5.1 Service Availability
Fig 2.1 summarizes the components of service availability in the district .There were
3.7 facilities (at all levels of hierarchy) per 10000 population as against the required
norm of 2 per 10000 population culminating into a score of 1.6 for facility density.
Inpatient bed density; a standardized indicator measuring levels of access to hospital
inpatient services by designated populations was nondescript in our study area with
only 7.13 beds per 10000 population yielding a score of 28%. On the other end of spectrum,
the score of maternal bed density was rather propitious at 85% indicating priority
setting of Maternal and Child health programs. The health worker density is the health
workforce indicator that is most commonly reported internationally and represents
critical starting point for understanding health system resources situation in an
area. The density of core health workers was 15.01 per 10000 health workers vis. a
vis. the health workforce density threshold of 23. Nonetheless, the goal of universal
health coverage requires a paradigm shift, going beyond a discourse on shortages but
rather focusing more explicitly on accessibility, acceptability, quality and productivity
of health workforce (WHO, 2014). Delving further into the workforce mix, it was revealed
that the shortage of specialists and doctors was particularly striking with district
having 54% vacancy of specialists and 76.6% vacancy of medical officers. There was
only 1 doctor/6241 population as against the guideline of 1 doctor/1000 population.
Doctor patient ratio in DH was 1/9880 which is 10 times less than recommended ratio,
PHC had a ratio of 1/5878 with majority of doctors from Indian System of Medicines
and no doctor was in position in any of the NTPHC. Strengthening service delivery
and augmenting utilization are indispensable to improve health status and outcomes.
Outpatient utilization that measures number of outpatient visits to health facilities
during one year relative to the total population of same geographical area was 1.64
as compared to the target of 5 generating a score of 32.5%. Inpatient utilization
(hospital discharges per 100 population excluding deliveries) was 88.3% of target
with 8.83 people getting hospitalized per 100 population.
Stakeholder’s analysis explored these themes in detail that were not in precinct of
SARA methodology. On the infrastructure front, even though results indicated favorable
facility density scores; the condition of building was disconcertingly dilapidated
and deficient posing challenges for effective service delivery. Subcenters, particularly
were in decrepit condition and 74% were operating from rented premises.
“The entrance to facility isn’t conducive for patients. There’s scree slope and loose
stones. Once an elderly man was maneuvering his way to facility; he slipped and broke
his backbone and had to be admitted to district hospital and later referred to capital.
I was consumed with guilt. But it’s not in my hands, you see.”
-Nursing Orderly, Subcenter
“It is becoming increasingly daunting to operate from this single, kutcha rented room
with no storage facility. We are grappling with problem of thefts every year. There’s
no compound wall and there are gaps in window panes due to which locals break and
steal furniture, medicines and even record registers. Entire untied funds gets dissipated
in replacing lost items.”
In conjunction with shortage of specialists and physicians; absorption and retention
of other workers was also identified as a colossal challenge in far flung and fragile
area. Workers were are not willing to serve in our area setting due to confluence
of dampening factors like isolation, difficult terrain, dense forests, absence of
road and transportation network, shelling hazards, inaccessibility to housing and
market and contractual mode of employment.
“Post rainy season jungles metamorphosis into dangerous form and there’s burgeoning
of grass and tall maize crops, making it a lurking ground for wild bears and providing
recesses for militants. My frequency of visiting center plummets significantly during
that season. Last season my ASHA worker was mauled by bear while going for vaccination
outreach. My family is urging me to quit the job. I haven’t been regularized for last
10 years and earning peanuts. Is it worth it?”
-Multipurpose worker, NTPHC
Due to non-existence of incentive structure, workers resort to liaison with local
political leaders for internal adjustment to get themselves attached to district/block
headquarters from their original location of posting; leaving remote area underserved.
In the absence of such arrangements, when workers serve in remote areas, they resort
to absenteeism and dereliction of duty. This causes challenges with distribution and
skill mix of health workforce with more than sanctioned workers in easy to access
areas and scarce and unmotivated workers in villages.
