4. Study design
This was a cross-sectional retrospective observational quantitative and qualitative study. The Health Index consists of indicators in the domains of Health Outcomes, Governance and Information, and Key Inputs/Processes. Health Outcomes are assigned the highest weight, indicators were selected on the basis of their importance and availability of reliable data at least annually from pre- existing data sources such as the Sample Registration System (SRS), Civil Registration System (CRS) and Health Management Information Systems (HMIS). Data on indicators is included for Index calculations only after validation by the IVA. A composite Index is calculated as a weighted average of various indicators, for a base year (BY) and a reference year (RY). The change in the Index score of each State from the base year to a reference year is the annual incremental progress of each State. States and UTs were grouped in 3 categories to ensure comparison among similar entities, namely 21 Larger States, 8 Smaller States, and 7 UTs [3, 4]. The same 23 indicators were used for the Health Index-2018 as in the first round. Taking into account importance and availability of reliable data 23 indicators were included in the Health Index. OOPE (out of pocket expenditure) used in first round was not available [3, 4].
5. Setting
For calculation of Index values and ranks, data was submitted online and validated by an Independent Validation Agency (IVA). The States were previously sensitized about the process for data submission through workshops and key stakeholders (Table-1). Data was submitted by participants States and UTs through online portal hosted by NITI Aayog and data from pre-existing sources in the public domain was pre-entered. After validation of data by an IVA it was used as an input into automated generation of Index values and ranks on the web-portal. The data was verified by IPE Global, an IVA prior to computing the Index and ranks for all States and UTs of India.
Table-1- List of key stakeholders - Roles and Responsibilities
Niti Aayog
|
states
|
technical
Assistance (TA)
Agency (the World Bank)
|
mentor Agencies
|
Independent
Validation Agency
(sambodhi)
|
Review, finalize and disseminate - the Health Index-2018 along with necessary guidance in close
partnership with
MoHFW
|
Adopt and share
Health Index2018 with various departments and districts as needed
|
TA to NITI Aayog in reviewing and finalizing the Health Index-2018 and protocols and guidelines
|
Mentor the States on data definitions and data requirements
for the Health Index2018
|
Validation and acceptance of the data submitted by the States for various indicators including comparison with other data sources as needed
|
Facilitate interaction between States and TA agency, mentor agencies, and the IVA
|
Enter and submit data in a timely manner on the indicators as per identified sources in web portal
|
Technical oversight to the mentor agencies, portal agency and the IVA
|
Provide guidance to the States for submission of data including visiting State Health
Departments/
Directorates as needed
|
Review of supporting
documents and
participation in data validation consultations with
States
|
Host a web portal for States to enter data, its validation
|
Coordination with different districts, mentor agencies and the IVA
|
Provide technical support for generation of composite Index
|
Follow up with States for timely submission of data/supporting documents on the on web portal
|
Final certification of data and generation and validation of Index scores and ranks
|
Overall coordination and management
|
|
Provide technical support for drafting and disseminating the report
|
|
Submission of a comprehensive report on validation
with details to NITI
Aayog
|
Source – NITI Aayog-India
This novel study was conducted over a period of eight months in 2018-19 see table-5. The States and UTs participated for finalization of the indicators/variables, workshops for sharing the methodology, process of data submission.
6. Participants
All states and UTs of India were participants. Multiple stakeholders as discussed above contributed to the Index development: The various Index was developed by NITI Aayog with help of World Bank, States and UTs, the Ministry of Health and Family Welfare (MoHFW), domestic and international sector experts and other development partners Categorization of States and UTs for ranking were based on the size, and administration[3,4]. The States were ranked in three categories, namely Larger States, Smaller States and UTs [1] (table-2).
