A Pragmatic Approach to Identifying and Profiling Primary Care Clinicians and Primary Care Practices in the USA.

BACKGROUND: There are no consistent data on US primary care clinicians and primary care practices owing to the lack of standard methods to identify them, hampering efforts in primary care improvement. METHODS: We develop a pragmatic framework that identifies primary care clinicians and practices in the context of the US healthcare system, and applied the framework to the IQVIA OneKey Healthcare Professional database to identify and profile primary care clinicians and practices in the USA. RESULTS: Our framework prescribes sequential steps to identify primary care clinicians by cross-examining clinician specialties and organizational affiliations, and then identify primary care practices based on organization types and presence of primary care clinicians. Applying this framework to the 2021 IQVIA data, we identified 365,751 physicians with a primary specialty in primary care, and after excluding those who further specialized (24%), served as hospitalists (5%), or worked in non-primary care settings (41%), we determined that 179,369 (49%) of them were actually practicing primary care. We identified 287,506 nurse practitioners and 134,083 physician assistants and determined that 88,574 (31%) and 29,781 (22%), respectively, were delivering primary care. We identified 94,489 primary care practices, and found that 45% of them were with one primary care physician, 15% had two physicians, 12% employed nurse practitioners or physician assistants only, and 19% employed both primary care physicians and specialists. CONCLUSIONS: Our approach offers a pragmatic and consistent alternative to the diverse methods currently used to identify and profile primary care workforce and organizations in the USA.

Electronic health record impact on work burden in small, unaffiliated, community-based primary care practices.

BACKGROUND: The use of electronic health records (EHR) is widely recommended as a means to improve the quality, safety and efficiency of US healthcare. Relatively little is known, however, about how implementation and use of this technology affects the work of clinicians and support staff who provide primary health care in small, independent practices. OBJECTIVE: To study the impact of EHR use on clinician and staff work burden in small, community-based primary care practices. DESIGN: We conducted in-depth field research in seven community-based primary care practices. A team of field researchers spent 9-14 days over a 4-8 week period observing work in each practice, following patients through the practices, conducting interviews with key informants, and collecting documents and photographs. Field research data were coded and analyzed by a multidisciplinary research team, using a grounded theory approach. PARTICIPANTS: All practice members and selected patients in seven community-based primary care practices in the Northeastern US. KEY RESULTS: The impact of EHR use on work burden differed for clinicians compared to support staff. EHR use reduced both clerical and clinical staff work burden by improving how they check in and room patients, how they chart their work, and how they communicate with both patients and providers. In contrast, EHR use reduced some clinician work (i.e., prescribing, some lab-related tasks, and communication within the office), while increasing other work (i.e., charting, chronic disease and preventive care tasks, and some lab-related tasks). Thoughtful implementation and strategic workflow redesign can mitigate the disproportionate EHR-related work burden for clinicians, as well as facilitate population-based care. CONCLUSIONS: The complex needs of the primary care clinician should be understood and considered as the next iteration of EHR systems are developed and implemented.

Typical electronic health record use in primary care practices and the quality of diabetes care.

PURPOSE: Recent efforts to encourage meaningful use of electronic health records (EHRs) assume that widespread adoption will improve the quality of ambulatory care, especially for complex clinical conditions such as diabetes. Cross-sectional studies of typical uses of commercially available ambulatory EHRs provide conflicting evidence for an association between EHR use and improved care, and effects of longer-term EHR use in community-based primary care settings on the quality of care are not well understood. METHODS: We analyzed data from 16 EHR-using and 26 non-EHR-using practices in 2 northeastern states participating in a group-randomized quality improvement trial. Measures of care were assessed for 798 patients with diabetes. We used hierarchical linear models to examine the relationship between EHR use and adherence to evidence-based diabetes care guidelines, and hierarchical logistic models to compare rates of improvement over 3 years. RESULTS: EHR use was not associated with better adherence to care guidelines or a more rapid improvement in adherence. In fact, patients in practices that did not use an EHR were more likely than those in practices that used an EHR to meet all of 3 intermediate outcomes targets for hemoglobin A(1c), low-density lipoprotein cholesterol, and blood pressure at the 2-year follow-up (odds ratio = 1.67; 95% CI, 1.12-2.51). Although the quality of care improved across all practices, rates of improvement did not differ between the 2 groups. CONCLUSIONS: Consistent use of an EHR over 3 years does not ensure successful use for improving the quality of diabetes care. Ongoing efforts to encourage adoption and meaningful use of EHRs in primary care should focus on ensuring that use succeeds in improving care. These efforts will need to include provision of assistance to longer-term EHR users.