“I am a sole worker here; it feels like walking at knife edge trail. I start by 7am
from home but can only reach facility by 12 noon after hiking for 2 hrs. I am forced
to lock the facility by 2:00 pm for the fear of missing last vehicle back home. Administration
is pestering me to stay near the facility; but where’s the housing?”
-Multipurpose worker, Subcenter
Low utilization rates of ambulatory care are inextricably related to obstructed service
delivery. However, in context of hilly and remote areas, high facility density score
should be interpreted with caution as it doesn’t necessarily translate to physical
accessibility for dispersed population living in higher reaches. Some pockets are
completely inaccessible warranting new facility/upgradation of lower tier facility
manned with skilled worker.
“We have population of 14,000 in the village; for this population, a PHC is required
especially to cater delivery services. From these far flung areas, we have to take
our women to district headquarter for delivery after paying hefty amount to hire private
vehicle as there’s no public transport post 3 pm. Even for other ailments, we don’t
want to walk for hours only to find the facility closed or without drugs.”
Sarpanch, Village Panchayat
5.2 General Service readiness
Hospitals had high readiness scores on an average (76%) as compared to the new type
primary health centers (24%). The average item availability for basic equipment ranged
from 29% to 89% with lowest being for new type primary health centers and highest
for district hospital. The average score for standard precaution against infection
was 60.2% across all level of facilities. The highest average score was noted in community
health centers with a value of 79%. Laboratory diagnostic capacity was subjacent for
new type Primary health centers at meagre 4%. The assessed items most likely to be
unavailable even in high performing facilities were essential medicines and amenities.
PCA for subcenters and primary health centers revealed that two components extracted
from 71 variables for subcenters explained 22% variance, whereas first two extracted
components from 221 variables for primary health centers explained 31.59% variance.
For each component, relative size of coefficients depicting the commonality in coefficients
is illustrated in Fig 4. The principal component for subcenters was weighted most
heavily on equipments whereas, second component was representative of medicines. Estimated
coefficients on principal component for primary health centers on the other hand,
had maximal relative strength on diagnostics and second component analogous to subcenters
Around 6.66% sub centers reported having none of the tracer items symptomatic with
amenities and one fourth facilities had less than 25% of 7 tracer items. However,
only half of the sub centers had readiness score greater than 50%. A tenuous 10% primary
health centers were equipped with half of the 58 tracer items. None of the primary
health center had communication network like email or NIC terminal although all of
them were endowed with electricity having power backup and government ownership of
building possessing adequate premises. However, only three PHC’s had quarter for staff
members and 40% didn’t have residential arrangements for medical doctors. However,
this was more pronounced for new type primary health centers where none of the facility
had quarter for staff members and 88.88% were bereft of quarters for medical officers.
Moreover, the electricity/power supply in new type primary health centers was intermittent
as well with just two facilities having continuous power supply. Although, these facilities
are characterized by geographical inaccessibility from settlements, and were marred
by unavailability of ambulances and basic communication network. Hospitals i.e. district
hospital and community health centers were found to be relatively accoutered with
amenities Vis a Vis lower level of facilities.
Fig 5.1 and 5.2 illustrates the scree plots generated from PCA. Results of Horn’s
parallel analysis revealed one component having eigenvalue greater than 1 explaining
44.54% of common variance for sub center. The principal component was weighted heaviest
for emergency transport and communication network. Concomitantly, first four components
explained 65.5% common variance for PHC’s and the principal component was characterized
most strongly for infrastructural impediments like provision of quarters for medical
officers and government ownership of building.
The stakeholder’s narratives were consonant with the above findings and acknowledged
incommensurable staff working conditions and nonresponsive emergency transport
rendering staff members to derelict from duty and patients to incarcerate/die in transit
as a barrier to service provisioning. Retaining health staff, particularly in remote
and conflict areas is an insurmountable challenge and amenities play a crucial role
in health staff decisions about absorbing and retaining posts. However, health workers
bemoaned about dearth of personal accommodation both at health post and in surrounding
“Construction of quarters for medical officers started ten years back. It’s still
incomplete. Ever since I joined the facility, I have been sleeping in labour room
with shell sprinters puncturing holes in the wall incessantly. When shell hits at/near
the labour room, I shift to the general ward to sleep and vice versa.”
