What factors influence the use of electronic health records during the first 10 minutes of the clinical encounter?

Figures & data

Table 1 Patient, physician and consultation characteristics

Patient characteristics	n=134
Median age (range), years	44 (19–80)
Male, n (%)	83 (59)
Physician characteristics	n=17
Median age (range), years	34 (30–53)
Male, n (%)	7 (41)
Median years of postgraduate experience (range)	6 (4–28)
Postgraduate title in primary care (%)	6 (35)
Mean level of expertise in typing (1–5 Likert scale) (SD)	2.65 (1.1)
Beliefs about EHR use – mean (1–5 Likert scale) (SD)
• Belief that computed is a barrier	3.50 (1.0)
• Belief that computer has a negative influence	3.65 (1.3)
Consultation characteristics	n=142
Type of consultation, n (%)
• New case	35 (25)
• Follow-up	105 (74)
• Data not available	2 (1)
Language used during the consultation, n (%)
• French	126 (89)
• English	16 (11)
Content of the first ten minutes of the consultation (number of utterances) n (%)	n=29,011
• Medical and therapeutic	9,475 (33)
• Psychosocial	1,637 (6)
• Lifestyle	967 (3)
• Positive talka	6,208 (21)
• Emotional talk	814 (3)
• Negative talkb	11 (0)
• Social talkc	367 (1)
• Partnershipd	5,551 (19)
• Others	492 (2)

Notes:

a Agreement, approval, give compliment and laughs.

b Disapproval and criticism.

c Personal remarks and social conversation.

d Asks for opinion, understanding, reassurance, permission and back-channel responses.

Abbreviation: EHR, electronic health record.

Table 2 Link between EHR use during the first 10 minutes of the clinical encounter (% of utterances, including silence) and patient, physician and consultation characteristics

Characteristics	Description of the variable % of use of the computer	Valuea	P	Value	P
		Univariable		Multivariable	Model
Age of patient	Increase if the patient is 1 year older	+0.004% (−0.208% to +0.216%)	0.9708	–
Sex of patient	Male	30.0% (23.5% to 36.4%)	0.2697	–
	Female	26.3% (21.4% to 31.3%)		–
Age of physician (MD), years	Increase if the MD is 1 year older	−0.4899% (−1.0485% to 0.0688%)	0.0850	–
Sex (MD)	Male	30.0% (25.8% to 34.2%)	0.0864	30.0% (17.0% to 42.9%)	0.1010
	Female	26.3% (21.4% to 31.3%)		24.6% (11.2% to 38.0%)
Postgraduate experience (MD)	Increase if the MD has one more year of experience	−0.5847% (−1.0950% to 0.0748%)	0.0251	−0.5994% (−1.1078% to 0.0910%)	0.0213
Level of expertise in typing MD (1–5 Likert scale, 1 being poor and 5 excellent)	Increase by 1 on the Likert scale	+1.8909% (−1.3734% to 5.1552%)	0.2534	–
Belief that computed is a barrier MD (1–5 Likert scale, 1 being do not agree and 5 fully agree)	Increase by 1 on the Likert scale	−1.2811% (−4.5862% to 2.0240%)	0.4439	–
Belief that computer has a negative influence (1–5 Likert scale, on 1 being do not agree and 5 fully agree)	Increase by 1 on the Likert scale	−2.3081% (−4.8521% to 0.2359%)	0.0749	–
Type of consultation	New	33.1% (27.0% to 39.3%)	0.0821	24.6% (11.2% to 38.0%)	0.0967
	Follow-up	26.8% (23.1% to 30.5%)		18.6% (6.4% to 30.9%)
Language spoken during consultation	English	27.1%	0.7164	–
	French	28.9%		–
Psychosocial content	Increase by 1% of the content	−0.4007% (−0.7408% to 0.0605%)	0.0214	–
Lifestyle content	Increase by 1% of the content	−0.1948% (−0.991% to 0.6014%)	0.6289	–
Psychosocial and lifestyle content	Increase by 1% of the content	−0.3581% (−0.6660% to 0.0503%)	0.0230	–
Biomedical content	Increase by 1% of the content	0.3774% (0.0695% to 0.6852%)	0.0167	+0.4016% (0.0708% to 0.7323%)	0.0178

Notes: Factors kept in the multivariable model were given in bold.

a Values of the estimated coefficients are displayed with 95% CIs (in parenthesis). “+” or “−” are used when the variable is continuous.

Abbreviation: MD, medical doctor.