Evaluation of risk equations for prediction of short-term coronary heart disease events in patients with long-standing type 2 diabetes: the Translating Research into Action for Diabetes (TRIAD) study.

BACKGROUND: To evaluate the U.K. Prospective Diabetes Study (UKPDS) and Framingham risk equations for predicting short-term risk of coronary heart disease (CHD) events among adults with long-standing type 2 diabetes, including those with and without preexisting CHD. METHODS: Prospective cohort of U.S. managed care enrollees aged ≥ 18 years and mean diabetes duration of more than 10 years, participating in the Translating Research into Action for Diabetes (TRIAD) study, was followed for the first occurrence of CHD events from 2000 to 2003. The UKPDS and Framingham risk equations were evaluated for discriminating power and calibration. RESULTS: A total of 8303 TRIAD participants, were identified to evaluate the UKPDS (n = 5914, 120 events), Framingham-initial (n = 5914, 218 events) and Framingham-secondary (n = 2389, 374 events) risk equations, according to their prior CHD history. All of these equations exhibited low discriminating power with Harrell's c-index <0.65. All except the Framingham-initial equation for women and the Framingham-secondary equation for men had low levels of calibration. After adjsusting for the average values of predictors and event rates in the TRIAD population, the calibration of these equations greatly improved. CONCLUSIONS: The UKPDS and Framingham risk equations may be inappropriate for predicting the short-term risk of CHD events in patients with long-standing type 2 diabetes, partly due to changes in medications used by patients with diabetes and other improvements in clinical care since the Frmaingham and UKPDS studies were conducted. Refinement of these equations to reflect contemporary CHD profiles, diagnostics and therapies are needed to provide reliable risk estimates to inform effective treatment.

Meaningful use of electronic prescribing in 5 exemplar primary care practices.

PURPOSE: Successful use of electronic prescribing (e-prescribing) is a key requirement for demonstrating meaningful use of electronic health records to qualify for federal incentives. Currently, many physicians who implement e-prescribing fail to make substantial use of these systems, and little is known about factors contributing to successful e-prescribing use. The objective of this study was to identify successful implementation and use techniques. METHODS: We conducted a multimethod qualitative case study of 5 ambulatory primary care practices identified as exemplars of effective e-prescribing. The practices were identified by a group of e-prescribing experts. Field researchers conducted in-depth interviews and observed prescription-related workflow in these practices. RESULTS: In these exemplar practices, successful use of e-prescribing required practice transformation. Practice members reported extensive efforts to redesign work processes to take advantage of e-prescribing capabilities and to create specific e-prescribing protocols to distribute prescription-related work among practice team members. These practices had substantial resources to support e-prescribing use, including local physician champions, ongoing training for practice members, and continuous on-site technical support. Practices faced considerable challenges during use of e-prescribing, however, deriving from problems coordinating new work processes with pharmacies and ineffective health information exchange that required workarounds to ensure the completeness of patient medical records. CONCLUSIONS: More widespread implementation and effective use of e-prescribing in ambulatory care settings will require practice transformation efforts that focus on work process redesign while being attentive to effects on patient and pharmacy involvement in prescribing. Improved health information exchange is required to fully realize expected quality, safety, and efficiency gains of e-prescribing.

