Identifying and prioritizing the key performance indicators for hospital management dashboard at a national level: Viewpoint of hospital managers

Abstract

Participation of main users in identifying key performance indicators (KPIs) for management dashboards contributes to their success. The aim of this study was to identify and prioritize the KPIs of hospital management dashboards from the viewpoint of hospital managers. This study was conducted on managers of public hospitals at a national level in Iran in 2020. Data were collected using a self-administrated questionnaire. The KPIs were classified into five categories, namely financial, operational, human resources, safety and quality of care, services provided to patients. A total of 234 hospital managers participated in this study. Totally, 25 KPIs were determined for the hospital management dashboard, including the patient falls rate, waiting time for patients in the emergency department, patient satisfaction, total hospital revenue, financial balance, bed occupancy rate, patients’ discharge with own agreement, average length of stay, and personnel satisfaction. For designing hospital management dashboards, the domains of services provided to patients, safety and quality of care, financial resources, human resources, and operational are important from the hospital managers’ viewpoint, respectively. The results of this study can be helpful for developers of business intelligence tools, such as hospital management dashboards, to visualize the most important indicators for managers.

Keywords

business intelligence dashboard hospital leadership hospital management key performance indicator

Backgrounds

Managers need reports for monitoring of their organization, better management of resources, and informed decision-making.^1–3 Decision-making is one of the most important duties of leaders and managers that needs to be based on information and evidence about the organization’s activities.^2,4 Poor decisions can lead to loss of resources and even threaten the organization’s survival.² Today, health managers are faced with a large amount of data from all parts of their organizations. This needs to be understood, interpreted, and responded to in a timely manner. Tools and aids that summarize and present current information are essential for managers too.^4,5

Business intelligence (BI) is a type of technology, tools, and methods developed to retrieve, analyze, and convert large amounts of data into visual information for business purposes.^6,7 BI in healthcare contains an integrated set of health informatics tools that allow users to convert data into meaningful information.⁸ BI tools can improve decision-making processes within an organization. An effective BI tool should present actionable information in alignment with organizational strategic plan of health institutions, such as hospitals.^8,9

Dashboards can display key performance indicators (KPIs) in various formats such as tables, charts, graphs, or even augmented reality and virtual reality.¹⁰ Management dashboards are one of the most important BI tools that can be used by managers in evidence-based decision-making.¹¹ Dashboards are computer interfaces that summarize the key information of an organization for managers.^12,13 These tools help measure the quality of services provided, manage time, resources and expenses of the organization, and monitor and control the organization’s performance.^11,14–16

Hospitals are increasingly complex institutions whose managers face challenges on a day-to-day basis. Besides concerns about patient safety and quality of healthcare services, hospital managers try to monitor various resources of the institution, including financial, physical, and human resources.¹⁷ Management dashboards can help improve quality of care, patient outcomes, efficiency, effectiveness, and utilization of hospital resources.^11,18–21

One of the most important points to consider in the development of information systems is utilizing end-users’ opinions and their real requirements in the design phase. This is a type of participatory design methodology that is derived from participatory action research.²² This method helps users have a better understanding of the target system, consider their information needs, and after implementation they use it easily and therefore have greater satisfaction.^23–25 On the other hand, if the design of an information system does not address the end-users’ opinions, the extent of the users’ acceptance and satisfaction may decrease.²³ Reduced users’ acceptance and satisfaction may lead to reduced benefits, fail implementation of high-cost information systems, and drive to acquisition of an alternative solution.²⁴ Therefore, developing management dashboards requires considering the managers’ viewpoints in the design phase.¹³ Moreover, the successful implementation of dashboards requires identifying and prioritizing KPIs as one of the most essential steps in this phase.^11,26,27

Data visualization is an essential technique in building dashboards. Managers are able to visualize KPIs on the management dashboards, generate specific and customized reports, find required information quickly, compare results appropriately, and use drill down capability to access more detailed information.²⁸ Also, these functionalities help to present a visual view of the overall business performance, provide performance feedback, reduce cognitive burden of managers, and improve cognitive data processing.^29,30

Various clinical dashboards have so far been developed in healthcare and implemented in different departments such as pathology, radiology, intensive care unit, nursing, and emergency care.^{12,27,31–35} These studies have shown that dashboards have been able to improve the quality of nursing care, increase efficiency, accelerate decision-making, reduce workload, and decrease clinical errors. To the best of our knowledge, no studies have yet been conducted on the design of dashboards specifically for hospital management. This study was aimed to determine and prioritize KPIs from the viewpoint of hospital managers to use in hospital management dashboards.

Methods

Study design and setting

This analytical study was conducted in 2020. The study participants were the managers of public hospitals in Iran. We surveyed the participants in the capacity building program held by the Ministry of Health and Medical Education of Iran program. This survey was a part of this educational program, and all the participants should have participated in this study.

Data collection

Data were collected by a questionnaire designed using the indicators extracted from scientific literature^{12,32,34–46} and the current reports and accreditation documents of Iranian hospitals.^47,48 Then, in two focus group sessions with the participation of five specialists in health information management (n = 3), medical informatics (n = 1), and healthcare service management (n = 1), the indicators were finalized and classified into five domains. The KPIs that were approved by at least three specialists were included in the questionnaire. The questionnaire consisted of two main parts. The first part contained demographic information about the hospital manager and the relevant hospital, i.e. gender, age, education, field of education, type of education (clinical, non-clinical), work experience as hospital manager, and type of hospital (general, specialized). The second part included 51 KPIs categorized in five domains i.e. financial resources (10 indicators included total hospital revenue, hospital financial balance, insurance claims), operational (22 indicators, e.g. bed occupancy ratio by wards, mean length of stay, patients discharge with own agreement), human resources (six indicators, e.g. personnel satisfaction, number of personnel, and workforce planning), safety and quality of care (10 indicators included patient fall rate, mean waiting time in the emergency department, successful and unsuccessful cardiopulmonary resuscitation (CPR) rates), and services provided to patients (three indicators, i.e. hospitalized and emergency patients’ satisfaction and patients’ complaints). The importance of the KPIs included in the questionnaire was scored based on a 10-point Likert scale, where one represented the lowest and 10 the highest importance. In addition to the 10 previous choices, a “Not Applicable” choice was also considered in the case of inapplicable KPIs for hospital management dashboard (Attachment 1). The validity of the questionnaire was verified by three health information management specialists, three health service management specialists, and two medical informatics specialists.

