Evidence map›Paper›PMID 29145834›Full record

ArticleBMC health services research2017

Identification of outliers and positive deviants for healthcare improvement: looking for high performers in hypoglycemia safety in patients with diabetes.

Brigid Wilson, Chin-Lin Tseng, Orysya Soroka, Leonard M Pogach, David C Aron

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Article in BMC health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Brigid WilsonIIRECC - EUL 5M677, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Blvd., Cleveland, OH, 44106, USA.
Chin-Lin TsengDepartment of Veterans Affairs-New Jersey Healthcare System, East Orange, NJ, USA.
Orysya SorokaDepartment of Veterans Affairs-New Jersey Healthcare System, East Orange, NJ, USA.
Leonard M PogachDepartment of Veterans Affairs - Office of Specialty Care Services, Washington DC, USA.
David C AronIIRECC - EUL 5M677, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, 10701 East Blvd., Cleveland, OH, 44106, USA. david.aron@va.gov.

Funding

Glycemic Control: Overtreatment, Hypoglycemia, Mortality and De-IntensificationI01HX001601 · VA · VA NEW JERSEY HEALTH CARE SYSTEM · PI TSENG, CHIN-LIN · 2018 to 2020
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HSRD VA I01 HX001601va hsr&d IIR 11-077va hsr&d RRP-12-492va hsr&d SCE 12-181
6 · The paper itself

Abstract

backgroundThe study objectives were to determine: (1) how statistical outliers exhibiting low rates of diabetes overtreatment performed on a reciprocal measure - rates of diabetes undertreatment; and (2) the impact of different criteria on high performing outlier status.

methodsThe design was serial cross-sectional, using yearly Veterans Health Administration (VHA) administrative data (2009-2013). Our primary outcome measure was facility rate of HbA1c overtreatment of diabetes in patients at risk for hypoglycemia. Outlier status was assessed by using two approaches: calculating a facility outlier value within year, comparator group, and A1c threshold while incorporating at risk population sizes; and examining standardized model residuals across year and A1c threshold. Facilities with outlier values in the lowest decile for all years of data using more than one threshold and comparator or with time-averaged model residuals in the lowest decile for all A1c thresholds were considered high performing outliers.

resultsUsing outlier values, three of the 27 high performers from 2009 were also identified in 2010-2013 and considered outliers. There was only modest overlap between facilities identified as top performers based on three thresholds: A1c < 6%, A1c < 6.5%, and A1c < 7%. There was little effect of facility complexity or regional Veterans Integrated Service Networks (VISNs) on outlier identification. Consistent high performing facilities for overtreatment had higher rates of undertreatment (A1c > 9%) than VA average in the population of patients at high risk for hypoglycemia.

conclusionsStatistical identification of positive deviants for diabetes overtreatment was dependent upon the specific measures and approaches used. Moreover, because two facilities may arrive at the same results via very different pathways, it is important to consider that a "best" practice may actually reflect a separate "worst" practice.

Indexed as

Medical OverusePatient SafetyQuality ImprovementAdultAgedCross-Sectional StudiesDiabetes MellitusFemaleGlycated HemoglobinHospitals, VeteransHumansHypoglycemiaMaleMiddle AgedRisk FactorsUnited StatesGlycated Hemoglobinhemoglobin A1c protein, humanBest practicesDiabetesOvertreatmentPositive deviance

Identifiers

PMID29145834
PMCPMC5691393

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.