scholarly journals Intermediate-linkage steps used to obtain longitudinal data (containing heath service use, morbidity and mortality) for a large cohort of patients who are homeless that visited, and were discharged from hospital in England.

2018 ◽  
Vol 3 (4) ◽  
Author(s):  
Hannah Evans ◽  
Ruth Blackburn ◽  
Michelle Cornes ◽  
Dee Menezes ◽  
Alistair Story ◽  
...  
Keyword(s):  
Hospital Discharge ◽  
Service Use ◽  
Data Linkage ◽  
Hospital Admissions ◽  
Proof Of Concept ◽  
Hospital Data ◽  
Housing Status ◽  
Treatment Services ◽  
Linkage Rate ◽  
Intermediate Linkage

IntroductionIn England, details on hospital admissions and mortality are recorded nationally, but housing status and patients’ hospital discharge arrangements are only recorded locally within discharge services. These data are required to evaluate specialist homeless hospital discharge (HHD) services in England, and can be obtained through linkage within and across sectors. Objectives and ApproachWe aimed to improve linkage to enable the evaluation of HHD schemes. 16 sites with a scheme were recruited along with a specialist facility that deliver screening and treatment services to homeless hostels (Find\&Treat). Linkage fields including National Health Service number (NHS number), name, gender and birthdate for clinical contacts between November 2013 and November 2016 were collected and linked to national hospital data, Hospital Episodes Statistics (HES). To improve linkage with HES, intermediate-linkage to a gender-names dictionary and a national demographic database (NDD) was performed. Ethics, access permissions were obtained through HRA-REC (REC16/EE/0018) and NHS CAG (16/CAG/0021). Results47,569 clinical contacts among people who were homeless were collected from Find&Treat and 12,931 from sites. The median age at mid-study period (15th May 2015) among contacts with sites compared to Find&Treat were similar at 44 (IQR 34-53, n=12,905) and 45 (IQR 35-54, n=47,569), respectively. Among Find&Treat, 82% (n=38,905) were contacts with Males and 18% (n=8,650) with Females. Gender was not collected at all HHD sites or for all admissions. 70% of contacts had missing gender and among these contacts, gender was assigned using the gender-names dictionary. After imputing gender, 52% of contacts all linkage fields and 47% had all but NHS number. These data were linked to the NDD, an approximate 60% linkage rate was achieved retrieving complete linkage fields for these contacts. Conclusion/ImplicationsIntermediate linkage steps described here provides the largest dataset of it’s kind, enabling investigations into effectiveness of hospital discharge schemes in England. The study provides generally a proof of concept that large cohorts of hard-to-reach population groups can be obtained through data linkage.

scholarly journals Resource use and costs associated with epilepsy in the Queensland hospital system: protocol for a population-based data linkage study

BMJ Open ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. e050070
Author(s):  
Ruth Tulleners ◽  
Robin Blythe ◽  
Sasha Dionisio ◽  
Hannah Carter
Keyword(s):  
Health Service ◽  
Service Use ◽  
Data Linkage ◽  
Hospital Admissions ◽  
Population Based ◽  
Health Service Use ◽  
Mortality Data ◽  
Service Utilisation ◽  
Indigenous Status ◽  
Hospital System

IntroductionEpilepsy places a large burden on health systems, with hospitalisations for seizures alone occurring more frequently than those related to diabetes. However, the cost of epilepsy to the Australian health system is not well understood. The primary aim of this study is to quantify the health service use and cost of epilepsy in Queensland, Australia. Secondary aims are to identify differences in health service use and cost across population and disease subgroups, and to explore the associations between health service use and common comorbidities.Methods and analysisThis project will use data linkage to identify the health service utilisation and costs associated with epilepsy. A base cohort of patients will be identified from the Queensland Hospital Admitted Patient Data Collection. We will select all patients admitted between 2014 and 2018 with a diagnosis classification related to epilepsy. Two comparison cohorts will also be identified. Retrospective hospital admissions data will be linked with emergency department presentations, clinical costing data, specialist outpatient and allied health occasions of service data and mortality data. The level of health service use in Queensland, and costs associated with this, will be quantified using descriptive statistics. Difference in health service costs between groups will be explored using logistic regression. Linear regression will be used to model the associations of interest. The analysis will adjust for confounders including age, sex, comorbidities, indigenous status, and remoteness.Ethics and disseminationEthical approval has been obtained through the QUT University Human Research Ethics Committee (1900000333). Permission to waive consent has been granted under the Public Health Act 2005, with approval provided by all relevant data custodians. Findings of the proposed research will be communicated through presentations at national and international conferences, presentations to key stakeholders and decision-makers, and publications in international peer-reviewed journals.

