548903 research-article2014
ANP0010.1177/0004867414548903Australian & New Zealand Journal of PsychiatryStanley and Laugharne
Viewpoint Australian & New Zealand Journal of Psychiatry 2014, Vol. 48(10) 889–894 DOI: 10.1177/0004867414548903
Physical health algorithms for mental health care
© The Royal Australian and New Zealand College of Psychiatrists 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav anp.sagepub.com
Susanne H Stanley and Jonathan DE Laugharne
Introduction It has been known for some time that many people with severe mental illness experience comorbid physical health problems (Lawrence et al., 2001). Indeed, the gap in life expectancy has widened between people with a mental illness and the general population for preventable illness, with most excess deaths (around 80%) associated with physical health conditions such as cardiovascular disease, cancer, and respiratory disease (Lawrence et al., 2013). Mortality rates coupled with high prevalence rates for other health conditions such as obesity and type 2 diabetes mellitus highlight the need for a pre-treatment baseline physical health assessment and ongoing monitoring (Bradshaw and Mairs, 2014; Stanley and Laugharne, 2011, 2014; Stanley et al., 2013). There is, therefore, an increasing requirement for an emphasis on preventative measures rather than reactive measures. Many mental health services around Australia are now implementing physical health screening protocols for mental health patients, with some states well ahead of others (New South Wales Department of Health, 2009). In Western Australia, the South Metropolitan Health Service (SMHS) Mental Health Physical Health Care Strategy Working Group acknowledged a need for the additional training of mental health staff. In order to assist with this process, we have developed a number of algorithms to aid clinical staff (doctors/ nurses) in the management of patients’
physical health and we present these algorithms here. These algorithms complement our Clinical Guidelines package (Stanley and Laugharne, 2011), which takes an holistic approach to physical health assessment and ongoing monitoring in the areas of lifestyle, medication effects, alcohol and drug problems, pre-existing or developing physical disorders and allergies, and social supports. The metabolic syndrome (MetS) algorithm (Figure 1) assesses blood pressure, waist circumference, fasting lipids and fasting blood glucose. Additional algorithms have been included in this paper covering clinical decision pathways for a number of key investigations – full blood count, liver function tests, urea and electrolytes (Figure 2), thyroid function tests, electrocardiogram (ECG) and serum prolactin (Figure 3). All algorithms were reviewed by a number of health professionals, including general practitioners, psychiatrists, and nursing staff. They were then endorsed for use in local mental health clinics by the Stokes Mental Health Review Implementation Steering Committee, a taskforce formed to ensure the consistent implementation of effective services, policies and practices within Western Australia mental health.
mellitus and cardiovascular disease (Barnes et al., 2008; International Diabetes Federation (IDF), 2006; Waterreus and Laugharne, 2009). The core components of MetS are central obesity, hypertension, hyperglycaemia and dyslipidaemia. As this condition is more prevalent in people with a mental illness when compared to the general population (Ganguli and Strassnig, 2011; John et al., 2009), screening is essential and must be conducted regularly (i.e. every 3–6 months), dependent upon the general health of the patient and the medication he/she is prescribed. The MetS algorithm details IDF (2006) worldwide consensus reference ranges for waist circumference, blood pressure, fasting lipids and fasting blood glucose (Waterreus and Laugharne, 2009). To be defined as having the MetS according to the IDF (2006) definition, an individual must have central obesity plus two of the remaining four factors – reduced highdensity lipoprotein cholesterol, or elevated triglycerides, blood pressure or fasting blood glucose – or be receiving treatment for at least two previously diagnosed conditions such
Metabolic syndrome
Corresponding author: Susanne H Stanley, Community, Culture and Mental Health Unit, School of Psychiatry and Clinical Neurosciences, University of Western Australia, Fremantle Hospital, W Block, L6, 1 Alma Street, Fremantle, WA 6160, Australia. Email: [email protected]
The first of the algorithms relates to MetS, a cluster of risk factors which contributes to increased risk for conditions such as type 2 diabetes
Community, Culture and Mental Health Unit, School of Psychiatry and Clinical Neurosciences, University of Western Australia, Fremantle, Australia
Australian & New Zealand Journal of Psychiatry, 48(10)
Downloaded from anp.sagepub.com at Bobst Library, New York University on May 5, 2015
Australian & New Zealand Journal of Psychiatry, 48(10) Downloaded from anp.sagepub.com at Bobst Library, New York University on May 5, 2015 Asian
Review medication Treat/refer to GP Consider referral to physiotherapy or group programme
>85mmHg
>1.03mmol/L (M) >1.29mmol/L (F)
>1.03mmol/L (M) >1.29mmol/L (F)
Baseline and 3 monthly monitoring
Within normal range no action required
Review medication Treat/refer to GP Consider referral to physiotherapy or group programme
HDL
>1.7mmol/L
Triglycerides
HDL
80cm (F)
