Between-visit workload in primary care

Intensity, Characteristics, and Factors Associated With Receipt of Care Coordination Among High-Risk Veterans in the Veterans Health Administration

BACKGROUND

The Veterans Health Administration (VHA) has initiatives underway to enhance the provision of care coordination (CC), particularly among high-risk Veterans. Yet, evidence detailing the characteristics of and who receives VHA CC is limited.

OBJECTIVES

We examined intensity, timing, setting, and factors associated with VHA CC among high-risk Veterans.

RESEARCH DESIGN

We conducted a retrospective observational cohort study, following Veterans for 1 year after being identified as high-risk for hospitalization or mortality, to characterize their CC. Demographic and clinical factors predictive of CC were identified via multivariate logistic regression.

SUBJECTS

A total of 1,843,272 VHA-enrolled high-risk Veterans in fiscal years 2019-2021.

MEASURES

We measured 5 CC variables during the year after Veterans were identified as high risk: (1) receipt of any service, (2) number of services received, (3) number of days to first service, (4) number of days between services, and (5) type of visit during which services were received.

RESULTS

Overall, 31% of high-risk Veterans in the sample received CC during one-year follow-up. Among Veterans who received ≥1 service, a median of 2 [IQR (1, 6)] services were received. Among Veterans who received ≥2 services, there was a median of 26 [IQR (10, 57)] days between services. Most services were received during outpatient psychiatry (46%) or medicine (16%) visits. Veterans' sociodemographic and clinical characteristics were associated with receipt of CC.

CONCLUSIONS

A minority of Veterans received CC in the year after being identified as high-risk, and there was variation in intensity, timing, and setting of CC. Research is needed to examine the fit between Veterans' CC needs and preferences and VHA CC delivery.

Primary Care Physicians' Experiences With and Adaptations to Time Constraints

Importance

The primary care workforce shortage is significant and persistent, with organizational and policy leaders urgently seeking interventions to enhance retention and recruitment. Time constraints are a valuable focus for action; however, designing effective interventions requires deeper understanding of how time constraints shape employees' experiences and outcomes of work.

Objective

To examine how time constraints affect primary care physicians' work experiences and careers.

Design, Setting, and Participants

Between May 1, 2021, and September 31, 2022, US-based primary care physicians who trained in family or internal medicine were interviewed. Using qualitative analysis of in-depth interviews, this study examined how participants experience and adapt to time constraints during a typical clinic day, taking account of their professional and personal responsibilities. It also incorporates physicians' reflections on implications for their careers.

Main Outcomes and Measures

Thematic analysis of in-depth interviews and a measure of well-being (American Medical Association Mini-Z survey).

Results

Interviews with 25 primary care physicians (14 [56%] female and 11 [44%] male; median [range] age, 43 [34-63] years) practicing in 11 US states were analyzed. Two physicians owned their own practice, whereas the rest worked as employees. The participants represented a wide range of years in practice (range, 1 to ≥21), with 11 participants (44%) in their first 5 years. Physicians described that the structure of their work hours did not match the work that was expected of them. This structural mismatch between time allocation and work expectations created a constant experience of time scarcity. Physicians described having to make tradeoffs between maintaining high-quality patient care and having their work overflow into their personal lives. These experiences led to feelings of guilt, disillusionment, and dissatisfaction. To attempt to sustain long-term careers in primary care, many sought ways to see fewer patients.

Conclusions and Relevance

These findings suggest that organizational leaders must align schedules with work expectations for primary care physicians to mitigate physicians' withdrawal from work as a coping mechanism. Specific strategies are needed to achieve this realignment, including incorporating more slack into schedules and establishing realistic work expectations for physicians.

Primary Care Physician Gender and Electronic Health Record Workload

BACKGROUND

Prior research indicates that female physicians spend more time working in the electronic health record (EHR) than do male physicians.

OBJECTIVE

To examine gender differences in EHR usage among primary care physicians and identify potential causes for those differences.

DESIGN

Retrospective study of EHR usage by primary care physicians (PCPs) in an academic hospital system.

PARTICIPANTS

One hundred twenty-five primary care physicians INTERVENTIONS: N/A MAIN MEASURES: EHR usage including time spent working and volume of staff messages and patient messages.