scholarly journals How does general practitioner discontinuity affect healthcare utilisation? An observational cohort study of 2.4 million Norwegians 2007–2017

BMJ Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. e042391
Author(s):  
Lena Janita Skarshaug ◽  
Silje Lill Kaspersen ◽  
Johan Håkon Bjørngaard ◽  
Kristine Pape
Keyword(s):  
Cohort Study ◽  
General Practitioner ◽  
Service Use ◽  
Hospital Admissions ◽  
Age Groups ◽  
Healthcare Utilisation ◽  
Acute Hospital ◽  
Secondary Outcome ◽  
Out Of Hours ◽  
Adult Age

ObjectivesPatients may benefit from continuity of care by a personal physician general practitioner (GP), but there are few studies on consequences of a break in continuity of GP. Investigate how a sudden discontinuity of GP care affects their list patients’ regular GP consultations, out-of-hours consultations and acute hospital admissions, including admissions for ambulatory care sensitive conditions (ACSC).DesignCohort study linking person-level national register data on use of health services and GP affiliation with data on GP activity and GP characteristics.SettingPrimary care.Participants2 409 409 Norwegians assigned to the patient lists of 2560 regular GPs who, after 12 months of stable practice, had a sudden discontinuity of practice lasting two or more months between 2007 and 2017.Primary and secondary outcome measuresMonthly GP consultations, out-of-hours consultations, acute hospital admissions and ACSC admissions in periods during and 12 months after the discontinuity, compared with the 12-month period before the discontinuity using logistic regression models.ResultsAll patient age groups had a 3%–5% decreased odds of monthly regular GP consultations during the discontinuity. Odds of monthly out-of-hours consultations increased 2%–6% during the discontinuity for all adult age groups. A 7%–9% increase in odds of ACSC admissions during the period 1–6 months after discontinuity was indicated in patients over the age of 65, but in general little or no change in acute hospital admissions was observed during or after the period of discontinuity.ConclusionsModest changes in health service use were observed during and after a sudden discontinuity in practice among patients with a previously stable regular GP. Older patients seem sensitive to increased acute hospital admissions in the absence of their personal GP.

scholarly journals Design of COVID-19 staged alert systems to ensure healthcare capacity with minimal closures

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Haoxiang Yang ◽  
Özge Sürer ◽  
Daniel Duque ◽  
David P. Morton ◽  
Bismark Singh ◽  
...  
Keyword(s):  
Hospital Admissions ◽  
Optimal Strategies ◽  
Mitigation Strategies ◽  
Mitigation Measures ◽  
Public Confidence ◽  
Proof Of Concept ◽  
Alert System ◽  
System Safety ◽  
Reducing Costs ◽  
Restrictive Measures

AbstractCommunity mitigation strategies to combat COVID-19, ranging from healthy hygiene to shelter-in-place orders, exact substantial socioeconomic costs. Judicious implementation and relaxation of restrictions amplify their public health benefits while reducing costs. We derive optimal strategies for toggling between mitigation stages using daily COVID-19 hospital admissions. With public compliance, the policy triggers ensure adequate intensive care unit capacity with high probability while minimizing the duration of strict mitigation measures. In comparison, we show that other sensible COVID-19 staging policies, including France’s ICU-based thresholds and a widely adopted indicator for reopening schools and businesses, require overly restrictive measures or trigger strict stages too late to avert catastrophic surges. As proof-of-concept, we describe the optimization and maintenance of the staged alert system that has guided COVID-19 policy in a large US city (Austin, Texas) since May 2020. As cities worldwide face future pandemic waves, our findings provide a robust strategy for tracking COVID-19 hospital admissions as an early indicator of hospital surges and enacting staged measures to ensure integrity of the health system, safety of the health workforce, and public confidence.

scholarly journals Healthcare use and costs in the last year of life: a national population data linkage study