EHR implementation without meaningful use can lead to worse outcomes.

Defying expectations, typical electronic health record (EHR) use in practices belonging to a primary care network has been associated with poorer diabetes care quality and outcomes. Current expansion of primary care EHR implementation must focus on use that improves care.

Using Learning Teams for Reflective Adaptation (ULTRA): insights from a team-based change management strategy in primary care.

PURPOSE: The Using Learning Teams for Reflective Adaptation (ULTRA) study used facilitated reflective adaptive process (RAP) teams to enhance communication and decision making in hopes of improving adherence to multiple clinical guidelines; however, the study failed to show significant clinical improvements. The purpose of this study was to examine qualitative data from 25 intervention practices to understand how they engaged in a team-based collaborative change management strategy and the types of issues they addressed. METHODS: We analyzed field notes and interviews from a multimethod practice assessment, as well as field notes and audio-taped recordings from RAP meetings, using an iterative group process and an immersion-crystallization approach. RESULTS: Despite a history of not meeting regularly, 18 of 25 practices successfully convened improvement teams. There was evidence of improved practice-wide communication in 12 of these practices. At follow-up, 8 practices continued RAP meetings and found the process valuable in problem solving and decision making. Seven practices failed to engage in RAP primarily because of key leaders dominating the meeting agenda or staff members hesitating to speak up in meetings. Although the number of improvement targets varied considerably, most RAP teams targeted patient care-related issues or practice-level organizational improvement issues. Not a single practice focused on adherence to clinical care guidelines. CONCLUSION: Primary care practices can successfully engage in facilitated team meetings; however, leaders must be engaged in the process. Additional strategies are needed to engage practice leaders, particularly physicians, and to target issues related to guideline adherence.

Thiazolidinediones, cardiovascular disease and cardiovascular mortality: translating research into action for diabetes (TRIAD).

BACKGROUND: Studies have associated thiazolidinedione (TZD) treatment with cardiovascular disease (CVD) and questioned whether the two available TZDs, rosiglitazone and pioglitazone, have different CVD risks. We compared CVD incidence, cardiovascular (CV), and all-cause mortality in type 2 diabetic patients treated with rosiglitazone or pioglitazone as their only TZD. METHODS: We analyzed survey, medical record, administrative, and National Death Index (NDI) data from 1999 through 2003 from Translating Research Into Action for Diabetes (TRIAD), a prospective observational study of diabetes care in managed care. Medications, CV procedures, and CVD were determined from health plan (HP) administrative data, and mortality was from NDI. Adjusted hazard rates (AHR) were derived from Cox proportional hazard models adjusted for age, sex, race/ethnicity, income, history of diabetic nephropathy, history of CVD, insulin use, and HP. RESULTS: Across TRIAD's 10 HPs, 1,815 patients (24%) filled prescriptions for a TZD, 773 (10%) for only rosiglitazone, 711 (10%) for only pioglitazone, and 331 (4%) for multiple TZDs. In the seven HPs using both TZDs, 1,159 patients (33%) filled a prescription for a TZD, 564 (16%) for only rosiglitazone, 334 (10%) for only pioglitazone, and 261 (7%) for multiple TZDs. For all CV events, CV, and all-cause mortality, we found no significant difference between rosiglitazone and pioglitazone. CONCLUSIONS: In this relatively small, prospective, observational study, we found no statistically significant differences in CV outcomes for rosiglitazone- compared to pioglitazone-treated patients. There does not appear to be a pattern of clinically meaningful differences in CV outcomes for rosiglitazone- versus pioglitazone-treated patients.

Low-Intensity Intervention Supports Diabetes Registry Implementation: A Cluster-Randomized Trial in the Ambulatory Care Outcomes Research Network (ACORN).