KEY RESULTS

After adjusting for panel size and appointment volume, female PCPs spend 20% more time (1.9 h/month) in the EHR inbasket and 22% more time (3.7 h/month) on notes than do their male colleagues (p values 0.02 and 0.04, respectively). Female PCPs receive 24% more staff messages (9.6 messages/month), and 26% more patient messages (51.5 messages/month) (p values 0.03 and 0.004, respectively). The differences in EHR time are not explained by the percentage of female patients in a PCP's panel.

CONCLUSIONS

Female physicians spend more time working in their EHR inbaskets because both staff and patients make more requests of female PCPs. These differential EHR burdens may contribute to higher burnout rates in female PCPs.

The Underuse of Medicare's Prevention and Coordination Codes in Primary Care : A Cross-Sectional and Modeling Study

BACKGROUND

Efforts to better support primary care include the addition of primary care-focused billing codes to the Medicare Physician Fee Schedule (MPFS).

OBJECTIVE

To examine potential and actual use by primary care physicians (PCPs) of the prevention and coordination codes that have been added to the MPFS.

DESIGN

Cross-sectional and modeling study.

SETTING

Nationally representative claims and survey data.

PARTICIPANTS

Medicare patients.

MEASUREMENTS

Frequency of use and estimated Medicare revenue involving 34 billing codes representing prevention and coordination services for which PCPs could but do not necessarily bill.

RESULTS

Eligibility among Medicare patients for each service ranged from 8.8% to 100%. Among eligible patients, the median use of billing codes was 2.3%, even though PCPs provided code-appropriate services to more patients, for example, to 5.0% to 60.6% of patients eligible for prevention services. If a PCP provided and billed all prevention and coordination services to half of all eligible patients, the PCP could add to the practice's annual revenue $124 435 (interquartile range [IQR], $30 654 to $226 813) for prevention services and $86 082 (IQR, $18 011 to $154 152) for coordination services.

LIMITATION

Service provision based on survey questions may not reflect all billing requirements; revenues do not incorporate the compliance, billing, and opportunity costs that may be incurred when using these codes.

CONCLUSION

Primary care physicians forego considerable amounts of revenue because they infrequently use billing codes for prevention and coordination services despite having eligible patients and providing code-appropriate services to some of those patients. Therefore, creating additional billing codes for distinct activities in the MPFS may not be an effective strategy for supporting primary care.

PRIMARY FUNDING SOURCE

National Institute on Aging.

A time motion study of manual versus artificial intelligence methods for wound assessment

Objectives

This time-motion study explored the amount of time clinicians spent on wound assessments in a real-world environment using wound assessment digital application utilizing Artificial Intelligence (AI) vs. manual methods. The study also aimed at comparing the proportion of captured quality wound images on the first attempt by the assessment method.

Methods

Clinicians practicing at Valley Wound Center who agreed to join the study were asked to record the time needed to complete wound assessment activities for patients with active wounds referred for a routine evaluation on the follow-up days at the clinic. Assessment activities included: labelling wounds, capturing images, measuring wounds, calculating surface areas, and transferring data into the patient’s record.

Results

A total of 91 patients with 115 wounds were assessed. The average time to capture and access wound image with the AI digital tool was significantly faster than a standard digital camera with an average of 62 seconds (P<0.001). The digital application was significantly faster by 77% at accurately measuring and calculating the wound surface area with an average of 45.05 seconds (P<0.001). Overall, the average time to complete a wound assessment using Swift was significantly faster by 79%. Using the AI application, the staff completed all steps in about half of the time (54%) normally spent on manual wound evaluation activities. Moreover, acquiring acceptable wound image was significantly more likely to be achieved the first time using the digital tool than the manual methods (92.2% vs. 75.7%, P<0.004).

Conclusions

Using the digital assessment tool saved significant time for clinicians in assessing wounds. It also successfully captured quality wound images at the first attempt.

Effective Hearing Loss Screening in Primary Care: The Early Auditory Referral-Primary Care Study

PURPOSE

Hearing loss, the second most common disability in the United States, is under-diagnosed and under-treated. Identifying it in early stages could prevent its known substantial adverse outcomes.

METHODS

A multiple baseline design was implemented to assess a screening paradigm for identifying and referring patients aged ≥55 years with hearing loss at 10 family medicine clinics in 2 health systems. Patients completed a consent form and the Hearing Handicap Inventory for the Elderly (HHI). An electronic alert prompted clinicians to screen for hearing loss during visits.