In order to collect the data, one of the researchers attended the capacity building program held by the Ministry of Health and Medical Education of Iran, in collaboration with the World Health Organization (WHO), in 10 major medical sciences universities (i.e. Tehran, Iran, Mashhad, Isfahan, Tabriz, Shiraz, Kerman, Ahvaz, Mazandaran, and Kermanshah) for the managers of public Iranian hospitals.⁴⁹ After explaining the study objectives and obtaining the hospital managers’ consent, the researcher distributed the questionnaires.

Statistical analysis

In order to determine the priority of the five domains in hospital management dashboard, the mean total score of individual indicators and the mean total score of each domain were calculated and sorted. Participants’ views on prioritizing the KPIs were classified in five categories, namely first-priority (mean 8 ≤ 10), second-priority (mean 6 ≤ 8), third-priority (mean 4 ≤ 6), fourth-priority (mean 2 ≤ 4), and fifth-priority (mean 0 ≤ 2). Moreover, the KPIs from the open-ended questions emphasized by more than two participants were included.

Data were analyzed in SPSS 22 (IBM SPSS Statistics, IBM Corporation, Armonk, NY, USA). After checking the normality of data, the Mann Whitney U test was used to examine the difference between the mean total score of each domain and the managers’ gender, domain of study (i.e. clinical and non-clinical), and type of hospital (i.e. general and specialized). The Kruskal-Wallis test was also used to examine the difference between the mean total score of each domain and education level (BSc, MSc, MD, and PhD), field of study (medicine, nursing, health sciences and nutrition, para-medical, HIM/HCM/HM, accounting and management, and other), and hospital information system (HIS) companies (A, B, C, D, E, F, G, H, J, K, and others). As well as, to examine the relationship between mean total score of each domain and age and work experience, the Spearman test was used.

Characteristics of the participants

The questionnaire was distributed to managers with bachelors, masters, professional doctorate, and Ph.D. degrees in fields related to management, hospital management, and health sciences. The managers’ domain of study was divided into two main categories: clinical (medicine and nursing) and non-clinical (other disciplines related to health sciences and non-medical fields).

Out of 242 participants in the program, we received 234 full completed questionnaires (incomplete questionnaire: 8). The questionnaires were collected by one of the researchers after completion. The mean age and work experience of the participants as hospital manager were 43.0 ± 7.08 and 5.36 ± 5.38 years, respectively. A total of 87% (n = 203) of the participants were male, 56% (n = 130) had non-clinical education, 44% (n = 102) had a bachelor’s degree, and 78.6% (n = 184) worked in general hospitals (Table 1).

Table 1.

The characteristics of the participants.

Characteristic		Frequency (%)
Gender	Female	28 (12)
	Male	203 (86.8)
	Missing	3 (1.3)
Education	Bachelor's degree	102 (43.6)
	Master’s degree	96 (41)
	Professional doctorate	26 (11.1)
	Ph.D	5 (2.1)
	Missing	5 (2.1)
Type of education	Clinical	95 (41)
	Non-clinical	130 (56)
	Missing	9 (3)
Type of hospital	General	184 (79)
	Specialized	45 (19)
	Missing	5 (2)

Results

Prioritizing the subject domains of the indicators

Figure 1 shows the mean score of each domain based on the total score of its indicators and based on the type of hospitals. From the viewpoint of the hospital managers, the priority of the domains (from most to least important) was as follows: services provided to patients (mean = 8.62 ± 2.12), safety and quality of care (8.35 ± 1.34), financial resources (8.3 ± 1.23), human resources (7.91 ± 1.44) and operational (7.24 ± 1.42).

Figure 1.

The mean score of the domains related to the hospital management dashboard.

As shown in Table 2, the mean total score of each domain in female managers were higher than males, but this difference was not statistically significant (p > .1). Managers with various education level had not significant difference in the mean total score of each domain (p > .17). Also, the mean total score of each domain in managers with non-clinical domain were higher than clinical managers (p > .09), but only the mean total score of financial domain was significantly different in clinical and non-clinical managers (p = .01). Only the mean total score of operational domain in general hospital managers was significantly higher than those who manage specialized hospitals (p = .03).

Table 2.

The mean total score of each domain based on characteristics of the participants.

