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Digital transformation holds promise for addressing one of the biggest challenges in health care – misdiagnosis. About 30 per cent of health spending in 2009, i.e. roughly $750bn, was wasted on unnecessary services, excessive administrative costs, fraud and other problems. Moreover, inefficiencies cause needless suffering, states the Institute of Medicine. Leveraging emerging digital technologies in this sector stands to save thousands of lives and billions of dollars. Digital technology is being applied to this field owing to the great demand for a solution. Misdiagnosis is causing a major hemorrhaging hundreds of billions of dollars in the health industry – an estimated 10-20 per cent of cases are misdiagnosed, sometimes resulting in death or permanent disability, according to studies cited by the National Center for Policy Analysis. Additionally, experts believe as many as 31 per cent of all breast cancer cases are misdiagnosed, according to the New England Journal of Medicine, and 90,000 women are misdiagnosed with invasive breast cancer, according to Susan G. Komen.

Digital technology is being applied to this field owing to the great demand for a solution. Misdiagnosis is causing a major hemorrhaging hundreds of billions of dollars in the health industry – an estimated 10-20 percent of cases are misdiagnosed, sometimes resulting in death or permanent disability, according to studies cited by the National Center for Policy Analysis. Additionally, experts believe as many as 31 percent of all breast cancer cases are misdiagnosed, according to the New England Journal of Medicine, and 90,000 women are misdiagnosed with invasive breast cancer, according to Susan G. Komen.

Advance Medical’s experience is that 39 per cent of a self-selecting group of medical advocacy seekers are misdiagnosed. Directly related to this challenge, a major battleground where the war on escalating healthcare costs is being fought is in the space of utilization management tools, which help ensure insurers are paying for the right care. These tools depend on the doctor making the right diagnosis and that the treatment matches the diagnosis. But these tools are broken. Instead of checking accuracy of diagnosis (e.g. the right test was done and interpreted accurately), they are at best checking to see if the “box was checked” for any testing being done. The solution is to not only to ensure that the diagnosis is correct by having it reviewed independently but also to use technology to aid diagnosis and the physician’s overall job. Using tools such as patient portals and data management technology can aid doctors to not burn out from sorting through data but rather using healthcare technology to reduce physician exhaustion and thus misdiagnosis.

New and old tools hold promise for addressing one of the costliest and most able-to-be-impacted challenges in health care – misdiagnosis. Because of misdiagnosis, the health industry is hemorrhaging hundreds of billions of dollars and causing patients undue stress and negative medical impact. Not only does misdiagnosis have a strong effect on the economy and the solvency of the US health care system, it also has a profound effect on the people who are being misdiagnosed, as well as their families and loved ones.

The purpose of this paper is to establish a stylized model to solve the pricing strategy, resource allocation and consumer surplus problems of multichannel healthcare services.

This paper considers a two-stage decision model with different levels of consumers’ knowledge. Faced with physical problems, knowledgeable consumers can solve their problems by seeking online healthcare channels, while unknowledgeable consumers need to make a two-stage decision to try to solve their problems.

The effective diagnosis rate and the proportion of knowledgeable consumers positively impact the optimal pricing in online and offline channels. In addition, a higher proportion of knowledgeable consumers does not result in higher demand in the online and offline channels. Moreover, if service providers lower their prices a small amount, they will lose some profit, but the consumer surplus will be higher, which will encourage more consumers to access healthcare services.

Knowledge levels are simplified into two categories. Also, the authors assume the resources of online and offline healthcare services are comparable.

This paper incorporates the knowledge level and misdiagnosis rate into the model framework to study the most effective pricing strategy for multichannel healthcare services.

The purpose of this paper is to explore the different clinical features of pathological demand avoidance (PDA) and antisocial personality disorder (ASPD) presented in the form of a single case study. The study highlights the potential of misdiagnosis and conceptual confusions to practitioners in forensic settings between the two conditions when working with offenders with personality disorders.

A case formulation using the “five Ps” method based on the personal history of an incarcerated male is presented and the clinical similarities and differences between PDA and ASPD are delineated. These differences and similarities are evaluated and applied to offender management including intervention options.

There are considerable similarities between ASPD and PDA making the two conditions difficult to separate. Both diagnostic criteria identify childhood behavioural problems, aggression, destructiveness, conduct disorder (CD), manipulation and non-compliance as indications of the disorder. For example, the criteria for later adult ASPD are the presence of childhood antisocial behaviour and CD. However, these behaviours may also be suggestive of the attention deficit hyperactivity disorder and non-compliance that are part of PDA. Violent behaviours and aggression can also be perceived in a similar way. Misdiagnosis of PDA as ASPD reduces the efficiency of treatment programmes.

The implications of these findings could prove useful in the successful risk management of offenders with PDA. Given the similar behavioural characteristics between PDA and ASPD, the prevalence of PDA among offenders may be higher than observed. The aim of this study is to raise awareness of potential conceptual complications and clinical confusions between the two conditions with a view to aid offender management through case formulation. A large scale study into offenders with PDA would draw attention to the prevalence of the condition as well as its association with offending behaviour.

Purpose – One-third of the world's population is infected with tuberculosis (TB) and there are two million TB-related deaths worldwide every year. Along the U.S.-Mexico border, migration patterns, and reduced access to health care contribute to high rates of TB. Delayed diagnosis of TB, the focus of this chapter, increases the likelihood that a patient will progress to more advanced stages of the disease and heightens the risk of TB transmission to others as patients are contagious for longer periods of time.

