Gestational diabetes screening and management: the issues of GDM risk factors and phone number documentations

INTRODUCTION

GDM is a serious pregnancy complication, in which women without previous diagnosis of diabetes develop chronic hyperglycaemia during pregnancy.¹ GDM arises due in part to the aberrations in insulin receptors and signalling and this can resolve after delivery, however, it is established that between 40-60% of GDM patients develop type 2 diabetes mellitus (T2DM) in ten to twenty years.^2,3 The various risk factors (RFs) for GDM include older age, overweight and obesity, previous GDM, excessive weight gain during pregnancy, a family history of diabetes, polycystic ovary syndrome, habitual smoking and a history of stillbirth or giving birth to an infant with a congenital abnormality.⁴

Studies have reported a wide range of prevalence values.⁵ For instance, in Nigeria, three different studies that attempted two comparative measures each have reported varying levels of prevalence of GDM.^6-8 These wide variations show that the current understanding of GDM epidemiology require more controlled studies. Reasons for the variations have been highlighted to include some studies being limited to women with GDM RF.⁹ This implies a problem with selective screening, which depends on availability of patients’ data vis-à-vis complete documentation in medical records.

Focusing on documentation, it is pertinent to bring to the fore that a large percentage of GDM cases are undiagnosed and prevalence of postpartum T2DM is unknown, especially in developing countries such as Nigeria and Africa at large.¹⁰

Statement of the problems

So far, there is at least thirteen (13) RFs of GDM, excluding laboratory tests. The need for completeness of medical records to include all 13 RFs is important in patients’ selection for laboratory screening of GDM. While lack of completeness of data is noted as a barrier, there is dearth of data on the extent and pattern that incomplete documentation of patients’ phone numbers can help or prevent recall of antenatal clients in Nigeria is unknown hence the need for further elucidation.^11,12

Research aim

The main aim was to progress discourse on GDM screening by evaluating phone contacts on medical records and assess levels of GDM RF in patients. Specific objectives included were to assess: the describe reasons for ‘unreached’ phone calls; and the prevalence of each of 13-RF among those reached and prevalence of each RF.

METHODS

Study design

It was a descriptive quantitative re-evaluation of previously published data.

Ethical approval

As it was previously published additional state-wide approval was obtained from the Delta State Ministry of Health (HM/596/T/197).

Data

In 2020, the files of initial 123 sample records of pregnant women were reviewed to ascertain if the phone numbers were effective for purpose. In the previous report, it was indicated that 98/123 of the patients were able to receive services via telehealth. Here, the n=98 was further audited and described.

The 98-patients were called on the phone number provided in their records. Those (n=41) who answered their phones were interviewed for GDM risk factors using the ‘proposed gestational diabetes risk assessment and screening sheet’ previously published. Here, the prevalence of the 13 GDM RFs were reviewed.

Statistics

The statistics used were descriptive frequency evaluation.

RESULTS

This re-evaluation shows that among the 123 files, 98 had telephone numbers recorded and these were segregated based on telehealth attempt whereby 41.8% (41/98) of the phone numbers were reached and 58.2% unreached. Among the n=41 pilot dataset, prevalence of number of risk factors assessed during ‘telehealth’ antenatal monitoring is shown in Figure 1.

*GDM risk factors.

On further evaluation of the prevalence of GDM risk factors, results show that most of the mothers at ‘initial routine data’ were less than 35 years of age, lived a sedentary lifestyle, and did not have family history of diabetes. Approximately 30% has ‘previous history’ factor, while 44% had no risk factors observable at ‘antenatal monitoring’ (Table 1). On average, prevalence of risk factors assessed during the three stages of initial routine data collection, previous history assessment and at antenatal monitoring phase are approximately 25%, 21% and 38% respectively.

DISCUSSION

In this report, n=41 participants who answered their phones were interviewed on the risk factors for GDM using the screening form, which were entered in register-dataset. In addition to data in Figure 1, further details highlighted the prevalence of each risk factor among the n=41 dataset (Table 1).

Effectiveness of phone to follow-up ANC cases of incomplete data

Results on the effectiveness of phone calls showed that 31.7% of those who answered the phone have three or more GDM risk factors that could be picked up at ANC monitoring. This represented the proportion of that qualifies for GDM screening. When previous history and initial routine data were reviewed, as recommended for African populations, those showing ≥3 risk factors increase to 41.5%.^13-15 This observation showed that phone call vis-à-vis telehealth can be effective in identifying risk for GDM.