-Medical officer (PHC at Zero Line)
Budget constraints was identified to be an Achilles heel stymying the funding of stalled
projects and paying for the amenities.
“There is a serious concern pertaining to funds. We couldn’t complete stalled projects,
purchase needed ambulances or any bullet proof ambulance. We don’t even have adequate
funds to pay the monthly rent of facilities. There are no NGO’s, no AID agencies and
no PPP. We can’t even provide incentives to attract workers in most disturbed areas”
-Senior district administrator
There was perceptible variation in the availability of equipment in subcenters and
hospitals. In subcenters, the availability of equipment ranged from 4% to 70% with
the average availability of 40% and 12 facilities having less than 25% items. Striking
difference in the readiness scores was found between PHC’s and NTPHC’s. None of the
PHC had inventory of eye care equipment and only three PHC’s were equipped with phototherapy
unit and MVA/MTP suction aspirators whereas this list was protracted to enfold all
the equipments in newborn baby corner and neonatal pediatric unit viz radiant warmer,
laryngoscope/endotracheal equipment, mucus extractor and baby bassinet etc for NTPHC’s.
With the average equipment score of 29%, NTPHC’s score was abominable specifically
for delivery preparedness and cold storage. The highest performing NTPHC merely possessed
half of the tracer equipments on the day of survey. Community health centers and district
hospital were devoid of the equipments pertaining to NCD care and none of the facility
had e-ventilator for operation theatre, noninvasive ventilator, spirometer, dialysis
machine, memography, stadiometer and colposcope etc. However, all the hospitals had
basic equipments required for labour room and newborn corner. CHCs with a readiness
score of 68% and district hospital with a score of 88% were efficacious vis a vis
primary care facilities. Provisioning of effective care gets thwarted by equipment
that is unavailable, non-functional and outdated and One fourth of the equipments
in facilities were rendered non-functional biting the dust.
As illustrated in Fig 5.2.2, for subcenters only one component had adjusted eigenvalue
greater than one explaining 33.8% variation. The principal component was represented
predominantly by equipments enabling delivery such as delivery forceps, cord cutting
scissors and sterilizers. On the other hand, for primary health centers illustrated
in Fig 5.1.2, two components explaining 53.29% variance explained the common variance.
Principal component was characterized by neonatal care like availability of neonatal
resuscitation mask, resuscitation kit, feeding tubes and radiant warmer for babies
which is congruent to average availability scores. Further, delineating second component
revealed the dominance of indicators associated with delivery preparedness. Marking
a dissimilitude to component one, neonatal care factored negatively and strongly on
In-depth conversations with health workers unfolded a nuanced account of obsolete
methods of care or denial of care which they have to resort to due to unavailable/non-functional
equipments. Some of the equipments were not germane to requirements and were supplied
in surplus making it redundant e.g. few subcenters received around twenty thermometers
each in the month preceding to survey indicating insufficient allocation of resources.
“We don’t have equipment and infrastructure for delivery. We couldn’t afford labour
table with meagre funds and are conducting deliveries on wooden plank without sterilizer.
Once a pregnant lady suffered the lacerations which needed suturing but I didn’t have
necessary kit, it endangered her life and finally succumbed to complications. I am
reeling under guilt since then. What was my training worth?”
5.2.3 Infection Control Protocol
Results indicated that healthcare settings lacked robust infection control infrastructure
and no Healthcare Associated Infections (HAI) surveillance system existed in place.
The list of tracer items incorporated practices like incineration of infectious materials,
use of disinfectants and gloves, availability of deep burial pit and colour coded
dustbins etc. For subcenters, more than one third facilities had only 25% items and
17 facilities were compliant to more than half the requirements. The readiness of
NTPHC’s were obsequious as compared to PHC’s, the domain scores for facilities, on
an average, were in range of 40%-90% for PHCs’s and 0%-80% for NTPHCs. CHCs and DH
however, were complying with 79% and 75% requirements respectively.
