Census transformation in New Zealand: Using administrative data without a population register

2015 ◽  
Vol 31 (3) ◽  
pp. 401-411
Author(s):  
Christine Bycroft
Keyword(s):  
New Zealand ◽  
Administrative Data ◽  
Population Register

scholarly journals Linkage of Census and Administrative Data to Quality Assure the 2011 Census for England and Wales

2015 ◽  
Vol 31 (3) ◽  
pp. 453-473 ◽  
Author(s):  
Louisa Blackwell ◽  
Andrew Charlesworth ◽  
Nicola Jane Rogers
Keyword(s):  
Quality Assurance ◽  
National Health Service ◽  
Health Service ◽  
Administrative Data ◽  
Record Linkage ◽  
Population Register ◽  
England And Wales ◽  
Quality Assurance Process ◽  
Assurance Process

Abstract The 2011 Census for England and Wales made extensive use of administrative data to quality assure the estimates. This included record linkage between census and administrative data. This article describes the role of record linkage in the quality-assurance process. It outlines the operational challenges that we faced and how we resolved them. Record linkage was confined to a sample within 58 carefully selected local authorities. We found characteristic patterns of under- and overcoverage in the National Health Service Patient Register, which we illustrate here with examples. Our findings may be useful in countries that, like England and Wales, do not have a comprehensive population register to draw on and that need to understand issues of coverage in their routinely collected administrative data and the use of these data to estimate populations.

scholarly journals How to use administrative data for surgical outcomes in acute diverticulitis

2016 ◽  
Vol 1 (1) ◽  
pp. 15 ◽  
Author(s):  
Michael K-Y Hong ◽  
Anita R Skandarajah ◽  
Omar D Faiz ◽  
Ian P Hayes
Keyword(s):  
New Zealand ◽  
Administrative Data ◽  
Surgical Outcomes ◽  
Acute Diverticulitis ◽  
Complicated Diverticulitis ◽  
Administrative Database ◽  
Coding System ◽  
Diverticular Bleeding ◽  
Predictive Values ◽  
Uncomplicated Diverticulitis

<p>The measurement of quality outcomes is crucial in surgical care. Administrative data are increasingly used but their ability to provide clinically useful information is reliant on how closely the coding can define a particular cohort.        In acute admissions for diverticular disease, it is important to differentiate between complicated and uncomplicated diverticulitis, and between diverticulitis and diverticular bleeding. We aim to develop a method to define clinically relevant cohorts of patients from an administrative database in acute diverticulitis. Codes for acute diverticulitis were found from the ICD-10-AM (Australia and New Zealand) coding system, and the accuracy was established with retrospective chart review and cross-referenced with a clinical database at a single institution. Coding of non-diverticular and missed diverticular  cases was examined to determine non-diverticular codes that could differentiate these cases. These were combined into  logic algorithms designed to differentiate between uncomplicated and complicated diverticulitis admissions derived from   an administrative database. Specific K57 diverticular codes possessed sensitivity and positive predictive values of 0.92    and 0.69 for uncomplicated diverticulitis, respectively, with 0.61 and 0.92 for complicated diverticulitis, respectively, based on 153 cases. Most of the missing cases were usually complicated diverticulitis whilst some cases coded incorrectly  as uncomplicated diverticulitis were often found as undifferentiated abdominal pain. Diagnostic codes combined into algorithms that accounted for predictable variations improved cohort definition. In conclusion, algorithms with combined codes improved definitions of clinically relevant cohorts for acute diverticulitis from an Australian or New Zealand administrative database. This method may be used to develop logic algorithms for other surgical conditions and enable widespread measurement of relevant surgical outcomes.</p>

scholarly journals A Bayesian Approach to Population Estimation with Administrative Data

2015 ◽  
Vol 31 (3) ◽  
pp. 475-487 ◽  
Author(s):  
John R. Bryant ◽  
Patrick Graham
Keyword(s):  
New Zealand ◽  
Administrative Data ◽  
Bayesian Approach ◽  
Model Building ◽  
Population Estimation ◽  
Data Sources ◽  
Population Estimates ◽  
Building Process ◽  
Coverage Rates ◽  
Model Building Process