Among the 57/98 unanswered calls, nearly 60% were switched off, while answering machine gave different reasons for others. Although, this was beyond the control of the clinicians and medical records officers, it was presumable that some of those without phone and with unanswered calls have risk for GDM also. More discussions were necessary on how mobile phone these days were important tool not only for telehealth, but also for information (mass media) e.g., on lifestyles that mitigate several diseases such as DM and cardiovascular disease.^16-18 What this report expounds is the significance of phones in facilitating telehealth in ANC to follow-up clients for GDM management. Perhaps, lessons from eCommerce experience need to be drawn.

Implications of contact details on telehealth potentials

Common knowledge from the eCommerce sector indicates that assurance of clients’ ability to receive calls is necessary, especially as physical home addresses are unreliable even in metropolitan cities.¹⁹ Besides mobile phones registrations, eCommerce has recognized other digital identifiers including subscriber identity module (SIM) number.²⁰ Perhaps, it may be worth investigating if registration of SIM numbers besides telephone number could help improve the effectiveness of the latter in contacting patients.

In a consideration of telehealth in pathology service, it was concluded that no amount of telepathology support can meet all requirements but the education of local practitioners is imperative.²¹ In this study on antenatal services for GDM management, the same point was hereby postulated that ANC providers and medical records personnel would need professional development education to improve on effectiveness of patients’ phone numbers being collected.

There is no gain saying that in modern time, telephone is being used to remind patients about their appointments and for counselling. Even in the recent times of COVID-19, telephone has been the main modality of telehealth consultations. Further, mobile phones are a source of information inclusive of health updates. Therefore, the need to advance to telehealth and discuss the issue of phone numbers that are not reachable is imperative.

GDM risk factor analysis

GDM management has long been identified as one of new challenges in Africa.²² It is associated with a variety of adverse pregnancy outcomes such as macrosomia, dystocia, birth trauma, and metabolic complications in both mother and the newborn.^15,23,24 Patients with GDM are known to be at increased risk of developing overt DM postpartum.²⁵ Consequently, it is important to identify and manage GDM as early as possible and such management can be through complete records and use of phone platforms. However, selective criteria for GDM screening have been advocated in preference to universal approach for reason of affordability. Perhaps, it is pertinent to note the following points regarding selection criteria for laboratory test.

Assessment of risk factors are generally non-invasive and can be obtained during ANC registration and history taking.^13-15

Risk scoring systems exist but unknown in ANC practices. However, a user-friendly algorithm or chart is yet to be developed.

Pending availability of user-friendly risk scoring chart, a pregnant woman with any ×3 of 13 RFs should qualify for laboratory screening of GDM (Table 1).

Studies in Tanzania reported that testing of blood glucose levels was a challenge due to limited resources and capacity in most healthcare facilities. Hence, a call for a simple, affordable, and practical non-invasive tool to predict undiagnosed GDM.¹⁵ Further, a recent systematic review of “Barriers to screening, diagnosis and management of hyperglycaemia in pregnancy in Africa” had echoed that the limitations to GDM screening are multifaceted but including the healthcare systems and every facet requires its targeted intervention.²⁶

What this paper contributed to the discourse was empirical and epidemiological data that could serve as evidence-base for retraining of healthcare professionals regarding patients’ telephone numbers and telehealth potentials. The observations highlight behavioural change wheel issues on GDM screening and primary healthcare that need concerted focus on antenatal health services and policy improvement. The significance is the need for GDM management, postpartum follow-up and women’s health.

CONCLUSION

GDM is one of the common medical complications of pregnancy. Selective screening for GDM is therefore important and to complement this there is need for complete medical records in the antenatal health services. This report describes reasons of patients’ phone numbers being unreached for effective GDM management in antenatal care service. The COHORT of patients reached by use of mobile telephone for telehealth functionalities are also described to demonstrate feasibility and imperativeness of phone numbers. The healthcare providers need to utilize simple and effective tools such as the ‘GDM risk assessment and screening sheet’ questionnaire. Also, attention needs to be given to reasons why majority of patients are unreachable on their phones.

Funding: No funding sources

Conflict of interest: None declared

Ethical approval: The study was approved by the Delta State Ministry of Health (HM/596/T/197)

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