Table-2- Categorization of States and UTs
Category
|
Number of
States and UTs
|
States and UTs
|
Larger States
|
21
|
Andhra Pradesh, Assam, Bihar, Chhattisgarh, Gujarat, Haryana, Himachal Pradesh, Jammu & Kashmir, Jharkhand, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Odisha, Punjab, Rajasthan, Tamil Nadu, Telangana, Uttar Pradesh, Uttarakhand, West Bengal
|
Smaller States
|
8
|
Arunachal Pradesh, Goa, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura
|
Union Territories
|
7
|
Andaman & Nicobar, Chandigarh, Dadra & Nagar Haveli, Daman & Diu, Delhi, Lakshadweep, Puducherry
|
Source – NITI Aayog-India
This categorization was done due to the following reasons: • The SRS data on health outcomes (NMR, U5MR, TFR and SRB) were not available for 8 Smaller States and 7 UTs, • reliable estimates for these outcome indicators/variables based on raw data obtained from SRS for the Smaller States and UTs could not be derived due to statistically small sample size and insufficient number of events.
7. Variables
The main criteria for inclusion of indicators/variables were the availability of reliable data with at least an annual frequency. The output Index is a weighted composite Index based on indicators/variables in 3 fields: (1) Health Outcomes; (2) Governance and Information; and (3) Key Inputs/Processes. Each domain was assigned a weight based on its importance. The indicator values are scaled from 0 to 100 for generating composite Index scores and performance rankings for 2015-16 (Base Year) to 2017-18 (Reference Year), i.e., a two-year period. The annual incremental progress made from BY to RY is used to generate incremental ranks. Table 3 shows the number of indicators/variables in each domain and sub-domain along with weights, while Table-4 provides the detailed Health Index with indicators/variables, their definitions, data sources, and specifics of base and reference years.
Table 3 - Health Index: Summary
|
|
larger states
|
smaller states
|
Union territories
|
Domain
|
sub-domain
|
number of Indicators
|
Weight
|
number of Indicators
|
Weight
|
number of Indicators
|
Weight
|
Health Outcomes
|
Key Outcomes
|
5
|
500
|
1
|
100
|
1
|
100
|
Intermediate Outcomes
|
5
|
250
|
5
|
250
|
4
|
200
|
governance and Information
|
Health Monitoring and Data Integrity
|
1
|
70
|
1
|
70
|
1
|
70
|
Governance
|
2
|
60
|
2
|
60
|
2
|
60
|
key Inputs/ Processes
|
Health Systems/ Service Delivery
|
10
|
200
|
10
|
200
|
10
|
200
|
Total
|
23
|
1,080
|
19
|
680
|
18
|
630
|
Source – NITI Aayog-India
Here it is important to mention that for round-2 larger states have 23 indicators unlike 24 of round 1and total weight 1080 instead of 1130; smaller states 19 instead of 20 of round 1 and weight 680 instead of 730; UTs 18 indicators instead of 19 of round 1 and weight 630 instead of 680 for round1. * The data for indicator no. 1.2.6 related to out of pocket expenditure was available only for 2015-16 and hence was used to calculate independently the RY Index and rank of round1.
8. Data sources/measurement
The Health Index consists of 23 indicators/variables related to Health Outcomes, Governance and Information, and Key Inputs/Processes (Table 4 provides Health Index-indicator details and data sources).
Table-4-Health Index: Indicators/variables, definitions, data sources, base and reference years
s. no.
|
Indicator
|
Definition
|
Base Year (BY)
Data source and Reference
Year (RY)
|
Domain: Health Outcomes
|
1.1.1
|
Neonatal Mortality Rate (NMR)[1]
|
Number of infant deaths of less than 29 days per thousand live births during a specific year.
|
SRS [pre-filled]
|
BY:2015 RY:2016
|
1.1.2
|
Under-five Mortality Rate (U5MR)[2]
|
Number of child deaths of less than 5 years per thousand live births during a specific year.
|
SRS [pre-filled]
|
BY:2015 RY:2016
|
1.1.3
|
Total Fertility Rate (TFR)[3]
|
Average number of children that would be born to a woman if she experiences the current fertility pattern throughout her reproductive span (15-49 years), during a specific year.
