Value of Technology to Transfer Discharge Information

Interprofessional Relations Clinical Trial

Official title:

Value of Technology to Transfer Discharge Information

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT00101868
• Other study ID #: 1RO1HS015084-01
• Secondary ID: 1RO1HS015084-02
• Status: Completed
• Phase: N/A
• First received: January 14, 2005
• Last updated: April 16, 2012
• Start date: December 2004
• Est. completion date: August 2007

Study information

• Verified date: April 2012
• Source: Agency for Healthcare Research and Quality (AHRQ)
• Contact: n/a
• Is FDA regulated: No
• Health authority: United States: Federal Government
• Study type: Interventional

Clinical Trial Summary

The transition from hospital to home is a high-risk period in a patient's illness. Poor communication between healthcare providers at hospital discharge is common and contributes to adverse events affecting patients after discharge. The importance of good communication at discharge will increase as more primary care providers delegate inpatient care to hospitalists. Any process that improves information transfer among providers at discharge might improve the health and safety of patients discharged from U.S. hospitals each year, and to appreciably reduce unnecessary healthcare expenditures. Information transfer among healthcare providers and their patients can be undermined because of inaccuracies, omissions, illegibility, logistical failure (e.g., information is never delivered), and delays in generation (i.e., dictation or transcription) or transmission. Root causes include recall error, increased physician workloads, interface failures (e.g., physician-clerical) and poor training of physicians in the discharge process. Many of the deficiencies in the current process of information transfer at hospital discharge could be effectively addressed by the application of information technology. The proposed study will measure the value of a software application to facilitate information transfer at hospital discharge. The study is designed to compare the benefits of discharge health information technology versus usual care in high-risk patients recently discharged from acute care hospitalization. The design is a randomized, single-blind, controlled trial. The outcomes are readmission within 6 months, adverse events, and effectiveness and satisfaction with the discharge process from the patient and physician perspectives. The cost outcome is the physician time required to use the discharge software.

Description:

Objectives: The study is designed to compare the benefits of discharge health information technology versus usual care in high-risk patients recently discharged from acute care hospitalization.

STUDY HYPOTHESES:

The primary efficacy endpoint is the proportion of patients readmitted at least once within 6 months after the index admission. Readmission is for any reason and includes observation status and full admission status.

Primary hypothesis: Among high-risk patients recently discharged from acute care hospitalization, there is a significant decrease in the primary efficacy endpoint for patients who receive discharge health information technology versus usual care discharge instructions.

Secondary hypothesis 1A: In the same patient population, the time to first readmission is greater for patients who receive discharge health information technology versus usual care discharge instructions.

Secondary hypothesis 1B: In the same patient population, the mean number of hospital days per patient within 6 months after index hospital discharge is lower for patients who receive discharge health information technology versus usual care discharge instructions.

Secondary hypothesis 2: In the same patient population, the mean score for effectiveness and satisfaction with discharge process is greater for patients who receive discharge health information technology versus usual care discharge instructions.

Secondary hypothesis 3: In the same patient population, the proportion of patients who report their pharmacist needed to clarify the discharge prescription is lower for patients who receive discharge health information technology versus usual care discharge instructions.

Secondary hypothesis 4: In the same patient population, the proportion of patients with at least one adverse event within 4 weeks after hospital discharge is lower for patients who receive discharge health information technology versus usual care discharge instructions.

Secondary hypothesis 5: In the same population, the mean satisfaction score with drug information will be higher for patients who receive discharge health information technology versus usual care discharge instructions.

Secondary hypothesis 6: Among primary care physicians who provide post-discharge care to high-risk patients, the mean score for discharge process effectiveness and satisfaction will be greater for patients who receive discharge health information technology versus usual care discharge instructions.

Secondary hypothesis 7: Among hospitalist physicians who discharge high-risk patients, the mean score for physicians' satisfaction with the discharge process will be greater for physicians assigned to discharge health information technology versus usual care discharge instructions.

METHODS: The trial design is a randomized cluster, single-blind (outcome assessors blind), controlled trial. The study design conforms to recent guidelines for randomized controlled trials. The test intervention is discharge application of health information technology. The control intervention is usual care (hand-written discharge instructions) described below. Each patient will remain in the study for 6 months. Enrollment in the study will last approximately 18 months. There will be no interim analysis.

