People’s experiences of hospital care on the weekend: secondary analysis of data from two national patient surveys

2017 ◽  
Vol 27 (6) ◽  
pp. 455-463 ◽  
Author(s):  
Chris Graham
Keyword(s):  
Emergency Departments ◽  
Waiting Times ◽  
Secondary Analysis ◽  
Patient Characteristics ◽  
Two Dimensions ◽  
Inpatient Episode ◽  
National Patient ◽  
Care And Treatment ◽  
Group Sex ◽  
Public Holidays

ObjectiveTo determine whether patients treated in hospital on the weekend report different experiences of care compared with those treated on weekdays.DesignThis is a secondary analysis of the 2014 National Health Service (NHS) adult inpatient survey and accident and emergency (A&E) department surveys. Differences were tested using independent samples t-tests and multiple regression, adjusting for patient age group, sex, ethnicity, proxy response, NHS trust, route of admission (for the inpatient survey) and destination on discharge (for the A&E survey).SettingThe inpatient survey included 154 NHS hospital trusts providing overnight care; the A&E survey 142 trusts with major emergency departments.ParticipantsThree cohorts were analysed: patients attending A&E, admitted to hospital and discharged from hospital. From the inpatient survey’s 59 083 responses, 10 382 were admitted and 11 542 discharged on weekends or public holidays. The A&E survey received 39 320 responses, including 11 542 (29.4%) who attended on the weekend or on public holidays. Weekday and weekend attendees’ response rates were similar once demographic characteristics were accounted for.Main outcome measuresFor the A&E survey, six composite dimensions covered waiting times, doctors and nurse, care and treatment, cleanliness, information on discharge, and overall experiences. For the inpatient survey, three questions covered admissions and two dimensions covered information about discharge and about medicines.ResultsPeople attending A&E on weekends were significantly more favourable about ‘doctors and nurses’ and ‘care and treatment’. Inpatients admitted via A&E on a weekend were more positive about the information given to them in A&E than others. Other dimensions showed no differences between people treated on weekdays or on weekends.ConclusionsPatients attending emergency departments or admitted to or discharged from an inpatient episode on weekends and public holidays report similar or more positive experiences of care to other patients after adjusting for patient characteristics.

Announcing Waiting Time in Emergency Departments

2019 ◽  
pp. 1-6
Author(s):  
Martin Lariviere ◽  
Sarang Deo
Keyword(s):  
Waiting Time ◽  
Emergency Departments ◽  
Waiting Times ◽  
Large Network ◽  
Regional Networks ◽  
Marketing Campaign ◽  
National Healthcare ◽  
Time Estimates ◽  
Patient Waiting Time ◽  
Patient Waiting

First National Healthcare (FNH) runs a large network of hospitals and has worked to systematically reduce waiting times in its emergency departments. One of FNH's regional networks has run a successful marketing campaign promoting its low ED waiting times that other regions want to emulate. The corporate quality manager must now determine whether to allow these campaigns to be rolled out and, if so, which waiting time estimates to use. Are the numbers currently being reported accurate? Is there a more accurate way of estimating patient waiting time that can be easily understood by consumers?

Waiting times in English emergency departments reach eight year high

BMJ ◽  
2012 ◽  
Vol 344 (may30 1) ◽  
pp. e3766-e3766
Author(s):  
A. O'Dowd
Keyword(s):  
Emergency Departments ◽  
Waiting Times

scholarly journals Using linked English cancer registration data to assess variation in diagnostic pathway length

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Jess Fraser ◽  
Clare Pearson ◽  
Jon Shelton ◽  
Jodie Moffat
Keyword(s):  
Secondary Care ◽  
Waiting Times ◽  
Patient Characteristics ◽  
Cancer Site ◽  
Diagnostic Process ◽  
Cancer Registration ◽  
Diagnostic Pathway ◽  
Registration Data ◽  
Emergency Presentation ◽  
Pathway Length

