| Abstract|| |
Background: There is little information available on the type, pattern, trend, and demographic differentials of psychiatric cases attending a subdistrict level facility in India. Our objectives were to describe the sociodemographic profile of the patients availing the psychiatric outpatient department services and document the diagnosis.
Materials and Methods: This study is based on a retrospective analysis of routinely recorded administrative data collected during psychiatry consultations that took place between January 2010 and June 2014, at the subdistrict level hospital, Ballabgarh, Faridabad district, Haryana, Northern India. The data were abstracted in Microsoft Excel, scrutinized for duplicates, and cleaned in terms of the International Classification of Diseases 10th Revision coding. Descriptive analysis was done for dependent variables and continuous variables were compared using independent t-test.
Results: A total of 2806 people (new registrations) were provided psychiatric consultations between January 2010 and June 2014. The mean age of males was 33.7 years (95% confidence interval [CI], 32.9, 34.5) and of females was 35.6 years (95% CI, 34.9, 36.3). Neurotic, stress-related, and somatoform disorders (F40–F48) comprised the major category of diagnoses with 661 cases (24%), followed by unspecified mental disorders (F99) with 528 cases (19%), mood (affective) disorders (F30–F39) with 448 cases (16%), and episodic and paroxysmal disorders (G40–G47) with 334 cases (12%).
Conclusions: We reported an increase in level and trend in the monthly attendance of patients who required psychiatric at a secondary care hospital in Northern India. We suggest that setting up of mental health units only at district hospital might not be a sufficient health system's approach as has been envisaged under the District Mental Health Program.
Keywords: Age group, diagnosis, diseases, India, mental illness, pattern, prevalence
|How to cite this article:|
Haldar P, Sagar R, Malhotra S, Kant S. Burden of psychiatric morbidity among attendees of a secondary level hospital in Northern India: Implications for integration of mental health care at subdistrict level. Indian J Psychiatry 2017;59:176-82
|How to cite this URL:|
Haldar P, Sagar R, Malhotra S, Kant S. Burden of psychiatric morbidity among attendees of a secondary level hospital in Northern India: Implications for integration of mental health care at subdistrict level. Indian J Psychiatry [serial online] 2017 [cited 2019 Oct 17];59:176-82. Available from: http://www.indianjpsychiatry.org/text.asp?2017/59/2/176/210739
| Introduction|| |
The World Health Organization (WHO) defines health as the presence of physical, social, and mental well-being and not merely the absence of disease. However, globally, one out of four people is affected with some kind of mental illness, and an estimated 80% of them live in low- and middle-income countries. As per the Global Burden of Disease Study (2013), mental disorders accounted for 13% of total DALYs. Compared to the DALY loss around 6% as per the Global Burden of Disease Study (2010), the current levels are almost double. The WHO's Mental Health Action Plan calls for an increase in service coverage for severe mental disorders by at least 20% by the year 2020. The highest prevalence of mental illness is observed in the age group of 25–44 years, the most productive years of life. It has grave social and economic implications for the individual, families, and societies.
The community-based epidemiological studies conducted in India on mental and behavioral disorders report varying prevalence rates, ranging from 9.5 to 102/1000 population. According to an analysis of data published in the report of the National Sample Survey Organization (2002) on disability, overall population prevalence of mental illness was 14.9/1000, higher in rural areas (17.1/1000) than urban (12.7/1000). Between 1990 and 2013, the estimated burden of mental disorders in India grew by 44% along with neurological and substance use disorders; this is estimated to increase further by 23% in India between 2013 and 2025. The poor state of individual in this period of the life cycle leads to severe degrees of unproductivity and its spiraling effects on quality of life with associated stigma. The gross disparity between the number of mentally ill persons and the available treatment facilities and trained professionals is reflected in the large “treatment gap” in the community.
The National Mental Health Survey of India, 2016, conducted among a nationally representative sample of 34,802 individuals, sampled across 12 states of India reported a lifetime prevalence of mental morbidity in the surveyed population as 13.7%. This proportion translates to a large number of people in India, who suffer from a mental disorder and require treatment, care, and support to be able to lead economically and socially productive life.