Domain		Financial resources		Operational		Human resources		Safety and quality of care		Services provided to patients	p-value
Demographic information		Mean	p-value	Mean	p-value	Mean	p-value	Mean	p-value	Mean	p-value
Gender	Female	8.55	p = .1	7.3	p = .45	8.14	p = .38	8.53	p = .33	8.93	p = .11
Gender	Male	8.27		7.25		7.89		8.33		8.63
Education	Bachelor's degree	8.3	p = .71	7.15	p = .32	7.89	p = .17	8.19	p = .79	8.43	p = .28
	Master’s degree	8.37		7.46		8.14		8.52		8.95
	Professional doctorate (MD)	8.13		7.02		7.38		8.38		8.45
	Ph.D	8.58		7.02		8.07		8.58		9.53
Type of education	Clinical	8.14	p = .06	6.97	p = .04	7.74	p = .17	8.19	p = .11	8.53	p = .14
Type of education	Non-clinical	8.44		7.53		8.04		8.51		8.72
Filed	Medicine	7.98		6.79	p = .01	7.33	p = .33	8.22	p = .52	8.38
	Nursing	8.16		6.98		7.9		8.12		8.57
	Health sciences and nutrition	8.84		7.81		8.34		8.51		8.54
	Para-medical	8.53	p = .09	7.23	p = .03	7.87	p = .59	8.17	p = .78	8.18	p = .66
	HIM/HCM/HM	8.63		7.87		8.08		8.59		9.3
	Accounting and management	8.3		7.32		8.11		8.65		8.53
	Other	8		6.95		7.87		8.36		8.4
Type of hospital	General	8.26	p = .41	7.36		7.86		8.35		8.63	p = .32
Type of hospital	Specialized	8.39		6.67		8.09		8.31		8.54
HIS company	A	8.32		7.43		8.33		8.41		9.19
	B	7.95		7.17		7.74		8.4		8.56
	C	8.55		7.63		8.29		8.74		8.6
	D	8.47		7.24		8.32		8.38		9.02
	E	8.98		6.91		7.38		7.58		8.91
	F	9.35	p = .008	7.94	p = .62	8.95	p = .07	9.13	p = .08	9.91	p = .046
	G	8.23		7.33		7.82		7.88		8.28
	H	8.07		8.53		7.34		8.55		7.02
	J	8.53		7.28		7.34		8.55		7.02
	K	9.02		8.02		8.52		8.52		8.42
	Other	8.19		6.99		7.8		8.22		8.52
Age		(r = 0.017, p = .8)		(r = −0.12, p = 0.86)		(r = 0.45, p = 0.51)		(r = 0.03, p = 0.68)		(r = 0.049, p = 0.47)
Work experience		(r = −0.06, p = 0.36)		(r = −0.035, p = 0.59)		(r = −0.024, p = .72)		(r = 0.06, p = 0.35)		(r = −0.16, p = 0.81)

The Kruskal-Wallis test showed managers with various educational fields had not significant difference in the mean total score of financial resources, human resources, safety and quality of care, and services provided to patients' domains (p > .05). However, the mean total score of operational domain had significant difference in the managers with various educational fields. The mean total score of operational domain in managers with background in health information management (HIM), health care management (HCM), and hospital management (HM) was significantly higher than other hospital managers (p = .01). The managers that used “F” HIS have the higher mean total score of each domain (except in operational domain). These differences were significant in financial resources domain (p < .046). The Spearman test showed no significant difference in the managers with different age and work experience and the mean total score of each domain (p > .05).

The selected key performance indicators

Table 3 shows the prioritized KPIs of all domains totally and by hospital type. The findings showed, out of a total of 51 indicators, 23, 26, and 25 KPIs in general, specialized, and total hospitals have the high priority to include in the management dashboard. Other KPIs had the next priorities.

Table 3.

The selected KPIs for hospital management dashboard.

Financial resources	KPI	Mean	Priority	KPI	Mean	Priority	KPI	Mean	Priority
Domains and KPIs	General hospitals			Specialized hospitals			Total hospitals
F1-revenue from outpatient admissions	F2	9.29	First priority	F2	9.56	First priority	F2	9.36	First priority
F2-total hospital revenue	F10	9.05		F10	9.18		F10	9.09
F3-hospital global budgeting (divided by seasons)	F8	8.85		F8	9.02		F8	8.89
F4-Hospital debt (divided by creditors)	F5	8.57		F3	8.64		F5	8.55
F5-unpaid claims from insurance companies	F4	8.53		F5	8.4		F4	8.53
F6-paid claims from insurance companies	F3	8.29		F6	8.38		F3	8.39
F7-discount rate applied to patients	F6	8.3		F4	8.36		F6	8.33
F8-hospital deductions (divided by insurance)	F1	7.43	Second priority	F1	7.91	Second priority	F1	7.54	Second priority
F9-hospital fund balance	F7	7.23		F7	7.31		F7	7.28
F10-hospital financial balance	F9	7.09		F9	7.13		F9	7.1
Operational	General hospitals			Specialized hospitals			Total hospitals
O1-average length of stay	O2	8.98	First priority	O2	8.69	First priority	O2	8.93	First priority
O2-bed occupancy ratio by wards	O21	8.27		O1	8.27		O22	8.07
O3-number of outpatients admitted	O18	8.07		O4	8		O1	8.01
O4-number of hospitalized patients	O22	8.05		O22	7.98	Second priority	O18	8
O5-number of discharged patients	O1	7.93	Second priority	O18	7.64		O4	7.94	Second priority
O6-number of elective surgeries	O4	7.9		O10	7.64		O10	7.83
O7-number of outpatient surgeries	O10	7.88		O20	7.33		O8	7.67
O8-number of emergency surgeries	O8	7.88		O9	7.31		O20	7.67
O9-number of patients with a length of stay less than 24 h	O11	7.84		O3	7.29		O11	7.62
O10-number of patients with a length of stay in the emergency department less than 6 h	O20	7.77		O5	6.89		O21	7.62
O11-number of patients with a length of stay in the emergency department between six to 12 h	O6	7.73		O11	6.71		O6	7.54
O12-number of patients admitted through the emergency calls	O9	7.48		O8	6.67		O3	7.45
O13-number of patients admitted from other health care centers	O3	7.47		O6	6.64		O9	7.45
O14-number of patients which were referred to other health care centers temporarily	O17	7.36		O14	6.33		O5	7.24
O15-number of patients who were moved to other health care centers	O5	7.3		O15	6.07		O5	6.96
O16-coefficient for isolation bed occupancy	O5	7.15		O7	5.98	Third priority	O17	6.95
O17-coefficient for maternity bed occupancy	O15	7.02		O13	5.87		O15	6.87
O18-coefficient for emergency bed occupancy	O14	6.47		O12	5.67		O14	6.48
O19-coefficient for burn bed occupancy	O12	6.31		O16	5.58		O12	6.21
O20-coefficient for intensive care bed occupancy	O16	6.3		O17	5.27		O16	6.18
O21-number of natural and cesarean deliveries	O13	5.97	Third priority	O21	4.82		O13	5.99	Third priority
O22-Rate of patients discharge with own agreement	O19	4.86		O19	4.07		O19	4.79
Human resources	General hospitals			Specialized hospitals			Total hospitals
H1-number of physicians (by type of employment)	H6	8.76	First priority	H6	9.04	First priority	H6	8.83	First priority
H2-number of nurses (by type of employment)	H2	7.86	Second priority	H2	8.13		H2	7.93	Second priority
H3-number of personnel (by type of employment)	H4	7.77		H4	8.09		H4	7.84
H4-workforce planning in departments/units (by work shift)	H3	7.74		H3	8.02		H3	7.81
H5-personnel recruitment/separation rate during the year	H5	7.66		H5	7.82	Second priority	H5	7.71
H6-personnel satisfaction rate	H1	7.37		H1	7.42		H1	7.4
Safety and quality of care	General hospitals			Specialized hospitals			Total hospitals
Q1-mortality rate before and after 24 h	Q3	8.72	First priority	Q3	8.82	First priority	Q3	8.76	First priority
Q2-Re-hospitalization rate 15 days after the initial visit	Q5	8.7		Q8	8.62		Q5	8.67
Q3-patient fall rate	Q4	8.51		Q5	8.47		Q4	8.47
Q4-successful and unsuccessful CPR rate	Q6	8.42		Q4	8.36		Q8	8.44
Q5-mean waiting time in the emergency department	Q8	8.38		Q6	8.33		Q6	8.42
Q6-expensive drugs consumed	Q1	8.36		Q9	8.33		Q1	8.36
Q7-inventory of expensive drugs	Q10	8.29		Q1	8.29		Q10	8.16
Q8-commonly-used drugs consumed	Q7	8.1		Q2	8.16		Q7	8.11
Q9-inventory of commonly-used drugs	Q2	7.99	Second priority	Q7	8.04		Q9	8.08
Q10-prescription rate of important drug groups, such as antibiotics	Q9	7.99		Q10	7.64	Second priority	Q2	8.04
Services provided to patients	General hospitals			Specialized hospitals			Total hospitals
S1-Hospitalized patients’ satisfaction rate	S1	8.7	First priority	S1	8.62	First priority	S1	8.69	First priority
S2-emergency department patients’ satisfaction rate	S2	8.7		S2	8.62		S2	8.69
S3-patients’ complaints	S3	8.49		S3	8.38		S3	8.5
	General hospitals			Specialized hospitals			Total hospitals
Number of priorities	First priority: 23 KPIs			First priority: 26 KPIs			First priority: 25 KPIs
	Second priority: 26 KPIs			Second priority: 18 KPIs			Second priority: 24 KPIs
	Third priority: 2 KPIs			Third priority: 7 KPIs			Third priority: 2 KPIs

