Scaling Lean in Primary Care: Impacts on System Performance

Lean redesigns in primary care improved workflow efficiencies, physician productivity, and overall satisfaction among patients, physicians, and staff, with no adverse effects on clinical quality.
Published Online: March 17, 2017
Dorothy Y. Hung, PhD; Michael I. Harrison, PhD; Meghan C. Martinez, MPH; and Harold S. Luft, PhD
ABSTRACT

Objectives:
We examined a wide range of performance outcomes after Lean methodology—a leading strategy to enhance efficiency and patient value—was implemented and scaled across all primary care clinics in a nonprofit, ambulatory care delivery system.

Study Design: Using a stepped wedge approach, we assessed changes associated with the phased introduction of Lean-based redesigns across 46 primary care departments in 17 different clinic locations. Longitudinal analysis of operational metrics included: workflow efficiency, physician productivity, operating expenses, clinical quality, and satisfaction among patients, physicians, and staff. 

Methods: We used interrupted time series analysis with generalized linear mixed models to estimate Lean impacts over time. Projected outcomes in the absence of changes (ie, counterfactuals) were compared with observed outcomes after Lean redesigns were implemented, and mean differences were assessed using 95% bias-corrected bootstrap confidence intervals (CIs).

Results: We observed systemwide improvements in workflow efficiencies (eg, 95% CI, 5.8-10.4) and physician productivity (95% CI, 3.9-27.2), with no adverse effects on clinical quality. Patient satisfaction increased with respect to access to care (95% CI, 15.2-20.7), handling of personal issues (95% CI, 2.1-6.9), and overall experience of care (95% CI, 11.0-17.0), but decreased with respect to interactions with care providers (95% CI, –13.4 to –5.7). Departmental operating costs decreased, and annual staff and physician satisfaction scores increased particularly among early adopters, with key improvements in employee engagement, connection to purpose, relationships with staff, and physician time spent working.

Conclusions: Lean redesigns can benefit primary care patients, physicians, and staff without negatively impacting the quality of clinical care. Study results may lead other delivery system leaders to innovate using Lean techniques and may further enhance support for Lean learning among public and private payers.

Am J Manag Care. 2017;23(3):161-168
Takeaway Points

Lean is emerging as a leading strategy to enhance efficiency and patient value. Using a stepped wedge design, we assessed changes associated with the phased introduction of Lean-based redesigns across 46 primary care departments in a nonprofit, ambulatory care delivery system. 
  • We observed systemwide improvements in workflow efficiencies, physician productivity, and patient satisfaction measures. 
  • Operating costs decreased, and staff and physician satisfaction scores increased in key domains, including employee engagement and physician time spent working. 
  • Study findings may lead other delivery system leaders to innovate using Lean techniques and may enhance support for Lean learning among public and private payers.
In the past decade, Lean methodology has emerged as one of the leading strategies for redesigning care to increase efficiency and patient value. Several prominent health system leaders have championed Lean’s potential contribution to reducing waste, enhancing quality, and facilitating patient and provider engagement.1-3 In the past several years, Lean has been highlighted by the National Academy of Medicine (formerly the Institute of Medicine) and the President’s Council of Advisors on Science and Technology as a powerful system approach.4,5 

Adapted from manufacturing, Lean is a change strategy with roots in continuous quality improvement. System leaders who adopt Lean provide frontline staff with training on how to use analytic tools and methods to identify and remedy sources of waste. In healthcare, waste is defined as anything that does not add value for patients or the process of delivering their care. Aided initially by Lean experts, staff members learn to pinpoint sources of waste and develop solutions to operational problems; these solutions often streamline work processes to enhance efficiency and workflow. Other aspects of Lean management include standardizing tasks to ensure reliability and coordination across roles and units, creating common baselines for measuring continuous improvements, and redefining roles to empower staff to improve quality and efficiency, as well as to accept shared responsibility for improving outcomes.6-8

Despite widespread interest and growing use, only a few articles and a handful of books provide empirical details on systemwide Lean initiatives.9-14 These were ambitious programs lasting 5 years or more, driven by visionary leaders who were also highly effective managers. However, most research on Lean in peer-reviewed journals reports on the effects of specific Lean interventions on a few selected metrics, typically in 1 or a few sites. Also, most studies examine inpatient settings or integrated systems in which incentives are aligned for improving efficiency,6,15,16 but the implications of such research for fee-for-service (FFS) primary care are unclear. Most of the work on Lean in healthcare is anecdotal or relies on weak before-and-after study designs, and published studies rarely provide information on Lean’s effects on overall care quality and satisfaction among patients and providers. 

We report here on a longitudinal study using a wide range of efficiency, quality, and satisfaction measures to assess the implementation of Lean-based redesigns as they were spread across primary care clinics in a large FFS ambulatory care delivery system. Executive leaders envisioned the Lean initiative as a systemwide transformation, which began with the redesign of existing work spaces and care processes in all primary care departments and clinic locations throughout the system. These redesigns were intended to improve the work environment and process of delivering care among physicians and staff and to achieve tangible improvements in patient experiences of care. 

