Introduction: In India, there is a paucity of morbidity and mortality information de-segregated at facility level. Present study was undertaken to report the morbidity and mortality of in-patient at a secondary care hospital. There are no data available on morbidity and mortality patterns in hospitalized patients of the state of Uttarakhand in India.
Materials and methods: Study was conducted in a secondary care Government Doon Hospital at Dehradun, Uttarakhand State, India. It is a record based retrospective study. Diagnoses are coded as per the International statistical Classification of Diseases (ICD.10). Relevant information pertaining to socio-demographic indicators, diagnosis and outcome at discharge about inpatients (1/1/2012 to 31/12/2012) were retrieved from HMIS archives. Descriptive analysis was done.
Results: During the study period, a total of 18309 patients were admitted in all departments/wards. Out of these 10735 (58.6%) were males and 7574 (41.4%) were females. A statistically significant difference was seen between males and females for morbidity disease category of eye and adnexa [ICD.10: H00-H59, 3.3 (p<0.05)] with subcategory of disease [ICD.10:H25.2, 2.5(p<0.05)], diseases of the respiratory system [ICD.10:J00-99,2.2(p<0.05)] and morbidity disease category of injury, poisoning and certain other consequences of external causes [ICD.10:S00-T98, 3.0(p<0.05)]. The average bed occupancy rate of the hospital was 97.2 percent recorded throughout the year and overall mortality rate was 40.4/1000 admissions.
Conclusion: The present study only highlights the status of different types of morbidity, mortality and bed occupancy rates in a secondary care hospital. This is a record based study.
Key message: There is need to upgrade existing health infrastructure at secondary care level facility to increase bed occupancy and minimize referral rate. The reasons for the high LAMA rate needs to be studied in detail to bring it down.
India is a large country with huge variations in health indicators across states and districts of the country.Unlike other big nations, for instance Russia, China and the USA, the Indian population consists of many communities with different cultures and habits. The morbidity and mortality pattern across India varies significantly as would be expected from the wide health and health determinant disparity spread across length and breadth of India[2,3].
Life expectancy at birth, mortality and morbidity rates are important indicators of health status of a population. In India the life expectancy has increased from 23years in 1901 to 62.6in 2002-06, and infant mortality has declined from 215 per thousand in 1901 to 50 in 2009. The death rates have declined from 44 per 1000 in 1901 to 10 in 1992 and 7.3 in 2009.However, there are no realistic and comparable estimates of morbidity over a period of time. The life expectancy at birth is an important indicator of quality of the people.The estimates of morbidity in general and the disease specific incidence rates in particularwould serve as valuable information to the health planners and administrators for appropriate and timely measures to monitor, control and eradicate the diseases.It will also enable the administrators to allocate resources for health facilities such as hospitals, physicians, medicines, etc., and provide basic infrastructure such as sanitation and drinking water. Recently morbidity estimates have been used to assess the burden of diseases.Although a low morbidity rate can be considered as an indicator of better health status, it need not necessarily be true. Low morbidity can occur from actual reduction in incidence of illness or due to under reporting or due to lack of disease consciousness. There is considerable disagreement among researchers on how to define and measure morbidity since it is highly subjective based on perception and reporting. In certain cases morbidity may be the reflection of poverty itself . In India, there is a paucity of morbidity and mortality information de-segregated at facility level.There have been few studies documenting the morbidity profile of a population over a period of time in other parts of India, but none in the state of Uttarakhand.Central Bureau of Health Information (CBHI) does report aggregated state level and national level morbidity information but this information has limited use at district and sub-district level.
National Rural Health Mission (NRHM) has emphasized the importance of de-centralization of health system policy and planning. Following this, there is renewed interest in health planning at district and sub-district level. One of the prerequisites of decentralized planning is the availability of locally relevant valid information including morbidity and mortality statistics to guide planning[8,9].
The overload in hospital ward remains a major source of concern in many countries, including India, for policy makers. The availability of hospital beds has always been a problem in developing countries. It is the most important single factor in determination of the utilization of hospital beds in a country. In India, shortage of hospital beds is a huge problem, the average bed population ratio being 9 per 10,000 population in comparison with the world average of 27 per 10,000 during 2000-2009.
