Sage Journals: Discover world-class research

Abstract

Background:

Development of coordinated management approaches is important to facilitate self-care in people with diabetes (PwD). Gaining a better understanding of suboptimal insulin use is key in this endeavor. This review aimed, for the first time, to systematically identify and narratively summarize real-world evidence on the extent of suboptimal insulin use (missed and mistimed insulin) in PwD.

Methods:

A systematic literature search of MEDLINE, EMBASE, and the Cochrane Database of Systematic Reviews identified studies reporting on missed and mistimed insulin dosing.

Results:

From 3305 studies, 37 publications reporting on 30 unique studies that involved 58,617 PwD were included. Studies were conducted across 12 different countries and most employed cross-sectional surveys. Observations regarding missed and mistimed insulin doses were reported in 25 and 10 studies, respectively. PwD reported missing insulin doses, but rates varied due to differences in reporting methods, participant populations, and insulin regimens. The association between missed dosing and glycemic control was evaluated in ten studies in which the authors reported lower glycated hemoglobin (HbA1c) levels in PwD who did not omit insulin. The proportion of PwD reporting mistiming of insulin was in the range of 20–45%, depending on the study; this was associated with higher rates of hypoglycemia and higher HbA1c as reported by study authors. Reasons for suboptimal insulin use were multifactorial, occurring due to disrupted daily routines, social situations, and hypoglycemia avoidance.

Conclusions:

This review suggests that suboptimal insulin use is widespread and that PwD using insulin may still be struggling with disease management. There is an unmet need for better integrated support in managing the complexities of insulin therapy and for the development of systems (e.g. digital solutions) that empower people to take control of insulin-treated diabetes.

Introduction

Over the past several decades, the management of diabetes has seen significant improvements through advances in drug development and device technology. Yet despite all the innovations, diabetes remains a significant human and economic burden.¹ In general, levels of glycemic control do not appear to have improved in recent years or have even deteriorated.^2
–4 Furthermore, evidence suggests that many insulin-treated people with diabetes (PwD) are still failing to reach glycemic targets.^5

–9 This trend of inadequate glycemic control is already having a detrimental impact, with national statistics and epidemiological studies demonstrating that rates of diabetes-related complications have increased in recent years.¹⁰

Failure to achieve glycemic control at a population level has been linked with the inherent complexities of medication taking.¹¹ With respect to insulin treatment, it is important that PwD do not miss doses, take insulin at suitable times, and take the appropriate dose accounting for glucose measurements, carbohydrate intake, and physical activity. Successful disease management is, therefore, highly challenging for insulin-treated individuals (who must engage in multiple time-consuming and complex behaviors while trying to live as normal a life as possible) and for their physicians.¹² Unsurprisingly, inadequate management of prescribed insulin regimens has been widely reported.^13
–15

Understanding the extent, impact, and possible causes of suboptimal insulin use is key for the development of coordinated management approaches that integrate the benefits of monitoring, education, and clinical support to facilitate self-care among PwD. The current systematic literature review was therefore undertaken to identify and narratively summarize evidence on the extent of suboptimal insulin use with respect to missed and mistimed doses in PwD in real-world practice.

Materials and Methods

The systematic literature search was conducted according to a reproducible protocol that described the proposed approach, objectives, search strategy, study selection criteria, methods for data extraction and synthesis, and outcomes of interest that were specified a priori. This article is a review and analysis of previously published studies and does not include any new studies on human or animal subjects performed by any of the authors, therefore ethics approval was not required

Search strategy

Journal articles published in English between January 2005 and February 2020 were identified from searches of MEDLINE, EMBASE, and the Cochrane Database of Systematic Reviews. To capture recent relevant studies that might not yet be published, abstract books were electronically searched on EMBASE from relevant congresses held during 2019 as follows: all congresses of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR), the European Association for the Study of Diabetes (EASD), and the American Diabetes Association (ADA). In addition, the abstract book from the Advanced Technologies and Treatments for Diabetes Conference (ATTD), which was not indexed on EMBASE, was hand-searched for relevant studies. A hand-search of the reference lists of eligible studies identified in the main review was also conducted.

A search strategy was developed for each database to understand suboptimal insulin use in PwD (search strings for each database are provided in the Supplementary Tables S1–S3. The main search strategy consisted of three concepts: diabetes mellitus, insulin, and suboptimal dosing outcomes. Terms for nonspecific “insulin” and insulin brand names were those as provided at: https://www.drugs.com/drug-class/insulin.html. The strategy excluded animal studies using a standard algorithm.

A gray search of the literature was undertaken based on the authors' own knowledge of the field and review of company websites based on known congress presentations.

Inclusion criteria

Study inclusion and exclusion criteria as related to patient population, interventions, outcomes, and study type are given in Table 1.

Table 1.

Study Eligibility Criteria

Study characteristics	Eligible	Ineligible
Patient population	Children and adult PwD	Gestational DM PwD with eating disorders or psychiatric disorders^a
Intervention	Insulin injectable treatment Insulin pumps Insulin infusions	Other injectable treatments for DM Patients without a planned insulin regimen Oral treatments
Outcomes^b	Missed insulin doses Mistimed insulin doses^c Reasons for suboptimal insulin dosing behavior in PwD (excluding specific populations)	Studies that do not report on missed or mistimed insulin doses Other outcomes
Study type	Real-world cross-sectional Real-world case–control study Real-world cohort study Administrative or claims database study Real-world EHR study Registry study representing real-world clinical practice Questionnaires and surveys relating to real-world clinical practice Qualitative research	Nonobservational studies that do not reflect real-world clinical practice Clinical trials Case studies Pragmatic or RCTs Utility studies Preference or satisfaction studies based on hypothetical profiles Reviews Editorials/comments Economic evaluations Methods papers

Exclusion criteria further refined based on cluster of studies found with these comorbid conditions that was deemed out of scope based on the study aim and eligibility.

Clinical outcomes were only reported if included in studies that reported suboptimal insulin dosing behavior.

Mistimed doses defined as insulin doses not taken at the specified times and so includes delayed administration (e.g., postprandial) and irregular dose timing.

DM, diabetes mellitus; EHR, electronic health record; PwD, people with diabetes; RCT, randomized controlled trial.

Article selection

Results obtained using the search strategy were assessed independently by two reviewers using a two-phase approach. Initial screening involved a broad review of titles and/or abstract of results to identify studies meeting or possibly meeting eligibility criteria. Studies identified as being potentially eligible were subject to in-depth full-text review. Articles excluded at this stage were assigned an exclusion code and reported in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. Any discrepancies between reviewers were discussed until consensus was reached or by involving a third reviewer.

Data extraction and reporting

Data were extracted from the included full-text articles. The following fields were included country of conduct, study objective, design, setting, and duration, methods of data collection, insulin dosing behavior captured, and patient population (number, diabetes type, age, and gender). A data extraction table was populated by one team member and quality checked by a second. Synthesis of findings was narrative.

Results

Study selection

In total, the literature research resulted in the selection of 37 full journal publications describing 30 unique studies. Four different studies yielded 11 separate publications: the first Global Attitudes of Patients and Physicians in Insulin Therapy Survey (GAPP1) contributed data to three separate publications^16
–18; the GAPP2 survey contributed data to four publications^19

–22; a U.S. cross-sectional survey (using Harris Interactive Chronic Illness Panel) regarding the burden of insulin therapy contributed data to two publications^23,24; and a Swedish qualitative study contributed data to two publications.^25,26 No relevant congress abstracts were identified. The study selection process is shown in the PRISMA flow diagram (Fig. 1).

FIG. 1.