RESULTS

The 14,877 eligible patients during the study period had 36,701 encounters. Referral rates in the family medicine clinics increased from a baseline rate of 3.2% to 14.4% in 1 health system and from a baseline rate of 0.7% to 4.7% in the other. A general medicine comparison group showed referral rate increase from the 3.0% baseline rate to 3.3%. Of the 5,883 study patients who completed the HHI 25.2% (n=1,484) had HHI scores suggestive of hearing loss; those patients had higher referral rates, 28% vs 9.2% (P <.001). Of 1,660 patients referred for hearing testing, 717 had audiology data available for analysis: 669 (93.3%) were rated appropriately referred and 421 (58.7%) were considered hearing aid candidates. Overall, 71.5% of patients contacted felt their referral was appropriate.

CONCLUSION

An electronic alert used to remind clinicians to ask patients aged ≥55 years about hearing loss significantly increased audiology referrals for at-risk patients. Audiologic and audiogram data support the effectiveness of the prompt. Clinicians should consider adopting this method to identify patients with hearing loss to reduce its known and adverse sequelae.

What Is the Optimal Primary Care Panel Size?: A Systematic Review

BACKGROUND

Primary care for a panel of patients is a central component of population health, but the optimal panel size is unclear.

PURPOSE

To review evidence about the association of primary care panel size with health care outcomes and provider burnout.

DATA SOURCES

English-language searches of multiple databases from inception to October 2019 and Google searches performed in September 2019.

STUDY SELECTION

English-language studies of any design, including simulation models, that assessed the association between primary care panel size and safety, efficacy, patient-centeredness, timeliness, efficiency, equity, or provider burnout.

DATA EXTRACTION

Independent, dual-reviewer extraction; group consensus rating of certainty of evidence.

DATA SYNTHESIS

Sixteen hypothesis-testing studies and 12 simulation modeling studies met inclusion criteria. All but 1 hypothesis-testing study were cross-sectional assessments of association. Three studies each provided low-certainty evidence that increasing panel size was associated with no or modestly adverse effects on patient-centered and effective care. Eight studies provided low-certainty evidence that increasing panel size was associated with variable effects on timely care. No studies assessed the effect of panel size on safety, efficiency, or equity. One study provided very-low-certainty evidence of an association between increased panel size and provider burnout. The 12 simulation studies evaluated 5 models; all used access as the only outcome of care. Five and 2 studies, respectively, provided moderate-certainty evidence that adjusting panel size for case mix and adding clinical conditions to the case mix resulted in better access.

LIMITATION

No studies had concurrent comparison groups, and published and unpublished studies may have been missed.

CONCLUSION

Evidence is insufficient to make evidence-based recommendations about the optimal primary care panel size for achieving beneficial health outcomes.

PRIMARY FUNDING SOURCE

Veterans Affairs Quality Enhancement Research Initiative.

EHR audit logs: A new goldmine for health services research?

A byproduct of the transition to electronic health records (EHRs) is the associated observational data that capture EHR users' granular interactions with the medical record. Often referred to as audit log data or event log data, these datasets capture and timestamp user activity while they are logged in to the EHR. These data - alone and in combination with other datasets - offer a new source of insights, which cannot be gleaned from claims data or clinical data, to support health services research and those studying healthcare processes and outcomes. In this commentary, we seek to promote broader awareness of EHR audit log data and to stimulate their use in many contexts. We do so by describing EHR audit log data and offering a framework for their potential uses in quality domains (as defined by the National Academy of Medicine). The framework is illustrated with select examples in the safety and efficiency domains, along with their accompanying methodologies, which serve as a proof of concept. This article also discusses insights and challenges from working with EHR audit log data. Ensuring that researchers are aware of such data, and the new opportunities they offer, is one way to assure that our healthcare system benefits from the digital revolution.

Use of Chronic Care Management Codes for Medicare Beneficiaries: a Missed Opportunity?

BACKGROUND

Physicians spend significant time outside of regular office visits caring for complex patients, and this work is often uncompensated. In 2015, the Centers for Medicare & Medicaid Services (CMS) introduced a billing code for care coordination between office visits for beneficiaries with multiple chronic conditions.

OBJECTIVE

Characterize use of the Chronic Care Management (CCM) code in New England in 2015.

