Fluent Essays

QM 6640 Critical Thinking Assessment Read the case from the QM 6640 Medical Debt PDF document, and review the data from the QM 6640 Assessment Patient Data Excel file. Then, write a concise report answering questions 1-6 from the end of the case, using the data to assist in justifying your answers. Using past due amount as the dependent variable and all other variables as predictors (independent variables), run appropriate statistical analyses in Excel to mine the data. Insert tables and graphs from Excel in your report as appropriate. Label sections of your report to correspond to the questions. The completed report is the deliverable for this assignment. Patient Data Income Past Due Amount Insurance Years Since Last Visit Year Born Gender Hospitalizations Ethnicity Marital Status 9268 0 Medicaid 0 1955 Female 1 Caucasian Married 12099 0 Medicare 1 1934 Male 8 Caucasian Married 96397 0 Private 0 1973 Female 2 Caucasian Married 63027 327 Private 1 1958 Female 6 Hispanic Divorced 273245 0 Private 0 1963 Female 3 Caucasian Married 58756 0 Private 0 1975 Male 2 Caucasian Married 139832 0 Private 3 1992 Male 1 Caucasian Married 19930 0 Medicare 0 1945 Female 6 Hispanic Married 37615 149 Medicaid 2 1969 Female 4 Asian Widowed 7686 3616 Private 1 1989 Male 2 Caucasian Married 24125 197 Private 0 1947 Male 0 Caucasian Married 28650 58 Medicaid 2 1968 Male 1 Asian Divorced 15340 0 Private 1 1956 Female 5 Caucasian Married 20274 4506 Private 2 1952 Male 5 Hispanic Married 20249 0 Medicare 1 1938 Male 7 African American Married 33959 171 Private 3 1978 Male 3 Hispanic Divorced 177266 267 Private 0 1989 Female 2 Asian Divorced 25020 266 Medicaid 2 1957 Female 1 Caucasian Divorced 163109 168 Private 0 1979 Male 3 Caucasian Divorced 16650 1544 Medicaid 0 1980 Female 1 Caucasian Divorced 25664 155 Medicaid 1 1981 Male 2 Caucasian Divorced 14896 428 Medicaid 2 1970 Female 1 African American Married 76008 0 Private 0 1970 Female 2 Caucasian Married 174119 307 Private 0 1962 Male 4 Caucasian Married 29516 324 Private 0 1981 Male 2 Caucasian Separated 41614 0 Private 1 1967 Male 0 Caucasian Divorced 7016 1277 Medicaid 0 1989 Female 1 African American Married 29586 0 Medicaid 2 1985 Male 2 Caucasian Married 21671 346 Medicaid 0 1959 Female 5 Caucasian Married 170421 0 Private 1 1987 Female 2 Caucasian Married 114948 0 Medicare 0 1940 Female 2 Caucasian Married 9267 137 Private 0 1965 Male 0 Caucasian Divorced 144920 0 Private 3 1985 Male 2 Asian Divorced 68926 0 Private 0 1983 Male 2 Asian Married 124873 0 Private 1 1989 Female 1 Caucasian Separated 129358 0 Medicare 0 1942 Female 9 Caucasian Married 186134 145 Medicare 0 1941 Male 2 Caucasian Married 8926 0 Private 0 1965 Male 5 Caucasian Divorced 8441 1174 None 2 1991 Female 1 Caucasian Divorced 20214 0 Private + Medicare 0 1933 Female 4 Hispanic Divorced 43988 410 Private 0 1971 Female 2 Caucasian Single 172494 0 Private 0 1985 Male 1 Asian Divorced 289543 0 Private 0 1956 Female 0 Caucasian Divorced 51294 360 Private 1 1967 Male 1 Caucasian Married 29621 960 Medicaid 1 1987 Male 2 Caucasian Divorced 192763 0 Private 0 1948 Male 6 Hispanic Married 77959 173 Private 0 1986 Female 3 Asian Married 8859 368 Private 3 1980 Female 0 Caucasian Separated 256103 208 Private 0 1984 Male 1 Caucasian Widowed 48289 475 Private 0 1965 Male 5 Asian Married 111048 0 Medicare 2 1939 Male 1 Caucasian Married 19274 63 None 2 1947 Female 1 Other Married 25629 0 Private + Medicare 2 1943 Female 6 Hispanic Divorced 12940 0 Private + Medicare 0 1946 Male 1 Caucasian Married 102797 500 Medicare 0 1934 Male 9 Caucasian Divorced 9153 0 Private 0 1947 Male 4 African American Married 26884 0 Medicare 1 1942 Male 6 Caucasian Married 58016 0 Private 1 1988 Female 2 Caucasian Married 7519 429 Private 3 1976 Female 2 Other Divorced 25948 484 Medicare 1 1939 Male 8 Caucasian Married 147116 59 Private 0 1979 Female 1 African American Married 17582 69 Private 1 1947 Female 4 Caucasian Married 29101 364 Medicare 0 1935 Male 11 Hispanic Married 25892 0 Medicaid 0 1968 Male 1 Hispanic Divorced 64146 0 Private 0 1979 Male 0 African American Married 69688 0 Private + Medicare 3 1934 Male 8 Caucasian Divorced 12739 1452 Medicaid 0 1983 Male 1 Asian Married 221574 0 Private 0 1963 Male 5 Hispanic Widowed 89151 0 Private 2 1963 Female 2 Caucasian Divorced 21651 332 Medicaid 1 1969 Male 3 Hispanic Married 49988 1802 Private 3 1969 Male 4 Caucasian Married 58244 360 Private 2 1978 Female 3 Hispanic Separated 6004 0 Private 1 1955 Male 3 Caucasian Divorced 9402 278 Medicaid 0 1975 Male 4 African American Married 100088 0 None 0 1955 Female 6 Caucasian Married 115420 0 None 0 1963 Female 0 Hispanic Married 15321 0 Medicare 0 1939 Female 10 Caucasian Married 218481 291 Private 4 1975 Male 3 Caucasian Married 221217 0 Medicare 0 1938 Female 11 Asian Married 215248 0 Private 0 1988 Female 2 Caucasian Married 135772 0 Private 0 1992 Male 0 Caucasian Divorced 81499 0 Private 3 1950 Male 0 Caucasian Divorced 138647 0 Private 0 1964 Male 1 African American Divorced 12476 4239 Private 0 1953 Male 3 Asian Married 78631 168 Private 4 1988 Female 1 Caucasian Married 23234 0 Private + Medicare 0 1933 Male 12 Hispanic Single 108879 0 Private 0 1982 Female 2 Asian Divorced 