PCA results for subcenters conceded principal component explaining 41.22% variance
and weighed positively by presence of sewerage system and appropriate disposal of
waste material. Whereas, for primary health centers, proportion of variance explained
by first two components with eigenvalues greater than one was 77.29%. First component
was characterized by the availability of guidelines and infection control protocol
followed by segregation and disposal of waste material. Obversely, component 2 was
positively associated with the presence of sewage system and negatively associated
with adequate hypodermic syringe for single use.
On an institutional level, healthcare facilities should work to foster organizational
attributes and it should be endeavored to implement systems throughout organization
that are prompt and reinforces the embodiment of infection control and prevention
in all aspects of care. Even though health workers were conversant with standard
operating procedures and guidelines, lack of supplies and infrastructural constraints
made it difficult to practice standard precaution. No constant replenishing of exhausted
materials such as gloves and needles was in place and health workers were purchasing
it locally with the untied funds. All health workers griped about grappling with problem
of waste disposal as they have to dig kutcha pit every time for disposing syringe/needles
in the absence of pucca pit in the premises. Health workers also narrated the absence
of government ownership of buildings as a stumbling block for adherence to infection
control as observing hygiene/sanitation also hinges on owner of buildings from where
they are running the facility as they reside cheek by jowl in same building.
“Ours is rented building and landlord has insisted on keeping his livestock and fodder
in same building. There’s gutter next to building and mosquito scourge due to that.
Our woes doesn’t stop here, since this building is situated on river bed; we can’t
bury the waste here, so we carry used up dressing material, syringes etc. 30 kms away
to our PHC for disposal.”
5.2.4 Diagnostics services
Diagnostic capacity of facilities surveyed is represented in Fig 3. Subcenters are
stipulated to provide very basic diagnostic tests such as Haemoglobin, Urine, Blood
Sugar and Blood slide for malaria; nevertheless, it could effectuate only 43% readiness
score. Less than one tenth facilities had all the four tracer items and more than
one fourth of facilities were traipsing around 25% domain scores indicating suboptimal
performance. PHCs, on an average, were also obscured by low readiness reaching just
50% score and scarcely any facility was conducting 2% sputum testing and possessing
reagents and testing kits such as KOH solution, gram’s iodine and safranin stain.
Further, all NTPHCs except one was performing at less than 10% score and 63% facilities
were unequipped with even basic kits like Hbmeter, colorimeter and urine dipstick.
There was serious vacuity connected with diagnostic capacity for Non communicable
diseases and radiology in CHCs and District hospital as none of them was providing
services like memography, colposcopy, endoscopy, stress test, coomb’s test, Pap smear
and CT scan. On the sanguine side, all the hospitals were designated as Diagnostic
Microscopy Centers conducting an array of serological, pathological and microbiological
tests like urine analysis, stool analysis, RA factor test, VDRL test, LTF test, RPR
for syphilis and ultrasound etc.
Two components following PCA were revealed to have eigenvalue greater than 1 explaining
82.52% common variance in subcenters. The principal component was highest loaded on
availability of urine albumin and sugar testing kit and the component two was characterized
by the collection of sputum samples in facility. Further, Horn’s parallel analysis
indicating first two components to be extracted explained 61% common variance in Primary
health centers. Rotated factor loadings on principal component was denotative of presence
of reagents like colorimeter, safranin stain followed by availability of functional
microscope in laboratory. Whereas, second component evinced the presence of reagents
and consumables required for testing of Tuberculosis with the loadings ranging from
0.19 to 0.61.
In-depth interviews with laboratory technicians divulged that even if facility is
having diagnostic capacity, other conditions are not conducive for operations. Also,
geographical inaccessibility to the point of care induces a choice trade-off between
public and private providers and the patients generally chose later due to time flexibility;
thereby, contracting the demand for diagnostic services.
“I am unable to conduct the TB test due to dearth of water and space. Dental technician
consults in the same room and his patients are always anxious of contracting infections.