DESIGN

Retrospective observational analysis.

PARTICIPANTS

All Medicare fee-for-service beneficiaries in New England continuously enrolled in Parts A and B in 2015.

INTERVENTION

None.

MAIN MEASURES

The primary outcome was the number of beneficiaries with a CCM claim per 1000 eligible beneficiaries. Secondary outcomes included the total number of CCM claims, total reimbursement, mean number of claims per beneficiary, and beneficiary characteristics independently associated with receiving CCM services.

KEY RESULTS

Of the more than two million Medicare fee-for-service beneficiaries in New England, almost 1.7 million were potentially eligible for CCM services. Among eligible beneficiaries, 10,951 (0.65%) had a CCM claim in 2015. Massachusetts had the highest penetration of CCM use (9.40 claims per 1000 eligible beneficiaries); Vermont had the lowest (0.54 claims per 1000 eligible beneficiaries). Mean reimbursement per physician was $1745.98. Age, race/ethnicity, dual-eligible status, income, number of chronic conditions, and state of residence were associated with receiving CCM services in an adjusted model.

CONCLUSIONS

The CCM code is likely underutilized in New England; the program may therefore not be achieving its intended goal of encouraging consistent, team-based chronic care management for Medicare's most complex beneficiaries. Or practices may be foregoing reimbursement for care coordination that they are already providing. Recently implemented revisions may improve uptake of CCM services; it will be important to compare our results with future utilization.

Electronic Health Record Logs Indicate That Physicians Split Time Evenly Between Seeing Patients And Desktop Medicine

Time spent by physicians is a key resource in health care delivery. This study used data captured by the access time stamp functionality of an electronic health record (EHR) to examine physician work effort. This is a potentially powerful, yet unobtrusive, way to study physicians' use of time. We used data on physicians' time allocation patterns captured by over thirty-one million EHR transactions in the period 2011-14 recorded by 471 primary care physicians, who collectively worked on 765,129 patients' EHRs. Our results suggest that the physicians logged an average of 3.08 hours on office visits and 3.17 hours on desktop medicine each day. Desktop medicine consists of activities such as communicating with patients through a secure patient portal, responding to patients' online requests for prescription refills or medical advice, ordering tests, sending staff messages, and reviewing test results. Over time, log records from physicians showed a decline in the time allocated to face-to-face visits, accompanied by an increase in time allocated to desktop medicine. Staffing and scheduling in the physician's office, as well as provider payment models for primary care practice, should account for these desktop medicine efforts.

Initial Results of the Early Auditory Referral-Primary Care (EAR-PC) Study

INTRODUCTION

Hearing loss (HL) is the second most common disability in the U.S., yet is clinically underdiagnosed. To manage its common adverse psychosocial and cognitive outcomes, early identification of HL must be improved.

METHODS

A feasibility study conducted to increase screening for HL and referral of patients aged ≥55 years arriving at two family medicine clinics. Eligible patients were asked to complete a self-administered consent form and the Hearing Handicap Inventory (HHI). Independently, clinicians received a brief educational program after which an electronic clinical prompt (intervention) alerted them (blinded to HHI results) to screen for HL during applicable patient visits. Pre- and post-intervention differences were analyzed to assess the proportion of patients referred to audiology and those diagnosed with HL (primary outcomes) and the audiology referral appropriateness (secondary outcome). Referral rates for those who screened positive for HL on the HHI were compared with those who scored negatively.

RESULTS

There were 5,520 eligible patients during the study period, of which 1,236 (22.4%) consented. After the intervention's implementation, audiology referral rates increased from 1.2% to 7.1% (p<0.001). Overall, 293 consented patients (24%) completed the HHI and scored >10, indicating probable HL. Of these 293 patients, 28.0% were referred to audiology versus only 7.4% with scores <10 (p<0.001). Forty-two of the 54 referred patients seen by audiology were diagnosed with HL (78%). Overall, the diagnosis of HL on problem lists increased from 90 of 4,815 patients (1.9%) at baseline to 163 of 5,520 patients (3.0%, p<0.001) over only 8 months.

CONCLUSIONS

The electronic clinical prompt significantly increased audiology referrals for at-risk patients for HL in two family medicine clinics. Larger-scale studies are needed to address the U.S. Preventive Services Task Force call to assess the long-term impact of HL screening in community populations.