BackgroundFor the majority of cancer patients, the length of the diagnostic pathway is unknown. Only those on a specific pathway are monitored. Quantifying pathway length is important in understating which patients may benefit most from an expedited pathway. AimThis study aimed to develop a novel methodology using linked cancer registration data to calculate the Secondary Care Diagnostic Interval (SDCI): the period from first interaction with secondary care to receiving a cancer diagnosis. Subsequently variation in SCDIs across twenty-five cancer sites were analysed. MethodsEnglish cancer registrations (2014-15) from Public Health England’s National Cancer Registration and Analysis Service were linked to three routine health datasets: Hospital Episode Statistics, Diagnostic Imaging Dataset and Cancer Waiting Times. The SCDI was calculated as the difference between the earliest event relating to the secondary care diagnostic process (comprised of referral into/secondary care appointment or diagnostic procedure in the 6 months before diagnosis) and the diagnosis date. SCDI length was stratified by stage at diagnosis, route to diagnosis (e.g. emergency presentation, GP referral) and patient characteristics. ResultsThe median SCDI (days) was shortest for acute lymphoblastic leukaemia (ALL) (2) and longest for kidney (45). In general, SCDIs decreased with later stage (for example stage 1-4 colorectal: 35 to 20, lung: 75 to 25). Patients diagnosed after routine GP referrals had longest SCDIs compared to urgent referrals, for all sites except ALL. Geographical variation in SCDIs exists by Cancer Alliance, with the greatest differences compared to the England average observed for prostate cancer (median national SCDI: 28, Cancer Alliance range: 21 - 42). ConclusionSubstantial variation exists in SCDIs by cancer site, stage and presentation route. Many patients are experiencing SCDIs over 28 days, even those diagnosed via urgent GP referrals. Understanding variation can support creation of targeted initiatives to expedite diagnostic pathways where appropriate.

Waiting times in California's emergency departments

2003 ◽  
Vol 41 (1) ◽  
pp. 35-44 ◽  
Author(s):  
Susan Lambe ◽  
Donna L. Washington ◽  
Arlene Fink ◽  
Marianne Laouri ◽  
Honghu Liu ◽  
...  
Keyword(s):  
Emergency Departments ◽  
Waiting Times

scholarly journals The national incidence of PML in Sweden, 1988–2013

Neurology ◽  
2018 ◽  
Vol 90 (6) ◽  
pp. e498-e506 ◽  
Author(s):  
Ellen Iacobaeus ◽  
Sarah Burkill ◽  
Shahram Bahmanyar ◽  
Ramil Hakim ◽  
Camilla Byström ◽  
...  
Keyword(s):  
Monoclonal Antibody ◽  
Patient Characteristics ◽  
Hematologic Malignancies ◽  
Antibody Treatment ◽  
Monoclonal Antibody Treatment ◽  
National Patient ◽  
Notable Increase ◽  
High Level ◽  
Underlying Diseases ◽  
Record Review

ObjectiveTo investigate the incidence of progressive multifocal leukoencephalopathy (PML) and patient characteristics in Sweden between 1988 and 2013.MethodsAll PML diagnoses in Sweden between 1988 and 2013 were identified in the National Patient Register. Information to validate the diagnosis and patient characteristics was obtained from medical records.ResultsMedical record review classified 108 out of 250 patients (43%) as definite (n = 84), probable (n = 4), or possible (n = 20) PML according to diagnostic criteria. Accurate diagnoses were more common in records obtained from neurology departments (82% of patients seen in neurology departments) compared with other departments (31%) (p < 0.001). The incidence of PML increased from a largely stable level at 0.026 (95% confidence interval [CI] 0.021–0.031) per 100,000 individuals per year during 1988–2010 to 0.11 (95% CI 083–0.137) during 2011–2013, during which time there was a notable increase (p < 0.001). Hematologic malignancies (n = 34), HIV/AIDS (n = 33), and autoimmune disease (n = 23) were the most common underlying diseases. Treatment with a monoclonal antibody prior to PML diagnosis was identified in 26 patients.ConclusionAn increased incidence of PML in Sweden was observed and coincided with the prior use of monoclonal antibody treatment. The high level of misdiagnosis emphasizes the importance of immediate contact with a neurology center upon suspicion of PML.

scholarly journals Invasive Coronary Angiography after Chest Pain Presentations to Emergency Departments

