|
 |
| CONCEPT PAPER |
|
| Year : 2021 | Volume
: 14
| Issue : 1 | Page : 112-114 |
|
|
Creating a database for psychiatric disorders in the community of an urban and rural industrial areas of pimpri-chinchwad
Daniel Saldanha, Suprakash Chaudhury, Swaleha Mujawar, Amitav Banerjee
Department of Psychiatry, Dr D Y Patil Medical College, Hospital and Research Centre, Dr D Y Patil Vidyapeeth, Pune, Maharashtra, India
| Date of Submission | 10-Dec-2020 |
| Date of Decision | 12-Dec-2020 |
| Date of Acceptance | 15-Dec-2020 |
| Date of Web Publication | 22-Jan-2021 |
Correspondence Address:
Suprakash Chaudhury
Department of Psychiatry, Dr D Y Patil Medical College, Dr D Y Patil Vidyapeeth, Pimpri, Pune - 411 018, Maharashtra
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/mjdrdypu.mjdrdypu_702_20
Mental Health Issues are an important public health problem. It has also social and economic costs. The Government of India is implementing the National Mental Health Program which includes upgrading of Psychiatry services of the medical colleges so as to provide community psychiatry services. This concept paper discusses the modalities of setting up a data base of psychiatric illnesses in the field practice areas of a medical college located in the twin township of Pimpri-Chinchwad, Pune District, Maharashtra. This database will enable practice of community psychiatry in collaboration with the Department of Community Medicine and can be a model for adoption in other medical institutions and nonteaching public hospitals as well as private hospitals. Most psychiatric illnesses require follow up and a good digital tracking system would minimise attritions. It would also facilitate community based research in mental disorders.
Keywords: Community psychiatry, database, psychiatric disorders
How to cite this article:
Saldanha D, Chaudhury S, Mujawar S, Banerjee A. Creating a database for psychiatric disorders in the community of an urban and rural industrial areas of pimpri-chinchwad. Med J DY Patil Vidyapeeth 2021;14:112-4 |
How to cite this URL:
Saldanha D, Chaudhury S, Mujawar S, Banerjee A. Creating a database for psychiatric disorders in the community of an urban and rural industrial areas of pimpri-chinchwad. Med J DY Patil Vidyapeeth [serial online] 2021 [cited 2021 Mar 7];14:112-4. Available from: https://www.mjdrdypv.org/text.asp?2021/14/1/112/307689 |
Demographic data, clinical information, details of treatment, and service utilization data are now-a-days collected as a routine for the purposes of medical audit. Clinicians often view this as a waste of time, an avoidable burden imposed on them by bureaucratic overreach driven by political agendas. This is because of the lack of awareness among doctors of both the practical utility and immense research value of databases.[1] Despite growing attention from various medical disciplines for the research using “big data” resources, very little work has been done in psychiatry, due to various reasons including the lack of biomarkers or diagnostic findings on imaging and variability in the diagnosis. However, there is a long tradition of using routine data in psychiatric research from asylum records to research involving case registers. At present, especially in developed countries, large volumes of clinical data are accumulating in the form of electronic case records which can be utilized for the research.[2]
There are a large number of databases worldwide. The largest anonymous database of clinical data is the General Practice Research Database (GPRD) in the UK. It is based on the data from about 400 practices. It contains the data of 35 million patient years and includes the diagnoses of the subjects, treatment given, hospitalizations, and outcomes of treatment. The data are adequate for the purposes of psychiatric research.[3] A number of studies have been carried out using the GPRD database. One study concluded that suicide risk was determined by suicidal ideation, male sex, recent prescription of antidepressants, use of high doses, and a past history of using different antidepressants but not by the type of antidepressant.[4],[5] Another study of over 59,000 patients with depression revealed that switching of antidepressants occurred in 16%, most of them (72%) within 3 months of initiating treatment. Patients needing switching usually had a more severe disorder and past history of depressive episodes or other psychiatric disorders. They also had a higher prevalence of comorbid psychiatric disorders, particularly anxiety disorder and concurrent prescriptions of anxiolytics and hypnotics. Switching occurred most frequently with amitriptyline (27%) and least with venlafaxine (17%) and selective serotonin reuptake inhibitor (15%).[6] Another study analyzed 1.4 million registered psychiatric patients between 1993 and 1998 and identified 3969 patients having both substance use disorder and a psychiatric disorder. The baseline prevalence of psychiatric disorders and substance use disorders was 15% and 0.3%, respectively. Relative risk (RR) for psychiatric disorders in patients with substance user disorders compared with nonsubstance users was 1.54 (95% CI 1.47–1.62). RR for substance use disorders in patients with psychiatric disorders compared with nonpsychiatric disorders was 2.09 (95% CI 1.99–2.22). Population attributable risk (PAR) for psychiatric disorders attributable to substance use disorder was 0.2%. PAR for substance use disorders attributable to psychiatric disorder was 14.2%. The present study concluded that only a small percentage of psychiatric disorders are attributable to substance use disorders, while a larger percentage of substance use disorder may be attributable to psychiatric disorders.[7] Despite advances, there are limitations in each of these databases. A multidisciplinary team of psychiatrists, data scientists, and software engineers have recognized that ease of access, adequate protection of privacy of the data, and flexibility of data sources are the important qualities that would assure short- and long-term stability and usefulness of the platform. They also designed a prototype platform.[8]