Research personnel will obtain informed consent from potentially eligible inpatients. Informed consent from patients will occur during the screening visit.

Screening visit: Investigators will train research personnel to perform screening and informed consent. The screening visit may occur within 2 days of the planned discharge. After obtaining informed consent, research personnel will record items in the baseline assessment. Research personnel will ask patients about self-rated health, coronary artery disease (including angina pectoris myocardial infarction), diabetes mellitus in past year, hospitalization in past year, number of doctor visits in past year, presence of an informal caregiver able to care for the patient for several days, age, and gender. The screening questionnaire was validated. Research personnel will calculate a PRA score during the screening visit. PRA scores 0.5 and above define high-risk patients who have a 50% probability of being admitted to a hospital two or more times within 4 years. When the PRA score is applied to Medicaid beneficiaries followed for one year, 57% of patients with PRA 0.5 and above will have at least one hospital admission or 0.99 +/- 0.24 hospital admissions per person-year survived (mean +/- SE). Research personnel will offer informed consent to patients with PRA score 0.4 and above.

Research personnel will record limited information for patients who are ineligible or who refuse consent.

Baseline Assessment: The baseline assessment will occur after informed consent and before discharge. The ten-point clock test will be used as the screening instrument for orientation. Research personnel will record patient's name, address, age, stated race, gender, and discharge medication prescription. Research personnel will record patient contact information and alternate contact information in order to perform post-hospital telephone interviews required by the protocol.

Intervention allocation: The time of random treatment allocation will be after the baseline assessment and before discharge. Patients will not receive study treatment if they fail to consent or if they fail the inclusion/exclusion criteria. Treatment assignment will be in a 1:1 ratio to either discharge application of health information technology or usual care discharge instructions. The unit of randomization will be the hospitalist physician who performs the discharge process. The randomization process is designed to assure random allocation by cluster with the cluster determined by the discharging physician. Allocation concealment is not possible since all the enrolled patients who are discharged by the hospitalist physician will receive the same study intervention.

Dispense patient logbook: The purpose of the patient logbook is to promote ascertainment of study endpoints.

Patient telephone interview: discharge process effectiveness and satisfaction The purpose of the first telephone interview is to acquire data to measure secondary endpoints 2, 3, and 5. One week (5 to 9 days) after the hospital discharge date, research personnel will perform a telephone interview with the patient. Interviewers will instruct the patient to avoid mentioning the random intervention assignment. To address secondary hypothesis 2, interview questions will follow the PREPARED text. The PREPARED instrument surveys four key process domains: information exchange (community services and equipment), medication management, preparation for coping after discharge and control of discharge circumstances. The questions in PREPARED measure the patient's overall satisfaction with discharge, whether equipment and community service needs were met, and use of health services and health related costs post-discharge. The telephone interviewers will ask patients if their pharmacist had to call the doctor when attempting to fill the discharge prescriptions. The purpose of the question about pharmacists is to address secondary hypothesis 3. The telephone interviewers will ask questions from the Satisfaction with Information about Medicines Scale (SIMS). The SIMS is a 17-item survey with internal consistency and test-retest reliability. The SIMS survey instrument addresses secondary hypothesis 5.

Primary care physician questionnaire: discharge process effectiveness and satisfaction. The primary care physician questionnaire addresses secondary hypothesis 6. Within 10 to 18 days after the hospital discharge date, research personnel will contact the primary care physician to perform a survey.

Patient interview: adverse event assessment. The purpose of the second patient interview is to address secondary hypothesis 4. Approximately 4 weeks (20 to 40 days) after the index hospital discharge date, research physician personnel will perform a telephone interview with the patient. Physicians trained to assess adverse events will perform the telephone interview. Interviewers will instruct the patient to avoid mentioning the random intervention assignment. The interview tool is a modification of a validated survey instrument.

Hospitalist (discharging) physician questionnaire: The purpose of the survey is to address secondary hypothesis 7.