Abstract The article describes a Bayesian approach to deriving population estimates from multiple administrative data sources. Coverage rates play an important role in the approach: identifying anomalies in coverage rates is a key step in the model-building process, and data sources receive more weight within the model if their coverage rates are more consistent. Random variation in population processes and measurement processes is dealt with naturally within the model, and all outputs come with measures of uncertainty. The model is applied to the problem of estimating regional populations in New Zealand. The New Zealand example illustrates the continuing importance of coverage surveys.

scholarly journals The enrolment gap: who is not enrolling with primary health organizations in Aotearoa New Zealand and what are the implications? An exploration of 2015–2019 administrative data

2021 ◽  
Author(s):  
Maite Irurzun-Lopez ◽  
Mona Jeffreys ◽  
Jacqueline Cumming
Keyword(s):  
Health Care ◽  
New Zealand ◽  
Administrative Data ◽  
District Health ◽  
Health Organizations ◽  
Equity In Health ◽  
Demographic Groups ◽  
Aotearoa New Zealand ◽  
Primary Health ◽  
Equity In Health Care

Abstract Background Primary Health Care (PHC) is the entry point to accessing health services in many countries. Having a high proportion of the population enrolled with a PHC provider is key to ensuring PHC fulfils this role and that it contributes to achieving better equity in health. We aimed to understand the extent to which people in Aotearoa New Zealand are enrolling with Primary Health Organizations (PHOs), how enrolment rates have evolved over time, and variations across District Health Boards (DHBs) and socio-demographic groups. Methods We analysed administrative data on the proportion of people enrolled in PHOs and breakdowns across DHBs, and by age, ethnicity and deprivation, for the years 2015–2019. Results About 6% of the population was not enrolled in 2019. There are persistent differences across socio-demographic groups as well as geographically. Māori have lower enrolment rates than New Zealand European/Other groups. Young people (15–24 years) are the least likely to be enrolled. The most affluent areas have the highest enrolment rates. Auckland DHB shows the lowest enrolment rates. Conclusions Enrolments remain below full population coverage and inequities exist between socio-demographic and geographic groups. Potential reasons explaining these trends include methodological limitations as well as real issues in accessing services. We recommend (a) work towards minimising data issues in relation to this indicator to improve its accuracy and value in signalling trends in access to PHC services, and (b) investigating the reasons for the potential widening of the inequities identified, in particular issues preventing Māori and younger people from enrolling. This study deepens our understanding of enrolment rates as an indicator for tracking equity in PHC. Other countries can learn from the Aotearoa New Zealand case to draw lessons for improving equity in health care.

scholarly journals Measuring patient safety in New Zealand public hospitals

2021 ◽  
Author(s):  
◽  
Nicholas Bowden
Keyword(s):  
Patient Safety ◽  
Quality Of Care ◽  
New Zealand ◽  
Administrative Data ◽  
Risk Adjustment ◽  
Public Hospitals ◽  
Hospital Administrative ◽  
The Impact ◽  
Hospital Administrative Data

<p>In New Zealand the Ministry of Health recognises quality of care as an integral part of a high performing health system and identifies patient safety as one of the key dimensions of quality. Over recent years a greater emphasis has been placed on improving patient safety mostly as a result of increased awareness around the frequency of medical error and resulting economic cost. However tools used to measure patient safety are limited. In particular the use of hospital administrative data to measure patient safety is scarce and existing safety measures often ignore one of the major issues confronting comparative analyses of hospital safety, risk adjustment to control for the differences in populations hospitals serve.   The objective of this research is to develop comparable measures of patient safety for New Zealand public hospitals. It uses risk adjustment strategies applied to the Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) with New Zealand hospital administrative data, the National Minimum Dataset 2001 to 2009. The research employs econometric techniques to address risk adjustment of the PSIs, utilising existing AHRQ models but adapting and re-estimating them with New Zealand administrative data.   The findings from the research indicate that to use the AHRQ PSIs as measures of hospital patient safety in New Zealand, risk adjustment should first be employed to ensure measures are comparable across hospitals and over time. Overall, although the impact of risk adjustment appears to be minor, it has relevance and this should be recognised. Relative hospital performance is affected by risk adjustment. In particular, it has the greatest impact on those hospitals with poor rankings. The research takes us a step closer to being able to confidently measure patient safety and quality of care in New Zealand public hospitals in an innovative way.</p>

scholarly journals The enrolment gap: who is not enrolling with primary health organizations in Aotearoa New Zealand and what are the implications? An exploration of 2015-2019 administrative data

