Health and care data: approaches to data linkage for evidence-informed policy

An indispensable prerequisite for answering research questions in health services research is the availability and accessibility of comprehensive, high quality data. It can be assumed that health services research in the comingyears will be increasingly based on data linkage, i.e., the linking, or connecting, of several data sources based on suitable common key variables. A range of approaches to data collection, storage, linkage and availability exists across countries, particularly for secondary research purposes (i.e., the use of data initially collected for other purposes), such as health systems research. The main goal of this review is to develop an overview of, and gain insights into, current approaches to linking data sources in the context of health services research, with the view to inform policy, based on existing practices in high-income countries in Europe and beyond. In doing so, another objective is to provide lessons for countries looking for possible or alternative approaches to data linkage. Thirteen country case studies of data linkage approaches were selected and analyzed. Rather than being comprehensive, this review aimed to identify varied and potentially useful case studies to showcase different approaches to data linkage worldwide. A conceptual framework was developed to guide the selection and description of case studies. Information was first identified and collected from publicly available sources and a profile was then created for each country and each case study; these profiles were forwarded to appropriate country experts for validation and completion.

Understanding disparities in post-operative mortality for Indigenous patients.

There is an urgent need for high-quality evidence regarding post-operative mortality among Indigenous peoples. Our group recently published a national audit of 4,000,000 procedures conducted between 2005-2017, which identified considerable disparities in post-operative mortality between Indigenous Maori and non-Indigenous New Zealanders. Understanding the primary drivers of these disparities-for Maori, but likely also other Indigenous populations worldwide-requires us to consider the multiple levels at which these drivers might arise. To that end, in this paper we breakdown these drivers in detail, conceptualising these drivers as operating in layers with each factor leading to the next. These layers include structural factors, care system factors, care process factors, care team factors and patient factors. Each of these factors are presented within a framework that can be used to begin to understand them - with a view to rousing action and inspiring intervention to address inequities in post-operative outcomes experienced by Indigenous peoples.

Regional variation in post-operative mortality in New Zealand.

BACKGROUND: There is a growing body of evidence that access to best practice perioperative care varies within our population. In this study, we use national-level data to begin to address gaps in our understanding of regional variation in post-operative outcomes within New Zealand. METHODS: Using National Collections data, we examined all inpatient procedures in New Zealand public hospitals between 2005 and 2017 (859 171 acute, 2 276 986 elective/waiting list), and identified deaths within 30 days. We calculated crude and adjusted rates per 100 procedures for the 20 district health boards (DHBs), both for the total population and stratified by ethnicity (Maori/European). Odds ratios comparing the risk of post-operative mortality between Maori and European patients were calculated using crude and adjusted Poisson regression models. RESULTS: We observed regional variations in post-operative mortality outcomes. Maori, compared to European, patients experienced higher post-operative mortality rates in several DHBs, with a trend to higher mortality in almost all DHBs. Regional variation in patterns of age, procedure, deprivation and comorbidity (in particular) largely drives regional variation in post-operative mortality, although variation persists in some regions even after adjusting for these factors. Inequitable outcomes for Maori also persist in several regions despite adjustment for multiple factors, particularly in the elective setting. CONCLUSIONS: The persistence of variation and ethnic disparities in spite of adjustment for confounding and mediating factors suggests that multiple regions require additional resource and support to improve outcomes. Efforts to reduce variation and improve outcomes for patients will require both central planning and monitoring, as well as region-specific intervention.

Disparities in post-operative mortality between Maori and non-Indigenous ethnic groups in New Zealand.

AIM: To describe disparities in post-operative mortality experienced by Indigenous Maori compared to non-Indigenous New Zealanders. METHODS: We completed a national study of all those undergoing a surgical procedure between 2005 and 2017 in New Zealand. We examined 30-day and 90-day post-operative mortality for all surgical specialties and by common procedures. We compared age-standardised rates between ethnic groups (Maori, Pacific, Asian, European, MELAA/Other) and calculated hazard ratios (HRs) using Cox proportional hazards regression modelling adjusted for age, sex, deprivation, rurality, comorbidity, ASA score, anaesthetic type, procedure risk and procedure specialty. RESULTS: From nearly 3.9 million surgical procedures (876,976 acute, 2,990,726 elective/waiting list), we observed ethnic disparities in post-operative mortality across procedures, with the largest disparities occurring between Maori and Europeans. Maori had higher rates of 30- and 90-day post-operative mortality across most broad procedure categories, with the disparity between Maori and Europeans strongest for elective/waiting list procedures (eg, elective/waiting list musculoskeletal procedures, 30-day mortality: adj. HR 1.93, 95% CI 1.56-2.39). CONCLUSIONS: The disparities we observed are likely driven by a combination of healthcare system, process and clinical team factors, and we have presented the key mechanisms within these factors.

