Governance and oversight of researcher access to electronic health data: the role of the Independent Scientific Advisory Committee for MHRA database research, 2006-2015

Lumos: a statewide linkage programme in Australia integrating general practice data to guide system redesign

Objective

With ageing of the Australian population, more people are living longer and experiencing chronic or complex health conditions. The challenge is to have information that supports the integration of services across the continuum of settings and providers, to deliver person-centred, seamless, efficient and effective healthcare. However, in Australia, data are typically siloed within health settings, precluding a comprehensive view of patient journeys. Here, we describe the establishment of the Lumos programme—the first statewide linked data asset across primary care and other settings in Australia and evaluate its representativeness to the census population.

Methods and analysis

Records extracted from general practices throughout New South Wales (NSW), Australia’s most populous state, were linked to patient records from acute and other settings. Innovative privacy and security technologies were employed to facilitate ongoing and regular updates. The marginal demographic distributions of the Lumos cohort were compared with the NSW census population by calculating multiple measures of representation to evaluate its generalisability.

Results

The first Lumos programme data extraction linked 1.3 million patients’ general practice records to other NSW health system data. This represented 16% of the NSW population. The demographic distribution of patients in Lumos was >95% aligned to that of the NSW population in the calculated measures of representativeness.

Conclusion

The Lumos programme delivers an enduring, regularly updated data resource, providing unique insights about statewide, cross-setting healthcare utilisation. General practice patients represented in the Lumos data asset are representative of the NSW population overall. Lumos data can reliably be used to identify at-risk regions and groups, to guide the planning and design of health services and to monitor their impact throughout NSW.

The effect of pre-diagnostic vitamin D supplementation on cancer survival in women: a cohort study within the UK Clinical Practice Research Datalink

BACKGROUND

There remains uncertainty in whether vitamin D status affects cancer survival. We investigated whether vitamin D (± calcium) supplementation affects cancer survival in women.

METHODS

Participants were women aged ≥55 years identified from the UK Clinical Practice Research Datalink (CPRD) with a first diagnosis of breast, colorectal, lung, ovarian or uterine cancer between 2002 and 2009, and at least 5 years of CPRD data prior to diagnosis. Cox proportional hazards were used to estimate hazard ratios (HR) and 95 % confidence intervals (CI) of the relationship between pre-diagnostic vitamin D supplementation and all-cause mortality. To avoid confounding by indication, the primary analysis compared women with 3+ to 1-2 (but no more) vitamin D prescriptions. Models were adjusted for pre-diagnostic body mass index, smoking, alcohol and deprivation. A sensitivity analysis excluded supplements prescribed in the year prior to diagnosis.

RESULTS

Exposure to 3 or more versus 1 to 2 prescriptions of vitamin D was not associated with survival from any of the cancers studied. Any vitamin D prescription, compared to never having been prescribed one, was associated with a better survival from breast cancer (HR 0.78, 95 % CI 0.70 to 0.88). The sensitivity analysis suggested a possible detrimental effect of vitamin D supplementation on lung cancer outcomes (HR for 3 versus 1 or 2 prescriptions 1.22 (95 % CI 0.94 to 1.57); HR for any versus no prescriptions 1.09 (0.98 to 1.22)).

CONCLUSIONS

We found no evidence that vitamin D supplementation is associated with survival among women with cancer. Previous observational findings of beneficial effects of vitamin D supplementation on cancer survival may be confounded.