Operationalizing Organizational Capacity Assessment for Identifying Capability Gaps in the Indian Hospital Sector

Abstract

This study interprets the development and validation of the organizational capacity assessment tool, which is designed to evaluate the gaps in capabilities of hospitals across India. This assessment tool was tested on 300 managers working in hospitals across 16 states of India, with a majority coming from small-sized hospitals. The 40-item measure assessed six factors of organizational capabilities, namely, organizational foundation, organizational resources, organizational capacities, core task implementation, benefits and impacts, and external relations. Gaps in the capacities were identified. Internal consistency was evaluated using the Cronbach’s alpha. Confirmatory factor analysis supported the inclusion of the items in the questionnaire. In addition, structural equation modeling was conducted to evaluate the goodness of fit of the model demonstrating the relationships between the study variables. It was found that individual factors such as core task implementation and organizational foundation significantly influenced benefits and impacts as well as external relations. Similarly, organizational resources positively impacted evaluation capacity outcomes. In contrast, organizational capacity had no significant influence on either benefits and impacts or external relations. This study only validates the capacity assessment tool; however, it needs to be measured with varied types of work personnel within the healthcare sector as there is a huge diversity in the work force of this area. Based on this empirical study, many future research implications were suggested.

Keywords

Organizational capacity assessment healthcare sector benefits and impacts external relations financial resources core task implementation

1. Introduction

The Indian healthcare sector forms among the top-ranking industries in India with respect to revenue generation and employment strength (IBEF, 2020). Growth drivers include increased infrastructure in the near future, enhanced use of services due to increase in average life expectancy of Indians, heightened scope for medical tourism, presence of healthcare centers, rising earnings, and rise in automatic processes through robots (India Health, 2019). Typically, the meaning of healthcare sectors includes hospitals, healthcare centers, pharmaceuticals, diagnostics, medical tourism, telemedicine, health insurance, equipment as well as supplies. Even though the market size is exponentially increasing with a compound annual growth rate (CAGR) of 22%, India is ranked lowly in terms of quality and approachability, standing at the 145th position within 195 nations (IBEF, 2020). Thus, working toward improving quality and accessibility should be our primary concern. This clearly implies that India has a great potential for improvement as public and private investments in healthcare infrastructure is increasing at a staggering rate to the tune of CAGR of 16%–17%. On the other hand, India can be considered to be in an advantageous position as there is a large pool of well-trained medical professionals available and government policy that are supportive of growth. The first step toward improving ranking lies in the evaluation of healthcare areas. Since the scope of healthcare areas is broad, therefore, considering hospitals as healthcare organizations will be convenient for our study. Sulaiman et al. (2018) have described hospitals as organizations which are “capital-intensive,” human resource-rich, technologically furnished business units that handle business by rendering services in terms of medical, nursing, nutritional, pharmaceutical, and diagnostic, along with general administrative work and financial accounting for its smooth functioning. Therefore, considering hospitals as organizations, this study adopted an approach for assessment of organizational capacity in hospitals from 14 states across India using an assessment tool. Moreover, it was observed that there are hardly any studies describing capacity assessment in hospitals. Organizational capacity assessment has mostly been employed by organizations when in need of funding. Thus, our study is a necessity for managers who are in the pursuit of improving their organizational efficiency.

The primary aim of our study was developed so as to provide an answer to the following research question: “How can the organizational capacity assessment tool be applied in identifying gaps in capabilities of different types of hospitals?” Based on the research question, the following objectives are proposed:

To identify the gaps which are present in the capabilities of the hospitals using the organizational capacity assessment tool.

To validate the components of the organizational capacity assessment tool used for identifying gaps in organizational capabilities of hospitals.