Morbidity and mortality reporting of in-patients will not only provide valuable information regarding burden and cause of illness but also enable us to assess the adequacy of the available facilities. It will further provide inputs to restructure and upgrade the existing health services. Present study was undertaken to find out the pattern and distribution of morbidities, case fatality rate and bed occupancy rate of in-patient at a secondary care hospital at Dehradun with aim to identify key areas that require improvement in the existing health system and also for planning and resource allocation in a similar secondary level health settings. To our knowledge, there has not been any study documenting the morbidity profile of admissions in a secondarycare hospitalof Uttarakhand State, which will aid in deciding whether specialists staffing is required or not. We therefore felt the need to record the morbidity profile of admissions in a secondary healthcare hospital.The hospital patients consist of private fee-paying patients and staff/dependents of government or private companies, which have retained the services of the hospital. The patients therefore represent various strata of the society cutting across social classes, religions and ethnic groups.The place of residence of majority of the patients extended from close vicinity of the hospital to a distance as far as 100km approximately. The worst affected were villagers who trekked several kilometers from the hilly terrains of the State.In view of the increasing patient load, the Uttarakhand State Government has taken the decision to convert the “Doon Hospital”to a medical college.
Specifying that written permission for conducting the study was obtained prior to collecting the data from the additional health secretary and mission director, NRHM, Director General of Health Services(DGHS) of the Uttarakhandstate and also from medical superintendent of the Doon Hospital by explaining the purpose of the study. Strict confidentiality was maintained on the data collected. No financial sources were involved to conduct this study also no ethical clearance was required to conduct this study.
Collected data were entered in Microsoft Excel and were analyzed using software Statistical Package for Social Sciences (SPSS) version 21.0.Descriptive statistical measures such as percentage, mean were applied. Inferential statistical tests such as Z-test and Chi-square test were applied to identify important relationships between variables and determine the level of significance. A p-value of < 0.05 was considered statistically significant.
Table 1 shows distribution of patients according to morbidity, mortality and Case Fatality Rate (CFR) by 5 year age groups andgender. A total of 18,309 patients were admitted in all the wards from1stJanuary, 2012 to 31stDecember, 2012. Of these 10,735 (58.6%) were males and 7,574 (41.4%) were females resulting ina sex ratio of males 1000 to females 705.The highest number of admissions came from the 20-24 year old age group in both sexes[male n=987 (5.4%), females n=604 (3.3%)]as compared to other age groups.In males the highest number of deaths/mortality belonged to the 60-64 year old age group [n=60 (8.1%)] followed by the 75+ years old age group [n=49 (6.6%)]while in females the highest number of deaths/mortality belonged to the 75+ year old age group [n=41 (5.5%)] followed by the 60-64 year old age group[n=27 (3.6%)]. Over all CFRwere 4.0 per 1000for both sexes (male - 4.5%, female - 3.4%) (Figure 1),statistically significant association was found between age groups, morbidity (22.9, p<0.001) and in mortality (7.9, p<0.001) by sex.
Figure 1: Distribution of patients according to morbidity, mortality and Case Fatality Rate (CFR) by age and gende
Table 2 shows the distribution of patients according to condition at discharge and ages. It was found that out of the total(n=18309) admitted casesin hospital among various wards, 10271 patients (56.1%) were discharged as cured, 3566 (19.5%) were relieved, 3113 (17.0%) Left Against Medical Advice (LAMA), 740 (4.0%) patients expired and the remaining 619 (3.4%) were referred(Figure 2). Statistically significant association was found between the age groups andpatients discharge conditions.
Figure 2: Percentage distribution of patients according to condition at discharge.
Dehradun, the capital city of the state of Uttarakhand, is one of the most visited tourist destinations in India that attracts both domestic and international visitors.The climate of Dehradun is generally temperate, although it varies from hot in summers (up to 40°C) to severely cold (down to 1°C) in winters.Although the nearby hilly regions often get snowfall during winter, in Dehradunit is not a frequent occurrence. During the monsoon season, there is often heavy and protracted rainfall. Dehradun and other plains areas of Uttarakhand statesee almost as much rainfall as coastal areas of Maharashtra state and more than the state of Assam .