19262 0 Private 3 1980 Female 1 Asian Single 21747 0 Private 0 1986 Male 1 Caucasian Married 200536 0 Medicare 1 1938 Male 4 Caucasian Married 21973 154 Medicaid 0 1977 Male 3 Caucasian Married 9900 0 Private 0 1960 Female 2 Caucasian Divorced 9970 2091 Private 0 1982 Male 2 Other Divorced 8104 0 Private + Medicare 1 1937 Female 10 Hispanic Married 159693 192 Private 0 1982 Female 1 Caucasian Married 19673 0 Medicaid 2 1966 Male 1 Asian Married 21564 0 Medicaid 0 1989 Male 0 Asian Single 68761 0 Private 0 1962 Female 1 Caucasian Divorced 34456 371 Medicare 2 1939 Male 6 Asian Divorced 132128 0 Private 3 1973 Female 0 Caucasian Married 22713 0 Private 0 1977 Male 3 Asian Married 149093 0 Medicare 3 1942 Male 7 Caucasian Divorced 88150 0 Private 0 1970 Female 3 Caucasian Married 51086 183 Private 3 1974 Male 3 Caucasian Separated 16601 0 Medicaid 3 1984 Female 0 Caucasian Single 77232 0 Private + Medicare 0 1932 Male 10 Caucasian Divorced 211570 395 Private 2 1990 Male 2 Caucasian Married 19615 0 Medicare 1 1942 Female 6 African American Married 24786 0 Medicaid 1 1992 Male 1 Caucasian Married 181985 162 None 3 1988 Male 1 Asian Married 9553 1344 Medicaid 1 1973 Female 0 Caucasian Married 22014 1462 Medicaid 0 1984 Female 2 African American Married 70481 0 Private 0 1971 Male 0 Caucasian Divorced 54352 0 Private 3 1992 Male 1 African American Divorced 27180 3800 Private 3 1990 Female 2 Caucasian Separated 168600 174 None 0 1953 Male 5 Caucasian Divorced 248433 0 Private 0 1957 Male 5 Caucasian Separated 44458 155 Private 2 1962 Female 4 Caucasian Divorced 7819 0 Private 1 1987 Female 2 Asian Divorced 145660 71 Private 1 1988 Female 2 Caucasian Divorced 118922 0 Private 0 1965 Male 4 Caucasian Married 179674 383 Private 2 1956 Female 4 Asian Married 44338 478 Medicare 0 1936 Male 2 Caucasian Married 9998 0 Private 4 1977 Female 0 Caucasian Divorced 7662 620 Private 0 1958 Male 1 Hispanic Divorced 159752 0 Private + Medicare 0 1933 Male 14 Caucasian Married 29265 0 Private 3 1979 Female 3 Other Divorced 59861 0 Private 3 1973 Male 4 Caucasian Widowed 59560 0 Private 0 1966 Female 3 Caucasian Divorced 6932 3924 Medicaid 0 1950 Male 2 Caucasian Married 66328 359 Private + Medicare 1 1937 Male 10 Asian Married 7482 0 Medicaid 0 1955 Male 5 African American Divorced 147925 0 Private 0 1973 Female 2 Caucasian Single 73072 250 Private 0 1950 Female 6 Caucasian Married 59954 0 Private 0 1951 Male 4 Other Married 15800 308 Medicaid 1 1979 Male 2 Other Married 29886 0 Private 0 1950 Female 1 Caucasian Married 189592 0 Private + Medicare 0 1936 Female 7 Hispanic Separated 21314 1631 Private 0 1955 Female 3 Caucasian Divorced 140312 0 Private 0 1971 Female 4 African American Divorced 12298 420 Medicaid 2 1988 Male 1 African American Married 9118 0 Medicare 1 1946 Female 3 Caucasian Single 257836 0 None 0 1961 Female 5 Hispanic Divorced 10400 2120 Private + Medicare 0 1946 Male 2 Asian Divorced 146238 0 Medicare 0 1932 Female 13 Other Married 192380 89 Private 3 1974 Female 4 Hispanic Married 82161 0 Medicare 1 1943 Male 1 Hispanic Married 33153 0 Medicaid 0 1965 Female 2 Hispanic Married 25202 4715 Private + Medicare 0 1933 Male 8 Caucasian Married 111843 0 Private 0 1963 Male 1 African American Married 8986 0 Private 1 1983 Female 1 Caucasian Married 6683 483 Medicaid 1 1975 Female 1 Hispanic Single 11212 2724 Private 1 1990 Male 1 Hispanic Separated 29064 871 Private 2 1987 Male 2 Hispanic Separated 10600 222 Private 3 1950 Male 3 Caucasian Married 67996 0 Private 0 1957 Male 3 Hispanic Married 163038 3184 Private 0 1966 Male 2 Caucasian Married 74924 0 Private 0 1967 Male 2 Caucasian Divorced 97760 461 Private 0 1962 Female 4 Asian Widowed 173816 0 Private 0 1964 Male 1 Caucasian Married 93423 0 Private 0 1951 Female 5 Hispanic Married 8905 1666 Medicaid 0 1977 Female 1 Caucasian Married 14074 0 Medicaid 0 1980 Male 2 Caucasian Divorced 121033 0 Private 4 1983 Female 1 Caucasian Single 51791 172 Private 0 1949 Female 1 Caucasian Married 150620 0 Private 2 1969 Female 0 Asian Divorced 24601 1570 Medicare 2 1934 Male 6 Caucasian Single 21484 0 Medicaid 0 1988 Female 1 Caucasian Divorced 34423 0 Private 0 1985 Male 1 Caucasian Widowed 214567 0 Medicare 1 1944 Female 3 Hispanic Married 74299 324 Private 0 1972 Male 1 Caucasian Divorced 194615 0 Medicare 2 1935 Male 9 Caucasian Widowed 197045 0 Private 0 1950 Female 6 Asian Single 16581 0 Medicare 0 1939 Male 9 Caucasian Widowed 92608 14 Medicare 2 1934 Female 10 Caucasian Married 18046 0 Private 0 1984 Male 0 Hispanic Divorced 48692 0 Private 0 1971 Male 3 Caucasian Widowed 187231 188 Private 3 1952 Male 3 Caucasian Married 44676 0 Private 0 1970 Male 1 Caucasian Divorced 161957 0 Private 0 1979 Male 1 Hispanic Married 63142 0 Private 3 1961 Male 5 African American Divorced 89659 0 Medicare 0 1942 Male 7 Caucasian Divorced 7191 143 Private 1 1991 Male 0 Caucasian Separated 14807 758 Medicaid 1 1979 Female 3 Caucasian Divorced 25609 86 Private 0 1988 Male 1 Hispanic Married 27501 124 Private 1 1979 Male 1 Other Married 118179 0 Private 0 1952 Female 6 Caucasian Widowed 210310 0 Private 4 1978 Female 0 Caucasian Married 23727 0 Private 0 1968 Male 0 Hispanic Married 111021 0 Private 2 1952 Male 5 African American Married 8980 0 