***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
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    Input: ABSTRACT BACKGROUND Patients admitted to general medicine inpatient services are increasingly cared for by hospital-based physicians rather than their primary care providers ( PCPs ) . This separation of hospital and ambulatory care may result in important care discontinuities after discharge . We sought to determine whether communication between hospital-based physicians and PCPs influences patient outcomes . METHODS We approached consecutive patients admitted to general medicine services at six US academic centers from July 2001 to June 2003 . A r and om sample of the PCPs for consented patients was contacted 2 weeks after patient discharge and surveyed about communication with the hospital medical team . Responses were linked with the 30-day composite patient outcomes of mortality , hospital readmission , and emergency department ( ED ) visits obtained through follow-up telephone survey and National Death Index search . We used hierarchical multi-variable logistic regression to model whether communication with the patient ’s PCP was associated with the 30-day composite outcome . RESULTS A total of 1,772 PCPs for 2,336 patients were surveyed with 908 PCPs responses and complete patient follow-up available for 1,078 patients . The PCPs for 834 patients ( 77 % ) were aware that their patient had been admitted to the hospital . Of these , direct communication between PCPs and inpatient physicians took place for 194 patients ( 23 % ) , and a discharge summary was available within 2 weeks of discharge for 347 patients ( 42 % ) . Within 30 days of discharge , 233 ( 22 % ) patients died , were readmitted to the hospital , or visited an ED . In adjusted analyses , no relationship was seen between the composite outcome and direct physician communication ( adjusted odds ratio 0.87 , 95 % confidence interval 0.56 – 1.34 ) , the presence of a discharge summary ( 0.84 , 95 % CI 0.57–1.22 ) , or PCP awareness of the index hospitalization ( 1.08 , 95 % CI 0.73–1.59 ) . CONCLUSION Analysis of communication between PCPs and inpatient medical teams revealed much room for improvement . Although communication during h and offs of care is important , we were not able to find a relationship between several aspects of communication and associated adverse clinical outcomes in this multi-center patient sample The term hospitalist has been introduced to describe physicians who specialize in inpatient medicine and who manage the care of hospitalized patients for primary care physicians [ 1 ] . As both hospital admissions and length of stay decline , the decreasing proportion of time that the average primary care physician spends on the inpatient service and the dem and for efficiency in the practice of medicine have generated interest in hospitalists [ 2 , 3 ] . Potential advantages of the use of hospitalists include the greater expertise and experience of the physicians providing inpatient care , availability of the inpatient physician to make decisions throughout the day , and greater efficiency in the use of time of the outpatient physician , who is freed from inpatient duty [ 1 - 4 ] . These advantages must be weighed against potential disadvantages result ing from the loss of continuity of care . The primary care physician loses the care of the hospitalized patient , and the inpatient physician loses follow-up care when the patient is discharged . The replacement of the familiar outpatient physician by an unfamiliar inpatient physician may decrease patient satisfaction . The relative merits of the hospitalist program can be determined only by studies that measure quality of care , patient satisfaction , and cost and efficiency of care in various setting s [ 1 ] . We report here the experience of a community teaching hospital during the initial year of a hospitalist program . Methods Study Setting Our study was conducted in a 542-bed , independent , urban community hospital in the northeastern United States . The hospital had approximately 19 000 admissions per year during the 2 years of the study . Of these admissions , approximately 5000 were admissions by primary care physicians . The hospital had its own independent residencies in internal medicine , family medicine , radiology , obstetrics and gynecology , and anesthesia . It is affiliated with a medical school and participates in university hospital-based training programs in emergency medicine and plastic surgery . Both the internal medicine and radiology residencies support subspecialty fellowships . Study Patients In the fall of 1995 , a large primary care physician group whose practice was managed by our hospital 's medical services organization agreed to have its inpatient admissions managed by hospitalists , who were members of the full-time faculty in the division of general internal medicine . The study group ( hospitalist group ) consisted of all patients who were admitted to the study hospital by these primary care physicians during the first 12 months in which  hospitalists cared for patients admitted to this hospital . The group 's major primary care office practice was in a hospital-owned physician practice building adjacent to the hospital . The group also had outlying offices and a large nursing home and personal care home practice . Approximately 50 % of its