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Case Management

Case Management is a collaborative process that assesses, plans, implements, coordinates, monitors, and evaluates the options and services required to meet an individual's health needs.
It is designed to promote quality, cost-effective outcomes by fostering communication and ensuring continuity of care.
This approach optimizes the use of resources, minimizes fragmentation and duplication of services, and enhances patient outcomes and satisfaction.
Case Management is an essential tool for streamlining healthcare delivery and improving patient experiences.
It empowers individuals to actively participate in their care, while also leveraging AI-driven technologies like PubCompare.ai to enhance research reproducibility and identify the most effective protocols from literature, preprints, and patents.

Most cited protocols related to «Case Management»

1
Patient Navigation for Cancer Care
The working definition of patient navigation was provided by the NCI’s CRHCD in their request for applications. 13 In this definition, patient navigation refers to support and guidance offered to persons with abnormal cancer screening or a new cancer diagnosis in accessing the cancer care system, overcoming barriers, and facilitating timely, quality care provided in a culturally sensitive manner. Patient navigation is intended to target those who are most at risk for delays in care, including racial and ethnic minorities and those from low income populations. Furthermore, patient navigation targets specific time points in the cancer care continuum; we operationally define patient navigation as starting at the time of an abnormal screening result and ending at the determination that the screening test was a false positive or, for those individuals with a new cancer diagnosis, continuing through the completion of cancer treatment. The goal of patient navigation is to facilitate timely access to quality cancer care that meets cultural needs and standards of care for all patients.
Examples of navigation services include: arranging various forms of financial support, arranging for transportation to and childcare during scheduled appointments, identifying and scheduling appointments with culturally sensitive caregivers, coordinating care among providers, arranging for interpreter services, ensuring coordination of services among medical personnel, ensuring that medical records are available at each scheduled appointment, and providing other services to overcome access barriers encountered during the cancer care process including linkage to community resources. Navigators work to address health literacy and to train patients to advocate for themselves in the health care system. They are also trained to provide emotional support to patients during this stressful period. Navigators may also identify systems issues that serve as barriers to many patients, and work towards reduce the complexity to the patient of the multidisciplinary approach to care.
The concept of patient navigation is based upon the care management or case management model, which has four components.14 The first is case identification, which is a systematic approach to the identification of those individuals with abnormal cancer screening in need of follow-up care or incident cancers. The second is identifying individual barriers to receiving care. Navigators contact patients and elicit information about the barriers to completion of recommended care. The third is developing an individualized plan to address the barriers that are identified. The fourth is tracking, which is a systematic method of following each case through resolution of the problem. In the case of cancer navigation, this is to resolution of a diagnostic evaluation when a benign condition is diagnosed or follow-up to completion of primary therapy when a cancer or pre-malignant condition is diagnosed.
The navigator will focus on assisting patients and coordinating care of the patients among providers, community, and the patients and their families. Given that patient navigators are working primarily with racial/ethnic minority and low-income patients, cultural competence is a key feature. Cultural and linguistic competence is a set of congruent behaviors, attitudes, and policies that enable effective work in cross-cultural situations.15
PNRP sites vary in the prior training, skill sets, and educational background of navigators and include lay community peers, health educators and advocates, medical assistants, social workers, and nurses. The study has set a minimum requirement of a high school diploma or General Education Diploma. In an effort to achieve a core set of knowledge, skills, and competencies across navigators, a standardized training has been developed. The curriculum focuses on basic information about cancer and its diagnosis and treatment, professionalism, understanding barriers to care, communication skills, cultural competency, ethical conduct of human subjects research, and developing a local network of resources to support patients.16
Freund K.M., Battaglia T.A., Calhoun E., Dudley D.J., Fiscella K., Paskett E., Raich P.C, & Roetzheim R.G. (2008). The NCI Patient Navigation Research Program Methods, Protocol and Measures. Cancer, 113(12), 3391-3399.
Publication 2008