There are an estimated 0·3 psychiatrists per 100,000 people in India, and as per the 2002 National Survey of Mental Health Resources that corresponds to a shortfall of 77%., A large proportion of people seek care from traditional and faith healers, particularly for psychoses and epilepsy, often delaying biomedical care. Nevertheless, the utilization of the available resources for mental illness is suboptimal owing to the ignorance about the presence of treatment facility and associated stigma in utilizing them. The primary governmental response in India has been through the National Mental Health Program (NMHP), launched in 1982. The District Mental Health Program (DMHP) was launched in 1996 for providing community-oriented services that had envisioned the presence of a district mental health unit at each district hospital.
At present, (as of 2014) the coverage was 241 (36%) districts, with a target to cover all districts in the country by the year 2017. Furthermore, integration with primary care is envisaged as one of the important facets of the NMHP. In the year 2014, one of the large southern state (Karnataka) in India launched an innovative initiative, “the Manochaitanya” to integrate mental health in all public health-care institutions within the administrative divisions, i.e., district hospitals, with community health centers and primary health centers. It includes provisions for distribution of certain psychiatric drugs and training of doctors.
The National Mental Health Survey reaffirmed that the current planning of mental health programs in India was “hampered by the lack of valid, reliable, timely, sensitive, and specific outcome indicators” with hardly any use of routine data. Moreover, the strategic planning for prioritization of mental health program needs at a district would require information on psychiatric caseloads at subdistrict level also, which is totally lacking as of date. There is little information on the type, pattern, trend, and demographic differentials of psychiatric cases attending a subdistrict level facility in India. Hence, our objectives were to describe the sociodemographic profile of the patients availing the psychiatric outpatient department services and document the diagnosis as well as caseload in a subdistrict hospital (SDH) setting in India.
| Materials and Methods|| |
This study is based on a retrospective analysis of routinely recorded administrative data collected during psychiatry consultations that took place between January 2010 and June 2014, at the SDH, Ballabgarh, Faridabad district, Haryana, Northern India. The present study was a secondary analysis of the routinely collected service provision-related information on patient's attendance and diagnosis made at the psychiatry clinic of secondary level civil hospital at Ballabgarh taluk of Faridabad district, Haryana, India. The overall administration of this civil hospital was the responsibility of the Centre for Community Medicine of the All India Institute of Medical Sciences, New Delhi, managed through its Comprehensive Rural Health Services Project at Ballabgarh. The SDH provided daily outpatient services in the specialties of medicine, surgery, obstetrics and gynecology, pediatrics, ophthalmology, dental, and AYUSH, apart from the daily psychiatry clinics. Selected days on week were earmarked for certain special consultations that included antenatal cases, noncommunicable diseases, ear-nose-throat cases, orthopedics, physical medicine and rehabilitation, and pediatric surgery. The SDH served mostly periurban and rural areas adjoining it. Through its sixty beds, this SDH catered to inpatient care in medicine, surgery, obstetrics and gynecology, pediatrics, and ophthalmology. This health facility also served as a first referral unit to two primary health centers, namely, Dayalpur and Chhainsa, situated at a distance of 10 and 20 km from SDH, respectively. Utilization of the facility was high with a total outpatient attendance of more than 2.25 lakhs in year 2013 and total admissions of more than 57,000 in the same year. Usual attendance at outpatient clinics, all specialties combined were around 1000/day. We analyzed the clinic-based data for the psychiatry consultations, provided by psychiatrist, between January 2010 and June 2014. The routine information recorded patient's central registration number, age, sex, and diagnosis. The diagnoses were coded as per the International Classification of Diseases 10th Revision (ICD-10) criteria. A preliminary check for duplication was performed using a combination of names and patient's central registration number, and thus, the duplicate entries were identified and removed. Final data were delinked of the name and central registration number so as to anonymize the information of any personal identifier.
The data were abstracted in Microsoft Excel, scrutinized for duplicates, and cleaned in terms of the ICD-10 coding. The final analysis was done in Stata version 12, StataCorp College Station, Texas, USA. Descriptive analysis was done for dependent variables and continuous variables were compared using independent t-test.
| Results|| |
First, we present the results for the cumulative data. A total of 2806 people (new registrations) were provided psychiatric consultations between January 2010 and June 2014, out of which 1321 were males and 1485 were females [Table 1]. The mean age of males was 33.7 years (95% confidence interval [CI], 32.9, 34.5) and of females was 35.6 years (95% CI, 34.9, 36.3). On an average, for all cases taken together across the years, males were found to be about 2 years younger than females, and this was statistically significant with P = 0.0002 (independent samples t-test).
