Rates, levels, and determinants of electronic health record system adoption: A study of hospitals in Riyadh, Saudi Arabia

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Rates, levels, and determinants of electronic health record system adoption: A study of hospitals in Riyadh, Saudi Arabia Bakheet Aldosari ∗ Department of Health Informatics, King Saud Bin AbdulAziz University, Mail Code: 2350, PO Box 22490, Riyadh 11426, Saudi Arabia

a r t i c l e

i n f o

a b s t r a c t

Article history:

Objective: Outside a small number of OECD countries, little information exists regarding the

Received 28 February 2013

rates, levels, and determinants of hospital electronic health record (EHR) system adoption.

Received in revised form

This study examines EHR system adoption in Riyadh, Saudi Arabia.

1 January 2014

Materials and methods: Respondents from 22 hospitals were surveyed regarding the imple-

Accepted 10 January 2014

mentation, maintenance, and improvement phases of EHR system adoption. Thirty-seven items were graded on a three-point scale of preparedness/completion. Measured determi-

Keywords:

nants included hospital size, level of care, ownership, and EHR system development team

Electronic health records

composition.

Hospital information systems

Results: Eleven of the hospitals had implemented fully functioning EHR systems, eight had

Levels and determinants of EHR

systems in progress, and three had not adopted a system. Sixteen different systems were

system adoption

being used across the 19 adopting hospitals. Differential adoption levels were positively

Saudi Arabia

related to hospital size and negatively to the level of care (secondary versus tertiary). Hospital ownership (nonprofit versus private) and development team composition showed mixed effects depending on the particular adoption phase being considered. Discussion: Adoption rates compare favourably with those reported from other countries and other districts in Saudi Arabia, but wide variations exist among hospitals in the levels of adoption of individual items. General weaknesses in the implementation phase concern the legacy of paper data systems, including document scanning and data conversion; in the maintenance phase concern updating/maintaining software; and in the improvement phase concern the communication and exchange of health information. Conclusion: This study is the first to investigate the level and determinants of EHR system adoption for public, other nonprofit, and private hospitals in Saudi Arabia. Wide interhospital variations in adoption bear implications for policy-making and funding intervention. Identified areas of weakness require action to increase the degree of adoption and usefulness of EHR systems. © 2014 Elsevier Ireland Ltd. All rights reserved.

1.

Introduction and background

An electronic health record (EHR) is a centralized and longitudinal electronic record that holds patient health information

∗

such as patient demographics, progress notes, medications, vital signs, medical history, laboratory tests, and radiology reports [1]. EHRs report incidences of care across multiple healthcare personnel and organizations both within and between regions. EHRs support two main functions: the first

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i n t e r n a t i o n a l j o u r n a l o f m e d i c a l i n f o r m a t i c s 8 3 ( 2 0 1 4 ) 330–342

function includes patient care functions such as clinical reviews, decision support, and the provision of documentation, and the second is the administrative and financial functions such as statistical reports and quality measurement. The term “EHR system” describes the electronic organizational framework and infrastructure that allows EHRs to be stored, accessed, altered, and analyzed. EHR systems provide important benefits for healthcare, including positive effects on outcomes such as the efficiency of care, the effectiveness of care, the reduction of error rates, and the reduction of healthcare costs [2–8]. Such systems will be particularly important in helping relieve overburdened health systems in the face of ageing populations and dramatic increases in the prevalence of chronic conditions. EHR systems should also enable new interfaces to be established between healthcare and research environments, leading to improvements in the scope and efficiency of research and the integration of new scientific evidence into practice [2,3]. Given the importance of EHR systems to the better management of healthcare, research interest has developed regarding the rates and levels of adoption of these systems and the determinants of differential adoption rates.

1.1.

Rates and levels of hospital EHR system adoption

Studies of EHR system adoption show that adoption rates in hospital care settings are much lower than those in primary care (GP/family physician) settings (e.g., [9]). Jha et al. [9] studied EHR adoption rates in hospital care settings for the US, Canada, UK, Germany, Netherlands, Australia, and New Zealand. High quality data on EHR use in acute hospital care were lacking, highlighting a lack of reliable, systematic information. EHR adoption in hospitals was found to be low, with fewer than 10% of hospitals in any single country having the key components of an EHR system. The low rates were explained in terms of the lack of attention by policy-makers to adoption, and the expense and disruption initially caused by the systems and the need to integrate them with existing IT systems. Jha et al. [10] used a survey of acute care hospitals in the US (as of March 2009) and found that the percentage of hospitals that had adopted either basic or comprehensive EHR systems had risen from 8.7% in 2008 to 11.9% in 2009. The percentages for basic EHR systems were 7.2% to 9.2%, and for comprehensive EHR systems were 1.5% to 2.7%. As of early 2007, 18.9% of hospitals (249 from a sample of 1316 hospitals from a national total of 9026) in Japan had introduced EHR systems [11]. The adoption rate varied according to hospital size: 500 beds or more (37%), 400–499 (25%), 300–399 (17%), and <300 beds (7%). Adoption rates were higher for public hospitals than for private ones, 22.7% and 12.9%, respectively. Bah et al. [12] surveyed all 19 public hospitals in Eastern Province, Saudi Arabia, and found that only three (16%) used EHR systems (data late 2010).