2020 ◽  
Author(s):  
Maite Irurzun-Lopez ◽  
Mona Jeffreys ◽  
Jacqueline Cumming
Keyword(s):  
Health Care ◽  
New Zealand ◽  
Administrative Data ◽  
District Health ◽  
Equity In Health ◽  
Demographic Groups ◽  
Aotearoa New Zealand ◽  
Primary Health ◽  
Time Variations ◽  
Equity In Health Care

Abstract Background - Primary Health Care (PHC) is the entry point to accessing health services in many countries. Having a high proportion of the population enrolled with a PHC provider is key to ensuring PHC fulfils this role and that it contributes to achieving better equity in health. We aimed to understand the extent to which people in Aotearoa New Zealand are enrolling with Primary Health Organisations (PHOs), how enrolment rates have evolved over time, variations across District Health Boards (DHBs), and socio-demographic groups.Methods - We analysed administrative data on the proportion of people enrolled in PHOs and breakdowns across DHBs, and by age, ethnicity and deprivation, for the years 2015-2019.Results - About 6% of the population was not enrolled in 2019. There are persistent differences across socio-demographic groups as well as geographically. Māori have lower enrolment rates than New Zealand European/Other groups. Young people (15-24 years) are the least likely to be enrolled. The most affluent areas have the highest enrolment rates. Auckland DHB shows the lowest enrolment rates.Conclusions - Enrolments remain below full population coverage and inequities exist between socio-demographic and geographic groups. Potential reasons explaining these trends include methodological limitations as well as real issues in accessing services. We recommend (a) work towards minimising data issues in relation to this indicator to improve its accuracy and value in signalling trends in access to PHC services, and (b) investigating the reasons for the potential widening of the inequities identified, in particular issues preventing Māori and younger people from enrolling. This study deepens our understanding of the enrolment system and its potential pitfalls specially in relation to equity. Other countries can learn from the Aotearoa New Zealand case to draw lessons for improving equity in health care.

scholarly journals Impact of improved insulation and heating on mortality risk of older cohort members with prior cardiovascular or respiratory hospitalisations

BMJ Open ◽  
2017 ◽  
Vol 7 (11) ◽  
pp. e018079 ◽  
Author(s):  
Nicholas Preval ◽  
Michael Keall ◽  
Lucy Telfar-Barnard ◽  
Arthur Grimes ◽  
Philippa Howden-Chapman
Keyword(s):  
New Zealand ◽  
Protective Effect ◽  
Administrative Data ◽  
Secondary Outcome ◽  
Control Group ◽  
Study Cohort ◽  
All Cause Mortality ◽  
Related Hospitalisation ◽  
Icd 10 ◽  
Group Members

ObjectivesWe carried out an evaluation of a large-scale New Zealand retrofit programme using administrative data that provided the statistical power to assess the effect of insulation and/or heating retrofits on cardiovascular and respiratory-related mortality in people aged 65 and over with prior respiratory or circulatory hospitalisations.DesignQuasi-experimental cohort study based on administrative data.SettingNew Zealand.ParticipantsFrom a larger study cohort of over 900 000 people, we selected two subcohorts: 3287 people who were aged 65 and over and had experienced pretreatment period cardiovascular-related hospitalisation (ICD-10 chapter 9), and 1561 people aged 65 and over who had experienced pretreatment respiratory-related hospitalisation (ICD-10 chapter 10).InterventionsTreatment group individuals lived in a home that received insulation and/or heating retrofits under the Warm Up New Zealand: Heat Smart programme. Control group individuals lived in a home that was matched to a treatment home based on physical characteristics and location.Primary and secondary outcome measuresHR for all-cause mortality for treatment with insulation, heating, or insulation and heating relative to control group.ResultsPeople with pretreatment circulatory hospitalisation who occupied a household that received only insulation had an HR for all-cause mortality of 0.673 (95% CI 0.535 to 0.847) (p<0.001) relative to control group members. Individuals with a pretreatment respiratory hospitalisation who occupied a household that received only an insulation retrofit had an HR for all-cause mortality of 0.830 (95% CI 0.655 to 1.051) (p=0.122) relative to control group members. There was no evidence of an additional benefit from receiving heating.ConclusionsWe interpret the hazard rate observed for cardiovascular subcohort individuals who received insulation as evidence of a protective effect, reducing the risk of mortality for vulnerable older adults. There is suggestive evidence of a protective effect of insulation for the respiratory subcohort.