admissions were to other hospitals , primarily those near its other practice sites . Patients admitted to these other hospitals were cared for by the primary care physicians in the primary care group , not hospitalists . All admissions to this hospital during the study years , including multiple admissions for the same patient , were counted as admissions in the study . Admissions to other hospitals were not included . We compared all patients admitted to the study hospital by the hospitalist group in the first year of the hospitalist program ( hospitalist year ) with all patients admitted to the study hospital by the same physician group in the 12 months immediately preceding the study year ( prehospitalist year ) ( comparison group 1 ) . Because many factors in our community influenced length of stay and cost of care during these 2 years , we used two additional comparison groups . To avoid selection bias , we also studied an unselected comparison group consisting of all patients admitted to the study hospital by all primary care internal medicine and family medicine private practice physicians ( with the exception of the study group physicians and the full-time faculty group ) during the prehospitalist year ( comparison group 2 ) and the hospitalist year ( comparison group 3 ) . Patients of these outpatient practice s had a shorter length of stay during the prehospitalist year than the patients of the practice that adopted the hospitalist system . Because this difference could have influenced our results , we also identified subsets of comparison groups 2 and 3 , composed of patients from the five primary care practice s with the longest length of stay , as additional comparison groups ( comparison group 2a for the prehospitalist year and comparison group 3a for the hospitalist year ) . Comparison groups 2a and 3a consisted of patients from outpatient practice s whose prehospitalist lengths of stay were similar to that of the study patients . Physicians of patients in both comparison groups admitted patients to several other hospitals . Most admissions to other hospitals were to suburban hospitals and were based on the hospitals ' geographic proximity to the patient . At the study hospital , all patients in the hospitalist group and comparison groups were admitted to the same nursing units . For all groups , all patients admitted to the intensive care unit and the coronary care unit were assigned resident coverage . One housestaff team with a second-year resident and two first-year residents provided this coverage for patients not admitted to special care units . This team had a maximum capacity of 24 patients . When this capacity was exceeded , newly admitted patients were not assigned housestaff coverage . Approximately 75 % of patients in comparison groups 2 , 3 , 2a , and 3a had resident coverage in both years . Patients in the comparison groups were also admitted without resident coverage when the capacity of the resident teams was exceeded . A few attending physicians preferred to write their own orders and did not have resident coverage on the general medicine floors . On resident-covered services , residents must write all orders . Coverage by a physician assistant was available for all patients who did not have resident coverage .  Physician assistants did not care for patients covered by residents . In comparison group 1 , patients not admitted to critical care units were covered by a physician assistant , but not a resident . We have previously reported that in our hospital , patients with and those without resident coverage had similar diagnosis-related group (DRG)-adjusted lengths of stay [ 5 ] . In all groups , the attending physician responsible for inpatient care was expected to see the patient at least once daily and to communicate with the medical resident or physician assistant . Hospitalist System The hospitalists were members of the full-time faculty in general internal medicine . Two hospitalists covered an average combined inpatient census of 28 study group patients . The hospitalists were in the hospital and available for patient care during regular working hours from Monday through Friday . Three hospitalists spent at least 50 % of their time on inpatient care . One of the hospitalists functioned as a hospitalist throughout the year ; the other two were hospitalists for approximately 6 months per year . Weekend and night call were rotated among all members of the general medicine faculty group . The primary care physicians could make courtesy visits to their patients on the hospitalist service . Hospitalists communicated discharge information to the patients ' primary care physicians through telephone calls to the physicians ' offices and copies of written discharge instructions and discharge summaries . Before the hospitalist year , physicians in comparison group 1 had participated in inpatient rounds on a daily rotating schedule . Thus , patients infrequently saw their own primary care physician . One member of the group spent a large proportion of the time caring for in patients . Most patients in comparison groups 2 , 2a , 3 , and 3a were cared for by their own primary care physician in both study years . Because the hospitalists were present in the hospital throughout the day , they could evaluate patients and make decisions at any time ; in contrast , other attending physicians usually evaluated