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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis 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) advise us on study design and interview questions. The steering group was composed of members of the QHCA's 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 subcommittee), 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 Dartmouth 's 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. Batalden's separate proposal to study micro-systems. To maximize communications between the Dartmouth group and IOM project, we 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); appointed Dr. Batalden as a consultant to the committee and a member of the steering group; and 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 Improvement's 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. Donaldson participated in a two-day conference of these site leaders which provided further insight into some organizational and leadership issues relevant to improving performance. Because some of the recommended sites were participants in ID-COP, it also helped this study's site selection process.
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis Finally, Andrew Balas, M.D., Ph.D., University of Missouri-Columbia, convened experts 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 the members recognize themselves as having a common aim, service line, or clinical 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 defined purpose; or units that have a direct service relationship to patients; that is, they speak to or touch the patient or are “one step away” from doing so; the members recognize themselves as part of a team that consciously organizes its work processes; the people who share an intimacy of working relationship; and 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 directly with these patients. Stage 2: Study Design and Data Collection During the second stage of the study we developed and finalized the protocol, selected 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 1999—we 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
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis 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 interview. 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 respondent 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 conceptual 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 experience, (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 (“Level of Performance ”) included the following questions: What is your micro-system successful at doing? How do you define success? How do you know you are successful? What data are you collecting? If I were a patient, how would I experience care at your micro-system differently? If I were a clinician, how would I experience it differently from another micro-system that treats similar patients? How would you describe the day-to-day work environment? What does it feel like to work at____? What has your micro-system done to support professional ethics, encourage peer feedback or skill development? Optional: How long has the micro-system been working this way? How is it different now from an earlier time?
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis Site Selection Sites were selected based on their likelihood of informing the research. We used an interative process sometimes called a “snowball strategy ” (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 Improvement's Breakthrough Series who had made significant improvement between the beginning 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 IHI's 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 Cooperative of Puget Sound and national program office for “Improving Chronic Illness Care” 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 winnowing 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 States—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
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis TABLE 2 Range of Micro-Systems Studied 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 respondent, 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 simultaneously take good notes, the interview process was simplified to include a single interviewer-
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis 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 because 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 complete and return the pre-interview survey prior to the telephone interview. All the sites complied with this request. The Preinterview Survey. The purpose of the pre-interview survey was to gather basic information 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 review basic descriptive information about the site before the interview and to ask for any clarification of pre-interview responses during the interview. Based on the pre-interview responses, 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 interview 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 timeframe, June 29, 1999 through September 3, 1999. Interviews were conducted with the person identified as the “leader” 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 individuals 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.
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis TABLE 2 Micro-System Descriptions Primary Care Micro-Systems (n = 15) We are a primary care practice with five physicians. Each physician makes three or four home visits a day. We are a multi-physician family practice office with three full-time and four part-time physicians plus one physician assistant. We have four office staff to answer phones and make appointments, a “fringe ” 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. 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. 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 incomes below the Federal Poverty Level. 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. 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 receptionists and three billing people. A community based practice with four physicians, two NPs, one PA, three MAs, five receptionists, and office manager. We care for 6,500 patients. 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. We deliver primary care through a team of four physicians, two LPNs, a RN, a MA. We deliver care to about 6,000 people. We operate within a clinic of about 20 physicians 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. We integrate acute and long-term care for frail elders into a single system. 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.
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis 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. 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 PA's, two LCSW, five NP's, one RD), three RN's, four Prenatal case managers, two LPN's, two Referral case managers, one medical assistant, front office, and administrative support 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) We are an ob/gyn private practice with five physicians, two PAs, two NPs, one office manager and 25 employees. We have an in-house lab and attached outpatient surgical center. 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 coordinator and medical director assigned to it. 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. The Diabetes Care Team consists of the patient, their primary care practitioner, a Primary Care Coordinator (RN), and a Diabetes Self-Care Specialist (LPN) 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. A Spine Center with 18 physicians from 15 disciplines (all depts are represented from primary care to neurosurgery); multidisciplinary care for multidimensional problem - one stop shopping; diagnosis and care for patients with various spine maladies, acute, chronic, operative, non-operative. 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. Breast Cancer Screening Program. When women come to our micro-system, it is a screening center that also has a radiology center, as well as all the necessary elements for coordination of care and follow-up of care.