1.2.

Determinants of hospital EHR system adoption

Detailed information about determinants is available only from OECD countries, the US in particular. Various studies have tested empirical relationships between measures of the

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dependent variable (adoption level/status) and plausible independent variables (determinants) such as hospital size and ownership, and these same studies have proposed theoretical arguments explaining how these determinants are expected to influence EHR system adoption. The determinants identified are wide ranging and include: the degree of urbanicity and health system affiliation (positive effect [10,12,13]); hospital size (positive [10,12–16]); external incentives for improving quality (positive [16]); academic/teaching hospital status (positive [17,18]); maintenance costs (negative [17]); and public hospital (cf. private) status (positive [11,18]; negative [10]; no effect [13]). The influences of social proximity (hospitals in the same system) and spatial proximity to EHR-adopting hospitals on the likelihood of adoption in other hospitals have also been shown to have positive effects [18]. Hypothesized influences shown to have no effect include hospital financial position [16]. Elnahal et al. [19] used 2009 American Hospital Association survey data to compare levels of EHR adoption between high- and low-quality hospitals assessed using Hospital Quality Alliance quality of care measures. They found higher levels of adoption in high-quality hospitals in 11 of the 24 key EHR functions measured. High-quality hospitals tended to be: larger, nonprofit in ownership, teaching hospitals, members of a hospital system, and located in urban areas. Two-thirds of nonadopting and low-quality hospitals had no plans to implement EHR functions. McGinn et al. [20] completed an extensive literature review of factors influencing EHR system implementation/adoption in North America, Europe, and Australasia. Factors included design and technical concerns, ease of use, interoperability between departments, privacy and security, costs, productivity, familiarity with EHRs, motivation to use EHRs, and user time/workload. Findings also indicated the importance of organization size, IT support, training, the relationship between administration and health professionals, and the choice of the particular EHR system.

1.3.

Research rationale and objectives

Despite the prevailing view that EHR systems carry benefits for healthcare organizations, and despite governments in various countries developing policies and allocating funding for the implementation of hospital EHR systems, the uptake has been slow. Little is known about the rates and determinants of adoption outside a few OECD countries. Also, the findings of studies of adoption determinants are not consistent, reflecting variability in the drivers of adoption according to national, regional, and local health system contexts. Identification of the determinants of EHR system adoption is important so that variations in the rates of adoption in hospitals can be understood, and the rates themselves potentially accelerated. This paper aims to establish the rates, levels, and determinants of EHR system adoption in a sample of Saudi hospitals. In the study, ‘rate’ refers to the percentage of hospitals that have adopted an EHR system, and ‘level’ refers to the degree to which an institution has completed the separate phases of implementation, maintenance, and improvement of its EHR system. The Saudi Ministry of Health (MoH) provides approximately 60% of healthcare services to citizens,

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including controlling 244 hospitals (33,277 beds) [21]. The remaining 40% of provision is divided between other nonprofit government institutions such as referral hospitals and the National Guard health affairs (combined total of 39 hospitals, 10,822 beds), and the private sector (125 hospitals, 11,833 beds) [21]. The level of adoption of EHR systems in Saudi Arabian hospitals is currently poorly known, and the determinants of adoption have not been quantified. In the single previously published study of adoption rates, Bah et al. [12] found that three of 19 MoH (public) hospitals in the Eastern Province of the country had implemented an EHR system. Therefore, this study evaluates the status of adoption of EHR systems in nonprofit and private hospitals located in Riyadh. The objectives are: to determine the rate of EHR system adoption across the hospitals; to determine the levels of EHR system adoption with respect to the three phases of implementation, maintenance, and improvement; and to assess any differences in the level of adoption associated with hospital size, level of care (secondary versus tertiary), ownership (nonprofit versus private), and EHR system development team source (outsourced versus in-house) and composition (IT staff ± clinicians ± medical record staff).

2.

Methodology

Riyadh was chosen as the region of interest because: it is the national capital; it has a large number of hospitals (30); it has a wide variety of hospitals regarding parameters such as size and specialty; and it has a mix of public (MoH) and private hospitals. The large number of hospitals and the variation in size, speciality, and public/private ownership meant that the existence of variation in EHR system adoption was likely, and also favoured the explanation of differential levels of EHR system adoption between hospitals. Three phases of EHR system adoption were measured: implementation, maintenance, and improvement. Implementation is the physical realization of an EHR system, involving the installation of new databases and application programs and the use of new procedures. Maintenance refers to the degree to which an EHR system is looked after so that it functions properly. Improvement refers to any subsequent installation or physical change made to an EHR system to increase its value and utility or to improve its functionality.

2.1.

