The impact of e-prescribing on prescriber and staff time in ... - PowerPoint by OQ4WiL

VIEWS: 7 PAGES: 19

									The impact of e-prescribing on
 prescriber and staff time in
   ambulatory care clinics:
     A time-motion study
 W Hollingworth, EB Devine, RN Hansen, BA
 Comstock, JL Wilson-Norton, NM Lawless, A
         Fisk, KL Tharp, SD Sullivan

         AHRQ HIT Grant #: 1 UC1 HS15319-01


   Department of Pharmacy, University of Washington &
         The Everett Clinic, Everett, Washington
        The Everett Clinic
• Physician owned and managed multi-specialty
  integrated health-system with a 79-year history
• 13 locations; 60 clinics
• Ancillary services
• 225 Physicians/1,500+ Employees
• 200,000 patients
• 600,000 ambulatory visits annually
• 2.5 Million Rx annually
The Everett Clinic’s e-prescribing system
• Internally-developed EMR began in 1995: charts,
  labs and imaging reports
• e-prescribing implemented beginning in 2003
• Features of e-prescribing system
   – Write new prescriptions (output: fax/print)
   – Refill prescriptions
   – Optimizes choice of medication
   – Automatically generates medication list as prescriptions are
     written
   – Pediatric antibiotic dosing by weight
• Utilizes subscription to commercial drug database as
  back end
• Builds patient drug database, improving disease
  management
           AHRQ HIT Grant
            Specific Aims
• Evaluate impact on medication errors and
  adverse drug events
• Evaluate impact on human factors
  – Focus groups
  – Survey assessing readiness to adopt IT
• Measure impact on workload
  – Process metrics (chart pulls, Rx written)
  – Time-motion study
           AHRQ HIT Grant
            Specific Aims
• Evaluate impact on medication errors and
  adverse drug events
• Evaluate impact on human factors
  – Focus groups
  – Survey assessing readiness to adopt IT
• Measure impact on workload
  – Process metrics (chart pulls, Rx written)
  – Time-motion study
    Time-motion: Study Aim



Evaluate whether the implementation of e-
  prescribing was at least time-neutral for
      physicians and staff members
 Time-motion: Study Design
• Research Coordinator shadowed
  Physicians & Staff after training period
• 3 locations at different stages of e-
  prescribing implementation
• Over a 4 hour shift (8am -12 noon, or
  1pm-5pm)
• With consent of clinician & patient
     Time-motion: Study Design
         Controlled ‘before and after’ study
                    Before                       After
Clinic         Date      Rx System     Date        Rx System

Silver Lake Feb-Mar 05     Paper      3rd/ 4th      Exam Room
                                      Quarter        Desktop
                                       2006
Harbour        Aug 05     MD office   3rd/ 4th      Exam Room
Pointe                    Desktop     Quarter        Desktop
                                       2006
Snohomish     Nov 05 –    Wireless    3rd/ 4th      Exam Room
               Jan 06     Laptop      Quarter        Desktop
                                       2006
     Time-motion: Data Collection



All timing data collected with
         Timer ProTM

http://performance-measurement.com/
  Time-motion: Data Elements
Major Category                Minor Sub-categories
   Computer           New Rx; Renew Rx; Fax Rx; Article; Drug Ref; e-
                       mail; Lit search; Look Up Data; Review results;
                      Chart Pull; Review Dictation; Writing PEF; Writing
                                          Order; Other
    Writing           New Rx; Renew Rx; Letter; Notes/Charts; Orders;
                                         Other
    Phone              Getting Results; FAX; Paging; Patient; Personal;
                      Scheduling test; New Rx; Prior Authorization; Other

               Other Major Categories
        Looking For                                Forms
         Procedure                             Examine / Read
           Talking                                 Walking
      Unable to observe                        Miscellaneous

     Categories based on Overhage et al JAMIA 2001: 361-371
Time-motion: Data Output
             Time-motion: Results
                   Silver Lake        Harbour        Snohomish
                                       Pointe
# of Prescribers         8               11               8
Tracked
Specialty          3 Family Prac    4 Family Prac    4 Family Prac
                    1 Pediatrics     2 Pediatrics     1 Pediatrics
                       2 WIC            2 WIC            1 WIC
                   2 Int Medicine   3 Int Medicine     2 Int Med
% Female            38% (3/8)       27% (3/11)        63% (5/8)
Mean Age               43.9             46.0             41.3
Average Hours          3.54             3.61             3.44
Observed
# of Staff         11 (3.53 hrs)    21 (3.63 hrs)    10 (3.77 hrs)
Tracked
 Time-motion: Overall Activity
     Types (Prescribers)
                          Silver Lake        Harbour        Snohomish
                                              Pointe
Talking (pt or family)        33%              30%                35%
Examine Patient               15%              8%                 8%
Writing*                      15%              9%                 9%
Talking Other                 10%              20%                14%
Examine/Read Other            10%              9%                 10%
Computer Tasks*               6%               12%                13%
All Other                     12%              12%                10%

        *p<0.01; Chi-Squared test Silver Lake vs. Other Clinics
Time-motion: Prescribing Activity
         (Prescribers)
                           Silver Lake      Harbour       Snohomish
                                             Pointe
  % Rx events written         68/68           26/63          11/52
  on paper                   (100%)           (41%)          (21%)
  Time per Rx event*       47 seconds      42 seconds 71 seconds
  Time per paper-          47 seconds      38 seconds 66 seconds
  based Rx event
  Time per computer-           N/A         45 seconds 74 seconds
  based Rx event

  * Linear mixed effect model comparing Silver Lake with other two
  clinics. Mean difference = 9 seconds; p=0.31
 Time-motion: Overall Activity
    Types (Support Staff)
                            Silver Lake        Harbour        Snohomish
                                                Pointe
Computer*                       17%              24%                18%
Talking Other                   17%              19%                12%

Phone Patient                   8%               6%                 6%
Walking                         8%               8%                 8%
Phone Other                     8%               11%                8%
Examine/Read Other              8%               13%                10%
Writing                         7%               7%                 4%
All Other                       27%              12%                33%
          *p<0.01; Chi-Squared test Silver Lake vs. Other Clinics
Time-motion: Prescribing Activity
        (Support Staff)

               Preliminary Analysis
                         Silver Lake   Harbour   Snohomish
                                        Pointe
  % Rx events written      21/22        5/132    1/25 (4%)
  on paper / via phone     (95%)        (4%)
  Time per Rx event         111           73     78 seconds
                          seconds      seconds
        Selected Previous Work in
            Ambulatory Care

Author                Year Setting                   Outcome
Pizziferri et al. J   2005   Before & After EHR      Mean time per
Biomed Inform.               at 5 primary care       patient fell by 30
                             clinics (n=20 MDs)      seconds; NS
Overhage et al.       2001   RCT of POE at 11        Mean time per
JAMIA                        primary care clinics    patient increased
                             (n=34 MDs)              by 26 seconds; NS
Makoul et al.         2001   Cross-sectional      Mean time per
JAMIA                        study of POE at 1    patient increased
                             GIM clinic (n=6 MDs) by 3 minutes; NS


For a more comprehensive review see Poissant et al. JAMIA 2005.
           Limitations

•   Currently cross-sectional data
•   Small numbers of clinicians
•   Limited to specific time periods
    during the day
•   Limited details on type of Rx,
    number of Rx per script etc.
          Conclusions
•   e-prescribing successfully
    implemented at 2 clinics and used
    for >=60% of prescriptions
•   e-prescribing has minimal impact
    on prescriber time (<10 seconds
    per event)
•   e-prescribing may have small
    benefit for support staff time

								
To top