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4 INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS â¢ an information environment to support the work of caregivers and patients; and â¢ support staff, equipment, and a work environment. Accordingly, for this study, we defined a micro-system as: a small, organized patient care unit with a specific clinical purpose, set of patients, technologies and practitioners who work directly with these patients. One example of a health care micro-system is a primary care or specialty practice; an office-based, physician-led practice caring for 9,800 patients with, for example, about 3,000 square feet of space in a downtown office building, six physicians, two nurse-practitioners, staff, hospital privileges, and so forth. Other micro-systems include: a cardiac care unit in a medical center, an emergency department in a community hospital, a hospice, a dialysis unit, a diabetes management program, or a back-pain treatment center. For every micro-system, clusters of tasks can be specified. Such clusters in office practice include, for example, greeting and establishing a relationship with a patient; making an initial assessment and re- cording findings; ordering laboratory tests and incorporating results into care plans; per- forming procedures, and providing instructions for self-care, next steps, and follow-up. The key components of a micro-system are not new: patients, populations, clinicians, activities, and information technology exist in every health care setting. However, most often these small systemsï£§their elements and working dynamicsï£§are not recognized by the larger organizations that provide the organizational context for their work, such as in the de- sign of human resource policies and information technologies, or by groups outside health care organizations, such as third party payers devising payment policies and employers seeking accountability for the care of their employees. As a result, payment and incentives may ignore collaborative working relationships and be misdirected at too âlowâ or too âhighâ a level. For example, payment policies are typically devised to affect the behavior of physicians rather than a collaborative multi- disciplinary team. Conversely, incentives and regulations may be directed at entire organiza- tions (such as hospitals) rather than recognizing and rewarding the small work groupsï£§micro-systemsï£§that affect quality directly. Micro-systems do their work today along a spectrum of performance that can range from very good to very poor. We emphasize that in this study, the term micro-system is not reserved for groups that demonstrate extraordinary performance along all the dimensions of care or in their âsystemness.â In part, this is because at present that would constitute an ex- tremely small, perhaps a null, set. More importantly, it draws attention to the fact that these small care systems are ubiquitous throughout health care, and their influence on quality is key to understanding how to improve care. Batalden and his colleagues have suggested that effective micro-systems might pro- vide (1) greater standardization of common activities and customization of care to individual patients, (2) greater use and analysis of information to support daily work, (3) consistent, measured improvement in performance, (4) extensive cooperation and teamwork within the
INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS 5 micro-system, (5) and an opportunity for spread of best practices across micro-systems within their larger organizations.8 Some previous research on teams has focused on functional and interdisciplinary workgroups and the systems that facilitate or impede the management of these workgroups.9 For example, a firm systemï£§parallel teams of practitioners and students and patients ran- domly assigned to the teamsï£§was introduced over two decades ago at MetroHealth Medical Center in Cleveland, Ohio as a way to create and maintain longitudinal relationship of small groups of teachers, students, and patients.10, 11, 12 This has been a valuable approach to evalu- ating different innovations in patient care and organizational design. This study continues the tradition of learning about innovation and improvement from clinical practices in dynamic settings. It used a purposive sampling of what experts in the field considered to be high performing micro-systems to learn about their organization, aims, and their approaches to measurement and improvement. Micro-systems do not, of course, function in isolation. Many work processes cut across micro-systems as well as clinical disease states such as those involving multiple chronic illnesses. Micro-systems must coordinate seamlessly with other micro-systems, and a major challenge is effectively managing the handoffs and feedback of information among micro-systems. The interaction of micro-systems is critical to ensuring that information is available when needed and is consistent, that patients receive timely services, and that waste and duplication are minimized. The larger organizations of which they are a partâwhich we call the macro- or um- brella organizationâcan help this to occur. That is, in addition to linkages among micro- systems, micro-systems may be part of a larger organization (e.g., a cardiac care unit in a hospital, a group practice that has contracts with health plans, an ophthamology practice within a multispecialty clinic), and they are embedded in and interact with a legal, financial, and regulatory environment that may foster or impede their effectiveness. Although not a fo- cus of this study, leaders of macro-organizations interact with the environment to mediate the effect on micro-systems of such financial incentives, regulation, or workforce issues. Use of Qualitative Methods Qualitative inquiry cultivates the most useful of all human capacitiesâthe ca- pacity to learn from others. âPatton 199413 This study examined micro-systems in the context in which they exist so that mean- ingful inferences could be made about them. Choosing a strategy to guide the work required careful consideration of quantitative and qualitative methodologies. Both qualitative and quantitative research involves a process of inquiry into a human or social problem. The method selected, however, depends on the questions that the researcher seeks to answer. For example, small area analysis of quantitative data14 shows that diabetic Medicare beneficiaries vary in their rates of retinal exams, HgA1c, and low-density lipoprotein (LDL) monitoring.
