Using Process Analysis to Assess the Impact of Medical Education on the Delivery of Pain Services

Williams, Kayode; Chambers, Chester; Dada, Maqbool; Hough, Douglas E.; Aron, Ravi; Ulatowski, John A.

doi:10.1097/aln.0b013e31824a88d0

Cited by 6 publications

(12 citation statements)

References 16 publications

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“…Appt.=appointment. Adapted with permission from Lippincott Williams and Wilken/Wolters Kluwer Health 14. Promotional and commercial use of the material in print, digital or mobile device format is prohibited without the permission from the publisher Lippincott Williams & Wilkins.…”

Section: Methodsmentioning

confidence: 99%

“…Type 1=patients who come to the clinic for an initial visit; type 2=patients who come for a follow-up visit; type 3=patients who come for services routinely handled by the physician's assistant (P/A). Reproduced with permission 14. Promotional and commercial use of the material in print, digital or mobile device format is prohibited without the permission from the publisher Lippincott Williams & Wilkins.…”

Section: Methodsmentioning

confidence: 99%

“…These parameters were used as inputs to a discrete event simulation of the clinic that was carried out with ExtendSim, V.7.0 (Imagine That Inc, San Jose, California, USA). This approach has a long history in the study of outpatient clinics 14 16 17…”

Section: Methodsmentioning

confidence: 99%

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Patient punctuality and clinic performance: observations from an academic-based private practice pain centre: a prospective quality improvement study

et al. 2014

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ObjectivesThe aim of this study was to examine the effects of an intervention to alter patient unpunctuality. The major hypothesis was that the intervention will change the distribution of patient unpunctuality by decreasing patient tardiness and increasing patient earliness.DesignProspective Quality Improvement.SettingSpecialty Pain Clinic in suburban Baltimore, Maryland, USA.ParticipantsThe patient population ranged in age from 18 to 93 years. All patients presenting to the clinic during the study period were included in the study. The average monthly volume was 86.2 (SD=13) patients. A total of 1500 patient visits were included in this study.InterventionsWe tracked appointment times and patient arrival times at an ambulatory pain clinic. An intervention was made in which patients were informed that tardy patients would not be seen and would be rescheduled. This policy was enforced over a 12-month period.Primary and secondary outcome measuresThe distribution of patient unpunctuality was developed preintervention and at 12 months after implementation. Distribution parameters were used as inputs to a discrete event simulation to determine effects of the change in patient unpunctuality on clinic delay.ResultsData regarding patient unpunctuality were gathered by direct observation before and after implementation of the intervention. The mean unpunctuality changed from −20.5 min (110 observations, SD=1.7) preintervention to −23.2 (169, 1.2) at 1 month after the intervention, −23.8 min (69, 1.8) at 6 months and −25.0 min (71, 1.2) after 1 year. The unpunctuality 12 months after initiation of the intervention was significantly different from that prior to the intervention (p<0.05).ConclusionsPhysicians and staff are able to alter patient arrival patterns to reduce patient unpunctuality. Reducing tardiness improves some measures of clinic performance, but may not always improve waiting times. Accommodating early arriving patients does serve to improve clinic performance.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Patient punctuality and clinic performance: observations from an academic-based private practice pain centre: a prospective quality improvement study

et al. 2014

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“…Published studies have been limited in size and have had conflicting findings. For example, 2 studies 11,12 found that the presence of trainees was associated with improved clinical efficiency by shortening patient wait times, whereas another study 13 found that trainees were associated with lengthened patient wait times and overall appointment times. This issue has implications for clinical efficiency and physician reimbursement models, particularly in academic medical centers.…”