I have to fetch water manually from a hand pump situated 2.5 kms away, sometimes it’s
not feasible to go, due to which I am always susceptible to infections. The equipments
are getting corroded by rust and chemicals are expired; I haven’t bothered to ask
for new supplies as I know it would just sit idle.
Lab technician, 24*7 Primary health center
Provisioning of affordable, high quality and appropriate essential medicines is a
quintessential component of a well-functioning health system. Fig 3 illustrates the
distribution of health facilities based on availability of non-expired drugs. Essential
medicine domain comprised a list of 38 drugs for subcenters and on an average, they
were stocked with 52% drugs. Only half the facilities had anti-allergic and antibiotics,
moreover, average availability of injectables and fluids was reprehensible with a
score of 2%. In a more expansive drug list and consumables; PHCs were stocked with
37% of medicines whereas NTPHCs egregiously had less than one fourth of medicines.
No primary health center had insulin, inhalators and injectibles like amikacin, kanamycin
and streptomycin, drugs for mental health disorders, antidotes for poisoning, expectorants,
drugs for cardiovascular diseases and consumables like spinal disposable needle.
On a sanguine note, all PHCs were stocked with vaccines for immunization and basic
first aid kit. The domain score for CHCs and District hospital was 63% and 60% respectively,
although, hospitals were also bereft of adequate consumables like mucus sucker, catheters
and drugs required to treat non-communicable disease conditions.
The results of PCA for subcenters elucidated first four components with eigenvalue
greater than 1 explaining 53.38% common variance. Rotated component loadings for principal
component underscored positive and heavy loadings on consumables for first aid like
cotton bandages, povidone iodine solution followed by anti-allergens and antibiotics.
Subsequent components were characterized by availability of antibiotics, zinc sulphate
tablets and Vitamin syrup. Furthermore, for primary health centers, the variables
possessing heaviest loadings on principal component were positively associated with
injectibles, consumables viz intracath canulas, gloves and surgical spirit. In a
dissimilitude to first component, injectibles however, weighed down the second component
but were positively associated with drugs related to blood pressure and cardio-vascular
diseases such as nifedipine, isosorbide and glyceryl trinitrate. First two components
explained 32.18% common variance for primary care institutions.
Inadequate supply of drugs was identified as paramount domain leading to patient-provider
wedge. The medicines received were not contingent to the needs as the morbidity profile
of study area is dominated by blood pressure related and non-communicable diseases
but the drugs addressing these conditions were absent in supply. Moreover, basic drugs
for fever, gastrointestinal problems and antibiotics were reported to be exiguous.
“People come every-day and demand antibiotics and anti-allergens but we seldom receive
it in stock. They hurl insults at us and proclaim why do you even bother to come to
facility when you can’t provide us with anything? They further insist upon administering
steroids and sometimes we acquiesce otherwise they bad mouth us.”
At PHC level, the average time taken for medicine to reach post indenting was six
weeks and the same was eight weeks for subcenters. Among the medicines which were
unavailable in subcenters at time of survey, nearly 20% were out of stock for 3-6
months whereas, 40% were out of stock for more than 6 months. However, half of tracer
drugs, surgical and suture items adapted from essential drug list were not procured
and supplied ever by state medical supply corporation. Ensuring availability and optimizing
expenditure is incumbent upon minimizing/eliminating wastage of drugs including pilferage,
misuse and expiry. Expiry of medicines was identified as debilitating issue plaguing
all the facilities, thereby, jeopardizing already constraint supply of medicines.
Majority of health workers piqued over supply of drugs with very short shelf life.
And it was more common for drugs related to vertical health programmes such as Vitamin
A, IFA tablets, albendazole etc. The facilities didn’t adhere to scientific inventory
management method of First Expiry, First Out and 30% facilities were found having
stock of expired medicines.
“I received 1000 PCM tablets to last 13 months. Panting, exasperated an elderly female
came to facility last week after trudging a distance of 2 hours down with fever but
the medicine was out of stock and she got offended and dejected. Next day only Tikka
express delivered boxes of expired ORS. Naturally, I expressed dissent, but they forced
it upon me saying it’s your buck to deal with.”