Medicare 2 1942 Female 6 Caucasian Widowed 257891 0 Private 0 1964 Female 4 Caucasian Separated 24459 368 Medicare 0 1938 Female 8 Asian Separated 50744 0 Medicare 3 1936 Male 6 Caucasian Married 11714 461 Private 1 1975 Female 3 Caucasian Married 63043 316 Private 0 1962 Female 1 Caucasian Widowed 93868 92 Private 0 1950 Male 3 African American Divorced 36216 0 Medicaid 1 1950 Female 0 Caucasian Divorced 323341 183 Private 0 1952 Female 5 Other Married 277673 171 Private 0 1968 Female 3 Caucasian Married 136134 0 Private 1 1992 Female 0 Hispanic Married 12849 2127 Private + Medicare 0 1944 Male 1 Caucasian Divorced 244100 0 Private 0 1978 Female 3 Caucasian Married 58770 0 Private 0 1956 Female 0 Caucasian Married 86428 0 Private + Medicare 0 1936 Male 2 Caucasian Married 43479 0 Private 0 1986 Male 2 Caucasian Married 92629 0 Private 0 1960 Female 4 Asian Separated 14789 156 Medicaid 2 1947 Female 7 Caucasian Divorced 163293 0 Private 0 1989 Female 1 Asian Divorced 12873 3331 Private 0 1959 Female 5 Hispanic Married 168778 0 Private 1 1986 Male 1 Caucasian Separated 83624 0 None 0 1969 Female 4 Hispanic Married 56647 0 Private 0 1962 Male 1 Caucasian Separated 8636 0 Private 0 1985 Female 1 Caucasian Married 259498 0 Private 1 1954 Male 4 African American Divorced 15283 2343 Private 3 1947 Female 6 Caucasian Divorced 12172 0 Private 0 1954 Female 4 African American Divorced 200485 173 Private 2 1949 Male 2 Caucasian Married 135507 0 Private 0 1980 Male 1 Caucasian Separated 63675 0 Private 3 1972 Female 4 Caucasian Married 9823 3122 Private 2 1970 Female 2 Caucasian Divorced 237307 0 Medicare 3 1933 Female 11 Caucasian Married 58852 0 Private 0 1977 Female 2 Caucasian Separated 10811 0 Medicare 0 1945 Female 3 Caucasian Separated 6269 426 Private + Medicare 0 1946 Female 3 Caucasian Married 20180 0 Medicaid 0 1966 Female 4 Caucasian Widowed 28582 0 Private + Medicare 0 1942 Female 7 Asian Married 8575 89 Private 1 1965 Male 2 Caucasian Single 10016 3070 Medicaid 0 1966 Male 0 Caucasian Married 9844 0 Medicare 2 1942 Male 3 Caucasian Divorced 86781 0 Private 1 1947 Male 1 Caucasian Divorced 62086 0 Medicare 0 1945 Male 7 Caucasian Married 98214 0 Private 0 1979 Male 3 Hispanic Separated 104358 0 Private 2 1982 Female 1 Caucasian Married 182863 0 Private 0 1990 Female 2 Caucasian Divorced 14795 290 Medicare 0 1942 Male 5 Caucasian Married 13439 37 Private + Medicare 0 1944 Male 5 Caucasian Married 27415 0 Private 3 1972 Female 3 Other Divorced 249809 0 Private 0 1964 Male 5 Hispanic Divorced 119104 0 None 0 1948 Female 5 African American Married 31529 176 Medicaid 0 1954 Female 6 Caucasian Widowed 137964 0 None 0 1962 Female 5 Other Married 189343 0 Private 0 1953 Female 4 Caucasian Married 126007 328 Private 0 1969 Male 2 Caucasian Widowed 85611 0 Private 0 1976 Female 4 Caucasian Married 8047 134 Medicaid 2 1969 Male 2 Caucasian Married 10925 147 Medicaid 0 1969 Male 1 Other Divorced 143201 354 Private 0 1950 Male 4 Caucasian Divorced 16864 0 Private 3 1986 Female 0 African American Married 12794 5398 Medicaid 0 1974 Male 0 Hispanic Single 196877 0 Private 0 1950 Male 4 Caucasian Divorced 68431 0 Private + Medicare 0 1936 Female 10 Caucasian Single 12655 5966 Private + Medicare 2 1940 Female 2 Hispanic Married 13629 0 Private + Medicare 0 1941 Male 5 Asian Married 18434 0 Medicare 2 1938 Male 7 Caucasian Married 26685 0 Private + Medicare 0 1937 Female 6 Caucasian Single 100698 0 Private 0 1951 Male 5 Caucasian Divorced 163262 0 Private 0 1973 Male 4 Caucasian Divorced 50319 0 Private 3 1958 Male 3 Asian Divorced 132416 215 None 0 1952 Female 5 Caucasian Single 18966 0 Medicaid 0 1983 Female 3 Caucasian Separated 81001 0 Private 0 1963 Male 3 Caucasian Widowed 31774 0 Medicaid 0 1961 Female 0 African American Single 86550 421 Private 2 1977 Female 0 Caucasian Divorced 19478 88 Private 1 1972 Female 1 Caucasian Separated 27017 0 Private 3 1968 Male 2 Hispanic Married 68601 0 Private 0 1967 Female 4 Caucasian Divorced 25700 16 Medicaid 1 1985 Male 2 African American Divorced 9057 0 Private 0 1987 Female 1 Caucasian Separated 10569 1428 Medicaid 3 1981 Male 1 Caucasian Married 8423 4059 Private 0 1953 Male 4 African American Married 83971 0 Medicare 1 1942 Male 3 Asian Divorced 269157 0 Private 1 1977 Male 1 Asian Divorced 19860 0 Medicaid 0 1960 Male 5 Caucasian Widowed 48559 0 Private 0 1966 Male 2 African American Married 194512 0 Medicare 1 1937 Female 3 Caucasian Widowed 47906 308 Private 2 1985 Male 1 Hispanic Divorced 27533 0 Medicare 0 1932 Male 17 African American Married 116061 0 Private 0 1961 Female 2 Hispanic Married 43512 0 Private 3 1953 Female 6 African American Married 135844 0 Medicare 0 1946 Male 2 African American Married 6919 2316 Private 0 1953 Male 2 Asian Divorced 106850 0 Private 0 1992 Male 2 Caucasian Single 45194 2609 Private 0 1982 Male 1 Asian Widowed 7684 359 Private 1 1954 Male 5 Caucasian Widowed 180617 0 Private 3 1987 Male 1 Hispanic Married 26418 0 Medicaid 0 1950 Male 1 Caucasian Widowed 336113 400 Private 0 1984 Male 1 Caucasian Single 29742 194 Private 1 1965 Female 4 Caucasian Married 29029 0 Private 0 1989 Male 0 Caucasian Married 110198 422 Private + Medicare 0 1935 Male 2 Caucasian Married 7967 0 Medicare 1 1939 Female 11 