In total, the patient fall rate (mean = 8.76) was selected as the most important indicator in “safety and quality of care” domain. The patients’ satisfaction rate (mean = 8.69) was the most important KPI in “services provided to patients” domain. The total hospital revenue (mean = 9.36) had the highest score among the 10 KPIs in “financial resources” domain. According to the hospital managers, personnel satisfaction rate (mean = 8.83) was the most important indicator in “human resources” domain. The bed occupancy ratio by wards (mean = 8.93) was selected as the most important indicator in operational domain.

In response to the open-ended questions, the number of human resources by occupational groups, type of employment, cost of purchasing consumables and medical equipment (drug, tools, medical devices and equipment, prostheses, implants) by wards (in financial resources’ domain), patient satisfaction with hoteling services of hospital (in services provided to patients’ domain), rate of nosocomial infection by wards (in safety and quality of care domain), and the rate of sending para-clinical services to other centers; number of referrals of patients to specialized centers on the outside of the hospital by cause; number of canceled surgeries (in operational domain) were the most other suggested KPIs by hospital managers (Table 4).

Table 4.

The most other suggested KPIs based on open questions.

Domain name	KPI
Financial	The cost of purchasing consumables and medical equipment (drug, tools, medical devices and equipment, prostheses, implants, etc.) by wards (n = 10), income and deductions of the hospital by inpatient and outpatient wards; claims and payments of personnel by occupational groups; inventory of drugs and consumables tools in warehouse and stocks; cost of the purchasing, repairing and maintaining hospital facilities and medical equipment; income and expenses of the hospital by wards (n = 6), income, payments and debts to outsourced companies; cost of the treatment, drug and consumables tools per bed; costs of the energy and hoteling services of hospital (n = 3), maximum of the insurance payments for hospital services; debt to pharmaceutical and medical equipment companies (n = 2)
Operational	Rate of the sending para-clinical services to other centers; number of the referrals of patients to specialized centers in the outside of the hospital by its cause; number of the canceled surgeries (n = 3), number of the performed para-medical tests; number of the expensive para-clinical tests and services; average time of the surgeries based on the type of surgery; number of the patients referred to clinics and para-clinics (physiotherapy, medical imaging, laboratory, etc.) (n = 2)
Human resources	Number of the human resources by occupational groups, type of the employment, gender, and ward (n = 17), employee attendance; Ratio of human resources (by occupational groups) per bed (n = 5), personnel satisfaction; number of retired or near-retired personnel (n = 3)
Safety and quality of care	Rate of nosocomial infection by ward (n = 6), the rate of bed sores by ward (n = 4), average time of the first visit of the patient by the physician; Rate of hospital, medical and medication errors; number of requests for para-clinical tests by physicians; average time of patient care by the nurse after the physician's order (n = 3), Hospital mortality rate (n = 2)
Services provided to patients	Patient satisfaction with hoteling services of hospital (n = 10), patient satisfaction with personnel services (physician, nurse, paramedical, etc.) (n = 5), patients with para-clinical services; patient satisfaction and complaints with clinics care and appointments; patient satisfaction and complaints with delivered services by wards; patient satisfaction with hospital process (n = 4), patient leaving hospital with satisfaction (n = 2)

Discussion

Principal findings

Based on the results obtained, out of a total of 51 indicators examined in five domains, half of KPIs (25 KPIs) obtained the highest scores and were selected for hospital management dashboards. According to the managers of public Iranian hospitals and the mean scores obtained, the order of priority given to the five domains was as follows: services provided to patients, safety and quality of care, financial resources, human resources, and operational domain.

