scholarly journals Annual consultation incidence of osteoarthritis estimated from population-based health care data in England

Rheumatology ◽  
2015 ◽  
Vol 54 (11) ◽  
pp. 2051-2060 ◽  
Author(s):  
Dahai Yu ◽  
George Peat ◽  
John Bedson ◽  
Kelvin P. Jordan
Keyword(s):  
Health Care ◽  
Population Based ◽  
Health Care Data ◽  
Annual Consultation

scholarly journals Determining the Cancer Diagnostic Interval Using Administrative Health Care Data in a Breast Cancer Cohort

2019 ◽  
pp. 1-10 ◽  
Author(s):  
Patti A. Groome ◽  
Colleen Webber ◽  
Marlo Whitehead ◽  
Rahim Moineddin ◽  
Eva Grunfeld ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Health Care ◽  
Control Charts ◽  
Population Level ◽  
Population Based ◽  
Statistical Control ◽  
Health Care Data ◽  
Cancer Diagnostic ◽  
Breast Cancer Cohort ◽  
Diagnostic Interval

PURPOSE Population-based administrative health care data could be a valuable resource with which to study the cancer diagnostic interval. The objective of the current study was to determine the first encounter in the diagnostic interval and compute that interval in a cohort of patients with breast cancer using an empirical approach. METHODS This is a retrospective cohort study of patients with breast cancer diagnosed in Ontario, Canada, between 2007 and 2015. We used cancer registry, physician claims, hospital discharge, and emergency department visit data to identify and categorize cancer-related encounters that were more common in the three months before diagnosis. We used statistical control charts to define lookback periods for each encounter category. We identified the earliest cancer-related encounter that marked the start of the diagnostic interval. The end of the interval was the cancer diagnosis date. RESULTS The final cohort included 69,717 patients with breast cancer. We identified an initial encounter in 97.8% of patients. Median diagnostic interval was 36 days (interquartile range [IQR], 19 to 71 days). Median interval decreased with increasing stage at diagnosis and varied across initial encounter categories, from 9 days (IQR, 1 to 35 days) for encounters with other cancer as the diagnosis to 231 days (IQR 77 to 311 days) for encounters with cyst aspiration or drainage as the procedure. CONCLUSION Diagnostic interval research can inform early detection guidelines and assess the success of diagnostic assessment programs. Use of administrative data for this purpose is a powerful tool for improving diagnostic processes at the population level.

scholarly journals A validation study of the identification of haemophagocytic lymphohistiocytosis in England using population-based health data

2021 ◽  
Author(s):  
Mark John Bishton ◽  
Peter Stilwell ◽  
Tim Card ◽  
Peter Lanyon ◽  
Lu Ban ◽  
...  
Keyword(s):  
Health Care ◽  
Predictive Value ◽  
Population Based ◽  
Future Research ◽  
Mortality Data ◽  
Free Text ◽  
Active Case Finding ◽  
Haemophagocytic Lymphohistiocytosis ◽  
Health Care Data ◽  
Icd 10

We assessed the validity of coded health care data to identify cases of haemophagocytic lymphohistiocytosis (HLH). Hospital Episode Statistics (HES) identified 127 cases within five hospital Trusts 2013-2018 using ICD-10 codes D76.1, D76.2 and D76.3. Hospital records were reviewed to validate diagnoses. 73/74 patients with confirmed/probable HLH were coded D76.1 or D76.2 (positive predictive value 89.0% [95% CI 80.2-94.9%]). For cases considered not HLH, 44/53 were coded D76.3 (negative predictive value 97.8% [95% CI 88.2%-99.9%]). D76.1 or D76.2 had 68% sensitivity in detecting HLH compared to an established active case finding HLH register in Sheffield. Office for National Statistics (ONS) mortality data (2003-2018) identified 698 patients coded D76.1, D76.2 and D76.3 on death certificates. 541 were coded D76.1 or D76.2 of whom 524(96.9%) had HLH in the free text cause of death. Of 157 coded D76.3, 66(42.0%) had HLH in free text. D76.1 and D76.2 codes reliably identify HLH cases, and provide a lower bound on incidence. Non-concordance between D76.3 and HLH excludes D76.3 as an ascertainment source from HES. Our results suggest electronic health care data in England can enable population wide registration and analysis of HLH for future research.