Specifically, redesigns that were introduced as part of the Lean initiative included: 1) standardization of medical equipment, supplies, and health education materials in patient exam rooms; 2) redesign of patient call center functions; 3) co-location of physician and staff care teams in a shared workspace; and 4) redesign of care team workflows. Standardized workflows included daily morning huddles to review patient schedules, agenda setting with patients by the medical assistant (MA) at the start of each office visit, and retrieval by the MA of all incoming items (eg, patient messages, lab/imaging results, prescription refills, referral requests) from the physician’s electronic inbox to address tasks as appropriate or to prepare them for the physician’s attention.

The implementation of Lean redesigns was formally staged: first, they were developed and implemented in 1 pilot clinic, then refined in 3 “beta” test clinics, and finally, scaled to 13 remaining clinics across the system. Each clinic location housed 1 to 3 primary care departments (Family Medicine, Internal Medicine, and/or Pediatrics) for a total of 46 primary care departments in which Lean redesigns were introduced. 

METHODS

Performance Metrics and Data Sources

As indicated above, the implementation of Lean in primary care focused largely on efforts to improve workflow. Targeted improvements included reductions of physician time required for each patient encounter, with the aim to improve patient access to care. Reductions of other forms of waste during office encounters were also aimed to increase efficiency and productivity while reducing operating costs. It would not be acceptable, however, if Lean were to achieve these objectives at the expense of worsening clinical quality, patient satisfaction with services delivered, or physician and staff satisfaction. As the organization did not expend resources in developing major new metrics to monitor these outcomes, we relied on operational dashboards, billing and financial sources, scheduling systems, electronic health records (EHRs), and routinely administered surveys to study the effects of Lean implementation. The advantage in doing so is that we had longitudinal, uniformly collected measures across all clinics, both before and after Lean redesigns were implemented.

Workflow efficiency data were sourced from the EHRs and measured physicians’ timely completion of tasks associated with 4 types of patient encounters. These were the percentages of: 1) office visit charts closed within 2 hours of seeing the patient, 2) electronic reply to patient messages within 4 business hours, 3) prescription medications renewed within 4 business hours, and 4) telephoned patient care items resolved within 4 business hours. Physician productivity was measured by monthly work-relative value units (wRVUs) (restated to CMS 2012 valuation) per physician full-time equivalent (FTE) and per office visit. Departmental operating expenses, consisting mainly of nonphysician staff compensation and supply costs, per total RVU (tRVU), were calculated using data provided by the Finance department and adjusted for inflation using the Western Urban Consumer Price Index for medical care commodities.17 Clinical quality was assessed using pay-for-performance metrics routinely reported by the organization to the Integrated Healthcare Association (see the eAppendix, available at www.ajmc.com). Finally, physician, staff, and patient satisfaction data were collected by third-party survey administrators—the American Medical Group Association (physicians), Hay Group (staff), and Press-Ganey (patients). The physician and staff surveys are conducted annually, while Press-Ganey surveys are fielded to patients on an ongoing basis, with data aggregated by month.

To minimize the effects of turnover, metrics were based on physicians continuously employed during the study period. Continuous employment was defined as more than 5% FTE for at least two-thirds of the months both pre- and post-Lean implementation at a given clinic location. The number of qualifying months depended on when the clinic implemented Lean, with post-Lean periods ranging from 4 to 25 months. A total of 328 primary care physicians were included during the study period (2011-2014).

Statistical Analysis

We assessed the effects of implementing Lean redesigns using an interrupted time series. In such analyses, an outcome is monitored over time and may have “interruptions” following an intervention that can be modeled in a segmented regression.18 Because Lean was deployed in phases, the data were analyzed using a nonrandomized stepped wedge design with 1-way crossover; thus, the observation period began with all locations initially without exposure to the intervention, with sequential training and “crossover” of clinics from control to intervention groups, until all clinics were exposed by the end of the study period (Figure).

For most analyses, generalized linear mixed models were used with the physician-month as the unit of observation. Fixed effects included the terms used for the segmented regression and potential confounders, including covariates such as physicians’ scheduled clinic hours, the mean age of patients on a physician’s panel, and the proportion of new patient visits. The nested structure of physicians working in departments within clinic locations was accounted for using random effects in the models. The autocorrelation of repeated measures over time was accounted for using a first-order autoregressive R-side covariance structure. 

A projected value for each performance outcome in the absence of Lean was estimated as of the end of the observation period, adjusting for secular trends and the potential confounders described above. This counterfactual was compared with the observed values at the end of the study period after Lean redesigns had been implemented in all clinic locations. To determine whether the mean difference was statistically significant, a 95% bias-corrected bootstrap confidence interval (CI) was calculated using 2000 samples.19

Annual staff and physician satisfaction survey data were provided by vendors at aggregated levels to protect respondent confidentiality, so these data were analyzed at either the clinic or the overall system level. As physician satisfaction data were available at the clinic level, results were grouped by the 3 phases of Lean implementation. All data management and statistical analysis for all metrics were conducted using SAS version 9.3 (SAS Institute, Cary, North Carolina). 

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