Defining Team Effort Involved in Patient Care from the Primary Care Physician's Perspective

BACKGROUND

A better understanding of the attributes of patients who require more effort to manage may improve risk adjustment approaches and lead to more efficient resource allocation, improved patient care and health outcomes, and reduced burnout in primary care clinicians.

OBJECTIVE

To identify and characterize high-effort patients from the physician's perspective.

DESIGN

Cohort study.

PARTICIPANTS

Ninety-nine primary care physicians in an academic primary care network.

MAIN MEASURES

From a list of 100 randomly selected patients in their panels, PCPs identified patients who required a high level of team-based effort and patients they considered complex. For high-effort patients, PCPs indicated which factors influenced their decision: medical/care coordination, behavioral health, and/or socioeconomic factors. We examined differences in patient characteristics based on PCP-defined effort and complexity.

KEY RESULTS

Among 9594 eligible patients, PCPs classified 2277 (23.7 %) as high-effort and 2676 (27.9 %) as complex. Behavioral health issues were the major driver of effort in younger patients, while medical/care coordination issues predominated in older patients. Compared to low-effort patients, high-effort patients were significantly (P < 0.01 for all) more likely to have higher rates of medical (e.g. 23.2 % vs. 6.3 % for diabetes) and behavioral health problems (e.g. 9.8 % vs. 2.9 % for substance use disorder), more frequent primary care visits (10.9 vs. 6.0 visits), and higher acute care utilization rates (25.8 % vs. 7.7 % for emergency department [ED] visits and 15.0 % vs. 3.9 % for hospitalization). Almost one in five (18 %) patients who were considered high-effort were not deemed complex by the same PCPs.

CONCLUSIONS

Patients defined as high-effort by their primary care physicians, not all of whom were medically complex, appear to have a high burden of psychosocial issues that may not be accounted for in current chronic disease-focused risk adjustment approaches.

Team Process Variation Across Diabetes Quality of Care Trajectories

Conceptual frameworks in health care do not address mechanisms whereby teamwork processes affect quality of care. We seek to fill this gap by applying a framework of teamwork processes to compare different patterns of primary care performance over time. We thematically analyzed 114 primary care staff interviews across 17 primary care clinics. We purposefully selected clinics using diabetes quality of care over 3 years using four categories: consistently high, improving, worsening, and consistently low. Analyses compared participant responses within and between performance categories. Differences were observed among performance categories for action processes (monitoring progress and coordination), transition processes (goal specification and strategy formulation), and interpersonal processes (conflict management and affect management). Analyses also revealed emergent concepts related to psychological and organizational context that were reported to affect team processes. This study is a first step toward a comprehensive model of how teamwork processes might affect quality of care.

The myth of standardized workflow in primary care

OBJECTIVE

Primary care efficiency and quality are essential for the nation's health. The demands on primary care physicians (PCPs) are increasing as healthcare becomes more complex. A more complete understanding of PCP workflow variation is needed to guide future healthcare redesigns.

METHODS

This analysis evaluates workflow variation in terms of the sequence of tasks performed during patient visits. Two patient visits from 10 PCPs from 10 different United States Midwestern primary care clinics were analyzed to determine physician workflow. Tasks and the progressive sequence of those tasks were observed, documented, and coded by task category using a PCP task list. Variations in the sequence and prevalence of tasks at each stage of the primary care visit were assessed considering the physician, the patient, the visit's progression, and the presence of an electronic health record (EHR) at the clinic.

RESULTS

PCP workflow during patient visits varies significantly, even for an individual physician, with no single or even common workflow pattern being present. The prevalence of specific tasks shifts significantly as primary care visits progress to their conclusion but, notably, PCPs collect patient information throughout the visit.

DISCUSSION

PCP workflows were unpredictable during face-to-face patient visits. Workflow emerges as the result of a "dance" between physician and patient as their separate agendas are addressed, a side effect of patient-centered practice.

CONCLUSIONS

Future healthcare redesigns should support a wide variety of task sequences to deliver high-quality primary care. The development of tools such as electronic health records must be based on the realities of primary care visits if they are to successfully support a PCP's mental and physical work, resulting in effective, safe, and efficient primary care.

A Qualitative Analysis of Physician Perspectives on Missed and Delayed Outpatient Diagnosis: The Focus on System-Related Factors

BACKGROUND

Delayed and missed diagnoses lead to significant patient harm. Because physician actions are fundamental to the outpatient diagnostic process, a study was conducted to explore physician perspectives on diagnosis.

