Disparities in critical care resources across Pakistan – ndings from a national survey

Background: In response to the COVID-19 pandemic, concerted efforts were made by provincial and federal governments to invest in critical care infrastructure and medical equipment to bridge the gap of resource-limitation in Intensive Care Units (ICUs) across Pakistan. An initial step in creating a plan towards strengthening Pakistan’s baseline critical care capacity was to carry out a needs-assessment within the country to assess gaps and devise strategies for improving the quality of critical care facilities. Methods: To assess the baseline critical care capacity of Pakistan, we conducted a series of cross-sectional surveys of hospitals providing COVID-19 care across the country. These hospitals were pre-identied by the Health Services Academy (HSA), Pakistan. Surveys were administered via telephonic and on-site interviews and based on a unique checklist for assessing critical care units which was adapted from the Partners in Health 4S Framework, which is: Space, Staff, Stuff, and Systems. These components were scored, weighted equally, and then ranked into quartiles. Results: A total of 106 hospitals were surveyed, with the majority being in the public sector (71.7%) and in the metropolitan setting (56.6%). We found infrastructure, stang, and systems lacking as only 19.8% of hospitals had negative pressure rooms and 44.4% had quarantine facilities for staff. Merely 36.8% of hospitals employed accredited intensivists and 54.8% of hospitals maintained an ideal nurse-to-patient ratio. 31.1% of hospitals did not have a stang model while 37.7% of hospitals did not have surge policies. On chi-square analysis, statistically signicant differences (p<0.05) were noted between public and private sectors along with metropolitan versus rural settings in various elements. Almost all ranks showed signicant disparity between public-private and metropolitan-rural settings, with private and metropolitan hospitals having a greater proportion in the 1 st rank, while public and rural hospitals had a greater proportion in the lower ranks. Conclusion: Pakistan has an underdeveloped critical care network with signicant inequity between public-private and metropolitan-rural strata. We hope for future resource allocation and capacity development projects for critical care in order to reduce these disparities. and healthcare structure. The nature of Pakistan’s decentralized healthcare system and lacking infrastructure represent key areas for policy development and resource allocation by decisionmakers to overcome the disparities in critical care. Our survey model may be replicated in other countries to assess the adequacy of healthcare delivery, in critical care and beyond.


Study Setting, Population and De nitions:
With over 220 million residents, Pakistan is a developing country that employs two large-scale independent healthcare networks: the public setup that is led by provincial governments and the private one that is administered by autonomous stakeholders. We de ned ICU as any hospital unit with the availability of invasive mechanical ventilation for the maximum number of patients within that unit. We also surveyed high-dependency units (HDUs) if hospitals did not have ICUs available for the care of Covid-19 patients, and HDUs were de ned as units which offered continuous monitoring and care to patients short of delivering invasive mechanical ventilation. Neonatal and pediatric facilities were excluded.
Study Instrument (Supplement 1): We deployed a novel 52-point checklist that utilizes the Partners in Health, 4S (Staff, Stuff, Systems and Space) framework to assess and evaluate critical care facilities (Supplement 1). The existing framework was modi ed to account for contextual applicability after a detailed literature search and expert review.
This foundational assessment included information on essential and recommended facilities in an ICU/HDU. Basic hospital information collected included number of hospital beds, number of ICU beds and type of unit. The components were: Space (infrastructure), Staff (healthcare workers in a critical care unit) Stuff (consumable and non-consumable supplies, both medical and non-medical) and System (policies and protocols). Data collection was done in two phases. In the rst phase, the Pakistan Ministry of National Health Services Regulations and Coordination provided the core research team an o cial, authorized list of existing hospital facilities to be surveyed, along with their contact information. The rst phase took place from May 2020 to November 2020. In the second phase, a list of hospitals was obtained from each of Pakistan's respective provincial national ministries. This phase took place from June 2021 to August 2021. A bimodal interview strategy was executed, whereby, telephonic, or on-site interviews were conducted. All collected data from the checklists was entered onto a standardized REDCap survey form.
Quality control: Prior to data collection, all team members were trained through orientation and practice sessions. To further augment this and minimize inter-operator reporting bias, a guidance document with descriptions of each item on the checklist and a uniform written script were also provided to all interviewers. Pilot testing of the study instrument was done prior to o cial rollout of the survey. A central communications team was also established to keep track of all outgoing correspondence and conduct real-time troubleshooting.
Statistical Analysis: Analyses were done using R version 4.1.1. Descriptive statistics have been reported as frequencies and percentages for the categorical variables and mean and standard deviation for the continuous variables. Chi-square analysis and Fischer's exact test were done to analyze the differences between public against private hospitals, and also metropolitan against rural hospitals.
As the score of each of the 4S components did not add up to same amount, we used a weighted index by dividing the total number of questions by the number of questions in each component so that all the components were scored uniformly out of a denominator of 25. These sections were then also added up to make an overall percentage score out of 100. Analysis of variance (ANOVA) and post-hoc Tukey's Honestly Signi cant Difference (HSD) tests were done to observe any statistically signi cant heterogeneity between component scores.
The hospitals were then ranked using the quartiles from the percentage scores. Ranks were also clustered within the individual components of Space, Staff, Stuff, and Systems, within which we observed the proportionate breakup of hospitals along the lines of hospital setting, sector, and size.

