Health Information Technology: Current Situation & What to Expect

in The Near Future

Dr. Made Indra WijayaAssistant Medical Director

BIMC Hospital

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April 2009 ; 21 provinces in Indonesia ; 97 respondents ; questionnaire

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BIMC Hospital (January – August 2009)

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Patient Year 2009BIMC Hospital

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A cross sectional survey design Data were collected between April

2009 and June 2009 The sample was derived from BIMC

Hospital Sampling targeted Indonesian (200

samples)

Statements Strongly agree

Agree Unsure Disagree Strongly disagree

I can talk easily with the doctor 19% (38) 68%

(136) 8% (16) 5% (10) 0%

I feel the doctor is listening to me 19% (38) 56%

(112) 18% (36) 1% (2) 6% (12)

I feel the doctor is distracted 5% (10) 22%

(44) 25% (50) 38% (76) 10% (20)

The doctor looks at the computer screen more than at me

3% (6) 12% (24) 13% (26) 53%

(106) 19% (38)

The doctor often explains the role of the computer to me

2% (4) 26% (52) 21% (42) 38% (76) 13% (26)

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Statements Strongly agree

Agree Neutral Disagree Strongly disagree

I am receiving a better standard of treatment 12% (24) 51%

(102) 19% (38) 14% (28) 4% (8)

The doctor can access my medical files more quickly 39% (87) 50%

(100) 9% (18) 1% (2) 1% (2)

The issuing of prescriptions is improved 38% (76) 50%

(100) 10% (20) 1% (2) 1% (2)

The doctor has ready access to useful referencing tools for up-to-date medications

38% (76) 50% (100) 12% (24) 0% 0%

Assess to information regarding patient education is easier

19% (38) 48% (96) 26% (52) 7% (14) 0%

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Chi Square Analysis50 respondentsPatient’s perceptions :

1 = score 0-92 = score 10-193 = score 20-294 = score 30-395 = score 40-50

Nationality :1 = Australian2 = Indonesian

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Nationality

Total

Australian Indonesian

patient's perceptions

0-9 2 0 2

10-19 2 0 2

20-29 5 5 10

30-39 14 11 25

40-50 3 8 11

Total 26 24 50

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Chi-Square Tests

 

Value dfAsymp. Sig. (2-

sided)

Pearson Chi-Square 6.563a 4 .161

Likelihood Ratio 8.184 4 .085

Linear-by-Linear Association

4.636 1 .031

N of Valid Cases 50    

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H0 accepted H0 rejected

9.448

6.563

Pearson chi square (X2 measured) = 6.563

Table chi square (X2 table) : significance 0.05 ; Degree of freedom = 4 ; X2 = 9.488 or on MsExcel =chiinv(0.05,4) 9.488

X2 measured < X2 table (6.563 < 9.488) No significance difference between

Australian and Indonesian with regard to patient’s perception

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What to expect in the near future

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HIM falls into three categories

Factors Influencing Attitudes Toward Computerization

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Otieno George Ochieng, 2005Otieno George Ochieng, 2005

EMR diffusion is the extent to which the full potential of EMR should be embedded within patient care processes

3 hospitals in JapanAttitudes toward computerization is the

most influencing factor to EMR diffusion

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A cross sectional survey design Data were collected between April

2009 and June 2009 The sample was derived from 12

hospitals in Bali Sampling targeted doctors, nurses,

and healthcare administrators

The questionnaire consisted of three sections:1.Two items on IT skills with response options

ranging from none/never to a great deal/always

2.A list of 16 functions in patient care where respondents were asked to check whether each had been computerized (yes, no, not sure)

3. A 10-item attitude scale assessing the healthcare workers’ attitude towards the use of computers in patient care, where response were : strongly disagree, disagree, agree, and strongly agree

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Data were analyzed using SPSS v17IT skills were measured on a four-point scale

ranging from ‘none/never’ (1) to ‘a great deal/always’ (4)

Current status of computerization was on a 3-point scale ranging from ‘no’ (1), ‘not sure’ (2), to ‘yes’ (3)

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Attitudes were measured on a 4-point scale ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (4).