METHODS

As part of a quality improvement initiative, an integrated health system conducted six physician focus groups in 2004 and 2005. The focus groups included questions about the process of diagnosis, specific factors contributing to missed diagnosis, use of guidelines, atypical vs. typical presentations of disease, diagnostic tools, and follow-up, all with regard to delays in the diagnostic process. The interviews were analyzed (1) deductively, with application of the Systems Engineering Initiative for Patient Safety (SEIPS) model, which addresses systems design, quality management, job design, and technology implementations that affect safety-related patient and organizational and/or staff outcomes, and (2) inductively, with identification of novel themes using content analysis.

RESULTS

A total of 25 physicians participated in the six focus groups, which yielded 12 hours of discussion. Providers identified multiple barriers to timely and accurate diagnosis, including organizational culture, information availability, and communication factors.

CONCLUSIONS

Multiple themes relating to each of the participants in the diagnostic process-health system, provider, and patient-emerged. Concerns about health system structure and providers' interactions with one another and with patients far exceeded discussion of the cognitive factors that might affect the diagnostic process. The results suggest that, at least in physicians' views, improving the diagnostic process requires attention to the organization of the health system in addition to the cognitive aspects of diagnosis.

What keeps family physicians busy in Portugal? A multicentre observational study of work other than direct patient contacts

OBJECTIVES

To quantify the time spent by family physicians (FP) on tasks other than direct patient contact, to evaluate job satisfaction, to analyse the association between time spent on tasks and physician characteristics, the association between the number of tasks performed and physician characteristics and the association between time spent on tasks and job satisfaction.

DESIGN

Cross-sectional, using time-and-motion techniques. Two workdays were documented by direct observation. A significance level of 0.05 was adopted.

SETTING

Multicentric in 104 Portuguese family practices.

PARTICIPANTS

A convenience sample of FP, with lists of over 1000 patients, teaching senior medical students and first-year family medicine residents in 2012, was obtained. Of the 217 FP invited to participate, 155 completed the study.

MAIN OUTCOMES MEASURED

Time spent on tasks other than direct patient contact and on the performance of more than one task simultaneously, the number of direct patient contacts in the office, the number of indirect patient contacts, job satisfaction, demographic and professional characteristics associated with time spent on tasks and the number of different tasks performed, and the association between time spent on tasks and job satisfaction.

RESULTS

FP (n=155) spent a mean of 143.6 min/day (95% CI 135.2 to 152.0) performing tasks such as prescription refills, teaching, meetings, management and communication with other professionals (33.4% of their workload). FP with larger patient lists spent less time on these tasks (p=0.002). Older FP (p=0.021) and those with larger lists (p=0.011) performed fewer tasks. The mean job satisfaction score was 3.5 (out of 5). No association was found between job satisfaction and time spent on tasks.

CONCLUSIONS

FP spent one-third of their workday in coordinating care, teaching and managing. Time devoted to these tasks decreases with increasing list size and physician age.

Time providing care outside visits in a home-based primary care program

OBJECTIVES

To assess how much time physicians in a large home-based primary care (HBPC) program spend providing care outside of home visits. Unreimbursed time and patient and provider-related factors that may contribute to that time were considered.

DESIGN

Mount Sinai Visiting Doctors (MSVD) providers filled out research forms for every interaction involving care provision outside of home visits. Data collected included length of interaction, mode, nature, and with whom the interaction was for 3 weeks.

SETTING

MSVD, an academic home-visit program in Manhattan, New York.

PARTICIPANTS

All primary care physicians (PCPs) in MSVD (n = 14) agreed to participate.

MEASUREMENTS

Time data were analyzed using a comprehensive estimate and conservative estimates to quantify unbillable time.

RESULTS

Data on 1,151 interactions for 537 patients were collected. An average 8.2 h/wk was spent providing nonhome visit care for a full-time provider. Using the most conservative estimates, 3.6 h/wk was estimated to be unreimbursed per full-time provider. No significant differences in interaction times were found between patients with and without dementia, new and established patients, and primary-panel and covered patients.

CONCLUSION

Home-based primary care providers spend substantial time providing care outside home visits, much of which goes unrecognized in the current reimbursement system. These findings may help guide practice development and creation of new payment systems for HBPC and similar models of care.