2. Organizational Capacity Assessment Tools

The organizational assessment (OA), also known as organizational capacity assessment (OCA), can be defined as a structured tool for a facilitated self-evaluation of an organization's capacity followed by action planning for capacity improvements and initiative developments (Simister & Garbutt, 2017). In addition, this may include both monitoring and evaluation. The organization capacity assessment tool described by Booth et al. (1998) showed that the participation cycle identifies the problem and then reflects on the real needs, followed by decision-making and finally action is taken. Ibrahim and Gambo (2019a) described it as an instrument that evaluates the internal and external factors rather than using any fixed-format or tried-and-tested practices. These facilitate the organization to diagnose the underachieved areas for the scope of performance improvisations in the organizations (Breuer et al., 2015). Since there is no fixed formula for organizational success, each organization needs to find its own loopholes and do corrective measures for amendment. Booth et al. (1998) used OCA tool as a diagnostic measure for evaluating the maturity of firms, for estimating the existing capabilities as well as teaching the employees regarding their effective functioning and creation of commitment goals. Shapiro (2007) and LeMay (2010) listed some of the advantages that OCA can reveal about the organization such as providing crucial information controls the functioning of programs, ensures proper reporting of procedures and confirming the use of standardized processes. This self-assessment approach increases the ownership of the action plan. The OCA format helps the organization reflect on its processes and functions and score itself against benchmarks. Based on the discussions and the scoring, the organization shapes and sets priorities for actions that it can take to strengthen its capacity.

According to Booth et al. (1998) and Simister and Garbutt (2017), the OA undergoes four basic stages. As reported by Booth et al. (1998), it grows with the organization, commencing from nascent to emerging to expanding to mature. However, Simister and Garbutt (2017) elaborated that stage 1 starts with the division of capacity into distinct zones according to their functions such as management, leadership, resources etc. This is followed by the development of a transparent ‘rating system’ (stage 2). Stage 3 involves the receipt of assent from various stakeholders of the organization and then final stage 4 encompasses the critical analysis of the rating system and enforces the action plan to enhance the status of capacity in the organizations.

Dearing (2018) presents a list of OCA tools developed by various organizations, according to their needs. The typical purpose of using this tool, mostly by NGOs, has been used to get funding for improving the capacity of the organizations. Out of the various types of OA tools, the common ones include the McKinsey capacity assessment, capacity assessment framework, participatory organization evaluation tool (POET), USAID questionnaire, etc. The components varied from one tool to another as observed from Table 1. Validity and reliability testing of these tools have not been conducted for all, with a few exceptions such as Krishnaveni and Sripirabaa (2008a, b).

Table 1.

Components of OA Tools Used by Various Researchers.

Sl.	Name of the Tool	Variables	Reference
1.	OCAT	Governance, management practices, human resources, financial resources, service delivery, external relations, and sustainability	Booth et al. (1998), Mundia (2009)
2.	Capacity assessment	Inputs (leadership, finances, infrastructure, human resources, financial policy context, and organizational culture context), process (financial management, strategic planning, resource mobilization, advocacy, etc.), output (staff training, external links, and operational plans), and outcomes in terms of financial reliance	Brown et al. (2001)
3.	Capacity assessment areas	Recruitment and selection, performance management system and training and development	Krishnaveni and Sripirabaa (2008a)
4.	Modified POET tool	Identification of training needs, designing and implementing training programs, transfer of training, evaluation of training program benefits, partnering, financial resource management, and alignment of training and development goals	Krishnaveni and Sripirabaa (2008b)
5.	Holistic organizational capacity assessment instrument	Identity and governance, strategy and planning, general management, external relations and partnerships, sustainability, organizational learning, human, financial and physical resource management, programming, and services and results	Catholic Relief Services (2011)
6.	Organizational capacity for public health	Fiscal and economic resources, workforce and human resources, physical infrastructure, interorganizational relationships, data and informational resources, system boundaries and size, governance and decision-making structure, and organizational culture	Meyer et al. (2012)
7.	Clinic capacity checklist	People, process, and technology	Shea et al. (2014)
8.	Self-administered internal faculty survey	Forces in the external environment, organizational motivation and commitment, and organizational capacity	Jessani et al. (2014)
9.	OCAT	Leadership, planning and control, organization and systems, education, community services, research, human resource management, student management, and facilities and infrastructure	Deuren et al. (2015)
10.	Organization readiness tool	Organizational attributes, management and governance, collaboration, organizational performance, and external environment	Dearing (2018)
11.	Church OCA	Staffing and space, health promotion experience, and external collaborations	Holt et al. (2018)
12.	OCAT	Governance, coordination and partnerships, planning, budgeting and finance, monitoring and evaluation, human resource management, service delivery, infrastructural facilities, and resource mobilization	Ibrahim and Gambo (2019a, b)