PRISMA flow diagram. ^aArticles describe data from 30 unique studies. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; RWE, real-world evidence.

Study characteristics

Detailed study characteristics are given in Supplementary Table S4 in the Supplementary Data. Included articles were published between 2005 and 2019. Studies were conducted in 12 different countries, with the United States being the most represented (n = 15 studies); four studies were multinational, and one was conducted in Canada and the United States. Most studies employed cross-sectional surveys that were administered in a variety of ways including online, face-to-face, or through telephone interview. Each survey was administered at a point in time and requested information regarding insulin dosing irregularities over a specified retrospective period, which generally varied from 1 week to 3 months across studies. A total of 58,617 PwD were included in the 30 unique studies. People with type 1 diabetes (T1D) were included in 17 unique studies (n = 48,554) and those with type 2 diabetes (T2D) in five unique studies (n = 6333). A mixed population of T1D and T2D were included in eight unique studies (n = 3730) and health care professional responses regarding the insulin dosing behaviors of their PwD were solicited in three studies that involved 2473 health care professionals (HCPs) in total. Observations regarding missed insulin doses were reported in 25 studies (32 publications) and on mistimed insulin doses in 10 studies (14 publications). Missed or mistimed dosing was reported with bolus insulin in 11 studies, basal insulin in 3 studies, and both basal and bolus insulin in 3 studies. Nearly half of the included publications did not specify insulin when reporting on suboptimal insulin dosing behaviors.

Missed insulin doses

Studies in T1D

Evidence for missed insulin dosing was reported in 16 studies in people with T1D. All studies identified reported various degrees of missed dose behavior, with rates varying considerably on account of differences in reporting methodologies and time ranges, patient population. For example, in one study it was reported that 56.2% of adults missed at least one bolus insulin dose in the last month,²⁷ another demonstrated that 21.4% missed at least one dose (insulin type not specified) in the last week,²⁸ and a third study reported that 12% missed at least one bolus dose per day.²⁹ Key findings from studies in T1D are given in Table 2. Some studies in T1D involved adolescents (13 to <18 years) or emerging adults (18 to <26 years), and these demonstrated that there were differences in the frequency of missed insulin doses according to age (Table 2). Adolescents/emerging adults were more likely to miss bolus doses compared with younger children and compared with older individuals (≥45 years).^29,33 Insulin dose omission was also commonly reported among children and adolescents with T1D who were using continuous subcutaneous insulin infusions (CSII), with frequent missing of bolus insulin at mealtimes and when snacking (Table 2).^37
–39

Table 2.

Key Findings From Studies Reporting Missed Insulin Doses

Author (year)	Key study findings
Studies in T1D
Datye et al. (2018)²⁹	19% of PwD report missing ≥1 bolus dose/week; of these, 64%, 20%, and 4% missed doses weekly on 1–2 days, 3–4 days, and 5–6 days, respectively, and 12% missed ≥1 dose/day; adolescents and young adults (≥13 years) more likely to miss bolus insulin doses vs. children
Giani et al. (2017)³⁰	38% of PwD (8–17 years) missed insulin doses; more frequent use of CGM was associated with lower likelihood of omitting insulin (P = 0.02)
Hessler et al. (2017)³¹	PwD missed 13% of insulin bolus doses in the prior 2 weeks
Joiner et al. (2018)³²	42.7% of adolescents and young adults missed insulin doses at least once per week; 18.1% missed doses ≥3 times/week
McCarthy and Grey (2018)³³	≤3% of PwD missed ≥1 insulin dose/day; emerging adults (18–24 years) more likely to miss doses vs. older age groups
Mukama et al. (2013)³⁴	36% of children missed >6 doses of insulin
Mulvaney et al. (2012)³⁵	Adolescents reported missing 20.4% of insulin doses over a 10-day period
Mulvaney et al. (2019)³⁶	Bolus doses missed in 4% of 1472 mealtime assessments over 1 month
Olinder et al. (2009)³⁷	38% adolescents on CSII missed >15% of bolus doses scheduled the previous day
Pańkowska et al. (2005)³⁸	10% of children and adults on CSII missed ≥1 missed insulin bolus/day over a 2-week period
Smythe et al. (2018)²⁷	56.2% and 39.5% of PwD missed >1 bolus or basal insulin dose/month, respectively
Trief et al. (2014)²⁸	21.4% of PwD reported missing ≥1 insulin dose/week
Vanderwel et al. (2010)³⁹	48.2% CGM excursions involved a snack with missed insulin bolus in adolescents on CSII
Studies in T2D
Ampudia-Blasco et al. (2014)¹⁹	1% of PwD (Spanish GAPP2 cohort) reported missing basal insulin doses in the previous 30 days for a mean of 1.0 occasion; 69% missed basal insulin doses unintentionally
Brod et al. (2012)²⁰	22% of PwD (global GAPP2 cohort) missed ≥1 basal insulin dose in the previous 30 days, with 17% missing insulin ≥5 times; 83% missed doses were unintentionally
Leiter et al. (2014)²¹	23% of PwD (Canadian GAPP2 cohort) missed ≥1 basal insulin dose in the past 30 days for a mean of 3.2 missed doses, and 2.6% missed a dose >5 times; 87% missed doses unintentionally
Mashitani et al. (2015)⁴⁰	22.9% of PwD reported not always taking their insulin as scheduled
Munro and Barnett (2014)²²	16% of PwD (UK GAPP2 cohort) missed ≥1 basal insulin dose in the previous 30 days for a mean of 1.8 missed doses, and 8% missed a dose ≥5 times; HCPs reported that 78% of their PwD missed ≥1 basal insulin dose in a typical month
Yavuz et al. (2015)⁴¹	20.3% of PwD missed an insulin dose at least once per week (more frequent with basal-bolus regimens, 61.3%); 9.4% omitted an insulin dose for >1 day
Studies in T1D and T2D
Brod et al. (2014)⁴²	PwD forgot when their last dose of insulin was taken on 1.9 occasions in the past month
Gerada et al. (2017)⁴³	8.2% of PwD reported missing insulin doses
Harashima et al. (2017)¹⁸	44% of PwD (Japanese GAPP1 cohort) missed insulin or failed to take insulin as prescribed for a mean of 2.94 injections/month; 66% of physicians believed PwD failed to take insulin as prescribed and that basal insulin doses were missed/not taken as prescribed on 6.18 days in the past month
Olamoyegun et al. (2018)⁴⁴	27.2% of PwD missed insulin doses intentionally (5.2% often missed) and 20.2% missed doses unintentionally (2.8% often)
Peyrot et al. (2010)²⁴,^a	57% of PwD skipped insulin injections they knew they should take
Peyrot et al. (2012)¹⁶	33.2% of PwD (global GAPP1 cohort) missed insulin or did not take as prescribed on ≥1 day in the past month for a mean of 3.3 days; 72.5% of physicians reported that their typical PwD did not take insulin as prescribed, with omission/non-adherence occurring on 4.3 (basal) and 5.7 days/month (bolus)
Peyrot et al. (2012)¹⁷,^b	34.6% of PwD (global GAPP1 cohort) reported ≥1 day of insulin omission/nonadherence in past month, for a mean of 3.41 days/month
Rubin et al. (2009)²³	20% of PwD reported skipping insulin doses sometimes or often; 80% of HCPs reported that PwD skipped insulin doses sometimes or often

Same patient cohort as Rubin et al.²³ but additional data reported in the publication.

Appears to be same patient cohort as Peyrot et al.¹⁶ but some differences in the data reported.