BACKGROUND: Previous research demonstrated that registries are effective for improving clinical guideline adherence for the care of patients with type 2 diabetes. However, registry implementation has typically relied on intensive support (such as practice facilitators) for practice change and care improvement. OBJECTIVE: To determine whether a remotely delivered, low-intensity organizational change intervention supports implementation and use of diabetes registries in primary care. DESIGN: Cluster-randomized controlled effectiveness trial of providing limited external support leveraging internal practice resources and problem-solving capacities for driving diabetes registry implementation in 32 practices in Virginia. INTERVENTION: All practices identified local implementation champions who participated in an in-person education session on the value and use of diabetes registries, while intervention practices were also paired with peer mentors and had access to a physician informaticist, who worked remotely to assist practices with implementation. MAIN MEASURES: Practice champions reported progress on registry implementation milestone achievement, and reported practice-level organizational capacity by using a modified version of the Assessment of Chronic Illness Care (ACIC). KEY RESULTS: Intervention practices were significantly more likely to have implemented a registry (44% vs 6%, P = .04) and to have achieved more implementation milestones (5.5 vs 2.6, P < .0001) than control practices. Baseline ACIC scores indicated room for organizational improvement with regard to chronic illness care (overall median, 6.4; range, 3.8 to 10.8) and clinical information systems use (median, 6.0; range, 0 to 11) with no significant differences between intervention and control practices. CONCLUSIONS: Remotely provided guidance paired with limited in-person assistance can support rapid implementation of diabetes registries in typical primary care practices.

Perceptions of standards-based electronic prescribing systems as implemented in outpatient primary care: a physician survey.

OBJECTIVE To compare the experiences of e-prescribing users and nonusers regarding prescription safety and workload and to assess the use of information from two e-prescribing standards (for medication history and formulary and benefit information), as they are implemented. DESIGN Cross-sectional survey of physicians who either had installed or were awaiting installation of one of two commercial e-prescribing systems. MEASUREMENTS Perceptions about medication history and formulary and benefit information among all respondents, and among e-prescribing users, experiences with system usability, job performance impact, and amount of e-prescribing. RESULTS Of 395 eligible physicians, 228 (58%) completed the survey. E-prescribers (n = 139) were more likely than non-e-prescribers (n = 89) to perceive that they could identify clinically important drug-drug interactions (83 versus 67%, p = 0.004) but not that they could identify prescriptions from other providers (65 versus 60%, p = 0.49). They also perceived no significant difference in calls about drug coverage problems (76 versus 71% reported getting 10 or fewer such calls per week; p = 0.43). Most e-prescribers reported high satisfaction with their systems, but 17% had stopped using the system and another 46% said they sometimes reverted to handwriting for prescriptions that they could write electronically. The volume of e-prescribing was correlated with perceptions that it enhanced job performance, whereas quitting was associated with perceptions of poor usability. CONCLUSIONS E-prescribing users reported patient safety benefits but they did not perceive the enhanced benefits expected from using standardized medication history or formulary and benefit information. Additional work is needed for these standards to have the desired effects.

A comparison of chronic illness care quality in US and UK family medicine practices prior to pay-for-performance initiatives.

BACKGROUND: The Quality and Outcomes Framework (QOF) has contributed to modest improvements in chronic illness care in the UK. US policymakers have proposed similar pay-for-performance (P4P) approaches to improve care. Since previous studies have not compared chronic illness care quality in US and UK primary care practices prior to the QOF, the relative preparedness of practices to respond to P4P incentives is unknown. OBJECTIVE: To compare US and UK practices on P4P measures prior to program implementation. METHODS: We analysed medical record data collected before QOF implementation from randomly selected patients with diabetes or coronary artery disease (CAD) in 42 UK and 55 US family medicine practices. We compared care processes and intermediate outcomes using hierarchical logistic regression. RESULTS: While we found gaps in chronic illness care quality across both samples, variation was lower in UK practices. UK patients were more likely to receive recommended care processes for diabetes [odds ratio (OR), 8.94; 95% confidence interval (CI), 4.26-18.74] and CAD (OR, 9.18; 95% CI, 5.22-16.17) but less likely to achieve intermediate diabetes outcome targets (OR, 0.50; 95% CI, 0.39-0.64). CONCLUSIONS: Following National Health Service (NHS) investment in primary care preparedness, but prior to the QOF, UK practices provided more standardized care but did not achieve better intermediate outcomes than a sample of typical US practices. US policymakers should focus on reducing variation in care documentation to ensure the effectiveness of P4P efforts while the NHS should focus on moving from process documentation to better patient outcomes.

