- •Care coordination has been implemented in diverse ways, and most commonly focusses on communication and monitoring within and between health-care teams.
- •Outcome measures of care coordination emphasize biometric patient-level outcomes as opposed to overall quality of care, or integrated health and social care.
- •Future research should explore patient and provider preferences and emphasize comprehensive needs assessment in traditional and virtual delivery systems.
- 1.How is implementation of care coordination reported in literature?
- 2.How is care coordination commonly evaluated?
1. Search strategy
2. Sources of evidence screening and selection
3. Data extraction
4. Data Analysis
|Author, year, country||Aim||Methodology||Population characteristics||Care coordination||Reported outcomes|
|Andrich and Foronda, 2020, USA||To improve glycemic control and QoL of Medicare patients aged ≥65 years of with T2DM.||Practice improvement project, CP||Medicare outpatients of endocrinology clinic (n=24), mean age 74 years, 62.5% male and A1C of ≥7% (mean 7.7%, SD=8).||NPs provided 1 session of diabetes self-management education and support and goal setting, with a 4-week follow up, and care coordination.||Fasting blood glucose decreased from 146.2 (SD=18.7) to 136.0 (SD= 17.1) mg/dL (p<0.05). Overall diabetes-specific quality of life improved significantly (p<0.05).|
|Barnett et al, 2006, USA||To assess health-care use among veterans with T2DM in a care coordination–home telehealth program||Retrospective concurrent matched cohort study, CP||Veterans from VA medical centres at high risk for hospitalization or ED visits (n=391 treatment, n=391 control), with mean age 68.1 years (treatment).||Nurse care coordinators (RN or NP) monitored telehealth data, called patients, performed patient assessments, placed new medication orders, helped manage medications, scheduled appointments and reminded patients of appointments.||Treatment group had statistically significant reductions in likelihood of all-cause (38.8% to 30.0%) and DM-related hospitalizations (35.3% to 26.9%).|
|Barnett et al, 2007, USA||To assess the cost–utility of a care coordination–home telehealth program.||Retrospective, pre–post cohort study, CP||Veterans from VA medical centres at high risk for hospitalization or ED visits (n=470), with mean age 68.2 years and 99% male.||RN or NP care coordinators monitored telehealth data, called patients, performed patient assessments, placed new medication orders, helped manage medications, scheduled appointments and reminded patients of appointments.||The overall mean incremental cost-effectiveness ratio for the program at 1 year was $60,941. The program was cost-effective for one third of participants.|
|Bayliss et al, 2008, USA||To explore processes of care desired by elderly patients with multiple morbidities that may present competing demands for patients and providers.||Qualitative study||Community-dwelling older adults aged ≥65 years, and had (at minimum) diabetes, depression and osteoarthritis (n=26), with 46% between 65 and 74 and 54% between 74 and 84 years of age, and 50% male.||NA||Participants’ desired processes of care included the need for convenient access to providers, providers with a caring attitude, clear communication of individualized care plans, support from a single coordinator of care and continuity of relationships.|
|Bazzano et al, 2018, USA||To understand the perspectives of health-care providers and system administrators and identify challenges and facilitators to the successful implementation of non–face-to-face long-term care management programs.||Qualitative study||Care providers, including physicians (n=12) and nurses (n=4), and staff, administrators or billing specialists (n=4).||NA||Health system personnel view non–face-to-face care as potentially providing value for patients and addressing systemic needs yet challenging to implement in practice. Barriers include major time commitment and patient needs extending beyond the program, whereas facilitators include the strategic use of resources in an already constrained environment.|
|Bazzano et al, 2019, USA||To investigate views on non–face-to-face care management held by elderly patients with diabetes and other chronic conditions.||Qualitative study||T2DM patients with at least 1 comorbid condition, in an in-home virtual setting (n=30), mean age 68.3 years and 33% were male.||RNs (and other clinic staff) made regular phone calls between patients, developed and reviewed care management plans and connected patients to resources when needed.||Patient engagement and enthusiasm influenced positively by perceived self-sufficiency and self-efficacy. Patients preferred support in changing behaviours surrounding diet and nutrition, as opposed to simply education. Finally, patients expressed the value of speaking with providers in person (vs non–face-to-face), and of having personal, caring relationships with PCPs.|