CGM, continuous glucose monitoring; CSII, continuous subcutaneous insulin infusion; GAPP, Global Attitudes of Patients and Physicians in Insulin Therapy for Diabetes Mellitus; HCP, health care professional; PwD, people with diabetes; T1D, type 1 diabetes; T2D, type 2 diabetes.

Studies in T2D

Four studies (n = 7 publications) reported missed insulin dosing among people with T2D, with much of the data deriving from the GAPP2 study) (Table 2). For example, missing at least one dose of basal insulin in the previous 30 days was reported in 16%, 22%, and 23% of the United Kingdom, global, and Canadian GAPP2 cohorts, respectively,^20
–22 although this was reported in only 1% of the Spanish cohort possibly because of a shorter disease duration at baseline in these individuals compared with other countries.¹⁹ Most PwD participating in the GAPP2 study missed insulin doses unintentionally (Table 2).^19
–21 Similar rates of insulin omission were reported in the other included studies.^40,41 A single study compared insulin regimens and found that more PwD on a basal-bolus insulin missed insulin doses compared with those on premix or basal insulin (61.3% vs. 22.7% and 15.9%, respectively).⁴¹

Studies in types 1 and 2 diabetes

Five studies (n = 8 publications) that described results from a mixed population of PwD also indicated that insulin omission occurred in a substantial proportion of participants (Table 2). For example, in the GAPP1 survey 44% and 33.2% of PwD in the Japanese and multinational cohorts, respectively, omitted insulin or did not take insulin as prescribed over the previous month.^16,18 Physicians included in GAPP1 and in another U.S. survey indicated that a high proportion of PwD missed insulin doses or failed to take insulin as prescribed (Table 2).^16,18,23 Omission of insulin was reported to occur both intentionally and unintentionally in studies of mixed diabetes populations,⁴⁴ with forgetfulness emerging as a key theme in a qualitative analysis.⁴²

Association between missed doses and clinical outcomes

Eleven studies (n = 13 publications) reported on the association between missed insulin doses and clinical outcomes; key findings are given in Table 3. Missed insulin doses were consistently reported to be associated with higher HbA1c levels in people with T1D.^{27,29,33,37,38,45,46} Similarly, in the GAPP2 study in people with T2D, HCPs indicated that missed insulin doses were associated with negative clinical effects, reporting that ∼3 to 4 missed basal insulin doses per month significantly impacted glycemic control.^19
–21 Although data are more limited, it was suggested by two studies that missed insulin doses may be negatively associated with health-related quality of life (QoL) in adolescents with T1D³⁷ and adults with T2D.⁴⁰

Table 3.

Key Findings on the Impact of Missed Insulin Doses on Clinical Outcomes

Author (year)	Key study findings
Studies in T1D
Glycemic control
Campbell et al. (2014)⁴⁵	Fewer missed bolus doses in PwD with HbA1c <7.0% vs. ≥9.0% (P < 0.001); PwD were 24.5-fold more likely to have HbA1c <7.0% if insulin doses were never missed vs. missed ≥3 times per week
Datye et al. (2018)²⁹	Missing ≥1 bolus dose/week was associated with higher HbA1c vs. missing <1 dose/week (P < 0.001)
McCarthy and Grey (2018)³³	Missed insulin doses were independently associated with HbA1c ≥7.0% in all age groups except ≥65 years
Olinder et al. (2009)³⁷	Higher HbA1c in adolescents who missed >15% of bolus doses vs. missed ≤15% (P < 0.001)
Pańkowska et al. (2005)³⁸	HbA1c higher in PwD who missed insulin bolus doses vs. those who did not miss doses (P < 0.05)
Simmons et al. (2013)⁴⁶	More PwD with HbA1c ≥8.5% missed ≥1 insulin dose/week vs. PwD with HbA1c <6.5% (43.2% vs. 6.1%)
Smythe et al. (2018)²⁷	More PwD with HbA1c >7.0% missed bolus or basal insulin >1/month vs. PwD with HbA1c ≤7.0% (P = 0.034 and P = 0.016, respectively)
Vanderwel et al. (2010)³⁹	BG >180 mg/dL was more common after snacks with missed insulin bolus vs. those with an insulin bolus (P < 0.0001), and higher change in glucose-adjusted mean (P < 0.001) and average rate of change from baseline to excursion peak (P < 0.005)
HRQoL
Olinder et al. (2009)³⁷	Perceived HRQoL (DISABKIDS) was lower in adolescents who missed >15% of doses (diabetes ruled their days more: P ≤ 0.038) and treatment satisfaction was lower (P = 0.029)
Other
Datye et al. (2018)²⁹	Missing ≥1 bolus dose/week was associated with ≥1 diabetic ketoacidosis event in the past 3 months vs. missing <1 dose/week (P < 0.001)
Studies in T2D
Glycemic control
Ampudia-Blasco et al. (2014)¹⁹	4.3 missed basal doses in the previous 30 days were estimated by HCPs to have a significant impact on glucose control
Brod et al. (2012)²⁰	4.3 missed basal doses in past 30 days were estimated by HCPs to have a significant impact on glucose control
Leiter et al. (2014)²¹	3.6 missed basal doses in the past 30 days were estimated by HCPs to have a clinically significant impact
Mashitani et al. (2015)⁴⁰	Lower HbA1c levels in PwD who always took insulin as scheduled vs. those who injected as scheduled >50% of the time or not always (7.7% vs. 9.3% and 8.5%, respectively; P < 0.001)
HRQoL
Mashitani et al. (2015)⁴⁰	HRQoL (DTR-QOL) was lower in PwD who did not always take insulin as scheduled vs. those who did take doses as scheduled (P < 0.0001)
Other
Stephenson et al. (2018)⁴⁷	More PwD with poor medication adherence (MMAS <6) missed ≥1 basal insulin dose in a typical month vs. those with high adherence (MMAS = 8) (79.3% vs. 12.6%)

BG, blood glucose; DTR-QOL, diabetes therapy-related quality of life; HbA1c, glycated hemoglobin; HCP, health care professional; HRQoL, health-related quality of life; MMAS-8, 8-item Morisky Medication Adherence Scale; PwD, people with diabetes.

Mistimed doses

Key findings from the 10 studies that reported mistiming of insulin doses are described in Table 4. Three studies evaluated the delayed administration of bolus insulin specifically and demonstrated that ∼25% to 30% of PwD (T1D or T2D) administer insulin boluses during or after meals contrary to guideline recommendations.^48,49,51 In the GAPP2 study, mistiming of basal insulin in people with T2D was defined as administration ±2 h from the prescribed time. The rate of basal dose mistiming ranged from 20% to 26% in the previous 30 days across the United Kingdom, global, and Canadian cohorts.^20
–22 Similar rates of mistimed basal doses (>2 h outside agreed dose time) were reported among people with T1D in a Japanese study although rates were somewhat higher in people with T2D (Table 4).⁵⁰ Although rates of mistimed insulin dosing were not specifically reported in the GAPP1 study, both PwD and physicians indicated that dose timing was a key difficulty with respect to insulin self-management (Table 4).^16,18

Table 4.