5.3 SERVICE SPECIFIC READINESS
Fig 6. Presents a succinct snapshot of package specific composite measures capturing
the capacity of facilities to deliver broad spectrum of services. Substantial heterogeneity
in the readiness scores was found across the packages and facility types underscoring
variation in the quality of care. On an average, the readiness of district and sub
district hospitals across platforms were colossally different from facilities at the
lower hierarchy of pyramid. Reproductive, maternal and child health were identified
as better performing as facilities had an average of 91%, 70% and 66% of requisite
components and supplies for provision of immunization, family planning and maternal
and child care. The dissimilitude amongst district hospital and lower level health centers for birth
preparedness and complication was colossal with district hospital effectuating 75%
of desired inputs and processes for delivery care, whereas NTPHC’s and sub centers
were impaired with decrepit standards having 23% and 27% composite scores respectively.
Adding a caveat, onlyone tenth of sub centers and NTPHC’s reported providing obstetric and newborn services
highlighting major lacunae in the delivery care. The readiness of services under Disease
Control Program aiming to bridle the prevalence of vector borne diseases exhibited
similar pattern with sub centers having disconcertingly low scores. These results
reflect some compelling evidence on inadequate level of preventive care at the peripheral
level which is otherwise indispensable for low resource settings due to cost effectiveness.
In general, overall readiness for management of Tuberculosis and leprosy comprising
screening, referral and follow up on cases with confirmed diagnosis and prescribed
treatment was 60% for higher level health facilities which is quite suboptimal for
priority targeted interventions. The score was subjacent at 30% for sub centers and
lowest at 15% for NTPHC’s as compared to other levels of care. The capacity of facilities
to optimally diagnose and treat non-communicable diseases across the continuum of
care is abysmally low across all levels of care while the population grapples with
high burden of non-communicable diseases leading to gargantuan demand-supply gap wedge.
For respiratory conditions, though 81% facilities provided services but no facility
had all tracer commodities and staff for administering services and were equipped
with 38% of recommended requirements only. Concomitantly, while secondary care hospitals
provided 38% of services for diabetes, these figures nosedived for primary care facilities
and further deflated down to 0% for sub centers connoting none of the sub center had
any diabetes related services and preparedness. However, the degree of readiness for
cardiovascular diseases oscillated between with 29% for hospitals to merely 6% for
sub centers and was mostly characterized by drugs for treatment of blood pressure.
Although lower level facilities are relegated with basic functions like screening,
referral and monitoring of symptoms of cancer, they failed to comply with the norms
and were completely defunct in provision of services. The provisioning of mental health
services was also appalling with service provision being null and void in hospitals
and only counselling related services provided in primary care. Only 6% of public
health workers in rural peripheries reported providing counselling services albeit
they were not trained in counselling, thereby, casting a shadow over the quality and
effectiveness of such services. This is particularly alarming in a tense geopolitical
scenario such as for people living along the borders are for most part powerless,
with little control over their environment and are also extremely vulnerable to physical
and psychological injury. It is also tenable to have robust emergency preparedness
and response as people residing in study sites find themselves in direct line of fire
as the area is strewn with landmines and is perturbed by cross border shelling and
militarized encounters. Emergency referral is critical to improving outcomes in such
time sensitive conditions. In spite of this district having high exposure to risk,
emergency preparedness scores were low at merely 30% for district hospital and 9%
for sub centers with no priority preparedness being for facilities at the precipice
of border and less venerable to risk facilities. Poor readiness was found for indicators
like presence of bunkers in vulnerable facilities, availability of bullet proof ambulances,
strong communication network and availability of surgeons and blood transfusion etc.