2020 ◽  
Vol 17 (24) ◽  
pp. 9502
Author(s):  
Frank M. Sanfilippo ◽  
Graham S. Hillis ◽  
Jamie M. Rankin ◽  
Donald Latchem ◽  
Carl J. Schultz ◽  
...  
Keyword(s):  
Chest Pain ◽  
Coronary Angiography ◽  
Emergency Departments ◽  
Invasive Coronary Angiography ◽  
Patient Characteristics ◽  
Tertiary Hospital ◽  
Discharge Diagnosis ◽  
Coronary Syndrome ◽  
Interhospital Transfer ◽  
And Gender

We investigated patients presenting to emergency departments (EDs) with chest pain to identify factors that influence the use of invasive coronary angiography (ICA). Using linked ED, hospitalisations, death and cardiac biomarker data, we identified people aged 20 years and over who presented with chest pain to tertiary public hospital EDs in Western Australia from 1 January 2016 to 31 March 2017 (ED chest pain cohort). We report patient characteristics, ED discharge diagnosis, pathways to ICA, ICA within 90 days, troponin test results, and gender differences. Associations were examined with the Pearson Chi-squared test and multivariate logistic regression. There were 16,974 people in the ED chest pain cohort, with a mean age of 55.6 years and 50.7% males, accounting for 20,131 ED presentations. Acute coronary syndrome was the ED discharge diagnosis in 10.4% of presentations. ED pathways were: discharged home (57.5%); hospitalisation (41.7%); interhospital transfer (0.4%); and died in ED (0.03%)/inpatients (0.3%). There were 1546 (9.1%) ICAs performed within 90 days of the first ED chest pain visit, of which 59 visits (3.8%) had no troponin tests and 565 visits (36.6%) had normal troponin. ICAs were performed in more men than women (12.3% vs. 6.1%, p < 0.0001; adjusted OR 1.89, 95% CI 1.65, 2.18), and mostly within 7 days. Equal numbers of males and females present with chest pain to tertiary hospital EDs, but men are twice as likely to get ICA. Over one-third of ICAs occur in those with normal troponin levels, indicating that further investigation is required to determine risk profile, outcomes and cost effectiveness.

scholarly journals Why are there long waits at English emergency departments?

2019 ◽  
Vol 21 (2) ◽  
pp. 209-218 ◽  
Author(s):  
James Gaughan ◽  
Panagiotis Kasteridis ◽  
Anne Mason ◽  
Andrew Street
Keyword(s):  
Emergency Departments ◽  
Fixed Effects ◽  
Waiting Times ◽  
Poisson Model ◽  
Bed Occupancy ◽  
Term Care ◽  
Delayed Discharges ◽  
A Minor ◽  
The Impact

Abstract A core performance target for the English National Health Service (NHS) concerns waiting times at Emergency Departments (EDs), with the aim of minimising long waits. We investigate the drivers of long waits. We analyse weekly data for all major EDs in England from April 2011 to March 2016. A Poisson model with ED fixed effects is used to explore the impact on long (> 4 h) waits of variations in demand (population need and patient case-mix) and supply (emergency physicians, introduction of a Minor Injury Unit (MIU), inpatient bed occupancy, delayed discharges and long-term care). We assess overall ED waits and waits on a trolley (gurney) before admission. We also investigate variation in performance among EDs. The rate of long overall waits is higher in EDs serving older patients (4.2%), where a higher proportion of attendees leave without being treated (15.1%), in EDs with a higher death rate (3.3%) and in those located in hospitals with greater bed occupancy (1.5%). These factors are also significantly associated with higher rates of long trolley waits. The introduction of a co-located MIU is significantly and positively associated with long overall waits, but not with trolley waits. There is substantial variation in waits among EDs that cannot be explained by observed demand and supply characteristics. The drivers of long waits are only partially understood but addressing them is likely to require a multi-faceted approach. EDs with high rates of unexplained long waits would repay further investigation to ascertain how they might improve.

scholarly journals Characteristics of older adults using patient web portals to view their DXA results

