Patient Care Flow with Awareness and Misdiagnosis

From SystemsWiki

Jump to: navigation, search

We will now slightly modify the general diagnosis and treatment model to capture more of the patient’s perspective, using an example we developed for people with migraine headaches. We have now divided people with a disease into unaware, aware, seeking treatment and on treatment states. We have also added the possibility of being misdiagnosed and people who switch treatment rather than discontinue. Here is an ithink model and outputs.

Contents

Swimming Pool Metaphor

Fig. 1 - Patient Care Flow Swimming Pool Metaphor [Source]

ithink model

Fig. 2 - Swimming Pool ithink Model Source

Model Output

Fig. 3 - Simulation Run Results Source

Discussion

A care episode is usually started by a person presenting to a health care service with a problem they believe can be helped by modern medical treatments. So expectations and awareness may be important reasons why people present to services. The completion of a care episode used to end with death or recovery. In chronic incurable health conditions there remains the ongoing need to manage the condition so the patients illness does not progress and they can maintain their function for as long as possible. Not only does this mean living well with disease and disability but also it means dying well with humane palliative care when the end of life is anticipated. In addition to presenting with problems, there has been an increasing trend for healthy people to have check-ups to detect diseases and abnormal conditions which will lead to later diseases and to participate in general health promotion and prevention activities.

An additional feature of clinical practice is the appropriate assessment and testing, followed by referral to the appropriate treatment and management services. Within this framework we try to maintain both the quality of the patient experience – being treated humanely and the technical quality of care by removing sources of error from individual events and delays and organizing safer systems. This task is made more difficult by the need to incorporate new technologies and adjust to increasing expectations of the many people involved in giving and receiving health care at the individual and population level. At the system level we need to balance resources to provide equitable care, which often may be at the expense of efficiency. We also need to guard against sub-optimising care in the short-term so that long-term outcomes are not compromised by overuse of limited resources. One early example of this suboptimization we encountered was the improved management of asthmatic attacks in the emergency department. Although a desirable outcome for asthmatics during an acute attack, this intervention had the unfortunate unintended long term effect of weakening the relationship between the asthma patient and her primary carer so chronic management to prevent acute attacks was postponed, leading to more frequent attacks and ED presentations. This model can be further extended to include spontaneous recovery and people with a history of disease. Also we need to adjust for the way the disease is diagnosed. This includes patient surveys of recent and life-time diagnoses and the rate at which past diagnoses are forgotten. This is an important problem in reconciling different estimates of mental illness and drug use. For further detail see Mark Paich Corey Peck and Jason Valant Pharmaceutical product strategy Using Dynamic Modeling for Effective Brand Planning Informa healthcare New York 2008 and second edition 2010 with Peck as main author. This book links patient flow, doctor adoption and treatment attractiveness for pharmaceutical strategy. It also covers the new drug pipeline.

Questions & Comments to Geoff McDonnell
Personal tools