|Benzer et al, 2019, USA||To determine how cardiovascular and mental health comorbidities relate to patient-centred coordinated care in the VA department.||Observational study using patient surveys||Veteran patients from 29 VA medical centres with T2DM and cardiovascular and mental health comorbidities (n=5,807), mean age 67.92 years, 90.8% male and 4.2% sex not reported.||Clinician and clinic staff coordinated care through organizational processes, procedures and information exchange, as well as formal relationships between organizations such as contracts, formal relationships among parts of organizations such as services or clinics and informal relationships among people.||Based on patients’ perceptions of integrated care survey, mental health comorbidities were significantly associated with lower patient experiences of coordinated care. Higher severity comorbidities were associated with more knowledge fragmentation, lower treatment-related communication, greater information flow to specialists and better hospital transitions.|
|Benzer et al, 2020, USA||To determine VA patients' and clinicians' experiences of coordination across VA and non-VA settings.||Mixed methods, CP||Veteran patients with T2DM and either cardiovascular or mental health comorbidity from 8 VA sites, or non-VA clinics (n=5,807), mean age 67.92 years and 90.8% male (same sample as Benzer et al, 2019).||The effectiveness of care coordination by clinicians and clinic staff across VA and non-VA settings depending on the degree to which VA coordination is prioritized, how it structured its regional non-VA networks, what mechanisms it implemented to facilitate coordination, what barriers to coordination it removed and how VA measures the coordination components of quality of care.||Based on patients’ perceptions of integrated care survey, veterans who received both VA and non-VA care reported significantly worse care coordination experiences (0.11–0.24 lower scores) than veterans only receiving care within the VA department. Clinicians identified challenges such as limited information exchange capabilities, and bureaucratic and opaque procedures that adversely impacted clinical decision-making.|
|Brown et al, 2016, USA||To describe the successful implementation of a new model of chronic disease management.||Quasi-experimental design, NI||Patients with high-risk diabetes from a virtual RN outreach clinic in the VA department (phase 1: n=24, intervention, n=28 historical controls; phase 2: n=155), mean age 66 years, 93.5% male and A1C of >9% (mean 9.646, SD=1.73).||Phase 1: RNs and NPs coordinated care, including establishing individualized A1C goals, providing education, coaching and support; adjusting medications; and reviewing of patients’ self-monitored blood glucose data transmitted via home telephone devices daily. Phase 2: RNs received additional education to provide medication titration. NPs entered insulin adjustment orders.||Phase 1: Time to achievement of A1C goals was significantly improved in the intervention group (p<0.001) vs historic controls. Phase 2: Mean baseline A1C was reduced from 9.6% to 7.7% in the intervention group.|
|Chumbler, Neugaard et al, 2005|
|To report on the impact of a VHA program that implemented care coordination enhanced by CCHT in a large group of veterans with DM across 4 sites.||Retrospective, single-group study design, CP||Veteran patients who were frail with diabetes in the VA department, at high risk for expensive care service visits, in an in-home virtual setting (n=445), mean age 68.4 years and 98.7% male.||Patients answered questions daily using an in-home messaging device containing disease management dialogues, and care coordinators reviewed responses daily to determine the risk for health-care emergencies. Patients treated holistically. In the case of comorbidities, care coordinators monitored difficult-to-manage conditions more intensely; in rare cases, 2-way audiovisual communication was used.||The intervention resulted in a statistically significant reduction in the proportion of patients hospitalized (50% reduction), a reduction in emergency room use (by 11%), a reduction in average bed days of care (by an average of 3 days) and improvement in health-related quality of life in the domains of role–physical functioning, bodily pain and social functioning.|
|Chumbler, Vogel et al, 2005, USA||To examine the effectiveness of a VA patient-centred CCHT program as an adjunct to treatment for veterans with diabetes.||Retrospective, concurrent matched cohort study design, CP||Veterans with diabetes in the VA department at high risk for expensive, multiple care visits, in an in-home virtual setting, (n=800 total, 400 treatments, 400 in comparison group), with mean age 68.2 years (treatment).||RN or NP care coordinators managed treatment, equipped veterans with self-management skills and attempted to increase preventive service use. They also monitored patients’ daily responses to a dialogue box that asked them health status questions to determine whether it was necessary to call the patient or facilitate a provider appointment.||At 1 year post-enrolment, there was a significant difference between treatment and comparison groups in terms of needs-based primary care visits, increasing in the treatment group by 7.6% and decreasing in the comparison group by 12% (p<0.01); in a subgroup analysis that was controlled for A1C, the treatment group had a lower likelihood of hospitalizations vs the comparison group.|