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Stephanie Edmonds ◽  
Yiyue Lou ◽  
Brandi Robinson ◽  
Peter Cram ◽  
Douglas W. Roblin ◽  
...  
Keyword(s):  
Bone Density ◽  
Controlled Trial ◽  
Secondary Analysis ◽  
Patient Characteristics ◽  
Test Results ◽  
Web Portals ◽  
Web Portal ◽  
University Of Iowa ◽  
Kaiser Permanente ◽  
The Web

Abstract Background Sharing test results with patients via patient web portals is a new trend in healthcare. No research has been done examining patient web portal use with bone density test results. The objective of our study was to identify patient characteristics associated with the use of patient web portals to view their bone density test results. Methods A secondary analysis of data from a pragmatic randomized controlled trial of 7749 participants ≥50 years old that had presented for a dual energy X-ray absorptiometry (DXA) bone density test. Patients were interviewed at enrollment and 12 weeks later. Multivariable logistic regression identified patient characteristics that differentiated those who used the web portal from those who did not. Results Our sample included 4669 patients at the two (University of Iowa [UI], and Kaiser Permanente of Georgia [KPGA]) clinical sites that had patient web portals. Of these patients, 3399 (72.8%) reported knowing their test results 12 weeks post-DXA, with 649 (13.9%) reporting that they viewed their DXA results using the web portal. Web portal users were more likely to be from UI than KPGA, and were younger, more educated, had higher health literacy, had osteopenia, and had the same sex as their referring physician (all p < 0.05). Conclusion Only 19.1% of the 3399 patients who knew their DXA results used the available patient web portals to find out about them. Web portal users differed from non-users on several characteristics. This suggests that simply making patient web portals available for use may not be sufficient to appreciably enhance patient awareness of their test results. Based on these findings, a better understanding of the reasons why older, less educated, and less activated patients do not access their test results through patient web portals is needed.

scholarly journals Waiting times in emergency departments: exploring the factors associated with longer patient waits for emergency care in England using routinely collected daily data

2020 ◽  
pp. emermed-2019-208849
Author(s):  
Steven Paling ◽  
Jennifer Lambert ◽  
Jasper Clouting ◽  
Júlia González-Esquerré ◽  
Toby Auterson
Keyword(s):  
Emergency Departments ◽  
Fixed Effects ◽  
Patient Flow ◽  
Waiting Times ◽  
Healthcare Providers ◽  
Ordinary Least Squares ◽  
Hospital Length Of Stay ◽  
Bed Occupancy ◽  
Point Change ◽  
Factors Associated

BackgroundLong lengths of stay (also called waiting times) in emergency departments (EDs) are associated with higher patient mortality and worse outcomes.ObjectiveTo add to the literature using high-frequency data from a large number of hospitals to analyse factors associated with long waiting times, including exploring non-linearities for 'tipping points'.MethodsMultivariate ordinary least squares regressions with fixed effects were used to analyse factors associated with the proportion of patients in EDs in England waiting more than 4 hours to be seen, treated and admitted or discharged. Daily situation reports (Sitrep), hospital episode statistics and electronic staffing records data over 90 days between December 2016 and February 2017 were used for all 138 English NHS healthcare providers with a major ED.ResultsHigher inpatient bed occupancy was correlated with longer ED waiting times, with a non-linear association. In a full hospital, with 100% bed occupancy, the proportion of patients who remained in the ED for more than 4 hours was 9 percentage points higher (95% CI 7.5% to 11.1%) than with an 85% occupancy level. For each percentage point change in the following factors, the proportion of ED stays over 4 hours also increased: more inpatients with hospital length of stay over 21 days (0.07%, 95% CI 0.008% to 0.13%); higher emergency admissions (0.08%, 95% CI 0.06% to 0.10%); and lower discharges relative to admissions on the same day (0.04%, 95% CI 0.02% to 0.06%), the following day (0.05%, 95% CI 0.03% to 0.06%) and at 2 days (0.05%, 95% CI 0.04% to 0.07%).ConclusionsThese results suggest that tackling patient flow and capacity in the wider hospital, particularly very high bed occupancy levels and patient discharge, is important to reduce ED waiting times and improve patient outcomes.

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