patients only once per day . It was the attending physician 's and the hospitalist 's responsibility to inform patients of the hospitalist system . The hospitalists had no financial incentive to decrease length of stay or cost of care , but it was understood that these reductions would become a goal of the program . All attending physicians from all groups admitted their patients to the same nursing units and had access to the same clinical protocol s , clinical pathways , utilization review , and discharge planning services . Data Collection and Study Outcomes The methods for data collection and analysis were identical for all groups for both study years . The number of admissions , patient age and other demographic data , insurance source , and length of stay were collected from the Clinical Cost Accounting System ( Huff , Barrington , and Owen Co. ) . Patients were assigned to groups on the basis of the attending physician at discharge listed in this administrative data base .  Discharge diagnosis , DRG , and mortality data were also obtained from this data base . We computed a DRG-adjusted Health Care Financing Administration ( HCFA ) expected length of stay for each group using HCFA expected length of stay adjusted for the DRG assigned to each admission . We also obtained the Medicare case-mix index . We calculated cost of care using a relative value scale method developed by our hospital accounting system as the best approximation of actual hospital costs . Relative value units were developed for every billable patient service . Each unit includes labor , nonlabor , and overhead costs . Readmissions to the study hospital within 14 and 30 days after discharge were collected prospect ively by the hospital as part of its quality Objectives : Authors hypothesized that building safe hospital systems to improve value-based surgical outcomes is predicated on workflow re design for dynamic risk stratification , coupled with “ real-time ” mitigation of risk . We developed a comanagement model for hospitalized surgical cohort , and determined whether this iterative process re design for surgery will be adaptable to disparate hospital systems and will be beneficial for combined medical/surgical adult in patients . Context : Concerns about preventable harm in hospitalized patients have generated a plethora of both , process-driven and outcome -based strategies in US Healthcare . Although comparison between hospitals is a common mechanism to drive quality , other innovative approaches are needed for real-time risk mitigation to improve outcomes . Methods : Prospect i ve implementation of Surgical Continuum of Care ( SCoC ) model in hospitals initially for surgery patients ; subsequently Continuum of Care ( CoC ) for medical/surgical population . Re design of hospital care delivery model : patient cohorting , floor-based team building , and intensivist/hospitalist staffing of progressive care unit ( PCU ) . Work flow re design for clinical effectiveness : multidisciplinary team rounds , acuity stratified care rounding based on dynamic risk assessment into a novel HAWK ( high risk)/DOVE ( low risk ) patient grouping , intensivist/hospitalist comanagement of surgical patients , and targeted response . Study : Pre- and postintervention with concurrent cohort control design . Setting : Academic medical centers for SCoC and integrated health system hospital for CoC. Patient Groups : SCoC Pilot Study –Campus A : Preintervention control group 1998–2000 , Intervention Group 2001–2004 ; Campus B : Comparator Control Group 1998–2004.SCoC Validation Study –Campus C : Preintervention Group 2001–2005 ; Intervention Group 2006–2008 . CoC Study –Campus D : Hospital-wide Group 2009 . Metrics : Mortality , length of stay ( LOS ) : overall , surgical intensive care unit and PCU , readmission rates , and cost . Case mix index for risk adjustment . Results : Total > 100,000 admissions . There was a significant reduction in overall surgical mortality in both , pilot ( P < 0.002 ) and validation ( P < 0.02 ) SCoC studies and overall hospital mortality in the medical/surgical CoC study ( risk-adjusted mortality index progressively declined in CoC study from 1.16 pre-CoC to 0.77 six months post-CoC implementation ; significant at 75 % confidence level ) . Case mix index was unchanged during study period in each campus . Nested study in validation cohort of hospital-wide versus surgery alone ( observed/expected mortality index ) demonstrated significant benefit to SCoC in intervention group . The mortality benefit was primarily derived from risk-stratified rounding and actively managing risk prone population in the PCU . Surgical intensive care unit , PCU , and total hospital patient-days significantly decreased in SCoC pilot study ( P < 0.05 ) , reflecting enhanced throughput . LOS reduction benefit persisted in SCoC validation and CoC studies . In addition to decreased LOS , cost savings were 
    Output:
    
Results The majority of review ed articles demonstrated that hospitalists are efficient providers of inpatient care on the basis of reductions in their patients ' average length of stay ( 69 % ) and total hospital costs ( 70 % ) ; however , the clinical quality of hospitalist care appears to be comparable to that provided by their colleagues .
The method ological quality of hospitalist evaluations  remains a concern and has not improved over time .