From the Table 1, few commonalities as well as differences were observed amongst the above defined commonly used OCA tools. Financial and human resources were the basis for commonality among all these tools, whereas each OCAT from organisations varied in terms of variables such as governance, training needs, partnerships and sustainability. Hazy (2008) conducted a survey on cultural dimensions and found that the four dimensions namely, strategy and roadmap, member engagement, decision quality and timeliness and norm execution influence the member behaviour in culture formation in an organization. Hence it is suggested to include these items in capturing culture in the organizational capacity assessment. Korst et al., (2011) conducted a study on the hospital readiness to participate in health information exchange as part of the organisational capacity assessment and found that human resource factor (e.g., hospital leadership) predominantly contributed to the quality improvement culture of the hospitals.

Booth et al. (1998) described some of the disadvantages of these self-assessment tools. It is expected that the participants need to be more matured and experienced enough for proper implementation. Moreover, it can become time-consuming and lagging in the required quality of information, thereby causing improper conclusions. Lafond and Brown (2003) reported that capacity assessment involves only one-time measurement. However, these assessment tools have been found to be useful by many organizations as capacity has been considered to be one of the main factors influencing performance (Brown et al., 2001). Even though there are many OCA scales available, there are hardly any studies on validation of scales testing the organizational capacity, especially in case of hospitals. To the best of our understanding, the concept of using organization capacity assessment as tool for improving organizational performance has not yet been explored in the area of healthcare industry but seems to have a huge potential in the future.

3. Methodology

3.1 Sampling Design

The current study employs convenient sampling technique, a nonprobability sampling technique where subjects are selected because of their convenient accessibility and proximity to the researcher. Ideally, the entire population comprising of all the managers working in various hospitals forms our general population for this study. However, it is physically impossible to collect data from each of these managers on the research topic. Therefore, the target population was represented by the managers working in hospitals across India, which is estimated to be 1,200. The minimum sample size estimated using Cochran’s formula for unknown population with the 95% confidence level and a 5% margin of error was calculated to be 291. Thus, a total sample size of 300 managers from various hospitals across India was selected, well above the estimated count.

3.2 Study Participants and Their Organizations

The demographical characteristics of the participating managers have been elaborated in Table 2. The sample population comprised of 171 males and 129 females. The demographic overview showed that the majority of our participating population comprised of 30–39 years old male managers working in the medical department at middle-level managerial positions. However, more than half of them (55.3%) had 5–10 years of work experience.

Table 2.

Demographics of the Hospital Managers.

Demographics	Categories	Frequency	Percent
Gender	Male	171	57
Gender	Female	129	43
Age	20–29 years	47	15.7
	30–39 years	148	49.3
	40–49 years	52	17.3
	> 49 years	53	17.7
Department	Emergency care	73	24.3
	Finance	5	1.7
	HR	24	8
	Medical	112	37.3
	Operations	24	8
	Pathology	62	20.7
Work experience	< 5 years	99	33
	5–10 years	167	55.7
	> 10 years	34	11.3
Managerial position	Lower	103	34.3
	Middle	145	48.3
	Senior	52	17.4
Total		300	100

Source: Survey data.

For understanding the characteristics of the organizations, the hospitals can be classified according to their functionality, size, and type of services rendered. For our study, we categorized each hospital according to their sizes into large, medium, and small units. Any hospital with fewer than 100 beds was considered as small, whereas hospitals with 100 to 499 beds were labeled as medium, and hospitals having more than 500 or more beds were called large. In our study, each hospital was represented by a single manager working in the hospital. Table 3 lists the distribution of hospitals located within India according to their size. It was observed that the maximum hospitals chosen for the study belonged to the state of Karnataka.

Table 3.

Distribution of Hospitals Across India That Were Taken into Consideration in Our Study.

Sl.	State	Large Hospitals	Medium Hospitals	Small Hospitals	Total Respondents
1	Andhra Pradesh	4	3	8	15
2	Assam	1	3	6	10
3	Bihar	1	6	8	15
4	Delhi NCR	7	8	15	30
5	Himachal Pradesh	4	7	9	20
6	Karnataka	8	11	20	39
7	Kerala	4	8	10	22
8	Madhya Pradesh	2	4	8	14
9	Maharashtra	5	10	12	27
10	Orissa	4	7	10	21
11	Rajasthan	3	7	10	20
12	Tamil Nadu	3	9	12	24
13	Telangana	2	2	5	9
15	Uttarakhand	0	5	6	11
16	West Bengal	2	10	11	23
	Total	50	100	150	300

Source: Survey data.