Patient interview: readmission assessment. The purpose of the third patient interview is to ascertain the primary endpoint, secondary endpoints (1A, 1B), and tertiary endpoints. Approximately 6 months (170 to 190 days) after the hospital discharge date, research personnel who are blinded to intervention assignment will perform a telephone interview with the patient. Interviewers will instruct the patient to avoid mentioning the random intervention assignment. Interviewers will ask the patient to consult their patient logbook while answering questions. Interviewers will record the admissions to the hospital, dates of admission, duration of hospital stay, number of outpatient physician visits, and number of emergency department visits that did not result in hospital admission.

Guess treatment assignment by blinded observers: The purpose of the guess is to measure the effectiveness of the blind.

Conditions for Early Withdrawal of Treatment: Patients may terminate study intervention at any time and return to the standard care if they withdraw their consent. If a patient withdraws from the study for any reason, then research personnel will conduct an end-of-study visit.

Sample size determination: The primary analysis is the difference in proportion of patients in the two study groups who achieve the primary efficacy endpoint of readmission within 6 months of discharge. The estimated event rate in the standard therapy group is 37%, which is the control group event rate from a systematic review of randomized controlled trials of discharge interventions. The minimum clinically relevant difference, 13%, corresponds to a standardized increment of 28.2% and is the empirical boundary for quantitative significance.

The required sample size for the primary analysis is 275 patients in the group assigned to discharge application of health information technology and 275 patients in the group assigned to control (usual care) therapy. In a previous study of discharge planning, the investigators enrolled 28% (363/1296) of potentially eligible patients. In the same study, 72% (262/363) of enrolled patients completed the 6-month assessment. Our hospitalist service discharges 297 patients per month. We estimate we will screen 5456 patients within 18.37 months. We estimate 50% of screened patients will be potentially eligible according to the Pra criteria. Among potentially eligible patients, we estimate 28% will consent to study enrollment. Therefore, the number of enrolled patients will be 5456 x 50% x 28% = 764. We estimate 72% (550/764) of enrolled patients will continue in the study until the 6-month assessment.

After 3 months of patient enrollment, we found the rate of enrollment was too low to achieve the required sample size. In 2005, we requested and received approval from Agency Healthcare Research Quality and Institutional Review Board to lower patient inclusion criterion, probability or repeat admission (PRA), from 0.50 to 0.40.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 631
• Est. completion date: August 2007
• Est. primary completion date: August 2007
• Accepts healthy volunteers: No
• Gender: Both
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Inpatients at OSF Saint Francis Medical Center

• Discharged by the hospitalist service or other inpatient services

• High risk for poor post-discharge outcomes defined as probability of readmission (PRA) 0.4 or above

Exclusion Criteria:

• Less than 18 years old

• Unwilling or unable to provide written consent

• Life expectancy less than 6 months

• Will receive outpatient care from a primary care physician who is the same as the discharging physician

• Do not speak English or Spanish

• Not alert and oriented when admitted

• Do not have telephone for post-discharge contact

• Do not reside in Central Illinois

• Will be discharged to a nursing home

• Previously enrolled as subjects in the trial

Study Design

Allocation: Randomized, Endpoint Classification: Safety/Efficacy Study, Intervention Model: Parallel Assignment, Masking: Single Blind (Outcomes Assessor), Primary Purpose: Health Services Research

Related Conditions & MeSH terms

• Information Dissemination
• Interprofessional Relations

Intervention

Device:
• Discharge communication software
Computerized physician order entry software used by discharging physician

Other:
• Usual care discharge process
Handwritten

Locations

Country	Name	City	State
United States	OSF Saint Francis Medical Center	Peoria	Illinois

Sponsors (2)

Lead Sponsor	Collaborator
Agency for Healthcare Research and Quality (AHRQ)	University of Illinois at Chicago

Country where clinical trial is conducted

United States, 

References & Publications (54)

Andersen HE, Schultz-Larsen K, Kreiner S, Forchhammer BH, Eriksen K, Brown A. Can readmission after stroke be prevented? Results of a randomized clinical study: a postdischarge follow-up service for stroke survivors. Stroke. 2000 May;31(5):1038-45. — View Citation

Anderson GF, Steinberg EP. Hospital readmissions in the Medicare population. N Engl J Med. 1984 Nov 22;311(21):1349-53. — View Citation

