Mental health informatics

Mental health informatics is a branch of health or clinical informatics focused on the use of information technology (IT) and information to improve mental health. Like health informatics, mental health informatics is a multidisciplinary field that promotes care delivery, research and education [1] as well as the technology and methodologies required to implement it.

## Contents

* 1 Metrics and coding
* 2 Data collection and storage systems
* 2.1 Mobile and digital sensors
* 3 Telehealth
* 3.1 Patient perspectives
* 3.2 Technology to promote healthy practices
* 3.3 Augmenting care delivery
* 4 Data analysis
* 5 Need for mental health informatics
* 6 Concerns
* 7 References

## Metrics and coding

* Terminology and coding systems such as the (DSM)[2]
* Specific mental health assessment[3] and diagnostic [4] systems

## Data collection and storage systems

Systematic collection of information is fundamental to successful practices. Collecting data useful for mental illness diagnosis and treatment is challenging, as we lack quantitative biomarkers that might be used in standard health informatics, such as body temperature or blood pressure. Largely, current diagnosis and treatment is driven by clinical interviews between professionals and patients. Interviews are not only difficult to draw standardized data from because of diverse individual experience, condition, and accuracy of a patient's memory. Rapid advancements in computation and storage systems have the potential to transform this data collection process.[5] For example, a 2014 study in Ireland explored the use of a smartphone application to record daily mood and thoughts.[6] Such a collection process would provide plentiful standardized data less afflicted by patient recollection issues.

* Integration of mental health function into electronic health record systems (EHRs) and larger organisational systems

### Mobile and digital sensors

The ubiquity of smartphones and other mobile computing platforms is beginning to enable new types of data collection. Recent work has pioneered the use of passive data collection combined with analysis to provide highly relevant features such as: amount of time exposed to human speech, geospatial activity (total distance traveled throughout the day), physical activity, and sleep duration.[7] Additionally, researchers are prototyping simple mobile applications that could replace portions of infrequent qualitative clinical interviews with more regular quantitative data.[8][6][9]

## Telehealth

Telehealth, telemedicine and telepsychiatry are new care delivery methods made possible by information technology. Specifically, there is a body of research investigating the use of mobile devices to deliver treatment suggestions or treatment reminders in the context of mental health.

Much of the telehealth literature is concerned with patient populations that are difficult to provide traditional medical care to, such as those in rural locations, soldiers, or veterans. These groups stand to benefit from telehealth practices. An inspector general review of US Veterans Affairs facilities in North Carolina and Virginia revealed that 36% of patients had to wait more than a month for appointments.[10] Telehealth professionals are interested in decreasing these wait times by increasing aspects of appointment efficiency.

### Patient perspectives

Of course, introducing significant use of new technology into medical practice is a large departure from conventional mental health treatment. Several studies investigate the effect of introducing technology into general medical interventions as well as mental health treatments specifically. A review of several studies found that patients were generally satisfied with the medical care received via Telehealth, however the effectiveness and efficiency of programs reported mixed results. In many studies it's challenging to determine if the outcomes were a result of the introduction of technology, as authors fail to describe why they are making such an intervention.[11]

A study investigating the design of a passive mental health mobile application for use by teenagers and young adults indicated that teenagers would be most open to using technology to help with mental health issues if it was developed as a smartphone application. Additionally, teenagers would be more motivated in using such applications if there was a social or gamified component, however they expressed potential concern about negative perceptions about using the app.[6] Research indicates that while older patients struggle to accept changes in care, technological resistance is generational, indicating that current and future generations would be open to using telehealth.[12]

### Technology to promote healthy practices

In addition to providing more accurate and reliable data for mental health care providers, smartphones have the ability to provide reminders for healthy practices and appointments. Jen Hyatt, the founder and CEO of Big White Wall, a UK behavioral health social enterprise, comments that existing mental healthcare focuses on diseases rather than health practices and behaviors.[13] Particularly, research has shown that how much we travel and communicate with other people throughout the day is an important factor in our overall mental health. Future applications may leverage location systems in modern mobile phones to track a user's geospatial activity and suggest certain actions through notifications if dangerous patterns are detected.[14]

