Evidence map›Paper›PMID 32094222›Full record

ArticleBMJ open diabetes research & care2020

Exploring geographic variation of and influencing factors for utilization of four diabetes management measures in Swiss population using claims data.

Wenjia Wei, Oliver Gruebner, Viktor von Wyl, Holger Dressel, Agne Ulyte, Beat Brüngger, Eva Blozik, Caroline Bähler, Julia Braun, Matthias Schwenkglenks

Abstract read
In one paragraph

Article in BMJ open diabetes research & care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Wenjia WeiDepartment of Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland wenjia.wei@uzh.ch.ORCID 0000-0002-1977-8416
Oliver GruebnerDepartment of Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Viktor von WylDepartment of Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Holger DresselDivision of Occupational and Environmental Medicine, Department of Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich and University Hospital Zurich, Zurich, Switzerland.
Agne UlyteDepartment of Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Beat BrünggerDepartment of Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.ORCID 0000-0001-6173-5375
Eva BlozikDepartment of Health Sciences, Helsana Versicherungen AG, Dübendorf, Switzerland.
Caroline BählerDepartment of Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Julia BraunDepartments of Biostatistics and Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Matthias SchwenkglenksDepartment of Epidemiology, Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionFour strongly recommended diabetes management measures are biannual glycated hemoglobin (HbA1c) testing, annual eye examination, kidney function examination, and low-density lipoprotein (LDL) testing in patients below 75 years. We aimed to describe regional variation in the utilization of the four measures across small regions in Switzerland and to explore potential influencing factors. RESEARCH DESIGN AND

methodsWe conducted a cross-sectional study of adult patients with drug-treated diabetes in 2014 using claims data. Four binary outcomes represented adherence to the recommendations. Possible influencing factors included sociodemographics, health insurance preferences, and clinical characteristics. We performed multilevel modeling with Medstat regions as the higher level. We calculated the median odds ratio (MOR) and checked spatial autocorrelation in region level residuals using Moran's I statistic. When significant, we further conducted spatial multilevel modeling.

resultsOf 49 198 patients with diabetes (33 957 below 75 years), 69.6% had biannual HbA1c testing, 44.3% each had annual eye examination and kidney function examination, and 55.5% of the patients below 75 years had annual LDL testing. The effects of health insurance preferences were substantial and consistent. Having any supplementary insurance (ORs across measures were between 1.08 and 1.28), having supplementary hospital care insurance (1.08-1.30), having chosen a lower deductible level (eg, SFr2500 compared with SFr300: 0.57-0.69), and having chosen a managed care model (1.04-1.17) were positively associated with recommendations adherence. The MORs (1.27-1.33) showed only moderate unexplained variation, and we observed inconsistent spatial patterns of unexplained variation across the four measures.

conclusionOur findings indicate that the uptake of strongly recommended measures in diabetes management could possibly be optimized by providing further incentives to patients and care providers through insurance scheme design. The absence of marked regional variation implies limited potential for improvement by targeted regional intervention, while provider-specific promotion may be more impactful.

Indexed as

Kidney Function TestsPatient Acceptance of Health CareVision ScreeningAdultAgedAged, 80 and overCross-Sectional StudiesDiabetes MellitusFemaleGlycated HemoglobinGuideline AdherenceHumansHypoglycemic AgentsLipoproteins, LDLMaleManaged Care ProgramsGlycated Hemoglobinhemoglobin A1c protein, humanHypoglycemic AgentsLipoproteins, LDLguideline adherencehealth care utilizationhealth service research

Identifiers

PMID32094222
PMCPMC7039601

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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.