The survey instrument

A questionnaire survey was executed to measure items of interest regarding EHR system adoption in the hospitals. The first part of the survey tool included closed-ended questions focusing on a description of the hospitals, including: the type of organization (private or public); the level of care (secondary or tertiary); the number of beds; and whether or not the hospital had an EHR system. If the hospital did have an EHR system, the respondents were asked: when was the EHR implemented; when will it be fully functional; and how was the system developed. The second part of the survey tool consisted of 37 closedended statement items that covered the three different phases of EHR system adoption: implementation (22 items),

maintenance (4 items), and improvement (11 items). The survey tool allowed respondents to grade the level of preparedness or completion for each item on a three-point scale: 1 = not yet prepared; 2 = prepared for or in progress; 3 = completed/ongoing. To establish the validity of the second part of the survey, three steps were followed. First, the items and format of the questionnaire was taken directly from The Doctor’s Office Quality Information Technology (DOQIT) project, a recognized quality improvement initiative to promote EHR implementation. Previous studies in the field of EHRs and related health information technology topics have used various parts of the DOQ-IT survey documentation [22–24]. Second, the questionnaire was piloted and tested on a small group of colleagues knowledgeable in the field and hospital staff, after which small refinements in wording were made to some items to improve clarity. And third, the reliability of the questionnaire was measured using Cronbach’s alpha coefficient, which indicated a high value of >0.9.

2.2.

Participants

The survey was conducted in 16 public and six private hospitals in Riyadh (Table 1) from January to March 2011. Eight of the 30 hospitals in Riyadh did not participate in the survey. Respondents from each hospital were selected based on a judgmental sampling approach and included project managers, medical directors, heads of IT departments, and senior members of the EHR development teams. Several respondents were used from each hospital to discover whether variation in agreement/disagreement existed across multiple respondents from the same institution, as well as between institutions. Completed surveys from 280 respondents were collected, spread across the different hospitals with respondent numbers in close proportion to the size of the hospitals. The surveys were conducted face-to-face with respondents on-site, and all respondents answered all questions. The role of the interviewers was purely to administer the survey and not to ask questions or to discuss issues with respondents.

2.3.

Methods of data analysis

Data were analyzed using the SPSSTM software program. Descriptive statistics were calculated, including percentages of respondents in each of the three grading categories (not yet prepared, prepared for/in progress, and completed/ongoing) for each questionnaire item. Inferential analysis included t-tests for differences between two groups and one-way ANOVA for differences between three groups. Mean levels of preparation/completion for EHR system implementation, maintenance, and improvement were calculated by averaging the three-point item scores obtained from respondents’ answers to yield a mean score for each hospital. These mean scores for implementation, maintenance, and improvement for each hospital were then used to calculate differences between groups (e.g., private versus public), and therefore the unit of analysis for the inferential statistics is the hospital rather than the survey respondent. Using hospitals as the unit of analysis rather than respondents ensured that a conservative approach was taken for detecting differences between

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Table 1 – Characteristics of surveyed hospitals. Hospital name

Number of respondents surveyed

A. Nonprofit Hospitals in Riyadh Ministry of Health (public) Hospitals In Riyadh City 21 1. King Fahad Medical City 27 2. King Saud Medical City 12 3. Prince Salamn Bin Abdulaziz Hospital 4. Alyamamah Hospital 9 5. Aleman General Hospital 6. Al-Amal Psychiatry Hospital 7. King Saud Chest diseases Hospital 8. Rehabilitation Hospital

Main specialty

Number of beds

Target patients

Type of EHR/EHR components

1200 1500 300

Tertiary General General

Public Public Public

Kortex EMR Medisys Medica plus

360

Public

Medica plus

Public Public Public

Oasis Oasis None (Paper)

6 11 6

300 500 150

Maternity and children General Psychiatry Chest

7

270

Rehabilitation

Public

None (Paper)

Tertiary care centre and Research centre Medical Rehabilitation

Eligible patients only

Cerner EMR

Eligible patients only

Intersystem (HBO) EMR

Other Nonprofit Governmental Organizations’ Hospitals In Riyadh City 30 936 9. King Faisal Specialist Hospital and Research Centre 10. Prince Sultan bin Abdul-Aziz Humanitarian City 11. King Abdul-Aziz Medical City, National Guard Health Affair 12. Riyadh armed forces hospital 13. King Khalid Eye Specialist Hospital

12

400

36

1250

Tertiary

Eligible patients only

QuartaMed EMR

25

1300

General

Eligible patients only

13

228

Eligible patients only

14. King Khalid University Hospital

9

800

Tertiary care ophthalmic facility Tertiary

In-house Patient Management system None (Paper)

15. King Abdulaziz University Hospital

6

110

Tertiary, ENT, Ophthalmology

Eligible patients only

16. Security Forces Hospital

7

508

General

Eligible patients only

B. For-profit (private) hospitals in Riyadh. 6 17. Al Hammady Hospital

300

General

Paying/Insured Public

8

400

Specialist

Paying/Insured Public

13 4

220 300

General General

Paying/Insured Public Paying/Insured Public

5

300

General

Paying/Insured Public

7

100

General

Paying/Insured Public

18. Specialized Medical Center Hospital 19. Dallah Hospital 20. Habib Medical Centres (Arryan) 21. Habib Medical Centres (Olaya complex) 22. Kingdom Hospital

groups of hospitals when testing for the influence of the proposed determinants.

3.

Results

3.1.