Sample = 12Validity test

Reliability test

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Current status : Pearson correlation of item 1 to item 16 were ranging from 0.648 to 0.932 (table r, significance 0.05, 2-tailed, N=12 0.576) all items are valid

IT skills : Pearson correlation of item 1 & item 2 were 0.851 & 0.880 respectively (table r, significance 0.05, 2-tailed, N=12 0.576 all items are valid

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Attitudes toward computerization: Pearson correlation were ranging from 0.664 to 0.872 (table r, significance 0.05, 2-tailed, N=12 0.576) all items are valid

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CURRENT STATUS

Reliability Statistics

Cronbach's Alpha N of Items

.976 16

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Attitudes Toward Computerization

Reliability Statistics

Cronbach's Alpha N of Items

.926 10

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Healthcare Workers IT skills

Reliability Statistics

Cronbach's Alpha N of Items

.663 2

Current status: Cronbach’s alpha was 0.976 (table r, significance 0.05, 2-tailed, N=12 0.576) reliable

Attitudes toward computerization: Cronbach’s alpha was 0.926 (table r, significance 0.05, 2-tailed, N=12 0.576) reliable

IT skills: Cronbach’s alpha was 0.663 (table r, significance 0.05, 2-tailed, N=12 0.576) reliable

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Measures of normalityTest for linearity

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Measures of normality

attitudes current IT skills

skewness -0.706 0.515 -0.517

std. error 0.393 0.393 0.393

ratio -1.796 1.310 -1.316

kurtosis -1.100 -1.370 -1.235

std. error 0.768 0.768 0.768

ratio -1.432 -1.784 -1.608

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Differ from Normal

distribution

NormalDistribution

Differ fromNormal

distribution

-2 -2

Current status: skewness/std error ratio was 1.310 & kurtosis/std error ratio was -1.784 between -2 to 2 normal distribution

Attitudes: skewness/std error ratio was -1.796 & kurtosis/std error ratio was 0.768 between -2 to 2 normal distribution

IT skills: skewness/std error ratio was -1.316 & kurtosis/std error ratio was -1.608 between -2 to 2 normal distribution

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ANOVA Table

      Sum of Squares dfMean

SquareF Sig.

attitudes * current status

Between Groups

(Combined) 989.000 6 164.833 5.670 .001

Linearity 149.699 1 149.699 5.150 .031

Deviation from Linearity

839.301 5 167.860 5.775 .001

Within Groups 843.000 29 29.069    

Total 1832.000 35      

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ANOVA Table

      Sum of Squares dfMean

SquareF Sig.

attitudes * IT skills

Between Groups

(Combined) 1702.100 4 425.525 101.549 .000

Linearity 1496.910 1 1496.910 357.230 .000

Deviation from Linearity

205.190 3 68.397 16.323 .000

Within Groups 129.900 31 4.190    

Total 1832.000 35      

Attitudes * current status : P value (linearity) < 0.05 Current status

has linear correlation with attitudes toward computerization

Attitudes * IT skills : P value (linearity) < 0.05 IT skills has

linear correlation with attitudes toward computerization

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MULTICOLLINEARITY TESTHETEROSKEDASTICITY TESTAUTOCORRELATION TEST

Classical Assumption Deviation Tests

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Collinearity Statistics

Tolerance VIF

current status .936 1.068

IT skills .936 1.068

Multicollinearity test

Collinearity statistics from linear regression revealed VIF (variance inflation factor) of both current status and IT skills were 1.068 (less than 5, Santoso, 2001) no multicollinearity problem between independent variables

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Unstandardized Coefficients

t Sig.