>80cm (F)
ANP0010.1177/0004867414548903Australian & New Zealand Journal of PsychiatryStanley and Laugharne
Viewpoint Australian & New Zealand Journal of Psychiatry 2014, Vol. 48(10) 889–894 DOI: 10.1177/0004867414548903
Physical health algorithms for mental health care
© The Royal Australian and New Zealand College of Psychiatrists 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav anp.sagepub.com
Susanne H Stanley and Jonathan DE Laugharne
Introduction It has been known for some time that many people with severe mental illness experience comorbid physical health problems (Lawrence et al., 2001). Indeed, the gap in life expectancy has widened between people with a mental illness and the general population for preventable illness, with most excess deaths (around 80%) associated with physical health conditions such as cardiovascular disease, cancer, and respiratory disease (Lawrence et al., 2013). Mortality rates coupled with high prevalence rates for other health conditions such as obesity and type 2 diabetes mellitus highlight the need for a pre-treatment baseline physical health assessment and ongoing monitoring (Bradshaw and Mairs, 2014; Stanley and Laugharne, 2011, 2014; Stanley et al., 2013). There is, therefore, an increasing requirement for an emphasis on preventative measures rather than reactive measures. Many mental health services around Australia are now implementing physical health screening protocols for mental health patients, with some states well ahead of others (New South Wales Department of Health, 2009). In Western Australia, the South Metropolitan Health Service (SMHS) Mental Health Physical Health Care Strategy Working Group acknowledged a need for the additional training of mental health staff. In order to assist with this process, we have developed a number of algorithms to aid clinical staff (doctors/ nurses) in the management of patients’
physical health and we present these algorithms here. These algorithms complement our Clinical Guidelines package (Stanley and Laugharne, 2011), which takes an holistic approach to physical health assessment and ongoing monitoring in the areas of lifestyle, medication effects, alcohol and drug problems, pre-existing or developing physical disorders and allergies, and social supports. The metabolic syndrome (MetS) algorithm (Figure 1) assesses blood pressure, waist circumference, fasting lipids and fasting blood glucose. Additional algorithms have been included in this paper covering clinical decision pathways for a number of key investigations – full blood count, liver function tests, urea and electrolytes (Figure 2), thyroid function tests, electrocardiogram (ECG) and serum prolactin (Figure 3). All algorithms were reviewed by a number of health professionals, including general practitioners, psychiatrists, and nursing staff. They were then endorsed for use in local mental health clinics by the Stokes Mental Health Review Implementation Steering Committee, a taskforce formed to ensure the consistent implementation of effective services, policies and practices within Western Australia mental health.
mellitus and cardiovascular disease (Barnes et al., 2008; International Diabetes Federation (IDF), 2006; Waterreus and Laugharne, 2009). The core components of MetS are central obesity, hypertension, hyperglycaemia and dyslipidaemia. As this condition is more prevalent in people with a mental illness when compared to the general population (Ganguli and Strassnig, 2011; John et al., 2009), screening is essential and must be conducted regularly (i.e. every 3–6 months), dependent upon the general health of the patient and the medication he/she is prescribed. The MetS algorithm details IDF (2006) worldwide consensus reference ranges for waist circumference, blood pressure, fasting lipids and fasting blood glucose (Waterreus and Laugharne, 2009). To be defined as having the MetS according to the IDF (2006) definition, an individual must have central obesity plus two of the remaining four factors – reduced highdensity lipoprotein cholesterol, or elevated triglycerides, blood pressure or fasting blood glucose – or be receiving treatment for at least two previously diagnosed conditions such
Metabolic syndrome
Corresponding author: Susanne H Stanley, Community, Culture and Mental Health Unit, School of Psychiatry and Clinical Neurosciences, University of Western Australia, Fremantle Hospital, W Block, L6, 1 Alma Street, Fremantle, WA 6160, Australia. Email: [email protected]
The first of the algorithms relates to MetS, a cluster of risk factors which contributes to increased risk for conditions such as type 2 diabetes
Community, Culture and Mental Health Unit, School of Psychiatry and Clinical Neurosciences, University of Western Australia, Fremantle, Australia
Australian & New Zealand Journal of Psychiatry, 48(10)
Downloaded from anp.sagepub.com at Bobst Library, New York University on May 5, 2015
Australian & New Zealand Journal of Psychiatry, 48(10) Downloaded from anp.sagepub.com at Bobst Library, New York University on May 5, 2015 Asian
Review medication Treat/refer to GP Consider referral to physiotherapy or group programme
>85mmHg
>1.03mmol/L (M) >1.29mmol/L (F)
>1.03mmol/L (M) >1.29mmol/L (F)
Baseline and 3 monthly monitoring
Within normal range no action required
Review medication Treat/refer to GP Consider referral to physiotherapy or group programme
HDL
>1.7mmol/L
Triglycerides
HDL
80cm (F)
>80cm (F)