Ethical Considerations and Data Management:
This study was approved by the Ethical Review Committee, the institutional review board at the Aga Khan University. Verbal consent was obtained before every interview and all data were kept con dential. Access to data was password-protected and limited to the core analysts only, to ensure due data privacy and security protocols.

Results
A total of 135 hospitals were approached, of which 106 (78.5%) responded, and their characteristics are displayed in Table 1. All these hospitals accepted care of adult COVID-19 patients. There were regional disparities in the distribution of critical care facilities, with almost 90% of ICUs/HDUs concentrated in Punjab, Sindh, and Khyber Pakhtunkhwa (KPK) respectively and fewer facilities in Gilgit-Baltistan (5.7%), Azad Jammu and Kashmir (AJK) (4.7%), Baluchistan (0.9%) ( Table 2). 76 hospitals (71.7%) were in the public sector, 26 (24.4%) were private hospitals, and 4 (3.77%) were administrated by philanthropy-based foundations. 60 hospitals (56.6%) were located in the metropolitan setting while 46 (43.4%) were located in the rural setting.  Type of healthcare setup and geographical location were the main categories for comparison. Philanthropy-based facilities were included as private hospitals for the purpose of analysis. The number of ICU beds per hospital in the public sector is 15.1 beds while in the private sector it is 13.8. In the metropolitan setting, it is 18.9 while in the rural setting, it is 9.2. There are 11.9 ventilators per hospital in public hospitals, 9.4 in private ones, 13.9 in metropolitan ones, and 7.6 in rural hospitals. Our 4S components were also analyzed along these lines.

Space
The majority of units had gaps in their infrastructure and were not adequately equipped. Only 21 (19.8%) contained negative pressure rooms, with greater scarcity in public sector hospitals compared to private ones (p=0.004). 59 facilities (55.6%) had no quarantine and lodging facility for the staff members and isolation rooms were present in 74 facilities (69.8%). Signi cant difference was noted in the availability of medical air, vacuum, adequate gas, and adequate power outlets at the beds in public sector hospitals and rural areas as compared to private or metropolitan hospitals. Notably, rural areas are comparatively lacking in a centralized manifold for oxygen delivery (p=0.048), with oxygen being delivered to patients via individual bedside cylinder. The mean score for the Space components was 5.91 out of a total of 9.
Detailed characteristics of the Space component can be seen in Table 3. Detailed characteristics of the Staff component can be seen in Table 4. Detailed characteristics of the Stuff component can be seen in Table 5. System information technology (IT) support and transport. Less had them for patient surge (62.3%), risk mitigation (51.9%) and environmental control (56.6%).
Signi cantly fewer rural and public hospitals had support access via biomedical, IT and infrastructure support policies. 73 hospitals (68.87%) had sta ng models for doctors and nurses, but ICU work ow policies with sta ng models for doctors (p=0.009) and nurses (p=0.028) were reported to be signi cantly less in rural hospitals. Public sector hospitals showed gaps in emphasizing infrastructure failure (p=0.013) and cardiopulmonary resuscitation (CPR) policy (p=0.05), with rural hospitals also being less likely to implement CPR policies (p=0.011) as well. The mean score for the System component was 11.68 out of a total of 16.
Detailed characteristics of the System component can be seen in Table 6. We had hypothesized that private hospitals were better-resourced as compared to public ones, and also that metropolitan hospitals more well-equipped than rural ones. We performed a cluster analysis where we made 4 quartiles of ranks in each of the 4S components, and also in overall scoring. We then observed the breakdown of each rank in the components according to hospital setting, hospital sector, and hospital size in terms of bed numbers, and this breakdown is seen in Table 7, which shows statistically signi cant disparity between these strata. comparisons were done between pairs of the 4 components and statistically signi cant differences were seen between stuff-staff (p<0.001), stuff-space (p<0.001), and system-stuff (p=0.008). Staff-space (p=0.921), system-space (p=0.157), and system-staff (p=0.463) did not show a statistically signi cant difference. The results of this are presented in Figure 2.