|
SRS [pre-filled]
|
BY:2015 RY:2016
|
1.1.4
|
Proportion of Low Birth Weight (LBW) among newborns
|
Proportion of low birth weight (<2.5 kg) newborns out of the total number of newborns weighed during a specific year born in a health facility.
|
HMIS
|
BY:2015-16 RY:2017-18
|
1.1.5
|
Sex Ratio at Birth (SRB)[4]
|
The number of girls born for every 1,000 boys born during a specific year.
|
SRS [pre-filled]
|
BY:2013-15 RY:2014-16
|
1.2.1
|
Full immunization coverage
|
Proportion of infants 9-11 months old who have received BCG, 3 doses of DPT, 3 doses of OPV and measles against estimated number of infants during a specific year.
|
HMIS
|
BY:2015-16 RY:2017-18
|
1.2.2
|
Proportion of institutional deliveries
|
Proportion of deliveries conducted in public and private health facilities against the number of estimated deliveries during a specific year.
|
HMIS
|
BY:2015-16 RY:2017-18
|
1.2.3
|
Total case notification rate of tuberculosis (TB)
|
Number of new and relapsed TB cases notified (public + private) per 1,00,000 population during a specific year.
|
Revised National
Tuberculosis Control Programme (RNTCP)
MIS, MoHFW
[pre-filled]
|
BY:2016 RY:2017
|
1.2.4
|
Treatment success rate of new microbiologically confirmed TB cases
|
Proportion of new cured and their treatment completed against the total number of new microbiologically confirmed TB cases registered during a specific year.
|
RNTCP MIS, MoHFW [pre-filled]
|
BY:2015 RY:2016
|
1.2.5
|
Proportion of people living with HIV (PLHIV) on antiretroviral therapy (ART)[5]
|
Proportion of PLHIVs receiving ART treatment against the number of estimated PLHIVs who needed ART treatment for the specific year.
|
Central MoHFW Data [pre-filled]
|
BY:2015-16 RY:2017-18
|
s. no.
|
Indicator
|
Definition
|
Data source
|
Base Year (BY) and Reference
Year (RY)
|
Domain: governance and Information
|
|
2.1.1
|
Data Integrity Measure7: a. Institutional deliveries
b. ANC registered within first trimester
|
Percentage deviation of reported data from standard survey data to assess the quality/integrity of reported data for a specific period.
|
HMIS and NFHS-4 (pre-filled)
|
BY and RY: 2015-16 (NFHS) BY and RY:
2011-12 to
2015-16 (HMIS)
BY: April 1,
2013-March 31, 2016
RY: April 1,
2015-March 31,
2018
|
2.2.1
|
Average occupancy of an officer (in months), combined for following three posts at State level for last three years 1. Principal Secretary
- M ission Director (NHM)
- D irector (Health Services)
|
Average occupancy of an officer (in months), combined for following posts in last three years: 1. Principal Secretary
- Mission Director (NHM)
- Director (Health Services)
|
State Report
|
2.2.2
|
Average occupancy of a full-time officer (in months) for all the districts in last three years - District Chief Medical Officers (CMOs) or equivalent post (heading District Health Services)
|
Average occupancy of a CMO (in months) for all the districts in last three years.
|
State Report
|
BY: April 1,
2013- March 31, 2016
RY: April 1,
2015-March 31,
2018
|
Domain: key Inputs and Processes
|
|
3.1.1
|
Proportion of vacant health care provider positions (regular + contractual) in public health facilities
|
Vacant healthcare provider positions in public health facilities against total sanctioned health care provider positions for following cadres (separately for each cadre) during a specific year:
- Auxiliary Nurse Mid-wife (ANM) at sub-centres (SCs)
- S taff nurse (SN) at Primary Health
Centres (PHCs) and Community
Health Centres (CHCs)
- Medical officers (MOs) at PHCs
- Specialists at District Hospitals (Medicine, Surgery, Obstetrics and Gynaecology, Pediatrics, Anesthesia, Ophthalmology,
Radiology, Pathology, Ear-NoseThroat (ENT), Dental, Psychiatry)
|
State Report
|
BY: As on
March 31, 2016
RY: As on
March 31, 2018
|
3.1.2
|
Proportion of total staff (regular + contractual) with e-payslip generated in the IT enabled Human
Resources Management Information System (HRMIS).