2021 ◽  
pp. bmjspcare-2020-002708
Author(s):  
Katharina Diernberger ◽  
Xhyljeta Luta ◽  
Joanna Bowden ◽  
Marie Fallon ◽  
Joanne Droney ◽  
...  
Keyword(s):  
End Of Life ◽  
Secondary Care ◽  
Urban Areas ◽  
Data Linkage ◽  
Hospital Admissions ◽  
Community Support ◽  
Population Data ◽  
Linkage Study ◽  
Healthcare Use ◽  
Admission Rates

BackgroundPeople who are nearing the end of life are high users of healthcare. The cost to providers is high and the value of care is uncertain.ObjectivesTo describe the pattern, trajectory and drivers of secondary care use and cost by people in Scotland in their last year of life.MethodsRetrospective whole-population secondary care administrative data linkage study of Scottish decedents of 60 years and over between 2012 and 2017 (N=274 048).ResultsSecondary care use was high in the last year of life with a sharp rise in inpatient admissions in the last 3 months. The mean cost was £10 000. Cause of death was associated with differing patterns of healthcare use: dying of cancer was preceded by the greatest number of hospital admissions and dementia the least. Greater age was associated with lower admission rates and cost. There was higher resource use in the urban areas. No difference was observed by deprivation.ConclusionsHospitalisation near the end of life was least frequent for older people and those living rurally, although length of stay for both groups, when they were admitted, was longer. Research is required to understand if variation in hospitalisation is due to variation in the quantity or quality of end-of-life care available, varying community support, patient preferences or an inevitable consequence of disease-specific needs.

Hospitalization Rates Among Dialysis Patients During Hurricane Katrina

2012 ◽  
Vol 27 (4) ◽  
pp. 325-329 ◽  
Author(s):  
David Howard ◽  
Rebecca Zhang ◽  
Yijian Huang ◽  
Nancy Kutner
Keyword(s):  
Hurricane Katrina ◽  
Large Scale ◽  
Service Use ◽  
Hospital Admissions ◽  
Gulf Coast ◽  
The United States ◽  
Time Varying ◽  
Dialysis Patients ◽  
Hospitalization Rates ◽  
The Impact

AbstractIntroductionDialysis centers struggled to maintain continuity of care for dialysis patients during and immediately following Hurricane Katrina's landfall on the US Gulf Coast in August 2005. However, the impact on patient health and service use is unclear.ProblemThe impact of Hurricane Katrina on hospitalization rates among dialysis patients was estimated.MethodsData from the United States Renal Data System were used to identify patients receiving dialysis from January 1, 2001 through August 29, 2005 at clinics that experienced service disruptions during Hurricane Katrina. A repeated events duration model was used with a time-varying Hurricane Katrina indicator to estimate trends in hospitalization rates. Trends were estimated separately by cause: surgical hospitalizations, medical, non-renal-related hospitalizations, and renal-related hospitalizations.ResultsThe rate ratio for all-cause hospitalization associated with the time-varying Hurricane Katrina indicator was 1.16 (95% CI, 1.05-1.29; P = .004). The ratios for cause-specific hospitalization were: surgery, 0.84 (95% CI, 0.68-1.04; P = .11); renal-related admissions, 2.53 (95% CI, 2.09-3.06); P < .001), and medical non-renal related, 1.04 (95% CI, 0.89-1.20; P = .63). The estimated number of excess renal-related hospital admissions attributable to Katrina was 140, representing approximately three percent of dialysis patients at the affected clinics.ConclusionsHospitalization rates among dialysis patients increased in the month following the Hurricane Katrina landfall, suggesting that providers and patients were not adequately prepared for large-scale disasters.Howard D, Zhang R, Huang Y, Kutner N. Hospitalization rates among dialysis patients during Hurricane Katrina. Prehosp Disaster Med. 2012;27(4):1-5.

Abstract O.02: Validation of Kawasaki Disease Incidence Assessment as Derived from Health System Administrative Databases vs. Active Retrospective Surveillance in Ontario, Canada

Circulation ◽  
2015 ◽  
Vol 131 (suppl_2) ◽  
Author(s):  
Cedric Manlhiot ◽  
Sunita O’Shea ◽  
Bailey Bernknopf ◽  
Michael Labelle ◽  
Mathew Mathew ◽  
...  
Keyword(s):  
Kawasaki Disease ◽  
Hospital Discharge ◽  
Hospital Admissions ◽  
Disease Incidence ◽  
Administrative Databases ◽  
Canadian Hospital ◽  
Hospital Discharge Database ◽  
Incident Cases ◽  
Discharge Database

