A Comparison in Diabetes Management between Rural and Urban Patients

What we already know: The prevalence of diabetes in New Zealand is projected to increase by 30% over a decade and will affect greatly those from deprived areas [1,2]. This will present a challenge in resources and cost for the primary health care sector. What this study adds: Is the location of the health care provider a contributing factor for patients managing their diabetes. This research demonstrates that in relation to the proximity of their health care can, does not necessary determine their diabetes management.

The prevalence of diabetes is both rising in New Zealand and worldwide [3]. Primary care has a very important role in diabetes management and utilization is strongly linked to reduced hospital admissions [4]. This paper will assess the equity with those patients that have a diagnosis of type 1 or 2 diabetes mellitus in relation to rural and urban patients. As a Long Term Conditions nurse my colleague and I began to question if those patients with diabetes that live rurally are worse off than those patients that live in urban areas. A barrier to diabetes management has a detrimental effect on a patients and their families well-being [5,6]. The locational proximity or travel time is a determinate of health service accessibility [4]. In their study [7] showed the main source of diabetes education patients received, is from general practice. It was hypothesised if proximity to their primary health care centre was detrimental to adequately managing their diabetes. There is no internationally recognised definition of a ‘rural’ area but has traditionally been residual areas not included in the urban definition (Stats NZ, 2019). For the purpose of this study the definition of rural are those patients outside a5kilometer radius from their health care provider. 

According to the Ministry of Health data 2011, diabetes mellitus in New Zealand had 11,000 new diagnoses, 180,000 prevalent diagnoses and 1900 deaths attributable to diagnosed disease and is forecast to get worse [4]. The prevalence of diabetes among M?ori is twice that of non-M?ori [8]. M?ori are often associated with co-morbidities and long-term conditions, with a high-risk of developing cardiovascular disease and cancer [9]. Renal failure is one of the complications of diabetes. Rates of renal failure with concurrent diabetes for M?ori aged 15 and over were more than 5 times that of non-M?ori at the same age group [8]. Therefore, it is important that patients practice good diabetes management to slow down disease progression with the help of their health care provider. Health literacy is a key determinant for enabling the empowerment of the patient and is recognized as a barrier particularly with Maori [9]. The patient’s understanding of medical terminology is influenced greatly by their level of health literacy. When caring for people with diabetes amongst indigenous communities, for every dollar invested in primary care can have a saving of four health dollars [10]. 

In general discussion with the diabetes team, it was suggested that perhaps distance from the health centre, may have influence their diabetes management. The aim of this paper is to identify comparisons between diabetes patient’s bio markers, in relation to the distance they live from their health care centre. The Health Centre used in this study has 91% identified as high needs. High needs defined as M?ori, Pacific and or Quintile 5. Of the enrolled population 78% are M?ori, 5% Pacific Island and 17% are other ethnicities [11]. The communities and environmental influences that affect health and wellbeing are for some peoples beyond their control [12]. These circumstances contribute to poor health and inequalities, resulting in burgeoning chronic disease and poor health literacy [13]. A common denominator of successful long-term models of support is indigenous support from the community. For this study, “high-risk” patients are defined as those with or at risk of long-term conditions, such as diabetes or heart disease [14]. Those deemed high-risk are expected to place further pressure on health resources with each long-term condition estimated to cost $100 million annually [15]. Improving access to primary care for patients to manage their diabetes, is both a benefit to the health of patients and in cost savings for the government.

Primary health care undertakes a variety of interventions in health prevention and health education while supporting healthy lifestyles. Area deprivation is strongly associated with poorer health and increased racial discrimination [16]. Such cohorts’ in health and economic status often go on to deteriorate, unless the right interventions are delivered (Buck &Frosini, 2012). Diabetes affects M?ori proportionally higher compared to non-M?ori in New Zealand. The New Zealand Health Strategy aims to address issues of equity in health for all the population. Within New Zealand some gains have been made towards health equity over the last 20 years, such as improved immunisation rates for M?ori. However, more work needs to be done to achieve health equity for M?ori [17]. It is shown that whilst M?ori keep their appointments with their general practitioner at the same rate as non-M?ori [18], M?ori have fewer diagnostic tests, less effective treatment plans and are referred for secondary or tertiary procedures at significantly lower rates than non-M?ori [19,20].

It is important that our practice as primary health professionals reflects the changing social determinates of health, particularly for high needs populations. My experience as a Long-Term Conditions nurse with a focus on diabetes and cardiovascular disease while working with high needs patients, is always about providing worthwhile and effective engagement. My role in the community team, allows for flexibility in resources. The team use a Kaupapa Maori framework with access to other Maori centred support agencies. Despite these resources we don’t always have the opportunity to make comparisons with the cohort which we work with.