Antibiotics Prescription Patterns in Primary Health Care in Qatar – A Population based study from 2017 to 2018

2020 ◽  
Author(s):  
Hanan Khudadad ◽  
Lukman Thalib
Keyword(s):  
Health Care ◽  
Antibiotic Resistance ◽  
Primary Health Care ◽  
Respiratory System ◽  
Population Based ◽  
Antibiotics Resistance ◽  
Prescription Patterns ◽  
Primary Health ◽  
Primary Health Care Centers ◽  
Health Care Centers

Background: Antibiotics are antimicrobial drugs used in the treatment and prevention of bacterial infections. They played a pivotal role in achieving major advances in medicine and surgery (1). Yet, due to increased and inappropriate use of antibiotics, antibiotic resistance (AR) has become a growing public health problem. Information on antibiotic prescription patterns are vital in developing a constructive approach to deal with growing antibiotic resistance (2). The study aims to describe the population based antibiotic prescriptions among patients attending primary care centers in Qatar. Methodology: A population based observational study of all medications prescribed in the all Primary Health Care Centers during the period of 2017-2018 in Qatar. Records with all medication prescriptions were extracted and linked to medical diagnosis. Antibiotics prescriptions records were compared to non- antibiotics records using logistic regression model in identifying the potential predictors for antibiotic prescriptions. Results: A total of 11,069,439 medication prescriptions given over a period of two-years, we found about 12.1% (n= 726,667) antibiotics prescriptions were antibiotics, and 65% of antibiotics are prescribed and received by the patients at the first visits. Paracetamol (22.3%) was the first highest medication prescribed followed by antibiotics (12.1 %) and vitamin D2 (10.2 %). More than half of all antibiotics prescribed during the period of January 2017 to December 2018 were Penicillin (56.9%). We found that half of the antibiotics (49.3 %) have been prescribed for the respiratory system comparing to the other body system. We found that males were 29% more likely be given an antibiotic compared to females (OR=1.29, 95% CI= 1.24- 1.33). Implications: The study provides a baseline data to enable PHCC management to design effective intervention program to address the problem of antibiotics resistance. Furthermore, it will help the policymakers to comprehend the size of the issue and develop a system to manage the antibiotics therapy. Conclusion: Antibiotics was the second highest medication prescribed in the Primary Health Care Centers in Qatar after paracetamol and most of the patients received it at the first visit. Most of the prescriptions in Primary Health Care Centers in Qatar were for the respiratory system, and Penicillin was the highest class prescribed. Male visitors were prescribed antibiotics more than female visitors.

scholarly journals Cervical cancer survivors and health care use: A Danish population-based register study

2021 ◽  
Vol 161 (2) ◽  
pp. 565-572
Author(s):  
Malene Skorstengaard ◽  
Maria Eiholm Frederiksen ◽  
Miguel Vázquez-Prada Baillet ◽  
Anna-Belle Beau ◽  
Pernille Tine Jensen ◽  
...  
Keyword(s):  
Health Care ◽  
Cervical Cancer ◽  
Cancer Survivors ◽  
Population Based ◽  
Health Care Use ◽  
Register Study ◽  
Danish Population

scholarly journals Economics of mental well-being: a prospective study estimating associated health care costs and sickness benefit transfers in Denmark

2021 ◽  
Author(s):  
Ziggi Ivan Santini ◽  
Hannah Becher ◽  
Maja Bæksgaard Jørgensen ◽  
Michael Davidsen ◽  
Line Nielsen ◽  
...  
Keyword(s):  
Health Care ◽  
Mental Illness ◽  
Healthcare Costs ◽  
Psychiatric Morbidity ◽  
Government Expenditure ◽  
Well Being ◽  
Population Based ◽  
Sickness Benefit ◽  
A Prospective Study ◽  
Mental Well Being