5.4 Creating Vulnerability Index
Vulnerability index is a parsimonious yet practical tool to adjust healthcare delivery
based on access and gauge the relative exigencies faced by the various facilities
in the context of difficult/fragile setting. In our area context; facilities are
navigating multitude of structural, non -structural and functional challenges such
as topographical, seismological, security, infrastructural and presence of vulnerable
communities and groups. The index was constructed incorporating myriad of indicators
adapted and modified from High Level Expert Group Report on Universal Health Coverage
for India (Planning Commission of India, 2011) and the scores for each indicator were
assigned across facilities based on exposure, sensitivity and resilience after having
deliberations with district administrative authorities. Operational vulnerability
of facility was chosen as the focal point based on the axis of external and internal
conditionals i.e. vulnerabilities spanning susceptibility and exposition to shocks
and stresses as external conditionals and incapacities/capacities of facilities to
amplify/attenuate the stresses and shocks as internal conditionals(Birkman and Wisner,2006).
The degree to which a facility delivers effective care is sensitive to the stressors
emanating from internal or external environment. The method coalesced 13 indicators
representing vulnerability on a scale of 0 to 50. The index takes into account variables
capturing a) isolation factor such as travel time to healthcare facility by walk/other modes of transport, difficulty
of terrain, availability of transport, distance to major district roads and public
transport b) density of health workers given population density and geography c) infrastructural impediments such as condition of the roads and availability of government accommodation d) security threat such as cross border firing zones and militancy affected areas and e) marginalized population such as proportion of tribal population in the catchment area. The detailed description
of indicators and weighting strategy for vulnerability index calculator is propounded
in Table 1, Appendix.
Following narrative echoes the various layers of vulnerabilities experienced by providers
in our context.
“As you can see that our facility is after crossing border’s fencing in zero line
and firing/shelling ensues erratically at drop of the hat. Every day we have to cross Army enclosure post cordoning formalities encumbered with
fear and uncertainty. No public transport comes here, I have to come in my bike till
the fence which costs me ten thousand rupees every month out of my fourteen thousand
rupees salary. Moreover, after crossing the fence, we have to walk for 2 kms amidst
thick forests and bushels. During winters, when fog gathers; it exacerbates risks
as leopards prowl here. During the days when shelling catapults, we have to take cover
and use alternate routes via gullies to reach facility. Last month only, a bullet
ricocheted off next to me and I panicked hard”.
-Male MPW(Contractual, Medical Aid Center)
5.5 Determinants of Health facility readiness scores
Health facility readiness score was modelled as a function of covariates and table
2 presents the results of generalized ordered modelling where a unit increase in independent
variable, alters the probability of falling in the jth alternative by marginal effect
in percentage terms. For each facility, general readiness score was calculated by
coalescing scores across five dimensions encompassing a legion of tracer indicators.
The distribution of average facility scores was fitted into quartiles to create a
three-level ordinal scale for health facility readiness. The dependent variable is
polychotomous and outcome falls into three quartile categories i.e. high, medium and
low. Vulnerability score, facility type and administrative area reflected the largest
magnitude of marginal impact on outcome probabilities. Medium vulnerability score
was found to be associated with poor readiness as it was 14.7% more probable than
lower vulnerability to result in poor readiness. However, facilities with menacing
vulnerability scores were 19.1% more likely to have poor outcome and conversely, 19.8%
less likely to yield good readiness scores compared to the reference category. It
can be surmised from table that frequent supervision and monitoring is associated
with 9.2% lesser probability than sporadic supervisory visits to beget poor readiness.
Although better supervision was more likely to have good readiness, this finding was
statistically insignificant. Facility type was found to be another impregnable factor
impacting the dependent variable as physician led clinics and hospitals were 24.7%
less and 14.3% more likely than peripheral sub centers to have poor and good readiness
respectively and in terms of magnitude, the effect of facility type was more extreme
at lower levels of readiness score. Similarly, the impact of administrative block
was quite cogent in explaining the readiness scores as facilities in health block
Mendhar had 14.4% lesser and 14.7% more probability to culminate poor readiness vis
a vis block Mandi. Understaffing of facilities however, was significantly more likely
than no vacancy of core health worker to have poor readiness by 10.3%.
Table 2: Marginal Effects of the Covariates for each outcome using partial proportional