Google ScholarJones R (2010d) Benchmarking length of stay. Br J Healthcare Manag 16(5): 248-50 Link, Google ScholarJones R (2010e) Forecasting demand. Br J Healthcare Manag 16(8): 392-93 Link, Google ScholarJones R (2010f) Nature of health care costs and financial risk in commissioning. Br J Healthcare Manag 16(9): 424-30 Link, Google ScholarJones R (2010g) Nature of health care costs and the HRG tariff. Br J Healthcare Manag 16(9): 451-2 Link, Google ScholarJones R (2010h) Forecasting emergency department attendances. Br J Healthcare Manag 16(10): 495-6 Link, Google ScholarJones R (2010i) Trends in Programme Budget expenditure. Br J Healthcare Manag 16(11): 518-26 Link, Google ScholarJones R (2010J) Gender ratio and hospital admissions. Br J Healthcare Manag 16(11):541 Link, Google ScholarJones R (2011) Infectious outbreaks and the NHS Capitation formula. Br J Healthcare Manag 17(2): in press Google Scholar FiguresReferencesRelatedDetailsCited byRoles for Cytomegalovirus in Infection, Inflammation, and AutoimmunityCMV and health care costs16 August 2013 | British Journal of Healthcare Management, Vol. 17, No. 4Cycles in gender-related costs for long-term conditions16 August 2013 | British Journal of Healthcare Management, Vol. 17, No. 3 1 February 2011Volume 17Issue 2ISSN (print): 1358-0574ISSN (online): 1759-7382 Metrics History Published online 16 August 2013 Published in print 1 February 2011 Information© MA Healthcare LimitedPDF download

Trends in emergency admissions

Part one of this series discusses how the more widely recognised factors, such as an ageing population, re-admissions and increasing expectations of medicine, only contribute to a baseline increase in emergency admissions. Seasonal variation is discussed in the context of the predictability, or otherwise of emergency admissions, in response to changes in the weather and the wider environment. However, these are unable to explain the observed cyclical events occurring in medicine every 4-6 years, and even longer cycles in surgical and trauma admissions. These cycles are discussed in part two, while part three investigates the implications on bed planning. The current methods for estimating the size of hospitals and bed pools within hospitals are shown to be inappropriate to the real needs of emergency care.

Trends in serious head injuries among cyclists in England: analysis of routinely collected data

As the health and environmental benefits of cycling have become better appreciated, successive governments in the United Kingdom have encouraged cycle use. Cyclists, however, face considerable risk of injury, of...