Reporting Clinical Activity On Military Operations - Time For Some Standardisation

Prescribing in the prehospital environment: a review of the pharmaceutical Module 501 on UK Military Exercise SAIF SAREEA 3. Can such analysis assist with the scaling of healthcare assets?

INTRODUCTION

Module 501 provides core medications which are fundamental to the capability of a prehospital treatment team (PHTT). The quantities of each medication in the module inventory undergo regular review, but these do not correspond to a population at risk (PAR) figure or deployment length for which they intend to be used. This article proposes how the quantities of Module 501 drugs can be scaled for a given deployment, in this example using statistics taken from static PHTTs on Exercise Saif Sareea 3 (SS3).

METHODS

The statistics were gathered using a custom-built search of electronic records from the Deployed Defence Medical Information Capability Programme in addition to written record-keeping, which were aligned to the weekly PAR at each PHTT location throughout their full operational capability periods. A quotient was then derived for each module item using a formula.

RESULTS

Among the 10 most commonly prescribed drugs were four analgesics and three antimicrobials. 42 of the 110 studied drugs were not prescribed during SS3.

DISCUSSION

The data from SS3 reflect the typical scope of disease encountered in the deployed land setting. Employing these data, the use of a formula to estimate the drug quantities needed to sustain a Strike Armoured Infantry Brigade over a 28-day period is demonstrated.

RECOMMENDATIONS

Further study of Module 501 across varied deployment environments would be valuable in evolving this approach to medicinal scaling if proven effective for the warm desert climate. It could then be applied to other modules to further inform future Strike medical planning.

LIMITATIONS

Several considerations when drawing deductions from the data are mentioned, including the inaccuracy of predictor variables taken from the EpiNATO-2 reports.

CONCLUSION

The proposed formula provides an evidence-based framework for scaling drug quantities for a deployment planning. This may improve patient safety and confer logistical, storage and fiscal benefits.

Exercise ASKARI SERPENT: enabling clinical data collection during exercises and operations to support future contingency planning and assurance of category-based reporting systems

INTRODUCTION

Exercise ASKARI SERPENT (Ex AS) is a British Army exercise that provides primary healthcare (PHC) to Kenyan civilians in support of local health authorities. It is conducted in partnership with the Kenya Defence Force Medical Services (KDFMS). Accurate epidemiological data is critical in planning the exercise and for any future short-notice contingency operations in similar environments. This paper reports epidemiological data for Ex AS using a novel data collection system.

METHODS

PHC on Ex AS was delivered by trained and validated combat medical technicians (CMTs) using a set of Read-coded protocols. The CMTs were also directly supported and supervised by medical officers and nurses.

RESULTS

A total of 3093 consultations were conducted over a 16-day period. Of these, 2707 (87.5%) consultations fell within the remit of the CMT protocols, with only 386 consultations (12.5%) being conducted exclusively by the medical officers or nurses.

DISCUSSION

A Read-coded matrix built on CMT protocols is a simple and useful tool, particularly in civilian populations, for collecting morbidity data with the vast majority of conditions accounted for in the protocols. It is anticipated that such a system can better inform training, manning, medical material and pharmaceutical procurement than current category-based morbidity surveillance systems such as EPINATO (NATO epidemiological data). There is clear advantage to directly linking data capture to treatment algorithms. Accuracy, both in terms of numbers and condition, is likely improved. Data is also captured contemporaneously rather than after indeterminate time. Read coding has the added benefit of being an established electronic standard. In addition, the system would support traditional reporting methods such as EPINATO by providing increased assurance.