Comparisons with existing literature

Services provided to patients

In this domain, the patients’ complaints and satisfaction were the most important indicators for the hospital managers. Patients’ satisfaction is a very important indicator of the quality of services provided by hospitals.^50,51 Patients’ satisfaction assessment should be a top priority for healthcare managers and providers, as it can bring a good reputation for healthcare institutions, increase the number of customers, increase the profitability compared to competitors and is one of the most important factors contributing to a manager’s success.⁵² Mendonça et al.³⁹ described patients' satisfaction with the services provided as one of the six KPIs in pharmaceutical service management dashboards. Three other studies^38,40,41 also used indicators related to the patients' satisfaction as well as their complaints of the services provided as KPIs. In one systematic review study, Si et al. (2005) also suggested patients’ satisfaction and complaints as the most important KPIs.⁴¹

Safety and quality of care

In the domain of safety and quality of care, the patient fall rate and waiting time in the emergency department were the most important indicators for the hospital managers. Falling from the bed is one of the most serious threats to patient safety in hospitals,^53–55 which in many cases, results in patient injury, followed by an increase in the length of stay, the medical costs and the patient's complaint from the healthcare organization.^56–60 In a study by Pemberton et al.,³⁶ similarly patient fall rate was included in the dental services’ dashboard. Long waiting times for patients increase the likelihood of adverse outcomes for patients with critical conditions in the emergency department, as well as the decreased quality of care, leaving the hospital without receiving services and ultimately reduced patient satisfaction with the hospital.^61–69 Using this KPI in hospital dashboards was also proposed in two other studies.^37,38

Financial resources

In this study, indicators such as the financial balance of the hospital and total hospital revenue were found to be of great importance. As Latham quotes: “Cash is king, so cash flow is the lifeblood of the kingdom”.⁷⁰ Awareness about budget, revenue, expenses, and debts is an effective factor for managers’ decision-making.¹ Although financial performance is not a main indicator of the success of healthcare institutions, it is not possible to achieve the healthcare goals without considering financial aspects.⁷¹ Investigating financial indicators enables hospital managers to specify the financial trend of the hospital in a given period of time and even compare it with other hospitals.⁷¹ Hospital managers therefore need key financial indicators for monitoring their institution’s financial situation. Saharia⁴³ proposed the organization revenue, the accounts receivable from Medicare, and the organization debt as the three most important financial indicators. Levin⁴² also recommended profit, gross revenue, total expenditure and expenses received as KPIs in dental practice. Taylor⁴⁴ also proposed the net and gross revenue and the profit from patient admission as the most important KPIs in the financial domain and used them for designing a dashboard.

Human resources

Personnel satisfaction was the most important KPI in the human resource domain for the hospital managers. The personnel satisfaction affects their loyalty to the organization, prevents absenteeism, and saves costs.⁷² Another reason for the importance of personnel’s satisfaction for managers may be competition among hospitals for recruiting and keeping qualified personnel. Personnel dissatisfaction can make them leave the organization. Recruiting and training qualified personnel for hospitals may cost a lot of time and money. Moreover, new and inexperienced personnel may not be able to provide patients with high-quality services,⁷³ which may lead to the patients’ dissatisfaction and no return to the hospital. Hospital managers know that the personnel’s satisfaction impacts patients’ satisfaction with the services received.⁷⁴ In line with these results, in two other studies,^38,41 personnel satisfaction and workflow were used as indicators for evaluating the performance of healthcare organizations.

Operational domain

Based on the results of this study, the bed occupancy ratio by wards, patients’ discharge with own agreement, and average length of stay were some of the operational indicators that were highly important to the hospital managers. The bed occupancy ratio by wards and length of stay are some main criteria used for evaluating the efficiency and productivity of hospitals. The bed occupancy ratio by wards helps decide whether to increase the number of beds in the hospital and indicates the appropriate use of hospital resources and facilities.^75,76 The length of stay is associated with many factors, such as the chance of repeated infections, readmission rate, medical expense burdens on patients and their families, and also patient satisfaction.^77–80 Regarding the limited resources in healthcare, knowing about the bed occupancy ratio and average length of stay helps hospital managers' better plan for and manage their hospital resources. In line with the present findings, Martinez et al.⁴⁶ also found that indicators including the length of stay, bed occupancy rate and hospital discharge as well as the number of patients in the emergency department were the most important indicators. Elliot et al.³⁷ proposed the hospital bed occupancy rate, the emergency department bed occupancy rate, the length of stay and the rate of patients’ discharge contrary to the recommendations (i.e. with personal consent) as the major KPIs for pediatric hospitals.

According to this study, the managers of general hospitals prioritized operational KPIs significantly more than managers of specialized ones. In a general hospital, most of the treatment procedures for almost all types of diseases may be performed, while a specialized hospital specializes in the treatment of a particular or a group of related diseases. Thus, it seems rational that some operational KPIs such as bed occupancy ratio by wards, coefficient for emergency bed occupancy, and rate of patients discharge with own agreement be important for general hospital managers.

Strengths and limitations

This study used a participatory design method to identify and prioritize the KPIs for hospital management dashboard. According to this methodology, if the users and stakeholders of management and clinical dashboards are involved in determining the KPIs, more relevant and reliable indicators can be obtained.¹⁸ Therefore, since hospital managers are the main users of hospitals’ management dashboards, this study investigated the views of a proper sample of managers in public Iranian hospitals. To the best of the researchers’ knowledge, no studies have yet been conducted to determine the KPIs of hospital management dashboards.