Assessment of Variation in Electronic Health Record Capabilities and Reported Clinical Quality Performance in Ambulatory Care Clinics, 2014-2017.

Importance: Electronic health records (EHRs) are widely promoted to improve the quality of health care, but information about the association of multifunctional EHRs with broad measures of quality in ambulatory settings is scarce. Objective: To assess the association between EHRs with different degrees of capabilities and publicly reported ambulatory quality measures in at least 3 clinical domains of care. Design, Setting, and Participants: This cross-sectional and longitudinal study was conducted using survey responses from 1141 ambulatory clinics in Minnesota, Washington, and Wisconsin affiliated with a health system that responded to the Healthcare Information and Management Systems Society Annual Survey and reported performance measures in 2014 to 2017. Statistical analysis was performed from July 10, 2019, through February 26, 2021. Main Outcomes and Measures: A composite measure of EHR capability that considered 50 EHR capabilities in 7 functional domains, grouped into the following ordered categories: no functional EHR, EHR underuser, EHR, neither underuser or superuser, EHR superuser; as well as a standardized composite of ambulatory clinical performance measures that included 3 to 25 individual measures (median, 13 individual measures). Results: In 2014, 381 of 746 clinics (51%) were EHR superusers; this proportion increased in each subsequent year (457 of 846 clinics [54%] in 2015, 510 of 881 clinics [58%] in 2016, and 566 of 932 clinics [61%] in 2017). In each cross-sectional analysis year, EHR superusers had better clinical quality performance than other clinics (adjusted difference in score: 0.39 [95% CI, 0.12-0.65] in 2014; 0.29 [95% CI, -0.01 to 0.59] in 2015; 0.26 [95% CI, -0.05 to 0.56] in 2016; and 0.20 [95% CI, -0.04 to 0.45] in 2017). This difference in scores translates into an approximately 9% difference in a clinic's rank order in clinical quality. In longitudinal analyses, clinics that progressed to EHR superuser status had only slightly better gains in clinical quality between 2014 and 2017 compared with the gains in clinical quality of clinics that were static in terms of their EHR status (0.10 [95% CI, -0.13 to 0.32]). In an exploratory analysis, different types of EHR capability progressions had different degrees of associated improvements in ambulatory clinical quality (eg, progression from no functional EHR to a status short of superuser, 0.06 [95% CI, -0.40 to 0.52]; progression from EHR underuser to EHR superuser, 0.18 [95% CI, -0.14 to 0.50]). Conclusions and Relevance: Between 2014 and 2017, ambulatory clinics in Minnesota, Washington, and Wisconsin with EHRs having greater capabilities had better composite measures of clinical quality than other clinics, but clinics that gained EHR capabilities during this time had smaller increases in clinical quality that were not statistically significant.

The Electronic Health Record and Health IT to Decrease Racial/Ethnic Disparities in Care.

The Electronic Health Record (EHR) now has high penetration in both ambulatory and hospital care. How can this technology be utilized to reduce racial and ethnic disparities in health care quality? We suggest a three-step process. First, routinely obtain accurate, detailed, and complete race and ethnicity data. Second, use these data to identify and monitor inequities in care, and explore the contributing factors. The third and most important step, is to employ the power of the EHR and its associated digital tools for interventions to actively reduce the extent of these disparities.

Diabetes associated with early labor-force exit: a comparison of sixteen high-income countries.

