Please use this identifier to cite or link to this item: http://docs.prosentient.com.au/prosentientjspui/handle/1/10197
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dc.contributor.authorMatthews, Veronica-
dc.contributor.authorSchierhout, Gill-
dc.contributor.authorMcBroom, James-
dc.contributor.authorConnors, Christine-
dc.contributor.authorKennedy, Catherine-
dc.contributor.authorKwedza, Ru-
dc.contributor.authorLarkins, Sarah-
dc.contributor.authorMoore, Elizabeth-
dc.contributor.authorThompson, Sandra-
dc.contributor.authorScrimgeour, David-
dc.contributor.authorBailie, Ross-
dc.date2014-
dc.date.accessioned2018-05-15T23:01:08Z-
dc.date.accessioned2019-06-29T00:36:53Z-
dc.date.available2018-05-15T23:01:08Z-
dc.date.available2019-06-29T00:36:53Z-
dc.date.issued2014-11-19-
dc.identifier.citationBMC health services research 2014-11-19; 14: 578-
dc.identifier.urihttp://docs.prosentient.com.au/prosentientjspui/handle/1/10197-
dc.description.abstractIt is generally recognised that continuous quality improvement (CQI) programs support development of high quality primary health care systems. However, there is limited evidence demonstrating their system-wide effectiveness. We examined variation in quality of Type 2 diabetes service delivery in over 100 Aboriginal and Torres Strait Islander primary health care centres participating in a wide-scale CQI project over the past decade, and determined the influence of health centre and patient level factors on quality of care, with specific attention to health centre duration of participation in a CQI program. We analysed over 10,000 clinical audit records to assess quality of Type 2 diabetes care of patients in 132 Aboriginal and Torres Strait Islander community health centres in five states/territories participating in the ABCD project for varying periods between 2005 and 2012. Process indicators of quality of care for each patient were calculated by determining the proportion of recommended guideline scheduled services that were documented as delivered. Multilevel regression models were used to quantify the amount of variation in Type 2 diabetes service delivery attributable to health centre or patient level factors and to identify those factors associated with greater adherence to best practice guidelines. Health centre factors that were independently associated with adherence to best practice guidelines included longer participation in the CQI program, remoteness of health centres, and regularity of client attendance. Significantly associated patient level variables included greater age, and number of co-morbidities and disease complications. Health centre factors explained 37% of the differences in level of service delivery between jurisdictions with patient factors explaining only a further 1%. At the health centre level, Type 2 diabetes service delivery could be improved through long term commitment to CQI, encouraging regular attendance (for example, through patient reminder systems) and improved recording and coordination of patient care in the complex service provider environments that are characteristic of non-remote areas.-
dc.language.isoeng-
dc.subject.meshAdult-
dc.subject.meshAged-
dc.subject.meshAged, 80 and over-
dc.subject.meshAustralia-
dc.subject.meshClinical Audit-
dc.subject.meshCommunity Health Centers-
dc.subject.meshDelivery of Health Care-
dc.subject.meshDiabetes Mellitus, Type 2-
dc.subject.meshFemale-
dc.subject.meshHealth Services, Indigenous-
dc.subject.meshHumans-
dc.subject.meshHypoglycemic Agents-
dc.subject.meshMale-
dc.subject.meshMiddle Aged-
dc.subject.meshOceanic Ancestry Group-
dc.subject.meshPractice Guidelines as Topic-
dc.subject.meshPrimary Health Care-
dc.subject.meshQuality Improvement-
dc.subject.meshState Medicine-
dc.subject.meshYoung Adult-
dc.titleDuration of participation in continuous quality improvement: a key factor explaining improved delivery of Type 2 diabetes services.-
dc.typeJournal Article-
dc.typeResearch Support, Non-U.S. Gov't-
dc.identifier.doi10.1186/s12913-014-0578-1-
dc.identifier.journaltitleBMC health services research-
dc.identifier.pubmedurihttps://www.ezpdhcs.nt.gov.au/login?url=https://www.ncbi.nlm.nih.gov/pubmed/25408165-
dc.identifier.pubmedidhttps://www.ezpdhcs.nt.gov.au/login?url=https://www.ncbi.nlm.nih.gov/pubmed/25408165-
dc.identifier.affiliationMenzies School of Health Research, Brisbane, Queensland, Australia. veronica.matthews@menzies.edu.au..-
dc.identifier.affiliationMenzies School of Health Research, Brisbane, Queensland, Australia. gill.schierhout@menzies.edu.au..-
dc.identifier.affiliationSchool of Environment, Griffith University, Brisbane, Queensland, Australia. j.mcbroom@griffith.edu.au..-
dc.identifier.affiliationDepartment of Health, Darwin, Northern Territory, Australia. Christine.Connors@nt.gov.au..-
dc.identifier.affiliationMaari Ma Health Aboriginal Corporation, Broken Hill, Far West New South Wales, Australia. Cath.Kennedy@maarima.com.au..-
dc.identifier.affiliationQueensland Health, Cairns, Queensland, Australia. ru.kwedza@health.nsw.gov.au..-
dc.identifier.affiliationSchool of Medicine & Dentistry, James Cook University, Townsville, Queensland, Australia. sarah.larkins@jcu.edu.au..-
dc.identifier.affiliationAboriginal Medical Services Alliance Northern Territory, Alice Springs, Northern Territory, Australia. liz.moore@amsant.org.au..-
dc.identifier.affiliationWestern Australian Centre for Rural Health, University of Western Australia, Geraldton, Western Australia, Australia. sandra.thompson@uwa.edu.au..-
dc.identifier.affiliationAboriginal Health Council of South Australia, Adelaide, South Australia, Australia. David.Scrimgeour@ahcsa.org.au..-
dc.identifier.affiliationMenzies School of Health Research, Brisbane, Queensland, Australia. ross.bailie@menzies.edu.au..-
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