Beers MH, Sliwkowski J, Brooks J. Compliance with medication orders among the elderly after hospital discharge. Hosp Formul. 1992 Jul;27(7):720-4. — View Citation

Brook RH, Appel FA, Avery C, Orman M, Stevenson RL. Effectiveness of inpatient follow-up care. N Engl J Med. 1971 Dec 30;285(27):1509-14. — View Citation

Burnand B, Kernan WN, Feinstein AR. Indexes and boundaries for "quantitative significance" in statistical decisions. J Clin Epidemiol. 1990;43(12):1273-84. — View Citation

Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83. — View Citation

Corrigan JM, Martin JB. Identification of factors associated with hospital readmission and development of a predictive model. Health Serv Res. 1992 Apr;27(1):81-101. — View Citation

Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992 Jun;45(6):613-9. — View Citation

Donner A, Birkett N, Buck C. Randomization by cluster. Sample size requirements and analysis. Am J Epidemiol. 1981 Dec;114(6):906-14. — View Citation

Donner A, Donald A. Analysis of data arising from a stratified design with the cluster as unit of randomization. Stat Med. 1987 Jan-Feb;6(1):43-52. — View Citation

Donner A, Klar N. Pitfalls of and controversies in cluster randomization trials. Am J Public Health. 2004 Mar;94(3):416-22. — View Citation

Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med. 2003 Feb 4;138(3):161-7. — View Citation

Foster DS, Paterson C, Fairfield G. Evaluation of immediate discharge documents--room for improvement? Scott Med J. 2002 Aug;47(4):77-9. — View Citation

Graumlich JF, Grimmer-Somers K, Aldag JC. Discharge planning scale: community physicians' perspective. J Hosp Med. 2008 Nov-Dec;3(6):455-64. doi: 10.1002/jhm.371. — View Citation

Graumlich JF, Novotny NL, Aldag JC. Brief scale measuring patient preparedness for hospital discharge to home: Psychometric properties. J Hosp Med. 2008 Nov-Dec;3(6):446-54. doi: 10.1002/jhm.316. — View Citation

Graumlich JF, Novotny NL, Nace GS, Aldag JC. Patient and physician perceptions after software-assisted hospital discharge: cluster randomized trial. J Hosp Med. 2009 Jul;4(6):356-63. doi: 10.1002/jhm.565. — View Citation

Graumlich JF, Novotny NL, Stephen Nace G, Kaushal H, Ibrahim-Ali W, Theivanayagam S, William Scheibel L, Aldag JC. Patient readmissions, emergency visits, and adverse events after software-assisted discharge from hospital: cluster randomized trial. J Hosp — View Citation

Grimmer K, Moss J. The development, validity and application of a new instrument to assess the quality of discharge planning activities from the community perspective. Int J Qual Health Care. 2001 Apr;13(2):109-16. — View Citation

Hauck WW, Anderson S, Marcus SM. Should we adjust for covariates in nonlinear regression analyses of randomized trials? Control Clin Trials. 1998 Jun;19(3):249-56. Review. — View Citation

Hedeker D, Gibbons RD. MIXOR: a computer program for mixed-effects ordinal regression analysis. Comput Methods Programs Biomed. 1996 Mar;49(2):157-76. — View Citation

Hedeker D, Gibbons RD. MIXREG: a computer program for mixed-effects regression analysis with autocorrelated errors. Comput Methods Programs Biomed. 1996 May;49(3):229-52. — View Citation

Hedeker D, Siddiqui O, Hu FB. Random-effects regression analysis of correlated grouped-time survival data. Stat Methods Med Res. 2000 Apr;9(2):161-79. — View Citation

Heitjan DF. Annotation: what can be done about missing data? Approaches to imputation. Am J Public Health. 1997 Apr;87(4):548-50. — View Citation

Horne R, Hankins M, Jenkins R. The Satisfaction with Information about Medicines Scale (SIMS): a new measurement tool for audit and research. Qual Health Care. 2001 Sep;10(3):135-40. — View Citation