The economic burden of diabetes and the effects of the disease on the labor force are of substantial importance to policy makers. We examined the impact of diabetes on leaving the labor force across sixteen countries, using data about 66,542 participants in the Survey of Health, Ageing and Retirement in Europe; the US Health and Retirement Survey; or the English Longitudinal Study of Ageing. After matching people with diabetes to those without the disease in terms of age, sex, and years of education, we used Cox proportional hazards analyses to estimate the effect of diabetes on time of leaving the labor force. Across the sixteen countries, people diagnosed with diabetes had a 30 percent increase in the rate of labor-force exit, compared to people without the disease. The costs associated with earlier labor-force exit are likely to be substantial. These findings further support the value of greater public- and private-sector investment in preventing and managing diabetes.

The mismeasurement of quality by readmission rate: how blunt is too blunt an instrument?: a quantitative bias analysis.

BACKGROUND: The rate of readmission is widely used as a measure of hospital quality of care, often with funding implications for outlying facilities. OBJECTIVES: This study explored the plausibility of readmission as a proxy for health care quality with quantitative bias analysis and the application of a structural Directed Acyclic Graph framework. It applies this paradigm to observed ethnic differences in the odds of readmission in a sample of New Zealand hospital patients. RESEARCH DESIGN: Ethnicity was defined as the exposure, readmission rate as the proxy outcome, and quality of care as a missing mediator. Using data from 89,090 surgical patients from New Zealand, and estimates from the literature of the prevalence of "poor quality" and the strength of the quality-of-care readmission association, a series of sensitivity analyses were performed to calculate an odds ratio of the ethnicity-readmission association corrected for the missing mediator "quality." RESULTS: Given the assumptions applied, potentially only 29% of the excess odds of readmission for Maori compared with Europeans were due to poor quality of care. CONCLUSIONS: This investigation finds substantial error when using readmission as a marker of quality, and suggests that differences in readmission between populations are more likely to be due to factors other than quality of care.

Ethnic disparities in the quality of hospital care in New Zealand, as measured by 30-day rate of unplanned readmission/death.

OBJECTIVE: To compare the quality of hospital care for New Zealand (NZ) Maori and NZ European adult patients, using the rate of unplanned readmission or death within 30 days of discharge as an indicator of quality. DESIGN: Retrospective cohort study. SETTING: NZ public hospitals. PARTICIPANTS: Data from 89 658 patients who were admitted for one of a defined set of surgical procedures at NZ public hospitals 2002-8 were obtained from the NZ Ministry of Health. Outcome The odds of readmission for NZ Maori when compared with NZ European patients were calculated using logistic regression, incorporating variables for age, sex, comorbidity, index procedure, hospital volume and socioeconomic position. RESULTS: NZ Maori had 16% higher odds of readmission or death when compared with NZ European patients (OR = 1.16; 95% CI 1.08-1.24) after adjusting for all covariates. Readmission or death was also associated with being female (OR = 1.09; 1.03-1.15), older age (OR = 1.33; 1.19-1.48, for >79 years compared with 18-39 years), higher comorbidity (OR = 2.08; 1.89-2.31, for Charlson score 3+ compared with 0) and higher hospital volume (OR = 0.81; 0.76-0.86, for lowest volume compared with highest). CONCLUSIONS: This study suggests ethnic disparities in the quality of hospital care in NZ using unplanned readmission rate as an indicator of quality. There are well-documented differences in health outcomes between Maori and NZ Europeans, and it is possible that differential treatment within the health system contributes to these health status inequalities.

Not in my hospital? Ethnic disparities in quality of hospital care in New Zealand: a narrative review of the evidence.

There are well-documented differences in health outcomes between Maori and New Zealand Europeans, some of which persist despite adjustment or control for socioeconomic status and demographic variables. Lalonde defined the health system as being a determinant of health: is it possible that the services that are designed to improve health and well-being may be contributing to the ethnic health disparities in New Zealand? This narrative review studied the evidence for disparities in the quality of public hospital care for Maori and non-Maori in New Zealand. Medline and Embase databases were employed to identify studies assessing quality of care within the New Zealand hospital setting, with the analysis of ethnic groups. The studies obtained from the search were few and varied, using an array of indicators and assessing multiple discrete clinical conditions. Investigators also exhibited differing levels of commitment to the consideration of potential confounding factors. However, there is robust evidence for the existence of healthcare disparities for Maori, in particular related to obstetric intervention and the incidence of potentially avoidable adverse events.