B Std. Error

(Constant) 13.588 1.477 9.202 .000

lnx1 -.574 .664 -.865 .393

(Constant) 16.052 2.035 7.889 .000

lnx2 -2.572 1.503 -1.710 .097

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H0 rejected H0 accepted H0 rejected

-2.035 2.035-0.865

-1.710

Current status (Lnx1): t = -0.865 (-2.035 < t < 2.035) no symptom of heteroskedasticity between attitudes (Lnei2)and current status (Lnx1)

IT skills (Lnx2): t = -1.710 (-2.035 < t < 2.035) no symptom of heteroskedasticity between attitudes (Lnei2)and IT skills (Lnx2)

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R R SquareAdjusted R

SquareStd. Error of the Estimate

Durbin-Watson

.906a .821 .810 3.155 2.041

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doubtful No autocorrelation doubtful Autocorrelation

exists

dL =1.354

dU =1.587

4-dU =2.412

4-dL =2.646

DW =2.041

Autocorrelation exists

Table d (Durbin Watson), significance 0.05, n = 36, k’ = 2 dL = 1.354 ; dU = 1.587 ; 4-dU = 2.412 ; 4-dL = 2.646

Durbin-Watson (DW) = 2.041 (dU < DW < 4-dL) no autocorrelation between independent variables

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Multiple regressionMultiple correlation analysisDetermination analysisF testT test

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  Unstandardized Coefficients

  B Std. Error

(Constant) 5.772 2.167

current status .038 .047

IT skills 4.030 .346

Multiple regressionIf current status and IT skills scores were

both 0, attitudes toward computerization score would be 5.572

If IT skill was controlled, and current status score increased by 1, then attitudes toward computerization score would increase 0.038

If current status was controlled, and IT skill score increased by 1, then attitudes toward computerization score would increase 4.030

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R R SquareAdjusted R

SquareStd. Error of the Estimate

.906a .821 .810 3.155

Sugiyono, 2007, if correlation coefficient (R) :0.00 – 0.199 : very small0.20 – 0.399 : small0.40 – 0.599 : medium0.60 – 0.799 : large0.80 – 1.00 : very large

R = 0.906 Current status & IT skills combine have very large correlation with attitudes toward computerization

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Determination analysis

R2 (R square) = 0.821 current status & IT skills combine account for 82.1% of the variability in attitudes toward computerization

Standard error of the estimate was 3.155 predicted Attitudes toward computerization scores derived from this regression equation will differ from actual attitudes toward computerization scores by 3.155

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  Sum of Squares df Mean Square F Sig.

Regression 1503.495 2 751.748 75.517 .000a

Residual 328.505 33 9.955    

Total 1832.000 35      

H0 accepted H0 rejected

3.285 75.517

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Table F significance 0.05, Df1 = 2, Df2 = 33 3.285 or from MsExcel =FINV(0.05,2,33) 3.285

F measured = 75.517F measured > F table (P value < 0.05)

current status and IT skills combine have significant influence to attitudes toward computerization

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  Unstandardized CoefficientsStandardized Coefficients

t Sig.

  B Std. Error Beta

(Constant) 5.772 2.167   2.663 .012

current status .038 .047 .062 .813 .422

IT skills 4.030 .346 .888 11.662 .000

H0 rejected H0 rejectedH0 accepted

-2.035 2.035

0.813

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CURRENT STATUS OF HEALTHCARE COMPUTERIZATION

H0 rejected H0 rejectedH0 accepted

-2.035 2.035

11.662

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HEALTHCARE WORKERS’ IT SKILLS

Table t, significance 0.05, 2-tailed, Df = 33 2.035 or from MsExcel =TINV(0.05,33) 2.035

Current status: t measured = 0.813 (-2.035 < t < 2.035; P > 0.05) partially, current status does not have significance influence to attitudes toward computerization.

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t test for IT skills

Table t, significance 0.05, 2-tailed, Df = 33 2.035 or from MsExcel =TINV(0.05,33) 2.035

IT skills: t measured = 11.662 (t > 2.035; P < 0.05) partially, IT skills has significance influence to attitudes toward computerization.

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Attitudes toward computerization is heavily influenced by healthcare workers’ IT skills

Targeted training of healthcare workers is needed to foster positive attitudes about EMR

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A little knowledge that acts is worth infinitely more than much knowledge that is idle

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