|
Availability of a functional IT enabled HRMIS measured by the proportion of staff (regular + contractual) for whom an e-payslip can be generated in the IT enabled HRMIS against total number of staff (regular + contractual) during a specific year.
|
State Report
|
BY: As on
March 31, 2016
RY: As on
March 31, 2018
|
s. no.
|
Indicator
|
Definition
|
Base Year (BY)
Data source and Reference
Year (RY)
|
3.1.3
|
a. Proportion of specified type of facilities functioning as First Referral Units (FRUs) as against required norm
|
Proportion of public sector facilities conducting specified number of C-sections8 per year (FRUs) against the norm of one FRU per 5,00,000 population during a specific year.
|
State Report on number of functional FRUs, MoHFW data on required number of FRUs
|
BY:2015-16 RY:2017-18
|
b. Proportion of functional 24x7 PHCs as against required norm
|
Proportion of PHCs providing healthcare services9 as per the stipulated criteria against the norm of one 24x7 PHC per 1,00,000 population during a specific year.
|
State Report on number of functional 24x7 PHCs, MoHFW data on required number of PHCs
|
BY:2015-16 RY:2017-18
|
3.1.4
|
Average number of functional Cardiac Care Units (CCUs) per district
(*100)
|
Number of functional CCUs [with desired equipment ventilator, monitor, defibrillator, CCU beds, portable ECG machine, pulse oxymeter etc.), drugs, diagnostics and desired staff as per programme guidelines] per districts *100.
|
State Report
|
BY: As on
March 31, 2016
RY: As on
March 31, 2018
|
3.1.5
|
Proportion of ANC registered within first trimester against total registrations
|
Proportion of pregnant women registered for ANC within 12 weeks of pregnancy during a specific year.
|
HMIS
|
BY:2015-16 RY:2017-18
|
3.1.6
|
Level of registration of births
|
Proportion of births registered under Civil Registration System (CRS) against the estimated number of births during a specific year.
|
Civil Registration
System (CRS)
[pre-filled]
|
BY:2014 RY:2016
|
3.1.7
|
Completeness of Integrated
Disease Surveillance Programme (IDSP) reporting of P and L forms
|
Proportion of Reporting Units (RUs) reporting in stipulated time period against total RUs, for P and L forms during a specific year.
|
Central IDSP,
MoHFW Data
[pre-filled]
|
BY:2015 RY:2017
|
3.1.8
|
Proportion of CHCs with grading 4 points or above
|
Proportion of CHCs that are graded 4 points or above against total number of CHCs during a specific year.
|
HMIS
[pre-filled]
|
BY:2015-16 RY:2017-18
|
3.1.9
|
Proportion of public health facilities with accreditation certificates by a standard quality assurance program (NQAS/NABH/ISO/AHPI)
|
Proportion of specified type of public health facilities with accreditation certificates by a standard quality assurance program against the total number of following specified type of facilities during a specific year.
- District hospital (DH)/Sub-district hospital (SDH)
- CHC/Block PHC
|
State Report
|
BY: As on
March 31, 2016
RY: As on
March 31, 2018
|
3.1.10
|
Average number of days for transfer of Central NHM fund from State Treasury to implementation agency (Department/Society) based on all tranches of the last financial year
|
Average time taken (in number of days) by the State Treasury to transfer funds to implementation agencies during a specific year.
|
Centre NHM
Finance Data10 [pre-filled]
|
BY:2015-16 RY:2017-18
|
[1] . Not applicable for the category of Smaller States and UTs
[2] . Not applicable for the category of Smaller States and UTs
[3] . Not applicable for the category of Smaller States and UTs
[4] . Not applicable for the category of Smaller States and UTs
[5] . Not applicable for the category of UTs. Due to change in definition of the indicators, for Larger States and Smaller States, the Base Year data is repeated for the Reference Year.