3.3 Research Instrument

For the purpose of evaluating the capacity of the hospital, the measure for this study was selected from the various OA tools as mentioned in the website of a UK-based company.¹ This tool has been numbered 8, called the capacity assessment guide, which is a well-structured questionnaire. It included 40 items and divided into six sections pertaining to capabilities: organizational foundation, organizational resources, organizational capacities, core task implementation, benefits and impacts, and external relations. Organizational foundation and core task implementation formed the individual factors, whereas benefits and impacts and external relations constituted the evaluation capacity outcomes. The organizational resources were further divided into physical and information resources, financial resources and human resources. Leadership, organization, and management and learning constituted the measures for organizational capacities. Organizational foundations represent an organisation’s vision, mission and strategy that are clearly defined, consistent and shared among staff. They represent the strategy that links core programmes with organisational capacities and environmental realities, to promote sustainable change. Organisational resources are the financial, human resource, physical and information resources of an organisation while organisational capacities encompass leadership, learning, administration and management. Core task implementation indicates the performance and accountability of staff in an organisation. Monitoring and evaluation provides feedback used for performance improvement and organisational learning. Benefits and impacts are indicated through the programmes that build sustainable local capacities and resources rather than dependencies making the beneficiary perceive and value benefits. Organisation creates and maintains stable relationships with external environment. Organisation builds alliances with and learns from other NGOs and competitive firms. This particular tool was selected due to its holistic nature of covering all important and critical aspects of organisational capacity. Moreover, it was also found to be depending upon the staff size, budget, organisational culture, leadership, capacity requirements, logistics and other complexities within these organisations (Hewlett Foundation, n.d.). The questions for evaluating each variable were measured on a five-point Likert scale with values ranging from one to five, where 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, and 5 = strongly agree.

3.4 Data Analysis

The data collected were subjected to statistical analyses using statistical software IBM SPSS version 24, and meaningful inferences were drawn from the results. Various tests were conducted depending upon the study requirements. Descriptive statistics in the form of frequency with percentage and mean with standard deviation was used to summarize demographic data and other variables of the study. Pearson’s correlation was conducted to identify the gaps present in the capabilities of the hospitals using the organizational capacity tool, followed by which the assessment was tested for its reliability and validity. The reliability was tested using Cronbach’s alpha (α) as reported by Cronbach (1951). Confirmatory factor analysis (CFA) was done to measure how well the measured variables represent the number of constructs by assessing factor loadings, variance, and covariance (Bowen & Guo, 2012). After this, structural equation modeling (SEM) was used to evaluate any existing relationship using analysis of moment structures software. It is also known as analysis of covariance or causal modeling software. This helps in evaluating the goodness of fit of the theoretical model with the help of good and bad indices of fit such as chi-square, comparative fit index (CFI), Tucker–Lewis index (TLI), and root-mean-square error of approximation (RMSEA), respectively. RMSEA refers to the “discrepancy between the estimated and observed covariance matrices per degree of freedom in terms of the population, not the sample” (Hair et al., 2010), whereas the CFI compares the estimated model with the null model and is sensitive to the sample size of the study (Kline, 2011). TLI, on the other hand, “compares the estimated model fit to a null model and takes into account the model parsimony by assessing the degrees of freedom from the estimated model to the degrees of freedom of the null model” (Garver & Mentzer, 1999). It does not depend on the sample size. The recommended threshold values for χ² / df were less than 3, RMSEA should be between 0.5 and 0.8, whereas the recommended values for CFI and TLI are more than 0.90 (Hu & Bentler, 1999). CFA of first order and second order were made to assess the higher order of the constructs. CFA analysis and SEM were considered as a two-step process (Jöreskog, 1993). This is the graphical equivalent of the mathematical depiction of the relationship of the explanatory variables on dependent variables.