### Augmenting care delivery

In addition to new types of treatments and interactions, the introduction of technology and informatics has the ability to improve existing mental healthcare effectiveness and efficiency. A UK based study found that a simple digital intervention such as sending SMS (text message) reminders to patients a few days before a mental health appointment decreased missed clinical appointments by 25% to 28%, translating to a potential cost savings of more than £150 million.[15]

## Data analysis

Collection of enormous amounts of structured data on mental health patients introduces the possibility of improved mental health care, mental health policy, and overall perception of mental health. This analysis would be performed on a macro-scale, the study of the incidence of mental health in a public health and epidemiological context.[16]

## Need for mental health informatics

The need for and application of health informatics in primary and secondary health care has been well established in developed countries for 20 years or more.[17] The application of informatics in mental health has not become as pervasive, in spite of professional recognition[18][19] the domain appearing well suited to computerisation [20] and the need for quantified outcome evidence.[21] There also may be a professional reluctance to effect changes in established working patterns that the introduction of systems necessarily entails.[22]

## Concerns

Data and information in health informatics are inherently private and personal. Pervasive software systems designed to help diagnose and treat mental health symptoms expose a privacy vulnerability and will likely require regulatory standards and data protection compliance such as HIPAA to protect patients. A major impediment may be societal stigma associated with mental disorders as well as increased sensitivity about protecting the privacy and confidentiality of records in mental health care.[23]