Hospital and respondent characteristics

The number of beds in the hospitals ranged from 100 to 1500 with an average of 530 (Table 2). Eleven of the 22 hospitals had already established a fully functioning EHR system, with the year of implementation ranging from 2000 to 2008, while eight

Eligible patients only

McDonnell Douglas + In-house Patient Management system McDonnell Douglas + In-house Patient Management system Intersystem (HBO)

Wipro, RFID for Nursery + In-house Patient Management system In-house Patient Management system Commercial Careware Patient Management system Patient Management system Cerner EMR + Iris Care

hospitals were in the process of implementing one. Seventeen of the hospitals’ EHR systems had nine or fewer clinical applications (such applications include, amongst others, radiology information systems, picture archiving and communication systems, pharmacy information systems, clinical decision support systems, and medication administration record systems), 12 had five or fewer administrative applications (such as an electronic scheduling system for patient admission, transfer, and discharge), and 11 had two or fewer operational applications (applications concerning patient basic information management and tracking). Sixty percent of the EHR system projects had been outsourced, and 50% of the

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Table 2 – Statistics for demographic variables of all 22 hospitals (n = 280 respondents). Value

Percent Mean

Type of organization: 1 = Private 2 = Nonprofit

43 237

15 85

Total

280

100

Level of care: 1 = Primary 2 = Secondary 3 = Tertiary

0 28 252

0 10 90

Total

280

100

Number of beds

Min: 100 Max: 1500

530

Have EHR system: 1 = Yes 2 = No 3 = A work in progress

140 28 112

50 10 40

Total

280

100

Year implemented

Min: 2000 Max: 2008 Min: 2000 Max: 2011

Year full function

Number of applications: Clinical Administrative Operational

Min: 5, max: 45 Min: 3, max: 15 Min: 0, max: 5

Project was developed: 1 = In-house 2 = Outsourced 3 = Mix of the two

50 152 50

20 60 20

24 126 100

10 50 40

The development team was: 1 = IT only 2 = Clinicians and IT 3 = Clinicians, IT and Medical Records Personnel

11.88 6.33 2.75

development teams comprised clinicians and IT specialists while 40% additionally comprised medical record clerks. The types of respondents surveyed are reported in Table 3. Sixteen different types of respondent (defined by their role/position within the hospital) were surveyed across all hospitals. Not all types of respondent were surveyed at each hospital due to reasons of hospital size and the availability of personnel. Table 3 also reports the distribution of respondents for the three hospitals that approved the publishing of this information. One overall unexpected and uncommon feature of the survey results was that the responses provided by respondents at each hospital were unanimous for the questionnaire items. This lack of variation in response for each hospital may be because the communication and understanding regarding EHR system adoption in the hospitals is very clear. It may also reflect the fact that unlike questionnaires concerning, for example, user acceptance of technology, which measure aspects that are subject to opinion and user

experience/impression, the questions in this survey were more knowledge or fact based.

3.2.

Level of adoption: phases of EHR system adoption

3.2.1.

Implementation phase

Nine items of EHR system implementation were reported by 50% or more of the respondents as having been completed (Table 4). However, 30–40% of the respondents reported being not yet prepared for developing the following: an implementation test plan; design pilot testing; engaging users in building test scenarios; scanning strategy; management of old paper charts; and go live (phase I/subsequent). The major qualitative observation regarding the effect of hospital size is that the three nonadopting hospitals are small (150, 228, and 270 beds, respectively), are in the nonprofit sector, and are specialized facilities (Table 1). The level of implementation for the nonprofit hospitals is higher than for the private hospitals (mean levels of preparation/completion of 2.43 and 2.14 out of a maximum of 3, respectively; p < 0.000), and for tertiary hospitals than for secondary hospitals (mean levels of 2.32 and 1.95, respectively; p < 0.000). Regarding EHR system team composition for the 19 adopting hospitals, levels of preparation/completion for implementation are higher among those who developed the system by outsourcing (mean 2.34) or a mix between in-house and outsourced (2.48) compared with those who developed in-house (1.95) (p < 0.000, DF = 2, 16). Levels of preparation/completion are higher where the system was developed by IT personnel (mean 2.46) or IT personnel in conjunction with clinicians (2.33) than by IT personnel with both clinicians and medical records personnel (2.19) (p = 0.017, DF = 2, 16).

3.2.2.

Maintenance phase

The 19 adopting hospitals (i.e., those with EHR systems fully functioning or with implementation in progress) are mixed with regard to the four measured aspects of EHR system maintenance (Table 5). The most advanced levels of maintenance are found in ensuring hardware compatibility and upgrades and in establishing user preferences (78% and 66% of respondents reported that these were completed or ongoing, respectively). Lower levels are evident for updating software and maintaining the clinical decision support system (CDSS), reported as being completed or ongoing by 44% and 22% of respondents, respectively. Nonprofit hospitals have an overall higher level of maintenance than do private hospitals (means 2.45 and 2.15, respectively; p < 0.000), and tertiary hospitals have a higher level (mean 2.3) than do secondary hospitals (1.75) (p < 0.000). Tertiary hospitals are more advanced than secondary hospitals in both their preparation/completion for hardware requirements (means 2.8 and 2.0, respectively; p < 0.000) and in maintaining the CDSS (means 2.0 and 1.0, respectively; p < 0.000). Nonprofit hospitals are more advanced in their preparation/completion for updating relevant software compared with private hospitals (means 2.5 and 1.6, respectively; p < 0.000), and they have higher levels for establishing hardware requirements to keep the EHR system well maintained (means of 3.0 and 2.6, respectively; p < 0.000). However, private hospitals have higher levels of preparation/completion