|Chumbler et al, 2009, USA||To assess the effectiveness of the CCHT program in reducing mortality||Retrospectively matched intervention and control groups, CP||Veterans with diabetes from the VA department, in an in-home virtual setting, (n=387 treatment, n=387 control) and mean age 68 years (for both treatment and control groups).||Patients answered questions daily about symptoms and health status using an in-home messaging device, and RN and NP care coordinators monitored answers daily. Based on this, coordinators placed telephone calls to each patient, made physician referrals, consulted physicians, placed orders for new medications, helped manage medications and scheduled VA clinic appointments.||There were significantly more deaths in the control group (26%) vs the intervention group (19%); there was longer survival for the intervention group vs the control group (mean survival time 1,348 vs 1,278 days, p=0.015). The telemonitoring program was associated with reduced 4-year all-cause mortality (hazard ratio=0.7, p=0.013).|
|Dang et al, 2007, USA||To evaluate telemedicine in diabetes management and education in older adults from different ethnic backgrounds.||Pilot study of a care program, NI||Community-dwelling patients with DM receiving primary care, aged ≥60 years (n=41) and mean age 72 years||NPs and licensed social workers coordinated care, which included assessment, planning, coordination and follow-up of multiple health-care services for patients and ensuring the services were received. They also monitored patient data received via an in-home messaging device daily, which included patients’ responses to questions regarding blood sugar and answers to educational questions.||Mean A1C was 7.6% before enrolment, and 7.3% after 9 months (p=0.09), with the greatest decrease occurring in African Americans (0.65%, p=0.05). Total hospital admissions decreased from 31 pre-enrolment to 25 post-enrolment (p=0.0002). Bed days of care decreased from 368 to 149 (p=0.0002).|
|Fagan et al, 2010, USA||To examine the effects of an intervention comprising (1) practice-based care coordination program, (2) augmented by pay for performance for meeting quality targets and (3) complemented by a third-party disease management on quality of care and resource use. for older adults with diabetes.||Quasi-experimental, longitudinal study, NI||Older adults with diabetes in 9 primary care practices, (n=20,943 total, n=1,587 intervention, n=19,356 comparison), mean age 74.6 years (intervention) and 42.2% were male (intervention)||RNs, licensed practical nurses and medical assistants coordinated care onsite, and served as a liaison between PCPs and call centre nurses. Coordinator duties included alerting physicians to quality improvement opportunities, requesting hospital or specialists’ records and reviewing and conveying information to call centre nurses. so that they could follow up with patients.||Intervention sites had significantly greater improvements in A1C (p<0.0001) and LDL (p<0.01) vs the control group. Measures for quality of care, utilization and cost were not significantly different between the 2 study groups.|
|Gabbay et al, 2006, USA||To measure the impact of a patient-oriented structured approach to care coordination and patient education and counselling on improvements in BP, glycemic control, lipids, complication screening and DM-related distress.||RCT, NI||Primary care patients with T2DM managed by insulin or hypoglycemic agents (n=332 total, n=150 intervention, n=182 control), with a mean age 65 years (intervention), 57% male (intervention) and baseline A1C of 7.4%.||RN coordinated care including the following activities: behavioural goal-setting; individualized care planning; providing self-management education and surveillance; making phone calls to patients; providing referrals to specialists, dietitians or certified diabetes educators; ordering protocol-driven laboratory tests; tracking clinical outcomes; and making clinical recommendations.||After 1-year, BP decreased significantly from 137/77 to 129/72 mmHg in the intervention group, compared with an increase in BP in the control group from 136/77 to 138/79 mmHg. Problem areas in diabetes scores, assessing diabetes-related distress, significantly improved in the intervention group (23 to 10). Complication screening improved significantly in the intervention group vs the control group. A1C and LDL did not change significantly.|
|He et al, 2017, China||To investigate the frequency of follow-up visits and contents of care for case management of patients with T2DM in Chongqing, China, in terms of regional practice guideline, and to analyze factors associated with the use of care.||Observation study using patient surveys||Primary care patients with T2DM of either a township near a hospital, or far from one (n=496); 76.4% were >60 years of age and 40.32% were male||NA||Over 1-year, 65% of participants had at least 4 follow-up visits. The proportions of patients having recommended tests were 8%, 54%, 45% and 44% for A1C, blood lipid test, screening for nephropathy and eyes, respectively.|