4. Results

4.1 Correlation Studies

Table 4 demonstrates the mean, standard deviation, and correlation between all study variables, namely, organizational foundation, organizational resources, organizational capacities, core task implementation, benefits and impacts, and external relations. The highest capabilities were observed in organizational resources, particularly financial resources (4.17 ± 0.80) and lowest in core task implementation (3.07 ± 0.92). Statistically significant correlations at varying degrees were observed between the variables. The highest level of correlation was observed between benefits and impacts with external relations (r = 0.998). High level of association was also observed between core task implementation and benefits and impacts (r = 0.96); physical and informational resources and financial resources (r = 0.69), organizational capacity such as leadership with human resources (r = 0.85), benefits and impacts with organizational foundation (r = 0.96), and external relations also with organizational foundation (r = 0.96). Organizational foundation was found to be negatively correlated with organization and management (r = −0.30) as well as core task implementation (r = −0.23). Organization and management were also negatively influenced by organizational capacities such as learning (r = −0.17), evaluation capacity outcomes such as benefits and impacts (r = −0.28) and external relations (r = −0.287). The correlations were significant at P < 0.01 for all values mentioned above. From these results, it can be implied that a lot of gaps were identified in terms of capabilities of the hospitals used in the study. The managers perceive implementation as the major issue in capacity building. There was a clash between the vision and mission of the organization with communication within the peers. The divide and coordination between the structures of the organization prohibited problem-solving. Resources of all forms were associated with the supervisors and even higher authorities. Moreover, the top heads were linked to implementations of tasks. Within both the evaluation capacity outcomes, benefits and impacts are connected to the spread of external relations. Therefore, it is clear that these areas need improvement.

4.2 Reliability of the Assessment Tool

Table 5 represents the internal consistencies for each study construct, evaluated using Cronbach’s alpha. The Cronbach values greater than 0.6 are considered as acceptable, whereas values between 0.7 and 0.8 are considered satisfactory and more than 0.8 to less than 0.95 is considered to be good. All the constructs such as organizational foundation within individual factors (α = 0.76, N = 4), organization and management within organizational capacities, and benefits and impacts within evaluation capacity outcomes showed a satisfactory level of reliability. A good level of reliability was observed in the rest of the constructs such as core task implementation (α = 0.85, N = 4) within individual factors, physical and informational resources (α = 0.91, N = 3), financial resources (α = 0.86, N = 4) and human resources (α = 0.86, N = 4) within organizational resources, leadership (α = 0.93, N = 4) and learning (α = 0.80, N = 3) within organizational capacities and external relations (α = 0.86, N = 5) within evaluation capacity outcomes. This implies that a high level of internal consistency exists within the items of the questionnaire.

Table 4.

Correlation Between the Study Variables.

	Mean	SD	1	2	3	4	5	6	7	8	9	10
Organizational foundations (1)	3.350	0.871	1
Physical and informational resources (2)	3.897	0.946	−0.056	1
Financial resources (3)	4.176	0.803	−0.017	0.692**	1
Human resources (4)	3.944	0.840	−0.034	0.133*	0.224**	1
Leadership (5)	3.934	0.819	−0.026	0.116*	0.227**	0.851**	1
Organization and management (6)	3.613	0.779	−0.307**	−0.003	−0.033	0.045	0.012	1
Learning (7)	3.326	0.876	−0.078	0.056	0.057	−0.021	0.042	−0.170**	1
Core tasks implementation (8)	3.078	0.927	−0.236**	0.087	0.178**	0.110	0.176**	−0.020	0.469**	1
Benefits and impacts (9)	3.372	0.881	0.962**	−0.027	0.005	−0.043	−0.03	−0.289**	−0.076	0.962**	1
External relations (10)	3.375	0.884	0.966**	−0.028	0.005	−0.044	−0.03	−0.287**	−0.076	−0.183**	0.998**	1

Source: Survey data.

**Correlation is significant at P < 0.01. *Correlation is significant at P < 0.05.

Table 5.

Reliability Analysis.

Factors	Subfactors	Cronbach's Alpha	No. of Items
Individual factors	Organizational foundations	0.769	4
Individual factors	Core tasks implementation	0.852	4
Organizational resources	Physical and informational resources	0.912	3
	Financial resources	0.867	4
	Human resources	0.865	4
Organizational capacities	Leadership	0.936	4
	Organization and management	0.780	4
	Learning	0.803	3
Evaluation capacity outcomes	Benefits and impacts	0.790	5
Evaluation capacity outcomes	External relations	0.865	5

Source: Survey data.