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Table 3 – Characteristics of survey respondent types, and their distribution for three hospitals. Characteristics of respondents

Number of Participants Member

Role

EHR Team Lead

The EHR Team Lead is responsible for making final decisions regarding the implementation plan. The EHR Implementation Manager is responsible for keeping the project moving. In most implementations, there is a vendor counterpart to this position. The project manager monitors the work plan to ensure that the project is on schedule; maintaining a list of vendor and practice issues that need to be resolved; scheduling implementation-related events, such as hardware deliveries; and delegating tasks to other members of the implementation team. The role of the physician champion is to act as a liaison between the physicians in the group and the implementation team. The physician champion acts as a point of reference for how things are done from a clinical perspective and how physicians need the EHR application to function. The physician champion is responsible for keeping the physicians up to date on the progress of the EHR and for maintaining physician ‘buy-in’ to the project. The Nurse Lead plays a central role on the team and with fellow nurses; he or she should be a respected thought leader who understands clinical workflows, who can inspire nursing staff to embrace change, and who drives consensus among nursing staff. The Medical Assistant Lead plays a central role on the team and with medical assistants; he or she should understand medical assistant workflows, inspire medical assistant staff to embrace change, and drive consensus among medical assistants. The Scheduler Lead plays a central role on the team and with other scheduling assistants; he or she should understand scheduling workflows, inspire scheduling staff to embrace change, and drive consensus among scheduling staff.

EHR Implementation Manager

Physician Champion(S)

Nurse Lead/Team Member

Medical Assistant Lead/Team Member

Scheduler Lead/Team Member

Hospital Name King Abdul-Aziz Medical City, National Guard Health Affair

Prince Sultan bin Abdul-Aziz Humanitarian City

Riyadh armed forces hospital

36

12

25

1

1

1

1

1

1

4

1

3

8

1

4

4

1

2

3

1

2

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Table 3 – (Continued) Characteristics of respondents

Number of Participants Member

Role

Registration Staff Lead/Team Member

The Registration Lead plays a central role on the team and with other registration assistants; he or she should understand registration workflows, inspire registration staff to embrace change, and drive consensus among registration staff. The Lab Lead plays a central role on the team and with other laboratory staff; he or she should understand lab workflows, inspire lab staff to embrace change, and drive consensus among lab staff. The Pharmacy Lead plays a central role on the team and with other pharmacy staff; he or she should understand lab workflows, inspire pharmacy staff to embrace change, and drive consensus among Pharmacy staff. The Radiology Lead plays a central role on the team and with other radiology staff; he or she should understand lab workflows, inspire radiology staff to embrace change, and drive consensus among radiology staff. The Information Technology Lead is responsible for deployment and operation of the software and hardware (e.g., workstations, wireless tablets, printers, and scanners). This is the ‘go-to’ person for people who have questions about the operation of the software and hardware. The Billing Lead plays a central role on the team and with other billing staff; he or she should understand billing workflows, inspire billing staff to embrace change, and drive consensus among billing staff. The EHR Builder is responsible for building and customizing any EHR application areas such as templates, drop-down boxes, and pick lists. This person may also have regular communication with the EHR vendor and may be involved in the training of new staff in how to use the system. The Meaningful Use Lead is responsible for training staff in how to use the EHR system to successfully achieve meaningful use.

Lab staff Lead/Team Member

Pharmacy staff Lead/Team Member

Rad staff Lead/Team Member

Information Technology Lead/Team Member

Billing Lead/Team Member

EHR Builder

Meaningful Use Lead/Team Member

Hospital Name King Abdul-Aziz Medical City, National Guard Health Affair

Prince Sultan bin Abdul-Aziz Humanitarian City

Riyadh armed forces hospital

36

12

25

2

1

2

1

1

2

1

1

1

1

1

1

5

1

3

0

0

0

0

0

0

0

0

0

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Table 3 – (Continued) Characteristics of respondents

Hospital Name King Abdul-Aziz Medical City, National Guard Health Affair

Prince Sultan bin Abdul-Aziz Humanitarian City

36

12

25

2

0

1

3

1

2

Number of Participants Member

Role

Workflow Redesign Lead/Team Member

The Workflow Redesign Lead is responsible for training staff in how to assess current workflows and how to redesign workflows with EHR implementation. The Super-User Lead is responsible for drafting a description of super-user responsibilities and working with various other leadership team-leads to recruit and train super-users. A super-user is a regular staff member who learns the system prior to implementation so that they can expedite IT support and provide problem-solving at the point of need to other staff members during implementation.

Super-User Lead/Team Member

for updating and maintaining a CDSS than do nonprofit hospitals (means 2.0 and 1.75, respectively; p = 0.007).

3.2.3.

Riyadh armed forces hospital

and clinicians 1.57; IT, clinicians, and medical records personnel 1.81; p = 0.017, DF = 2, 16).