Cancer Screening Case Management Continuity of Patient Care Diagnosis Emotions Ethnic Minorities Follow-Up Care Health Educators Health Literacy Health Personnel Homo sapiens Low-Income Population Malignant Neoplasms Nurses Patient Navigation Patient Navigators Patients Quality of Health Care Racial Minorities
2
Comprehensive Malaria Modeling and Vaccination
The base model is a comprehensive, individual-based model of malaria and vaccination in humans that has been previously published in a supplement to the American Journal of Tropical Medicine and Hygiene[5] ,[30] (link)–[34] (link) Briefly, a simulated population of humans is updated at each 5-d time step via components representing new infections, parasite densities, acquired immunity, uncomplicated and severe malaria episodes (including severe malarial anemia), direct and indirect mortality, infectiousness to mosquitoes, case management [35] (link), and vaccination with a pre-erythrocytic vaccine [36] (link). The simulated malaria infections each have distinct parasite densities that vary by time step, while the level of malaria transmission is assumed to vary seasonally.
The models are constructed in a modular way, with distinct components that represent infection of humans, blood-stage parasite densities, infectiousness of humans to mosquitoes, incidence of morbidity, and mortality. Each of the components aims to capture the relevant biology, while at the same time fitting available data. Simulated immunity acts mainly by controlling parasite densities [30] (link). In turn, the simulated incidence of clinical malaria is a function of parasite density [32] (link), as are the incidences of severe disease and malaria-related mortality [31] (link). Natural immunity to infection without vaccination is acquired only after considerable exposure to Plasmodium falciparum malaria parasites [33] (link).
The ensemble was constructed by varying different modular components of the base model. A total of 30 models, each constructed by substituting different versions of one or more components, were investigated. Sixteen of these models were excluded from the ensemble, either because they were very similar to other models in the ensemble, or because the model-fitting algorithm did not find any sets of parameter values that provided an adequate fit to the data (see “Model Fitting” below). Fourteen models were retained. The modifications of the base model that resulted in inclusion of these 14 models are summarized in Table 2 and described in detail in Text S1. Each of these models was assigned the identifier used for the fitting process. Each specific parameterization evaluated in the fitting process (several thousands for each model; see Text S1) was also assigned a unique identifier. The models were programmed in C++ as part of the open source software platform OpenMalaria (http://code.google.com/p/openmalaria/).
Smith T., Ross A., Maire N., Chitnis N., Studer A., Hardy D., Brooks A., Penny M, & Tanner M. (2012). Ensemble Modeling of the Likely Public Health Impact of a Pre-Erythrocytic Malaria Vaccine. PLoS Medicine, 9(1), e1001157.
Publication 2012
Adaptive Immunity Anemia Case Management Culicidae Dietary Supplements Erythrocytes Homo sapiens Immunity, Innate Infection Malaria Malaria, Falciparum Parasites Response, Immune SERPINA3 protein, human Transmission, Communicable Disease Vaccination Vaccines
3
Health Literacy Assessment in Community Service Users
Data from the administration of Version 1 of the HLQ in the initial phase of a large multi-centre service improvement trial, the Ophelia (OPtimising HEalth LIteracy and Access) project [9 (link)] were used. The data were provided by 813 clients of 8 diverse community-based agencies in Victoria, Australia who were administered the HLQ during the needs assessment stage of the project. The settings and questionnaire respondents who were recruited for the study are described in detail elsewhere [9 (link), 10 (link)]. Briefly, 8 organisations providing Home and Community Care (HACC) services, Hospital Admission Risk Programs (HARP) or community nursing and other chronic disease services from 4 of 8 Department of Health (now Department of Health and Human Services) regions in Victoria were invited to participate in the Ophelia project through an expression of interest process. The respondents comprised people attending one of these 8 participating organisations. Each organisation selected a target group of clients based on a service-provision priority. The majority of the participants were expected to have a chronic health condition although this was not a pre-requisite for inclusion. Trained staff from each organisation collected data from a representative sample of clients within their target group using consecutive methods of recruitment where feasible and employing various strategies for recruiting clients who are traditionally ‘harder to reach’. Selection criteria required that participants should be cognitively able to provide informed consent to participate, and be over the age of 18 years.
Numbers in the selected organisations available for data analysis were:

A Melbourne metropolitan municipal community service = 102 cases;

A rural coastal community health service = 70;

A regional city case management service for chronic and complex clients = 132;

A Melbourne metropolitan community health service = 90;

A Melbourne outer metropolitan community health service = 108;

A Melbourne outer metropolitan municipal community service = 97;

A regional community health service = 99;

A Melbourne metropolitan domiciliary nursing service = 115.