This study used the views of experts in this field and the participation of hospital managers for developing hospital management dashboards. Although this study presents evidence of the selected KPIs based on the viewpoint of hospital managers, the results should be cautiously interpreted due to its limitations. Firstly, there are many evidences^81,82 about the importance of medical equipment in the performance and the costs of healthcare institutions. Ignoring the KPIs related to HITs was one of the limitations of our study. Secondly, the results of analyzing open-ended questions showed some of the important KPIs might be ignored by the researchers. Thirdly, the identified KPIs may not have been based on the specific conditions of certain other hospitals or they may have less use or importance in other settings, such as private, military, and charity (non-profit) hospitals.

Generally, this study suggests that the hospital managers consider the impact of management dashboards in decision-making and the necessity of identifying essential KPIs. This study carried out with the participation of the managers of Iranian hospitals at a national level, so the generalization of the results to hospitals in countries with different health systems should therefore be pursued with caution. The prioritized KPIs in this study may be helpful for future studies to identify other required KPIs of management dashboards in the health care domain.

Future studies are recommended to investigate and compare KPIs with consideration for specific hospital variables, such as the type and specialties available in the hospital as well as the healthcare system in place or the geographical region. Given the time, financial, and executive limitations in the design, implementation, and use of hospital management dashboards in this study, the impact of the determined indicators on the hospital business was not investigated. The researchers recommend that, after the implementation of the management dashboards, further studies investigate the impact of their use on the outcomes, processes, and management of resources in hospitals.

It is essential to use management dashboards in hospitals to avoid confusion in decision-making. The indicators determined in this study can help designers and developers of business intelligence tools, such as hospital management dashboards, to visualize the most important needs of managers. The results of this study demonstrate the common and general needs as a primary step and provide a basis for their complementation in future studies. The health managers can use these indicators to formulate strategic and operational plans for relevant organizations.

Conclusion

The results of this study showed that awareness about the services provided to patients and safety and quality of care is more important than any other domain for hospital managers. The KPIs identified in this study can be used as a basis for the development of hospital management dashboards. Hospital managers and administrators can use these indicators to monitor the status and performance of their organization in time and have a better control over their institution by adopting plans and making decisions.

Footnotes

Acknowledgements

This work was supported by Health Information Management Research Center, Kashan University of Medical Sciences (97119). The authors thank the hospitals’ managers participated in this study.

Author contributions

E.N, R.F, M.S, R.K and R.A contributed to the conception and design of the study, acquisition and interpretation of the data, and drafting the paper. E.N and R.A was primarily responsible for the statistical analysis of the data. All 5 authors read and approved the final version of the article submitted.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Ethical statement

ORCID iDs

Ehsan Nabovati

Reza Abbasi

Data Availability Statement

The data generated and analyzed during this study are available from the corresponding author on reasonable request.

References

Kidholm

Ølholm

Birk-Olsen

, et al. Hospital managers’ need for information in decision-making–An interview study in nine European countries. Health Pol 2015; 119(11): 1424–1432.

Baba

HakemZadeh

. Toward a theory of evidence based decision making. Manag Decis 2012; 50(5): 832–867.

Sampurno

Cally

Opie

, et al. Establishing a global quality of care benchmark report. Health Inf J 2021; 27(2): 14604582211015704.

Pfeffer

Sutton

. Hard facts, dangerous half-truths, and total nonsense: profiting from evidence-based management. Boston, MA: Harvard Business Press, 2006.

Hardee

. Magnet hospitals and benchmarking: the Perioperative dashboard. SSM 2003; 9(3): 13.

Karami

Fatehi

Torabi

, et al. Enhance hospital performance from intellectual capital to business intelligence. Radiol Manag 2013; 35(6): 30–35.

Mettler

Vimarlund

. Understanding business intelligence in the context of healthcare. Health Inf J 2009; 15(3): 254–264.

Ferranti

Langman

Tanaka

, et al. Bridging the gap: leveraging business intelligence tools in support of patient safety and financial effectiveness. J Am Med Inf Assoc 2010; 17(2): 136–143.

MEaPI Community . Executive Dashboard development guide: healthcare information and management systems society. Chicago, IL: HIMSS, 2009.

10.

Marreiros

Craamer

Garitano

, et al. From KPI dashboards to advanced visualization. In: The MANTIS book: cyber physical system based proactive collaborative maintenance, 2019, p. 239.

11.

Azadmanjir

Torabi

Safdari

, et al. A map for clinical laboratories management indicators in the intelligent dashboard. Acta Inf Med 2015; 23(4): 210.

12.

Morgan

Branstetter

Lionetti

, et al. The radiology digital dashboard: effects on report turnaround time. J Digit Imag 2008; 21(1): 50–58.

13.

Pauwels

Ambler

Clark

, et al.

Dashboards as a service: why, what, how, and what research is needed?

J Serv Res 2009; 12(2): 175–189.

14.

Dowding

Randell

Gardner

, et al. Dashboards for improving patient care: review of the literature. Int J Med Inf 2015; 84(2): 87–100.

15.

Velcu

(ed) Dashboards in performance management: the foundations and research opportunities for their effective use. In: Proceedings of the 5th International Conference Accounting and Management Information Systems: AMIS, Bucharest, Romania, June 16–18, May 2010: The Bucharest Academy of Economic Studies, vol. 2010.

16.

D’Souza

Rao

Muthana

, et al. ROTA: a system for automated scheduling of nursing duties in a tertiary teaching hospital in south India. Health Inf J 2021; 27(2): 14604582211001426.

17.

Parand

Dopson

Renz

, et al. The role of hospital managers in quality and patient safety: a systematic review. BMJ Open 2014; 4(9): e005055.

18.

