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Original ArticlesChronic Kidney Disease
Open Access

Digital Applications Targeting Medication Safety in Ambulatory High-Risk CKD Patients

Randomized Controlled Clinical Trial

Stephanie W. Ong, Sarbjit V. Jassal, Eveline C. Porter, Kyoyoon K. Min, Akib Uddin, Joseph A. Cafazzo, Valeria E. Rac, George Tomlinson and Alexander G. Logan
CJASN April 2021, 16 (4) 532-542; DOI: https://doi.org/10.2215/CJN.15020920
Stephanie W. Ong
1Department of Pharmacy, University Health Network, Toronto, Ontario, Canada
2Division of Nephrology, University Health Network, Toronto, Ontario, Canada
3Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada
4Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
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Sarbjit V. Jassal
2Division of Nephrology, University Health Network, Toronto, Ontario, Canada
4Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
5Department of Medicine, University Health Network, Toronto, Ontario, Canada
6Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
7Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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Eveline C. Porter
2Division of Nephrology, University Health Network, Toronto, Ontario, Canada
8Department of Nursing, University Health Network, Toronto, Ontario, Canada
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Kyoyoon K. Min
2Division of Nephrology, University Health Network, Toronto, Ontario, Canada
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Akib Uddin
9Centre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, Ontario, Canada
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Joseph A. Cafazzo
4Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
6Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
9Centre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, Ontario, Canada
10Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
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Valeria E. Rac
4Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
6Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
11Ted Rogers Centre for Heart Research, Peter Munk Cardiac Centre, Toronto, Ontario, Canada
12Program for Health System and Technology Evaluation, Toronto, Ontario, Canada
13Toronto Health Economics and Technology Assessment Collaborative, Toronto, Ontario, Canada
14Diabetes Action Canada, Canadian Institutes of Health Research Strategy for Patient-Oriented Research Network, Toronto, Ontario, Canada
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George Tomlinson
4Toronto General Hospital Research Institute, University Health Network, Toronto, Ontario, Canada
5Department of Medicine, University Health Network, Toronto, Ontario, Canada
6Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
7Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
13Toronto Health Economics and Technology Assessment Collaborative, Toronto, Ontario, Canada
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Alexander G. Logan
2Division of Nephrology, University Health Network, Toronto, Ontario, Canada
5Department of Medicine, University Health Network, Toronto, Ontario, Canada
6Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
7Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
15Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
16Department of Medicine, Sinai Health, Toronto, Ontario, Canada
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    Figure 1.

    System architecture. The components included a smartphone application and Bluetooth-enabled BP monitor for patients, web-based dashboard for clinicians, data servers to execute algorithms and store data, and live interfaces with clinical repositories for medications and laboratory results.

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    Figure 2.

    CONSORT diagram.

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    Figure 3.

    Mobile application usage data and sustainability. (A) Number of patients using eKidneyCare with ≥ one patient-initiated medication review during the study duration. (B) Percentage of patients by group with at least one home BP reading per month. *The sharp reduction in the number of medication reviews in study month 12 is related to the large number of participants completing the study exit assessment in the 11th month. The mean study duration was 10.8 months.

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    Table 1.

