Table 2.

Summary of 14 published studies evaluating mobile medical apps in the period January 2010 to December 2015

Author, (Reference), Year	Design Country Time Frame	Sample Type of Diabetes Mean Age	Platform/Name I and C Groups	Outcome Measures	Main Results
Barnard,16 2012	Survey United Kingdom 4–12 wk	n = 1412 T1DM <18–70 y	Glucose meter app: Accu-Chek Aviva Expert Survey 270 hospitals Patients using Accu-Chek Aviva Expert BG meter for at least 4 wk Bolus advisor with integrated BG meter Electronic log book		588 (41.6%) responded 80% (n = 456) ↑ ability to act on SMBG data ↑ of 28% in frequency of checking BG 4–5 times/d (n = 257–331) ↑ of 42% in frequency of checking BG >6 times/d (n = 133–189) ↓ fear of hypoglycemia
Bergenstal et al,18 2012	Observational United States 3 mo	n = 46 T1DM and T2DM (T1DM 43%)	Glucose meter app: DIGS by Hygeia DIGS provides weekly insulin dose adjustment based on sugar patterns 3 groups: I: T1DM on basal bolus II: T2DM on basal bolus III: T2DM on twice-daily premixed insulin	Primary: % dose adjustments approved by study team Secondary: ↓ in mean BG A1C	99.9% DIGS adjustments approved ↓ A1C 0.5% (P<.05)
Charpentier,10 2011	RCT TeleDiab 1 France 6 mo	n = 180 T1DM 33 y	Smartphone app: Diabeo Diabeo software with basal and prandial insulin dose advisor 3 groups (G1, G2, G3) C: G1 paper log book with in-person visit at 3 and 6 mo I: 2 groups G2 Smartphone with electronic logbook with in-person visit at 3 and 6 mo G3 Smartphone with electronic logbook 1 teleconsultation every 2 wk and visit at 6 mo	Primary: A1C	A1C ↓ 0.91 G3–G1 (P≤.001) A1C ↓ 0.67 G2–G1 (P≤.001) No difference in hypoglycemia G1 and G2 had 5-h ↑ hospital appointments
Franc,12 2012	Observational France 4 mo	n = 35 T1DM 39 y	Smartphone app: Diabeo 1 group Diabeo Software on smartphone with electronic logbook Insulin bolus calculator using BG, CHO, and physical activity to suggest mealtime insulin dose Algorithm calculated a 30% to 50% reduction in prandial insulin for the meal closest to the physical activity based on intensity of activity reported.	Primary: mean BG	Significant ↑ in 2-h PPBG after physical activity (P<.042) Returned to FBS/premeal levels by next meal (P = .29) No difference in hypoglycemia with or without physical activity
Franc,11 2014	Post hoc analysis of TeleDiab 1 France 6 mo	n = 180 T1DM 33 y	Smartphone app: Diabeo See description of TeleDiab 1 Charpentier, 2011 G1 high system users (greater than the median) G2 low system users (less than the median)	Primary: high users vs low users on A1C and impact of teleconsultation	High users had lower A1C at baseline (P = .008) and more familiar with CHO counting (P≤.001) High users ↓ A1C 0.05% with no difference between G2 and G3 (P = .89) Low users ↓ A1C 0.93% in G3 vs 0.46% in G2 (P = .084)
Javitt,21 2013	Retrospective	n = 141 T1DM and T2 DM GDM	Glucose meter app: Telcare I: used Telcare for bolus calculations and call center monitoring for those with high or low BG C: did not use product	Primary: change in allowed claims	↓ for $1600/y per person who used the product
Quinn,9 2011	Cluster RCT United States 12 mo	n = 163 T2DM 53 y	Smartphone app: Blue Star WellDoc C: UCI: 3 groupsG1 Mobile phone hand enter BG, CHO, medications Automated real-time feedback with virtual coaching G2: No analysis of log book data No PCP Web access to log book G3: PCP access to log book data via Web portal G4: SMBG real-time analysis with feedback using computerized decision support PCP receives summary via fax or email Fax or email to review an analyzed report of all patients	Primary: A1C	A1C ↓ 1.2% G4–UC (P<.001)
Quinn,8 2015	Observational United States 1 mo	n = 7 T2DM 70 y	Smartphone app: Blue Star WellDoc 1 group Entered glucose and self-care data and received automated feedback	Primary: self-efficacy SF-36 Depression	Trends in improvement in self-efficacy (P = .2), SF-36, and depression (P = .043)