## References

1. ↑ "Mental health informatics - Clinfowiki". http://www.clinfowiki.org/wiki/index.php?title=Mental_health_informatics.
2. ↑ "NIMH » Different Approaches to Understanding and Classifying Mental Disorders". https://www.nimh.nih.gov/news/science-updates/2017/different-approaches-to-understanding-and-classifying-mental-disorders.
3. ↑ "Information for researchers and professionals about the Strengths & Difficulties Questionnaires". https://sdqinfo.org/.
4. ↑ "Dawba". https://www.dawba.info/.
5. ↑ Aledavood, Talayeh; Triana Hoyos, Ana Maria; Alakörkkö, Tuomas; Kaski, Kimmo; Saramäki, Jari; Isometsä, Erkki; Darst, Richard K. (2017). "Data Collection for Mental Health Studies Through Digital Platforms: Requirements and Design of a Prototype". JMIR Research Protocols 6 (6): e110. doi:10.2196/resprot.6919. PMID 28600276.
6. ↑ 6.0 6.1 6.2 Kenny, Rachel; Dooley, Barbara; Fitzgerald, Amanda (2016). "Developing mental health mobile apps: Exploring adolescents' perspectives". Health Informatics Journal 22 (2): 265–275. doi:10.1177/1460458214555041. PMID 25385165. https://researchrepository.ucd.ie/bitstream/10197/6275/1/V2_Kenny_et_al._(2014)_Developing_Mental_Heath_Mobile_Apps.pdf. Retrieved 2019-09-29.
7. ↑ Ben-Zeev, Dror; Scherer, Emily A.; Wang, Rui; Xie, Haiyi; Campbell, Andrew T. (2015). "Next-Generation Psychiatric Assessment: Using Smartphone Sensors to Monitor Behavior and Mental Health". Psychiatric Rehabilitation Journal 38 (3): 218–226. doi:10.1037/prj0000130. PMID 25844912.
8. ↑ LiKamWa, Robert; Liu, Yunxin; Lane, Nicholas D.; Zhong, Lin (2013). "MoodScope: Building a mood sensor from smartphone usage patterns". Proceeding of the 11th annual international conference on Mobile systems, applications, and services. pp. 389–402. doi:10.1145/2462456.2464449. ISBN 978-1-4503-1672-9.
9. ↑ Luxton, David D.; McCann, Russell A.; Bush, Nigel E.; Mishkind, Matthew C.; Reger, Greg M. (2011). "mHealth for Mental Health: Integrating Smartphone Technology in Behavioral Healthcare". Professional Psychology: Research and Practice 42 (6): 505–512. doi:10.1037/a0024485.
10. ↑ Slack, Donovan (March 3, 2017). "Inaccurate VA wait times preclude thousands of vets from getting outside care, probe finds". USA Today (WASHINGTON). https://www.usatoday.com/story/news/politics/2017/03/03/veterans-affairs-inspector-general-widespread-inaccuracies-wait-times/98693856/.
11. ↑ Kruse, Clemens Scott; Krowski, Nicole; Rodriguez, Blanca; Tran, Lan; Vela, Jackeline; Brooks, Matthew (2017). "Telehealth and patient satisfaction: a systematic review and narrative analysis". BMJ Open 7 (8). doi:10.1136/bmjopen-2017-016242. PMID 28775188.
12. ↑ Kruse, Clemens Scott; Mileski, Michael; Moreno, Joshua (2017). "Mobile health solutions for the aging population: A systematic narrative analysis". Journal of Telemedicine and Telecare 23 (4): 439–451. doi:10.1177/1357633X16649790. PMID 27255207.
13. ↑ Hyatt, Jen (May 9, 2016). "How Big Data is Improving Mental Healthcare". Wired UK. https://www.youtube.com/watch?v=y2oHVQmOeNU.
14. ↑ Lam, Megan (July 24, 2018). "How Your Digital Data Can Help Mental Health Research". TEDxWanChai. https://www.youtube.com/watch?v=zRJArd5hc_4.
15. ↑ Sims, Hannah; Sanghara, Harpreet; Hayes, Daniel; Wandiembe, Symon; Finch, Matthew; Jakobsen, Hanne; Tsakanikos, Elias; Okocha, Chike Ify et al. (2012). "Text Message Reminders of Appointments: A Pilot Intervention at Four Community Mental Health Clinics in London". Psychiatric Services 63 (2): 161–168. doi:10.1176/appi.ps.201100211. PMID 22302334. http://psychiatryonline.org/article.aspx?articleID=433008. Retrieved 2020-08-28.
16. ↑ Ardis Hanson and Bruce Lubotsky Levin. Mental Health Informatics. Oxford University Press USA, 2013, 288 pp, ISBN 9780195183023.
17. ↑ Smith MF. Computer Systems in Healthcare: Management and Strategy. Kindle (2012) ISBN 978-1-301-36918-8.
18. ↑ "Informatics Committee". http://www.rcpsych.ac.uk/policyandparliamentary/informaticscommittee.aspx.
19. ↑ "Archived copy". http://www.healthcareconferencesuk.co.uk/news/newsfiles/Netta_Hollings_61.pdf.
20. ↑ Rotheray, Sebastian; Racey, Daniel; Rodgers, Lauren; McGilloway, Sinead; Berry, Vashti; Ford, Tamsin (2014). "Innovations in Practice: Further evidence on the effectiveness of the strengths and difficulties added value score as an outcome measure for child and adolescent services". Child and Adolescent Mental Health 19 (4): 270–273. doi:10.1111/camh.12059. PMID 32878351. http://clok.uclan.ac.uk/23192/7/23192 SDQSubmissionChangesV2 13 nov 2013.pdf. Retrieved 2020-11-05.
21. ↑ Stringaris, A.; Goodman, R. (2009). "Longitudinal outcome of youth oppositionality: Irritable, headstrong, and hurtful behaviors have distinctive predictions". Journal of the American Academy of Child & Adolescent Psychiatry 48 (4): 404–412. doi:10.1097/CHI.0b013e3181984f30. PMID 19318881.
22. ↑ "Interview med Robert Goodman". http://sdq-dawba.dk/interview-goodman/.
23. ↑ "How Societal Stigma Complicates Privacy Protection in Digital Mental Health". https://healingpixel.com/how-societal-stigma-complicates-privacy-protection-in-digital-mental-health/.

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