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confidence: 99%

Association of the Presence of Trainees With Outpatient Appointment Times in an Ophthalmology Clinic

et al. 2018

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IMPORTANCE Physicians face pressure to improve clinical efficiency, particularly with electronic health record (EHR) adoption and gradual shifts toward value-based reimbursement models. These pressures are especially pronounced in academic medical centers, where delivery of care must be balanced with medical education. However, the association of the presence of trainees with clinical efficiency in outpatient ophthalmology clinics is not known. OBJECTIVE To quantify the association of the presence of trainees (residents and fellows) and efficiency in an outpatient ophthalmology clinic. DESIGN, SETTING, AND PARTICIPANTS This single-center cohort study was conducted from January 1 through December 31, 2014, at an academic department of ophthalmology. Participants included 49 448 patient appointments with 33 attending physicians and 40 trainees. EXPOSURES Presence vs absence of trainees in an appointment or clinic session, as determined by review of the EHR audit log. MAIN OUTCOMES AND MEASURES Patient appointment time, as determined by time stamps in the EHR clinical data warehouse. Linear mixed models were developed to analyze variability among clinicians and patients. RESULTS Among the 33 study physicians (13 women [39%] and 20 men [61%]; median age, 44 years [interquartile range, 39-53 years]), appointments with trainees were significantly longer than appointments in clinic sessions without trainees (mean [SD], 105.0 [55.7] vs 80.3 [45.4] minutes; P < .001).The presence of a trainee in a clinic session was associated with longer mean appointment time, even in appointments for which the trainee was not present (mean [SD], 87.2 [49.2] vs 80.3 [45.4] minutes; P < .001). Among 33 study physicians, 3 (9%) had shorter mean appointment times when a trainee was present, 1 (3%) had no change, and 29 (88%) had longer mean appointment times when a trainee was present. Linear mixed models showed the presence of a resident was associated with a lengthening of appointment time of 17.0 minutes (95% CI, 15.6-18.5 minutes; P < .001), and the presence of a fellow was associated with a lengthening of appointment time of 13.5 minutes (95% CI, 12.3-14.8 minutes; P < .001).CONCLUSIONS AND RELEVANCE Presence of trainees was associated with longer appointment times, even for patients not seen by a trainee. Although numerous limitations to this study design might affect the interpretation of the findings, these results highlight a potential challenge of maintaining clinical efficiency in academic medical centers and raise questions about physician reimbursement models.

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“…Third, this case can be used along with the DES models provided which have been calibrated in the actual clinics and used in detailed research on clinic performance (Williams et al 2012(Williams et al , 2014(Williams et al , 2015Chambers et al 2016) Instructors can use the data and DES models in a variety of ways, depending on the emphasis of the course and background of the student population. This is useful because DES models are becoming increasingly common as elements of quality improvement (QI) efforts in healthcare settings (Jacobson et al 2006).…”

Section: Existing Case Studiesmentioning

confidence: 99%

Case Article—Miller Pain Treatment Center—Eastern Hospital Outpatient Center

Chambers¹,

Williams²

2017

INFORMS Transactions on Education

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Abstract. Introductory courses in operations management typically introduce students to process analysis and queuing theory. We apply these tools to consider patient flows in an outpatient clinic where processes are made more complex by inclusion of the teaching mission of an Academic Medical Center. The case narrative deals with a physician who moved his practice from a setting with no teaching mission to the academic setting. This created a natural experiment because he began treating the same patients using a different process flow. Students are asked to use data collected at both settings to compare and contrast these flows. The protagonist weighs options designed to improve an appointment schedule, change patient punctuality, and introduce a type of pre-processing of patients. Evaluation of these proposals calls for a different style of analysis. Students are introduced to the use of discrete event simulation to address such questions. Simulation models are provided corresponding to the two clinic settings. This allows students to conduct and learn from virtual experiments using calibrated models. The case fills a need for material that covers issues in healthcare delivery, which the basic tools of process analysis and queuing theory are insufficient to fully address.

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Using Process Analysis to Assess the Impact of Medical Education on the Delivery of Pain Services

Cited by 6 publications

References 16 publications

Patient punctuality and clinic performance: observations from an academic-based private practice pain centre: a prospective quality improvement study

Patient punctuality and clinic performance: observations from an academic-based private practice pain centre: a prospective quality improvement study

Association of the Presence of Trainees With Outpatient Appointment Times in an Ophthalmology Clinic

Case Article—Miller Pain Treatment Center—Eastern Hospital Outpatient Center

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