Using routine data to monitor population level interventions: the example of the Keep Well health check programme in Scotland

IntroductionThe Inverse Care Law (ICL) programme in Wales was setup to identify people in deprived communities at risk of cardiovascular disease (CVD) through a health check; offering lifestyle and medical intervention as appropriate. Evaluation of this programme to tackle health inequalities ensuring services are available is vital. Objectives and ApproachTo evaluate the uptake and long term outcomes of the programme, using longitudinal evidence-based results, it was necessary to develop an efficient and cost effective approach with a readily available source of data. To achieve this, the Welsh Longitudinal General Practice (WLGP) data held in Secure Anonymised Information Linkage (SAIL) databank was utilised, with programme-specific code deployed within primary care at the point of the health check, which identified the intervention, potential CVD risks, referrals and any follow-up. Lifestyle risk factors could be evaluated such as poor diet, physical inactivity, smoking and high alcohol intake. ResultsUtilising routine data sources and reproducible SQL (Standard Query Language), we evaluated the programme initialisation between February 2015 and November 2016, and found of 55 General Practices who participated, 31 of 35 in Aneurin Bevan (AB) and 17 of 20 in Cwm Taf (CT) University Health Boards, providing data which allowed identification of the health check and associated outcomes of interest in the routine data, with 3 (2 AB, 1 CT) since delivering. There are ongoing evaluations on the various risk factors longitudinally as well as the overall implementation of the programme itself, with this collaborative approach succeeding in utilising existing powerful data linkage within the SAIL databank to identify our intervention and facilitate long-term follow-up at an individual level using robust information governance mechanisms. Conclusion/ImplicationsLessons learned and challenges encountered are being fed back as part of our evaluation, with further work assessing the long term population level outcomes and impact of the health check and services provided across these deprivation groups, informing and refining programme delivery of similar work across Wales in the future.

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How universal are universal preschool health checks? An observational study using routine data from New Zealand’s B4 School Check

BMJ Open ◽

10.1136/bmjopen-2018-025535 ◽

2019 ◽

Vol 9 (4) ◽

pp. e025535 ◽

Cited By ~ 2

Author(s):

Sheree Gibb ◽

Barry Milne ◽

Nichola Shackleton ◽

Barry J Taylor ◽

Richard Audas

Keyword(s):

Routine Data ◽

Population Level ◽

Participation Rates ◽

Hearing Tests ◽

Universal Preschool ◽

Emergency Admissions ◽

Health Checks ◽

Strengths And Difficulties ◽

Parental Evaluation ◽

Health Screen

ObjectivesWe aimed to estimate how many children were attending a universal preschool health screen and to identify characteristics associated with non-participation.DesignAnalysis of population-level linked administrative data.ParticipantsChildren were considered eligible for a B4 School Check for a given year if:(1) they were ever resident in New Zealand (NZ),(2) lived in NZ for at least 6 months during the reference year, (3) were alive at the end of the reference year, (4) either appeared in any hospital (including emergency) admissions, community pharmaceutical dispensing or general practitioner enrolment datasets during the reference year or (5) had a registered birth in NZ. We analysed 252 273 records over 4 years, from 1 July 2011 to 30 June 2015.ResultsWe found that participation rates varied for each component of the B4 School Check (in 2014/2015 91.8% for vision and hearing tests (VHTs), 87.2% for nurse checks (including height, weight, oral health, Strengths and Difficulties Questionnaire [SDQ] and parental evaluation of development status) and 62.1% for SDQ – Teacher [SDQ-T]), but participation rates for all components increased over time. Māori and Pacific children were less likely to complete the checks than non-Māori and non-Pacific children (for VHTs: Māori: OR=0.60[95% CI 0.61 to 0.58], Pacific: OR=0.58[95% CI 0.60 to 0.56], for nurse checks: Māori: OR=0.63[95% CI 0.64 to 0.61], Pacific: OR=0.67[95% CI 0.69 to0.65] and for SDQ-T: Māori: OR=0.76[95% CI 0.78 to 0.75], Pacific: OR=0.37[95% CI 0.38 to 0.36]). Children from socioeconomically deprived areas, with younger mothers, from rented homes, residing in larger households, with worse health status and with higher rates of residential mobility were less likely to participate in the B4 School Check than other children.ConclusionThe patterns of non-participation suggest a reinforcing of existing disparities, whereby the children most in need are not getting the services they potentially require. There needs to be an increased effort by public health organisations, community and whānau/family to ensure that all children are tested and screened.