Key Findings From Studies Reporting Mistiming of Insulin Doses

Author (year)	Key study findings
Studies in T1D
Peters et al. (2017)⁴⁸	32% of PwD reported postprandial (suboptimal) insulin bolus dosing; higher rates reported in children
Simmons et al. (2013)⁴⁶	More PwD with HbA1c ≥8.5% failed to administer bolus insulin regularly vs. PwD with HbA1c <6.5% (6% vs. 2%) and were more likely to administer bolus insulin during or after a meal (27% vs. 14%) and less likely to administer boluses before a meal as generally recommended (54% vs. 69%)
Studies in T2D
Ampudia-Blasco et al. (2014)¹⁹	3% of PwD (Spanish GAPP2 cohort) mistimed basal insulin doses in the previous 30 days on a mean of 2.3 occasions; 60% mistimed doses unintentionally
Brod et al. (2012)²⁰	24% of PwD (global GAPP2 cohort) mistimed ≥1 basal insulin dose for a mean of 4.2 occasions in the past 30 days; 82% mistimed doses unintentionally
Leiter et al. (2014)²¹	26% of PwD (Canadian GAPP2 cohort) mistimed ≥1 basal insulin dose, 6.8% mistimed ≥5 doses, and mean number of mistimed doses was 4.8 in the past 30 days; 82% reported that mistiming was unintentional on the last occasionHCPs reported that 40% of their PwD mistimed ≥5 basal insulin doses in a typical month
Munro and Barnett (2014)²²	20% of PwD (UK GAPP2 cohort) mistimed their basal insulin dose in the past 30 days, with 21% reporting mistiming of ≥5 doses; mean number of mistimed doses was 3.694% of HCPs reported that their PwD mistimed ≥1 basal insulin dose in a typical month
Schaper et al. (2017)⁴⁹	24% of PwD administered bolus insulin during/after eating
Studies in T1D and T2D
Brod et al. (2014)⁴²	PwD reported forgetting to take insulin at the right time on a mean of 2.6 occasions in the past month
Gerada et al. (2017)⁴³	91.8% of PwD failed to administer insulin at a similar time each day
Harashima et al. (2017)¹⁸	33% of PwD (Japanese GAPP1 cohort) and 49% of physicians reported that taking insulin at the prescribed time or with meals each day was a key difficulty of insulin self-management
Nishimura et al. (2017)⁵⁰	21.1% and 44.8% of people with T1D or T2D, respectively, took basal insulin doses >2 h outside agreed dose time
Peyrot et al. (2012)¹⁶	27.6% of PwD (global GAPP1 cohort) and 54.5% of physicians reported that the most common difficulty of insulin management was taking doses at the prescribed time or with meals every day; 18.6% and 11.2% of physicians said PwD were successful in taking basal insulin at the same time each day or taking bolus/premixed as prescribed, respectively
Tamborlane et al. (2017)⁵¹	31.6% of PwD took bolus insulin during or after meals contrary to recommendations
Trief et al. (2016)⁵²	21.7% of PwD reported sometimes/never taking insulin at the correct time in the past month

HCP, health care professional; PwD, people with diabetes.

Association between mistimed doses and clinical outcomes

Five studies (n = 7 publications) also provided some insights regarding the association of mistimed dosing with clinical outcomes (Table 5). For example, rates of hypoglycemia were higher among PwD who dosed bolus insulin postprandially compared with those who dosed during or premeal.^48,49,51 In addition, glycemic control was reported to be better among PwD who dosed bolus insulin regularly and administered their dose premeal.^46,49 Findings from the GAPP2 study also demonstrated the importance of dosing insulin at the correct time with respect to clinical outcomes, HCPs estimated that 5.7–6.2 mistimed basal doses were associated with a significant impact on glycemic control over the previous 30 days (Table 5).^19
–21

Table 5.

Key Findings on the Impact of Mistimed Insulin Doses on Clinical Outcomes

Author (year)	Key study findings
Studies in T1D
Peters et al. (2017)⁴⁸	History of severe hypoglycemia more common in children (6 to <12 years) who dosed post- vs. preprandially (P = 0.006)
Studies in T2D
Ampudia-Blasco et al. (2014)¹⁹	HCPs estimated that 6.2 mistimed basal doses were accompanied by clinical impact over the previous 30 days
Brod et al. (2012)²⁰	HCPs estimated that 5.7 mistimed basal doses significantly impacted glycemic control over a 30-day period
Leiter et al. (2014)²¹	HCPs estimated that 5.7 mistimed basal doses significantly impacted glycemic control over a 30-day period
Schaper et al. (2017)⁴⁹	Higher rates of nonadherence (MMAS-8) (P < 0.01), major and minor hypoglycemic events, and higher HbA1c (≥9.0%) in PwD administering insulin boluses during/post- vs. premeal administration
Studies in T1D and T2D
Tamborlane et al. (2017)⁵¹	Mistiming of bolus insulin was associated with more hypoglycemia and postprandial hypoglycemia in the past week vs. dosing premeal (68.9% vs. 55.7% and 51.4% vs. 28.3%, respectively; both P < 0.001)
Trief et al. (2016)⁵²	PwD who sometimes/never take insulin at the correct time had significantly higher mean HbA1c vs. those who usually/always take insulin correctly (P = 0.007)

HbA1c, glycated hemoglobin; HCP, health care professional; MMAS-8, 8-item Morisky Medication Adherence Scale; PwD, people with diabetes.

Reasons for suboptimal insulin use

Of the included studies, 14 (n = 19 publications) reported on reasons for missed and mistimed insulin doses (Table 6). Reasons were multifactorial and commonly included forgetfulness,^{16,18,25,27,41,42} disruption to usual routines including traveling,^16,18,41 or that insulin interfered with the performance of usual daily activities.^16,17,24,44 PwD also reported missing or mistiming doses to avoid hypoglycemia or because their usual eating patterns had been disrupted.^{17,19
–21,27,41} Participants in the GAPP1 survey noted that regimen complexity was one of the reasons for insulin omission/nonadherence and that it was challenging to take insulin at the same time each day.^16,18 Other factors commonly associated with suboptimal insulin use were being embarrassed or uncomfortable administering doses in public or social situations or that injections were too painful.^{16,18,20,21,24,44} Two studies suggested that some PwD missed doses because they were feeling better and they considered injections unnecessary.^41,43 There was also evidence that diabetes-related distress, stress, and depression may increase suboptimal behaviors (Table 6).^28,31,36

Table 6.