    Baseline patient characteristics

    VariableaeKidneyCareMyMedRec
    N8993
    Age, yr (SD)56 (14)58 (16)
    Male, n (%)54 (61)64 (69)
    CKD stage, n (%)
     3b11 (12)13 (14)
     424 (27)33 (36)
     525 (28)16 (17)
     Dialysis29 (33)31 (33)
      Home nocturnal hemodialysis18 (20)19 (20)
      In-center hemodialysis0 (0)1 (1)
      Peritoneal dialysis11 (12)11 (12)
    Education, n (%)
     Graduate10 (11)24 (26)
     College/University53 (60)51 (55)
     High school19 (21)15 (16)
     Primary school5 (6)2 (2)
     Not stated2 (2)1 (1)
    Health literacy REALM scores, n (%)
     Grade 3 or below0 (0)2 (2)
     Grade 4–64 (5)1 (1)
     Grade 7–821 (24)16 (18)
     High school62 (71)71 (79)
    Ethnicity, n (%)
     White53 (60)49 (53)
     Black (Non-Hispanic)10 (11)17 (18)
     Asian (Southeast Asian, Asian, South Asian)22 (25)26 (28)
     First nations1 (1)0 (0)
     Hispanic2 (2)1 (1)
     Other or did not disclose1 (1)7 (8)
    Comorbidity
     Number of comorbidities, median (IQR)4 (3–6)5 (3–7)
     Number of comorbidities, n (%)
      0–15 (6)10 (11)
      2–329 (33)17 (18)
      4–527 (30)29 (31)
      ≥628 (32)37 (40)
     Diabetes mellitus, n (%)26 (29)31 (33)
     Hypertension, n (%)65 (73)60 (65)
    Medications
     Total number of medications per patient, median (IQR)10 (8–14)11 (8–15)
     Number with ten or more medications, n (%)44 (49)48 (52)
     Antihypertensive medications, median (IQR)2 (1–4)2 (1–4)
     Number with HTN medications, n (%)
      011 (12)14 (15)
      117 (19)20 (21)
      219 (21)19 (20)
      ≥342 (47)40 (43)
     Total medication discrepancy rate, median (IQR)0.38 (0.25–0.54)0.38 (0.29–0.53)
     Clinically relevant medication discrepancy rate, median (IQR)0.33 (0.20–0.46)0.30 (0.17–0.50)
    BP, mm Hg, mean±SD, mm Hg
     Clinic systolic BP125±23122±20
     Clinic diastolic BP77±1376±13
     Home systolic BP129±20126±18
     Home diastolic BP77±1376±12
    Laboratory tests, n (%) in range
     Hemoglobin (10.0–12.0 g/dl)47 (53)53 (57)
     Potassium (3.5–5.1 mEq/L)77 (88)80 (87)
     Phosphate (<4.6 mg/dl)29 (39)27 (34)
    Patient-reported outcome measures, mean±SD
     Hospital Anxiety and depression scale8.7±5.89.0±6.3
     Veterans Rand-12 physical component score39.6±10.440.2±9.6
     Veterans Rand-12 mental component score50.2±9.249.8±10.7
     EQ-5D0.8±0.20.8±0.2
    Use of technology, n (%)
     Personal computer75 (84)77 (83)
     Smartphone53 (60)56 (60)
     Cellphone43 (48)42 (45)
     Tablet49 (55)53 (57)
     Home BP monitor66 (74)63 (68)
    Use of medication management tools, n (%)
     Nothing30 (34)25 (27)
     Blister package9 (10)9 (10)
     Dosette box31 (35)35 (38)
     Handwritten list12 (14)9 (10)
     Self-generated computer list8 (9)7 (8)
     Pharmacy-generated list10 (11)17 (18)
    • REALM, Rapid Estimate of Adult Literacy in Medicine; IQR, interquartile range; HTN, hypertension; EQ-5D, EuroQol-5 Dimension.

    • ↵a There were no significant differences between the two groups for any variable.

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    Table 2.

