Impact of the Electronic Health Records on Patient Safety in King Khalid University Hospital

¶ … Electronic Medical Records (E-SIHI) in King Khalid University Hospital on Patient Safety

The objective of this study is to demonstrate the impact of e-SIHI (Electronic Medical Records) on patients with regards to their security and safety. The King Khalid University Hospital has implemented the e-SIHI since May 2015 for all departments. Two weeks after the implementation, QMD (Quality Management Department) conducted an audit to measure a compliance for the system and ascertain whether the e-SIHI can improve health and safety of patients. However, the QMD found that there are many areas requiring improvement in the system. The paper discusses the methodology used to evaluate the system to ascertain whether e-SIHI is beneficial to the patient.

Research Methodology

The research methodology reveals research design discussing the method of data collection, sample population, sample size, and project tool.

Study Design: The team audits the e-SIHI using a checklist to verify whether the EHRs are up-to-date, accurate, and meet organizations procedures and policies for effective information management.

Project Tool: The documents are reviewed using the JACHO checklist that consists of a review of medical records. The paper also uses the open record review to monitor the standard of care and quality of care delivered to patients. The open record review plays an important role towards making the documentation more streamlined and systematic. Approximate 3,500 patient's admissions are recorded by King Khalid University Hospital each month, and the study selects and reviews 350 files, which are 10% of the entire patient records. However, the study only reviews the files of patients admitted more than 48 hours and who have not yet been discharged

Data Collection: The study collects data from open electronic medical records, carries out the analysis and presents the final results to the department head to highlight the gaps that need improvement.

Data Source

The data are collected from the open electronic patient files. The study collects data from the departments that include surgery, medicine, pediatric, KFCC, critical care, orthopedic, oncology, OBGYNE, mental health, and emergency department. Moreover, the quality facilitators collected data, the secretaries entered the data into the system and the evaluation and monitoring specialists analyzed the data

Sample Size

The study reviews a number of 324 files from approximately 3,500 patient admission files per month. The files reviewed are 20 KFCC, 20 Critical Care, 40 OB, 150 Medicine, 45 Pedia, 77 Surgery and 10 Psychiatry.

Sample Group: The study carries out the internal audit by randomly selecting a group of files, and reviewing each of the files contents for completeness.

Leader: The leader is Heba Bou Mahdi, Quality Management Department, a Healthcare Quality and Monitoring and Evaluation Specialist.

Team: The quality facilitators collected data, encoded by the secretary, which was analyzed by the Quality Specialist

M&E Duration: The study carries out a comparative report between 3rd Quarter of 2015 and December 15-January.

The paper collects data to compare the clinical documentation, medication, medication error, and lab (phlebotomy) before the implementation of the system and after the system implementation.

Data Analysis

The data analysis is carried out using the quantitative technique. The comparative analysis is carried out to compare the impact of the system before and after the implementation. The study also uses out the descriptive statistics to summarize the data in a manageable form presenting the Mean value of the data.

Findings

The study presents the findings of the clinical documentation, medical reconciliation, medical errors, and phlebotomy of the King Khalid University Hospital before and after the implementation of the systems.

Clinical Documentation

The study carries out the descriptive statistics of the data collected for the clinical documentation between 2015 and 2016. The paper uses the data in Table 1 to develop the descriptive statistics. As being revealed in the descriptive statistics table, the Mean value of the clinical documentation before the system implementation is 69.32%, however, the Mean value is 77.42% with the system implementation. The outcome of the analysis reveals that the EHR is an effective tool for an improvement of clinical documentation. The effective clinical documentation will assist in eliminating the medical error. Moreover, the improvement in the clinical documentation will also speed the work of healthcare professionals leading to an improvement in patient safety and security. (Jang, Yu, Kim, Moon, ET al.2013).

