Methods for Measuring the Time of Transfer from Pediatric to Adult Care for Chronic Conditions Using Administrative Data: A Scoping Review

Figures & data

Figure 1 Flow diagram.

Table 1 Study Characteristics and Methods

First Author and Year of Publication	Location	Data Source	Disease Focus	Study Design	Methodology
Studies that define time of transfer based on last pediatric and first adult visits
Bollegala 2017^Citation21	Ontario, Canada	Population-based health administrative data	Inflammatory bowel disease (IBD)	Retrospective cohort	“pre-transfer”: 2 years before the last pediatric visit “transfer of care”: time between last pediatric visit and first adult visit occurring at age ≥18 “post-transfer”: time from the first adult visit onward for 2 years
Hale 2017^Citation22	England	Routine hospital administrative data	Diabetes	Retrospective cohort	“Successful transition” = any adult service contact within 6 months of last paediatric contact. “Successful retention” = first planned adult contact within 6 months of the last planned paediatric contact, and at least 2 further adult contacts within the next 2 years
Mannion 2016^Citation23	United States	National commercial insurance administrative claims database	Juvenile idiopathic arthritis (JIA)	Retrospective cohort	The first adult visit was defined as the transfer point; this resulted in 3 distinct intervals: pediatric, transfer, and adult
Wisk 2015^Citation24	United States	Harvard Pilgrim Health Care Claims Data	Children with chronic conditions and healthy children	Retrospective Cohort	Timing of transfer measured from 16 years to first adult-focused primary care provider visit Transfer date: date of first adult-focused primary care visit
Zhao 2018^Citation25	Ontario, Canada	Population-based health administrative data	Inflammatory bowel disease (IBD)	Retrospective cohort	Transfer period: time between first adult gastroenterologist visit and the last pediatric gastroenterologist visit.
Studies that defined time of transfer based on age
Blinder 2015^Citation26	United States	5 US State Medicaid databases	Sickle cell Disease	Retrospective cohort	18th birthday was defined as the age of transfer
Cohen 2016^Citation27	Ontario, Canada	Population-based health administrative data	Chronic health conditions	Retrospective cohort	18th birthday was defined as the age of transfer
Dickerson 2012^Citation28	United States	Administrative data from 25 children’s hospitals within the Pediatric Health Information System (PHIS),	Sickle cell disease	Retrospective cohort	18th birthday was defined as the age of transfer
Nakhla 2009^Citation13	Ontario, Canada	Population-based health administrative data	Diabetes	Retrospective cohort	18th birthday was defined as the age of transfer
Reilly 2017^Citation29	Sweden	Population-based Swedish Inpatient Register	Celiac Disease	Retrospective Cohort	Pre-transition age: 16–17 years Post-transition age:19–20 years
Shulman 2018^Citation15	Ontario, Canada	Population-based health administrative data	Diabetes	Retrospective cohort	Pre-transition age: 15–17 years Transition-age: 17–19 years Early adulthood: 19–26 years (end of study)
Singh 2019^Citation30	Wisconsin, United States	Medicaid Data	Sickle Cell Disease	Retrospective Cohort	Transition age: 19 years
Toulany 2019^Citation31	Ontario, Canada	Population-based health administrative data	Mental illness	Retrospective cohort	Pre-transition: 12–16 years During transition: 17–18 years After transition: 19–26 years
Wijlaars 2018^Citation32	England	Hospital Episode Statistics Admitted Patient Care data	Long-term conditions (LTCs) (defined using the International Classification of Diseases)	Cross-sectional study	Pre-transition (ages 10–15 years) and after transition (19–24 years)

Table 2 Approaches to Identifying the Timing of Transfer to Adult Care Within Health Administrative Data

Challenges of Identifying the Timing of Transfer to Adult Care	Methodological Approaches to Address Each Specific Challenge of Identifying the Time of Transfer
Identifying timing of transfer based on pediatric and adult visits	Define time of transfer based on the number and timing of pediatric and adult visit.^Citation22,Citation23,Citation25 Measure continuity of care after the initial adult visit.^Citation22 Use provider specialty codes from claims data to categorize providers as pediatric- or adult-focused providers.^Citation24 Set a minimum age at time of transfer to ensure that the transfer was due to age and not geographic relocation.^Citation23
Identifying the timing of transfer for individuals who have “shared care” ie a pediatric visit occurring after the first adult visit	Definition of a transfer period from the first adult visit to the final pediatric visit.^Citation25 Specify that individuals must have a pediatric visit followed by an adult visit and without a subsequent pediatric visit.^Citation23
Measuring disease onset, exposures, and outcomes relative to the timing of transfer	Use longitudinal data to capture diagnoses prior to transfer to ensure that the condition existed prior to receipt of adult care.^Citation32 Measure outcomes after a washout period that starts after the first adult visit.^Citation25 Measure exposures and outcomes immediately before and after a specific assumed date of transfer (eg, 18th birthday)^Citation13,Citation26-^Citation28 or a period of time within which transfer is assumed to occur.^Citation15,Citation29-^Citation31
Accounting for individuals who never successfully transfer to adult care	Create a comparator group, “lost to adult follow-up” for those who never have an adult visit within the study period.^Citation21
Other Limitations of Administrative Data	Methodological Approaches
Missing data: Physician and non-physician visits that may not be captured in administrative data sources Health services obtained by young adults who move away for post-secondary education	Recognize and acknowledge these potential missing data if applicable. If available, consider collecting from alternative data sources (eg, medical records or survey data).
Risk of selection bias caused by disease severity: Under-representation of adolescents with less severe disease who never see a pediatric provider but only ever see a family physician or an adult specialist	Adjust for unmeasured confounding factors such as disease severity by using a study design such as self-controlled case series (SCCS) design, in which patients act as their own controls.^Citation25
Non-comprehensive outcome data: Administrative data do not holistically capture the transition experience (eg, patient-report experience and outcome measures and social/educational/vocational outcomes)	Link to novel data sources such as community health surveys and employment data (via tax returns), for example.

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Zhao X, Bjerre LM, Nguyen GC, et al. Health services use during transition from pediatric to adult care for inflammatory bowel disease: a population-based study using health administrative data. J Pediatr. 2018;203:280–287.e284. doi:10.1016/j.jpeds.2018.08.02130266506

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