According to the survey of World Health Organization, around 36% of the Indian population is afflicted by depression, and by the year 2020, depression would rank second among disorders with significant morbidity and the most common disorder among females.[9] One in 20 individuals (5.25%) in India 18 years and above have suffered from depressive episode at least once in their lifespan.[10],[11] National Mental Health Survey Data reveal that most of the individuals suffering from depressive disorder are either not diagnosed early or not treated appropriately, which leads to a vicious cycle of social and functional impairment with financial crisis and increase in the severity of depression.[12],[13]
Mental illness is a significant public health issue that needs to be taken care as it poses a great economic burden on society at large. Point prevalence for neuropsychiatric conditions is about 10% for the adult population.[14],[15] National Mental health Programme is being implemented by the Government of India to support the state governments to supply personnel trained in psychiatry for the district mental health programme. Under this scheme, 11 centers of excellence, 120 PG departments in mental health specialties, and upgradation of psychiatric wings of medical colleges were implemented.[10]
Pimpri-Chinchwad Municipal Corporation (PCMC) was initially formed by the merger of Pimpri, Chinchwad, Akurdi, and Bhosari villages. At present, Pimpri-Chinchwad is the twin city of Pune. The PCMC industrial area began in 1954 when Hindustan Antibiotics, a premier pharmaceutical company was established. Pimpri Chinchwad Council, which was formed in 1970, covered an area of about 87 sq. km became a Municipal Corporation in 1982. It covers an area of 181 sq. km. PCMC is considered one of the richest and fastest-growing municipal corporations in Asia.[11] The population of Pimpri Chinchwad city is about 17, 29,000 (as per 2011 census) with a growth rate of 6% annually as opposed to a national average of 2.1%. Rapid urbanization induces the problems of stress in the populace. Depression is one of the most common mental disorders that affect people irrespective of their age group, gender, and socioeconomic status. In India, depression leads to significant morbidity and socioeconomic loss.[16] It not only has a huge impact on the individual and his family but also leads to poor quality of life. It affects all the spheres of one's life, including day to day functioning, planning, organizing and executive skills, and renders consistent deterioration in performance.[9],[16]
Dr D Y Patil Medical College, Hospital is located in PCMC. This institution has adopted the Urban Health Center at Ajmera Pimpri and Rural Health Center at Alandi to cater to the requirements of community in respect of health. Patients are being screened for psychiatric disorders and those requiring psychiatric assessment are referred to the Psychiatry outpatient department for detailed evaluation [Figure 1]. If this information is stored in a computer then over time a database will be available for research. It would be beneficial to the community if a database is created regarding the psychiatric disorders prevalent in the community so that effective measures can be implemented to minimize the suffering by providing effective psychiatric care at the earliest and follow them up in the long run.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | |  |
| 1. | Higgins N, Howard L. Database use in psychiatric research: An international review. Eur J Psychiat 2005;19:19-30.  |
| 2. | Stewart R, Davis K. “Big data” in mental health research: current status and emerging possibilities. Soc Psychiatry Psychiatr Epidemiol 2016;51:1055-72. |
| 3. | Herrett E, Thomas SL, Schoonen WM, Smeeth L, Hall AJ. Validation and validity of diagnoses in the General Practice Research Database: a systematic review. Br J Clin Pharmacol 2010;69:4-14. |
| 4. | Jick SS, Dean AD, Jick H. Antidepressants and suicide. BMJ 1995;310:215-8. |
| 5. | Donovan S. The use of the general practice research database to examine potential links between antidepressant medication and the incidence of suicide. Drug Inf J 1996;30:785-92. |
| 6. | Saragoussi D, Chollet J, Bineau S, Chalem Y, Milea D. Antidepressant switching patterns in the treatment of major depressive disorder: A general practice research database (GPRD) study. Int J Clin Pract 2012;66:1079-87. |
| 7. | Frisher M, Crome I, Macleod J, Millson D, Croft P. Substance misuse and psychiatric illness: prospective observational study using the general practice research database. J Epidemiol Community Health 2005;59:847-50. |
| 8. | Aledavood T, Triana Hoyos AM, Alakörkkö T, Kaski K, Saramäki J, Isometsä E, et al. Data collection for mental health studies through digital platforms: Requirements and design of a prototype. JMIR Res Protoc 2017;6:e110. |
| 9. | |
| 10. | Mishra N, Nagpal SS, Chadda RK, Sood M. Help-seeking behavior of patients with mental health problems visiting a tertiary care center in north India. Indian J Psychiatry 2011;53:234-8. [ PUBMED] [Full text] |
| 11. | Menon S. Industrial zone. Pune diary. Pimpri-Chinchwad industrial belt: Placing Pune at the front. The Hindu Business Line. [Retrieved 29 January 2012.] |
| 12. | Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006;3:e442. |
| 13. | Sengupta P, Benjamin AI. Prevalence of depression and associated risk factors among the elderly in urban and rural field practice areas of a tertiary care institution in Ludhiana. Indian J Public Health 2015;59:3-8. [ PUBMED] [Full text] |
| 14. | Bhugra D, Thompson N, Piracha S, Kapoor J, Oommen G, Wing JC. Mental health of ethnic minority elders in west London: Pathways into secondary care. Indian J Psychiatry 2003;45:27-30. [ PUBMED] [Full text] |
| 15. | Sinha SK, Kaur J. National mental health programme: Manpower development scheme of eleventh five-year plan. Indian J Psychiatry 2011;53:261-5. [ PUBMED] [Full text] |
| 16. | |
[Figure 1]
|
Search Pubmed for