Key Findings From Studies Reporting Reasons for Suboptimal Insulin Use

Author (year)	Key reasons for suboptimal dosing
Studies in T1D
Hessler et al. (2017)³¹	Diabetes-related distress was associated with baseline percentage of missed bolus insulin doses (P = 0.02) and baseline diabetes-related distress significantly predicted change in percent of missed boluses over time (P = 0.006) over time
Joiner et al. (2018)³²	PwD who had experienced a stressful life event were more likely to miss insulin doses ≥3 times per week vs. PwD who had not experienced a stressful life event
Mulvaney et al. (2019)³⁶	Stress, energy, mood, and fatigue were associated with a greater risk of missed bolus insulin in adolescents
Olinder et al. (2011)²⁵	“Lost focus” and “lost focus may cause a vicious circle” emerged as core reasons for missed bolus insulin doses from interviews with adolescents
Olinder et al. (2011)²⁶	Lack of responsibility (explained by the subcategories of distribution, transfer, and clarification of responsibility) was identified as a main reason for missed bolus doses and inadequate self-management in interviews with adolescents
Smythe et al. (2018)²⁷	Reasons commonly given for missed basal and bolus insulin doses: forgetting, being away from home and not having insulin on their person, being too busy, and having concerns regarding hypoglycemia
Trief et al. (2014)²⁸	Significantly more PwD with depression (PHQ-8 score ≥10) missed ≥1 insulin dose per week vs. PwD patients without depression (37.3% vs. 19.6%; P < 0.001)
Studies in T2D
Ampudia-Blasco et al. (2014)¹⁹	Main reasons for intentional missed or mistimed basal insulin doses were to reduce risk of hypoglycemia (91% and 67% of PwD missing/mistiming doses, respectively) and blood glucose too low (80% and 67%)
Brod et al. (2012)²⁰	Most common reasons for intentionally missed or mistimed basal insulin doses: skipped a meal (18% and 15%, respectively), eating pattern not as normal (28% and 35%), blood sugar low (38% and 23%), to reduce risk of low blood sugar (44% and 23%), ran out or running low on insulin (missed, 18%), uncomfortable taking insulin in social situations (mistimed, 19%)
Leiter et al. (2014)²¹	Most common reasons for intentionally missing or mistiming basal insulin doses: skipped a meal (56% and 23%, respectively), eating pattern not as normal (44% and 31%), blood sugar low (44% and 54%), to reduce risk of low blood sugar (44% and 54%), and uncomfortable taking insulin in social situations (mistimed, 23%)
Yavuz et al. (2015)⁴¹	Most frequent reasons for missing insulin dose: forgetting (mainly owing to disruptions in daily routine, distraction by social events, minor interruptions, and being busy, 40.9%), feeling good/consider injection not needed (22.7%), hypoglycemia (9%), drug availability (9%), workload (7.9%), normalization of blood glucose (5.6%), and inability to eat (4.5%)
Studies in T1D and T2D
Brod et al. (2014)⁴²	Six major themes associated with forgetfulness described in qualitative interviews: what people forget, why people forget, how people know they have forgotten, corrective actions taken after forgetting, consequences of forgetting, and feelings about forgetting
Gerada et al. (2017)⁴³	Reasons for missed insulin doses were cost, nature of work or work schedule, and feeling better
Harashima et al. (2017)¹⁸	Reasons for insulin omission/nonadherence reported by PwD or physicians, respectively: too busy (26% and 24%), forgot (23% and 2%), challenging to take at same time each day (14% and 15%), fell asleep (PwD, 11%), skipped meal (8% and 17%), embarrassed to inject in public (6% and 18%), forgot while traveling/insulin not taken out (PwD, 3%), regimen too complicated (both, 3%), traveling or change to normal routine (3% and 8%); injections too painful (both, 2%), and to avoid weight gain (physicians, 2%)
Olamoyegun et al. (2018)⁴⁴	Major reasons for missed insulin doses: insulin not available (21%), other reason (14%), tired of insulin injections (11%), injection pain (5%), person to administer not available (4%), interference with daily activities (2%), and embarrassment (1%)
Peyrot et al. (2010)²⁴,^a	Multiple regression assessing factors associated with intentional missed insulin doses: T2D vs. T1D, higher daily injection frequency, having to plan activities around injections, interference with activities of daily living, and dissatisfaction with injection pain or embarrassment (all P ≤ 0.002)
Peyrot et al. (2012)¹⁶	Reasons for insulin omission/nonadherence reported by PwD or physicians, respectively: too busy (18.9% and 41.9%), traveling (16.2% and 43.6%), skipped a meal (15% and 44.8%), stress or emotional problems (11.7% and 32.2%), embarrassed to inject in public (9.7% and 36.8%), challenging to take at same time each day (9.4% and 29.1%), forgot (7.4% and 2%), too many injections (6% and 26.4%), to avoid weight gain (4% and 13.4%), regimen too complicated (3.8% and 16.8%), and injections too painful (2.6% and 7.8%)
Peyrot et al. (2012)¹⁷,b	Multiple regression assessing factors associated with insulin omission/nonadherence: T2D vs. T1D (P < 0.05), more frequent hypoglycemia (P < 0.05), injections perceived to affect lifestyle (P < 0.05), injection difficulty (P < 0.05), and barriers to insulin adherence (P < 0.001)
Tamborlane et al. (2017)⁵¹	Mistimed bolus insulin (postmeal) was associated with skipping meals in the previous week and eating out

Same patient cohort as Rubin et al.²³ but additional data reported in the publication.

Appears to be same patient cohort as Peyrot et al.¹⁶ but some differences in the data reported.

PHQ, Patient Health Questionnaire; PwD, people with diabetes.

Discussion

This review identified and described 30 unique studies that reported on missed and mistimed insulin dosing in people with T1D or T2D. Findings from the studies described herein indicate that these suboptimal insulin dosing behaviors are not uncommon and suggest that despite advances in insulin therapy over the past several decades, PwD continue to struggle with the complexities of insulin self-management. It is likely that the prevalence of missed and mistimed insulin dosing is even higher than that reported in the included studies. Surveys often found discrepancies between the observations of HCPs and that of their PwDs, with higher rates of missed or mistimed doses being reported by HCPs.^16,22 Indeed, HCPs surveyed in the GAPP2 study believed that ∼30% of PwD underreport the number of basal insulin doses that they miss.²² That PwD are often reluctant to discuss self-care with their physician and frequently misrepresent or withhold important information on diet, exercise, blood glucose monitoring, and medication taking is well known.⁵³ Possible reasons for such reluctance may include fear of being judged, because they do not want to disappoint or “annoy” their physician, or because they do not understand medical recommendations.⁵³

The studies identified herein suggest that suboptimal insulin use may be associated with some PwD not achieving glycemic targets. Several analyses reported that insulin dose omission or mistiming of doses were associated with higher levels of HbA1c.^{27,29,33,37,38,40,45,46,49,52} PwD appear to be aware of the detrimental impact of suboptimal dosing; 65% of European GAPP2 participants recognized that missing basal insulin doses would negatively affect their health.¹⁹ Furthermore, a substantial proportion of PwD indicated that they felt worried or guilty about missing doses.^19,20,22 HCPs also clearly recognize the issues, with participants in GAPP2 estimating that 3.6–4.3 missed and 5.7–6.2 mistimed basal insulin doses in the previous month might have a negative effect on glycemic control.^19
–21 Given that the potential adverse consequences of missing or mistiming insulin are well understood, why are such behaviors so prevalent?

Several of the included studies reported on the reasons for suboptimal insulin use. Various factors were identified as being associated with missed or mistimed doses and were both unintentional (forgetting for various reasons) and intentional (deliberately not taking insulin as directed). Forgetfulness can be caused by disruptions in daily routines and interference by social situations.^{16,18,27,41,42} Insulin use requires countless decisions each day regarding lifestyle behaviors and medication, and these complexities of self-management can represent a significant barrier to consistency of dosing. For example, in the GAPP1 study, major difficulties associated with insulin management identified by PwD and physicians included having to take insulin at the same time each day, adjusting insulin doses, changing the timing of insulin dosing to meet daily needs, and following HCP instructions.¹⁶ As such, PwD perceive that insulin treatment interferes significantly with their ability to perform activities of daily living²⁴ and feel that treatment regimens prevent them from living a normal life.¹⁶ It must also be acknowledged that there may also be occasions when a deviation from the specified dosing is fully justifiable and clinically appropriate (e.g., in the setting of low blood glucose levels). Under these circumstances, for example, a dose should not be considered missed or mistimed. However, the current studies did not specifically report on this issue.

Another reason consistently shown to be associated with suboptimal insulin use is fear of hypoglycemia.⁵⁴ People with T1D and T2D report omitting insulin doses to reduce the risk of hypoglycemia, because their eating patterns are “not as usual,” or because they skipped a meal.^{19
–21,27,41} There is also evidence that given the relentlessness of diabetes self-management and the associated burden of insulin regimens, many PwD experience diabetes-related distress and diabetes burnout wherein they may disengage from self-care tasks.⁵⁵ For example, Hessler et al.³¹ found that diabetes-related distress was significantly associated with the frequency of missed bolus insulin doses. PwD sometimes describe feeling “defeated” by the challenges of disease self-management and anxious about failing to complete self-care tasks adequately.⁵⁶ Studies in this review suggest that feeling overwhelmed by diabetes management may be associated with insulin omission/nonadherence. For example, in their cross-sectional study, Olamoyegun et al.⁴⁴ reported that being “tired of injections” was one of the seven major reasons for insulin omission; and in a qualitative analysis, Brod et al.⁴² identified that PwD with a history of forgetting to dose insulin frequently felt tired and complacent with respect to disease management.