|Table 1: International Classification of Diseases 10th Revision classification of diagnosed disorders|
Click here to view
Out of 2806 cases that we analyzed, diagnosis could not be reported for 5.4% of the cases that included 103 for which diagnostic entry was not clear and another 51 which had missing information. [Table 1] lists the diagnoses as per the ICD-10 classification. Neurotic, stress-related, and somatoform disorders (F40–F48) comprised the major category of diagnoses with 661 cases (24%), followed by unspecified mental disorders (F99) with 528 cases (19%), mood (affective) disorders (F30–F39) with 448 cases (16%), and episodic and paroxysmal disorders (G40–G47) with 334 cases (12%). The schizophrenia, schizotypal, and delusional disorders (F20–F29) were the diagnosis in 238 cases (8%). Rest comprised ≤1% of the total cases [Table 1]. Episodic and paroxysmal disorders were the type of presentation in 334 (12%) cases. Common mental disorders including depression, anxiety, panic disorder, phobias, and obsessive-compulsive disorder (OCD) comprised 86.6% of the diagnoses.
We further analyzed for each of the major ICD-10 diagnosis reported in [Table 1] (the components) and described them by sex and mean age [Table 2]. Majority of the disorders under “neurotic, stress-related, and somatoform disorders” comprised anxiety disorders and somatoform disorders. On an average, males who reported with anxiety disorders were about 4 years younger in age than the females; it was statistically significant. Males who reported with OCDs were also significantly younger than females by about 7 years. Bipolar affective disorder and depressive episode were the major categories under “mood and affective disorders.” Tension-type headache and migraine were the major component diagnoses among the ICD coding of episodic and paroxysmal disorders. The males reporting with tension-type headaches were significantly younger, compared to the females.
We also looked at the trend of the number of cases attending over the period as a function of half-yearly time points [Table 3] and plotted a linear regression-based forecast using Microsoft Excel [Figure 1].
|Figure 1: Trend of patient attendance, by month, for data from Jan 2010, to Jun 2014. The trend line is a linear plotted using a linear regression based forecast using Microsoft Excel, the equation for which is given in the figure. y axis: Number of patients|
Click here to view
| Discussion|| |
We report the profile of patients who attended the psychiatric outpatient clinic of a subdistrict level hospital in North India, over a period of 4½ years starting from January 2010 to June 2014. The important message is that large numbers of patients requiring psychiatric consultation presented every month at this subdistrict hospital of North India. This reflects the burden of psychiatric illnesses existing at the periurban and rural setting of this North Indian town and the resulting mental healthcare need. Furthermore, the month-wise number of patients attending the clinic showed an increasing trend. On average, male patients were 2 years younger than females, which was statistically significant. Almost half of the patients were females and this had remained constant across the 54 months of study period. This might be reflective of the fact that while access to psychiatric care was not dependent on gender, perhaps, males were more forthcoming in terms of seeking an early institutional care for their problems. However, we must keep in mind that the majority of these patients had been referred from medicine outpatient clinic; only a small proportion of the patient attending the psychiatric clinic comprised direct walk-in clients.
The major diagnoses as per the ICD-10 coding comprised the neurotic, stress-related, and somatoform disorders, mood disorders, episodic and paroxysmal disorders, schizophrenic disorders, and delusional disorders. Due to differences in study methods and denominators used, it is difficult to compare our findings across studies. In a study from North India conducted in a tertiary care center, Singh et al. determined the pattern of psychiatric services utilization among 12,058 psychiatric patients restricted to four broad categories of diagnosis (mood disorders [F30–39]: neurotic stress-related and somatoform disorders [F40–48], schizophrenia, schizotypal, and delusional disorders [F20–29], and mental and behavioral disorders due to psychoactive substance use [F10–19]). The majority of those patients were suffering from neurotic stress-related and somatoform disorders (37%), followed by 35% of patients with mood disorders; schizophrenia, schizotypal, and delusional disorders constituted 12% of the total study population while those with mental and behavioral disorders due to psychoactive substance use constituted 16% of the study population. In our case as well, majority of the diagnosed cases were of neurotic, stress-related, and somatoform disorders (24%), followed by mood disorders (16%). Although the proportion of diagnoses for neurotic and mood disorders were lesser, which is perhaps due to the fact that our setting was a subdistrict hospital, surprisingly, the proportion of schizophrenia, schizotypal, and delusional disorders constituted 8% of all diagnoses which was not very far from what had been reported from tertiary care setting.