Approach – Despite the seriousness of these consequences, few sociological studies have examined delayed diagnosis of TB and why people affected by TB symptoms delay care. Because of this, we take a health narratives approach to understanding the experiences of 15 TB patients of Mexican descent in a high-risk border community (e.g., El Paso, Texas) in order to discover why delayed diagnoses happen and how they impact patients.

Findings – Fourteen of the fifteen patients experienced delayed diagnosis. Analysis of these fourteen narratives revealed two broad themes: (1) provider lack of awareness, including repeated misdiagnosis and TB test errors, and (2) patient disadvantage, including fear of U.S. immigration authorities and few economic resources for care.

Implications – Findings from this study suggest that prompt diagnosis of TB could be achieved if providers were more cognizant of TB and its symptoms and public health policies increased access to health care regardless of immigration status or socioeconomic status.

This paper aims to improve the fault detection adaptive threshold of aircraft flap control system to make the system fault diagnosis more accurate.

According to the complex mechanical–electrical–hydraulic structure and the multiple fault modes of the aircraft flap control system, the advanced fault diagnosis method based on the bond graph (BG) model is presented, and based on the system diagnostic BG model, the parameter uncertainty intervals are estimated and a new adaptive threshold is constructed by linear fraction transformation.

To construct a more reasonable and accurate adaptive threshold range to more accurately detect system failures, some typical failure modes’ diagnosis process are selected and completed for verification; the simulation results show that the proposed method is effective and feasible for complex systems’ fault diagnosis.

This study can provide a theoretical guidance and technical support for fault diagnosis of complex systems, which avoid misdiagnosis and missed diagnosis.

This study enables more accurate fault detection and diagnosis of complex systems when considering factors such as parameter uncertainty.

The authors review the call for cultural competence in psychiatric diagnosis and highlight the barrier of ‘monocultural ethnocentrism’ ‐ the tendency to presume that European‐American standards fit all cultural, racial and ethnic groups. They suggest that clinicians should: familiarise themselves with the history of racism in psychiatry; avoid stereotyping; appreciate the diversity within cultural, racial and ethnic groups; understand that individuals from various cultural, racial and ethnic groups may have had more traumatic experiences; and understand that individuals from the US and UK may have experiences with racism, some of which may cause mental illness. Finally the authors suggest strategies to increase cultural competence.

Autistic women and girls have received comparatively less attention within clinical practice and research. Research suggests women tend to be diagnosed later than men, and are more likely to experience misdiagnosis.

This paper aims to report a narrative literature review that examines research on the presentation, recognition, and diagnosis of autistic women and girls.

Findings suggest that autistic females present differently to males and highlight low recognition of the female presentation of autism among the general public, in social spheres, educational, clinical and forensic settings. This lack of recognition appears to affect the likelihood of females being referred for diagnosis, the reliability of diagnostic assessments and subsequent access to support.

Recommendations for clinical practice focus on initiatives to increase awareness of the female presentation of autism, improving the diagnostic process for females, increasing female representation within autism training and for future research to support these goals.

Estimates of the prevalence of AS in children throughout the entire population of the United States are highly limited and greatly variable. Ozonoff, Dawson, and McPartland (2002) stated that estimates of AS range from 0.2 to 0.5% (or 2–5 individuals in 1,000), while Volkmar and Klin (2000) cited studies reporting rates of 36 in 1,000 to approximately 1 in 10,000. The Diagnostic and Statistical Manual of the American Psychiatric Association (2000), fourth edition (DSM-IV-TR), states that “definitive data about the prevalence of Asperger Syndrome does not exist.”

This study investigated disparities in dual diagnosis (comorbid substance use and depressive/anxiety disorders) among US adults by nativity and racial–ethnic origin and socioeconomic, cultural, and psychosocial factors that may account for the observed disparities.

The study drew on data from two waves of the National Epidemiological Survey on Alcohol and Related Conditions. Racial–ethnic categories included African, Asian/Pacific Islander, European, Mexican, Puerto Rican, and other Hispanic/Latino. Substance use and depressive/anxiety disorders were assessed per DSM-IV. A four-category measure of comorbidity was constructed: no substance use or psychiatric disorder; substance use disorder only; depressive/anxiety disorder only; and dual diagnosis. The data were analyzed using multinomial logistic regression.

The prevalence of dual diagnosis was low but varied by nativity, with the highest rates among Europeans and Puerto Ricans born in US states, and the lowest among Mexicans and Asians/Pacific Islanders. The nativity and racial–ethnic effects on likelihood of having dual diagnosis remained significant after all adjustments.

The limitations included measures of immigrant status, race–ethnicity, and stress and potential misdiagnosis of mental disorder among ethnic minorities.

This new knowledge will help to guide public health and health care interventions addressing immigrant mental and behavioral health gaps.

This study addressed the research gap in regard to the prevalence and correlates of dual diagnosis among immigrants and racial–ethnic minorities. The study used the most current and comprehensive data addressing psychiatric conditions among US adults and examined factors rarely captured in epidemiologic surveys (e.g., acculturation).

Patients are often ill‐equipped to know which speciality to choose for their health problem. Especially in the presence of non‐specific symptoms, choosing the right specialist might not be so obvious. In such cases, misdirected self‐referrals by patients to self‐chosen specialists can sometimes lead to misdiagnosis resulting in unwarranted delays in getting the right treatment. The general physicians, on the other hand, are in a unique position to oversee the big picture of patients’ health, and are therefore better equipped to identify and sort out their individual health problems. Hence instead of a specialist if the first place of contact for patients is a general physician, they are likely to be guided along the right path of treatment for their various health problems. Such a system will minimize errors on the part of the patients by making certain that they are referred to the appropriate specialists.