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis We provide diabetes management with Certified Diabetes Educators (Nurses) and endocrinology support Breast Care/Screening in a breast center. Radiologists and support staff and general surgeons are integrated and comprise the system with some integration with the health system at large—primary care oncology, radiation therapy and pathology 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. 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 primary care and specialty physicians practicing in many locations, one clinical psychologist, one PA, six-10 RD, CDEs, 2200 primary care and specialty care physicians We work with cardiac services on improving clinical and financial outcomes, decreasing morbidity and mortality. We're a specialty clinic providing women's and newborn care. 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 endocrinologist, and the nutritionist. Diabetes care is integrated into primary care. We're providing diabetes care at a county health department. We are working as part of a grant for the state. We're working on improving pain management, throughout the our hospital. 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). We are a mental health department in a large multispecialty clinic —hospital 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.
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis Hospital Unit Micro-Systems (n = 9) We are a geriatric unit in a large medical center. We are a Level III Intensive Care Nursery caring for intermediate and critically ill newborns. It is staffed by a multidisciplinary team of neonatalogists, residents, NNPs, nurses, respiratory therapists, and others. We are an Emergency Department with 10 docs, a slew of nurses, and other people. We are a cardiothoracic surgical unit. The Critical Care micro-system consists of 36 beds divided into the 12 bed Shock-Trauma-Respiratory ICU, the 16 bed Medical-Surgical ICU, and the eight bed Respiratory Special Care Unit. All are open ICUs. The hospital is a academic referral center for a 400 mile radius and a Level 1 Trauma Center. The system integrates the activities of five full time hospital employed academic critical care medicine (CCM) physicians along with six private practice pulmonary/CCM physician with about 90 private staff physicians who admit and care for this population including the active Level 1 trauma and the neurosurgical services. Critical Care Services: MICU (10 beds), SICU (14 beds), CCU (10 beds (total = 34 beds), NICU, EC, and Critical Care Transport teams. 225 physicians, all specialties and subspecialties We do only [one or two surgical procedures]. We have 11 surgeons, eight assistants. The entire staff is about 75. We are five surgeons doing cardiothoracic surgery. Private practice, three partners, two associates. We work at the hospital with 12 mid-level PAs and NPs who were hired by the hospital. We have four secretarial office staff We are a MICU and SICU. We have an open ICU—any physician with admitting privileges can admit to the ICU. As noted, not every respondent was asked every question because some questions were not relevant or were optional. Table 3 summarizes the interview completion rate. For each question, the table shows the number of sites asked the question and the completion rate for that question (calculated as the number of sites asked divided by 43). This is a very conservative rate, however, because in responding to the open-ended questions, some respondents formulated a response to a later question before the interviewer had an opportunity to ask it. When this occurred, the information was recorded as part of the original question rather than breaking apart responses and inserting them into later sections. Responses that answered a later questions were frequent and are not reflected in this table. However, all responses were incorporated into the final analysis.