|Ishani et al, 2011, USA||To determine whether nurse case management with a therapeutic algorithm could effectively improve rates of control for hypertension, hyperglycemia and hyperlipidemia vs usual care among veterans with diabetes.||RCT, NI||Diabetic patients in primary care through the VA medical centre or affiliated outpatient clinics, in-home virtual intervention setting (n=278 intervention, n=278 usual care), mean age 64.9 years (intervention), 99.6% male (intervention), average A1C 8% (intervention).||Nurse case managers established lifestyle modification goals and personal action plans with patients, adjusted patient medications, made telephone calls, reviewed patients’ in-home BP measures, reviewed patient progress for blood glucose, lifestyle and BP goals, monitored adverse events associated with therapy and notified PCPs of medication changes.||A greater number of individuals in the intervention group achieved control over all 3 outcomes of A1C, LDL and BP vs the usual-care group (21.9% vs 10.1%, p<0.01). A greater number of intervention patients vs usual-care patients achieved individual treatment goals for A1C (73.7% vs 65.8%, p=0.04) and BP (45% vs 25.4%, p<0.01), but not for LDL (57.6% vs 55.4%, p=0.61).|
|Izquierdo et al, 2007, USA||To examine the detection and remediation of medically urgent situations among older patients receiving telemedicine case management for diabetes.||RCT, NI||Older patients with diabetes living in upstate New York, receiving an in-home virtual intervention (n=338), 43% male and mean A1C of 7%.||Nurse case managers coordinated care and coupled with dietitians and endocrinologists. Case managers reviewed patient responses to an in-home telemedicine unit; engaged in televisits every 4–6 weeks to discuss medications, BP and glucose readings; and made clinical recommendations to PCPs.||Over 36 months, 67 medically urgent situations were identified and addressed (1.9 events/month). Some of these were potentially life-threatening, including drug contraindications (n=24), other medical urgent situations (n=19) and medically urgent conditions like unstable angina (n=24).|
|Jia et al, 2009, USA||To assess the longitudinal effect of the VA CCHT program by determining the extent to which it was associated with a lower probability of preventable hospitalization use by veterans with DM over a 4-year period.||Retrospective matched treatment–control study, CP||Veteran patients with diabetes from a VA medical centre who were of high treatment priority (n=387 treatment, n=387 control), mean age 67.6 years and 98.3% male.||NP and RN care coordinators monitored patient responses received daily from an in-home messaging device, made telephone calls to patients, arranged referrals with physicians, scheduled VHA clinic appointments, placed new medication orders, helped with medication management, reminded patients of clinic appointments and assisted with technology difficulties.||After 4 years, the treatment group had significantly fewer preventable hospitalizations (0.7 vs 1.0), a lower crude death rate (19.4% vs 26.4%) and longer survival time (1,349.4 days vs 1,278.2 days) vs the control group.|
|Jia et al, 2011, USA||To assess the effects of the CCHT program for diabetes on the average number of inpatient stays and outpatient clinic visits over a follow-up period of 48 months.||Longitudinal study with quasi-experimental design, CP||Veterans with diabetes of VHA medical centres (n=387 treatment, n=387 control), mean age 68 years (treatment), and 99% male (treatment)||Care coordinators monitored patient information received daily from a home telehealth device regarding symptoms and health status, made telephone calls to patients, arranged referrals with physicians, scheduled VHA clinic appointments, placed patient medication orders, helped with medication management, reminded patients of clinic appointments and assisted with technology difficulties.||Compared with controls, intervention group patients were less likely to be admitted for inpatient care at 6- month (p<0.001) and 12-month (p<0.01) follow ups, and consistently more likely to visit outpatient clinics (p<0.001) during the complete 48-month follow-up period. The likelihood of an increase in outpatient utilization tended to decline over time.|
|Lo et al, 2016, Australia||To explore the perspectives of patients and their carers on the factors influencing healthcare of those with comorbid diabetes and CKD||Qualitative study||Participants with comorbid DM and CKD from Australian tertiary hospital health services, (n=58), median age 66 years and 70.69% male||Focus groups conducted to understand patient perspectives on care coordination provided by PCPs, potentially coordinating with specialists, pharmacists, social workers, nurse educators and others.||Patient-level factors influencing care were self-management, socioeconomic status and adverse experiences related to comorbid diabetes and CKD; health service–level factors affecting care were prevention and awareness of comorbid diabetes and CKD, poor continuity and coordination of care, patient and carer empowerment and poor recognition of psychological comorbidity.|