Improvement phase

For the 19 adopting hospitals, 60% of respondents from private hospitals indicated that the following aspects had been completed or were ongoing: quality outcomes, patient safety, personal health records, and continuity of care records (Table 6). Sixty to one-hundred percent of private hospital respondents reported being not yet prepared for contributing to a national repository, disease registries, quality improvement, health information organizations (local, regional, and national), and participating in health information exchange across the continuum of care for EHR. For the nonprofit hospitals, 50% of respondents reported that quality outcome improvement was continuing, but all other items were rated at ≤25% for completed/ongoing. The items for which nonprofit hospitals are not yet well prepared for include development of the national repository and disease registries, external reporting of personal health records, providing data for population health and surveillance, participating in health information organizations/networks (local, regional, and national), and engaging in health information exchange across the continuum of care for EHRs. The mean level of preparation/completion of private hospitals (1.74) in the improvement phase is higher than that of nonprofit hospitals (1.58) (p < 0.000). Tertiary care hospitals (1.68) have a higher level of preparation/completion than do secondary care hospitals (1.47) (p = 0.002). There are significant differences in the level of preparation/completion according to the project development source (in-house 1.74, outsourced 1.68, mix of the two 1.53; p < 0.000, DF = 2, 16), and also in the level of preparation/completion according to the composition of the project development team (IT personnel only 1.51; IT

4.

Discussion

4.1.

Rates and levels of adoption of EHR systems

Eleven (50%) of the hospitals surveyed in Riyadh had implemented what could be described as fully functioning EHR systems, another eight (36%) had systems that could be described as works in progress, and three (14%) had not adopted a system. The 50% value compares with: 11.9% (2009 data) for acute care hospitals in the US [10]; <10% for Australia (2007 data), Canada (2007 data), UK (2004 data), and New Zealand (2007 data) [9]; <5% for Netherlands and Germany (both 2007 data) [9]; and 18.9% (2007 data) for Japan [11]. These values, broadly speaking, indicate that the Riyadh hospitals compare quite well in terms of EHR system adoption. However, several caveats need to be applied to the comparisons. First, the comparisons are subject to inter-study differences in the criteria and items used for measuring the functionality of EHR systems. Second, the current survey data were collected during January–March 2011, whereas the comparisons used date from 2004 to 2009, since when adoption rates will probably have increased. Although the sizes of the increase are unknown, Jha et al. [10] found for a sample of more than 3000 acute-care hospitals in the US an increase in EHR adoption rate from 8.7 to 11.9% of hospitals over one year. Third, Riyadh is an urban area and the Saudi capital, and it is known that urban location and spatial proximity increase the likelihood of EHR system adoption in US hospitals [10,12,13,18]. If similar effects exist in the Saudi system, the studied hospitals likely represent a sample at or

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Table 4 – EHR system implementation: all 22 hospitals by number and % of respondents. Item Issues documentation to ensure resolution Confirm turnover strategy Super-users training Web-based training A personalized training session Training plan involved three phases Develop implementation test plan Designed pilot testing Engaging users in building test scenarios Prepare to implement EHR functionality Install hardware, software, network, and storage capabilities Implement security controls and contingency planning Build and test system tables, files, templates, and reports Interface building and testing User training Converting data and compatibility Scanning strategy Management of old paper charts Policies and procedures that ensure a hybrid record situation does not result Stress-test systems Go live (phase i/subsequent) Assess readiness for acceptance

Not yet prepared n (%)

Prepared for or in progress n (%)

Completed or ongoing n (%)

28 (10)

84 (30)

168 (60)

28 (10)

28 (10)

224 (80)

28 (10) 84 (30) 28 (10)

84 (30) 84 (30) 140 (50)

168 (60) 112 (40) 112 (40)

28 (10)

168 (60)

84 (30)

84 (30)

84 (30)

112 (40)

84 (30)

56 (20)

140 (50)

84 (30)

28 (10)

168 (60)

28 (10)

140 (50)

112 (40)

0 (00)

140 (50)

140 (50)

0 (00)

168 (60)

112 (40)

56 (20)

140 (50)

84 (30)

28 (10)

112 (50)

112 (40)

00 (00) 28 (10)

140 (50) 196 (70)

140 (50) 56 (20)

112 (40) 140 (50)

84 (30) 84 (30)

84 (30) 56 (20)

56 (20)

84 (30)

140 (50)

56 (20) 140 (50)

56 (20) 84 (30)

168 (60) 56 (20)

56 (20)

140 (50)

84 (30)

Table 5 – EHR system maintenance phase for the 19 adopting hospitals (by % of respondents). Degree of Maintenance

Software updates (%)

Completed or ongoing Prepared for or in progress Not prepared

44 12 44

User preferences (%) 66 12 22

Hardware compatibility and upgrade (%) 78 22 0

Maintain CDSS (%) 22 44 34

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Table 6 – Improvement phase for the 19 adopting hospitals (by % of respondents). Statement 1. Realize benefits and take corrective action as necessary to improve adoption and outcomes

Item Quality outcomes

Not yet prepared (%)

Prepared for or in progress (%)

Completed or ongoing (%)