Weggelaar-Jansen

AMJ

Broekharst

de Bruijne

. Developing a hospital-wide quality and safety dashboard: a qualitative research study. BMJ Qual Saf 2018; 27(12): 1000–1007.

19.

Nagy

Konewko

Warnock

, et al. Novel, web-based, information-exploration approach for improving operating room logistics and system processes. Surg Innovat 2008; 15(1): 7–16.

20.

Dunn

Sprague

Grimshaw

, et al. A mixed methods evaluation of the maternal-newborn dashboard in Ontario: dashboard attributes, contextual factors, and facilitators and barriers to use: a study protocol. Implement Sci 2015; 11(1): 59.

21.

Gold

Karia

Link

, et al. Implementation and early adaptation of patient-reported outcome measures into an electronic health record: a technical report. Health Inf J 2020; 26(1): 129–140.

22.

Spinuzzi

. The methodology of participatory design. Tech Commun 2005; 52(2): 163–174.

23.

Marcus

. User interface design’s return on investment: examples and statistics. In: Cost-justifying usability. Amsterdam: Elsevier, 2005, p. 17–39.

24.

Khajouei

Peek

Wierenga

, et al. Effect of predefined order sets and usability problems on efficiency of computerized medication ordering. Int J Med Inf 2010; 79(10): 690–698.

25.

Khajouei

Abbasi

. Evaluating nurses’ satisfaction with two nursing information systems. Computers, informatics, nursing: CIN 2017; 35(6): 307–314.

26.

Jinpon

Jaroensutasinee

. Business intelligence and its applications in the public healthcare system. Walailak J Sci Technol 2011; 8(2): 97–110.

27.

Prevedello

Andriole

Hanson

, et al. Business intelligence tools for radiology: creating a prototype model using open-source tools. J Digit Imag 2010; 23(2): 133–141.

28.

Haque

Urquhart

Berg

, et al. Using business intelligence to analyze and share health system infrastructure data in a rural health authority. JMIR medical informatics 2014; 2(2): e3590.

29.

Khairat

Dukkipati

Lauria

, et al. The impact of visualization dashboards on quality of care and clinician satisfaction: integrative literature review. JMIR human factors 2018; 5(2): e22.

30.

Salehi

Moradi

Setodefar

Habibi

. Investigating the role of clinical dashboards in improving nursing care: A systematic review. Frontiers in Health Informatics. 2021 Aug; 2510(1): 87.

31.

Zimmermann

Moriconi

(eds) Implementing the clinical dashboard at VCUHS. NI 2012. In: Proceedings of the 11th international congress on nursing informatics. Washington, DC: American Medical Informatics Association, 2012.

32.

Egan

. Clinical dashboards: impact on workflow, care quality, and patient safety. Crit Care Nurs Q 2006; 29(4): 354–361.

33.

Halwani

Banerjee

, et al. A real-time dashboard for managing pathology processes. J Pathol Inf 2016; 7(1): 24.

34.

Stone-Griffith

Englebright

Cheung

, et al. Data-driven process and operational improvement in the emergency department: the ED dashboard and reporting application. J Healthc Manag 2012; 57(3): 167–181.

35.

Tan

Y-M

Hii

Chan

, et al. An electronic dashboard to improve nursing care. Stud Health Technol Inf 2013; 192: 190–194.

36.

Pemberton

Ashley

Shaw

, et al. Measuring patient safety in a UK dental hospital: development of a dental clinical effectiveness dashboard. Br Dent J 2014; 217(7): 375.

37.

Elliot

Mcullagh

Brydon

, et al. Developing key performance indicators for a tertiary children’s hospital network. Aust Health Rev 2018; 42(5): 491–500.

38.

Itoh

. Performance indicators: healthcare professionals’ views. Int J Health Care Qual Assur 2016; 29(7): 801–815.

39.

de Mendonça Lima

Aguiar

Storpirtis

. Development and validation of key performance indicators for medication management services provided for outpatients. Res Soc Adm Pharm 2018; 15(9): 1080–1087.

40.

Pongpagatip

Pradubwong

Chowchuen

. Development and monitoring the key performent index of the quality of care for patients with cleft/palate in Tawanchai center and out-patient surgical room srinagarind hospital Thailand. J Med Assoc Thai 2015; 98(7): S54–S59.

41.

S-L

You

X-Y

Liu

H-C

, et al. Identifying key performance indicators for holistic hospital management with a modified DEMATEL approach. Int J Environ Res Publ Health 2017; 14(8): 934.

42.

Levin

. The importance of key performance indicators. JADA (J Am Dent Assoc) (1939). 2012; 143(11): 1248.

43.

Saharia

. 5 KPIs that require revenue cycle managers’ attention. Healthc Financ Manag : Journal of the Healthcare Financial Management Association 2014; 68(9): 80–84.

44.

Using key performance indicators to do more with less in your practice. In: Seminars in hearing. Stuttgart: Thieme Medical Publishers, 2016.

45.

Wahba

Shah

Hill

, et al. A Novel early pregnancy assessment unit/gynaecology assessment unit dashboard an experience from a UK district general hospital. J Obstet Gynaecol 2015; 35(7): 703–706.

46.

Martinez

Kane

Jalalpour

, et al. An electronic dashboard to monitor patient flow at the Johns hopkins hospital: communication of key performance indicators using the donabedian model. J Med Syst 2018; 42(8): 133.

47.

A comprehensive guideline of the national accreditation of Iranian hospitals. Tabriz, Iran: Tabriz University of Medical Sciences, 2018. https://madanihosp.tbzmed.ac.ir/?pageid=107

48.

Accreditation indicators of Iran’s hospitals in 2018. Tehran, Iran: Tehran University of Medical Sciences, 2018. http://www.old.rhc.ac.ir/Files/Download/pdf/ff.pdf

49.

Doshmangir

Takian

. Capacity building to improve hospital managers’ performance in west asia. Int J Health Pol Manag 2019; 8(5): 319–320.

50.