Despite acknowledging the clinical relevance of suboptimal insulin dosing, 32% and 29% of HCPs in the GAPP2 study did not routinely discuss these behaviors with their PwDs on basal insulin or basal-bolus insulin regimens, respectively.²⁰ HCPs often indicate that there is a lack of time to support or fully understand the concerns of their PwDs and to take an individually tailored approach to treatment.⁵⁷ Indeed, even in the best-case scenarios, the number of clinic visits per year is insufficient for the majority of PwD.⁵⁸ Furthermore, ready access to accurate and reliable clinical data can be lacking for HCPs because PwD-recorded information through more traditional methods is sometimes incomplete or incorrect,^59,60 and there can be difficulties in sharing such information in a timely manner with the health care team.

A PwD-centered approach to enhance engagement with diabetes self-care is an important theme in clinical practice recommendations.^61,62 Empowering PwD to gain control over decisions affecting their health by providing them with the means to easily organize and execute the courses of action required for disease management is key for successful self-care.

Clearly, there is a need for innovative approaches to disease management that help both PwD and physicians optimize the use of insulin therapy and fine-tune dosing such that target HbA1c and glucose time-in-range metrics can be achieved.^63,64 In the management of diabetes, it is important to move away from historical data review and response to an ever-changing clinical situation and move toward dynamic, (near) real-time behavioral changes. Digital health tools, such as continuous glucose monitoring, mobile applications, smart insulin pens, and connection-enabled pen caps/clips and their connection into integrated platforms, are just one of several solutions now being used in clinical practice to facilitate better management.⁵⁸

Approaches to diabetes management that potentially place control back in the hands of the PwD through close self-monitoring and provision of real-time observations could improve their ability to fine-tune insulin dosing and so avoid detrimental short- and long-term consequences. The PwD-HCP relationship is acknowledged to be a key contributor to treatment success and effective communication at key points in the disease journey can improve the QoL of PwD and clinical outcomes.^65

–68 This relationship and communication between HCP and physician may perhaps be enhanced if based on the objective data that could be provided by digital health tools.⁶⁹

The current review was conducted according to a reproducible search protocol that reduced the impact of review author bias to ensure transparency and accountability and maximize the changes of accurate data extraction. However, the search was largely pragmatic, and it is possible that other studies of relevance may have been published. Furthermore, the search was restricted to articles in the English language; other relevant studies could have been published in other languages. Search results were reviewed according to a two-stage approach wherein the decision to include/exclude a publication was initially based on review of the title and abstract. As such, it is possible that potentially relevant studies could have been excluded at this stage because of lack of detail in the title/abstract. Inconsistencies in the description of real-world evidence in the literature and the range of terminologies used for this across studies also made the decision to include challenging in some cases. Finally, although the cut-off date of the current search was February 2020, the field is continually evolving, with new studies published all the time. Studies published since our cut-off data include one that reported racial/ethnic differences in insulin dosing behaviors in emerging adults⁷⁰ and another that demonstrated missed insulin doses in 27% of people with T1D during COVID-19 lockdown who also experienced an increase in HbA1c levels compared with pre-lockdown.⁷¹

Several limitations were also observed with respect to the evidence base. Cross-study comparisons are hindered by differences in the designs, reporting methodologies, and populations. For example, similar questions were phrased inconsistently across surveys, making it difficult to be certain that the behavior described in one was comparable with another. In addition, studies reported rates of insulin omission or mistiming in various ways. In surveys, participants were often recruited from preexisting research panels, and therefore might not be representative of the general diabetes population. Some questionnaires could have been administered online at a time when Internet access was not as widely available, perhaps leading to an over-representation of younger patients. It is also likely that any reported insulin dosing irregularities are underestimated, because surveys were mostly self-completed, which could potentially lead to incorrect classifications. Furthermore, recall and social bias could have led to underestimations of suboptimal insulin use, given that this may be perceived as potentially inappropriate medication-taking behavior. Because underreporting is highly likely across studies, the finding that reported behaviors were as widespread and prevalent as they were, is a cause for concern. It should also be noted that study designs did not allow causation to be inferred with respect to the impact of missed or mistimed dosing on clinical outcomes or with respect to the reasons for suboptimal dosing. Furthermore, the reasons for missing or mistiming doses may differ depending on how PwD administer their insulin (e.g., by insulin pump), but the included studies do not provide any further insight regarding this.

Finally, this search was originally undertaken based on a broader protocol that included the following additional concepts of interest: incorrect doses, over- and underdosing, and miscalculated doses (data on which can also be captured by digital health technology). Limited data were identified on these aspects of suboptimal insulin use, and the precise nature of the dosing errors was not always captured in detail. As such, the authors have made the decision not to report these in the current review and instead have added them as exclusions in the PRISMA diagram.

Conclusions

This systematic literature review demonstrated that suboptimal insulin use, including missed and mistimed doses, is widespread among people with T1D and T2D and that these behaviors may be negatively associated with clinical outcomes. These observations suggest that some individuals are continuing to struggle with the complexities of diabetes management and the specific challenges of insulin therapy. Approaches that facilitate better disease management are clearly needed, particularly those that empower and enable PwD and that improve the PwD-HCP relationship and communication through provision of objective data. Digital health tools may represent one such solution. Although their usefulness is still under investigation, it will be interesting to see what role these new technologies will play in the future of diabetes care.

Footnotes

Authors' Contributions

All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work, and have given their approval for this version to be published.

Acknowledgments

The authors thank Mick Arber (York Health Economic Consortium [YHEC]) for assistance with the literature search and Alison Terry of KMHO Ltd. for assistance with editing the article.

Author Disclosure Statement

S.R. and T.K.-M. received funding from Lilly to conduct the study. B.L. and R.S.N. are employees of Eli Lilly and Company. T.B. reports grants from NIH-NIDDK, grants from EU-EC-IMI, grants and personal fees from Novo Nordisk, personal fees from Eli Lilly, grants and personal fees from Sanofi, personal fees from AstraZeneca, grants and personal fees from Medtronic, grants and personal fees from Abbott, personal fees from Roche, grants from Zealand, personal fees from Indigo Diabetes, and personal fees and other from DreaMed Diabetes, outside the submitted work. T.B. was funded in part by the National Institutes of Health—NIDDK grant no. UC4DK108611, by the European Commission/IMI INNODIA Grant No. 664535, by the Slovenian National Research Agency Grants No. J3–6798, V3–1505 and P3–0343, and by the University Medical Centre Ljubljana Research and Development Grant no. 20110359.

Funding Information

The study was funded by Eli Lilly and Company (Indianapolis, IN).

Supplementary Material

Supplementary Table S1

Supplementary Table S2

Supplementary Table S3

Supplementary Table S4

References

International Diabetes Federation (IDF). Diabetes atlas. 9th ed. 2019. https://diabetesatlas.org/en/resources/ (accessed January 15, 2021 ).

Foster

, Beck

, Miller

, et al.: State of type 1 diabetes management and outcomes from the T1D Exchange in 2016–2018. Diabetes Technol Ther, 2019; 21:66–72.

Kazemian

, Shebi

, McCann

, et al.: Evaluation of the cascade of diabetes care in the United States, 2005–2016. JAMA Intern Med, 2019; 179:1376–1385.

