Impact of Continuous Care on Health Outcomes and Cost for Type 2 Diabetes Mellitus: Analysis Using National Health Insurance Cohort Database

Nam, Ji Hyun; Lee, Changwoo; Kim, Nayoung; Park, Keun Young; Ha, Jeonghoon; Yun, Jae-Moon; Shin, Dong Wook; Shin, Euichul

doi:10.4093/dmj.2018.0189

Cited by 15 publications

(24 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…None of the studies showed any improvement in lipid profile [ 32 , 34 , 36 , 42 , 46 , 51 ] or BMI [ 31 , 35 , 46 ]. All seven studies that examined the risk of disease-related complications such as cardiovascular disease, end-stage renal disease found that continuity of care reduced complication risks [ 29 , 40 , 47 , 52 – 55 ].…”

Section: Resultsmentioning

confidence: 99%

Effects of continuity of care on health outcomes among patients with diabetes mellitus and/or hypertension: a systematic review

et al. 2021

View full text Add to dashboard Cite

Background The rising prevalence of non-communicable diseases (NCDs) such as diabetes mellitus (DM) and hypertension (HT) has placed a tremendous burden on healthcare systems around the world, resulting in a call for more effective service delivery models. Better continuity of care (CoC) has been associated with improved health outcomes. This review examines the association between CoC and health outcomes in patients with DM and/or HT. Methods This was a systematic review with searches carried out on 13 March 2021 through PubMed, Embase, MEDLINE and CINAHL plus, clinical trials registry and bibliography reviews. Eligibility criteria were: published in English; from 2000 onwards; included adult DM and/or HT patients; examined CoC as their main intervention/exposure; and utilised quantifiable outcome measures (categorised into health indicators and service utilisation). The study quality was evaluated with Critical Appraisal Skills Programme (CASP) appraisal checklists. Results Initial searching yielded 21,090 results with 42 studies meeting the inclusion criteria. High CoC was associated with reduced hospitalisation (16 out of 18 studies), emergency room attendances (eight out of eight), mortality rate (six out of seven), disease-related complications (seven out of seven), and healthcare expenses (four out of four) but not with blood pressure (two out of 13), lipid profile (one out of six), body mass index (zero out of three). Six out of 12 studies on diabetic outcomes reported significant improvement in haemoglobin A1c by higher CoC. Variations in the classification of continuity of care and outcome definition were identified, making meta-analyses inappropriate. CASP evaluation rated most studies fair in quality, but found insufficient adjustment on confounders, selection bias and short follow-up period were common limitations of current literatures. Conclusion There is evidence of a strong association between higher continuity of care and reduced mortality rate, complication risks and health service utilisation among DM and/or HT patients but little to no improvement in various health indicators. Significant methodological heterogeneity in how CoC and patient outcomes are assessed limits the ability for meta-analysis of findings. Further studies comprising sufficient confounding adjustment and standardised definitions are needed to provide stronger evidence of the benefits of CoC on patients with DM and/or HT.

show abstract

Section: Resultsmentioning

confidence: 99%

Effects of continuity of care on health outcomes among patients with diabetes mellitus and/or hypertension: a systematic review

et al. 2021

View full text Add to dashboard Cite

show abstract

“…There was a de nite increase of continuity in age group 40-59, compared to other age groups. Continuity was distinctively lower in young age group (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39), which can partly be explained by milder severity of disease, less complication, and more frequent residential migration of the group. However, current phenomenon can pose an impending threat to the working population, since legacy effect of diabetes has been recently reported 16 .…”

Section: Discussionmentioning

confidence: 99%

“…Frailty has a negative impact on activities of daily living 19 , such as visiting doctors, ultimately resulting in lower continuity of care. Thus, healthcare policies to enhance continuity in older age group is imperative to lighten the socioeconomic disease burden for the rapidly ageing global population 20,21 .…”