Table 2: Descriptive Statistics

2015

2016

Mean

69,62%

77,42%

Standard Error

4,54%

4,53%

Median

76,95%

86,75%

Mode

71,80%

84,30%

Standard Deviation

25,70%

25,62%

Sample Variance

6,61%

6,56%

Kurtosis

-65,17%

161,26%

Skewness

-65,42%

-156,19%

Range

93,50%

98,10%

Minimum

6,50%

1,60%

Maximum

100,00%

99,70%

Sum

2227,88%

2477,50%

Count

3200,00%

3200,00%

Confidence Level (95, 0%)

9,27%

9,24%

Table 2:

2015

2016

Histories

Family History

44.98%

45.7%

Past Medical History

71.8%

84.3%

Procedure/Surgery History

71.8%

84.3%

Social History

71.8%

84.3%

Assessment/Physical Examination

Chief Complaint

96.7%

96.9%

Diagnosis

78.9%

91.1%

Problems

97.0%

98.3%

Physical Examination

98.0%

85.0%

Results of Lab/X-ray

88.1%

95.1%

Allergies

98.3%

99.7%

MEDICATION LIST

Medication Reconciliation History

77.3%

95.0%

Medication Reconciliation on Admission

76.6%

94.0%

ORDERS

Telephone orders cosigned within 24 hours

60.7%

75.0%

CONSULTATIONS

Request for consultation is completed

90.1%

91.1%

Status of Consultation (Routine/Urgent)

83.7%

80.4%

Consultation note is completed timely (Routine: 24 hours / Urgent: 8 hours / STAT: 2 hours)

80.3%

86.1%

INTERACTIVE VIEW & INTAKE OUTPUT-Nursing Documentation

Vital Signs

95.7%

Intake Output

97.0%

98.4%

Devices

83.9%

80.8%

Cannulas

95.3%

92.6%

DISCHARGE READINESS

Length of Stay is Documented

44.7%

94.0%

Estimated Discharge Date is Documented

6.5%

1.6%

Diagnosis is Documented

42.4%

69.5%

Patient Education is Documented

33.7%

27.7%

Follow up Appointment is Documented

37.5%

90.6%

Medication Reconciliation on Discharge is Documented

39.3%

87.4%

Discharge Note is Documented

40.8%

92.9%

Discharge Orders is Documented

36.9%

98.1%

Discharge Summary Handout is fully Completed

32.4%

21.9%

CONSENTS (Paper-based)

General Consent form for admission is completed

67.7%

42.9%

Surgery/Procedure Consent form is completed

92.8%

45.8%

Blood Consent form is completed

90.9%

51.3%

Medical Reconciliation

Comparative analysis of the medical reconciliation before and after the system implementation reveals that the King Khalid University Hospital has been able to derive benefits from the system with regard to the medical reconciliation. As being revealed in table 2 and Fig 1, the hospital has derived benefits from the system because the Mean value of the medical reconciliation is 64.4% before the system implementation and 92.13% after the implementation of the e-SIHI.

Table 2: Medication Reconciliation

2015

2016

Medication Reconciliation History

77.3%

95.0%

Medication Reconciliation on Admission

76.6%

94.0%

Medication Reconciliation on Discharge is Documented

39.3%

87.4%

Mean

64.40%

92.13%

Medication Errors

Medical errors refer to an unintended failure in treatment that can cause harm or potential harm to patients. (Bowman, 2013). King Khalid University Hospital had the histories of medication errors before the implementation of the systems. The overall medication errors in 2015 were 4431 that include errors in administration, prescribing, verification, preparation, dispensing, and monitoring. However, the new system has not been able to solve the problem of medication errors in the hospital. Between January and May 2015, the medication errors recorded were 645 (15%) however, the hospital recorded between June and December were 3798 (85%) medication errors revealing 70% increase in medication errors after the system implementation.

The medication errors

Number of Errors

2015

Administration

23

prescribing verification

8

preparation

3

dispensing

44

Monitoring

23

System

5

Other

total

Month

Jan

Feb

Mar

Apr

May

Jun

July

Aug

Sep

Oct

Nov

Dec

total

Number of errors

46

86

Jan

Feb

Mar

Apr

May

Jun

July

Aug

Sep

Oct

Nov

Dec

A

36

28

3

9

56

97

68

69

B

41

78

C

8

7

3

2

23

97

32

24

24

49

44

44

D

0

0

0

0

0

2

0

0

0

0

1

0

Discussion