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Improving the usefulness of mortality data in Brazil: reclassification of ill-defined causes of death

European Journal of Public Health ◽

10.1093/eurpub/ckaa165.049 ◽

2020 ◽

Vol 30 (Supplement_5) ◽

Author(s):

E França ◽

L Ishitani ◽

R Teixeira ◽

C Cunha ◽

F Marinho

Keyword(s):

Interpersonal Violence ◽

Large Scale ◽

Causes Of Death ◽

Age Groups ◽

Family Health ◽

Routine Data ◽

Population Level ◽

Mortality Data ◽

Access To Health Services ◽

Underlying Causes

Abstract Background Garbage codes (GC) among registered causes of death can bias mortality analysis. In Brazil, more than one million deaths occurred annually in 2006-2017 and around 100,000 deaths per year were originally attributed to GC ill-defined causes of death (IDCD) in the Mortality Information System (SIM - Sistema de Informação sobre Mortalidade). To provide more accurate cause-of-death analysis, routine investigations of IDCD in the health surveillance system have been implemented in the country since 2005. The objective of this study was to analyze specific underlying causes for deaths originally assigned as IDCD in the SIM in 2006-2017. Methods For all IDCD (ICD codes from chapter 18, or R-codes) identified in the SIM, municipal health professionals collected information about the final disease obtained from hospital records, autopsies, forms of family health teams, and home investigation. Proportions of reclassified deaths by cause-specific mortality fractions (CSMF) derived from the reclassified IDCD by age and four calendar periods were analyzed to assess specific causes detected after investigation. Results A high proportion of deaths due to IDCD was investigated in 2006-2017 (32%). From a total of 257,367 IDCD reclassified, chronic diseases (56.6%), injuries (7.2%), and infectious (5.2%) or neonatal, maternal, malnutrition (1.7%) were the underlying causes detected among IDCD. Neonatal-related conditions, interpersonal violence, ischemic heart disease and stroke were the leading causes detected in the age groups 0-9 years, 10-29 years, 30-69 years, 70 years and over, respectively. Conclusions High proportions of IDCD reassigned to more informative causes after review indicate the success of this approach to correct misclassification in the SIM, an initiative that should be maintained. Training physicians on death certification along with better quality of medical care and access to health services would lead to further improvement. Key messages Investigation of IDCD as part of routine data collection on a large scale as had occurred in Brazil in 2006-2017 is an innovative approach to strengthen population-level mortality statistics. In addition to reducing the proportions of IDCD by their reclassification into specific causes, this initiative opens up the prospect of using these results for redistributing remaining cases of IDCD.

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Rolling out new biomedical HIV prevention tools: what can be learned from Avahan, the India AIDS initiative?

Sexual Health ◽

10.1071/sh14064 ◽

2014 ◽

Vol 11 (2) ◽

pp. 207 ◽

Cited By ~ 5

Author(s):

Gina Dallabetta ◽

Padma Chandrasekaran ◽

Tisha Wheeler ◽

Anjana Das ◽

Lakshmi Ramakrishnan ◽

...

Keyword(s):

Hiv Prevention ◽

Health Services ◽

Routine Data ◽

Population Level ◽

Great Promise ◽

Data Systems ◽

African Countries ◽

Hiv Prevention Intervention ◽

Frontline Workers ◽

Biomedical Hiv Prevention

More than 30 years after HIV was first identified as a disease, with disastrous consequences for many subpopulations in most countries and for entire populations in some African countries, it continues to occupy centre stage among the world’s many global health challenges. Prevention still remains the primary long-term focus. New biomedical tools such as pre-exposure propyhlaxis (PrEP) and treatment hold great promise for select groups such as key populations (KPs) who are critical to transmission dynamics, and serodiscordant couples. Programs delivering these new tools will need to layer them over existing services, with potential modifications for increased and sustained engagement between health services and beneficiaries owing to the nature of the interventions. Avahan, an HIV prevention intervention for KPs in six states in India, achieved population-level impact with conventional prevention programming, which, however, required high program–beneficiary engagement. Avahan’s implementation strategy included articulating clear service definitions and denominator-based targets; establishing routine data systems with regular, multilevel supervision that allowed for cross-learning across the program; and developing a cadre of frontline workers through KP peer outreach workers who addressed structural issues and provided viable and sustainable mechanisms for sustained interaction between health services and KPs. This basic prevention implementation infrastructure was used to expand clinical services over time. Many of the lessons from programs such as Avahan can be applied to KP programs that are expanding service scope, including PrEP and treatment.

