Diabetes care scale: a first line screening of self-care and treatment behavior in diabetics seeking treatment at a tertiary care setting in Bhubaneswar, Odisha

Published

2020-12-31

DOI:

https://doi.org/10.47203/IJCH.2020.v32i04.013

Keywords:

Diabetic care scale, Quality of life in Diabetics (QOLID), Health Seeking Behavior, Patient Satisfaction

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Abstract

Background: Quality in diabetic management is the need of the hour, in eye of the menacing increase in the disease in India. Hence, a sensitive qualitative handling of outpatient visits is warranted and an inbuilt mechanism of Quality of life scales (which are proxy of the patient’s response to disease) and Diabetic care scales (proxy for patient’s satisfaction to the care extended), would offer supportive evidence to physicians, of areas where they will have to be more careful. Aims and Objectives: To assess the Diabetic Care scale (DCS) for the subjects seeking management from the diabetic care unit. To find out the factors associated with the DCS and derive inferences to improve upon quality of management in the given sample Methodology: Diabetics were made to answer to Quality of Life in Diabetics (QOLID) and Diabetic Care Scale (DCS), validated and pretested for Indian populations; and factors affecting patient’s responses were ascertained, to improve care. Final sample of 599 interviews were assessed. To identify the predictors of diabetic care, diabetic care scale was dichotomized on the basis of its median value. Results: QOLID domains were inversely correlated with DCS, strongly significant (treatment satisfaction, general health, symptom botherness, financial worries, emotional health and physical endurance). Role limitations to physical health were also positively related to DCS (-0.422; p<0.001), which indicated that this domain affected DCS positively and significantly. Overall QOLID and DCS scores were negatively correlated and significant (-0.650; p<0.005). Education (UOR 0.76; SD 0.64 - 0.90, p=0.002), treatment, medical adherence in diabetics about being careless with medications (AOR=2.38 SD 1.50 - 3.77, <0.001) emerged predictors of poor DCS scores. DCS can be used as a prelim screening to evaluate the quality of care in diabetic management in early stages so as to rectify any gaps and improve through specialized counselling in subsequent visits. Wide use of these tools is recommended, both in rural and urban scenario to improve and control the diabetic epidemic in India.

How to Cite

1.
Meher D, Kar S, Pathak M, Singh S. Diabetes care scale: a first line screening of self-care and treatment behavior in diabetics seeking treatment at a tertiary care setting in Bhubaneswar, Odisha. Indian J Community Health [Internet]. 2020 Dec. 31 [cited 2022 Aug. 17];32(4):688-93. Available from: https://www.iapsmupuk.org/journal/index.php/IJCH/article/view/1909

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References

Basu S, Sharma N. Diabetes self-care in primary health facilities in India - challenges and the way forward. World J Diabetes. 2019 15;10(6):341-349. doi: 10.4239/wjd.v10.i6.341. PMID: 31231457; PMCID: PMC6571487.[PubMed].

Bhojani U, Beerenahalli TS, Devadasan R, Munegowda CM, Devadasan N, Criel B, Kolsteren P. No longer diseases of the wealthy: prevalence and health-seeking for self-reported chronic conditions among urban poor in Southern India. BMC Health Services Research. 2013 1;13(1):306.

Srinivas G, Suresh E, Jagadeesan M, Amalraj E, Datta M. Treatment-seeking behavior and compliance of diabetic patients in a rural area of south India. Ann N Y Acad Sci. 2002;958:420-4. doi: 10.1111/j.1749-6632.2002.tb03017.x. PMID: 12021154.[PubMed].

Stewart MA. Effective physician-patient communication and health outcomes: a review. CMAJ. 1995 May 1;152(9):1423-33. PMID: 7728691; PMCID: PMC1337906.[PubMed].

Kaplan SH, Greenfield S, Ware JE Jr. Assessing the effects of physician- patient interactions on the outcomes of chronic disease. Med Care. 1989;27(3 Suppl):S110-27. doi: 10.1097/00005650-198903001-00010. Erratum in: Med Care 1989 Jul;27(7):679. PMID: 2646486.[PubMed].

