TY - JOUR
T1 - An Electronic Clinical Decision Support System for the Management of Low Back Pain in Community Pharmacy: Development and Mixed Methods Feasibility Study
AU - Downie, Aron Simon
AU - Hancock, Mark
AU - Abdel Shaheed, Christina
AU - McLachlan, Andrew J
AU - Kocaballi, Ahmet Baki
AU - Williams, Christopher M
AU - Michaleff, Zoe A
AU - Maher, Chris G
N1 - ©Aron Simon Downie, Mark Hancock, Christina Abdel Shaheed, Andrew J McLachlan, Ahmet Baki Kocaballi, Christopher M Williams, Zoe A Michaleff, Chris G Maher. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 11.05.2020.
PY - 2020/5/11
Y1 - 2020/5/11
N2 - BACKGROUND: People with low back pain (LBP) in the community often do not
receive evidence-based advice and management. Community pharmacists can play an
important role in supporting people with LBP as pharmacists are easily
accessible to provide first-line care. However, previous research suggests that
pharmacists may not consistently deliver advice that is concordant with
guideline recommendations and may demonstrate difficulty determining which
patients require prompt medical review. A clinical decision support system
(CDSS) may enhance first-line care of LBP, but none exists to support the
community pharmacist-client consultation.OBJECTIVE: This study aimed to develop a CDSS to guide first-line care of LBP
in the community pharmacy setting and to evaluate the pharmacist-reported
usability and acceptance of the prototype system.METHODS: A cross-platform Web app for the Apple iPad was developed in
conjunction with academic and clinical experts using an iterative user-centered
design process during interface design, clinical reasoning, program
development, and evaluation. The CDSS was evaluated via one-to-one user-testing
with 5 community pharmacists (5 case vignettes each). Data were collected via
video recording, screen capture, survey instrument (system usability scale),
and direct observation.RESULTS: Pharmacists' agreement with CDSS-generated self-care
recommendations was 90% (18/20), with medicines recommendations was 100%
(25/25), and with referral advice was 88% (22/25; total 70 recommendations).
Pharmacists expressed uncertainty when screening for serious pathology in 40%
(10/25) of cases. Pharmacists requested more direction from the CDSS in
relation to automated prompts for user input and page navigation. Overall
system usability was rated as excellent (mean score 92/100, SD 6.5; 90th
percentile compared with similar systems), with acceptance rated as good to
excellent.CONCLUSIONS: A novel CDSS (high-fidelity prototype) to enhance pharmacist care
of LBP was developed, underpinned by clinical practice guidelines and informed
by a multidisciplinary team of experts. User-testing revealed a high level of
usability and acceptance of the prototype system, with suggestions to improve
interface prompts and information delivery. The small study sample limits the
generalizability of the findings but offers important insights to inform the
next stage of system development.
AB - BACKGROUND: People with low back pain (LBP) in the community often do not
receive evidence-based advice and management. Community pharmacists can play an
important role in supporting people with LBP as pharmacists are easily
accessible to provide first-line care. However, previous research suggests that
pharmacists may not consistently deliver advice that is concordant with
guideline recommendations and may demonstrate difficulty determining which
patients require prompt medical review. A clinical decision support system
(CDSS) may enhance first-line care of LBP, but none exists to support the
community pharmacist-client consultation.OBJECTIVE: This study aimed to develop a CDSS to guide first-line care of LBP
in the community pharmacy setting and to evaluate the pharmacist-reported
usability and acceptance of the prototype system.METHODS: A cross-platform Web app for the Apple iPad was developed in
conjunction with academic and clinical experts using an iterative user-centered
design process during interface design, clinical reasoning, program
development, and evaluation. The CDSS was evaluated via one-to-one user-testing
with 5 community pharmacists (5 case vignettes each). Data were collected via
video recording, screen capture, survey instrument (system usability scale),
and direct observation.RESULTS: Pharmacists' agreement with CDSS-generated self-care
recommendations was 90% (18/20), with medicines recommendations was 100%
(25/25), and with referral advice was 88% (22/25; total 70 recommendations).
Pharmacists expressed uncertainty when screening for serious pathology in 40%
(10/25) of cases. Pharmacists requested more direction from the CDSS in
relation to automated prompts for user input and page navigation. Overall
system usability was rated as excellent (mean score 92/100, SD 6.5; 90th
percentile compared with similar systems), with acceptance rated as good to
excellent.CONCLUSIONS: A novel CDSS (high-fidelity prototype) to enhance pharmacist care
of LBP was developed, underpinned by clinical practice guidelines and informed
by a multidisciplinary team of experts. User-testing revealed a high level of
usability and acceptance of the prototype system, with suggestions to improve
interface prompts and information delivery. The small study sample limits the
generalizability of the findings but offers important insights to inform the
next stage of system development.
U2 - 10.2196/17203
DO - 10.2196/17203
M3 - Article
C2 - 32390593
SN - 2291-9694
VL - 8
JO - JMIR Medical Informatics
JF - JMIR Medical Informatics
IS - 5
M1 - e17203
ER -