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Justin Graham

Publications and source records attributed to Justin Graham.

5 recordsLinked to original sources
PubMed2007

Consensus recommendations for the diagnosis, treatment and control of Mycobacterium ulcerans infection (Bairnsdale or Buruli ulcer) in Victoria, Australia.

Mycobacterium ulcerans causes slowly progressive, destructive skin and soft tissue infections, known as Bairnsdale or Buruli ulcer (BU). Forty-six delegates with experience in the management of BU attended a 1-day conference in Melbourne on 10 February 2006, with the aim of developing a consensus approach to the diagnosis, treatment and control of BU. An initial draft document was extended and improved during a facilitated round table discussion. BU is an environmental infection that occurs in specific locations. The main risk factor for infection is contact with an endemic area. Prompt cleaning of abrasions sustained outdoors, wearing protective clothing, and avoiding mosquito bites may reduce an individual's risk of infection. BU can be rapidly and accurately diagnosed by polymerase chain reaction testing of ulcer swabs or biopsies. Best outcomes are obtained when the diagnosis is made early. To aid early diagnosis, health authorities should keep local populations informed of new outbreaks. BU is best treated with surgical excision, which, if possible, should include a small rim of healthy tissue. For small lesions this may be all that is required. However, there is a role for antibiotics for more extensive disease, and their use may allow more conservative surgery.

Humans↗
PubMed2006

Comparison of methodologies for calculating quality measures based on administrative data versus clinical data from an electronic health record system: implications for performance measures.

New reimbursement policies and pay-for-performance programs to reward providers for producing better outcomes are proliferating. Although electronic health record (EHR) systems could provide essential clinical data upon which to base quality measures, most metrics in use were derived from administrative claims data. We compared commonly used quality measures calculated from administrative data to those derived from clinical data in an EHR based on a random sample of 125 charts of Medicare patients with diabetes. Using standard definitions based on administrative data (which require two visits with an encounter diagnosis of diabetes during the measurement period), only 75% of diabetics determined by manually reviewing the EHR (the gold standard) were identified. In contrast, 97% of diabetics were identified using coded information in the EHR. The discrepancies in identified patients resulted in statistically significant differences in the quality measures for frequency of HbA1c testing, control of blood pressure, frequency of testing for urine protein, and frequency of eye exams for diabetic patients. New development of standardized quality measures should shift from claims-based measures to clinically based measures that can be derived from coded information in an EHR. Using data from EHRs will also leverage their clinical content without adding burden to the care process.

Blood Pressure↗
PubMed2005

An approach to "failure to thrive".

BACKGROUND: Infants commonly present with failure to thrive. Psychosocial and nutritional causes are commonly responsible, but significant organic pathology requires exclusion in all children with failure to thrive. OBJECTIVE: This article discusses an approach to the assessment of infants presenting with failure to thrive, together with information on management and available resources. DISCUSSION: Close liaison between those involved in the management of infants presenting with failure to thrive--including family, maternal child health nurse, family doctor and paediatrician--should usually allow for appropriate intervention to correct the failure to thrive.

Child Nutrition Disorders↗
PubMed2002

Knowledge-based bioterrorism surveillance.

An epidemic resulting from an act of bioterrorism could be catastrophic. However, if an epidemic can be detected and characterized early on, prompt public health intervention may mitigate its impact. Current surveillance approaches do not perform well in terms of rapid epidemic detection or epidemic monitoring. One reason for this shortcoming is their failure to bring existing knowledge and data to bear on the problem in a coherent manner. Knowledge-based methods can integrate surveillance data and knowledge, and allow for careful evaluation of problem-solving methods. This paper presents an argument for knowledge-based surveillance, describes a prototype of BioSTORM, a system for real-time epidemic surveillance, and shows an initial evaluation of this system applied to a simulated epidemic from a bioterrorism attack.

Artificial Intelligence↗