Rossi,14 2010	RCT Italy United Kingdom Spain 6 mo	n = 130 T1DM 36 y	Smartphone app: DID I: DID software installed in patient’s smartphone that works as a CHO/insulin bolus calculator Data sent to MD every 1–3 wk, reviewed, and new regimen texted to the patient C: received traditional education on CHO counting and bolusing (were not previously educated)	Primary: A1C Secondary: QOL Satisfaction with Rx Hypoglycemia	No difference in A1C No severe hypoglycemia in either group Improved in some mental health components Improved treatment satisfaction (P = .04)
Rossi,15 2013	RCT Italy 6 mo	n = 127 T1DM 37 y	Smartphone app: DID I: DID software installed in patient’s smartphone that works as a CHO/insulin bolus calculator Data sent to MD every 1–3 wk, reviewed, and new regimen texted to the patient C: received traditional education on CHO counting and bolusing (were not previously educated)	Primary: A1C Secondary: glucose variability Mean daily insulin dose Hypoglycemia	No difference in A1C (A1C ↓ 0.5% both groups, P = .73) I: lower mean insulin dose (P = .04) No reduction in glycemic variability 86% decrease in severe hypoglycemia (requiring third-party assistance)
Skrovseth,13 2015	RCT Norway 6 mo	n = 30 T1DM 40 y	Smartphone app: DD DD is a bolus calculator in its basic version. Dia-stat module can be added to allow a wireless transfer of BG values via Bluetooth and feedback module with BG graphs, trends I: DD 1 Diastat C: DD	Primary: number of hypoglycemia and hyperglycemia events Secondary: A1C	No difference in A1C or out-of-range BG All patients had ↓ A1C 0.6% (P = .001)
Sussman,19 2012	Observational United States 1 d	n = 205 T1DM and T2DM (T1DM: 48%) 51 y	Glucose meter app: FreeStyle InsuLinx 1 group 2 modes of operation: easy mode with fixed doses of rapid-acting insulin; advanced mode for patients who count CHO and calculate insulin doses Subjects had to calculate 2 prandial insulin doses: manually and via FreeStyle InsuLinx Compared accuracy of bolus calculation	Primary: frequency of insulin errors	63% (n = 256) manually calculated doses were incorrect 10 times fewer errors using meter (P<.0001)
Ziegler,17 2013	RCT United Kingdom Germany 6.5 mo	n = 193 T1DM (93%) 42 y	Glucose meter app: Accu-Chek Aviva Expert C: Enhanced UC Standard glucose meter, manual bolus calculation per individualized parameters 7-point BG profiles over 3 d Clinic visits focusing on diabetes care BG data downloaded for therapy adjustments I: Accu-Chek Aviva Expert meter with integrated bolus advisor to calculate insulin dosages 7-point BG profiles over 3 d BG data downloaded for therapy adjustments Prandial and correction bolus recommendations based on BG, CHO intake, and individualized therapy	Primary: A1C Secondary: hypoglycemia	↓ A1C 0.2% (I – UC) (P<.05 1 sided) 56% (C) vs 34.4% (I) had >0.5% A1C reduction (P<.01) Improved treatment satisfaction (11.4% vs 9%; P<.01) ↑ hypoglycemia in I compare to UC (P<.05)
Neil,20 2014	Observational United States 6 mo	n = 203 T1DM and T2DM (T1DM:64%) Age not reported	Glucose meter app: FreeStyle InsuLinx One group 2 modes of operation: easy mode with fixed doses of rapid-acting insulin; Advanced mode for patients who count CHO and calculate insulin doses	Primary: A1C Secondary: Confidence	↓ A1C 0.17% (P = .033) ↑ confidence in insulin calculation(P<.01)

Abbreviations: C, control; DD, Diabetes Diary; DID, Diabetes Interactive Diary; DIGS, Diabetes Insulin Guidance System; FBS, fasting blood sugar; I, intervention; PCP, primary care physician; PPBG, postprandial blood glucose; SF-36, Short Form 36; SMBG, self-monitoring BG; UC, usual care.