6 INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS Across the United States, retinal exams vary by geographic region from 25.1 percent to 66.1 percent. HbA1c monitoring varies from 8.9 percent to 70.2 percent, and LDL monitoring varies from 6.8 percent to 68 percent. Such a quantitative analysis does not explain, however, why such variation occurs or the barriers that may exist to providing these services. Nor does it reveal how to change the care to improve the outcomes. To connect the quantitative find- ings to small group behavior, qualitative methods can be helpful in elucidating the behavior of the system that is producing the results. Quantitative methods test theory, with an emphasis on hypothesis testing and verifi- cation. Data gathered in a quantitative study is in the form of numbers evaluated, using de- scriptive and inferential statistics. A quantitative approach to a study on health care micro- systems might involve a variable-oriented analysis that computes the correlation between a variable and a selected outcome. Another quantitative option would be to use regression analysis to determine the relative importance of a set of variables in determining such an out- come. These approaches, however, require clarity about the important variables going in to the study. Because this study was intended to be an exploratory look at micro-systems as a unit of analysis, the important variables were not clear at the outset but were, rather, expected to emerge as the study progressed. Neither was it clear what outcomes might be measured. We were interested in the performance of micro-systems, recognizing that in some cases this was measurable (e.g., rates of favorable or unfavorable patient outcomes), but that in other cases the outcomes of interest were subjective and not easily measured, for example, patientsâ ex- perience, the professional culture, and interest in innovation and assessment of performance. For these reasons, a qualitative strategy was chosen as most appropriate for this research. Qualitative methods develop theory by emphasizing rich description and discovery. These methods assume that the phenomena under study are part of a system and cannot be reduced to a few variables with a clear cause and effect relationship. Qualitative methods build on the theme of naturalistic inquiry, which is âa discovery-oriented approach that minimizes investigator manipulation of the study setting and places no prior constraints on the outcomes of the research.â15 Data are in the form of words and are evaluated subjectively by systematically reducing data to themes and categories. Qualitative methods are inductive to the extent that the research design allows important themes to emerge from patterns found in the data. A criticism of qualitative methods has been the focus on individual cases, which lim- its the external validity of the research. In response, it can be argued that generalizability is not a goal of qualitative research in general16, 17 nor of this study, in particular. The qualita- tive methods used in this study should best be understood as descriptive, hypothesis generat- ing and, to a limited extent, hypothesis testing (see below). Further data gathering and quali- tative analysis (for example using multiple respondents at each site or negative cases for comparison) paired with quantitative analysis to test hypotheses, may be the most fruitful route to confidence in the generalizablity of study findings and their predictive value.
INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS 7 Personal insights by the researchers are the essential information derived from the interview data and they are critical to understanding the complexities of micro-systems and the organizations in which they are embedded. However, the research must approach the phenomenon under study with what Patton calls âempathic neutrality.â18 To be neutral to the findings means not approaching the phenomenon with a set of preconceived ideas. That means one approaches micro-systems with a desire to learn about them as interrelationships emerge. In qualitative research, it is important to separate the description of the data from the interpretation of the data. Geertz19 and Denzin20 discuss âthickâ and âthinâ description. âThick descriptionâ depends on presenting descriptive data or recording verbatim comments so that researchers can make their own interpretations later. âThin description,â on the other hand, summarizes the facts without including any of the context. Thick description sets up analysis and makes possible interpretation.21 Appendix A shows examples of each type of description. For this research, thick description was used and later coded. Each micro-system was recorded and presented in sufficient detail so that the micro-system, or âcase,â could be understood in its local context. This study used two methods: first, descriptive summaries of the interviews derived from thick description; and, second, cross-case analysis. Cross-case analysis offers a way to reconcile the need for âthick descriptionâ of uniquely individual cases yet captures the themes and patterns that emerge across cases.22 Two approaches to cross-case analysis are available: case-oriented analysis and variable-oriented analysis.23 A case-oriented approach starts by considering each case as its own entity. Only after understanding the relationships, configurations, associations, and the like within the case does the researcher move to a com- parative case analysis. The goal is to discover the underlying themes, similarities, and asso- ciations that hold across cases. A variable-oriented approach to cross-case analysis starts with a framework of several variables or themes that cut across cases. For example, variables that may be relevant to a study of health care micro-systems may be the use of information, the role of information technology, or coordination of patient care. Although the study starts with key variables in mind, the variables may evolve and be clarified as the study progresses and as cases are in- cluded in the analysis. The variable-oriented approach is more conceptual and theory- centered from the beginning, and less emphasis is placed on the specific details of a particu- lar case. Neither approach to cross-case analysisâcase-oriented or variable-orientedâis nec- essarily better. As Miles and Huberman point out, the process is one of alternating, combin- ing, or integrating methods as a study progresses.24 They suggest a mixed strategy that com- bines the two approaches and uses a âstackingâ technique. Such a process was used in this study. To use this technique, the researcher writes up a series of cases using a more or less standard set of variables. Matrices are used to display the data for each case. Without losing any of the individual case-level data, cases are then âstackedâ in a âmeta-matrix.â Analysis continues by systematically comparing the stacked cases and condensing the meta-matrix.
8 INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS METHODS The study methodology was a qualitative analysis of structured interviews. It was conducted in three stages: (1) literature review, nomenclature, and study design; (2) protocol development, sampling, instrument design and testing, and data collection; and (3) analysis. Stage 1: Literature Review, Nomenclature, and Study Design The first phase of this study involved convening a steering group to (a) develop a working definition of a micro-system, (b) identify high performing micro-systems, and (c) ad- vise us on study design and interview questions. The steering group was composed of mem- bers of the QHCAâs Subcommittee on Developing the 21st Century Health System, chaired by Donald M. Berwick, M.D. The steering group included: Donald M. Berwick, M.D., Stephen M. Shortell, Ph.D., Eugene C. Nelson, Sc.D., Thomas Nolan, Ph.D. (all members of the sub- committee), and an unpaid consultant to the committee, Paul B. Batalden, M.D. In addition to the co-authors, Anand Parekh, an intern and second-year medical student, staffed the project. We conducted a literature review on characteristics of various micro-systems in health care as well as in other manufacturing and non-health care service industries. In addition to the steering group members, we sought suggestions for methodology and interview content from the staff of groups with substantial expertise and experience with qualitative analysis. In designing this study it was important that the effort be coordinated with the work of Paul B. Batalden, M.D. and his colleagues at Dartmouthâs Center for Clinical Evaluative Sciences for two reasons: 1) Dr. Batalden is a recognized expert in the area of micro-systems, and his input into the IOM project was considered a valuable resource; and 2) the data and information gathered by IOM on micro-systems were expected to be useful contributions to Dr. Bataldenâs separate proposal to study micro-systems. To maximize communications be- tween the Dartmouth group and IOM project, we â¢ held bi-weekly telephone conferences between Dartmouth and IOM staff during spring, 1999 seeking his review and comment at critical points in the project (i.e., selection of the sample frame, development of the interview protocol and methods, draft analysis of findings); â¢ appointed Dr. Batalden as a consultant to the committee and a member of the steering group; and â¢ were assisted by Julie Mohr, a Dartmouth College graduate student whose now completed doctoral dissertation topic was on micro-systems. We also collaborated with the leaders of the Institute for Health Care Improvementâs Idealized Design of Office Practice (ID-COP) project. That project has enlisted some 42 clinical sites to apply design principles for improvement in clinical office practice. Dr. Don- aldson participated in a two-day conference of these site leaders which provided further in- sight into some organizational and leadership issues relevant to improving performance. Be- cause some of the recommended sites were participants in ID-COP, it also helped this studyâs site selection process.
INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS 9 Finally, Andrew Balas, M.D., Ph.D., University of Missouri-Columbia, convened ex- perts in medical informatics for a telephone conference to assist the study staff in formulating questions about the role of information technologies in these micro-systems. Operational Definition The first task of the steering group was to develop a clear conceptual and operational definition of the micro-system that would be easily conveyed to the interview sites. Some questions the group addressed were: What size group is too big or too small to be a micro- system? How can we identify micro-systems? That is, what definition would include perhaps 80 percent of the groups that we were to talk with but not be too restrictive? The group did not establish a priori a minimal or maximum size for a micro-system. Generally, a micro- system must be large enough to accomplish its clinical purpose, but small enough to allow knowledge of the individual parts and to manage the interactions among its parts. The group identified several ways that micro-systems might recognize themselves as groups, including â¢ the members recognize themselves as having a common aim, service line, or clini- cal purpose such as care of patients with a specific clinical condition, a panel of patients, or care of a defined population; there is a self-conciousness about working together for a de- fined purpose; or â¢ units that have a direct service relationship to patients; that is, they speak to or touch the patient or are âone step awayâ from doing so; â¢ the members recognize themselves as part of a team that consciously organizes its work processes; â¢ the people who share an intimacy of working relationship; and â¢ the people who cross-cover for one another, share call rotation, define the content and process of care for their patients and formulate clinical guidelines. The Steering Group developed the following working definition of a micro-system, choosing a general and inclusive definition so that it might learn from the respondents how they describe their own micro-systems. A micro-system is a small, organized patient care unit with a specific clinical purpose, set of patients, technologies and practitioners who work di- rectly with these patients. Stage 2: Study Design and Data Collection During the second stage of the study we developed and finalized the protocol, se- lected the micro-system sites, drafted, pilot tested, and revised the interview instruments, conducted tests of interrater reliability, conducted the interviews, and transcribed notes. Instrument and Protocol Development During late spring and summer 1999âwe developed the methodology and structured interview content. The Steering Group reviewed several drafts of the interview protocol and instruments. The methodology used was a structured one and a half-hour interview with each micro-system leader preceded by a mailed two-page pre-interview survey
10 INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS The interview protocol included a letter of invitation from Dr. Berwick, chair of the Subcommittee on Building the 21st Century Health System (Appendix B), committee and subcommittee rosters (Appendix C), a two-page pre-interview survey (Appendix D), and an IOM brochure. Several days after mailing the letter of invitation, study staff called to make sure the invitation had been received and that it had been sent to the right person (the leader of the micro-system). An interview time was then scheduled and the respondent was asked to complete the pre-interview survey and fax it to us at least one day before the scheduled inter- view. Before the interview, the interviewer reviewed the pre-interview survey information to adjust the interview format and to make notes about which items needed to be clarified. The interview instrument is shown in Appendix E. At the time of the interview, the interviewer introduced him or herself and briefly explained the purpose of the interview, stated that no information would be attributed to them without their explicit permission, and that the interviewer would be taking notes and might wish to follow up to clarify information at a later time. Interviews were timed to be completed within 90 minutes unless the respon- dent wanted to continue. Immediately after the interview, the interviewer transcribed his or her notes and completed a summary sheet. The interviews were intended to gather information in two ways. The first was a form of hypothesis testing, the second hypothesis generating. With regard to the first, the concep- tual work of the IOM quality of care committee and the Steering Group had led to a series of guesses about how effective micro-systems might do their work, which led to question areas that the steering group outlined. We organized the questions into five topics to provide structure and order for the interview but intentionally made the questions related to them open ended so as to elicit new themes that the investigators might not expect. The interview addressed five overall topics: (1) level of performance, (2) patient ex- perience, (3) information and information technology, (4) investment in improvement, and (5) leadership. Each topic began with an open-ended question, such as (for the first topic): What does your micro-system do very well? Can you give me some examples? A number of more specific questions followed, including a set of optional probes. For example, the first section (âLevel of Performanceâ) included the following questions: â¢ What is your micro-system successful at doing? How do you define success? â¢ How do you know you are successful? What data are you collecting? â¢ If I were a patient, how would I experience care at your micro-system differently? â¢ If I were a clinician, how would I experience it differently from another micro- system that treats similar patients? â¢ How would you describe the day-to-day work environment? What does it feel like to work at ___? â¢ What has your micro-system done to support professional ethics, encourage peer feedback or skill development? â¢ Optional: How long has the micro-system been working this way? How is it differ- ent now from an earlier time?
INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS 11 Site Selection Sites were selected based on their likelihood of informing the research. We used an interative process sometimes called a âsnowball strategyâ (Patton 1994). Using this strategy one asks well-informed individuals to nominate sites and to provide the names of other knowledgeable people to ask for nominations. In this study we asked individuals to nominate sites that had a reputation for innovative models of delivery, innovative use of technology, level of performance, or investment in improvement. Sites were identified by (2) consultation with experts in the field of quality and members of the IOM steering group and Committee on the Quality of Health Care in America, (3) participants in the Institute for Healthcare Im- provementâs Breakthrough Series who had made significant improvement between the be- ginning and end of their project; (4) Dr. Paul Batalden, who identified micro-systems that he used as case studies in various educational programs at Dartmouth Medical School; (5) Dr. Joanne Lynn, who headed the Center to Improve Care of the Dying and IHIâs Breakthrough Series on end-of-life care and suggested hospice and palliative care programs, and (6) Dr. Connie Davis, Center for Health the Center for Health Studies of the Group Health Coopera- tive of Puget Sound and national program office for âImproving Chronic Illness Careâ who recommended several chronic disease management programs for inclusion, particularly those focused on diabetes care. We also sought published descriptions of the work of micro- systems, including disease management programs, in such journals as the Joint Commission Journal on Quality Improvement and the International Journal for Quality. This process yielded 112 suggestions for sites to include in the study. After further inquiry, we reduced this list to 77 and finally culled it by asking the steering group to pick a small number of their most highly recommended sites from the longer list. We chose only sites that were recommended by at least two members of the Steering Group. This winnow- ing process resulted in a final list of 45 sites. Two sites later declined to participate in the study, resulting in the final 43 sites that were included in the study. The distribution of sites is shown in Table 1. As shown in the table, the micro- systems included in the study are diverse geographically, clinically, and in terms of the population they serve. We interviewed individuals at a range of sites that included hospital units (such as emergency departments, cardiac care, and newborn intensive care), primary care and other ambulatory settings, chronic disease management programs, hospice care, and a hospital specializing in a single procedure. All except two sites were in the United Statesï£§one in Canada and one in the United Kingdom. Instrument Testing and Interviewer Reliability The interviewers took hand-written notes during the interview and did not tape record the interviews because of the quasi-public nature of the National Academies and the possible requirement for any formal communications with an Academy committee to be placed in a
12 INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS TABLE 2 Range of Micro-Systems Studied Geographic Setting Micro-Systems West/Soutwest West/Soutwest Studied West Coast Total Northeast Non-U.S. Midwest South 15 8 4 5 9 2 43 N % of Total Primary Care 15 6 2 0 1 5 1 35% Clinical Focus Specialty 19 4 7 2 2 4 0 44% Care Hospital Unit 9 5 0 2 1 0 1 21% 100% Pediatric 19 7 2 1 3 4 2 44% Adolescent 27 10 5 2 3 5 2 63% Population Served Adult 38 13 8 3 4 8 2 88% Geriatric 39 14 7 4 3 9 2 91% Rural 14 8 2 2 0 0 2 33% Urban 27 4 6 3 4 8 2 63% Suburban 15 4 3 2 2 2 2 35% For distribution of population served, percents do not add up to 100% because sites may serve more than one type of population public access file (pursuant to Section 15 of the Federal Advisory Committee Act). For this reason, it was essential that we establish the reliability of the three interviewers (Donaldson, Mohr, and Parekh). To assure the quality of note taking, the interview process was pilot tested in several ways. Several interviews were conducted as conference calls with the interviewer, the re- spondent, and two note takers. Immediately following the interview, the interviewer and note takers transcribed their notes and compared their documents. As a result, some questions were re-ordered or dropped, and probes were added. When we were confident that the interviewer could conduct an interview and simulta- neously take good notes, the interview process was simplified to include a single interviewer-
INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS 13 note taker. To facilitate interviewing and note taking, the interview was formatted with space for note taking after each question. This helped us keep track of the context of the answers be- cause the answers were kept with the questions, instead of having separate pages of notes. Transcripts were written up immediately following the interview, and most importantly, before conducting another interview. Data Collection Invitations to Participate. Key contacts within each micro-system (micro-system leaders) were identified and sent an introductory packet of information asking them to participate. A follow-up phone call from an IOM staff member was made several days after the introductory packet had been sent to schedule a time for the interview. Participants were reminded to com- plete and return the pre-interview survey prior to the telephone interview. All the sites com- plied with this request. The Preinterview Survey. The purpose of the pre-interview survey was to gather basic in- formation about the micro-system. This proved to be an effective method for learning, before the interview, what the micro-system does, the composition of the providers and staff, and the demographics of the population served. It allowed the person conducting the interview to re- view basic descriptive information about the site before the interview and to ask for any clari- fication of pre-interview responses during the interview. Based on the pre-interview re- sponses, the interview format could also be adjusted to delete questions that were not relevant to the site. For example, the interview contained a section on information technology, but some sites indicated that computer based clinical information was not relevant for their site. During the interview, the response was confirmed, and questions that related to computer- based clinical information were skipped. Deleting questions that were not applicable ahead of time helped to make the most efficient use of interview time. In addition, beginning the inter- view by discussing what the interviewer knew about the micro-system site helped to quickly establish rapport between interviewer and interviewee. Table 2 summarizes responses to the pre-interview survey, including how the micro-systems describe their own site and type of micro-system (primary care, specialty care, hospital unit) and how it was organized. Telephone Interviews. Telephone interviews were conducted during a three-month time- frame, June 29, 1999 through September 3, 1999. Interviews were conducted with the person identified as the âleaderâ of the micro-system. This was usually a physician, although several nurses were interviewed, as well as several administrative leaders. Three interviews included more than one interviewee on the call, but for the most part, the interviews included only one person at each site. Three people conducted the interviews. Of the 43 micro-system interviews, Mohr conducted 25, Donaldson conducted eight, and Parekh conducted 10 interviews. Several in- dividuals sent additional materials to provide more detail. In a few cases the interviews were interrupted by an urgent clinical situation, and the interviewer scheduled a time to complete the interview. In a number of interviews the respondent volunteered to stay past the 90- minute limit. Overall, the respondents expressed strong interest and willingness to help the committee in its work.
14 INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS TABLE 2 Micro-System Descriptions Primary Care Micro-Systems (n = 15) 1. We are a primary care practice with five physicians. Each physician makes three or four home visits a day. 2. We are a multi-physician family practice office with three full-time and four part-time phy- sicians plus one physician assistant. We have four office staff to answer phones and make appointments, a âfringeâ nurse to handle emergencies, nurses and medical assistants to get patients to rooms, give injections, and draw blood, a medical secretary, several file clerks, an office manager, a billing person and two managed care coordinators. 3. We are an outpatient primary care satellite of a larger multi-specialty system. There are three smaller subgroups that are increasingly independent with the help of an area manager. 4. We provide comprehensive primary health care to 28,000 patients annually through five neighborhood centers and an extensive Community Health Program. We employ a large number of our neighbors and patients as staff. 80 percent of our patients have household in- comes below the Federal Poverty Level. 5. We have 270,000 patients and 110 FTEs. We divided the geographic area into 15 teams with seven different sites. Each team has eight to nine FTEs (doctors and nurses). Patients are divided equitably among the sites. 6. We provide comprehensive primary care and hospital care to a small, rural town of about 15,000. We are a private practice with five GIM docs, three NPs, one PA, six RNs, two re- ceptionists and three billing people. 7. A community based practice with four physicians, two NPs, one PA, three MAs, five recep- tionists, and office manager. We care for 6,500 patients. 8. We are the largest family practice in the area. We have 25 physicians and nine nurses (RNs, LPNs, and MAs). We are divided into three teams. 9. We deliver primary care through a team of four physicians, two LPNs, a RN, a MA. We de- liver care to about 6,000 people. We operate within a clinic of about 20 physicians 10. 10 Family Practitioners and four associate providers are divided into three teams with two RNs and two MAs per team. The teams share a phone center and a receptionist. 11. We integrate acute and long-term care for frail elders into a single system. 12. We have 7.5 FTE physicians and 26 FTE staff taking care of 14,000 patients. 75% of our patients are in managed care programs. Continued
INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS 15 TABLE 2 Micro-System DescriptionsâContinued Primary Care Micro-Systems (n = 15)âContinued 13. We are a community health center with two primary care medical clinics, two school-based teen health centers, and four dental clinics. We have eight FPs, one PA, five NPs, three CNMs. Teams include a provider, nurse, medical assistant, social worker, nutritionist, and outreach worker. 14. We provide health care to indigent people. We have a large enhanced prenatal program. 11 board certified family practice physicians, two part-time pediatricians eight mid-level practitioners, three PAâs, two LCSW, five NPâs, one RD), three RNâs, four Prenatal case managers, two LPNâs, two Referral case managers, one medical assistant, front office, and administrative support 15. We focus on providing family medicine services. We are one FTE physician, two FTEs NP/PA providers, five FTE RNs. Specialty Care Micro-Systems (n = 19) 1. We are an ob/gyn private practice with five physicians, two PAs, two NPs, one office man- ager and 25 employees. We have an in-house lab and attached outpatient surgical center. 2. We are a hospice composed of three outpatient (home-based) teams (corresponding to three geographic areas of the state) and a 10-bed inpatient unit. Each team has a patient care co- ordinator and medical director assigned to it. 3. We provide team-based, function-focused behavioral health care for adults with severe mental illness. three psychiatrists, two vocational specialists, four therapists, eight nurses, six clinical case managers. 4. The Diabetes Care Team consists of the patient, their primary care practitioner, a Primary Care Coordinator (RN), and a Diabetes Self-Care Specialist (LPN) 5. This is an outpatient endoscopy unit with five part-time physicians, three fellows, one NP, six to eight RNs, three technicians, and clerical staff. We primarily care for adult patients. 6. A Spine Center with 18 physicians from 15 disciplines (all depts are represented from pri- mary care to neurosurgery); multidisciplinary care for multidimensional problem - one stop shopping; diagnosis and care for patients with various spine maladies, acute, chronic, op- erative, non-operative. 7. We are a joint effort of two health systems. We assist and encourage adults to do advanced care planning and then make sure written plans are available and followed. This involves 500 physicians. in the community and many RNs, PAs, and social workers. 8. Breast Cancer Screening Program. When women come to our micro-system, it is a screen- ing center that also has a radiology center, as well as all the necessary elements for coordi- nation of care and follow-up of care. Continued
16 INNOVATION AND QUALITY IMPROVEMENT IN MICRO-SYSTEMS TABLE 2 Micro-System DescriptionsâContinued Specialty Care Micro-Systems (n = 19)âContinued 9. We provide diabetes management with Certified Diabetes Educators (Nurses) and endocri- nology support 10. Breast Care/Screening in a breast center. Radiologists and support staff and general sur- geons are integrated and comprise the system with some integration with the health system at largeâprimary care oncology, radiation therapy and pathology 11. Three person congestive heart failure case management team which treats the patient as a whole. There are currently 150 active patients. 450 have been served by our program since it started on Jan. 1, 1995. Recently, in our clinic, I have been seeing 12-13 patients a day either in person or on the phone. 12. Diabetes services are provided throughout the multi-hospital integrated health care delivery system with medical support for this continuum of care provided in partnership with pri- mary care and specialty physicians practicing in many locations. one clinical psychologist, one PA, six-10 RD, CDEs, 2200 primary care and specialty care physicians 13. We work with cardiac services on improving clinical and financial outcomes, decreasing morbidity and mortality. 14. Weâre a specialty clinic providing womenâs and newborn care. 15. Our medical group is responsible for a population of 240,000. There are 7,000 patients with diabetes. The care team is the pcp, the diabetes resource nurse, the LPN, the endocrinolo- gist, and the nutritionist. Diabetes care is integrated into primary care. 16. Weâre providing diabetes care at a county health department. We are working as part of a grant for the state. 17. Weâre working on improving pain management, throughout the our hospital. 18. An ophthalmic consultation center specializing in the management/treatment of complex eye disease and surgery. The primary customer for care are patients and their referring eye doctors (mostly optometrists). 19. We are a mental health department in a large multispecialty clinicâhospital system. The department provides medical, counseling and psychological testing services to all age ranges. We have five psychiatrists (four adult, one child/adolescent), two psychologists, six registered nurses, 16 therapists, and three chemical dependency counselors. Continued