Korowai Aroha Health Centre is a M?ori health provider with an enrolled population of 5117 patients. The health centre has a staff of general practitioners registered nurses, community workers and support staff while managing several community health contracts. An audit of 372 patients with diabetes was undertaken using the patient diabetes data base from within the health centre. This consisted of those patients diagnosed with Type 1 and Type 2 diabetes mellitus, with the diagnosis defined in accordance with the New Zealand Group Guidelines (Ministry of Health, 2012). Those patients that are symptomatic with an HbA1c ≥ 50 mmol/molor asymptomatic with an HbA1c ≥ 50 mmol/mol, with 2 results above diagnostic cut-offs on separate occasions. These patients were then grouped into the following categories; type, year of diagnosis, age, visits to their primary health provider including hospital visits, gender, diagnosis of depression, gout, respiratory condition, Chronic Obstructive Pulmonary Disease (COPD), cardiovascular risk assessment, medication prescribed, blood pressure, medication, quintile, referral to other primary services, community service card user and proximity to the health centre. The clinical data was retrospectively collected within a 12 month period. The proximity to the health care provider was in 2 categories 0 to 4.9 kilometres and greater than 5 kilometres. The data was then analysed for a difference in diabetes management using the above bio markers and clinical interventions and social deprivation. Ethics approval was not required as this was an auditing method of data collection.

The results show a quarter of the registered population live rurally. Greater numbers of males with diabetes, live in the urban areas than rurally (Table 1). 

Table 1: Proximity to Health Centre. 

The difference between the two cohorts showed marginal difference in HbA1c, with overall high cardiovascular risk assessments in both cohorts. There were no statistically significant differences in both cohorts. However there was some evidence to show depression more in rural patients than urban. The table below shows the comparative data from those less than 5kms to the health centre to those living greater than 5ks (Table 2).

Table 2: Comparison markers. 

There is no statistical difference between cohorts for those prescribed medication; insulin, statins and Angiotensin-converting-enzyme inhibitors, which would indicate prescribed medications are used equally between the cohorts.

Visits to allied health professionals showed a 1% difference between the cohorts with retinal screening with more patients from the rural cohort visiting the podiatrist. This could be argued that those living rurally are not disadvantaged any less than the urban population. Interestingly, twice as many patients are diagnosed with depression in the rural sector (Table 3). 

The table below shows deprivation and community services card use. 

Table 3: Deprivation.

The greater population that live both less than and greater than 5ks from the health care provider, are in lower social deprivation areas.

Those with the greatest deprivation live greater than 5 Kilometres away from the Health centre. 

On average 59% in both cohorts have a community services card. This is comparable with the high quintile population. The key findings showed little difference in patient’s management of their diabetes between urban and rural areas. The data demonstrates this cohort is achieving equity within this M?ori population.

Research shows diabetes is one of the majority contributors to mortality for both M?ori and non-M?ori. As primary health care professionals it is always important to know if we are making a difference and if we have room for improvement or even to understand better those interventions that show improvement. Travel times from patient’s health care provider have been linked with poor health outcomes [4]. Whilst this study has highlighted areas for improvement, there are areas that appear to be working well. This may be contributed by the model of care this health centre is using for their diabetes patients. This could have implications for improving the modal of Long Term Conditions. This study shows some positive outcomes in biomarkers between both cohorts. Thus, suggesting distance from patient to health care provider may not be a disadvantage. Further research into analysing how the support these patients could add value for primary health professionals.

Whilst it is theorised that patients living in a rural location have poorer outcomes than those living in an urban environment. In this study, the results showed minimal difference in outcomes for this health centre.

    • A follow up study on those patients to explore why there is little difference between the cohorts in managing their diabetes
    • From a quality improvement perspective, it would be important to explore what interventions are used and how the service is influencing these patient’s diabetes management
    • Investigate why there is a greater number of rural patients with depression compared to urban patients with depression
    • This could be a potential learning opportunity for health professionals working in primary health care

This study would be interesting to compare if repeated in a similar health centre

It is acknowledged the limitations in this study are the size of the data base. The data could have included the rationale for visiting health professionals. This could determine if the visit was either related to their diabetes or completely an unrelated medical matter.

Primary health care services have an obligation to work with patients in an environment in which they feel supported in. Whilst sometimes this can present as a challenge for primary care professionals, supporting patients inside or outside the health centre is always worth investigating. Learning more about how we support a positive change in their environment can be a driver into improving our services.

The author declares no conflict of interest in this research.