Organizational culture influences health care workers' influenza immunization behavior.

BACKGROUND AND OBJECTIVES: Low rates of influenza immunization among health care workers (HCWs) pose a potential health risk to patients in primary care practices. Despite previous educational efforts and programs to reduce financial barriers, HCW influenza immunization rates remain low. Variation in practice-level organizational culture may affect immunization rates. To explore this relationship, we examined organizational cultures and HCWs' influenza immunization behaviors in three family medicine practices. METHODS: We used a multi-method comparative case study. A field researcher used participant observation, in-depth interviews, and key informant interviews to collect data in each practice in November-December 2003. A diverse team used grounded theory to analyze text data. RESULTS: Organizational culture varied among practices and differing HCW immunization rates were observed. The most structured and business-like practice achieved immunization of all HCWs, while the other two practices exhibited greater variation in HCW immunization rates. Physicians in the practices characterized as chaotic/disorganized or divided were immunized at higher rates than other members of the practices. CONCLUSIONS: In these practices, organizational culture was associated with varying rates of influenza immunization for HCWs, especially among nonphysicians. Addressing elements of organizational culture such as beliefs regarding influenza immunization and office policies may facilitate the immunization of all staff members.

Self-report versus medical records for assessing cancer-preventive services delivery.

Accurate measurement of cancer-preventive behaviors is important for quality improvement, research studies, and public health surveillance. Findings differ, however, depending on whether patient self-report or medical records are used as the data source. We evaluated concordance between patient self-report and medical records on risk factors, cancer screening, and behavioral counseling among primary care patients. Data from patient surveys and medical records were compared from 742 patients in 25 New Jersey primary care practices participating at baseline in SCOPE (supporting colorectal cancer outcomes through participatory enhancements), an intervention trial to improve colorectal cancer screening in primary care offices. Sensitivity, specificity, and rates of agreement describe concordance between self-report and medical records for risk factors (personal or family history of cancer, smoking), cancer screening (breast, cervical, colorectal, prostate), and counseling (cancer screening recommendations, diet or weight loss, exercise, smoking cessation). Rates of agreement ranged from 41% (smoking cessation counseling) to 96% (personal history of cancer). Cancer screening agreement ranged from 61% (Pap and prostate-specific antigen) to 83% (colorectal endoscopy) with self-report rates greater than medical record rates. Counseling was also reported more frequently by self-report (83% by patient self-report versus 34% by medical record for smoking cessation counseling). Deciding which data source to use will depend on the outcome of interest, whether the data is used for clinical decision making, performance tracking, or population surveillance; the availability of resources; and whether a false positive or a false negative is of more concern.

Variation in electronic prescribing implementation among twelve ambulatory practices.