|Markle-Reid et al, 2016, Canada||To examine the feasibility of implementation in practice (primary) and the feasibility of study methods and potential effectiveness (secondary) of the Aging, Community, and Health Research Unit–Community Partnership Program.||Mixed methods, NI||Community-dwelling older adults with T2DM, diagnosed with at least 2 additional chronic conditions and receiving in-home care (n=36), 33% were 65–69 years old and 14% were ≥80 years old, and were 44% male.||RN and RD coordinators offered 4 in-home visits and 6 monthly group sessions; facilitated access to services and supports; and coordinated communication among participants, caregivers, the program team and PCPs. Coordinators also met monthly with a team for case conferences to develop client-centred care plans.||Participants and providers viewed the program as acceptable and feasible. Participants had a higher short-form health survey physical component summary score at 6 months vs baseline (difference 3.0), and median costs for diabetes care increased over 6 months.|
|Markle-Reid et al, 2018, Canada||To compare the effect of a 6-month, community-based intervention with that of usual care on QoL, depressive symptoms, anxiety, self-efficacy, self-management and health-care costs in older adults with T2DM and 2 or more comorbidities.||RCT, NI||Community-dwelling older adults with T2DM, diagnosed with at least 2 additional chronic conditions (n=200 total, n=101 intervention, n=99 control), 32.5% between 65 and 69 years, 40% between 70 and 74 years, and 27.5% >75 years of age, and 42.5% male (intervention).||RN and RD care coordinators provided up to 3 in-home visits, and monthly group wellness sessions. Coordinators also engaged in monthly case conferences with team members, as well as ongoing nurse-led care coordination.||The 6-month intervention significantly improved QoL and self-management, and reduced depressive symptoms, without increasing total health-care costs.|
|Mateo-Abad et al, 2020, Spain||To evaluate, in the Basque Country, the impact of the Care Well integrated care model for older patients with multimorbidity.||Mixed methods, NI||Complex patients ≥65 years of age with at least 2 chronic conditions (1 of which was chronic obstructive pulmonary disease, congestive heart failure or DM), treated across home, hospital, primary care and virtual settings (n=200 total, n=101 intervention, n=99 control), mean age 79.4 years, 63% male, and mean A1C of 6.8%.||Nurse case managers worked with a multidisciplinary care team to identify frail older individuals, conduct comprehensive baseline assessments, define therapeutic plans, coordinate hospital discharge, communicate with health-care providers and empower patients through home-based care.||The intervention reduced the number of hospitalizations and emergency department visits and increased the number of primary care contacts. Clinical changes such as significant decreases in body mass index and blood glucose levels were observed. Satisfaction level was high for stakeholders.|
|McCants et al, 2019, USA||To determine the impact of integrated case management services compared with usual treatment for patients diagnosed with diabetes and concomitant CHF.||Retrospective, descriptive study, NI||Adults with CHF and DM, between hospital and home settings, (n=68 total, n=49 intervention, n=19 usual treatment), and mean age 77.8 years (SD=11.7) (intervention) and 53.1% male.||Social worker and nurse case managers prioritized discharge needs and assessed, planned, implemented, evaluated and interacted to devise cohesive care plans to reduce costs and increase quality of care and coordinated transportation and home health.||Of the intervention participants, 81.6% did not re-admit within 30 days, whereas only 47.4% of usual-treatment participants did not re-admit (p=0.012).|
|Miklavcic et al, 2020, Canada||To evaluate the effect of a 6-month community-based intervention vs usual care on physical functioning, mental health, depressive symptoms, anxiety, self-efficacy, self-management and health-care costs in older adults with T2DM and 2 or more comorbidities.||Pragmatic RCT, NI||Older adults with T2DM and 2 or more chronic conditions, from in-home and community agency settings (n=132 total, n=70 intervention, n=62 usual care), 58% between 65 and 74 years of age, 42% ≥75 years of age and 45% male.||RN and RD care coordinators provided up to 3 in-home visits, 6 monthly community group sessions and coordination through linking the client to community services.||No significant group differences were seen in the change from baseline and 6 months in physical functioning (p=0.56), mental functioning (p=0.30) or other secondary outcomes.|