Quality improvement

42 210 42 210 42 210 42 210 42 210 42 210

20 0 20 0 80 100 40 75 80 100 60 25

60 50 20 75 0 0 60 25 0 0 20 50

20 50 60 25 20 0 0 0 20 0 20 25

Personal health record Continuity-of-care record Population health and surveillance Health information organizations/networks

Private Nonprofit Private Nonprofit Private Nonprofit Private Nonprofit

42 210 42 210 42 210 42 210

20 75 0 50 20 75 80 75

20 25 40 50 60 0 20 25

60 0 60 0 20 25 0 0

Private Nonprofit

42 210

80 50

20 25

0 25

Patient safety

Pay for performance Disease registries

3. Engage in health information exchange

n

Private Nonprofit Private Nonprofit Private Nonprofit Private Nonprofit Private Nonprofit Private Nonprofit

National repository

2. Contribute data for external reporting

Organization type

near the top of the range; this inference is supported by the lower rate of adoption (16%) for 19 hospitals across the country’s Eastern Province, which contains both rural and urban areas [12]. Two implications of these caveats are that the Saudi national average EHR system take-up is probably lower than that reported in the Riyadh sample (50%), and that the differences in the rates of adoption between the Riyadh sample and those reported from other countries are probably smaller than those indicated by the face values. The WHO ranks the Saudi Arabian healthcare system as 26th of 190 in the world [21]. It is therefore not unexpected that a high rate of hospital EHR system adoption might be found in the country’s principal urban area. However, despite the high international ranking, the MoH is facing challenges regarding health funding due to population increase, the cost of new technologies, and rising public awareness about health [21]. There is also concern about the underdevelopment of electronic health systems in Saudi Arabia [21,25,26]. Given that the MoH 10-year health ICT strategy incorporates many initiatives besides EHR system adoption, the distribution of funding across them will influence how rapidly further adoption occurs. Recently, the privatization of public hospitals has been proposed to help reform the Saudi healthcare system by reducing the government’s total health spending and concentrating its funding [21]. Given the mixed results here regarding EHR system adoption and hospital ownership type, it is not clear what effect privatization might have on either the rate or level of adoption. There are disparities in hospital EHR system take-up between regions in Saudi Arabia, as evidenced by the contrasting results between the Riyadh hospitals and the Eastern Province hospitals studied by Bah et al. [12]. The Eastern Province hospitals were a mixture of urban and rural hospitals, and comprised only MoH hospitals, compared to the urban,

nonprofit (both MoH and other agencies), and private hospitals surveyed here. To avoid regional inequalities in e-health provision, further efforts should be made to identify inequalities and rectify them. This would require a wider survey of public hospitals across the whole of the country (around 240 hospitals), although any rectification would be dependent on the MoH’s policies and funding priorities. Concerning the level of adoption, as examined using the three phases of adoption (implementation, maintenance, and improvement), several insights can be drawn. For implementation, there is a cluster of low preparation/action regarding scanning strategy, management of old paper records, and converting data and issues of compatibility (Table 4). These relate to the transition from paper-based information to electronic information and the legacy of the paper record system. Particular attention needs to be paid to these items of implementation in a Saudi hospital context. Concerning EHR system maintenance items, there is a deficiency with respect to software, both in ensuring that software updates are completed and in the maintenance/updating of the CDSS (Table 5). Software, therefore, appears to be an area of weakness and suggests a point of required action. With respect to improvement, a particular deficiency involves aspects of health information communication and sharing, with items of weakness including the continued development of a national repository and disease registry, the establishment of and participation in health information networks/organizations, and participation in health information exchange (Table 6). Clearly, there remains much to do regarding health information communication and sharing, which is partly a function of interoperability. Problems of interoperability have been identified in various countries, some with advanced levels of EHR system adoption [3,7,11]. In Saudi Arabia, information systems in MoH institutions are not

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connected to each other, nor are they connected to other health organizations [21,25]. The present findings suggest that any movement towards interoperability and information sharing is currently extremely slow. Ways to better coordinate and integrate the sharing of information among institutions need to be found so that the use and utility of EHRs and EHR systems can be improved [3]. Specifications are needed that enable disparate healthcare applications to securely share key clinical and administrative data. The importance of specifications is evident in the success of the Turkish National Health Information System, which has high rates of hospital participation and which has enabled different vendor-based systems to access and share EHRs on a nationwide basis [27]. With the need for interoperability, however, there is also a need for individuality, as a gap exists between standard generic software solutions and the requirements, contexts, and practices of individual organizations [28], which has led to problems regarding EHR implementation in hospitals in the UK, for example [4,28]. The 19 adopting Riyadh hospitals use 16 different EHR systems. Given the range of EHR systems available and in use in Saudi Arabia, and the differences between the various systems that discourage interoperability, the only solution to inter-provider sharing of clinical information will be the establishment of technical specifications and standards that enable interoperability.

4.2.