scholarly journals The enrolment gap: who is not enrolling with primary health organizations in Aotearoa New Zealand and what are the implications? An exploration of 2015–2019 administrative data

2021 ◽  
Author(s):  
Maite Irurzun-Lopez ◽  
Mona Jeffreys ◽  
Jacqueline Cumming
Keyword(s):  
Health Care ◽  
New Zealand ◽  
Administrative Data ◽  
District Health ◽  
Health Organizations ◽  
Equity In Health ◽  
Demographic Groups ◽  
Aotearoa New Zealand ◽  
Primary Health ◽  
Equity In Health Care

Abstract Background Primary Health Care (PHC) is the entry point to accessing health services in many countries. Having a high proportion of the population enrolled with a PHC provider is key to ensuring PHC fulfils this role and that it contributes to achieving better equity in health. We aimed to understand the extent to which people in Aotearoa New Zealand are enrolling with Primary Health Organizations (PHOs), how enrolment rates have evolved over time, and variations across District Health Boards (DHBs) and socio-demographic groups. Methods We analysed administrative data on the proportion of people enrolled in PHOs and breakdowns across DHBs, and by age, ethnicity and deprivation, for the years 2015–2019. Results About 6% of the population was not enrolled in 2019. There are persistent differences across socio-demographic groups as well as geographically. Māori have lower enrolment rates than New Zealand European/Other groups. Young people (15–24 years) are the least likely to be enrolled. The most affluent areas have the highest enrolment rates. Auckland DHB shows the lowest enrolment rates. Conclusions Enrolments remain below full population coverage and inequities exist between socio-demographic and geographic groups. Potential reasons explaining these trends include methodological limitations as well as real issues in accessing services. We recommend (a) work towards minimising data issues in relation to this indicator to improve its accuracy and value in signalling trends in access to PHC services, and (b) investigating the reasons for the potential widening of the inequities identified, in particular issues preventing Māori and younger people from enrolling. This study deepens our understanding of enrolment rates as an indicator for tracking equity in PHC. Other countries can learn from the Aotearoa New Zealand case to draw lessons for improving equity in health care.

scholarly journals Measuring Job Tenure Using Linked Employer-Employee Data

1970 ◽  
Author(s):  
Tas Papadopoulos
Keyword(s):  
New Zealand ◽  
Administrative Data ◽  
Job Tenure ◽  
Monthly Data ◽  
The Past ◽  
Key Issues ◽  
New Statistics ◽  
The Impact ◽  
Source Of Information ◽  
Employee Data

The publication of job tenure statistics from Statistics New Zealand's Linked Employer-Employee Dataset (LEED) in 2006 provided the first comprehensive source of information in this area for New Zealand. The most noteworthy aspect of the new statistics was the high number of jobs with short tenure. LEED job tenure statistics are constructed from administrative data that is collected for tax, not statistical, purposes. For this reason, Statistics NZ has had to address a number of issues before determining the appropriate methodology to measure job tenure. Two key issues were: (1) How breaks in job tenure are best identified from monthly data. (2) How to best correct for administrative chum in the dataset. This paper looks at the impact on the level o f short-tenured jobs when varying the treatment o f these two issues and the appropriateness of doing so. Consequently, if also explores the challenges of deriving longitudinal statistics from administrative data. This work is part of a review of LEED methods and outputs that Statistics NZ has been undertaking over the past year.

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