BACKGROUND: Electronic prescribing has been advocated as an important tool for improving the safety and quality of medication use in ambulatory settings. However, widespread adoption of e-prescribing in ambulatory settings has yet to be realized. The determinants of successful implementation and use in these settings are not well understood. OBJECTIVE: To describe the practice characteristics associated with implementation and use of e-prescribing in ambulatory settings. DESIGN: Multi-method qualitative case study of ambulatory practices before and after e-prescribing implementation. PARTICIPANTS: Sixteen physicians and 31 staff members working in 12 practices scheduled for implementation of an e-prescribing program and purposively sampled to ensure a mix of practice size and physician specialty. MEASUREMENTS: Field researchers used observational and interview techniques to collect data on prescription-related clinical workflow, information technology experience, and expectations. RESULTS: Five practices fully implemented e-prescribing, 3 installed but with only some prescribers or staff members using the program, 2 installed and then discontinued use, 2 failed to install. Compared to practice members in other groups, members of successful practices exhibited greater familiarity with the capabilities of health information technologies and had more modest expectations about the benefits likely to accrue from e-prescribing. Members of unsuccessful practices reported limited understanding of e-prescribing capabilities, expected that the program would increase the speed of clinical care and reported difficulties with technical aspects of the implementation and insufficient technical support. CONCLUSIONS: Practice leaders should plan implementation carefully, ensuring that practice members prepare for the effective integration of this technology into clinical workflow.

Diabetes flow sheet use associated with guideline adherence.

PURPOSE: Many intervention studies have found that flow sheet use improves patient care by drawing attention to a particular medical condition or needed preventive service and encouraging an immediate response from the health care professional; however, there are no studies examining how often flow sheets are used for diabetes in primary care practice. We assessed the relationship between diabetes flow sheet use and diabetes patient care outcomes in the everyday practice of primary care. METHODS: We abstracted the medical records of 1,016 patients with diabetes seen at 54 New Jersey and eastern Pennsylvania family practices participating in a quality improvement trial. The use of diabetes flow sheets was noted for each medical record. Scores for adherence to evidence-based diabetes guidelines in terms of assessment, treatment, and target attainment were determined on 100-point scales, with higher scores indicating better adherence. Generalized linear models were used to determine associations between use of diabetes flow sheets and adherence to guidelines. RESULTS: Diabetes flow sheets were used in 23% of the medical records of patients with diabetes. Use of flow sheets was associated with better mean guideline adherence scores for the assessment of diabetes (55.38 vs 50.13, P = .02) and the treatment of diabetes (79.59 vs 74.71, P = .004), but not for the attainment of intermediate diabetes outcome targets (hemoglobin A(1c) level, low-density lipoprotein cholesterol level, and blood pressure). CONCLUSIONS: Diabetes flow sheets can be used to promote better adherence to guidelines when it comes to assessing and treating diabetes. Additional research is needed to explore patient and physician variables that mediate the relationship between use of diabetes flow sheets and intermediate outcome targets for diabetes.

Electronic medical records and diabetes quality of care: results from a sample of family medicine practices.

PURPOSE: Care of patients with diabetes requires management of complex clinical information, which may be improved by the use of an electronic medical record (EMR); however, the actual relationship between EMR usage and diabetes care quality in primary care settings is not well understood. We assessed the relationship between EMR usage and diabetes care quality in a sample of family medicine practices. METHODS: We conducted cross-sectional analyses of baseline data from 50 practices participating in a practice improvement study. Between April 2003 and December 2004 chart auditors reviewed a random sample of medical records from patients with diabetes in each practice for adherence to guidelines for diabetes processes of care, treatment, and achievement of intermediate outcomes. Practice leaders provided medical record system information. We conducted multivariate analyses of the relationship between EMR usage and diabetes care adjusting for potential practice- and patient-level confounders and practice-level clustering. RESULTS: Diabetes care quality in all practices showed room for improvement; however, after adjustment, patient care in the 37 practices not using an EMR was more likely to meet guidelines for process (odds ratio [OR], 2.25; 95% confidence interval [CI], 1.42-3.57) treatment (OR, 1.67; 95% CI, 1.07-2.60), and intermediate outcomes (OR, 2.68; 95% CI, 1.49-4.82) than in the 13 practices using an EMR. CONCLUSIONS: The use of an EMR in primary care practices is insufficient for insuring high-quality diabetes care. Efforts to expand EMR use should focus not only on improving technology but also on developing methods for implementing and integrating this technology into practice reality.