Hsieh FY. Sample size formulae for intervention studies with the cluster as unit of randomization. Stat Med. 1988 Nov;7(11):1195-201. Erratum in: Stat Med 1997 Jun 15;16(11):1300. — View Citation

Hunsberger S, Murray D, Davis CE, Fabsitz RR. Imputation strategies for missing data in a school-based multi-centre study: the Pathways study. Stat Med. 2001 Jan 30;20(2):305-16. — View Citation

Johnson A, Sandford J, Tyndall J. Written and verbal information versus verbal information only for patients being discharged from acute hospital settings to home. Cochrane Database Syst Rev. 2003;(4):CD003716. Review. — View Citation

Kerry SM, Bland JM. Unequal cluster sizes for trials in English and Welsh general practice: implications for sample size calculations. Stat Med. 2001 Feb 15;20(3):377-90. — View Citation

Kiefe CI, Heudebert G, Box JB, Farmer RM, Michael M, Clancy CM. Compliance with post-hospitalization follow-up visits: rationing by inconvenience? Ethn Dis. 1999 Autumn;9(3):387-95. — View Citation

Manos PJ, Wu R. The ten point clock test: a quick screen and grading method for cognitive impairment in medical and surgical patients. Int J Psychiatry Med. 1994;24(3):229-44. — View Citation

Marcantonio ER, McKean S, Goldfinger M, Kleefield S, Yurkofsky M, Brennan TA. Factors associated with unplanned hospital readmission among patients 65 years of age and older in a Medicare managed care plan. Am J Med. 1999 Jul;107(1):13-7. — View Citation

McInnes E, Mira M, Atkin N, Kennedy P, Cullen J. Can GP input into discharge planning result in better outcomes for the frail aged: results from a randomized controlled trial. Fam Pract. 1999 Jun;16(3):289-93. — View Citation

Murray DM, Varnell SP, Blitstein JL. Design and analysis of group-randomized trials: a review of recent methodological developments. Am J Public Health. 2004 Mar;94(3):423-32. Review. — View Citation

Nace GS, Graumlich JF, Aldag JC. Software design to facilitate information transfer at hospital discharge. Inform Prim Care. 2006;14(2):109-19. — View Citation

Naranjo CA, Busto U, Sellers EM, Sandor P, Ruiz I, Roberts EA, Janecek E, Domecq C, Greenblatt DJ. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther. 1981 Aug;30(2):239-45. — View Citation

Naylor MD, Brooten D, Campbell R, Jacobsen BS, Mezey MD, Pauly MV, Schwartz JS. Comprehensive discharge planning and home follow-up of hospitalized elders: a randomized clinical trial. JAMA. 1999 Feb 17;281(7):613-20. — View Citation

Nazareth I, Burton A, Shulman S, Smith P, Haines A, Timberal H. A pharmacy discharge plan for hospitalized elderly patients--a randomized controlled trial. Age Ageing. 2001 Jan;30(1):33-40. — View Citation

Novotny NL, Anderson MA. Prediction of early readmission in medical inpatients using the Probability of Repeated Admission instrument. Nurs Res. 2008 Nov-Dec;57(6):406-15. doi: 10.1097/NNR.0b013e31818c3e06. — View Citation

O'Connell EM, Teich JM, Pedraza LA, Thomas D. A comprehensive inpatient discharge system. Proc AMIA Annu Fall Symp. 1996:699-703. — View Citation

Pacala JT, Boult C, Boult L. Predictive validity of a questionnaire that identifies older persons at risk for hospital admission. J Am Geriatr Soc. 1995 Apr;43(4):374-7. — View Citation

Pacala JT, Boult C, Reed RL, Aliberti E. Predictive validity of the Pra instrument among older recipients of managed care. J Am Geriatr Soc. 1997 May;45(5):614-7. — View Citation

Paquette-Lamontagne N, McLean WM, Besse L, Cusson J. Evaluation of a new integrated discharge prescription form. Ann Pharmacother. 2001 Jul-Aug;35(7-8):953-8. — View Citation

Phillips CO, Wright SM, Kern DE, Singa RM, Shepperd S, Rubin HR. Comprehensive discharge planning with postdischarge support for older patients with congestive heart failure: a meta-analysis. JAMA. 2004 Mar 17;291(11):1358-67. Erratum in: JAMA. 2004 Sep 1;292(9):1022. — View Citation