Elsworth G.R., Beauchamp A, & Osborne R.H. (2016). Measuring health literacy in community agencies: a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ). BMC Health Services Research, 16, 508.
Publication 2016
Case Management Disease, Chronic Health Literacy Needs Assessment Nursing Services
4
Prostate Cancer Biomarker Profiling
We identified 150 cases at the Atlanta Veterans Administration Medical Center (AVAMC) hospital between 1990–2000 that could potentially be used for this project. We were able to locate slides and formalin-fixed paraffin embedded (FFPE) blocks for 100 of those cases, and identified regions of cancer and benign tissue in slides for each of them. These samples were then submitted for processing to obtain 1 mm tissue cores. We prepared RNA from 99 AVAMC samples of which 79 passed our RNA quality control (QC) analysis for genomic profiling. We also obtained 81 samples from the Sunnybrook Health Science Center (Toronto, ON) and 99 RNA samples from the Moffitt Cancer Center (MCC) in Tampa, FL. Approximately 80% of samples passed QC analysis.
Those samples that were included had sufficient RNA yield, met specific inclusion criteria, had available tissue specimens, documented long term follow-up and consented to participate or were included by IRB consent waiver. MCC subjects were prostate cancer patients who underwent radical prostatectomy at the Moffitt Cancer Center between 1987–2003. Prostate cancer cases were men 21 years and older who had surgery for their disease at the Moffitt Cancer Center and had pathologically confirmed primary prostate cancer. AVAMC cases were prostate cancer patients who underwent radical prostatectomy between 1990–2000. University of Toronto (UT) cases were prostate cancer patients who underwent radical prostatectomy at the Sunnybrook Health Science Center between 1998–2006. Exclusion criterium included recurrent patients who underwent hormonal or radiation treatment before radical prostatectomy. The cases were assigned prostate ID numbers to protect their identities. These patients did not receive neo-adjuvant or concomitant hormonal therapy. Their demographic, treatment and long-term clinical outcome data have been collected and recorded in an electronic database. Clinical data recorded include PSA measurements, radiological studies and findings, clinical findings, tissue biopsies and additional therapies that the subjects may have received. In total, 106 samples from 100 patients were sequenced by next generation sequencing: 61 from the AVAMC, 35 from Toronto, and 10 from MCC. Of these cases 49 had biochemical recurrence (BCR) and 51 had no BCR. Of those 100 patients, 97 had complete PSA data and were included in construction of biomarker prediction models. We used only 10 of the 99 MCC cases for several reasons including limited RNA yield, the fact that only three cases had BCR, and funding limitations to conduct sequencing analyses.
Long Q., Xu J., Osunkoya A.O., Sannigrahi S., Johnson B.A., Zhou W., Gillespie T., Park J.Y., Nam R.K., Sugar L., Stanimirovic A., Seth A.K., Petros J.A, & Moreno C.S. (2014). Global transcriptome analysis of formalin-fixed prostate cancer specimens identifies biomarkers of disease recurrence. Cancer research, 74(12), 3228-3237.
Publication 2014
Biological Markers Biopsy Case Management Formalin Malignant Neoplasms Operative Surgical Procedures Paraffin Embedding Patients Pharmaceutical Adjuvants Prostate Prostate Cancer Prostatectomy Radiotherapy Recurrence Sequence Analysis Signs and Symptoms Tissues Veterans X-Rays, Diagnostic
5
Multifaceted Weight Loss Intervention Protocol
Randomization was stratified according to sex and was generated in blocks of 3 and 6 with the use of a Web-based program. The research staff who notified participants of their assignment were not involved in the collection of follow-up data.