Asian Married 118943 309 Medicare 0 1940 Male 8 Hispanic Single 58683 0 Medicare 0 1936 Female 7 Caucasian Separated 7312 1413 None 0 1957 Male 6 Asian Married 136053 198 Private 0 1982 Male 0 Caucasian Married 28792 0 Medicaid 2 1947 Male 5 Hispanic Divorced 14768 484 None 0 1966 Female 2 Hispanic Divorced 27242 1780 Private + Medicare 0 1934 Female 11 Asian Married 8476 0 Medicaid 0 1991 Female 1 Caucasian Single 25104 0 Private 0 1986 Male 1 Other Divorced 28577 321 Medicaid 3 1975 Male 2 Hispanic Divorced 222824 0 Private 3 1980 Male 2 Caucasian Married 11487 912 None 0 1954 Male 6 Caucasian Married 22316 3659 Medicaid 1 1970 Male 2 Caucasian Widowed 80894 0 None 1 1972 Female 2 Caucasian Married 20582 0 Medicaid 0 1967 Male 4 African American Single 200240 0 None 0 1954 Male 5 Caucasian Separated 89287 306 Private 0 1960 Male 1 African American Divorced 98039 0 Private 0 1980 Male 2 Caucasian Divorced 36375 0 Private + Medicare 0 1940 Male 6 Caucasian Widowed 165829 1806 Private 2 1990 Male 2 Caucasian Married 264905 0 Private 0 1953 Female 6 Caucasian Married 153633 0 Private 0 1956 Female 2 Caucasian Married 82960 0 Private 3 1985 Male 0 Caucasian Married 62923 369 Medicare 0 1936 Female 4 Hispanic Divorced 88204 0 Private 0 1986 Female 2 Caucasian Married 234354 0 Private 2 1952 Female 2 Asian Married 141515 0 Private + Medicare 1 1936 Male 5 Caucasian Married 197818 0 Private 3 1976 Female 4 Caucasian Divorced 156778 0 Private 0 1949 Male 5 Caucasian Widowed 23188 0 Medicaid 1 1968 Male 4 Caucasian Married 69139 0 Medicare 0 1943 Female 2 Caucasian Divorced 193316 0 Medicare 0 1938 Female 8 Caucasian Married 24942 0 Private 0 1975 Female 3 Caucasian Married 118499 298 Private 0 1962 Male 1 Caucasian Married 29857 203 Private + Medicare 2 1937 Female 7 Caucasian Married 21204 208 Medicaid 0 1990 Female 1 Hispanic Married 9336 0 Private 0 1981 Female 1 Caucasian Married 9284 1156 Medicaid 0 1960 Female 2 Caucasian Separated 318548 0 Private + Medicare 1 1936 Female 9 Asian Married 184381 0 Private 2 1961 Male 4 Caucasian Separated 223712 0 Private 0 1949 Male 6 Other Married 33806 0 Medicaid 2 1984 Male 3 Caucasian Married 9407 0 Medicaid 0 1983 Female 1 Caucasian Widowed 115327 50 None 2 1958 Male 2 Caucasian Single 222526 0 Private 2 1992 Male 1 Caucasian Divorced 8150 110 Private 0 1988 Male 2 Caucasian Divorced 62604 0 Private 2 1951 Female 6 Caucasian Married 82867 65 Private 0 1947 Male 4 Hispanic Divorced 14968 0 Private 1 1977 Female 0 Caucasian Divorced 8624 0 Medicare 0 1942 Male 1 African American Divorced 46744 0 Private 2 1981 Female 1 Caucasian Divorced 59654 0 Private 0 1989 Male 1 Caucasian Married 108306 0 Private 0 1991 Female 1 Caucasian Married 270394 0 Private 3 1972 Female 2 Caucasian Divorced 14908 1979 Medicare 1 1935 Male 10 Caucasian Widowed 24317 0 Private 0 1969 Female 3 Hispanic Divorced 21196 494 Medicaid 1 1957 Female 2 Caucasian Married 7467 3267 Medicaid 0 1957 Female 5 Caucasian Divorced 23345 83 Medicaid 1 1952 Male 3 Caucasian Divorced 89019 0 Medicare 1 1939 Female 4 Caucasian Married 64826 0 Private 2 1948 Female 3 Caucasian Married 21924 0 Medicare 0 1946 Female 2 Hispanic Divorced 9079 0 Medicare 0 1937 Female 8 Caucasian Married 12261 0 Private 0 1958 Female 3 African American Divorced 9615 0 Private 1 1961 Male 4 Caucasian Married 29190 226 None 0 1955 Female 3 Caucasian Married 169726 0 Private 0 1971 Female 0 Caucasian Married 270447 0 Medicare 2 1937 Male 6 Asian Divorced 135355 396 Private 1 1967 Male 5 Hispanic Separated 271228 0 Private 0 1948 Female 3 Caucasian Married 171689 0 Private 0 1957 Male 1 Caucasian Single 116616 0 Private 0 1988 Male 1 Caucasian Divorced 124408 212 Medicare 2 1940 Male 5 Caucasian Married 9133 211 Medicaid 0 1969 Male 3 Caucasian Single 26548 0 Private + Medicare 1 1933 Female 7 Hispanic Single 23550 0 Medicare 0 1932 Female 15 Other Separated 33551 348 Medicaid 0 1963 Female 0 African American Married 117216 34 Private 0 1969 Male 2 Caucasian Divorced 60861 211 Medicare 1 1946 Male 0 Asian Divorced 145429 0 Medicare 1 1941 Male 2 African American Divorced 13943 1972 None 0 1985 Male 0 Asian Separated 108343 45 None 0 1976 Male 1 Caucasian Divorced 34417 406 Private 0 1972 Female 2 African American Married 24746 0 Medicaid 3 1976 Female 3 Hispanic Widowed 171924 218 Private 0 1965 Male 1 Asian Divorced 13647 0 Private + Medicare 0 1938 Female 7 Caucasian Married 16999 310 Medicaid 2 1968 Male 4 Caucasian Married 58873 0 Private 0 1977 Male 1 Caucasian Married 251395 2029 Private 1 1991 Male 1 Caucasian Married 224407 0 Private 0 1965 Male 1 Caucasian Divorced 72728 392 Private + Medicare 0 1943 Female 1 Caucasian Divorced 197285 148 Private 1 1977 Male 3 Caucasian Separated 9768 465 Private 0 1983 Male 1 Caucasian Married 163419 396 None 1 1967 Female 1 Hispanic Married 58156 0 Private + Medicare 0 1932 Female 10 Caucasian Separated 28724 0 Medicare 2 1933 Female 5 Caucasian Divorced 7162 0 Medicare 0 1945 Female 3 Caucasian Divorced 11658 0 Private + Medicare 3 1944 Female 4 Hispanic Married 17714 351 Private 0 1981 Male 3 African American Single 13578 0 Medicaid 2 1978 Male 3 Hispanic Married 8006 2838 Private + Medicare 2 1934 Male 8 Caucasian Divorced 73081 56 Private 0 1978 Female 0 Caucasian Divorced 160973 0 None 1 1961 Female 3 Hispanic Divorced 27708 0 Private 0 1967 Male 1 Caucasian Divorced 211054 0 Private 3 1973 Male 2 Caucasian Married 142758 0 Private 0 1953 Male 2 Caucasian Single 257051 0 Medicare 0 1941 Male 5 Caucasian Married 9200 114 Medicaid 0 1990 Female 2 Caucasian Widowed 28794 0 Private 2 1971 Female 2 Caucasian Married 19421 0 Medicaid 0 1962 Female 2 Caucasian Separated 14800 410 Medicaid 2 1978 Male 3 Caucasian Widowed 108418 0 Private 0 1974 Male 2 Hispanic Married 315739 62 Private 2 1987 Male 1 Hispanic Married 9529 0 Medicaid 2 1958 Male 3 Caucasian Divorced 21395 0 Private 0 1988 Male 2 Caucasian Married 8533 0 Private 0 1983 Female 2 Caucasian Divorced 21779 0 Private 3 1992 Female 0 Hispanic Separated 210197 39 Private 0 1966 Female 4 African American Married 107420 459 Private 1 1992 Male 2 Caucasian Married 103350 237 Private 0 1948 Male 2 Caucasian Divorced 6040 406 Private 3 1961 Male 5 African American Married 160122 1990 Private 1 1947 Male 3 Caucasian Separated 308438 0 Private 1 1988 Female 0 Asian Married 9161 382 None 3 1965 Male 3 African American Separated 29204 0 None 2 1952 Female 5 African American Widowed 94150 221 Medicare 1 1935 Male 9 Caucasian Married 88998 0 Medicare 0 1941 Female 7 Caucasian Divorced 9739 64 Medicare 3 1946 Male 5 Caucasian Married 8599 989 Private 1 1950 Female 0 Caucasian Married 59408 0 Private 0 1953 Female 5 Hispanic Divorced 147091 178 Private + Medicare 0 1939 Female 8 African American Widowed 16813 0 Private 0 1976 Female 3 Caucasian Divorced 36111 32 Medicaid 0 1963 Female 5 Caucasian Married 157486 0 Private 2 1947 Male 6 Caucasian Married 133374 0 Private 0 1975 Male 0 Caucasian Married 14154 0 Private 0 1972 Female 1 Asian Married 11320 0 None 3 1987 Male 0 Hispanic Divorced 53263 0 Private 0 1972 Female 3 Caucasian Separated 29362 410 Private 0 1948 Male 1 African American Divorced 14268 0 Medicare 0 1939 Male 9 Caucasian Married 15510 0 Medicaid 3 1983 Male 2 Caucasian Single 325956 276 Private 0 1958 Male 5 Caucasian Married 17081 4297 Medicaid 3 1970 Female 3 Hispanic Divorced 74181 124 Medicare 0 1946 Male 1 Caucasian Widowed 64589 0 Private 0 1979 Male 3 African American Married 17759 0 Medicare 0 1934 Female 5 African American Separated 155953 0 Private + Medicare 0 1941 Female 8 African American Divorced 70088 0 Private 0 1986 Female 2 Caucasian Married 74119 151 Private 0 1956 Male 3 Hispanic Married 47264 0 Medicare 3 1933 Female 7 Caucasian Married 25073 87 Private 0 1980 Male 2 Hispanic Married 17629 3143 Medicaid 2 1963 Male 0 Caucasian Divorced 137786 0 Private 0 1980 Male 1 Caucasian Divorced 56727 0 Private 4 1969 Female 1 Hispanic Married 9105 0 Private 3 1974 Female 2 Hispanic Divorced 19696 0 Medicaid 0 1948 Male 3 Hispanic Divorced 127381 417 Private 3 1986 Male 3 Caucasian Married 53952 57 Private 0 1990 Male 0 Other Single 79471 0 Private 0 1955 Female 5 Caucasian Widowed 18545 208 Medicaid 1 1984 Male 0 Caucasian Married 9099 200 Private 0 1986 Male 0 Caucasian Married 70642 0 Private 1 1960 Female 5 Other Single 156643 0 Private 0 1951 Female 6 Caucasian Married 146177 441 Private 0 1986 Male 2 Caucasian Divorced 35997 0 Medicare 0 1944 Male 4 Caucasian Married 26425 129 None 3 1984 Female 3 Caucasian Divorced 196699 0 Private 4 1975 Female 0 Asian Divorced 17354 0 Medicare 0 1932 Female 6 African American Married 157903 0 Private 0 1968 Male 0 Hispanic Divorced 25999 380 Medicaid 0 1961 Male 5 Caucasian Married 174417 147 Private 2 1979 Male 1 Caucasian Married 245036 499 Private 3 1980 Male 1 Caucasian Married 200537 0 Medicare 1 1940 Female 9 African American Married 9006 272 Medicare 0 1946 Male 2 Hispanic Married 36765 0 Private 2 1991 Male 0 Hispanic Separated 17197 0 Medicare 0 1946 Male 7 Hispanic Divorced 7754 0 Medicaid 0 1978 Male 1 Caucasian Married 9500 2436 Private 2 1976 Female 0 Caucasian Married 23525 0 Medicare 1 1944 Female 1 Caucasian Married 160968 300 Private + Medicare 2 1945 Male 5 Asian Married 14411 0 Medicare 2 1946 Male 1 African American Divorced 111595 0 Private + Medicare 2 1937 Female 2 Hispanic Separated 27782 0 Medicaid 0 1988 Female 2 Hispanic Divorced 21268 0 Private + Medicare 0 1935 Male 7 African American Divorced 109494 359 None 1 1956 Male 1 Other Divorced 141705 0 Private 3 1948 Male 3 Caucasian Married 11531 271 Private + Medicare 0 1933 Male 5 African American Married 76856 0 Medicare 0 1941 Female 8 Caucasian Married 44130 0 Private + Medicare 0 1945 Female 8 Caucasian Married 8580 4920 Private 0 1963 Female 2 Asian Divorced 34730 0 Medicaid 1 1949 Female 0 Caucasian Married 17602 1208 Medicaid 2 1988 Female 1 Caucasian Divorced 14959 310 Private 0 1976 Female 1 Caucasian Married 103263 0 Private 0 1953 Female 4 Caucasian Single 72044 483 Medicare 2 1941 Male 6 Caucasian Divorced 12707 0 Medicare 1 1939 Female 2 Caucasian Separated 201379 0 Private 0 1954 Female 2 Caucasian Divorced 8080 0 Medicare 0 1942 Male 4 Caucasian Married 85738 0 Private 0 1971 Male 2 Caucasian Married 127122 0 Private 0 1949 Female 5 Hispanic Married 13354 271 Medicaid 0 1972 Male 3 African American Married 23604 0 Medicare 0 1933 Male 3 Caucasian Married 174675 309 Private 1 1984 Male 1 Other Married 25892 0 Medicaid 1 1982 Male 1 Asian Divorced 215745 0 Private 1 1975 Male 1 Caucasian Married 22889 214 None 0 1963 Female 4 Asian Single 25524 242 Medicare 0 1946 Female 7 Hispanic Divorced 175753 380 Private 0 1958 Male 1 Hispanic Married 68263 0 Private 2 1976 Female 2 Hispanic Married 113781 0 None 0 1967 Female 3 African American Divorced 25475 6281 Medicaid 0 1982 Male 2 Hispanic Divorced 23074 0 Medicare 0 1938 Male 3 Caucasian Married 84171 0 Private 0 1984 Female 1 Caucasian Married 10956 4290 Medicaid 0 1952 Female 5 Caucasian Married 8812 0 None 0 1987 Male 0 Caucasian Married 10829 632 Private 0 1989 Female 1 Hispanic Divorced 162843 63 Private 0 1984 Female 3 Caucasian Widowed 197433 0 Private 3 1979 Female 2 Caucasian Married 29125 0 Private 0 1947 Female 1 Caucasian Single 227725 0 Private 1 1988 Male 1 Caucasian Divorced 235255 0 Private 0 1956 Female 0 Asian Widowed 64911 0 Private 4 1977 Male 3 African American Married 124668 0 Private 0 1951 Male 2 Caucasian Married 12905 0 None 3 1978 Male 1 Caucasian Married 23505 426 Medicaid 1 1990 Male 0 Hispanic Married 50619 274 Private 4 1971 Male 1 Caucasian Divorced 140809 0 Private 0 1992 Male 2 Asian Divorced 36257 0 Medicaid 0 1979 Male 2 Caucasian Married 69519 0 Medicare 0 1945 Male 7 Caucasian Married 9344 67 Medicaid 0 1948 Female 2 African American Married 9574 5555 Medicaid 1 1952 Male 4 Asian Married 27866 0 Medicaid 3 1980 Female 3 Caucasian Divorced 9783 149 Private 0 1983 Male 3 Caucasian Married 152341 424 Private 3 1987 Female 0 Asian Married 9645 0 Medicaid 1 1972 Male 3 Caucasian Married 185845 137 Private 0 1956 Female 3 Caucasian Married 154341 385 Private 1 1971 Male 2 Other Widowed 7863 0 Medicaid 2 1979 Female 1 Caucasian Divorced 27380 5113 Medicaid 1 1976 Male 1 Caucasian Single 98117 0 Private 0 1963 Female 5 Other Married 131528 0 None 2 1967 Female 0 Other Divorced 36521 0 Private + Medicare 0 1941 Male 10 Caucasian Married 28861 0 Medicare 3 1945 Male 1 Caucasian Married 9041 2238 Private 0 1956 Female 1 Caucasian Married 20117 3075 Private 3 1976 Male 4 Caucasian Divorced 55650 0 Private 3 1987 Female 1 Asian Divorced 36305 0 Private 1 1952 Male 2 Caucasian Divorced 202196 263 Medicare 0 1937 Male 3 Caucasian Married 133230 0 Private 3 1968 Male 1 Caucasian Married 137532 0 Private 3 1982 Female 1 Caucasian Married 128955 0 Private 0 1972 Male 1 Caucasian Divorced 95608 45 Private 2 1971 Male 1 Caucasian Divorced 95842 153 Private 3 1979 Female 2 Hispanic Widowed 97230 0 Private 0 1970 Male 1 Caucasian Divorced 11157 202 Medicare 0 1939 Male 4 Caucasian Widowed 8133 1464 Medicaid 4 1970 Male 2 Caucasian Married 21867 221 Medicare 2 1938 Female 12 Caucasian Married 215527 0 Private 0 1964 Male 2 Hispanic Divorced 27754 0 Medicaid 0 1962 Male 5 African American Married 164426 293 None 0 1947 Female 7 Hispanic Married 8860 10 Private + Medicare 0 1944 Male 4 Caucasian Married 130189 0 Private 3 1951 Female 1 Caucasian Married 7704 0 Private 0 1964 Female 3 Caucasian Separated 93475 0 Private 1 1967 Female 0 Caucasian Widowed 21942 0 Private + Medicare 1 1934 Male 11 Asian Married 240707 0 Private 0 1961 Male 4 Asian Married 7756 0 Medicare 0 1934 Female 7 African American Widowed 141575 0 Private 0 1990 Female 2 Graduate Critical Thinking Rubric Rubric ID: GradCT NOTE: This rubric is for program assessment, not grading. If you will be grading the assignment, use a separate rubric. This will keep your grade for each student as well as any comments you make to them private as we will only download results for program assessment rubrics specifically. Program assessment rubrics must be completed and submitted in Blackboard for each student. Assessment results will be aggregated by program, location, and delivery mode, so individual students or instructors are not identified. 3 Exceeds Expectations 2 Meets Expectations 1 Below Expectations Explanation of issues Issue/problem to be considered critically is stated clearly and described comprehensively, delivering all relevant information necessary for full understanding. Issue/problem to be considered critically is stated but description leaves some terms undefined, ambiguities unexplored, boundaries undetermined, and/or backgrounds unknown. Issue/problem to be considered critically is stated without clarification or description. Evidence Selecting and using information to investigate a point of view or conclusion Information is taken from source(s) with enough interpretation/ evaluation, to develop a comprehensive analysis or synthesis. Viewpoints of experts are questioned thoroughly. Information is taken from source(s) with some interpretation/ evaluation, but not enough to develop a coherent analysis or synthesis. Viewpoints of experts are taken as mostly fact, with little questioning. Information is taken from source(s) without any interpretation/ evaluation. Viewpoints of experts are taken as fact, without question. Influence of context and assumptions Thoroughly (systematically and methodically) analyzes own and others' assumptions and carefully evaluates the relevance of contexts when presenting a position. Questions some assumptions. Identifies several relevant contexts when presenting a position. May be more aware of others' assumptions than one's own (or vice versa). Shows an emerging awareness of present assumptions (sometimes labels assertions as assumptions). Begins to identify some contexts when presenting a position. Student's position (perspective, thesis/hypothesis) Specific position (perspective, thesis/ hypothesis) is imaginative, taking into account the complexities of an issue. Limits of position (perspective, thesis/ hypothesis) are acknowledged. Others' points of view are synthesized within position (perspective, thesis/ hypothesis). Specific position (perspective, thesis/ hypothesis) acknowledges different sides of an issue. Specific position (perspective, thesis/ hypothesis) is stated, but is simplistic and obvious. Conclusions and related outcomes (implications and consequences Conclusions and related outcomes (consequences and implications) are logical and reflect student’s informed evaluation and ability to place evidence and perspectives discussed in priority order. Conclusion is logically tied to information (because information is chosen to fit the desired conclusion); some related outcomes (consequences and implications) are identified clearly. Conclusion is inconsistently tied to some of the information discussed; related outcomes (consequences and implications) are oversimplified. Directions for program assessment: For student number ______ 1. Read the essay/paragraphs/answers. 2. Using the program assessment rubric in Blackboard, check the box with the description that best describes the student’s contribution in relation to expectations: exceeds=3; meets=2; below expectations=1. 3. A student’s total score will be the total of the values of the checked boxes. 4. A student earns a satisfactory score if the total value is 8 or higher. Exceeds Expectations = 12-15 points Meets Expectations = 8-11 points Below Expectations = 5-7 points QM 6640 ASSESSMENT Medical Debt INSTRUCTIONS Read the case presented below from Businessweek on medical debt. Following the case are a series of questions, which must be answered using the provided dataset. The two rubrics provided will provide guidance on how the instructor will assess your submission. Type your responses to the questions into a single Word document titled QM6640_Assessment_LastFirst.docx. Insert tables and graphs in your report as appropriate. Upload the completed Word file to the Assessment Submission Area in Blackboard by the due date. Carmen Lewis, PhD QM 6640 1 Why Hospitals Want Patients to Pay Upfront By John Tozzi September 25, 2014 Tozzi is a reporter for Bloomberg Businessweek in New York. URL: http://www.businessweek.com/articles/2014-09-25/why-hospitals-want-patients-to-pay-upfront Melody Rempe spends much of her day telling people who are about to go into the hospital how much they’ll have to pay. As a patient financial counselor at Nebraska Methodist Health System, she calls patients about a week before they go in for procedures with estimates of their bills and what portion insurance will cover. Although many are grateful, some cry or yell. “Sometimes you’re talking to them about the biggest thing in their life,” she says. Rempe says most calls end well when she walks patients through the hospital’s payment-plan options or other financial assistance. Hospitals have good reason to be concerned about their patients’ finances: Even people with insurance are increasingly responsible for a big portion of their medical bills. Among Americans who get health coverage at work, 41 percent have deductibles of at least $1,000 they must meet before insurance starts paying. That’s up from 10 percent in 2006, according to the Kaiser Family Foundation. Those with employer coverage are joined by 7 million new enrollees in Obamacare plans, which typically make patients share a large chunk of costs. The average deductible in the most popular “silver” tier of coverage is $2,267, according to an analysis by the Robert Wood Johnson Foundation. Raising deductibles helps employers and insurers limit premium hikes. It also shifts more of the risk onto individuals. That in turn boosts the chances that doctors and hospitals won’t get paid. If a patient has a $2,900 deductible, “it’s far more difficult to get that $2,900 from an individual patient than it is from the Medicare program or from Blue Cross Blue Shield,” says Richard Gundling, vice president of the Healthcare Financial Management Association, a trade group. A March report on hospitals from Moody’s (MCO), the credit-rating firm, was blunt: “Today’s high deductibles are tomorrow’s bad debt.” Hospitals’ total cost of uncompensated care reached $46 billion in 2012, equal to about 6 percent of their expenses, the American Hospital Association says. Large for-profit chains such as LifePoint Hospitals (LPNT), which operates more than 60 medical centers in 20 states, have felt the impact of rising deductibles. LifePoint’s bad debt related to copays and deductibles is running at $25 million per quarter this year, up from $15 million per quarter in 2013, Leif Murphy, the company’s chief financial officer, said on an earnings call in July. He blamed the increase in part on the growing prevalence of high- deductible plans. As the mechanics of insurance policies become more