AHRQ Grant HS021899: Related Publication Summaries
Improving Diabetes Quality Reports for Persons with Multiple Chronic Conditions
1. "The relationship of individual comorbid chronic conditions to diabetes care quality."
Magnan EM, Palta M, Mahoney JE, Pandhi N, Bolt DM, Fink J, Greenlee RT, Smith MA.
BMJ Open Diabetes Research Care 2015 Jul 23; 3(1):e000080.
PUBMED link: www.ncbi.nlm.nih.gov/pubmed/26217492
This study retrospectively analyzed electronic health record data for 23,430 adults with diabetes to determine which of 62 comorbid chronic conditions were related to diabetes care goals. A total of 17 conditions were related to achieving diabetes control, while half of the conditions were not found to predict control. For example, obesity was related to lack of HbA1c and blood pressure control. Three conditions were related to lack of cholesterol testing, including congestive heart failure and substance use disorders. Future interventions could target patients at risk for not meeting diabetes care goals based on their individual comorbidities.
2. "The impact of a patient's concordant and discordant chronic conditions on diabetes care quality measures."
Magnan EM, Palta M, Johnson HM, Bartels CM, Schumacher JR, Smith MA.
Journal of Diabetes Complications 2015 Mar; 29(2):288-94.
PUBMED link: www.ncbi.nlm.nih.gov/pubmed/25456821
This study examined the impact of the number of concordant conditions (that support diabetes care) and discordant chronic conditions (that compete with diabetes care) on diabetes care quality by analyzing electronic health record data from 7 health systems on 24,430 adults with diabetes. A higher number of concordant conditions were associated with higher odds of achieving testing and control goals for all outcomes except blood pressure control. There was no to minimal positive association between the number of discordant conditions and outcomes, except for cholesterol testing, which was less likely with 4 + discordant conditions.
3. "Can claims data algorithms identify the physician of record?"
DuGoff EH, Walden E, Ronk K, Palta M, Smith M.
Medical Care 2018 Mar;56(3):e16-e20.
PUBMED link: www.ncbi.nlm.nih.gov/pubmed/28319581
This study sought to determine the agreement of the primary care physician (PCP) identified by claims algorithms with the PCP of record in electronic health record data. It concluded that researchers may be more likely to identify a patient's PCP when focusing on primary care visits only. However, these algorithms perform less well among vulnerable populations and those experiencing fragmented care.
4. "Increasing consumer engagement by tailoring a public reporting website on the quality of diabetes care: a qualitative study."
Smith MA, Bednarz L, Nordby PA, Fink J, Greenlee RT, Bolt D, Magnan EM.
Journal of Medical Internet Research 2016 Dec 21;18(12):e332.
PUBMED link: www.ncbi.nlm.nih.gov/pubmed/28003173
The goal of this study was to determine if tailoring quality reports to persons with diabetes mellitus and co-occurring chronic conditions would increase user engagement with a website that publicly reports the quality of diabetes care. It concluded that tailoring can be used to improve public reporting sites for individuals with chronic conditions, ultimately allowing consumers to make more informed health care decisions.
5. "Establishing chronic condition concordance and discordance with diabetes: a Delphi study."
Magnan EM, Gittelson R, Bartels CM, Johnson HM, Pandhi N, Jacobs EA, Smith MA.
BMC Family Practice 2015 Mar 28;16:42.
PUBMED link: www.ncbi.nlm.nih.gov/pubmed/25887080
This study aimed to provide more information for the future research and clinical use of the concordant/discordant framework by increasing the number of conditions that can be characterized as concordant or discordant with diabetes. By finding that 12 conditions were concordant with diabetes care and 50 were discordant, the study significantly adds to the number of conditions for which there is information on concordance and discordance for diabetes care.
6. "Stratifying patients with diabetes into clinically relevant groups by combination of chronic conditions to identify gaps in quality of care."
Magnan EM, Bolt DM, Greenlee RT, Fink J, Smith MA.
Health Services Research 2018 Feb;53(1):450-468.
PUBMED link: www.ncbi.nlm.nih.gov/pubmed/27861829.
The purpose of this paper was to find clinically relevant combinations of chronic conditions among patients with diabetes and to examine their relationships with six diabetes quality metrics. The researchers analyzed 12 conditions that were concordant with diabetes care to define five mutually exclusive combinations of conditions based on condition co-occurrence. They found the following condition classes: severe cardiac, cardiac, noncardiac vascular, risk factors, and no concordant comorbidities. They concluded that patients had distinct quality metric achievement by condition class, and those in less severe classes were less likely to achieve diabetes metrics.
7. "Algorithm for identifying patients with multiple chronic conditions (multimorbidity)."
Magnan E. University of Wisconsin - Madison Department of Family Medicine, the University of California - Davis Department of Family and Community Medicine, and the UW Health Innovation Program; 2015. Available at: https://www.hipxchange.org/comorbidities.
The crafters of this toolkit used HCUP's Clinical Classification Software (CCS) to create indicator variables for the presence or absence of 69 chronic conditions. The toolkit contains an Excel file for importing into a statistical program. It contains ICD-9 diagnostic codes mapped to CCS codes, which are then bundled into 69 clinically relevant chronic condition categories. The diagnostic codes can be assessed in any patient timeframe desired.
8. "Division of primary care services between physicians, physician assistants, and nurse practitioners for older patients with diabetes."
Everett CM, Thorpe CT, Palta M, Carayon P, Gilchrist VJ, Smith MA.
Medical Care Research Review 2013 Oct;70(5):531-41.
PUBMED link: www.ncbi.nlm.nih.gov/pubmed/23868081
The investigators described the division of patients and services between primary care providers for older diabetes patients on panels with varying levels of PA/NP involvement. They concluded that understanding how patients and services are divided between PA/NPs and physicians will assist in defining provider roles on primary care teams.
9. "The roles of primary care PAs and NPs caring for older adults with diabetes."
Everett CM, Thorpe CT, Palta M, Carayon P, Gilchrist VJ, Smith MA.
JAAPA 2014 Apr;27(4):45-9.
PUBMED link: www.ncbi.nlm.nih.gov/pubmed/24662258
The investigators proposed a multidimensional characterization of PA and NP roles on panels of primary care patients with diabetes. They found that PAs and NPs in primary care perform a variety of roles and frequently perform multiple roles within a clinic.
10. "Physician assistants and nurse practitioners perform effective roles on teams caring for Medicare patients with diabetes."
Everett C, Thorpe C, Palta M, Carayon P, Bartels C, Smith MA.
Health Affairs 2013 Nov;32(11):1942-8.
PUBMED link: www.ncbi.nlm.nih.gov/pubmed/24191084
The investigators compared outcomes for two groups of adult Medicare patients with diabetes whose conditions were at various levels of complexity: those whose care teams included PAs or NPs in various roles, and those who received care from physicians only. They found that outcomes were generally equivalent in thirteen comparisons, but mixed in seven others, so that no role was best for all outcomes. They concluded that patient characteristics, as well as patients' and organizations' goals, should be considered when determining when and how to deploy PAs and NPs on primary care teams.
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