Table 3 provides the distribution of seasonal variations in morbidity, mortality,CFR and Bed Occupancy Rate (BOR).The climate in Dehradun area cannot be exactly differentiated into the conventional four seasons. A more practical demarcation is the winter months of December, January and February, the spring season months of March and April, the hot-dry period of May and June, the hot-wet monsoon (rainy) period of July, August and September, and autumn comprising October and November.Out of the total admission (n=18309), the high point in the frequency of morbidities [both sexes: n=4696 (25.6%), male: 2785 and female: 1911] and mortalities [n=181 (24.5%), male: 118 and female: 63] were found in the hot-wet season (July to September month). Overall CFR was 4.0 per 1000population (male: 4.5 and female: 3.4). A high (4.7) case fatality rate per 1000 population was seen in the autumn season (October: 5.3, November: 3.9) and minimum (3.0) in winter seasons (December: 2.9, January: 3.6 and February: 2.6).Overall BORwas 97.2 percent. The month of Maysaw very high BOR (113.8%) followed by July (103.6), August (102.7)and September (102.3). January recorded the lowest BOR(81.8)(Figure 3).A z-test was applied to know the statistical significance difference among the BOR during different seasons of the year.Statistically highly significant difference was observed during the winter season (6.1, p<0.001) alsostatistically significant difference was observed in springseason (2.9, p<0.05) and inautumn season (2.1,p<.05).
In females the leading causes of morbidity were symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified[n=2311 (30.5%)] followed by infectious parasitic disease [n=1332 (17.6%)], diseases of eye and adnexa[n=823 (10.9%)], injury, poisoning and certain other consequences of external cause[n=610 (8.1%)] and diseases of respiratory system (n=541 (7.1%)](Figure5).Statistically significant differenceswere seen among males and females for morbidity disease category of eye and adnexa3.3 (p<0.05), diseases of the respiratory system 2.2(p<0.05) and morbidity disease category of injury, poisoning and certain other consequences of external causes3.0(p<0.05).
Figure 5: Leading causes of morbidity in females.
In males and females,leading causes of mortality were symptoms, signs and abnormalclinical and laboratory findings with 28.6% and 29.8% respectively,followed by diseases of respiratory system(16.2%and 12.4%), infectious parasitic disease(12.9% and 13.2%), diseases of circulatory system (10.2% and 10.1%)respectively(Figures 6 and 7).
This study only analyzed hospital admissions, which did not include patients seen in the emergency and Outpatients (OPD) Departments per se.Nevertheless, similar results would be expected if OPD patients were to be included, since most of them present there for post-hospitalization follow-up, although some patients with more acute problems are referred directly to the OPD. Despite obvious limitations associated with the validity of hospital records (e.g: omissions, inaccurate recording of diagnosis at the time of admission, etc.), the examination of such data has still yielded a reasonably representative picture of the prevailing ills in the community served by Doon Hospital. A significant proportion of cured patients [n=10271 (56.1%)] in both sexes was much higher as compared to the other conditions at discharge.The proportions of referrals in the age group of 35-64 years (46.2%) were higher as compared to other age groups. A significant proportion of patients left the health facility against medical advice(17.0%). The probable reason would be either non-satisfaction with the medical care available or inability to continue the treatment at the facility. The referral (3.4%) rate was substantially low as compared to the other conditions of discharge. This may probably due to the fact that our facility follows the standards/guidelines laid down in Indian Public Health Standards (IPHS). Results ofthe District Level Household Survey - III 2007-08 (DLHS - III) shows majority of health facilities at secondarycare does not conform to IPHS standards.The overall mortality rate of 4.0 per thousand admissions in our study is comparablewith the mortality rate of other secondary care centers.Some limitations arebeing noted in this study. Being a retrospective study, extraction of final diagnoses from patient’s folders who presented with multiple complaints/morbidities could alter the actual prevalence of the disease entities so recorded. Secondly we relied on the clinical soundness of the attending physician in patients’ diagnoses which may vary from individual to individual based on experience, qualifications and other factors.
The present study only highlights the status of different types of morbidities, mortalities and bed occupancy rate in asecondary health care hospital. This is the first study amongst admitted patients of all causes of morbidity and mortality with all ages to highlight the morbidity and mortality pattern of hospitalized patients in all ages and the case fatality rate.
Author will like to acknowledgeDr. BC Pathak (Ex DG), Shri Piyush Singh (Addl Health Secretary & Mission Director), Director General of Medical Health Services & Medical Superintendent of Doon hospital, Government of Uttarakhand who given permission to collect the valuable data of this research work.
A very special expression of appreciation is extended to Shri VK Negi (Statistical Officer) &to the medical records staff for their assistance in retrieving the relevant case notes.
Citation: Tyagi BB, Aswal RS, Haroon AS(2015) Morbidity Patterns Amongst Hospitalized Patients in a Secondary Care Hospital of Dehradun, Uttarakhand State, India. J intern Med Prim Healthcare 2: 1.
Copyright: © 2015 BrijBhushan Tyagi, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.