Using the Consolidated Framework for Implementation Research (CFIR) to produce actionable findings: a rapid-cycle evaluation approach to improving implementation.

BACKGROUND: Much research does not address the practical needs of stakeholders responsible for introducing health care delivery interventions into organizations working to achieve better outcomes. In this article, we present an approach to using the Consolidated Framework for Implementation Research (CFIR) to guide systematic research that supports rapid-cycle evaluation of the implementation of health care delivery interventions and produces actionable evaluation findings intended to improve implementation in a timely manner. METHODS: To present our approach, we describe a formative cross-case qualitative investigation of 21 primary care practices participating in the Comprehensive Primary Care (CPC) initiative, a multi-payer supported primary care practice transformation intervention led by the Centers for Medicare and Medicaid Services. Qualitative data include observational field notes and semi-structured interviews with primary care practice leadership, clinicians, and administrative and medical support staff. We use intervention-specific codes, and CFIR constructs to reduce and organize the data to support cross-case analysis of patterns of barriers and facilitators relating to different CPC components. RESULTS: Using the CFIR to guide data collection, coding, analysis, and reporting of findings supported a systematic, comprehensive, and timely understanding of barriers and facilitators to practice transformation. Our approach to using the CFIR produced actionable findings for improving implementation effectiveness during this initiative and for identifying improvements to implementation strategies for future practice transformation efforts. CONCLUSIONS: The CFIR is a useful tool for guiding rapid-cycle evaluation of the implementation of practice transformation initiatives. Using the approach described here, we systematically identified where adjustments and refinements to the intervention could be made in the second year of the 4-year intervention. We think the approach we describe has broad application and encourage others to use the CFIR, along with intervention-specific codes, to guide the efficient and rigorous analysis of rich qualitative data. TRIAL REGISTRATION: NCT02318108.

Early Experiences Engaging Patients Through Patient and Family Advisory Councils.

Primary care practices are increasingly asked to engage patients in improving care delivery. We report early experiences with Patient and Family Advisory Councils (PFACs) from interviews of patients and practice staff in the Comprehensive Primary Care initiative, and identify ways to improve PFACs. Patients and practice staff report PFACs help practices elicit patient feedback and, in response, improve care delivery. Nonetheless, there are areas for refinement, including recruiting more diverse patients, providing an orientation to members, overcoming reticence of some patients to raise issues, and increasing transparency by sharing progress with PFAC members and patients in the practice more generally.

Implementing an electronic medical record in a family medicine practice: communication, decision making, and conflict.

PURPOSE: Electronic medical record (EMR) systems offer substantial opportunities to organize and manage clinical data in ways that can potentially improve preventive health care, the management of chronic illness, and the financial health of primary care practices. The functionality of EMRs as implemented, however, can vary substantially from that envisaged by their designers and even from those who purchase the programs. The purpose of this study was to explore how unique aspects of a family medicine office culture affect the initial implementation of an EMR. METHODS: As part of a larger study, we conducted a qualitative case study of a private family medicine practice that had recently purchased and implemented an EMR. We collected data using participant observation, in-depth interviews, and key informant interviews. After the initial data collection, we shared our observations with practice members and returned 1 year later to collect additional data. RESULTS: Dysfunctional communication patterns, the distribution of formal and informal decision-making power, and internal conflicts limited the effective implementation and use of the EMR. The implementation and use of the EMR made tracking and monitoring of preventive health and chronic illness unwieldy and offered little or no improvement when compared with paper charts. CONCLUSIONS: Implementing an EMR without an understanding of the systemic effects and communication and the decision-making processes within an office practice and without methods for bringing to the surface and addressing conflicts limits the opportunities for improved care offered by EMRs. Understanding how these common issues manifest within unique practice settings can enhance the effective implementation and use of EMRs.