Abstract Background Previous literature has examined the societal costs of mental illness, but few studies have estimated the costs associated with mental well-being. In this study, a prospective analysis was conducted on Danish data to determine 1) the association between mental well-being (measured in 2016) and government expenditure in 2017, specifially healthcare costs and sickness benefit transfers. Methods Data stem from a Danish population-based survey of 3,508 adults (aged 16 + years) in 2016, which was linked to Danish registry data. A validated scale (WEMWBS) was used for the assessment of mental well-being. Costs are expressed in USD PPP. A two-part model was applied to predict costs in 2017, adjusting for sociodemographics, health status (including psychiatric morbidity and health behaviour), as well as costs in the previous year (2016). Results Each point increase in mental well-being (measured in 2016) was associated with lower healthcare costs ($− 42.5, 95% CI = $− 78.7, $− 6.3) and lower costs in terms of sickness benefit transfers ($− 23.1, 95% CI = $− 41.9, $− 4.3) per person in 2017. Conclusions Estimated reductions in costs related to mental well-being add to what is already known about potential savings related to the prevention of mental illness. It does so by illustrating the savings that could be made by moving from lower to higher levels of mental well-being both within and beyond the clinical range. Our estimates pertain to costs associated with those health-related outcomes that were included in the study, but excluding other social and economic outcomes and benefits. They cover immediate cost estimates (costs generated the year following mental well-being measurement) and not those that could follow improved mental well-being over the longer term. They may therefore be considered conservative from a societal perspective. Population approaches to mental health promotion are necessary, not only to potentiate disease prevention strategies, but also to reduce costs related to lower levels of mental well-being in the non-mental illness population. Our results suggest that useful reductions in both health care resource use and costs, as well as in costs due to sick leave from the workplace, could be achieved from investment in mental well-being promotion within a year.

scholarly journals Demographic Characteristics, Care, and Outcomes for Children with Oral Clefts in Three States Using Participants from the National Birth Defects Prevention Study

2009 ◽  
Vol 46 (6) ◽  
pp. 575-582 ◽  
Author(s):  
Peter Damiano ◽  
Margaret Tyler ◽  
Paul A. Romitti ◽  
Charlotte Druschel ◽  
April A. Austin ◽  
...  
Keyword(s):  
Health Care ◽  
New York ◽  
Health Status ◽  
Birth Defects ◽  
Population Based ◽  
Primary Objective ◽  
Demographic Characteristics ◽  
Prevention Study ◽  
Care Needs ◽  
Oral Clefts

Objective: The primary objective of this study was to evaluate whether there were differences in the characteristics and outcomes of care for children with oral clefts (OCs) among population-based samples in three states. Design: Data on the health status and on speech and esthetic outcomes were collected using structured telephone interviews conducted during 2005–2006 with mothers of children with OCs aged 2 to 7 in Arkansas, Iowa, and New York. Participants: Mothers of children born with nonsyndromic OCs on or after January 1, 1998, and on or before December 31, 2003, in Arkansas, Iowa, or New York. Subjects were identified through their participation in the ongoing National Birth Defects Prevention Study. Main Outcome Measures: Demographic characteristics, rating of cleft care, severity of condition, health status, esthetic outcomes, and speech problems were evaluated by state of residence. Results: Children with OCs from Arkansas were from lower income families, and their parents were less likely to be married. Children with OCs from Arkansas were more likely to have special health care needs and to require mental health care. Few differences were found across states in type of cleft, severity of cleft, or outcomes of cleft care. Conclusions: Combining results from population-based samples across multiple studies increases the variability of sample characteristics. Including multiple states can be an efficient way to learn more about the outcomes of medical care for less common conditions such as oral cleft.

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