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Wales Inverse Care Law Programme - Design and Implementation of Routine Data Evaluation and Lessons Learned

International Journal for Population Data Science ◽

10.23889/ijpds.v5i5.1517 ◽

2020 ◽

Vol 5 (5) ◽

Author(s):

Ashley Akbari ◽

Rowena Griffiths ◽

Alice Puchades ◽

Sara Thomas

Keyword(s):

Health Care Providers ◽

Large Scale ◽

Routine Data ◽

Lessons Learned ◽

Health Check ◽

Final Report ◽

Care Providers ◽

Targeted Interventions ◽

Inverse Care Law ◽

The Impact

IntroductionThe Inverse Care Law (ICL) programme in Wales was setup to tackle health inequalities. Eligible populations from deprived communities, at higher risk of cardiovascular disease (CVD) were invited to a health-check and offered appropriate lifestyle and clinical interventions. Objectives and ApproachEvaluation of this programme is vital to ensure that targeted interventions have been received by those most in need, including referrals to lifestyle services and support. The use of longitudinal population-scale routine-data required the development of an approach which was both efficient and cost effective. To achieve this, the Welsh Longitudinal General Practice (WLGP) data held in SAIL Databank was utilised. A programme-specific methodology was agreed by the programme-board and developed so that data collected from GP records prior, during and post health-check accurately identified the eligible population and allowed the effective assessment of lifestyle and clinical risk factors for CVD; poor diet, physical inactivity, smoking and high alcohol intake, so appropriate interventions could be offered. ResultsWe evaluated the programme from 2015 to 2019 in 70 GP’s across the participating Health-Boards, and identified 175,671 individuals eligible by the programme criteria. Substantial preliminary work has been carried out to ensure the specification of outcome measures are both clinically and epidemiologically accurate and relevant. The final report scheduled for release in August-2020, which will evaluate the impact of the programme. Conclusion / ImplicationsThis ambitious evaluation of a large-scale programme set in the community involving disparate systems and a range of stakeholders, has been both complex and challenging, requiring substantial effort to design and implement. We hope the outcomes and lessons learned from our experience will improve the design, implementation and evaluation of the programme and lead to improvements in services and the quality of life for people in Wales, and provide an exemplar for health care providers worldwide wishing to conduct similar programmes in the future.

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The depression phenotype in a European population-based study

European Journal of Public Health ◽

10.1093/eurpub/ckz186.554 ◽

2019 ◽

Vol 29 (Supplement_4) ◽

Author(s):

S Cuschieri ◽

J Mamo

Keyword(s):

Low Socioeconomic Status ◽

Primary Care Physicians ◽

Population Level ◽

Female Gender ◽

Educational Status ◽

Population Based ◽

European Population ◽

Health Check ◽

Health Concern ◽

Cross Sectional

Abstract Introduction Depression is a growing public health concern and associated with a number of co-morbidities including diabetes mellitus. The aim was to estimate the prevalence of depression at a population level across different glycaemic statuses while establishing phenotypic characteristics of this sub-population. Methods A national representative cross-sectional study was conducted in Malta (2014-6). Participants were categorized into different sub-populations according to their glycaemic status. Depression prevalence rates and bio-socio-economic characteristics for each sub-population were established. Multiple regression analyses performed to identify links between glycaemic status and depression. Results Depression was prevalent in 17.15% of our study population (CI 95%: 16.01 - 18.36) with a female predominance. The normoglycaemic sub-population had the highest depression rates. Persons with known diabetes had a higher probability of having a history of depression (OR:2.36 CI 95%:1.12 - 4.96), as well as with being of female gender, having lower educational status, smoking tobacco and having established cardiovascular disease. Conclusions Depression was highly prevalent among the normoglycaemic population. Primary care physicians should implement a depression screening tool as part of their routine health check-ups, with special attention to those with cardiovascular co-morbidities and low socioeconomic status. Key messages Depression prevalent mostly in the normoglycemic population. Screening for depression should be part of routine health check-ups.