|Min et al, 2017, USA||To test for measurable improvement over time in diabetes care quality and utilization during implementation of PCMHs at the University of Michigan Health System in 2009, including 1 year pre- and 1 year post- implementation.||Longitudinal cohort study, NI||Patients with diabetes in primary care (n=2,221), mean age 71.6 years (pharmacy-led PCMHs), mean age 70.0 years (nurse-led PCMHs), 45.5% male (pharmacy-led PCMHs), and 43.6% male (nurse-led PCMHs).||Pharmacist and nurse care coordinators provided self-management support and improved patient communication, which included standing lab-order sets, note templates, patient handouts and database and flow sheets to track improvement.||Quality of care improved, and utilization decreased over 2.5 years. Both pharmacy and nurse-led coordination improved LDL and DBP by 2.5 years, although the trajectory differed. Only the pharmacy-led approach decreased primary care visits.|
|Mohr et al, 2019, USA||To examine how organizational coordination measures, reported by PCPs, were associated with patient experiences of care coordination.||Cross-sectional surveys||VA patients with T2DM, and one of either hypertension, congestive heart failure, depression/anxiety or severe mental illness or PTSD, from the VHA, (3,183 patients matched to 233 PCPs), 71.9% ≥65 years of age, 91.1% male and 46.8% with A1C >7%.||RNs and licensed practical nurses provided care coordination.||Patient ratings of specialist knowledge management and knowledge integration were significantly lower when either PCPs did not use feedback coordination, or rated feedback coordination lower. Teamwork was significantly related to specialist knowledge management (b=0.06), knowledge integration (b=0.04) and knowledge fragmentation (b=−0.04).|
|Munshi et al, 2013, USA||To evaluate whether assessment of barriers to self-care and strategies to cope with these barriers in older adults with diabetes is superior to usual care with attention control (same frequency of contact, but no advice provided).||RCT, NI||Patients with poorly controlled T1DM or T2DM, from a specialized diabetes outpatient clinic (n=100 total, n=70 intervention, n=30 attention control), mean age 75 years, 43% male (intervention) and baseline A1C of >8%.||A diabetes educator care coordinator evaluated barriers to self-care, identified strategies to cope with barriers and made phone calls to educate, guide and follow up with patients. The control group educator made phone calls to participants, only discussing non–diabetes-related life events.||Over 12 months, A1C decreased by 0.45% in the intervention group vs 0.31% in the control group. At 12 months, it decreased further in the intervention group (0.21% vs 0%) vs the control group. The intervention group showed additional benefits in measures of self-care, gait and balance and endurance compared with the control group. Diabetes-related distress improved in both groups.|
|Ni et al, 2019, China||To evaluate the effect of community nurse–led multidisciplinary team management on A1C, QoL, hospitalization and help-seeking behaviour in people with T2DM.||Quasi-experimental trial, NI||Community individuals with T2DM, ≥35 years of age, in an in-home virtual setting (n=179 total, n=88 intervention, n=91 control), mean age 66.5 years, A1C of 7.08% (intervention).||A nurse-led multidisciplinary team coordinated care, which included organizing group health education classes, providing individualized counselling via telephone and face-to-face follow-up visits and providing pamphlets and self-monitoring workbooks. Coordinators also served as liaisons between participants and PCPs.||During the 24-month period, the intervention group had significantly reduced A1C (1.08%) vs the control group, which achieved an increase of 0.45% (p<0.001). The intervention group showed significant increases in QoL scores and seeking help from nurses, and a significantly larger decrease in hospitalizations vs the control group.|
|Rafiq et al, 2019, Sweden||To describe the characteristics of heart/cardiac, nephrology, diabetes and mellitus patients and to explore the initial effects of a multidisciplinary and person-centred care on total care utilization.||RCT, NI||Patients in the outpatient centre with T1DM or T2DM, kidney disease and cardiovascular disease (n=42 intervention, n=35 control), mean age 74.2 years (intervention), 83.3% male (intervention).||A multidisciplinary care team led by nurse managers, supported by registered practical nurse coordinated care by developing sustainable care management plans, engaging in twice-weekly case conferences with senior consultants and ensuring patients received all necessary treatment at a single location.||Heart/cardiac, nephrology and diabetes mellitus patients were sicker than control group participants, but service utilization indicators were similar between the 2 arms. No between-group differences were statistically significant other than an increase in telephone visits in the intervention group.|