Determinants of EHR system adoption

Hospital size is an established positive driver of EHR system takeup [10,12–15]. The wider and more complex mix of cases in larger hospitals means that such hospitals gain more benefit in clinical and operational terms from system adoption than do small hospitals [15,29]. This complexity–size relationship is apparent in Riyadh, with the three nonadopting hospitals being small (<300 beds) and focusing on a single specialty (chest, eye, and rehabilitation, respectively). Tertiary hospitals are similarly likely to be more advanced in their adoption of EHR systems than are secondary hospitals, due to the wider complexity of the case-mix encountered. Hospital ownership (nonprofit or private) is known in other jurisdictions to influence EHR system adoption, although findings have revealed both positive and negative relationships, and sometimes no effect [10,11,13,18]. The Riyadh sample was mixed in that the nonadopting hospitals were nonprofit (although this result is also partly explained by the small size and specialist nature of the hospitals) but the adopting nonprofit hospitals were more advanced than the private hospitals in their level of implementation. In addition, for the adopting hospitals, private hospitals lagged the nonprofit sector in their level of preparation/completion for maintenance, but were more advanced in EHR system improvement. Various factors have been proposed to explain differences in EHR system adoption between nonprofit and private hospitals in the US, including the greater financial resources of the latter, different organizational missions, and their greater pursuit of organizational efficiency [13]. It is not known what particular inherent factors distinguish nonprofit from private hospitals in Riyadh with respect to adoption. However, the mixed findings for the Riyadh hospitals demonstrate the need for a multistage

adoption approach and multi-item measures to be used when assessing the degree of adoption and its determinants. The results regarding the development team were mixed but suggest that the team source and composition may influence EHR system implementation and improvement. However, it is not clear how the effect works or why there is variation in the results according to which stage of adoption is considered; for example, outsourcing appears to help in the implementation phase, but not in the maintenance or improvement phases. Participation of users during EHR implementation is likely to allow “decision-makers to consider users’ perspectives, gain their support, and adapt the technology to users’ needs” [20]. For example, physician involvement and participation with the IT project team was perceived by users as being the seventh most important factor (of 32) in the successful implementation of a computerized physician order entry system at Riyadh’s King Abdulaziz Medical City (KAMC) [30]. Physician resistance to EHR systems in the Eastern Province hospitals was reported by surveyed respondents as a major factor slowing the systems’ implementation and usefulness [12]. In this regard, there is a need to study user acceptance of EHR systems in Saudi Arabian hospitals, similar to the investigation by Aldosari [31] regarding the implementation of a picture archiving and communication system at KAMC. The study would examine aspects of the system development team in a more detailed way than conducted here, in particular the relationships between EHR system implementation, clinicians’ involvement in system selection/development, and user acceptance [20].

5.

Conclusion and recommendations

This study is the first to investigate the level and determinants of EHR system adoption for public, other nonprofit, and private hospitals in Saudi Arabia. The hospitals show variation in various aspects of system implementation, maintenance, and improvement, attributable to hospital size, level of care, type of ownership (nonprofit versus private), and EHR system development team source and composition. The major findings and their implications are: 1. Variations exist in the rate and level of EHR system adoption in Saudi Arabia between hospitals (and between regions). There is a need to measure adoption rates and levels in a geographically wider sample to confirm the magnitudes of the inequalities discovered. A reduction in the degree of inequality would require policy direction and funding from the Saudi government. 2. Further research is needed on the determinants of adoption by incorporating a more widespread sample to verify the presented findings. The research should include the determinants studied here, and detailed investigations should also be made of physician involvement in the implementation of EHR systems and of user acceptance of the systems. 3. Regarding the implementation phase, an area of weakness across the hospitals involves the legacy of paper data systems, including document scanning, record management, and data conversion. These deficiencies need to be addressed so that the efficiency and usefulness of EHR

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Summary points What was already known on the topic:

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Conflict of interest statement The author has no conflicts of interest to declare.

• Electronic health record (EHR) systems in hospitals help improve the efficiency and effectiveness of healthcare, and will be increasingly important in relieving overburdened health systems. • If the benefits of EHR systems are to be realized, the rates/levels of adoption of these systems and the determinants of differential adoption rates need to be better and more widely quantified. • Little information exists regarding the rates, levels, and determinants of hospital EHR system adoption for the vast majority of countries, including Saudi Arabia. What this study added to our knowledge: • EHR system adoption rates among 22 surveyed hospitals in Riyadh, Saudi Arabia, are high compared with those of other countries and other Saudi regions. • Levels of adoption as measured by the degree of completion of the implementation, maintenance, and improvement phases vary across the studied hospitals. • The variation in the level of EHR system adoption is attributable to hospital size, level of care, ownership (nonprofit versus private), and EHR system development team characteristics. • General weaknesses across the hospitals relate to the legacy of paper systems (e.g., record management and data conversion), updating and maintenance of system software, and poor interoperability and information exchange due to the variety of EHR systems used.

systems can be maximized in adopting hospitals, and to ease implementation by current nonadopters. 4. In the maintenance phase, there is a weakness with respect to software updating and maintenance, including updating CDSS software. The reasons for this weakness need to be identified, although could include the high annual cost of updating purchased software. 5. For the improvement phase, there is a deficiency in health information communication and sharing, including deficiencies in the development of data repositories, in the establishment of information networks, and in information exchange. The barriers to information sharing need to be better defined, including the problem of interoperability between the many different hospital EHR systems in use.

Author’s contribution The author was the sole contributor from the conception of the study through to the writing of the final version of the paper.

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