Participants had an equal chance of being assigned to any one of the three study groups. The theoretical framework for the two active interventions was based on social cognitive theory and incorporated behavioral self-management approaches designed to help participants set weight-related goals, self-monitor weight and weight-related behaviors (exercise and reduced calorie intake), increase self-efficacy and social support, and solve problems. These approaches were modeled on those tested in previous trials.15 (link)–17 (link) Motivational interviewing was the primary approach to interactions with participants. Participants in the two intervention groups were encouraged to lose 5% of their baseline weight within 6 months and to maintain the reduced weight until the end of the study. Table 1 shows the key features of the two intervention groups. (For more information on the interventions, see the protocol and the Supplementary Appendix, available at NEJM.org.)
Participants in both intervention groups were encouraged to log on to the study-specific Web site weekly. The Web site contained learning modules; opportunities for self-monitoring of weight, calorie intake, and exercise; and feedback on progress in these key behaviors. Each participant who was assigned to an active intervention received automated monthly e-mail messages summarizing his or her progress. Automated re-engagement e-mail messages were sent to participants who had not logged on to the Web site in the preceding 7 days.
Weight-loss coaches encouraged participants to complete the learning modules and provided positive reinforcement of key behaviors, with an emphasis on self-monitoring of weight, calorie intake, and exercise. Individual sessions (in person or by telephone) were approximately 20 minutes long; group sessions conducted for the group receiving in-person support typically lasted 90 minutes. Participants in both intervention groups were offered weekly contact with coaches during the first 3 months (nine group sessions and three individual sessions for participants receiving in-person support, and 12 weekly calls for those receiving only remote support). During the next 3 months, participants receiving in-person support were offered three monthly contacts (one group session and two individual sessions), whereas the group receiving only remote support were offered 1 call each month. For the remainder of the study, participants in the group receiving in-person support were offered two monthly contacts (one group session and one individual session, with the latter conducted either in person or by telephone), and the group receiving only remote support continued to be offered monthly calls.
The coaches for the group receiving in-person support were employees of Johns Hopkins University, and the coaches for the group receiving only remote support were employees of Healthways. Coaches were trained before enrollment of the first participant and on a quarterly basis thereafter. The topics covered included behavioral theory and strategies, basic nutritional and exercise guidelines, motivational interviewing techniques, and study procedures, including use of the intervention Web site. To assess fidelity to the protocol and to promote motivational interviewing techniques, a case-management team observed the coaches and provided feedback monthly for the first 3 months of the study and quarterly thereafter.
Participants in the control group met with a weight-loss coach at the time of randomization and, if desired, after the final data-collection visit, at 24 months. They also received brochures and a list of recommended Web sites promoting weight loss.
Appel L.J., Clark J.M., Yeh H.C., Wang N.Y., Coughlin J.W., Daumit G., Miller ER I.I.I., Dalcin A., Jerome G.J., Geller S., Noronha G., Pozefsky T., Charleston J., Reynolds J.B., Durkin N., Rubin R.R., Louis T.A, & Brancati F.L. (2011). Comparative Effectiveness of Weight-Loss Interventions in Clinical Practice. The New England journal of medicine, 365(21), 1959-1968.
Publication 2011
Case Management Conditioning, Psychology Positive Reinforcement Self-Management