|Regina et al, 2020, Italy||To explore the potential of pharmacy services by community pharmacists in the management of T2DM alongside general and specialists’ medical practitioners to improve quality of diabetes care.||Observational, noncontrolled pilot study, NI||Participants with T2DM from a rural community pharmacy, ≥18 years of age (n = 40), mean age 64.5 years and 50% male.||Over 12 months, the pharmacist case manager received an individualized care plan from each participant’s physician. The pharmacist carried out examinations (electrocardiogram, fundus examination, self-analysis of blood and urine), booked examinations at accredited units and reported results to the physician.||Patient adherence to the care plan increased significantly (98% in the first quarter and 100% in the remaining 3 quarters). Mean percentage change was −4% for A1C (SD=5), −10% for LDL (SD=7), −13% for SBP (SD=4) and −9% for DBP (SD=2). 80% of participants reported better patient information and easier accessibility to services.|
|Shea et al, 2006,|
|To examine the impact of the IDEATel intervention on clinical outcomes, including A1C, BP and lipid levels vs usual care.||RCT, NI||Older adults ≥55 years of age, living in medically underserved areas of New York state, receiving in-home virtual care (n=1,665, n=844 intervention, n=821 usual care), mean age 71 years and 36.5% male (intervention).||Nurse case managers (supervised by diabetologists) regularly communicated with patients via a Web-enabled computer and an existing telephone line, remotely monitored glucose and BP daily, provided patients with access to their own clinical data and provided access to an educational website.||Over 1 year, the intervention group had significantly improved net reductions in A1C (0.18% net change, p=0.006), SBP and DBP (3.4 and 1.9 mmHg net change, p<0.001), and LDL (9.5 mg/dL net change, p<0.001) vs the control group.|
|Shea et al, 2009,|
|To examine the effectiveness of a telemedicine intervention to achieve clinical management goals in older, ethnically diverse, medically underserved patients with diabetes.||RCT, NI||Older adults ≥55 years of age, from medically underserved areas of New York state, receiving in-home virtual care (n=1,665, n=844 intervention, n=821 usual care), mean age 71 years, 36.5% male (intervention) (same sample as Shea et al, 2006).||Nurse case managers (supervised by diabetologists) regularly communicated with patients via a Web-enabled computer and an existing telephone line, remotely monitored glucose and BP daily, provided patients with access to their own clinical data, and provided access to an educational website (same care coordination as Shea et al, 2006).||Over 5 years of follow up, the intervention significantly reduced A1C (p=0.001) by 0.29, LDL (p<0.01) by 3.84 and SBP and DBP by 4.32 mmHg and 2.64 mmHg (p = 0.024 and p<0.001), respectively.|
|Shea et al, 2013, USA||To examine the social impact of the telemedicine intervention effects in lower and higher socioeconomic status participants in the IDEATel study.||RCT, NI||Older adults ≥55 years of age, living in medically underserved areas of New York state, receiving care in an in-home virtual setting (n= 1,665, n=844 intervention, n=821 usual care), mean age 71 years, 36.5% male (intervention) (same sample as Shea et al, 2006).||Nurse case managers (supervised by endocrinologists) regularly communicated with patients via a Web-enabled computer and an existing telephone line, remotely monitored glucose and BP daily, provided patients with access to their own clinical data, and provided access to an educational website. Case managers contacted PCPs if a change in management was required (same sample as Shea et al, 2006).||A1C was higher in lower income participants at baseline. However, after 5 years, the intervention did not seem to increase disparities. The lowest income group showed greater intervention effects in A1C (p=0.004) and SBP (p=0.023).|
|Trief et al, 2006, USA||To investigate the effect of comorbid depression on glycemic control and on response to a telemedicine case management intervention for elderly, ethnically diverse diabetes patients.||RCT, NI||Older adults ≥55 years of age with diabetes, living in medically underserved areas, in an in-home virtual setting, (n=1,665 total, n=844 intervention, n=821 usual care), mean age 70.8 years, 37.2% male and mean A1C 7.4%.||Nurse case managers, under the supervision of an endocrinologist, monitored BP and blood glucose via a home telemedicine unit, video-conferenced with patients, provided patients with access to individualized graphic displays and educational content, and consulted with PCPs to make treatment planning decisions.||At baseline, there was a significant correlation between depression and A1C. However, after 1 year, the intervention group reported a greater reduction in A1C compared with the control group, but depression did not predict changes in A1C.|
|Trief et al, 2008, USA||To understand the experiences of older patients with diabetes who participated in a telemedicine case management intervention.||Qualitative study||Older adults with DM who participated in in-home, virtual care coordination (n=40), mean age 67.93 years, 57.5% were male and mean A1C 7.38%.||Nurse case managers coordinated care with the help of dietitians, including monitoring patient blood glucose and BP via web-enabled home telehealth units, video-conferencing with patients to educate and facilitate goal setting, providing support, and consulting with PCPs who made the final treatment decisions.||Most patients enrolled in the program primarily because health-care providers encouraged them. Patients’ goals were to improve diabetes control, and they valued an emphasis on monitoring of health outcomes and supportive contact with staff.|
