Utilisation of prehospital emergency medical services for hyperglycaemia: A community-based observational study

Abstract

AimsThis study examines prehospital Emergency Medical Service (EMS) utilisation and patterns of demand for hyperglycaemia management, including characteristics of individuals and factors related to hospital transport.Materials and methodsA state-wide, community-based observational study of all patients requiring prehospital EMS for hyperglycaemia during a 7 year study period (Jan 2009–Dec 2015) using electronic data from the Ambulance Victoria data warehouse was conducted. Pre-specified variables related to patient demographics, comorbidities, examination findings, paramedic treatment and transport outcomes were obtained. Logistic regression was used to assess factors associated with transport to hospital.ResultsThere were 11,417 cases of hyperglycaemia attended by paramedics during the study period, accounting for 0.3–0.4% of the total annual EMS caseload, and equating to 0.54 attendances per 100 people with diabetes in the state of Victoria, Australia, per year. There was a significant increase in annual utilisation, with a rate ratio of 1.62 between 2009 (2.42 cases per 10,000 population) and 2015 (3.91 cases per 10,000 population). Fifty-one percent of cases had type 2 diabetes, 37% had type 1 diabetes, 4% had diabetes with the type unspecified and 8% had no recorded history of diabetes. Ninety percent of cases were transported to hospital. Factors associated with increased odds of transport to hospital included no known history of diabetes, regional/rural locations, case time between 0600 and <1800 hours, increasing number of comorbidities and increasingly unstable vital sign observations.ConclusionThere is substantial utilisation of prehospital EMS for hyperglycaemia. With increased population prevalence of diabetes predicted, further research on opportunities for prevention, as well as optimal management in the prehospital environment is warranted.

Hypoglycaemia in older home-dwelling people with diabetes- a scoping review

“…In total, 11 studies reported on the incidence of hypoglycaemia in home-dwelling older people (Table 1 ) [ 30 – 32 , 36 , 37 , 39 , 42 , 44 , 47 , 50 , 51 ]. The majority of the studies reported data from ambulance records or emergency hospital visits [ 30 , 36 , 37 , 39 , 42 , 44 , 47 , 50 , 51 ], while one reported combined data of episodes of hypoglycaemia from outpatient visits, emergency departments and inpatient encounters with admission diagnosis hypoglycaemia [ 31 ]. Only one study reported observational data of mild, moderate and severe hypoglycaemia in home-dwelling older individuals registered by continuous glucose monitoring (CGM) [ 32 ].…”

“…Most studies reported incidences of hypoglycaemia requiring prehospital emergency medical care with or without hospital admission in patients with diabetes mellitus from 0.5–2.5 episodes/100 patient years [ 30 , 36 , 39 , 44 , 50 , 51 ]. The incidence of hypoglycaemia reported by Parsaik and colleagues with data from the US was somewhat higher; ambulance calls related to hypoglycaemia were performed in 9/100 individuals with type 2 diabetes and the calls for hypoglycaemia were 2% of the total number of calls for emergency assistance [ 42 ].…”

“…In total, 6 studies reported on the consequences of hypoglycaemia for use of health care services [ 30 , 38 , 42 , 44 , 50 , 51 ]. All studies focused on emergency situations, such as transfer to an emergency department, admission to hospital, or length of hospitalization.…”

“…Several studies showed that hypoglycaemia in older home-dwelling individuals more often required hospitalizations than in younger individuals [ 30 , 42 , 50 ]. In the study by Farmer et al, 35% of the calls resulted in hospital admission, and the likelihood of being taken to hospital was almost double in individuals of 80 years or older compared to 20–60-year olds [ 30 ].…”

Forecasting Diabetes Patients Attendance at Al-Baha Hospitals Using Autoregressive Fractional Integrated Moving Average (ARFIMA) Models

“…Within the period from January 2009 until December 2015. The SARIMA (0, 1, 0) × (0, 1, 0) 12 model provided the best fit model dealing with the number of patients [7].…”