7 The NFHS data were available only for Base Year and the data for this were repeated for the Reference Year.
8 Criteria for fully operational FRUs: SDHs/CHCs - conducting minimum 60 C-sections per year (36 C-sections per year for Hilly and North-Eastern States except for Assam); DHs - conducting minimum 120 C-sections per year (72 C-sections per year for Hilly and North-Eastern States except Assam).
9 Criteria for functional 24x7 PHCs: 10 deliveries per month (5 deliveries per month for Hilly and North-Eastern States except Assam).
10 Centre NHM Finance data includes the RCH flexi-pool and NHM-Health System Strengthening flexi-pool data (representing a substantial portion of the NHM funds) for calculating delay in transfer of funds.
11 Source – NITI Aayog-India
9. Bias
Grouping and ranking the states according to size is a biased view. The researcher feels that population density/ per capita income/ literacy rate/ health workforce/ corruption-scam index etc. should be considered for ranking states. Summarizing the complexities and condensing it in an Index has limitations. Health Outcomes are assigned the highest weight knowing the fact that it is entirely dependent on input and governance. The governance in states such as Bihar is always controversial such as lack of Directorate, corruption, posting scams etc. [5].Hence the researcher feels that governance and input indicators are more important and it is a total biased view to provide health outcome highest weight which is totally dependent on other two.
10. Study size
All states and UTs of India were participants. Table 5 shows study period (This second edition of this exercise was conducted over a period of eight months in 2018-19.) The States were informed about the Health Index-2018 on July 14, 2018 through video conference chaired by the Chief Executive Officer (CEO), NITI Aayog. During the discussions an agreement was reached that the Base Year would be 2015-16, while the Reference Year would be 2017-18 for round 2.
[Table 5 is in the supplementary files section.]
11. Quantitative variables
See table-4
12. Statistical methods
Methodological details of constructing the Index-Computation of Index scores and ranks
After validation of data by the IVA, data was used for the Health Index score calculations. Indicator value was scaled, based on the nature of the indicator, for positive indicators, where higher the value, better the performance, the scaled value (Si ) for the ith indicator, with data value as Xi , was calculated as follows:
Scaled value (Si) for positive indicator = (Xi – Minimum value) x 100/ (Maximum value – Minimum value)
For negative indicators where lower the value, better the performance (e.g. NMR, U5MR,) scaled value was calculated as follows:
Scaled value (Si) for negative indicator = (Maximum value – Xi) x 100/ (Maximum value – Minimum value)
The minimum and maximum values of each indicator were ascertained based on the values for that indicator across States within the grouping of States (Larger States, Smaller States, and UTs) for that year. Indicator value lies between the ranges of 0 to 100; e.g. the State with the lowest institutional deliveries will get a scaled value of 0, while the State with the highest institutional deliveries will get a scaled value of 100. For a negative indicator such as NMR, the State with the highest NMR will get a scaled value of 0, while the one with the lowest NMR will get a scaled value of 100. Accordingly, the scaled value of other States will lie between 0 and 100 in both cases. Based on these scaled values (Si), a composite Index score was calculated for the base year and reference year by application of the weights using the formula:
Composite Index = (∑ Wi *Si)/ (∑ Wi) --Where Wi is the weight for ith indicator
The composite Index score has been used for generating overall performance ranks. The difference between the composite Index score of reference and base years was the annual incremental performance. The ranking is primarily based on the incremental progress, however, rankings based on Index scores for the base year and the reference year performance calculated to provide the overall performance of the States and UTs.