Section: Discussionmentioning

confidence: 99%

Analysis of continuity of care and related factors in diabetic patients in Korea

Shin¹,

Kim²,

Cho³

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Diabetes is one of the fastest growing diseases with approximately 463 million patients worldwide. It is established that to manage diabetes, continuity of care in primary care setting is crucial. We aim to statistically define and analyze factors of continuity that are associated with patient, clinic, and geographical relationship.Methods: We used 2014~2015 claim data from National Health Insurance Service (NHIS), with 39,096 eligible outpatient attendances across 29,912 office-based clinics. We applied multivariable logistic regression to analyze factors that may affect three kinds of continuity of care index for each patient: most frequent provider continuity index (MFPC), modified-modified continuity index (MMCI), and continuity of care index (COC). Results: Mean value of continuity of care indices were MFPC 0.90, MMCI 0.96, COC 0.85. Among patient factors, old age above 80 (MFPC 0.81 [0.74-0.89], MMCI 0.84 [0.76-0.92], COC 0.81 [0.74-0.89]) and disability were strongly associated with lower continuity of care. Another significant factor was residential area: further the patients lived from their primary care clinic, lower the continuity of diabetes care (MFPC 0.74 [0.70–0.78], MMCI 0.70 [0.66–0.73], COC 0.74 [0.70–0.78]). Patients who lived in metropolitan areas had higher continuity of care compared to those of other areas (metropolitan area, MFPC 1.19 [1.17-1.27], MMCI 1.17 [1.10-1.25], COC 1.19 [1.12-1.27]). There was no statistical significance among clinic factors, such as the number of physicians or nurses hired per clinic, between the lower and the higher continuity of care groups.Conclusion: Geographical proximity of patient’s residential area and clinic location showed the strongest correlation as factor of continuity. Political support is necessary to geographically align the imbalance of supply and demand of medical needs.

show abstract

“…There was a de nite increase of continuity in age group 40-59, compared to other age groups. Continuity was distinctively lower in young age (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39), which can partly be explained by mild severity, less complication, and more frequent residential migration of the group. However, current phenomenon can pose an impending threat to the working population since legacy effect of diabetes has been recently reported 16 .…”

Section: Discussionmentioning

confidence: 99%

“…Frailty has a negative impact on activities of daily living 19 , such as visiting doctors, which eventually results in lower continuity of care. Thus, healthcare policies to enhance continuity in older age group is imperative to lighten the socioeconomic disease burden for the rapidly ageing global population 20,21 .…”

Section: Discussionmentioning

confidence: 99%

Analysis of Continuity of Care and Related Factors in Diabetes Patients in Korea

Shin

Kim

Cho

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Diabetes is one of the fastest growing diseases with approximately 463 million patients worldwide. It is established that to manage diabetes, continuity of care in primary care setting is crucial. We aim to statistically define and analyze factors of continuity that are associated with patient, clinic and geographical relationship.Methods: We used 2014~2015 claim data from National Health Insurance Service (NHIS), with 39,096 eligible outpatient attendances across 29,912 office-based clinics. We applied multivariable logistic regression to analyze factors that may affect three kinds of continuity of care index for each patient: most frequent provider continuity index (MFPC), modified-modified continuity index (MMCI), and continuity of care index (COC). Results: Mean value of continuity of care indices were MFPC 0.90, MMCI 0.96, COC 0.85. Among patient factors, old age above 80 (MFPC 0.81 [0.74-0.89], MMCI 0.84 [0.76-0.92], COC 0.81 [0.74-0.89]) and disability were strongly associated with lower continuity of care. Another significant factor was residential area: further the patients lived from their primary care clinic, lower the continuity of diabetes care (MFPC 0.74 [0.70–0.78], MMCI 0.70 [0.66–0.73], COC 0.74 [0.70–0.78]). Patients who lived in metropolitan area had higher continuity of care compared to other areas (metropolitan area, MFPC 1.19 [1.17-1.27], MMCI 1.17 [1.10-1.25], COC 1.19 [1.12-1.27]). There was no statistical significance among clinic factors, such as number of hired physicians or nurses hired per clinic, between the lower and the higher continuity of care groups.Conclusion: Geographical proximity of patient’s residential area and clinic location showed highest correlation as factor of continuity. Political support is necessary to geographically align the imbalance of supply and demand of medical needs.

show abstract

Impact of Continuous Care on Health Outcomes and Cost for Type 2 Diabetes Mellitus: Analysis Using National Health Insurance Cohort Database

Cited by 15 publications

References 32 publications

Effects of continuity of care on health outcomes among patients with diabetes mellitus and/or hypertension: a systematic review

Effects of continuity of care on health outcomes among patients with diabetes mellitus and/or hypertension: a systematic review

Analysis of continuity of care and related factors in diabetic patients in Korea

Analysis of Continuity of Care and Related Factors in Diabetes Patients in Korea

Contact Info

Product

Resources

About