Toward Rigorous Data Harmonization in Cancer Epidemiology Research: One Approach.

Cancer epidemiologists have a long history of combining data sets in pooled analyses, often harmonizing heterogeneous data from multiple studies into 1 large data set. Although there are useful websites on data harmonization with recommendations and support, there is little research on best practices in data harmonization; each project conducts harmonization according to its own internal standards. The field would be greatly served by charting the process of data harmonization to enhance the quality of the harmonized data. Here, we describe the data harmonization process utilized at the Fred Hutchinson Cancer Research Center (Seattle, Washington) by the coordinating centers of several research projects. We describe a 6-step harmonization process, including: 1) identification of questions the harmonized data set is required to answer; 2) identification of high-level data concepts to answer those questions; 3) assessment of data availability for data concepts; 4) development of common data elements for each data concept; 5) mapping and transformation of individual data points to common data elements; and 6) quality-control procedures. Our aim here is not to claim a "correct" way of doing data harmonization but to encourage others to describe their processes in order that we can begin to create rigorous approaches. We also propose a research agenda around this issue.

Ophthalmic digital image transfer: benefits to triage, patient care and resource.

PURPOSE: Hospital capacity in the UK is currently significantly challenged due to new treatments, targets and resource limitations. There have been significant improvements in training, equipment and shared care services in community primary care optometry services. Despite this the challenges to ophthalmic service delivery are considerable. One area of potential benefit is the effect on outcome when a clinical image is attached to a referral. We aimed to quantify the effect of attaching digital images to ophthalmic referrals. METHODS: Retrospective analysis of 358 consecutive optometry referrals to the Hospital Eye Service in Dunfermline, Scotland using electronic referral with digital images. All images were screened by consultant ophthalmologists. RESULTS: The patients were aged between 9 and 100 years (mean age 63.6 years). Sixty four (18%) referrals were deemed urgent (requiring appointment within 24-60 h), with the majority, 28 (8%) being wet macular degeneration. One hundred and seventy (48%) were deemed routine (appointment within 2-6 weeks), with categories including macular disease, glaucoma, cataract, optic disc and retinal abnormalities. Twenty seven (8%) patients were already attending the hospital eye service, or had been referred previously for the same condition. Categories were mainly glaucoma, diabetic retinopathy and cataract. Ninety-five (25%) were 'e-diagnosed' based on image and referral information (i.e. with no secondary eye care appointment). Diagnosis included glaucoma suspect (22, 6%), macular pathology (12, 3%), abnormal looking discs (9, 2.5%) and cataract (9, 2.5%). The overall 'did not attend' rate for those patients seen in the hospital eye service (254) was <1% (two patients). CONCLUSIONS: The attachment of digital images improved the quality of referral triaging from optometry to secondary eye care in the hospital eye service. It allowed detection of sight threatening disease early and more appropriate allocation of patients to specific specialist clinics at first visit. They allowed safe and speedy 'e-diagnosis' of a subgroup, saving hospital capacity and minimising patient inconvenience. Indirectly the service also reduced the 'did not attend' rate. With recent improvements in camera and internet technology digital images will have an ever increasing role in secondary eye care as it continues to adapt to meet modern demands.