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis TABLE 3 Question Completion Rate Interview Question Sites Asked % Completion (sites asked / 43) Level of Performance 43 100% Success 42 98% Measures 28 65% Patient 37 86% Clinician 28 65% Culture 23 53% Professional 10 23% How long 22 51% Patient and Clinician Experience 41 95% New Patient 28 65% Scheduling 15 35% Risk assessment 17 40% Pt information 23 53% Waits and delays 25 58% Incentives 9 21% Community 16 37% Information and IT 34 79% Improvement 40 93% Specific projects 28 65% Evidence of success 4 9% Barriers 26 60% Awareness of results 2 5% Funded projects 5 12% Leadership training 6 14% Expert systems 25 58% Clinical evidence 12 28% Best practices 15 35% Information sharing 6 14% Error and patient safety 21 49% What happens 21 49% Culture 3 7% Procedures 3 7% Sources of error 6 14% Leadership 42 98% Macro-system helps 19 44% Macro-system is toxic 17 40% Ideal financial structures 15 35% Replication 30 70% Barriers 23 53%
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis A contact summary sheet (top of Appendix D) was used to summarize each interview (Miles and Huberman 1994). Its purpose was to capture the primary issues that emerged from the interview shortly after it was completed. The contact summary sheet prompted the interviewer to think about the main issues that emerged during the interview and to identify verbatim comments that illustrated them. This step was helpful in the transition from transcribing notes to coding data because it engaged thinking about the analysis throughout the interview process and while the interview was fresh in mind, instead of waiting until the completion of all the interviews to begin analysis. Stage 3: Data Analysis Case-Level Summary Analysis of Health Care Micro-Systems Q.S.R. NUD*IST was selected as best suited for managing and organizing the data which comprised multiple cases but a single source from each case. Q.S.R. NUD*IST® 4.0 (Non numerical Unstructured Data Indexing Searching and Theorizing) is a multi-functional software system for the development, support and management of qualitative data analysis. Because this research was exploratory, it was important to be able to code and make coding revisions as the analysis progressed. This software facilitated the coding, sorting, and refining of categories by creating logs of the changes that were made and allowing custom searching and retrieval of text. Transcribed interviews were entered as data to form display matrices. These can be thought of as meta-matrices, or master charts used to assemble multiple cases in a standard format. 25 The objective is to include all the case-level data in one matrix before summarizing, refining, and further reducing the data. The matrices are considered to be “partially ordered” because very little order is imposed on the display of the data. The completed meta-matrices are the first look at the cross-case data. The creation of the matrices required identifying variables that were thought to be relevant to the study. To avoid imposing a rigid framework on the data early in the analysis, initially the interview questions were used as the relevant variables. For example, because each interview is coded by interview question, it is possible to find all the micro-system responses to Question I.6. “If I were a patient at____, how would I experience the care differently?” Although the questions from the interview served as the initial relevant variables, additional variables emerged as the study progressed. Looking at the data by interview question is useful, but still represents raw data. For this reason, coding was then used to assign descriptive codes to each phrase, sentence, or groups of words that represent common concepts. This is called “first level coding.” 26 Table 4 lists the variables that emerged from the transcripts and that were used for the first level coding of the interview data.
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Exploring Innovation and Quality Improvement in Health Care Micro-Systems: A Cross-Case Analysis TABLE 4 Micro-System Variables Variable Working Definition Investment in Improvement An effort to ensure that improvement is part of the work of the micro-system. Alignment of Roles and Training The match between a health professionals' educational training, certification, etc. and their work. Constancy of Purpose Integration of the aim throughout the micro-system. Values A set of beliefs that guide the work of the micro-system Organizational Support Ways the macro-system facilitates the work of the micro-system. Multidisciplinary Team The existence and recognition of the team approach to care. Community Connection Micro-system is a resource to the community/community is a resource to the micro-system. Micro-system Measures Variables high-performing micro-systems are monitoring (or think are important to monitor). Use of Information and Information Technology Information is key, technology can be very helpful. Barriers Challenges and constraints to the work of the micro-system. Resources for Replication Necessary elements to design and implement a similar micro-system. Evidence of the Micro-System An indication that the site is a micro-system. Improvement Example Examples of improvement projects made within the micro-systems Leadership Importance of leadership to the work of the micro-system Cross-Case Analysis Cross-case analysis involved searching each interview for examples. This was an iterative process because themes emerged and evolved throughout the coding. As the analysis continued, the variables listed in Table 4 were refined—some were grouped into categories, and some were dropped because they did not rise to the status of a theme that could characterize the micro-system. For example, “barriers” was a common idea found throughout the interviews, but barriers are not a characteristic of micro-systems. How the micro-systems deal with barriers, perhaps through an investment in improvement or use of information and information technology, did appear to be characteristic of the micro-systems interviewed, however and were coded in this way.
Representative terms from entire chapter: