Study On The Inpatients Behavior Of Hospitaled In Multi-levels Based On Hospital Healthcare Value In Rural China

[Purpose]Study on the factors which have influence on the choice of different hospitals and thehealthcare value based on the multi-levels inpatient, and analysis its features andinfluencing factors of this repeat and order behavior. Calculating and comparing thehealthcare value of different hospitalization based on the healthcare results and healthcareexpenses, and discuss the improvement of the inpatients’ value and the reduction of theinpatients’ expenses.[Methods](1) Literature review about the healthcare value, readmission, health quality from thedata base such as Pub Med, Google Scholar, CNKI, Wan fang, etc.(2) Medical evaluation. Collection the medical record of NRCMS inpatients withrespiratory system diseases from2007to2009, analysis the status quo and characteristics ofmulti-levels inpatients by the data from medical evaluation and information extractioncombining with the information from NRCMS Health insurance database.(3) Study on the influencing factors on the hospitalization choice and the multi-levelshospitalization by the Binary Logistic Regression, and analyze the risk factors onreadmission in one cycle time by the COX Regression.(4) Comprehensive evaluation method of medicine. Calculate the inpatients’ value byComprehensive Scoring Method and rank the different hospitalization by RSR-TOPSIS Me[Results](1) For the respiratory system disease patients,91%inpatient is in township hospitaland9%inpatient is in county hospital; during the readmission inpatients in one cycle time,83.5%inpatient have first hospitalization in township hospital and16.5%inpatient incounty hospital. Respiratory system disease in patients with chronic disease or non-chronicdisease have no significant different in township level and county level, and the type ofdisease have no effect on two levels. The multi units diagnosis coincidence rate is only12%to13%, which has significant different with one units rate. The LOS of respiratory system disease patients in Chongqing, Qianjiang is7.88, and27.52%of them is shorter than3. Thetransitional time in readmission inpatients is12.2, and pneumonia, chronic bronchitis andchronic bronchitis are the main disease. For the respiratory system disease patients, thehospitalization expenses have on significant difference in township level and county level.The hospitalization total expenses, the medicine expenses and the average bed fee ofinpatients have no significant difference in one agency hospitalization, same agencyreadmission, and multi-level readmission.Age group, the first time hospitalization in a year, distance group, long of stay andhospitalization type are the main influencing factors in the choice of hospital levels.(2) For the respiratory system disease patients who have first hospitalization intownship levels and readmission in county levels, the typing of record cases, lack of service,in-out diagnosis coincidence rate, hospital leave decision maker and the change of healthresults are the influencing factors to readmission after township hospitalization in a cycletime.For the readmission inpatients, transitional care influenced on the cycle timereadmission, and the doctor advice contained with “transfer” and “life guide” will affectpatient’s cycle-time readmission.For the respiratory system disease patients which have first hospitalization in townshiplevels and readmission in county levels, the transitional time is4.43,45%of them transferfrom township levels to county levels in that very day and accumulation to71.25%in3days. Among the referral inpatients, only30.55%transferred with doctor advice,42.86%leave the hospital by their own decision. Foe the readmission patients in the county hospital,27.16%of them keep still in their disease condition and48.15%aggravated.(3) Based on the ME Porter’s six level value evaluation framework, choose the changeof the disease condition, treat results, LOS, improper medical behavior, time to recoveryand multi-levels hospitalization to measure inpatients’ health outcomes. According to thesample, the score of one agency inpatients’ health outcome is34.18, value41.14, andmulti-levels (average) inpatients’ health outcome is24.18, value is33.03. The twohospitalization types have significant difference in health outcome and value.Hospital expenses, multi-level hospitalization, lack of service, drug combinations ofantibiotics, in-out diagnosis coincidence rate, change of health result, doctor advice of drug use and definite diagnosis in three days are the main factors influence the inpatients’ value.(4) According to the respiratory system disease patients, changing the hospitalizationways, such as make the inpatients have their first hospitalization in county level down tothe township level, by two factors (distance and age) adjusted separately, the inpatients’value improve18344.69and23553.69, which can improve every inpatient49.998score.What’s more, the hospital expenses declined by￥17612.87and￥17486.17, which can save￥20.91hospitalization expenses per patient with the respiratory system disease in Qianjiangdistrict.[Conclusions](1) According to patients’ free choice of hospitalization, the proportion in townshiphospital is much high than that in county level, combining with the high hospitalizationexpenses, which will increase the family burden.(2) As readmission inpatient will give more information to physicians, multi-levelinpatients have more positive examine results with fewer improper medical behaviors thanthat in one agency inpatients. The disease development in transitional time affects patients’multi-level readmission, and transitional care can reduce avoidable readmission andimprove patients’ value.(3) For the sample inpatients, the outcome score and value score of single agencyinpatients is better than that of multi-levels inpatients. The rank of different hospitalizationvalue shows as “multi-level township readmission equal to single township hospitalization,better than multi-level township first hospitalization, better than multi-level hospitalizationaverage, better than single county hospitalization, better than multi-levels countyreadmission, better than multi-levels county first hospitalization, better than multi-levelhospitalization accumulation. Changing the hospitalization ways, such as make the inpatients thathave their first hospitalization in county level down to the township level, can reduce hospitalizationexpenses and improve inpatients’ value.[Innovation and shortage]The study expends the field of readmission from same hospital to different levelhospital in30days, and defines the behavior of multi-levels inpatients. We compared thedifferent hospitalization behaviors between single agency and multi-levels, especially theunique characteristic in transitional time which will provide a good ways to improve the efficiency of health care and reduced the medical expenses. What’s more, we introduced theProfessor ME Porter’s value theory to inpatients’ study, and rank the order of differenthospitalization ways based on the value score according to the TOPSIS comprehensiveevaluation method, which will promote the hospital to improve their health quality andefficiency continuously.The shortage: First, as we only choose Qianjiang district in Chong Qing as ourresearch sites and the multi-levels inpatients are the minority member, so we just got asmall sample which may be affected by the missing answer or the variation. Second, themedical expenses of the sample may have some deviation from the population. The averagemedical expenses of the sample in county level of the single agency are higher than that ofpopulation, which may lower the inpatient value of county level inpatients. Third, theindicator chosen to judge the health outcome and inpatient value is lack the golden standard,so its scientificalness and rationality need further study. So does the way to calculate thetotal value of inpatients. Both of them have shortage in applying to different conditions andto different area. Last but not least, restricted by the authors’ academic level and knowledge,there is far from enough to explain the result and draw the conclusions, especiallycombined the data with the policy conditions, economic conditions and the whole healthcare system. We still have much work to do on it.