    Medication discrepancy outcomes at exit by study group

    OutcomeeKidneyCare (n=82)MyMedRec (n=83)P value
    Primary outcome
     All medications
      Discrepancy rate, median (IQR)0.45 (0.33–0.63)0.67 (0.40–1.00)0.001
      Change in discrepancies from entry, mean±SD0.13±0.270.30±0.410.007
      Number of discrepancies per patient, median (IQR)5 (3–7)6 (4–10)0.01
      Total number of medications per patient, median (IQR)11 (8–14)11 (8–13)0.95
    Secondary outcomes
     Proportion of patients with ≥1 clinically relevant medication discrepancies, n (%)62 (70)70 (75)0.30
    Clinically relevant medications
     Discrepancy rate, median (IQR)0.33 (0.20–0.46)0.50 (0.32–0.72)<0.001
     Change in discrepancies from entry, mean±SD.0.02±0.290.18±0.430.004
     Number of clinically relevant discrepancies per patient, median (IQR)3 (2–4)4 (2–6)0.001
     Number of clinically relevant medications per patient, median (IQR)8 (6–11)8 (6–11)0.97
    Severity of clinically relevant medication discrepanciesb, mean±SD
     All categories2.66±2.194.16±3.700.004 0.61 (0.48–0.78)a
     Category D or higher1.66±1.883.08±3.31<0.001 0.52 (0.38–0.70)a
     Category E or higher0.94±1.251.65±1.830.002 0.54 (0.39–0.76)a
     Category E1 or higher0.27±0.540.63±0.910.002 0.40 (0.24–0.66)a
    • IQR, interquartile range.

    • ↵a Rate ratio (95% confidence interval).

    • ↵b Severity on the basis of National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) Index.

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    Table 3.

    Secondary outcomes at exit by study group

    VariableeKidneyCarenMyMedRecNP Value
    BP, mm Hga
     Clinic BP, mean±SD
      6 mo systolic BP−0.16±20.182−1.21±18.9770.78
      Diastolic BP−0.26±11.182−1.78±9.9770.24
      12 mo systolic BP−1.81±22.283−2.61±19.4820.78
      Diastolic BP−1.52±12.983−1.49±10.3820.91
     Home BP, mean±SD
      12 mo systolic BP−2.22±16.9800.96±14.1620.33
      Diastolic BP−0.26±8.9800.10±7.1620.92
    Laboratory, mean±SDa
     Hemoglobin, g/dl0.01±1.29740.25±1.11660.31
     Potassium, mEq/L−0.1±0.673−0.1±0.7670.71
     Phosphate, mg/dl0.03±1.3661−0.19±1.49530.42
    Patient-reported outcome, mean±SDa
     HADS−0.1±4.6810.5±5.8700.33
     VR12-PCS−0.1±9.8830.2±7.6790.88
     VR12-MCS−1.1±8.983−0.7±10.3790.46
     EQ-5D0.8±0.1820.8±0.2770.41
    Patient satisfaction: Mobile app data usage
     Per-person totals of BP measurements over study period, median (IQR)194 (94–338)89102 (28–182)93<0.001
     Number of patients with a gap >60 d between consecutive BP readings over follow-up, n (%)13 (15)8963 (68)93<0.001
    • HADS, Hospital Anxiety and Depression Scale; VR12-PCS, Veterans Rand-12 Physical Component Score; VR12-MCS, Veterans Rand-12 Mental Component Score; EQ-5D, EuroQol-5 Dimension; IQR, interquartile range.

    • ↵a Mean±SD change from baseline to exit, with positive numbers indicating an increase and negative a decrease.

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Clinical Journal of the American Society of Nephrology: 16 (4)
Clinical Journal of the American Society of Nephrology
Vol. 16, Issue 4
April 07, 2021
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Digital Applications Targeting Medication Safety in Ambulatory High-Risk CKD Patients
Stephanie W. Ong, Sarbjit V. Jassal, Eveline C. Porter, Kyoyoon K. Min, Akib Uddin, Joseph A. Cafazzo, Valeria E. Rac, George Tomlinson, Alexander G. Logan
CJASN Apr 2021, 16 (4) 532-542; DOI: 10.2215/CJN.15020920

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Digital Applications Targeting Medication Safety in Ambulatory High-Risk CKD Patients
Stephanie W. Ong, Sarbjit V. Jassal, Eveline C. Porter, Kyoyoon K. Min, Akib Uddin, Joseph A. Cafazzo, Valeria E. Rac, George Tomlinson, Alexander G. Logan
CJASN Apr 2021, 16 (4) 532-542; DOI: 10.2215/CJN.15020920
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