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      Patterns of engagement with the health care system and risk of subsequent hospitalization amongst patients with diabetes

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          Abstract

          Background

          Re-hospitalization is common among patients with diabetes, and may be related to aspects of health care use. We sought to determine the association between patterns of health care engagement and risk of subsequent hospitalization within one year of discharge for patients with diabetes.

          Methods

          We identified adults with incident diabetes in Alberta, Canada, who had at least one hospitalization following their diabetes diagnosis between January 1, 2004 and March 31, 2011. We used Cox regression to estimate the association between factors related to health care engagement (prior emergency department use, primary care visits, and discharge disposition (i.e. whether the patient left against medical advice)) and the risk of subsequent all-cause hospitalization within one year.

          Results

          Of the 33811 adults with diabetes and at least one hospitalization, 11095 (32.8%) experienced a subsequent all-cause hospitalization within a mean (standard deviation) follow-up time of 0.68 (0.3) years. Compared to patients with no emergency department visits, there was a 4 percent increased risk of a subsequent hospitalization for every emergency department visit occurring prior to the index hospitalization (adjusted Hazard Ratio [HR]: 1.04; 95% CI: 1.03–1.05). Limited and increased use of primary care was also associated with increased risk of a subsequent hospitalization. Compared to patients with 1–4 visits, patients with no visits to a primary care physician (adjusted HR: 1.11; 95% CI: 0.99–1.25) and those with 5–9 visits (adjusted HR: 1.06; 95% CI: 1.00–1.12) were more likely to experience a subsequent hospitalization. Finally, compared to patients discharged home, those leaving against medical advice were more likely to have a subsequent hospitalization (adjusted HR: 1.74; 95% CI: 1.50–2.02) and almost 3 times more likely to have a diabetes-specific subsequent event (adjusted HR: 2.86; 95% CI: 1.82–4.49).

          Conclusions

          Patterns of health care use and the circumstances surrounding hospital discharge are associated with an increased risk of subsequent hospitalization among patients with diabetes. Whether these patterns are related to the health care systems ability to manage complex patients within a primary care setting, or to access to primary care services, remains to be determined.

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          Most cited references24

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          Preventable hospitalizations and access to health care.

          To examine whether the higher hospital admission rates for chronic medical conditions such as asthma, hypertension, congestive heart failure, chronic obstructive pulmonary disease, and diabetes in low-income communities resulted from community differences in access to care, prevalence of the diseases, propensity to seek care, or physician admitting style. Analysis of California hospital discharge data. We calculated the hospitalization rates for these five chronic conditions for the 250 ZIP code clusters that define urban California. We performed a random-digit telephone survey among adults residing in a random sample of 41 of these urban ZIP code clusters stratified by admission rates and a mailed survey of generalist and emergency physicians who practiced in the same 41 areas. Community based. A total of 6674 English- and Spanish-speaking adults aged 18 through 64 years residing in the 41 areas were asked about their access to care, their chronic medical conditions, and their propensity to seek health care. Physician admitting style was measured with written clinical vignettes among 723 generalist and emergency physicians practicing in the same communities. We compared respondents' reports of access to medical care in an area with the area's cumulative admission rate for these five chronic conditions. We then tested whether access to medical care remained independently associated with preventable hospitalization rates after controlling for the prevalence of the conditions, health care seeking, and physician practice style. Access to care was inversely associated with the hospitalization rates for the five chronic medical conditions (R2 = 0.50; P < .001). In a multivariate analysis that included a measure of access, the prevalence of conditions, health care seeking, and physician practice style to predict cumulative hospitalization rates for chronic medical conditions, both self-rated access to care (P < .002) and the prevalence of the conditions (P < .03) remained independent predictors. Communities where people perceive poor access to medical care have higher rates of hospitalization for chronic diseases. Improving access to care is more likely than changing patients' propensity to seek health care or eliminating variation in physician practice style to reduce hospitalization rates for chronic conditions.
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            Comparison of coding of heart failure and comorbidities in administrative and clinical data for use in outcomes research.

            Despite the potential usefulness of administrative databases for evaluating outcomes, coding of heart failure and associated comorbidities have not been definitively compared with clinical data. To compare the predictive value of heart failure diagnoses and secondary conditions identified in a large administrative database with chart-based records. The authors studied 1808 patient records sampled from 14 acute care hospitals and compared clinically recorded data with administrative records from the Canadian Institute for Health Information. The impact of comorbidity coding in the administrative data set according to the Charlson classification was examined in models of 30-day mortality. The positive predictive value (PPV) of a primary diagnosis ICD-9 428 was 94.3% using the Framingham criteria and 88.6% using criteria previously validated with pulmonary capillary wedge pressure. There was reduced prevalence of secondary comorbid conditions in administrative data in comparison with clinical chart data. The specificities and PPV/negative predictive values of administratively identified index comorbidities were high. The sensitivities of index comorbidities were low, but were enhanced by examination of hospitalizations within 1 year prior to the index heart failure admission. Using information from prior hospitalizations modestly enhanced 30-day mortality model performance; however, the odds ratio point estimates of the index and enhanced administrative data sets were consistent with the clinical model. The ICD-9 428 primary diagnosis is highly predictive of heart failure using clinical criteria. Examination of hospitalization data up to 1 year prior to the index admission improves comorbidity detection and may provide enhancements to future studies of heart failure mortality.
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              Overview of the Alberta Kidney Disease Network

              Background The Alberta Kidney Disease Network is a collaborative nephrology research organization based on a central repository of laboratory and administrative data from the Canadian province of Alberta. Description The laboratory data within the Alberta Kidney Disease Network can be used to define patient populations, such as individuals with chronic kidney disease (using serum creatinine measurements to estimate kidney function) or anemia (using hemoglobin measurements). The administrative data within the Alberta Kidney Disease Network can also be used to define cohorts with common medical conditions such as hypertension and diabetes. Linkage of data sources permits assessment of socio-demographic information, clinical variables including comorbidity, as well as ascertainment of relevant outcomes such as health service encounters and events, the occurrence of new specified clinical outcomes and mortality. Conclusion The unique ability to combine laboratory and administrative data for a large geographically defined population provides a rich data source not only for research purposes but for policy development and to guide the delivery of health care. This research model based on computerized laboratory data could serve as a prototype for the study of other chronic conditions.
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                Author and article information

                Contributors
                Journal
                BMC Health Serv Res
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central
                1472-6963
                2013
                9 October 2013
                : 13
                : 399
                Affiliations
                [1 ]Department of Community Health Sciences, Faculty of Medicine, University of Calgary, Calgary, Canada
                [2 ]Department of Medicine, Faculty of Medicine, University of Calgary, Calgary, Canada
                [3 ]Health Analysis Division, Statistics Canada, Ottawa, Ontario, Canada
                [4 ]Department of Medicine, Faculty of Medicine, University of Alberta, Edmonton, Canada
                Article
                1472-6963-13-399
                10.1186/1472-6963-13-399
                3851786
                24103159
                bbf2810a-d3f7-47a3-9844-705936efa110
                Copyright © 2013 Ronksley et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 29 July 2013
                : 4 October 2013
                Categories
                Research Article

                Health & Social care
                diabetes,administrative data,hospitalization
                Health & Social care
                diabetes, administrative data, hospitalization

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