4.3 CFA and SEM Model

For validation of the assessment tool, the relationship between the items and the first- as well as second-order latent constructs was evaluated, and the results showed that the first- and second-order CFA models were an acceptable fit for the data as observed in Table 6. Figure 1 illustrates the results obtained for the CFA of the latent variables followed by the SEM model. The basic fit statistics of the model suggest that the model has a good fit, which is the degree to which the observed input is forecasted by the estimated model. Although the chi-square was found to be significant (χ² = 113.356; df = 26; P = 0.000), the ratio of chi-square and degrees of freedom (χ²/df = 4.356) was observed to be fitting the model (Browne & Cudeck, 1992; Kelloway, 1995). Other fit indices such as TLI were also in the acceptable range. From the figure, it is evident that individual factors such as core task implementation and organizational foundation significantly influence benefits and impacts as well as external relations. Similarly, organizational resources positively impacted evaluation capacity outcomes. In contrast, organizational capacity had no significant influence on either benefits and impacts or external relations.

Table 6.

Indices of Fit.

Model	χ²	df	χ² / df	RMSEA	CFI	TLI
Step 1: CFA results
CFA#1: Individual factors	37.520	13	2.886	0.079	0.876	0.949
CFA#2: Organizational resources	113.091	35	3.231	0.086	0.972	0.956
CFA#3: Organizational capacities	82.144	38	2.162	0.062	0.975	0.964
CFA#4: Evaluation outcomes	44.589	31	1.438	0.038	0.991	0.986
Step 2:
Structural model	113.356	26	4.356	0.106	0.916	0.849

Source: Survey data

Figure 1.

Source: The authors.

5. Conclusion

Our results show that the OCA tool used here can be accepted as a critical instrument for the evaluation of organizational capacities. The research aim was fulfilled as all the proposed objectives were successfully met. The application of this new not-so-used assessment tool was found to be adept for testing capacity in hospitals. The gaps in capabilities were identified, and their associations with each other were pointed to overcome any forthcoming issues. Our study also validated the questionnaire and found it to be extremely reliable in nature. Core task implementation through development interventions lead to the long term benefit of the organization. Organisation learning and performance improvement will be developed through feedback on monitoring and evaluation of the core tasks. Organisation strategy and development is validated by the Core task implementation programmes. Furthermore, organisations can build alliances across segments to unravel development problems. To the best of our knowledge, this is the first study evaluating and validating any capacity assessment tool especially with respect to hospitals. Thus, this study can be considered as a pioneering work that establishes the authenticity of the scale. Moreover, it also suggests that improving organizational capacities require an integrated introspection of many factors apart from resources. Theoretically, a model demonstrating the supposed relationships between the variables could be successfully developed.

6. Limitations and Recommendations for Future Research

This study was restricted due to certain limitations common to empirical research. The number of hospitals spread across India is quite large; therefore, the sample size can be an issue. Moreover, not all the states were covered and only one representative from each hospital was considered which can be a source of bias. In addition, the sample population belonged to group with majority at the middle-level managerial positions. The perspective might change in the uppermost brass. Our questionnaire did not take into account governance and sustainability into picture. Our study shows a huge scope for future studies. This study only validates the capacity assessment tool; however, it needs to be measured with varied types of work personnel within the healthcare sector as there is a huge diversity in the work force of this area. Organisations with diverse workforce pose many challenges and the study using Organisational Capacity Assessment tools in such a scenario may yield noteworthy results. Even though there are some limitations in our study, we highly recommend the use of the tool in different areas to have a comparative opinion on the choice of tool selection. There can be differences in identifying gaps in capacity building between industries as each area works in a different manner. This tool can channelize the right number of resources and capabilities hopefully in the right direction. This can also form the basis for qualitative analysis so that the actual problem gets identified and fixed. In addition, changes in capacities due to functional or operational alterations within hospitals such as size, types of hospitals, and the services rendered by the hospitals can be considered in further studies.

Footnotes

Declaration of Conflicting Interests

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

Notes

ORCID iDs

Raghavendra A. N.

Adarsha K.

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