Most recents protocols related to «Case Management»

1
Burnout Prevention in VA Mental Health Teams
The study targeted clinicians in VA-based general outpatient mental health teams, known as BHIP teams. As noted above, mental health care teams often report high levels of burnout and occupational stress and require interdisciplinary coordinated care. These teams typically include 5–10 full-time mental health staff (e.g., psychiatrists, psychologists, social workers, nurses, and administrative support), treating about 1,000 Veteran patients per team (U.S. Department of Veterans Affairs, 2019 ). Clinical services delivered within BHIPs can include individual psychotherapy, group psychotherapy, medication management, peer support, and case management.
Spitzer E.G., Kaitz J., Fix G.M., Harvey K.L., Stadnick N.A., Sullivan J.L., Williamson A.K, & Miller C.J. (2023). Developing Relational Coordination: A Qualitative Study of Outpatient Mental Health Teams. Administration and Policy in Mental Health, 50(4), 591-602.
Publication 2023
Burnout, Psychological Case Management Group Psychotherapy Mental Health Nurses Outpatients Patients Pharmaceutical Preparations Psychiatrist Psychotherapy Respiratory Diaphragm Veterans
2
Malaria Intervention Approaches in Kisii County, Kenya
This study was conducted in Kisii County, Kenya in the year 2021, during the months of February to June. The county has nine sub-counties. The county is located approximately 306 kms from the capital city, Nairobi. It lies at latitude: (0.41°) South, longitude: (34.46°) East. According to the 2019 Kenya population and housing census, the county population size is 1,266,660 persons [16 ]. The main economic activity is agriculture. The county is characterized by hilly topography interspersed with ridges and valleys. The county is characterized by seasonal and permanent rivers which flow into Lake Victoria. The county exhibits a highland equatorial climate with an average rainfall of 1500 mm/year. The average temperature range is between 21 and 30 °C. Most of the population lives in rural areas, residing in local houses. The county health system consists of government and private-based health facilities. The government sector has one teaching and referral hospital (KTRH), which serves as a regional reference hospital and a teaching hospital for Kisii University Medical School. This county contains 14 sub-county hospitals. The county also contains 84 dispensaries, 28 health centres and 32 community health units, which serve as centres for minor health cases [17 ]. The county records three rain seasons namely; April–May, August–September and November–December. The main killer disease is malaria. The main malaria intervention approaches used to combat malaria in this region include proper case management with anti-malarial drugs, such as artemisinin-based combinations, intermittent prophylaxis during pregnancy (IPTp) and the use of mosquito nets. The current drug of choice for treating uncomplicated malaria is artemether-lumefantrine. Diagnosis and treatment services of malaria are available in all government health facilities and a few private facilities. The current study was conducted in hospitals selected from 4 sub-counties (Kenyenya, Marani, Bonchari,Nyamache) of Kisii County (Fig. 1). A molecular study was conducted at the Molecular Biology and Immunology Laboratory, School of Health Sciences, Makerere University, Kampala, Uganda.

A map showing the study area. A Shows the country Kenya where Kisii County is located. B Shows Nyanza region where Kisii County is located and C shows different sub-counties of Kisii County where sampling was conducted (Map drawn by author)