Fang

Trends in diabetes management among US adults: 1999–2016. J Gen Intern Med, 2020; 35:1427–1434.

Phan

, Boutmy

, Coulombel

. A cross-sectional study on insulin treatments and glycemic control in type 2 diabetes in France, Italy, Germany, UK and Spain. Value Health, 2015; 18:A335–A766.

Jude

, Nixon

, O'Leary

, et al.: Evaluating glycemic control in patients with type 2 diabetes suboptimally controlled on basal insulin: UK ATTAIN real-world study. Diabetes Ther, 2019; 10:1847–1858.

Idris

, Pen

, He

, et al.: The trend of high-dose insulin usage among patients with diabetes in the UK: a retrospective study. Diabetes Ther, 2018; 9:2245–2257.

Beck

, Bergenstal

, Cheng

, et al.: The relationships between time in range, hyperglycemia metrics, and HbA1c. J Diabetes Sci Technol, 2019; 13:614–626.

, Ma

, Zhou

, et al.: Association of time-in-range, as assessed by continuous glucose monitoring, with diabetic retinopathy in type 2 diabetes. Diabetes Care, 2018; 41:2370–2376.

10.

Gregg

, Hora

, Benoit

. Resurgence in diabetes-related complications. JAMA, 2019; 321:1867–1868.

11.

Carls

, Huynh

, Tuttle

, et al.: Achievement of glycated hemoglobin goals in the US remains unchanged through 2014. Diabetes Ther, 2017; 8:863–873.

12.

Bailey

, Walsh

, Stone

. Emerging technologies for diabetes care. Diabetes Technol Ther, 2018; 20(Suppl 2):S78–S84.

13.

Davies

, Gagliardino

, Gray

, et al.: Real-world factors affecting adherence to insulin therapy in patients with type 1 or type 2 diabetes mellitus: a systematic review. Diabet Med, 2013; 30:512–524.

14.

Chandran

, Bonafede

, Nigam

, et al.: Adherence to insulin pen therapy is associated with reduction in healthcare costs among patients with type 2 diabetes mellitus. Am Health Drug Benefits, 2015; 8:148–158.

15.

Munshi

, Slyne

, Greenberg

, et al.: Nonadherence to insulin therapy detected by Bluetooth-enabled pen cap is associated with poor glycemic control. Diabetes Care, 2019; 42:1129–1131.

16.

Peyrot

, Barnett

, Meneghini

, et al.: Insulin adherence behaviours and barriers in the multinational Global Attitudes of Patients and Physicians in Insulin Therapy study. Diabet Med, 2012; 29:682–689.

17.

Peyrot

, Barnett

, Meneghini

, et al.: Factors associated with injection omission/non-adherence in the Global Attitudes of Patients and Physicians in Insulin Therapy study. Diabetes Obes Metab, 2012; 14:1081–1087.

18.

Harashima

S-I

, Nishimura

, Inagaki

. Attitudes of patients and physicians to insulin therapy in Japan: an analysis of the Global Attitude of Patients and Physicians in Insulin Therapy study. Exp Opin Pharmacother, 2017; 18:5–11.

19.

Ampudia-Blasco

, Galan

, Brod

. A cross-sectional survey among patients and prescribers on insulin dosing irregularities and impact of mild (self-treated) hypoglycemia episodes in Spanish patients with type 2 diabetes as compared to other European patients. Endocrinol Nutr, 2014; 61:426–433.

20.

Brod

, Rana

, Barnett

. Adherence patterns in patients with type 2 diabetes on basal insulin analogues: missed, mistimed and reduced doses. Curr Med Res Opin, 2012; 28:1933–1946.

21.

Leiter

, Boras

, Woo

. Dosing irregularities and self-treated hypoglycemia in type 2 diabetes: results from the Canadian cohort of an international survey of patients and healthcare professionals. Can J Diabetes, 2014; 38:38–44.

22.

Munro

, Barnett

. Incidence, worry and discussion about dosing irregularities and self-treated hypoglycaemia amongst HCPs and patients with type 2 diabetes: results from the UK cohort of the Global Attitudes of Patient and Physicians (GAPP2) survey. Int J Clin Pract, 2014; 68:692–699.

23.

Rubin

, Peyrot

, Kruger

, et al.: Barriers to insulin injection therapy: patient and health care professional perspectives. Diabetes Educ, 2009; 35:1014–1022.

24.

Peyrot

, Rubin

, Kruger

, et al. Correlates of insulin injection omission. Diabetes Care, 2010; 33:240–245.

25.

Olinder

, Nyhlin

, Smide

Reasons for missed meal-time insulin boluses from the perspective of adolescents using insulin pumps: ‘lost focus.' Pediatr Diabetes 2011;12(4 Pt 2):402–409.

26.

Olinder

, Nyhlin

, Smide

. Clarifying responsibility for self-management of diabetes in adolescents using insulin pumps—a qualitative study. J Adv Nurs, 2011; 67:1547–1557.

27.

Smythe

, Saw

, Mak

, et al.: Carbohydrate knowledge, lifestyle and insulin: an observational study of their association with glycaemic control in adults with type 1 diabetes. J Hum Nutr Diet, 2018; 31:597–602.

28.

Trief

, Xing

, Foster

, et al.: Depression in adults in the T1D Exchange Clinic Registry. Diabetes Care, 2014; 37:1563–1572.

29.

Datye

, Boyle

, Simmons

, et al.: Timing of meal insulin and its relation to adherence to therapy in type 1 diabetes. J Diabetes Sci Technol, 2018; 12:349–355.

30.

Giani

, Snelgrove

, Volkening

, et al.: Continuous glucose monitoring (CGM) adherence in youth with type 1 diabetes: associations with biomedical and psychosocial variables. J Diabetes Sci Technol, 2017; 11:476–483.

31.

Hessler

, Fisher

, Polonsky

, et al.: Diabetes distress is linked with worsening diabetes management over time in adults with Type 1 diabetes. Diabet Med, 2017; 34:1228–1234.

32.

Joiner

, Holland

, Grey

. Stressful life events in young adults with type 1 diabetes in the US T1D Exchange Clinic Registry. J Nurs Scholarsh, 2018; 50:676–686.

33.

McCarthy

, Grey

. Type 1 diabetes self-management from emerging adulthood through older adulthood. Diabetes Care, 2018; 41:1608–1614.

34.

Mukama

, Moran

, Nyindo

, et al.: Improved glycemic control and acute complications among children with type 1 diabetes mellitus in Moshi, Tanzania. Pediatr Diabetes, 2013; 14:211–216.

35.

Mulvaney

, Rothman

, Dietrich

, et al.: Using mobile phones to measure adolescent diabetes adherence. Health Psychol, 2012; 31:43–50.

36.

Mulvaney

, Vaala

, Carroll

, et al.: A mobile app identifies momentary psychosocial and contextual factors related to mealtime self-management in adolescents with type 1 diabetes. J Am Med Inform Assoc, 2019; 26:1627–1631.

37.

Olinder

, Kernell

, Smide

. Missed bolus doses: devastating for metabolic control in CSII-treated adolescents with type 1 diabetes. Pediatr Diabetes, 2009; 10:142–148.

38.

Pańkowska

, Skorka

, Szypowska

, et al.: Memory of insulin pumps and their record as a source of information about insulin therapy in children and adolescents with type 1 diabetes. Diabetes Technol Ther, 2005; 7:308–314.

39.

Vanderwel

, Messer

, Horton

, et al.: Missed insulin boluses for snacks in youth with type 1 diabetes. Diabetes Care, 2010; 33:507–508.

40.

Mashitani

, Hayashino

, Okamura

, et al.: Diabetes treatment-related quality of life is associated with levels of self-care activities in insulin injection among Japanese patients with type 2 diabetes: diabetes Distress and Care Registry at Tenri (DDCRT 8). Acta Diabetol, 2015; 52:639–647.

41.

Yavuz

, Ozcan

, Deyneli

. Adherence to insulin treatment in insulin-naive type 2 diabetic patients initiated on different insulin regimens. Patient Prefer Adherence, 2015; 9:1225–1231.

42.

Brod

, Pohlman

, Kongso

. Insulin administration and the impacts of forgetting a dose. Patient, 2014; 7:63–71.

43.

Gerada

, Mengistu

, Demessie

, et al.: Adherence to insulin self administration and associated factors among diabetes mellitus patients at Tikur Anbessa specialized hospital. J Diabetes Metab Dis, 2017; 16:28.

44.

Olamoyegun

, Akinlade

, Ala

. Audit of insulin prescription patterns and associated burden among diabetics in a tertiary health institution in Nigeria. Afr Health Sci, 2018; 18:852–864.

45.

Campbell

, Schatz

, Chen

, et al.: A contrast between children and adolescents with excellent and poor control: the T1D Exchange clinic registry experience. Pediatr Diabetes, 2014; 15:110–117.

46.

Simmons

, Chen

, Miller

, et al.: Differences in the management of type 1 diabetes among adults under excellent control compared with those under poor control in the T1D Exchange Clinic Registry. Diabetes Care, 2013; 36:3573–3577.

47.

Stephenson

, Raval

, Kern

, et al.: Non-adherence to basal insulin among patients with type 2 diabetes in a US managed care population: results from a patient survey. Diabetes Obes Metab, 2018; 20:2700–2704.

48.

Peters

, Van Name

, Thorsted

, et al.: Postprandial dosing of bolus insulin in patients with type 1 diabetes: a cross-sectional study using data from the T1D Exchange Registry. Endocr Pract, 2017; 23:1201–1209.

49.

Schaper

, Nikolajsen

, Sandberg

, et al.: Timing of insulin injections, adherence, and glycemic control in a multinational sample of people with type 2 diabetes: a cross-sectional analysis. Diabetes Ther, 2017; 8:1319–1329.

50.

Nishimura

, Harashima

S-I

, Fukushige

, et al.: A large difference in dose timing of basal insulin introduces risk of hypoglycemia and overweight: a cross-sectional study. Diabetes Ther, 2017; 8:385–399.

51.

Tamborlane

, Pfeiffer

, Brod

, et al.: Understanding bolus insulin dose timing: the characteristics and experiences of people with diabetes who take bolus insulin. Curr Med Res Opin, 2017; 33:639–645.

52.

Trief

, Cibula

, Rodriguez

, et al.: Incorrect insulin administration: a problem that warrants attention. Clin Diabetes, 2016; 34:25–33.

53.

Beverly

, Ganda

, Ritholz

, et al.: Look who's (not) talking: diabetic patients' willingness to discuss self-care with physicians. Diabetes Care, 2012; 35:1466–1472.

54.

Ellis

, Mulnier

, Forbes

. Perceptions of insulin use in type 2 diabetes in primary care: a thematic synthesis. BMC Fam Pract, 2018; 19:70.

55.

Fisher

, Polonsky

, Hessler

, et al.: Understanding the sources of diabetes distress in adults with type 1 diabetes. J Diabetes Comp, 2015; 29:572–577.

56.

Psarou

, Cooper

, Wilding

JPH

. Patients' perspectives of oral and injectable type 2 diabetes medicines, their body weight and medicine taking behavior in the UK: a systematic review and meta-ethnography. Diabetes Ther, 2018; 9:1791–1810.

57.

Stuckey

, Vallis

, Kovacs Burns

, et al.: “I do my best to listen to patients”: qualitative insights into DAWN2 (diabetes psychosocial care from the perspective of health care professionals in the second Diabetes Attitudes, Wishes and Needs study). Clin Ther, 2015; 37:1986–1998.

58.

Levine

, Close

, Gabbay

. Reviewing US connected diabetes care: the newest member of the team. Diabetes Technol Ther, 2020; 22:1–9.

59.

Kazlauskaite

, Soni

, Evans

, et al.: Accuracy of self-monitored blood glucose in type 2 diabetes. Diabetes Technol Ther, 2009; 11:385–392.

60.

Given

, O'Kane

, Bunting

, et al.: Comparing patient-generated blood glucose diary records with meter memory in diabetes: a systematic review. Diabet Med, 2013; 30:901–913.

61.

American Diabetes Association (ADA). Improving care and promoting health in populations: standard of medical care in diabetes—2021. Diabetes Care, 2021; 44(Suppl 1):S7–S14.

62.

Davies

, D'Alessio

, Fradkin

, et al.: Management of hyperglycaemia in type 2 diabetes, 2018. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia, 2018; 61:2461–2498.

63.

American Diabetes Association (ADA). Glycemic targets: standard of medical care in diabetes—2021. Diabetes Care, 2021; 44(Suppl 1):S73–S84.

64.

Battelino

, Danne

, Bergenstal

, et al.: Clinical targets for continuous glucose monitoring data interpretation: recommendations from the International Consensus on Time in Range. Diabetes Care, 2019; 42:1593–1603.

65.

Linetzky

, Jiang

, Funnell

, et al.: Exploring the role of the patient-physician relationship on insulin adherence and clinical outcomes in type 2 diabetes: insights from the MOSAIc study. J Diabetes, 2017; 9:596–605.

66.

Polonsky

, Arsenault

, Fisher

, et al.: Initiating insulin: how to help people with type 2 diabetes start and continue insulin successfully. Int J Clin Pract, 2017; 71:e12973.

67.

Polonsky

, Capehorn

, Belton

, et al.: Physician-patient communication at diagnosis of type 2 diabetes and its links to patient outcomes: new results from the global IntroDia^® study. Diabetes Res Clin Pract, 2017; 127:265–274.

68.

Edelman

, Belton

, Down

, et al.: Physician-patient communication at prescription of an additional oral drug for type 2 diabetes and its links to patient outcomes—new findings from the global IntroDia^® study. Diabetes Res Clin Pract, 2019; 148:89–97.

69.

Herrmans

, Ehrmann

, Finke-Groene

, et al.: Trends in diabetes self-management education: where are we coming from and where are we going? A narrative review. Diabet Med, 2020; 37:436–447.

70.

Butler

, Weller

, Rodgers

CRR

, et al.: Type 1 diabetes self-management behaviors among emerging adults: racial/ethnic differences. Pediatr Diabetes, 2020; 21:979–986.

71.

Verma

, Rajput

, Verma

, et al.: Impact of lockdown in COVID 19 on glycemic control in patients with type 1 diabetes mellitus. Diabetes Metab Syndr, 2020; 14:1213–1216.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.30 MB

0.29 MB

Missed and Mistimed Insulin Doses in People with Diabetes: A Systematic Literature Review

Abstract

Background:

Methods:

Results:

Conclusions:

Introduction

Materials and Methods

Search strategy

Inclusion criteria

Article selection

Data extraction and reporting

Results

Study selection

Study characteristics

Missed insulin doses

Studies in T1D

Studies in T2D

Studies in types 1 and 2 diabetes

Association between missed doses and clinical outcomes

Mistimed doses

Association between mistimed doses and clinical outcomes

Reasons for suboptimal insulin use

Discussion

Conclusions

Footnotes

Authors' Contributions

Acknowledgments

Author Disclosure Statement

Funding Information

Supplementary Material

References

Supplementary Material