Applying systems engineering to implement an evidence-based intervention at a community health center

Impressive results in patient care and cost reduction have increased the demand for systems-engineering methodologies in large health care systems. This Report from the Field describes the feasibility of applying systems-engineering techniques at a community health center currently lacking the dedicated expertise and resources to perform these activities.

Challenges of making a diagnosis in the outpatient setting: a multi-site survey of primary care physicians

BACKGROUND

Although misdiagnosis in the outpatient setting leads to significant patient harm and wasted resources, it is not well studied. The authors surveyed primary care physicians (PCPs) about barriers to timely diagnosis in the outpatient setting and assessed their perceptions of diagnostic difficulty.

METHODS

Surveys of PCPs practicing in an integrated health system across 10 geographically dispersed states in 2005. The survey elicited information on key cognitive failures (including in clinical knowledge or judgement) for a specific case, and solicited strategies for reducing diagnostic delays. Content analysis was used to categorise cognitive failures and strategies for improvement. The authors examined the extent and predictors of diagnostic difficulty, defined as reporting >5% patients difficult to diagnose.

RESULTS

Of 1817 physicians surveyed, 1054 (58%) responded; 848 (80%) respondents primarily practiced in outpatient settings and had an assigned patient panel (inclusion sample). Inadequate knowledge (19.9%) was the most commonly reported cognitive factor. Half reported >5% of their patients were difficult to diagnose; more experienced physicians reported less diagnostic difficulty. In adjusted analyses, problems with information processing (information availability and time to review it) and the referral process were associated with greater diagnostic difficulty. Strategies for improvement most commonly involved workload issues (panel size, non-visit tasks).

CONCLUSIONS

PCPs report a variety of reasons for diagnostic difficulties in primary care practice. In this study, knowledge gaps appear to be a prominent concern. Interventions that address these gaps as well as practice level issues such as time to process diagnostic information and better subspecialty input may reduce diagnostic difficulties in primary care.

Notifications received by primary care practitioners in electronic health records: a taxonomy and time analysis

BACKGROUND

Asynchronous electronic health record (EHR)-based alerts used to notify practitioners via an inbox-like format rather than through synchronous computer "pop-up" messages are understudied. Our objective was to create an asynchronous alert taxonomy and measure the impact of different alert types on practitioner workload.

METHODS

We quantified and categorized asynchronous alerts according to the information they conveyed and conducted a time-motion analysis to assess practitioner workload. We reviewed alert information transmitted to all 47 primary care practitioners (PCPs) at a large, tertiary care Veterans Affairs facility over 4 evenly spaced 28-day periods. An interdisciplinary team used content analysis to categorize alerts according to their conveyed information. We then created an alert taxonomy and used it to calculate the mean number of alerts of each type PCPs received each day. We conducted a time-motion study of 26 PCPs while they processed their alerts. We used these data to estimate the uninterrupted time practitioners spend processing alerts each day.

RESULTS

We extracted 295,792 asynchronously generated alerts and created a taxonomy of 33 alert types categorized under 6 major categories: Test Results, Referrals, Note-Based Communication, Order Status, Patient Status Changes, and Incomplete Task Reminders. PCPs received a mean of 56.4 alerts/day containing new information. Based on 749 observed alert processing episodes, practitioners spent an estimated average of 49 minutes/day processing their alerts.

CONCLUSIONS

PCPs receive a large number of EHR-based asynchronous alerts daily and spend significant time processing them. The utility of transmitting large quantities and varieties of alerts to PCPs warrants further investigation.

Increasing Primary Care Comorbidity: A Conceptual Research and Practice Framework

Purpose: To present a “contrasting perspectives” conceptual framework reflecting the typically strained experiences of many comorbid adults now interacting with primary care clinicians across the world. Background: More comorbidity-related needs are presented to primary care clinicians during typically shorter office-based health care encounters. The overall perceptual differences between many comorbid consumers and health care clinicians and systems in many countries are likely to worsen. Conclusions: Conceptual implications are discussed for primary care researchers testing interventions and attempting to influence the outcomes of increasingly comorbid primary care adults. Implications for Nursing Research and Practice: Three strategies are offered for researchers and clinicians considering how to include elements of comorbidity into their prospective primary care study interventions and care delivery processes.