Reuben DB, Keeler E, Seeman TE, Sewall A, Hirsch SH, Guralnik JM. Development of a method to identify seniors at high risk for high hospital utilization. Med Care. 2002 Sep;40(9):782-93. — View Citation

Romano PS, Chan BK. Risk-adjusting acute myocardial infarction mortality: are APR-DRGs the right tool? Health Serv Res. 2000 Mar;34(7):1469-89. — View Citation

Sands DZ, Safran C. Closing the loop of patient care--a clinical trial of a computerized discharge medication program. Proc Annu Symp Comput Appl Med Care. 1994:841-5. — View Citation

Sexton J, Ho YJ, Green CF, Caldwell NA. Ensuring seamless care at hospital discharge: a national survey. J Clin Pharm Ther. 2000 Oct;25(5):385-93. — View Citation

Shelton P, Sager MA, Schraeder C. The community assessment risk screen (CARS): identifying elderly persons at risk for hospitalization or emergency department visit. Am J Manag Care. 2000 Aug;6(8):925-33. — View Citation

Shepperd S, Parkes J, McClaren J, Phillips C. Discharge planning from hospital to home. Cochrane Database Syst Rev. 2004;(1):CD000313. Review. Update in: Cochrane Database Syst Rev. 2010;(1):CD000313. — View Citation

Smith DM, Giobbie-Hurder A, Weinberger M, Oddone EZ, Henderson WG, Asch DA, Ashton CM, Feussner JR, Ginier P, Huey JM, Hynes DM, Loo L, Mengel CE. Predicting non-elective hospital readmissions: a multi-site study. Department of Veterans Affairs Cooperative Study Group on Primary Care and Readmissions. J Clin Epidemiol. 2000 Nov;53(11):1113-8. — View Citation

van Walraven C, Laupacis A, Seth R, Wells G. Dictated versus database-generated discharge summaries: a randomized clinical trial. CMAJ. 1999 Feb 9;160(3):319-26. — View Citation

van Walraven C, Seth R, Austin PC, Laupacis A. Effect of discharge summary availability during post-discharge visits on hospital readmission. J Gen Intern Med. 2002 Mar;17(3):186-92. — View Citation

van Walraven C, Seth R, Laupacis A. Dissemination of discharge summaries. Not reaching follow-up physicians. Can Fam Physician. 2002 Apr;48:737-42. — View Citation

Weinberger M, Oddone EZ, Henderson WG. Does increased access to primary care reduce hospital readmissions? Veterans Affairs Cooperative Study Group on Primary Care and Hospital Readmission. N Engl J Med. 1996 May 30;334(22):1441-7. — View Citation

* Note: There are 54 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Hospital Readmission, at Least One	Number of participants with at least one readmission within 6 months after discharge from index hospital visit	within 6 months after discharge	Yes
Secondary	Patients' Perception of Discharge Process, Effectiveness, Satisfaction, Preparedness		1 week after discharge	No
Secondary	Patients' Perception of Discharge Process, Satisfaction		1 week after discharge	No
Secondary	Pharmacist Needed to Clarify the Discharge Prescription		1 day after discharge	Yes
Secondary	Pharmacist's Satisfaction With Discharge Prescription		1 day after discharge	No
Secondary	At Least One Adverse Event Within One Month After Discharge	Number of participants with at least one adverse event within one month after discharge	1 month after discharge	Yes
Secondary	Patient's Satisfaction With Drug Information		1 week after discharge	No
Secondary	Primary Care Physician's Perception, Effectiveness		10 days after discharge	No
Secondary	Primary Care Physician's Perception, Satisfaction		10 days after discharge	No
Secondary	Discharge Physician Satisfaction With Discharge Process		6 months after using discharge process	No
Secondary	Number of Outpatient Visits		within 6 months after discharge	No
Secondary	Number of Emergency Department Visits	Number of participants with at least one emergency department visit within six months after discharge	within 6 months after discharge	Yes
Secondary	Physician Time Spent to Complete the Discharge Application		averaged over 2 years of patient enrollment	No