Xesfingi

Vozikis

. Patient satisfaction with the healthcare system: assessing the impact of socio-economic and healthcare provision factors. BMC Health Serv Res 2016; 16(1): 94.

51.

Allahham

. Determinants of customer satisfaction in healthcare services. International Journal of Business and Management Invention 2013; 2(12): 59–64.

52.

Stillwagon

, 14 Key Performance Indicators (KPIs) to Measure Customer Service. Small Business Trends. Mar 5, 2015. Available from: https://smallbiztrends.com/2015/03/how-to-measure-customer-service.html

53.

Staggs

Mion

Shorr

. Consistent differences in medical unit fall rates: implications for research and practice. J Am Geriatr Soc 2015; 63(5): 983–987.

54.

Cameron

Murray

Gillespie

, et al. Interventions for preventing falls in older people in nursing care facilities and hospitals. Cochrane Database Syst Rev 2010; 1(1): CD00546.

55.

Oliver

Healey

Haines

. Preventing falls and fall-related injuries in hospitals. Clin Geriatr Med 2010; 26(4): 645–692.

56.

Rubenstein

Josephson

. The epidemiology of falls and syncope. Clin Geriatr Med 2002; 18(2): 141–158.

57.

Brand

Sundararajan

. A 10-year cohort study of the burden and risk of in-hospital falls and fractures using routinely collected hospital data. BMJ Qual Saf 2010; 19(6): e51.

58.

Wong

Recktenwald

Jones

, et al. The cost of serious fall-related injuries at three Midwestern hospitals. Joint Comm J Qual Patient Saf 2011; 37(2): 81–87.

59.

Rosenthal

. Nonpayment for performance? Medicare's new reimbursement rule. N Engl J Med 2007; 357(16): 1573–1575.

60.

Oliver

Killick

Even

, et al. Do falls and falls-injuries in hospital indicate negligent care—and how big is the risk? A retrospective analysis of the NHS Litigation Authority Database of clinical negligence claims, resulting from falls in hospitals in England 1995 to 2006. BMJ Qual Saf 2008; 17(6): 431–436.

61.

Ackroyd-stolarz

Guernsey

Mackinnon

, et al. Is a prolonged stay in the emergency department associated with adverse events in older patients?: 158. Acad Emerg Med 2008; 15(5): S67.

62.

Diercks

Roe

Chen

, et al. Prolonged emergency department stays of non–ST-segment-elevation myocardial infarction patients are associated with worse adherence to the American College of Cardiology/American Heart Association guidelines for management and increased adverse events. Ann Emerg Med 2007; 50(5): 489–496.

63.

Liew

Kennedy

. Emergency department length of stay independently predicts excess inpatient length of stay. Med J Aust 2003; 179(10): 524–526.

64.

Pines

Hollander

Localio

, et al. The association between emergency department crowding and hospital performance on antibiotic timing for pneumonia and percutaneous intervention for myocardial infarction. Acad Emerg Med 2006; 13(8): 873–878.

65.

Sprivulis

Da Silva

Jacobs

, et al. The association between hospital overcrowding and mortality among patients admitted via Western Australian emergency departments. Med J Aust 2006; 184(5): 208–212.

66.

Bindman

Grumbach

Keane

, et al. Consequences of queuing for care at a public hospital emergency department. JAMA 1991; 266(8): 1091–1096.

67.

Miceli

Wolosin

. You’re “running late”—now what. Patient satisfaction, wait time and physician behavior. Orlando, FL: The World Organization of National Colleges, Academies, and Academic Associations of General Practitioners/Family Physicians, 2004.

68.

Spaite

Bartholomeaux

Guisto

, et al. Rapid process redesign in a university-based emergency department: decreasing waiting time intervals and improving patient satisfaction. Ann Emerg Med 2002; 39(2): 168–177.

69.

Bloom

Fendrick

. Waiting for care: queuing and resource allocation. Med Care 1987; 25: 131–139.

70.

Latham

. The healthcare CFO: squeezing more from IT. Health Manag Technol 2009; 30(1): 10–11.

71.

Suarez

Lesneski

Denison

. Making the case for using financial indicators in local public health agencies. Am J Publ Health 2011; 101(3): 419–425.

72.

Powell

. Conducting hospital employee satisfaction surveys. West Jefferson: Mountain States Group, 2001.

73.

Earp

JAL

French

Gilkey

. Patient advocacy for health care quality: strategies for achieving patient-centered care. Jones & Bartlett Publishers, 2008.

74.

Parmenter

. Key performance indicators for government and non profit agencies: implementing winning KPIs. John Wiley & Sons, 2012.

75.

Marahem

Seyedghodraty

Farzin

, et al. The importance of bed occupancy rate in evaluate the utilization of hospitals. Crescent Journal of Medical and Biological Sciences 2018; 5(4): 270–271.

76.

Varghese

. Bed occupancy rate. Med J Armed Forces India 2004; 60(3): 318.

77.

. Discussion on the method of shortening average length of stay. J Trad Chinese Med Manag 2014; 2: 295–296.

78.

Liu

Zhang

Guo

, et al. The correlation of hospital operational efficiency and average length of stay in China: a study based on provincial level data. J Biosci Med 2016; 4(12): 49.

79.

Tsai

Orav

Jha

. Patient satisfaction and quality of surgical care in US hospitals. Ann Surg 2015; 261(1): 2.

80.

Cropley

. The relationship-based care model: evaluation of the impact on patient satisfaction, length of stay, and readmission rates. J Nurs Adm 2012; 42(6): 333–339.

81.

Zamzam

Abdul Wahab

Azizan

, et al. A systematic review of medical equipment reliability assessment in improving the quality of healthcare services. Front Public Health 2021; 9(1426): 753951.

82.

Iadanza

Gonnelli

Satta

, et al. Evidence-based medical equipment management: a convenient implementation. Med Biol Eng Comput 2019; 57(10): 2215–2230.