Meher D, Kar S, Pathak M, Singh S. Quality of Life Assessment in Diabetic Patients Using a Validated Tool in a Patient Population Visiting a Tertiary Care Center in Bhubaneswar, Odisha, India. ScientificWorldJournal. 2020 29;2020:7571838. doi: 10.1155/2020/7571838. PMID: 33456400; PMCID: PMC7785381.[PubMed].

Nagpal J, Kumar A, Kakar S, Bhartia A. The development of 'Quality of Life Instrument for Indian Diabetes patients (QOLID): a validation and reliability study in middle and higher income groups. J Assoc Physicians India. 2010;58:295-304. PMID: 21117348.[PubMed].

Jacobson AM, de Groot M, Samson JA. The evaluation of two measures of quality of life in patients with type I and type II diabetes. Diabetes Care. 1994;17(4):267-74. doi: 10.2337/diacare.17.4.267. PMID: 8026281.[PubMed]

Reliability and validity of a diabetes quality-of-life measure for the diabetes control and complications trial (DCCT). The DCCT Research Group. Diabetes Care. 1988;11(9):725-32. doi: 10.2337/diacare.11.9.725. PMID: 3066604.[PubMed]

Ramachandran A, Snehalatha C, Kapur A, Vijay V, Mohan V, Das AK, Rao PV, Yajnik CS, Prasanna Kumar KM, Nair JD; Diabetes Epidemiology Study Group in India (DESI). High prevalence of diabetes and impaired glucose tolerance in India: National Urban Diabetes Survey. Diabetologia. 2001;44(9):1094-101. doi: 10.1007/s001250100627. PMID: 11596662.[PubMed]

Burroughs TE, Desikan R, Waterman BM, Gilin D, McGill J. Development and validation of the diabetes quality of life brief clinical inventory. Diabetes Spectrum. 2004 1;17(1):41-9.

India State-Level Disease Burden Initiative Diabetes Collaborators. The increasing burden of diabetes and variations among the states of India: the Global Burden of Disease Study 1990-2016. Lancet Glob Health. 2018;6(12):e1352-e1362. doi: 10.1016/S2214-109X(18)30387-5. Epub 2018 Sep 12. PMID: 30219315; PMCID: PMC6227383.[PubMed].

Mohapatra T. Prevalence of Diabetes Mellitus among the Elderly: An Empirical Study in Cuttack (Odisha). Indian Journal of Gerontology. 2014 1;28(2):303-16.

Akhtar SN, Dhillon P. Prevalence of diagnosed diabetes and associated risk factors: Evidence from the large-scale surveys in India. Journal of Social Health and Diabetes. 2017;5(1):28.

Gopichandran V, Lyndon S, Angel MK, Manayalil BP, Blessy KR, Alex RG, Kumaran V, Balraj V. Diabetes self-care activities: a community-based survey in urban southern India. Natl Med J India. 2012;25(1):14-7. PMID: 22680314.[PubMed].

Selvaraj K, Ramaswamy G, Radhakrishnan S, Thekkur P, Chinnakali P, Roy G. Self-care practices among diabetes patients registered in a chronic disease clinic in Puducherry, South India. Journal of Social Health and Diabetes. 2016;4(01):025-9.

Sasi ST, Kodali M, Burra KC, Muppala BS, Gutta P, Bethanbhatla MK. Self care activities, diabetic distress and other factors which affected the glycaemic control in a tertiary care teaching hospital in South India. Journal of clinical and diagnostic research: JCDR. 2013;7(5):857.

Rajput R, Gehlawat P, Gehlan D, Gupta R, Rajput M. Prevalence and predictors of depression and anxiety in patients of diabetes mellitus in a tertiary care center. Indian J Endocrinol Metab. 2016;20(6):746-751. doi: 10.4103/2230-8210.192924. PMID: 27867873; PMCID: PMC5105554.[PubMed].

Balhara YP, Sagar R. Correlates of anxiety and depression among patients with type 2 diabetes mellitus. Indian J Endocrinol Metab. 2011;15(Suppl 1):S50-4. doi: 10.4103/2230-8210.83057. PMID: 21847456; PMCID: PMC3152186.[PubMed].

Rath S, Tripathy A, Tripathy AR. Prediction of new active cases of coronavirus disease (COVID-19) pandemic using multiple linear regression model. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2020 Sep 1;14(5):1467-74.

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