Maniga J.N., Samuel M., John O., Rael M., Muchiri J.N., Bwogo P., Martin O., Sankarapandian V., Wilberforce M., Albert O., Onkoba S.K., Adebayo I.A., Adeyemo R.O, & Akinola S.A. (2023). Novel Plasmodium falciparum k13 gene polymorphisms from Kisii County, Kenya during an era of artemisinin-based combination therapy deployment. Malaria Journal, 22, 87.
Publication 2023
Antimalarials artemisinine Case Management Climate Diagnosis Lumefantrine, Artemether Malaria Mosquito Nets Pharmaceutical Preparations Pregnancy Rain Rivers
3
Screening and Referral for Pediatric Dental Patients
The demographic characteristics of the pediatric dental patient and parent/guardian participants were obtained from the Dentrix electronic health record (EHR) for each patient and supplemented by direct report of the parent/guardian participants prior to their completion of the following two surveys administered in English and Spanish: (1) Parent Adversity Scale, with validated questions pertaining to food security, basic household needs, literacy, personal safety, transportation needs, and other domains based on findings from the Institute of Medicine and CMS [19 ], and (2) Parent/Guardian Perceptions of Adversity Screening at Dental Visits, with questions on the acceptability of the SDOH screening and referral intervention in dental clinics that was developed by the principal investigator (R. K.) for this study. If they so desired, the parents/guardians who identified SDOH needs were then referred to the Family Support Center with case management provided by an assigned counselor who assisted them in obtaining required referrals, resources, and services.
The dental provider participants completed both pre- and post-intervention surveys developed by the principal investigator (R. K.) for this study regarding their experiences screening patients and their families for SDOH and their comfort in doing so on an ordinal rating scale (minimally comfortable, moderately knowledgeable, competent, highly experienced). Moreover, the pre-intervention survey also included questions on provider status (resident, faculty), years practicing dentistry, and training in SDOH. Finally, the post-intervention survey also included open-ended questions seeking suggestions for improving resident training in SDOH and recommendations for enhancing the intervention protocol.
Kaur R., Lieberman M., Mason M.K., Dapkins I.P., Gallager R., Hopkins K., Wu Y., Troxel A.B., Rashwan A., Hope C., Kane D.J, & Northridge M.E. (2023). A feasibility and acceptability study of screening the parents/guardians of pediatric dental patients for the social determinants of health. Pilot and Feasibility Studies, 9, 36.
Publication 2023
Case Management Counselors Dental Health Services Faculty Hispanic or Latino Households Legal Guardians Parent Patients Safety
4
Integrating SDOH Screening in Pediatric Dentistry
The NYU Grossman School of Medicine Institutional Review Board (IRB) reviewed and approved all study procedures (s20-00,696) for this prospective mixed-methods study. The IRB-approved protocol that includes the study instruments is available from the corresponding author upon written request. All Health Insurance Portability and Accountability Act (HIPAA) safeguards were followed. The provider participants in the study consist of 15 pediatric dentists (residents and faculty) employed at FHC who were introduced to the study during departmental meetings held in 2020, expressed a desire to be involved, provided informed consent, and underwent calibration on the administration of the SDOH screening instrument to the parents/guardians and the referral process for those desiring follow-up. The patient and parent/guardian participants consist of 40 pediatric dental patient–parent/guardian dyads who visited FHC in 2020–2021 for regularly scheduled dental appointments, were introduced to the study by a research team dentist who was not involved in treating the pediatric dental patient, and provided informed consent.
Feasibility was assessed using pediatric dental provider surveys administered pre- and post-implementation of the SDOH screening and referral protocol and the case management log of the assigned counselor in the Family Support Center at the health center. The a priori feasibility criterion was that post-intervention, 80% or more of the parents/guardians who endorsed SDOH needs were successfully referred to an assigned counselor at the Family Support Center. Acceptability was assessed using a parental/guardian perception questionnaire administered after completion of the SDOH screening and referral protocol. The a priori acceptability criterion was that 80% or more of the parent/guardian participants would feel comfortable completing the SDOH screening and referral intervention at the dental clinic.
Kaur R., Lieberman M., Mason M.K., Dapkins I.P., Gallager R., Hopkins K., Wu Y., Troxel A.B., Rashwan A., Hope C., Kane D.J, & Northridge M.E. (2023). A feasibility and acceptability study of screening the parents/guardians of pediatric dental patients for the social determinants of health. Pilot and Feasibility Studies, 9, 36.
Publication 2023
ARID1A protein, human Case Management Counselors Dental Health Services Dentist Ethics Committees, Research Faculty Feelings Legal Guardians Parent Patients Pediatric Dentist Pharmaceutical Preparations
5
Community-Based Older Adult Participation Study
Participants will be recruited into the study on a rolling basis and will be drawn from multiple community agencies as well as other public places, including social media and local news outlets. The social service agencies that participated in this study’s intervention development and implementation feasibility phase were predominantly Area Agencies on Aging based throughout Michigan. These agencies serve older adults by offering services to enable their clients to maintain independence. These services may involve case management, caregiver services, and meals on wheels. These agencies will refer participants to the study based on their judgment of the appropriateness of the intervention for their clients.
After receiving referrals, study personnel will contact potential participants via phone to screen for eligibility. The initial screening is expected to take 20 minutes to complete. Participants will provide recorded verbal consent. Those who decline to participate will be referred back to their case managers or agency when possible. Advertisements placed via social media (eg, Facebook and Nextdoor) and through research registries will also allow participants to self-refer and be screened for eligibility.
Those who qualify for the trial will be paid up to US $100. Compensation is determined based on the number of assessments completed. Partial compensation is available (eg, participants who complete only the baseline assessment will receive US $30).
Kayser J., Wang X., Wu Z., Dimoji A, & Xiang X. (2023). Layperson-Facilitated Internet-Delivered Cognitive Behavioral Therapy for Homebound Older Adults With Depression: Protocol for a Randomized Controlled Trial. JMIR Research Protocols, 12, e44210.
Publication 2023
Aged Case Management Case Manager Eligibility Determination

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