Introduction: Historically, 2 methods have been used to determine the incidence of Kawasaki disease (KD): active or passive surveillance, or the use of administrative databases. Given the increasing regulatory requirements, mainly around patient privacy, periodic retrospective surveillances have become increasingly challenging. Administrative databases are not curated datasets and doubts have been cast on their accuracy. Methods: The Hospital for Sick Children has been conducting retrospective triennial surveillances of KD since 1995 by contacting all hospitals in Ontario and manually reviewing all cases through chart review, reconciling inter-hospital transfers and multiple readmissions. We queried the Canadian hospital discharge database (Canadian Institute for Health Information) for hospitalizations associated with a diagnosis of KD between 2004-9. The administrative dataset was manually reviewed; patient national health number, institution and dates of admission/discharge were used to identify inter-hospital transfers, readmission and follow-up episodes. Results: The Canadian hospital discharge database reported 1,685 admissions during the study period (281±44 per year) for Ontario. Manual review of the dataset identified 219 (13%) as inter-hospital transfers (56, 26%), readmissions (122, 56%), admissions for follow-up of coronary artery aneurysms (14, 6%) or hospital admissions not related to KD (27, 12%). When these admissions were removed, the total number of incident cases for the study period was 1,466 (244±45 per year). The retrospective triennial surveillance identified 1,373 KD cases during the same period (229±33 per year). The Canadian hospital discharge database overestimated the number of cases in all 6 years by an average of 6.7±5.9%. The overestimation likely comes from patients who were originally diagnosed with KD but in whom the diagnosis of KD was subsequently excluded (historically ~5-6%). Conclusions: Reliance on administrative data to determine incidence of KD is possible and accurate; data should be manually reviewed to remove non-incident cases and estimates should be adjusted to reflect the expected proportion of patients in whom the diagnosis of KD will be subsequently excluded.

Abstract TP374: Data Linkage is Effective for Improving the Available Data for Stroke: An Example from the Australian Stroke Clinical Registry.

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Monique F Kilkenny ◽  
Helen M Dewey ◽  
Natasha A Lannin ◽  
Vijaya Sundararajan ◽  
Joyce Lim ◽  
...  
Keyword(s):  
Hospital Discharge ◽  
Hospital Discharge Data ◽  
Hospital Data ◽  
High Quality ◽  
Clinical Registry ◽  
Large Hospital ◽  
Common Data Elements ◽  
Discharge Data ◽  
Data Elements ◽  
Data Collections

Introduction: Multiple data collections can be a burden for clinicians. In 2009, the Australian Stroke Clinical Registry (AuSCR) was established by non-government and research organizations to provide quality of care data unavailable for acute stroke admissions. We show here the reliability of linking complimentary registry data with routinely collected hospital discharge data submitted to governmental bodies. Hypothesis: A high quality linkage with a > 90% rate is possible, but requires multiple personal identifiers common to each dataset. Methods: AuSCR identifying variables included date of birth (DoB), Medicare number, first name, surname, postcode, gender, hospital record number, hospital name and admission date. The Victorian Department of Health emergency department (ED) and hospital discharge linked dataset has most of these, with first name truncated to the first 3 digits, but no surname. Common data elements of AuSCR patients registered at a large hospital in Melbourne, Victoria (Australia) between 15 June 2009 and 31 December 2010 were submitted to undergo stepwise deterministic linkage. Results: The Victorian AuSCR sample had 818 records from 788 individuals. Three steps with 1) Medicare number, postcode, gender and DoB (80% matched); 2) hospital number/admit date; and 3) ED number/visit date were required to link AuSCR data with the ED and hospital discharge data. These led to an overall high quality linkage of >99% (782/788) of AuSCR patients, including 731/788 for ED records and 736/788 for hospital records. Conclusion: Multiple personal identifiers from registries are required to achieve reliable linkage to routinely collected hospital data. Benefits of these linked data include the ability to investigate a broader range of research questions than with a single dataset. Characters with spaces= 1941 (limit is 1950)

scholarly journals Hospitalisation for COPD in Puglia: the role of hospital discharge database to estimate prevalence and incidence