|Trief et al, 2009, USA||To assess whether diabetes self-efficacy relates to glycemic control (primary), and to BP and cholesterol (secondary), and whether a change in self-efficacy relates to change in these medical outcomes in a group of older, ethnically diverse individuals.||Analysis of pre-existing longitudinal data, NI||Older adults ≥55 years of age with T2DM, in an in-home, virtual setting, (n=1,665), mean age 70.82 years, 37.18% male and mean A1C 7.38% (same sample as Trief et al, 2006).||Nurse and RD case managers collaboratively formulated a plan with patients to address BP, blood glucose and lipid control; monitored these outcomes through patient data uploaded using a home telemedicine unit; and regularly video-conferenced with patients to educate and discuss goals.||The intervention significantly improved self-efficacy over time (p<0.0001). An increase in diabetes self-efficacy over time was related to improvement in glycemic control (p<0.0001), but not in BP or lipid levels.|
|Tu et al, 2020, China||To evaluate the effect of a nurse-coordinated hospital-initiated transitional care program on hypertension control for older people with diabetes in China.||A single-blinded cluster RCT,|
|Older adults with DM receiving care between hospital wards and community centres (n=270 total, n=135 intervention, n=135 control), mean age 70.9 years and 54.8% male.||Discharge nurses, community nurses and PCPs coordinated hospital-initiated transitional care, including providing individualized post-discharge support and referring patients to specialist clinics for timely medication adjustment.||The intervention group demonstrated a significant decrease in mean SBP (10.7 mmHg) DBP (4.1 mmHg) vs the control group. There were significant improvements in A1C, hypertension and diabetes knowledge, treatment adherence, QoL, hospital re-admission and emergency department visits in the intervention group vs the control group.|
|Wakefield et al, 2011, USA||To evaluate the efficacy of a nurse-managed home telehealth intervention to improve outcomes in veterans with comorbid diabetes and hypertension.||RCT, NI||Veterans with comorbid T2DM and hypertension in VA department primary care (n=302 total, n=107 usual care, n=93 high-intensity intervention, n=102 low-intensity intervention), mean age 68 years and 98% male.||RN care coordinators monitored patient responses on a home telehealth device daily for 6 months to determine whether patients required follow up. The low-intensity group received standard prompts, whereas the high-intensity group also received additional health questions and educational content.||Over 6 months, A1C in both intervention groups decreased significantly vs the control group (p=0.03 and 0.02 for low- and high-intensity groups), but differences were not maintained at 12 months. High-intensity subjects had a significant decrease (p=0.001) in SBP vs the control group at 6 and 12 months.|
|Walker et al, 2017, primarily studies from USA, 1 from Austria, 1 from UK||To explore home telemedicine interventions for the treatment of older adults with diabetes.||Systematic review||Studies including older adults with a mean age >65 years, with T1 or T2DM, with and without other chronic conditions and receiving virtual care.||Care coordination interventions involved education, closed-loop feedback and communication, a home telemedicine device or unit, remote monitoring, use of a telephone or telephone line and motivational interviewing or coaching.||The included studies suggest that case management or coordination can effectively decrease admissions, costs per person per year, mortality and cognitive decline in older adults with diabetes.|
|Yeager et al, 2018, USA||To provide insight into patient and provider experiences, specifically for the care of patients with diabetes and multiple chronic comorbidities.||Qualitative study||Patients ≥65 years old with DM and at least 1 other chronic condition, and health-care providers implementing the program in a virtual setting, (n=14 patients, n=19 providers).||Nurse case managers coordinated care through telephone, text, e-mail or patient portals, and had responsibilities such as answering patient questions, prescription management, appointment scheduling, billing and finance, self-care plans and coordination with and referral to other providers such as specialists or diabetes educators.||Providers identified challenges such as the large time commitment required to coordinate care for complex patients, low patient literacy and technology proficiency and high patient psychosocial needs. Providers believed the program benefitted patients, and that it improved continuity of care. Patients reported positive experiences, such as the program being applicable to their needs.|
Implementation of care coordination activities
Care coordination type
Comprehensive needs assessment
Individualized care planning
Regular communication and monitoring
- Dang S.
- Ma F.
- Nedd N.
- Florez H.
- Aguilar E.
- Roos B.A.