Primary care redesign: A simulation study at a pediatric clinic

ABSTRACT BackgroundEthnicity is an important factor to be considered in health research because of its association with inequality in disease prevalence and the utilisation of healthcare. Ethnicity recording has been incorporated in primary care electronic health records, and hence is available in large UK primary care databases such as The Health Improvement Network (THIN). However, since primary care data are routinely collected for clinical purposes, a large amount of data that are relevant for research including ethnicity is often missing. A popular approach for missing data is multiple imputation (MI). However, the conventional MI method assuming data are missing at random does not give plausible estimates of the ethnicity distribution in THIN compared to the general UK population. This might be due to the fact that ethnicity data in primary care are likely to be missing not at random. ObjectivesI propose a new MI method, termed ‘weighted multiple imputation’, to deal with data that are missing not at random in categorical variables.MethodsWeighted MI combines MI and probability weights which are calculated using external data sources. Census summary statistics for ethnicity can be used to form weights in weighted MI such that the correct marginal ethnic breakdown is recovered in THIN. I conducted a simulation study to examine weighted MI when ethnicity data are missing not at random. In this simulation study which resembled a THIN dataset, ethnicity was an independent variable in a survival model alongside other covariates. Weighted MI was compared to the conventional MI and other traditional missing data methods including complete case analysis and single imputation.ResultsWhile a small bias was still present in ethnicity coefficient estimates under weighted MI, it was less severe compared to MI assuming missing at random. Complete case analysis and single imputation were inadequate to handle data that are missing not at random in ethnicity.ConclusionsAlthough not a total cure, weighted MI represents a pragmatic approach that has potential applications not only in ethnicity but also in other incomplete categorical health indicators in electronic health records.

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Student Education in a University-Based General Pediatric Clinic

PEDIATRICS ◽

10.1542/peds.54.3.384b ◽

1974 ◽

Vol 54 (3) ◽

pp. 384-385

Author(s):

Jay E. Berkelhamer ◽

Janis Mendelsohn ◽

John D. Madden

Keyword(s):

Primary Care ◽

Child Care ◽

Medical Students ◽

Care Facility ◽

University Of Chicago ◽

Primary Care Facility ◽

Well Child Care ◽

Pediatric Clinic ◽

The Subject ◽

The University

Since effective education of medical students in general pediatric clinics has been the subject of much review lately,1-6 a survey of the General Pediatric Clinic of the University of Chicago was conducted. Medical students and patients appeared to be satisfied with their experience in our clinic. The clinic is a primary care facility where patients are seen on a nonreferral basis. Approximately 70% of the 12,000 patient visits per year are for continuous well child care.

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GP- and practice-related variation in ambulatory sensitive hospitalisations of older primary care patients

BMC Family Practice ◽

10.1186/s12875-020-01285-9 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Leah Palapar ◽

Laura Wilkinson-Meyers ◽

Thomas Lumley ◽

Ngaire Kerse

Keyword(s):

Primary Care ◽

New Zealand ◽

Older People ◽

Home Visiting ◽

Controlled Trial ◽

Community Dwelling ◽

Trial Registration ◽

Primary Care Redesign ◽

Practice Level ◽

Practice Characteristics

Abstract Background Reducing ambulatory sensitive hospitalisations (ASHs) is a strategy to control spending on hospital care and to improve quality of primary health care. This research investigated whether ASH rates in older people varied by GP and practice characteristics. Methods We identified ASHs from the national dataset of hospital events for 3755 community-dwelling participants aged 75+ enrolled in a cluster randomised controlled trial involving 60 randomly selected general practices in three regions in New Zealand. Poisson mixed models of 36-month ASH rates were fitted for the entire sample, for complex participants, and non-complex participants. We examined variation in ASH rates according to GP- and practice-level characteristics after adjusting for patient-level predictors of ASH. Results Lower rates of ASHs were observed in female GPs (IRR 0.83, CI 0.71 to 0.98). In non-complex participants, but not complex participants, practices in more deprived areas had lower ASH rates (4% lower per deprivation decile higher, IRR 0.96, CI 0.92 to 1.00), whereas main urban centre practices had higher rates (IRR 1.84, CI 1.15 to 2.96). Variance explained by these significant factors was small (0.4% of total variance for GP sex, 0.2% for deprivation, and 0.5% for area type). None of the modifiable practice-level characteristics such as home visiting and systematically contacting patients were significantly associated with ASH rates. Conclusions Only a few GP and non-modifiable practice characteristics were associated with variation in ASH rates in 60 New Zealand practices interested in a trial about care of older people. Where there were significant associations, the contribution to overall variance was minimal. It also remains unclear whether lower ASH rates in older people represents underservicing or less overuse of hospital services, particularly for the relatively well patient attending practices in less central, more disadvantaged communities. Thus, reducing ASHs through primary care redesign for older people should be approached carefully. Trial registration Australian and New Zealand Clinical Trials Register ACTRN12609000648224.

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