2016 ◽  
Vol 70 (3) ◽  
Author(s):  
P. Trerotoli ◽  
N. Bartolomeo ◽  
A.M. Moretti
Keyword(s):  
Disease Management ◽  
Hospital Discharge ◽  
Respiratory Diseases ◽  
Hospital Admissions ◽  
Diagnostic Procedures ◽  
Chronic Respiratory Disease ◽  
Chronic Obstructive ◽  
Chronic Respiratory Diseases ◽  
Hospital Discharge Database ◽  
Discharge Database

Background and aim. Chronic Obstructive Pulmonary Disease (COPD), although largely preventable, is a great health burden in all the countries worldwide. Statistics of morbidity and mortality of COPD show the need for correct management of the disease. Chronic Obstructive Respiratory Diseases (DRG 88) are in 9th place for discharge in in-patient hospital admission. It is necessary to establish specific indicators which are efficacious and relevant for the patient, the doctor and the health manager. This study will analyse the information in respect of hospital admissions (Hospital discharge database) in Puglia for the period 2000-2005. Methods. The analysis was carried out utilising the Puglia Region hospital patient discharge database, selecting those patients with admission for chronic respiratory disease as principal or secondary diagnosis. Results. Chronic respiratory diseases are more frequent in males and in people over 45 years old with frequency increasing with age. Geographical distribution shows that there are greater rates of hospitalisation in big cities and in the neighbourhood of industrial areas. Although the trend over time is slight. A higher percentage of re-admission has been found for patients with COPD, and the interval between the two admissions occurs within one or two months; the diagnosis at the second admission is the same as for the first. 10.6% of discharge forms report one diagnosis, especially in patients older than 65 years of age. Little could be said about diagnostic procedures because these are not reported on the discharge form. Conclusion. Hospitalisation data confirms expectations regarding age and sex of patients. The high hospitalisation rates indicate that in-patients care still remains the only viable treatment for COPD and other chronic respiratory diseases. The high number of exacerbations reflect the absence of out-patients service or community care, and the same diagnosis in more than one episode shows the lack of efficiency of health services and disease management. This data is necessary to understand disease distribution and the modification of disease management in order to reduce health care costs, to increase efficacy in disease control and to limit repeated exacerbation and so to obtain the maximum benefit for the patients.

scholarly journals The Stepping On Fall Prevention Program Scale-Up in NSW: Program Reach and Fall-Related Health Service Use

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Serene S Paul ◽  
Qiang Li ◽  
Lara Harvey ◽  
Therese Carroll ◽  
Annabel Priddis ◽  
...  
Keyword(s):  
Health Service ◽  
Fall Prevention ◽  
Prevention Program ◽  
Service Use ◽  
Hospital Admissions ◽  
Scale Up ◽  
Service Utilisation ◽  
Program Outcomes ◽  
Fall Prevention Program ◽  
Routinely Collected Data

IntroductionFalls in older adults are associated with increased healthcare costs. Falls may be prevented or minimised with multifactorial interventions including exercise and behavioural modification. Objectives and ApproachTo describe the reach of the scale-up of Stepping On, a fall prevention program targeting community-dwellers aged 65 years and older in NSW, Australia; and fall-related ambulance service use and fall-related hospitalisations after scale-up. Routinely-collected data on program reach, fall-related ambulance usage and fall-related hospital admissions in NSW residents aged ≥65 years between 2009 and 2015 were compared within Statistical Local Areas prior to and following implementation of Stepping On using multilevel models. ResultsFrom 2009 to 2014 the program was delivered in 1,077 sites to 10,096 people with an average (SD) age of 81.0 (7.2) years. Rates of fall-related ambulance use and hospital admissions per 100-person-years were 1-2 in people aged 66-74, 4-5 in people aged 75-84 and 12-13 in people aged ≥85. These rates increased over time (p<.001). Overall, the interaction between time and program delivery was not significant for fall-related ambulance use or hospital admissions. The time-related increase in fall-related ambulance usage in people aged 75-84 years may have been moderated by Stepping On (RR 0.97, 95% CI 0.93–1.00, p=.045). Conclusion / ImplicationsThere was no indication of either a reduced rate of fall-related ambulance use or hospital admissions across the entire sample. There was a suggestion of a reduction in ambulance call-outs for falls in people aged 75-84. The lack of a detectable impact on fall-related health service usage may be due to the use of routinely collected data not intended for research purposes or inability to remove those who would be ineligible for Stepping On from the data analyses. Increasing the program reach and targeting groups contributing most to health service utilisation may improve program outcomes.

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