Discussion
We found signi cant disparities between public/private and urban/rural hospitals with public and rural hospitals being signi cantly under-resourced. Overall, we found a de ciency in negative pressure rooms, quali ed intensivists, nurses, and institutional policies across Pakistan. We also found that public sector hospitals and rural hospitals were signi cantly under-resourced in a number of areas. Our scoring system is potentially valid assess healthcare capacity to care for critically ill patients.
Across the board, there is also a shortage of accredited intensivists and nurses in Pakistan's critical care units. Only 36.79% of hospitals had even 1 quali ed intensivist as the consultant physician in their ICU. While almost all hospitals employed nurses, only 54.72% of hospitals had an optimal nurse-to-patient ratio of 1:2, with a signi cant dip in their availability in both public and rural hospitals. The literature shows that higher nurse-to-patient ratios result in increased incidence of morbidity, mortality, and increased ventilator time for patients, so underquali cation and understa ng could lead to compromised patient outcomes (3,(18)(19)(20). Research to assess barriers towards critical care training is required to inform the advancement of accredited critical care training programs.
There were no hospitals at all that ranked 1 st in our System component, showing that Pakistan's ICUs require more well-de ned organizational policies across the board. Several hospitals were lacking in protocols for admissions, surge situations, PPE, airway management, and infrastructure failure, which could compromise patient care. Pakistan's rural hospitals were also signi cantly less likely to make use of sta ng models for doctors and nurses. This could potentially leave critical care doctors and nurses more susceptible to burnout. Healthcare systems abroad employ tiered sta ng models to circumvent shortages of healthcare workers by repurposing staff from other specialties for speci c critical care procedures, and this is recommended in managing ICU surge capacity (21,22). More work should be done in introducing policies and strategizing around the current constraints in critical care human resources.
We observed substantial variation in the overall healthcare delivery of critical care units throughout Pakistan. Pakistan's decentralized healthcare setup meant that we anticipated the differences in resources across provinces, as each province is responsible for the budgeting and upkeep of their own respective public hospitals. The lack of any robust healthcare coverage system means that substantial swathes of society are dependent on the subsidized public setup for healthcare. Therefore, the lack of adequate resources at these hospitals renders the less fortunate to inequitable critical care and possible morbidity or mortality (23,24). As of yet, there are no studies on the effect of public and private critical care on Covid-19 outcomes. However, there is literature from Brazil, a high-middle income country with a similar dichotomy in its public-private healthcare system as Pakistan, which showed that being treated at a public hospital ICU is an independent risk factor of mortality in sepsis patients (25). They reported that these hospitals featured an "unfavorable patient-healthcare professional ratio, non-optimized processes, and a lack of adequate infrastructure"; these ndings are also present in our setting.
Rural areas are more lacking in important consumable resources and infrastructural components, which is alarming because 63.56% of Pakistan's population is based in rural areas, a sizeable majority (17). They are lagging behind in several key characteristics in each section of our 4S checklist. While developed countries like the United States also experience disparity in critical care delivery between rural and metropolitan areas, the gap that we have found in our setting is more stark (26,27). The shortcomings in critical care delivery to these areas makes its populace susceptible to the worst complications of critical Covid-19.
The current literature that we found on ICU capacity assessment only includes descriptive data. Our checklist scoring and clustering system represents a novel and potentially useful method of assessing hospital resources. ANOVA testing of the means of our component scores reveals that there is a signi cant difference between components, and we can provisionally say that our system of scoring and ranking hospitals is valid. We did not capture any patient data in our study, but comparing clinical outcomes between hospital ranks would help assess our ranking system's applicability.
There are some limitations to our study. The list of hospitals was obtained from government registries which meant that we did not have access to hospitals that were not featured on such registries. Baluchistan was underrepresented, with only 1 hospital in our survey. More partnerships between the federal government and hospitals in Baluchistan are needed, as there was an overall lack of hospitals and limited accessibility to them. We were logistically unable to conduct a eld visit at each hospital, which meant data collection was left to the knowledge of the telephonic respondents who may or may not have had an adequate inventory of their hospitals.
However, this is still the rst national level cross-sectional survey conducted during the Covid-19 era; it employs and adapts the 4S data collection instrument to holistically assess and rank infrastructure, inventory, human resources, and policy at each critical care unit. It can also be utilized for other capacity strengthening initiatives in Pakistan and worldwide (21,28). We have observed the disparities in Pakistan's critical care delivery, between government and private hospitals and also between the metropolitan and rural settings. We hope that our study will encourage stakeholders to nd targeted solutions to better critical care delivery across Pakistan such as training programs, broader investment, and creative thinking.

Conclusion
The study has highlighted how Pakistan has an underdeveloped critical care network with signi cant inequity between across population densities and healthcare structure. The nature of Pakistan's decentralized healthcare system and lacking infrastructure represent key areas for policy development and resource allocation by decisionmakers to overcome the disparities in critical care. Our survey model may be replicated in other countries to assess the adequacy of healthcare delivery, in critical care and beyond.  Tukey's HSD testing of component scores, written as n, p-value

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