complicated, Americans are having a harder time understanding how their plan choices will affect their finances. Only 14 percent of insured adults correctly understand insurance jargon such as deductibles, coinsurance, copays, and out-of-pocket maximums, according to a 2013 study published in the Journal of Health Economics. Many Americans aren’t prepared for a medical emergency. Dr. Marilyn Peitso, a pediatrician in St. Cloud, Minn., says parents often can’t afford $300 to $400 for antibiotics to treat an ear infection. “For young working families, this can get to be a real financial burden, and it can make them less likely to http://www.businessweek.com/authors/1416-john-tozzi mailto:[email protected] http://www.businessweek.com/articles/2014-09-25/why-hospitals-want-patients-to-pay-upfront http://investing.businessweek.com/research/stocks/snapshot/snapshot.asp?ticker=LPNT 2 seek needed care,” she says. About 44 percent of households have less than three months of savings, according to an analysis by the Corporation for Enterprise Development, an antipoverty group. “Tell me what 28-year-old is going to be able to provide, especially in this economy, $6,000 of their own money?” says Jan Grigsby, chief financial officer at Springhill Medical Center in Mobile, Ala. Like Nebraska Methodist, Springhill reaches out to patients before scheduled procedures with an estimate of what they’ll owe, Grigsby says. For those who can’t pay immediately, the hospital works with lenders to arrange no-interest payment plans of as long as two years. Staff members also check whether patients are eligible for charity care from the hospital or if they qualify for Medicaid. Many hospitals try to get patients to pay upfront 30 percent to 50 percent of what they’ll owe and some offer discounts for paying early, says Yaro Voloshin of health-care consultant MedAssets (MDAS). One reason is that they want to avoid the damage to their reputations that accompanies aggressive debt collection practices. “Over the years there’s been some stigma about collecting from patients,” says Zac Stillerman, an executive with the Advisory Board, which sells software and consulting services to hospitals. “It’s a bit of a third rail.” Managers at Nebraska Methodist noticed payment problems getting worse about seven years ago, when a large employer in the Omaha area introduced a plan with a $5,000 deductible. “We would bill a procedure for a patient; the entire amount would be applied to the deductible,” says Bob Wagner, the hospital’s director for revenue cycle. “We actually got no money.” Now any patient scheduling a procedure expected to cost more than $500 out of pocket gets a call from Rempe or another of Nebraska Methodist’s five financial counselors. The hospital tries to get some payment in advance, but it doesn’t turn away those who can’t pay. Even simply identifying the indigent can help, says Gundling of the Healthcare Financial Management Association. “For both the patient and the facility,” he says, “trying to collect a debt that can’t be paid just wastes everybody’s time.” The bottom line: Some of the 17 million U.S. residents covered by high-deductible health plans are racking up medical debt. 3 With this case, you are provided a sample of patient data for your analyses. The provided link in Blackboard to the Excel workbook contains data on patients in a particular hospital. The dataset contains the following variables: Income: Patient's annual household income Past Due Amount: Amount of debt or money owed by the patient to the hospital. Insurance: Type (if any) of medical insurance. Years since last visit: Number of years since the patient's last appointment. Year born: The year in which the patient was born Gender: Patient's gender Hospitalizations: Lifetime hospitalizations of the patient Ethnicity: Patient's Race Marital Status: Patient's Marital Status Hospitals are concerned about patients’ ability to pay their medical bills. It is suggested that there is a relationship between type of medical insurance and medical debt. Write a concise report answering questions 1-6. Using past due amount as the dependent variable and all other variables as predictors (independent variables), run appropriate statistical analyses in Excel to mine the data. Label sections of your report to correspond to the questions. Insert tables and graphs from Excel in your report as appropriate. 1. Summarize the issue(s) and/or problems from the case in your own words. Support your answer(s). 2. Identify strategies for solving the problem. 3. Propose one or more solutions/hypotheses which address the problem(s). 4. Evaluate potential solutions to the problem(s). Analyze own and others’ assumptions. What inferences can you make from your dataset? Some suggestions are listed below; however, conduct additional analyses as deemed appropriate. a. Create a frequency table of insurance types. b. Construct a bar chart, a pie chart, and a Pareto diagram of insurance types. c. Which graphical method do you think is best to portray these data? d. Based on this data, what conclusions can you make about the insurance status of the patients? 5. Choose a solution. 6. Evaluate outcomes by reviewing the results relative to the problem(s) defined.