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Mixed method estimation of population level HIV viral suppression rate in the Western Cape, South Africa

10.1101/2020.03.19.20038745 ◽

2020 ◽

Author(s):

Elton Mukonda ◽

Nei-Yuan Hsiao ◽

Lara Vojnov ◽

Landon Myer ◽

Maia Lesosky

Keyword(s):

Viral Suppression ◽

Routine Data ◽

Population Level ◽

Hiv Prevalence ◽

Sub Saharan Africa ◽

Sensitivity Analyses ◽

People Living With Hiv ◽

Western Cape ◽

Test Results ◽

Individual Level

AbstractIntroductionThere are few population-wide data on viral suppression (VS) that can be used to monitor programmatic targets in sub-Saharan Africa. We describe how routinely collected viral load (VL) data from ART programmes can be extrapolated to estimate population VS and validate this using a combination of empiric and model-based estimates.MethodsVL test results from were matched using a record linkage algorithm to obtain linked results for individuals. Test- and individual-level VS rates were based on test VL values <1000 cps/ml, and individual VL <1000 cps/mL in a calendar year, respectively. We calculated population VS among people living with HIV (PLWH) in the province by combining census-derived mid-year population estimates, HIV prevalence estimates and individual level VS estimates from routine VL data.ResultsApproximately 1.9 million VL test results between 2008 – 2018 were analysed. Among individuals in care, VS increased from 85.5% in 2008 to 90% in 2018. Population VS among all PLWH in the province increased from 12.2% in 2008 to 51.0% in 2017. The estimates derived from this method are comparable to those from other published studies. Sensitivity analyses showed that the results are robust to variations in linkage method, but sensitive to the extreme combinations of assumed ART coverage and population HIV prevalence.ConclusionWhile validation of this method in other settings is required, this approach provides a simple, robust method for estimating population VS using routine data from ART services that can be employed by national programmes in high-burden settings.

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Mixed-method estimation of population-level HIV viral suppression rate in the Western Cape, South Africa

BMJ Global Health ◽

10.1136/bmjgh-2020-002522 ◽

2020 ◽

Vol 5 (8) ◽

pp. e002522

Author(s):

Elton Mukonda ◽

Nei-Yuan Hsiao ◽

Lara Vojnov ◽

Landon Myer ◽

Maia Lesosky

Keyword(s):

Viral Suppression ◽

Routine Data ◽

Population Level ◽

Hiv Prevalence ◽

Sub Saharan Africa ◽

Sensitivity Analyses ◽

People Living With Hiv ◽

Western Cape ◽

Test Results ◽

Individual Level

IntroductionThere are few population-wide data on viral suppression (VS) that can be used to monitor programmatic targets in sub-Saharan Africa. We describe how routinely collected viral load (VL) data from antiretroviral therapy (ART) programmes can be extrapolated to estimate population VS and validate this using a combination of empiric and model-based estimates.MethodsVL test results from were matched using a record linkage algorithm to obtain linked results for individuals. Test-level and individual-level VS rates were based on test VL values <1000 cps/mL, and individual VL <1000 cps/mL in a calendar year, respectively. We calculated population VS among people living with HIV (PLWH) in the province by combining census-derived midyear population estimates, HIV prevalence estimates and individual level VS estimates from routine VL data.ResultsApproximately 1.9 million VL test results between 2008 and 2018 were analysed. Among individuals in care, VS increased from 85.5% in 2008 to 90% in 2018. Population VS among all PLWH in the province increased from 12.2% in 2008 to 51.0% in 2017. The estimates derived from this method are comparable to those from other published studies. Sensitivity analyses showed that the results are robust to variations in linkage method, but sensitive to the extreme combinations of assumed VL testing coverage and population HIV prevalence.ConclusionWhile validation of this method in other settings is required, this approach provides a simple, robust method for estimating population VS using routine data from ART services that can be employed by national programmes in high-burden settings.

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