Almost one-fifth of the diagnoses were that of unspecified mental illness. While this being a retrospective study restricted us to investigate it in-depth, one possible explanation could be that these are reflective of an attendance of subthreshold psychiatric illness. As reported by Karsten et al., these might predict in the future a full-blown psychiatric illness, thereby carrying an implication for the future psychiatric caseload at subdistrict level health-care facilities.
Strength of our analysis was that the diagnoses were made by a qualified psychiatrist (MD in psychiatry), data were checked duplication and errors. All diagnoses were rechecked for the correctness of the ICD coding provided. Despite the strengths, our study has certain limitations. Being a retrospective study based on records, there remains a possibility of missing diagnosis that could not be resolved. However, in our case, this was only around 2% of the total cases, and hence, we believe that it should not affect the validity of the findings. The psychiatrist attending the clinics was on a rotatory monthly posting schedule. Hence, the possibility of diagnostic rigor between them could not be completely ruled out. However, since all the psychiatrists were qualified in their specialty, we feel that the diagnosis made by them was valid. Through this paper, we demonstrate that it was important to use regular, routinely collected, observational data generated on an account of service provision to gain insights into one's practice. While highlighting the need for integrating mental health-care indicators in the routine health management information system, the recently concluded National Mental Health Survey of India reported that mental health was currently included in the existing HMIS only in four states in the country (Chhattisgarh, Gujarat, Madhya Pradesh, and Punjab). The report also found that even in those states, the monitoring of mental health was limited to capture information on the number of cases registered for treatment (mainly psychosis, neurosis, mental retardation, and epilepsy).
The observations of the present study have a number of implications. The principal point is the presence of high psychiatric caseload at subdistrict hospital. Although the specific diagnoses might be lower in terms of overall proportion compared to a psychiatric clinic in a tertiary care hospital, the order of the burden of diagnoses is not much different from the same. This shows that in the presence of specialist psychiatric services, it is feasible to identify and provide care and treatment at a subdistrict hospital. This implies that setting up of mental health units only at district hospital might not be a sufficient health systems approach as has been envisaged under the DMHP. In addition to the presence of a well-functioning and staffed psychiatric clinic, in our setting, the reason for successful referrals of patients to the psychiatric clinic from other specialty clinic was possible due to the presence of clinicians who were well sensitized toward potential psychiatric presentations and symptoms. This might indicate that mere establishment of a psychiatric outpatient clinic might not ensure successful utilization of the same until referrals are ensured from other specialty clinic. In this regard, an important implication would be to conduct cross-learning workshops for doctors of nonpsychiatric specialty on the commonly reported psychiatric illnesses, i.e., neurotic, stress-related, and somatoform disorders, mood disorders, episodic and paroxysmal disorders, schizophrenic disorders, and delusional disorders. Thus, deputation of psychiatric care workforce without adequate training could be a futile effort. While the NMHP has well-structured training plan for the workforce, results from study like ours help prioritize the illness for training program of doctors and paramedics. Another implication of the finding was that only a small fraction of the patients have opted to attend the psychiatric outpatient clinic on their own, whereas the large majority were referred to psychiatric clinic; this indicated a lack of awareness of common symptoms of mental illness among people. A possible solution could be to establish large posters of common symptoms of psychiatric illnesses at the registration counters of a secondary care hospital where patients spend considerable time waiting in the queue.
In the context of a scarcity of mental health specialists, decentralization and integrated primary mental healthcare, embracing a task shifting approach, has been mooted as a mechanism to address the treatment gap for mental disorders in the contexts of low- and middle-income countries. However, a minimum number of mental health specialists are still required to provide supervision of nonspecialists as well as specialized referral treatment services. Similarly, a review by Padmanathan and De Silva  highlighted that task sharing is not an outright solution for overcoming human resource shortages in low- and middle-income countries and suggested that factors such as the incidence of distress experienced by the task-sharing workforce, their self-perceived level of competence, the acceptance of the workforce by other health-care professionals, and the incentives provided to ensure workforce retention need to be considered in order for task sharing to be acceptable and feasible.
The main component of the NMHP which is the DMHP was developed based on the pilot mental health program in one of the districts (Bellary) in Southern Indian state of Karnataka. However, the sociocultural and geographic heterogeneity across the country warrants generation of local district level information to customize the development of mental health annual action plan. To make mental health care more accessible to those who require them, the services would have to be strengthened and integrated with the primary level health-care delivery system. However, mere training of multipurpose health-care worker or the village level health activist also known as accredited social health activist or distribution of patient education material would not be able to help achieve the goals of the NMHP.
| Conclusion|| |
We reported an increase in level and trend in the monthly attendance of patients who required psychiatric consultation at a subdistrict hospital in Northern India. Majority of the cases were of neurotic, stress-related, and somatoform disorders followed by mood-related disorders and belonged to the age group of 19–35 years. Females comprised around half of the caseloads. We suggest that setting up of mental health units only at district hospital might not be a sufficient health systems approach as has been envisaged under the DMHP. Urgent efforts would be needed to ensure not only provision of mental health services at subdistrict hospitals but also cross-learning and sensitization of other specialties' clinicians who act as important gateway for referring patients to the mental health facility.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
World Health Organization (WHO), ECOSOC Meeting, Addressing Non-Communicable Diseases and Mental Health: Major Challenges to Sustainable Development in the 21st
Century, Discussion Paper: Mental Health, Poverty and Development; 2009. Available from: http://www.who.int/nmh/publications/discussion_paper_en.pdf
. [Last accessed 2017 Mar 20].
Global Burden of Disease Study Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 2015;386:743-800.
Whiteford HA, Ferrari AJ, Degenhardt L, Feigin V, Vos T. The global burden of mental, neurological and substance use disorders: An analysis from the Global Burden of Disease Study 2010. PLoS One 2015;10:e0116820.
Patel V, Xiao S, Chen H, Hanna F, Jotheeswaran AT, Luo D, et al.
The magnitude of and health system responses to the mental health treatment gap in adults in India and China. Lancet 2016;388:3074-84.
Math SB, Srinivasaraju R. Indian psychiatric epidemiological studies: Learning from the past. Indian J Psychiatry 2010;52 Suppl 1:S95-103.
Lakhan R, Ekúndayò OT. National sample survey organization survey report: An estimation of prevalence of mental illness and its association with age in India. J Neurosci Rural Pract 2015;6:51-4.
] [Full text]
Charlson FJ, Baxter AJ, Cheng HG, Shidhaye R, Whiteford HA. The burden of mental, neurological, and substance use disorders in China and India: A systematic analysis of community representative epidemiological studies. Lancet 2016;388:376-89.
Braden JB, Zhang L, Zimmerman FJ, Sullivan MD. Employment outcomes of persons with a mental disorder and comorbid chronic pain. Psychiatr Serv 2008;59:878-85.
Murthy RS. Mental health initiatives in India (1947-2010). Natl Med J India 2011;24:98-107.
NMHS Collaborators Group. National Mental Health Survey of India, 2015-16: Summary. Bengaluru, National Institute of Mental Health and Neuro Sciences, NIMHANS Publication No. 128; 2016.
Thirunavukarasu M, Thirunavukarasu P. Training and national deficit of psychiatrists in India – A critical analysis. Indian J Psychiatry 2010;52 Suppl 1:S83-8.
Manjunatha N, Singh G. Manochaitanya: Integrating mental health into primary health care. Lancet 2016;387:647-8.
Singh GP, Chavan BS, Arun P, Sidana A. Seasonal pattern of psychiatry service utilization in a tertiary care hospital. Indian J Psychiatry 2007;49:91-5.
] [Full text]
Karsten J, Hartman CA, Smit JH, Zitman FG, Beekman AT, Cuijpers P, et al.
Psychiatric history and subthreshold symptoms as predictors of the occurrence of depressive or anxiety disorder within 2 years. Br J Psychiatry 2011;198:206-12.
World Health Organization. Atlas: Mental Health Resources in the World. Geneva: WHO; 2005.
Saraceno B, van Ommeren M, Batniji R, Cohen A, Gureje O, Mahoney J, et al.
Barriers to improvement of mental health services in low-income and middle-income countries. Lancet 2007;370:1164-74.
Petersen I, Ssebunnya J, Bhana A, Baillie K; MhaPP Research Programme Consortium. Lessons from case studies of integrating mental health into primary health care in South Africa and Uganda. Int J Ment Health Syst 2011;5:8.
Padmanathan P, De Silva MJ. The acceptability and feasibility of task-sharing for mental healthcare in low and middle income countries: A systematic review. Soc Sci Med 2013;97:82-6.
Centre for Community Medicine, Old OT Block, All India Institute of Medical Sciences, Ansari Nagar, New Delhi
Source of Support: None, Conflict of Interest: None
[Table 1], [Table 2], [Table 3]